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Leading EdgeCell Volume 143 Number 1, October 1, 2010

IN THIS ISSUE

SELECT

5 Symmetry Breaking

BENCHMARKS

9 Lasker Lauds Leptin J.S. Flier and E. Maratos-Flier

13 Clinical Application ofTherapies Targeting VEGF

G.D. Yancopoulos

17 A Life-Long Quest to Understandand Treat Genetic Blood Disorders

D.G. Nathan

ESSAY

21 MicroRNAs and Cellular Phenotypy K.S. Kosik

PREVIEWS

27 How to Survive Aneuploidy B. Cetin and D.W. Cleveland

29 Auxin Paves the Wayfor Planar Morphogenesis

S. Pietra and M. Grebe

32 Cell Sorting during RegenerativeTissue Formation

R. Klein

SNAPSHOT

172 Nuclear Receptors III N.J. McKenna and B.W. O’Malley

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ArticlesCell Volume 143 Number 1, October 1, 2010

35 Myogenin and Class II HDACsControl Neurogenic Muscle Atrophyby Inducing E3 Ubiquitin Ligases

V. Moresi, A.H. Williams, E. Meadows, J.M. Flynn,M.J. Potthoff, J. McAnally, J.M. Shelton, J. Backs,W.H. Klein, J.A. Richardson, R. Bassel-Duby,and E.N. Olson

46 Long Noncoding RNAswith Enhancer-like Functionin Human Cells

U.A. Ørom, T. Derrien, M. Beringer, K. Gumireddy,A. Gardini, G. Bussotti, F. Lai, M. Zytnicki, C. Notredame,Q. Huang, R. Guigo, and R. Shiekhattar

59 Molecular Basis of RNA Polymerase IIITranscription Repression by Maf1

A. Vannini, R. Ringel, A.G. Kusser, O. Berninghausen,G.A. Kassavetis, and P. Cramer

71 Identification of Aneuploidy-Tolerating Mutations

E.M. Torres, N. Dephoure, A. Panneerselvam, C.M. Tucker,C.A. Whittaker, S.P. Gygi, M.J. Dunham, and A. Amon

84 Store-Independent Activation of Orai1by SPCA2 in Mammary Tumors

M. Feng, D.M. Grice, H.M. Faddy, N. Nguyen, S. Leitch,Y. Wang, S. Muend, P.A. Kenny, S. Sukumar,S.J. Roberts-Thomson, G.R. Monteith, and R. Rao

99 Cell Surface- and Rho GTPase-BasedAuxin Signaling Controls CellularInterdigitation in Arabidopsis

T. Xu, M. Wen, S. Nagawa, Y. Fu, J.-G. Chen, M.-J. Wu,C. Perrot-Rechenmann, J. Friml, A.M. Jones, and Z. Yang

111 ABP1 Mediates AuxinInhibition of Clathrin-DependentEndocytosis in Arabidopsis

S. Robert, J. Kleine-Vehn, E. Barbez, M. Sauer, T. Paciorek,P. Baster, S. Vanneste, J. Zhang, S. Simon, M. �Covanov�a,K. Hayashi, P. Dhonukshe, Z. Yang, S.Y. Bednarek,A.M. Jones, C. Luschnig, F. Aniento, E. Za�zımalov�a,and J. Friml

122 Activation-Induced Cytidine DeaminaseTargets DNA at Sites of RNA Polymerase IIStalling by Interaction with Spt5

R. Pavri, A. Gazumyan, M. Jankovic, M. Di Virgilio, I. Klein,C. Ansarah-Sobrinho, W. Resch, A. Yamane,B.R. San-Martin, V. Barreto, T.J. Nieland, D.E. Root,R. Casellas, and M.C. Nussenzweig

134 Intestinal Crypt Homeostasis Resultsfrom Neutral Competition betweenSymmetrically Dividing Lgr5 Stem Cells

H.J. Snippert, L.G. van der Flier, T. Sato, J.H. van Es,M. van den Born, C. Kroon-Veenboer, N. Barker, A.M. Klein,J. van Rheenen, B.D. Simons, and H. Clevers

145 EphB Signaling Directs PeripheralNerve Regeneration throughSox2-Dependent Schwann Cell Sorting

S. Parrinello, I. Napoli, S. Ribeiro, P.W. Digby, M. Fedorova,D.B. Parkinson, R.D.S. Doddrell, M. Nakayama,R.H. Adams, and A.C. Lloyd

(continued)

years of leadership in human genetics research,

education and service.

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156 Comparative Epigenomic Analysisof Murine and Human Adipogenesis

T.S. Mikkelsen, Z. Xu, X. Zhang, L. Wang, J.M. Gimble,E.S. Lander, and E.D. Rosen

ERRATUM

170 The In Vivo Patternof Binding of RAG1 and RAG2to Antigen Receptor Loci

Y. Ji, W. Resch, E. Corbett, A. Yamane, R. Casellas,and D.G. Schatz

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Leading Edge

In This Issue

Stress Factor Chokes Off TranscriptionPAGE 59

RNA polymerase (Pol) III transcribes short RNAs essential for cell growth andstability. Under stress conditions, the conserved protein Maf1 enters thenucleus and represses Pol III. Vannini et al. now report that Maf1 binds theclamp domain of Pol III and rearranges a protein subcomplex at the rim ofthe active center cleft, impairing the formation of a closed, active promotercomplex. These findings explain how Maf1 can globally repress transcriptionat Pol III loci, ensuring cell survival during stress.

Myogenin Is Muscle’s FrenemyPAGE 35

Maintenance of skeletal muscle structure and function requires innervation by motor neurons, and denervationcauses muscle atrophy. Here, Moresi et al. demonstrate a role for myogenin, an essential regulator of muscledevelopment, in promoting neurogenic muscle atrophy. Following denervation, myogenin is upregulated anddirectly activates the expression of factors that promote muscle atrophy. Thus, myogenin is both a regulatorof muscle development and an inducer of neurogenic atrophy and represents a potential therapeutic targetfor muscle-wasting disorders.

Channeling Ca2+ in Breast CancerPAGE 84

Dysregulation of Ca2+ homeostasis is associated with numerous diseases,including cancer. In this issue, Feng et al. identify an unconventional functionfor SPCA2, an isoform of the Secretory Pathway Ca2+-ATPase upregulated inbreast cancer cells. SPCA2 interacts directly with Orai1, a Ca2+ channel, to elicitconstitutive Ca2+ influx that is necessary for tumorigenesis. Surprisingly, thisinteraction is independent of SPCA2’s pump activity and of ER calcium stores.These findings reveal a new mechanism of Ca2+ signaling and potentialdruggable targets for breast cancer treatment.

ncRNAs Activate!PAGE 46

The number of long noncoding RNAs (ncRNAs) is on the rise, but for most, a cellular function remains elusive.In this issue, Ørom et al. identify a large family of new ncRNAs and find that some of them behave as classicenhancer elements, activating expression of neighboring protein-coding genes. These findings suggest an unan-ticipated mode of regulation of the mammalian genome impacting process from differentiation and developmentto oncogenesis.

Outgrowing AneuploidyPAGE 71

Aneuploidy causes a proliferative disadvantage in all normal cells analyzed to date, yet this condition isassociated with cancer, a disease characterized by unabated proliferative potential. To probe how cancercells tolerate the adverse effects of aneuploidy, Torres et al. isolated aneuploid yeast strains with improvedproliferation. Molecular characterization of these strains reveals aneuploidy-tolerating mutations that improvethe fitness of multiple different aneuploidies and highlight the importance of ubiquitin-mediated proteasomaldegradation in suppressing the adverse effects of aneuploidy.

Cell 143, October 1, 2010 ª2010 Elsevier Inc. 1

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Symmetric Stem Cell Divisions Carry the CryptPAGE 134

Each intestinal crypt has 14 stem cells at its base. Using a multicolor randomlyinducible reporter system to map the individual fates of each crypt stem cell,Snippert et al. now demonstrate that most of the stem cell divisions aresymmetric. The stem cells compete for residency in the crypt, leading thecrypt to drift towards monoclonality over time. The results indicate that, aftersymmetric division, each daughter cell stochastically adopts either the stemor progenitor cell fate. This model contrasts with a hierarchical view of stemcell divisions in which each division yields one stem cell and one transit-amplifying cell.

Auxin Signaling, No Transcription RequiredPAGE 99

Auxin signaling in plants is vital for initiating specific transcriptional responses. Now, two studies identify nontran-scriptional roles for auxin signaling through the AUXIN-BINDING PROTEIN 1 (ABP1) receptor. Xu et al. look atdevelopment of puzzle piece-shaped pavement cells and find that auxin activates two Rho GTPases, whichpromote the formation of complementary lobes and indentations in adjacent cells. The response to auxin isfast and requires ABP1. Auxin is exported by PIN1, and Robert et al. show how auxin itself modulates the cellsurface expression of PIN1. They report that ABP1 promotes clathrin-mediated endocytosis of PIN1 and othercargos. Auxin binding to ABP1 blocks this activity and dampens endocytosis, leading to more PIN1 at the surfaceand elevated levels of auxin export.

Schwann Cells Soothe Frayed NervesPAGE 145

Peripheral nerves have remarkable regenerative capabilities. Following a cut,severed nerve ends refind each other, creating a bridge of new tissue.Regrowing axons must then traverse this bridge on the journey back to theirtargets. Parrinello et al. show that fibroblasts that accumulate at the site ofinjury modulate the behavior of Schwann cells via ephrin-B signaling,promoting their outgrowth from the nerve stumps as multicellular cords. TheSchwann cells provide a platform to guide axons across the wound.

AID Carjacks Stalled PolymerasePAGE 122

Activation-induced cytidine deaminase (AID) initiates antibody gene diversification by creating U:G mismatches.However, AID is not specific for antibody genes, and off-target lesions can initiate chromosomal translocations.How AID finds its targets is unknown. Pavri et al now show that Spt5, a factor associated with stalled RNApolymerase II (Pol II), is required for class switch recombination. Spt5 interacts with AID and stalled Pol II andfacilitates AID recruitment to both Ig and non-Ig sequences. Thus, AID is targeted to sites of Pol II stalling viaSpt5.

Chromatin Cairns on the Path to AdipogenesisPAGE 156

The gene regulatory networks that govern adipogenesis are poorly understood. Here, Mikkelsen et al. mapseveral modified histones and transcription factors across the genome in differentiating mouse and humanadipocytes. The data provide high-resolution views of chromatin remodeling during cellular differentiation andallow identification of thousands of putative preadipocyte- and adipocyte-specific cis-regulatory elementsbased on dynamic chromatin signatures. The authors also utilize the close relationship between open chromatinmarks and transcription factor motifs to identify and validate PLZF and SRF as regulators of adipogenesis.


Leading Edge

Select: Symmetry Breaking

Symmetry lies at the core of bilaterian development. Although mostly maintained, in some circumstances it is brokenpurposefully to create asymmetric structures, such as the heart. Recent discoveries reveal previously unappreciatedstrategies for maintaining or breaking symmetry in flies, nematodes, zebrafish, and mice and explore the functionalconsequences of disrupting these morphogenetic processes.

Apoptosis Throws Organs for a LoopDuring the pupal stage of Drosophila development, the genitalplate completes a 360� rotation around the body axis. A new reportby Suzanne et al. (2010) shows that this dramatic morphogeneticevent results from the movement of two concentric rings of cellsthat surround the genital plate. Each ring rotates by 180�, suchthat the inner ring completes the full 360�. Prior work has shownthat the loss of myosin ID (MyoID), a left-right patterning determi-nant, switches the direction of rotation of the genital plate fromclockwise to counterclockwise. The authors now show that whenMyoID is inactivated in only one of the two ring domains, the ringsrotate in opposite directions, with the net effect of canceling eachother out. Curiously, this places the genitalia in the same positionas where they normally end up in wild-type flies, and males with

‘‘nonrotating’’ genitalia appear none the worse for wear in terms of fertility. Of course this begs the question, why botherundertaking this developmental ‘‘loop-de-loop’’? The answer, according to the authors, lies in Drosophila’s evolutionaryhistory. At some point, one of its ancestors switched from having its genitalia at the 180� position back to 0� and madethis change through the duplication of the functional module that created the initial 180� rotation. The authors further explorethe trigger for the movements and provide evidence implicating localized apoptosis at the anterior regions of the ring bound-aries. Thus, they propose a model in which cell death releases the rings from neighboring tissue, thereby acting as a brakerelease mechanism. Future work may examine what initiates apoptosis in these cells to trigger the movement and mayalso spur others to assess the impact of apoptosis in initiating other types of morphogenetic movements.M. Suzanne et al. (2010). Curr. Biol. Published online September 9, 2010. 10.1016/j.cub.2010.08.056.

Putting an Unusual Twist on EmbryogenesisIn C. elegans, left-right asymmetry first arises early in embryogenesis at the transition betweenthe 4- and 6-cell stages. Pohl and Bao (2010) now show that this initial skew is reinforced andelaborated at the 8-cell stage by a unique morphogenetic phenomenon that the authors termchiral morphogenesis. During chiral morphogenesis, the midline, which divides the embryo intoleft and right sides, is uncoupled from the antero-posterior axis, such that the midline becomestilted to the right. This facilitates differential induction by Notch signaling to distinguish cell fateson the left versus the right side of the embryo. At the subcellular level, the authors observe left-right asymmetric protrusions and actomyosin contractility in otherwise equivalent sister cells(ABpl and ABpr). At the molecular level, they show that these structures are triggered by non-canonical Wnt signaling, well-known for its roles in planar cell polarity. The timing of thesemovements appears to be dictated by the division of the neighboring EMS cell. The authors show that the extension of theventral protrusion of the ABpl cell coincides with the EMS cell forming a contractile ring, and evidence of direct causality isobtained in experiments in which EMS cell division is delayed by irradiation. Thus, these finding unexpectedly link cell-cycleduration and symmetry breaking and point to signaling mechanisms, yet to be fully explored, that mediate communicationbetween the EMS cell and the ABpl cell.C. Pohl and Z. Bao (2010). Dev. Cell 19, 402–412.

Wnt Signals Do the Electric SlideIn vertebrates, some regions of the myocardium propagate electrical signals faster than others. In recent work, Panakovaet al. (2010) carefully document the origins of this electrical polarity in zebrafish development and uncover the patterningsignals that give rise to it. They visualize the timing of electrical activation across the myocardium by imaging of fluorescent

The genital plate of the Drosophila pupa goes full circle.

Shown at the initial (0�) and halfway (180�) points. Image cour-

tesy of S. Noselli.

Visualizing cellular dynamics

during chiral morphogenesis

in C. elegans embryos. Image

courtesy of Z. Bao.


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Stem Cells Scientific Facts and FictionChristine Mummery, Ian Wilmut, Anja Van de Stolpe and Bernard RoelenNovember 2010 | 400 pages | Paperback | $79.95 | €57.95 | £48.99 | ISBN: 9780123815354

Principles of Regenerative Medicine, 2nd EditionAnthony Atala and Robert LanzaNovember 2010 | 1400 pages | Hardback | $199.95 | €143.00 | £125.00 | ISBN: 9780123814227

Heart Development and Regeneration, 2-Volume SetNadia Rosenthal and Richard P. HarveyJune 2010 | 1072 pp. | Hardback | $199.95 | €143.00 | £125.00 | AU$296.00 | ISBN: 9780123813329

Essentials of Stem Cell Biology, 2nd EditionRobert Lanza, Roger Pedersen, John Gearhart, E. Donnall Thomas, Brigid Hogan, James Thomson, Douglas Melton and Sir Ian WilmutJune 2009 | 600 pp. | Hardback | $199.95 | €134.00 | £125.00 | AU$302.00 | ISBN: 9780123747297

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dyes sensitive to transmembrane potential and focus their effort on theobserved differences in the conduction velocities between the myocardialinner curvature (the future base of the ventricle) and the outer curvature(the future apex of the ventricle). These regional differences do not appearto arise from intrinsic variation in the prevalence of gap junctions, nor arethey are consequence of the physical effects of heart contraction. Instead,the authors present evidence implicating the morphogen Wnt11 in estab-lishing the gradient. Surprisingly, this effect is independent of Wnt11’s rolein planar cell polarity and instead is due to the regulation of a transmembraneconductance by L-type Ca2+ channels. The pharyngeal arches, which residenext to the heart, are the apparent source of endogenous Wnt11. Althoughadditional work is needed to connect the dots between Wnt11 and L-typeCa2+ channel regulation, this report is likely to motivate efforts to re-examinethe impact of Wnt11 signaling on electrically coupled tissues, such asepithelia.D. Panakova et al. (2010). Nature 466, 874–878.

Generating Rhythm in a Roundabout WayThe regulation of breathing arises from a population of neurons in the brain stem,known as the preBotzinger complex (preBotC), which establishes the rhythm thatdrives motor neurons controlling muscles for breathing. Bouvier et al. (2010) nowexamine how interneurons of the preBotC are specified during development. Giventhat breathing requires coordination of movement between the left and right sidesof the body, their efforts were motivated in part by prior evidence demonstratingthat neurons that control walking movements (that is, left-right alternation) in micederive from neural progenitors that express the homeobox protein Dbx1.The authorsexamine the consequences of Dbx1 deficiency and show that Dbx1 null mutants dieat birth due to a lack of breathing movement. This appears to result from the loss ofglutamatergic interneurons that generate the preBotC rhythm. Having identified thiscritical preBotC population, they further assess the consequences of disruptingneuronal communication across the midline by inactivating the axon guidancereceptor roundabout homolog 3 (Robo3) during development in Dbx1-derivedneurons. Interestingly, these mice exhibit preBotC rhythms that are not synchronizedbetween the left and right sides, which may account for their premature death asneonates. The authors make the interesting speculation that left-right asynchronyin diaphragm contractions could contribute to the abnormal posture of individualswith horizontal gaze palsy with progressive scoliosis (HGPPS), a syndrome that islinked to mutations in human ROBO3. Having identified this population of commissural interneurons, future work mayshed light on how the circuit dynamics synchronize the activities of the left and right preBotC regions.J. Bouvier et al. (2010). Nat. Neurosci. 13, 1066–1074.

Robert P. Kruger

In mice, Robo3-expressing commissural

interneurons (top) ensure left-right syn-

chronous activity (bottom) of the preBot-

zinger complex.

An isochronal map of a zebrafish embryonic heart

at 72 hr post-fertilization demonstrating the gra-

dient of conduction velocities that forms between

the outer curvature (OC) and the inner curvature

(IC). Image courtesy of C. MacRae.


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Leading Edge

BenchMarks

Lasker Lauds LeptinJeffrey S. Flier1,2,* and Eleftheria Maratos-Flier2,*1Office of the Dean, Harvard Medical School, Boston, MA 02215, USA2Division of Endocrinology, Beth Israel Deaconess Medical Center, Boston, MA 02215, UA*Correspondence: [email protected] (J.S.F.), [email protected] (E.M.-F.)

DOI 10.1016/j.cell.2010.09.021

This year, the Albert Lasker Basic Medical Research Award will be shared by Douglas Coleman andJeffrey Friedman for their discovery of leptin, a hormone that regulates appetite and body weight.By uncovering a critical physiologic system, their discovery markedly accelerated our capacity toapply molecular and genetic techniques to understand obesity.

The discovery of leptin was a landmark

event in modern physiology. Leptin is

a hormone derived from fat that informs

the brain about the status of energy stores

in peripheral tissues, and its discovery

closed a physiologic feedback loop that

was long hypothesized to control normal

energy homeostasis. Now, the Albert

Lasker Basic Medical Research Award

is recognizing the researchers who

produced this breakthrough, Douglas

Coleman at The Jackson Laboratory

and Jeffrey Friedman at The Rockefeller

University and the Howard Hughes

Medical Institute.

Although the contributions of the two

awardees differed in approach and

occurred three decades apart, their joint

recognition reflects the essential contri-

butions that each researcher made to

this field-changing discovery. Doug Cole-

man is recognized for demonstrating that

a ‘‘satiety factor’’ circulating in the blood

stream was absent in a mutant mouse

strain (ob/ob) that is severely obese

and for correctly predicting that the hypo-

thalamus is the target of this factor.

Stimulated by Coleman’s results, Jeffrey

Friedman took up the ambitious goal of

cloning the genes mutated in the mouse

strain at a time when such a feat was

extremely difficult. He found that the ob

gene encodes a protein hormone that

reverses obesity and metabolic abnor-

malities in the ob/ob mice. These discov-

eries revised our understanding of inte-

grative metabolism and set the stage for

explosive and still accelerating research

efforts in numerous fields.

Background HistorySometimes in science, a single break-

through changes a field in such a dramatic

way that newcomers to the field have diffi-

culty appreciating the ‘‘landscape’’ of the

research prior to the discovery. This is

surely the case for the field of energy

balance regulation before and after the

discovery of leptin. Even 30 years before

leptin’s discovery, a substantial body of

evidence suggested that energy intake

and expenditure were tightly regulated.

For example, when animals were forcibly

overfed (or starved) and then returned to

their original diets, they reliably and often

quite precisely returned to their initial

weights. Clearly, a physiologic homeo-

static system of some type was in play.

Furthermore, it was known that small

lesions in the hypothalamus caused either

obesity or leanness in humans and mice

by disrupting food intake and possibly

energy expenditure. For some scientists,

these results suggested that regions

within the hypothalamus might be master

regulators of energy balance, integrating

signals from peripheral organs that reflect

the energy status of the organism and

then engaging pathways to adjust nutrient

intake and energy expenditure to maintain

homeostasis.

Experimental support for this concept

emerged slowly. In 1959, the British phys-

iologist William Hervey published a

prescient study reporting the results

of surgically joining normal rats with

those given lesions in the ventromedial

Together, Douglas Coleman (left) and Jeffrey Friedman (right) discovered the hormone leptin,

which signals to the brain the state of energy stores in peripheral tissues.


hypothalamus (VMH), which were known

to cause obesity (Hervey, 1959). In these

‘‘parabiotic’’ experiments, Hervey con-

nected the rats through their subcuta-

neous tissues, permitting a low-rate

exchange of extracellular and blood-

borne elements from one animal to the

other. Although Hervey was not the first

researcher to employ this experimental

model, the surgical unions between these

particular rats generated a particularly

interesting result.

As expected, the rats with VMH lesions

became obese. Surprisingly, however, the

normal rats ingested far less food than

usual and lost substantial weight when

they were joined to the obese rats. Based

on these results, Hervey postulated that

the VMH normally responds to a satiety

signal that regulates feeding. Without

a functional VMH, the rats could not

respond to this signal; they became obese

and then overproduced the satiety signal,

which Hervey postulated was a peripheral

factor. Furthermore, Hervey surmised that

high levels of this signal crossed over into

the circulation of the normal rats, sup-

pressing their food intake and weight.

Remarkably, this hypothesis proved to

be correct. However, given the complexity

of the parabiotic model used in the study,

more pedestrian explanations might

easily have accounted for the decreased

food intake of the normal rats. Plus, identi-

fying a hypothesized hormone from an

unknown site was a daunting task, which

led many in the field to look elsewhere

for interesting experiments to pursue.

Despite much speculation and the

suggestive evidence from this study and

related approaches, no convincing proof

had emerged for the existenceofaspecific

physiologic system that controls energy

intake, energy expenditure, and body

weight when Douglas Coleman began to

tackle the problem over the next decade.

Coleman Connects the DotsDouglas Coleman obtained a doctorate in

biochemistry at the University of Wiscon-

sin and took his first position at The Jack-

son Laboratory in Bar Harbor, Maine in

1958, where he expected to remain for

only a couple of years to extend his under-

standing of genetics. Instead, he spent his

entire career at The Jackson Laboratory

until he retired in 1991. At the beginning,

his research focused on muscle disorders

in mice. However, his most notable ac-

complishments occurred while studying

mice with genetic syndromes of obesity

and diabetes, and at the time, The Jack-

son Laboratory was fertile soil for sowing

such studies.

In 1949, an autosomal recessive

syndrome of severe obesity appeared

spontaneously in a colony of mice at The

Jackson Laboratory. The mutation map-

ped to chromosome 6 and was desig-

nated obese (ob). In 1966, Coleman and

his associates identified a second obesity

syndrome with very similar symptoms,

but this mutation, designated diabetes

(db), mapped to chromosome 4 (Hummel

et al., 1966). Mice homozygous for both of

these mutations demonstrated dramatic

early onset obesity, insulin resistance

(with varying severity of diabetes), infer-

tility, and a variety of other symptoms,

including hyperphagia (i.e., overeating)

and decreased locomotor activity. Of

interest, when the mutations were bred

onto strains with different genetic back-

grounds, the mice displayed substantial

phenotypic variation in several features,

including the presence of overt diabetes.

The Coleman lab carried out extensive

mouse breeding and phenotyping experi-

ments in an effort to understand how

the genetic background regulates these

metabolic phenotypes, an important but

still largely unresolved question.

Coleman’s most important observa-

tions, however, came from a series of

parabiosis experiments with the mutant

animals. When the subcutaneous tissues

of ob/ob mice were surgically connected

to that of either wild-type or db/db

animals, the ob/ob mice decreased

feeding and lost weight, and this effect

reversed when the union was ended.

Control mice were unaffected by the

union with ob/ob mice (Coleman, 1973).

In contrast, when normal mice were

parabiosed to db/db mice, control mice

stopped eating and lost substantial

amounts of weight, but the db/db mice

were unaffected. These results led Cole-

man to conclude correctly that ob/ob

mice lacked a satiety factor in their blood

stream that regulates feeding and weight.

Although both the control and db/db mice

supplied this factor to the ob/ob mice, the

db/db mice did so more robustly. Cole-

man, therefore, speculated that db/db

mice overproduced the circulating factor

to which they could not themselves

respond but which could be parabiotically

transferred to other animals to regulate

feeding and weight.

Aware of the experiments by Hervey

(1959), Coleman surmised that the hypo-

thalamus probably contained the center

that responds to the circulating factor.

As with conclusions from Hervey’s

studies, Coleman’s hypothesis proved to

be right on target. However, in the

absence of an identified circulating factor,

many physiologists and obesity investiga-

tors continued to reserve judgment about

the ultimate validity of the Coleman

hypothesis, just as they did with Hervey’s

conclusions. Nevertheless, some daring

investigators pursued this hypothesis

and sought to biochemically purify and

identify a factor from fat or other tissues

that regulates food intake. This approach,

although rational, did not succeed. For

a quarter of a century after Coleman’s

insightful experiments, researchers iden-

tified neither a specific factor, its site of

origin, nor its site of action. In fact, many

leaders of the field questioned whether

the efforts to find such a factor were

scientifically justified.

Friedman Finds the GenesEnter Jeffrey Friedman, two decades after

Coleman’s work. Trained as a physician,

Friedman initially intended to become a

gastroenterologist. However, the emerg-

ing power of molecular genetics lured

him into a basic science laboratory to

study physiology and disease. Working

at The Rockefeller University, where he

obtained a PhD in the laboratory of James

Darnell Jr., Friedman became interested

in the genetics of body weight regulation

and decided to tackle the daunting task

of cloning the ob gene. Initially in collabo-

ration with other obesity researchers at

Rockefeller, including Rudolph Leibel,

Friedman methodically attacked this

goal and ultimately accomplished it. The

results led to insights that were nothing

short of breathtaking.

In a classic 1994 Nature paper, Fried-

man and colleagues described the ob

gene as a 4.5 kb transcript expressed

exclusively in adipose tissue and pre-

dicted to encode a secreted peptide

with 167 amino acids (Zhang et al.,

1994). Moreover, the transcript was dis-

rupted in both available ob alleles. Soon

10 Cell 143, October 1, 2010 ª2010 Elsevier Inc.

after this initial paper, the Friedman group

and two others laboratories demon-

strated that treating ob/ob mice with the

recombinant peptide dramatically cor-

rected the animal’s obesity and hyper-

phagia (Halaas et al., 1995). Thus, the

peptide was named ‘‘leptin’’ from the

Greek root leptos for ‘‘thin.’’

Leptin was considerably more potent

when injected directly into the CNS than

into the blood stream, suggesting that

the primary target of leptin is in the CNS,

as Coleman predicted. Furthermore, lep-

tin failed to act in db/db mice, which nicely

ruled out a nonspecific basis for the

weight loss and confirmed Coleman’s

hypothesis about the db/db mice lacking

the ability to detect the circulating satiety

factor. Thus, after almost a half a century

of searching, the biochemical cause of

obesity of the ob/ob mouse was finally

understood.

In work that soon followed, the Fried-

man laboratory and one other group found

that the db locus encodes a family of leptin

receptors that are alternatively spliced

and members of the cytokine receptor

family (Lee et al., 1996). The db allele

altered only a single splice variant that,

unlike the other variants, is expressed

strongly in the hypothalamus. This variant

was also the only leptin receptor predicted

to mediate signaling through the Jak/Stat

pathway. Not surprisingly, the Friedman

laboratory soon demonstrated that leptin

activates STAT3 in the hypothalamus

when it is systemically administered

(Vaisse et al., 1996). Furthermore, selec-

tively deleting this leptin receptor variant

from neurons recapitulates the major

features of the ob/ob syndrome.

Together, these findings demonstrated

the existence of a previously unknown

endocrine system through which the

status of energy stores in fat is communi-

cated by the hormone leptin to regulatory

centers in the brain. Absence of either the

ligand or the receptor caused severe and

similar obesity syndromes, revealing the

critical importance of this pathway and

its potential relevance to human disease.

Needless to say, this discovery trans-

formed the field of nutritional metabolism.

Leptin Research TodayOver the ensuing 15 years, researchers

have learned much more about the

biology and pathophysiology of leptin.

Indeed, a PubMed search for ‘‘leptin’’

reveals more than 18,000 citations. The

major developments in this intensive

area of research can be grouped into

three areas: the physiologic role of leptin;

how leptin’s action is limited in human

obesity induced by diet or the environ-

ment; and the neural and peripheral

circuits upon which leptin acts.

Initially, leptin was thought of as a mole-

cule produced by excess adipose tissue

to provide a negative feedback signal to

the brain to limit obesity by reducing

appetite and increasing energy expendi-

ture. However, new data and physiologic

thinking have substantially extended

this initial understanding. Clearly, leptin

reverses the syndrome of ob/ob mice,

and recombinant leptin has equally

dramatic effects on obese humans with

rare loss-of-function mutations in the lep-

tin gene (Farooqi et al., 1999). However,

disappointingly, both mice and humans

with more common forms of obesity typi-

cally have high levels of leptin, and more

importantly, their body weights respond

weakly or not at all to pharmacologic

supplementation of leptin (Heymsfield

et al., 1999). This suggests that ‘‘common

obesity’’ is a state of leptin resistance, as

opposed to leptin deficiency.

Of interest, obesity has long been

known to be a state of resistance to

insulin, the preeminent metabolic hor-

mone. Numerous studies have character-

ized the molecular mechanisms and

implications of insulin resistance associ-

ated with obesity. In obese patients,

raising already high levels of insulin even

further with exogenous doses typically

lowers blood glucose, revealing that

the resistance to insulin action on blood

glucose is relative, not absolute. In con-

trast, raising leptin levels even further in

the obese state has minimal effects on

body weight, suggesting that leptin resis-

tance to this important endpoint is almost

absolute. Consequently, the identification

of the molecular mechanisms underlying

leptin resistance is a central question to

address if we are to understand the path-

ophysiology of obesity as it occurs in

most people.

Studies in mice have identified two

likely mediators of leptin resistance. The

most well-characterized one, suppressor

of cytokine signaling 3 (SOCS3) (Bjørbaek

et al., 1998), is an intracellular inhibitor of

Jak/Stat signaling. Leptin acutely induces

expression of SOCS3 in target neurons,

and SOCS3 expression is also increased

in the hypothalamus of mice with diet-

induced obesity. Most decisively, disrupt-

ing the function of SOCS3 enhances

leptin signaling and limits obesity when

susceptible mice are placed on diets

that cause obesity (Howard et al., 2004).

A second candidate for an inhibitor of

leptin signaling is the tyrosine phospha-

tase PTP1b. As with SOCS3, disrupting

PTP1b protects against diet-induced

obesity (Zabolotny et al., 2002).

The most critical leptin signals are ex-

erted in the hypothalamus. The hypothal-

amus cannot be probed experimentally

in humans, and thus, our capacity to

assess the roles of SOCS3 and PTP1b in

human obesity is currently limited. Until

approaches are identified to counter

these inhibitory pathways, the existence

of leptin resistance in humans will limit

the therapeutic potential of leptin. Never-

theless, researchers are still actively

searching for obese individuals that

respond to leptin alone or in combination

with other therapies.

It seems likely that leptin will also have

therapeutic potential in disorders distinct

from obesity. Several states of ‘‘low lep-

tin’’ are associated neither with obesity

nor with mutations of the leptin gene.

For example, leanness and low body fat

can cause low levels of leptin in women

athletes, leading to amenorrhea and

anovulation, and leptin supplementation

may restore reproductive capacity in

these cases (Welt et al., 2004). In patients

with syndromes of ‘‘lipodystrophy,’’

multiple causes lead to a deficiency of

adipose tissue and thus leptin. Treatment

with leptin dramatically improves fatty

liver and insulin resistance in these

patients (Petersen et al., 2002).

Although a threshold of leptin action is

clearly required for preventing severe

obesity, this ‘‘anti-obesity’’ function para-

doxically may not be the singular or even

dominant physiologic role of leptin. Leptin

levels rise in obesity, consistent with

leptin’s function as a negative feedback

signal of energy stores. However, leptin

expression and circulating levels fall

quickly when normal mice and humans

are starved. May leptin be a signal for

adapting to starvation, as well as a signal

for resisting excessive weight gain?


In addition to increased hunger, starva-

tion induces a specific array of adaptive

endocrine and metabolic consequences,

including, most prominently, the suppres-

sion of reproductive capacity and de-

creased thyroid function. Importantly,

these changes are severely blunted

when leptin levels are kept constant by

exogenous supplementation during star-

vation of mice (Ahima et al., 1996). This

finding led to the hypothesis that falling

leptin is the dominant signal for initiating

a broad program of adaptation to starva-

tion. Indeed, the predicted impairments

of endocrine function during starvation

are also seen in ob/ob mice, such that

these mutant mice are actually experi-

encing the physiology of starvation

despite their severe obesity. We now

understand that these two faces of

leptin, mediating both the response to

starvation as levels fall and the response

to overfeeding as levels rise, represent

the full range of leptin biology. In 1998,

we hypothesized that leptin resistance

of weight regulatory pathways during

periods of energy excess provides an

evolutionary advantage; it limits the

capacity of leptin to keep an individual

excessively lean, which would cause

a more rapid demise during periods of

food deprivation.

The discovery of leptin has also

provided a powerful tool to explore the

central neural circuits that control energy

balance and related physiologies. A new

era in the neurobiology of energy balance

has been ushered in by the localization

of leptin receptors in specific regions of

the hypothalamus and the characteriza-

tion of the leptin’s ability to modulate

expression of neuropeptides involved

in regulation of appetite and body

weight. Researchers have demonstrated

that leptin reduces expression of several

neuropeptides that potently stimulate

feeding, such as Neuropeptide Y (NPY),

Agouti-related protein (AgRP), and

melanin concentrating hormone (MCH).

Conversely, leptin administration stimu-

lates expression of neuropeptides that

suppress feeding and weight. For

example, when neurons expressing pro-

opiomelanocortin (POMC) are stimulated

by leptin, they produce the neuropeptide

aMSH, which stimulates central melano-

cortin 4 receptors on downstream

neurons. The consequence of this stimu-

lation is to suppress food intake and

body weight. The critical relevance of

this melanocortin circuit is evident not

only from its identity as a target of leptin

activation, but also from the fact that

loss of function of the cognate melano-

cortin 4 receptor is the most common

genetic cause of human obesity, account-

ing for 3%–5% of severe obesity in

humans. Leptin also has direct and indi-

rect actions in brain regions apart from

hypothalamus, and it is clear that the full

integrated circuitry of leptin action in brain

will require much additional research.

ConclusionsWhat lessons can we learn from the

discovery of leptin? First, indirect argu-

ments or data supporting the existence

of a physiologic system can be heuristi-

cally important and can serve as

strong stimuli to drive groundbreaking

research. Nevertheless, no matter how

compelling, such arguments are often

unconvincing to the scientific community

until the specific molecules underlying

the physiology are identified. Second,

the discovery of a powerful regulator of

appetite, energy balance, and body

weight can still leave many outstanding

questions about the mechanisms under-

lying disorders of body weight in humans.

This can frustrate efforts to translate the

discovery into an effective therapy for

common forms of obesity. Finally, we

should take note of the fact that both

The Rockefeller University and Howard

Hughes Medical Institute believed in Jeff

Friedman’s research project and sup-

ported his efforts during many years of

hard work when tangible results were

few and far between. The ability to make

such long-term bets on people and their

projects is difficult for funding agencies

and institutions. We should celebrate

the cases in which such confidence and

support is given, especially when the

researchers are successful and prove

that the outcome was well worth the

risk, as was the case here.

ACKNOWLEDGMENTS

We would like to thank Bruce Spiegelman for

helpful comments on this article.

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Leading Edge

BenchMarks

Clinical Application ofTherapies Targeting VEGFGeorge D. Yancopoulos1,*1Regeneron Pharmaceuticals, Inc., 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA

*Correspondence: [email protected] 10.1016/j.cell.2010.09.028

This year’s Lasker DeBakey Clinical Research Award goes to Napoleone Ferrara for the discovery ofvascular endothelial growth factor (VEGF) as a major mediator of angiogenesis and for the develop-ment of an effective anti-VEGF therapy for wet macular degeneration, a leading cause of blindnessin the elderly.

Many of us have been lured into a career

in science by the hope that we would

someday make a scientific discovery

benefiting patients suffering from a pre-

viously incurable disease. Only as we

progress in our careers do we realize

how difficult and rare such a discovery

is, not to mention how disconnected the

actual scientific discovery often is from

the development of a new therapeutic

based on that discovery. Thus it is excep-

tionally rare that a single individual not

only makes the seminal discovery but

also helps to champion the development

of an effective new class of therapeutics.

Napoleone Ferrara, recipient of this year’s

Lasker DeBakey Clinical Reseach Award,

provides a rare such example.

Ferrara’s landmark scientific discovery

involved the isolation and cDNA cloning

of vascular endothelial growth factor

(VEGF) as a mitogen for vascular endo-

thelial cells. In large part due to Ferrara’s

subsequent efforts, we now know that

VEGF is the most important driver in the

body of normal as well as pathological

blood vessel growth. We also now realize

that VEGF not only induces vessel sprout-

ing and growth but can also regulate

vessel function in other ways, so as to

regulate vascular tone and blood pres-

sure, as well as vessel wall integrity and

vascular permeability. The Lasker com-

mittee is recognizing Ferrara for the dis-

covery of VEGF and for his specific

contribution to the eye field, where he

played a key role in the development of

an anti-VEGF therapy for age-related

macular degeneration (AMD), a leading

cause of blindness in the elderly. Although

not directly acknowledged in the current

award, Ferrara made arguably even

more exceptional contributions to the

parallel development of a similar therapy

for cancer.

Distinct Vascular Pathologies in EyeDiseases and in CancerThe vasculature plays a critical role in a

variety of eye diseases as well as in

cancer growth. In AMD, the most severe

vision loss occurs in patients who develop

the ‘‘wet form’’ of the disease character-

ized by choroidal neovascularization

(CNV). CNV refers to the growth of ab-

normal vessels originating from the cho-

roidal vascular network, directly under-

lying the retina. The abnormal vessels do

not usually invade the neural retina and

thus do not directly disrupt the retina

and its function. Instead, these abnormal

vessels become excessively leaky,

leading to retinal swelling and edema,

which in turn impairs vision. Optical

coherence tomography (OCT) can beauti-

fully image the living retina and reveal the

extent of swelling, including within the

macula and its foveal region, the tiny

central portion of the retina that is respon-

sible for the ‘‘central vision’’ critical to

important tasks such as reading and

driving. OCT images demonstrate that

patients with AMD can have marked

swelling in their central retina to over three

times normal thickness, resulting in

severe vision loss (Figure 1).

As Ferrara himself has thoroughly re-

viewed, the observation that tumor growth

is associated with increased vascularity

was initially made over 100 years ago,

and this observation was then followed

by a series of classic papers over the

following decades suggesting that tumors

might produce a diffusible factor that

stimulates angiogenesis, and that this

angiogenesis could be required for tumor

growth (Ferrara et al., 2004). The realiza-

tion that the apparently disparate vascular

pathologies in cancer and eye diseases

had a common trigger, and thus poten-

tially a related cure, awaited the discovery

and cloning of VEGF.

The Discovery and Cloningof VEGF and VPFIn 1989, Ferrara and Henzel, working at

Genentech, reported the purification and

amino-terminal sequence of an endothe-

lial-specific mitogen; they termed this

protein VEGF. Shortly thereafter, Ferrara

and colleagues described the molecular

cloning of the cDNA encoding VEGF

(Leung et al., 1989). While Ferrara and

his colleagues focused on the endothelial

growth properties of this new protein, a

parallel effort was unknowingly trying to

purify and clone the same protein, but

with an eye toward a totally different

biological function. In 1983, the Dvorak

laboratory identified a tumor-derived

factor, which they termed ‘‘vascular per-

meability factor’’ (VPF), that rapidly and

potently induced microvascular perme-

ability and fluid leak but for which they

had no molecular sequence (Senger

et al., 1983); I remember first hearing the

VPF story directly from Dvorak in the

mid-1980s at Cold Spring Harbor when

he attended the cloning course that I

was teaching, along with Fred Alt and Al

Bothwell, in which Dvorak was trying to

gain the expertise to clone this intriguing

factor. Presumably because our training


of Dvorak was not sufficient,

cloning of VPF was subse-

quently undertaken by the

Monsanto Company, which

published the amino-terminal

protein sequence as well as

the cDNA sequence in 1989

(Connolly et al., 1989; Keck,

1989).

Cloning of VEGF and VPF

revealed that they were the

same factor, and this conver-

gence showed that this new

factor had at least two fasci-

nating biologic activities—

not only could it induce

endothelial cell proliferation,

but it could cause vascular

leak and edema. Over the

next two decades, Ferrara

was the clear world leader in

further elucidating the biology

and pathological roles of this

new growth factor, helping

drive more widespread adop-

tion of VEGF as its name.

Ferrara early on realized the

value of using genetic inacti-

vation in mice, as well as en-

gineered biologics that could

work in multiple species,

as powerful tools. In 1996,

he demonstrated that early

mouse development de-

pended on precise dosing of VEGF by

showing that inactivation of even a single

VEGF allele resulted in embryonic lethality

due to severe vascular abnormalities.

He cleverly developed and elegantly ex-

ploited biologics-based blockers (such

as antibodies and soluble receptors) to

show that VEGF is required for overall

postnatal growth, and to define its roles

in structures such as growing bones and

the cycling ovary (Gerber et al., 1999a,

1999b). He also worked with collabora-

tors to show that VEGF acted via an endo-

thelial-specific receptor tyrosine kinase,

further confirming that evolution had

selected VEGF to act specifically on the

vascular endothelium by limiting its

receptor distribution to these cells.

VEGF and Tumor AngiogenesisAs noted above, it had long been appreci-

ated that neo-angiogenesis accompanies

and might be required for tumor growth.

Building on this background, Folkman

was the first to propose that therapies

designed to prevent such angiogenesis

might provide a useful new way to combat

cancer (Folkman, 1971). Folkman, how-

ever, also presented a rather complicated

view of tumor angiogenesis in which there

were myriad positive and negative regula-

tors, almost all of which (such as fibroblast

growth factors, transforming growth

factors, collagen fragments known as

endostatin, and plasminogen fragments

known as angiostatin) served roles out-

side of the vasculature as well; Folkman

suggested that tumor angiogenesis de-

pended on a complex integration of these

various positive and negative regulators

but did not propose a specific angiogenic

pathway nor a key trigger. In contrast, Fer-

rara showed that angiogenesis depended

on a clear cascade of factors, with VEGF

as the key initiator of most angiogenic

processes; Ferrara’s demonstration of

the primacy of VEGF also pushed the field

to realize that additional growth factors

had also evolved to specifi-

cally regulate the endothelium

by similarly utilizing endothe-

lial-specific receptors, such

as other members of the

VEGF family as well as the

more recently discovered

angiopoietin family (Yanco-

poulos et al., 2000).

Diligently pursuinghis focus

on VEGF, Ferrara developed

a mouse monoclonal antibody

to block VEGF, termed

A.4.6.1. It was initial experi-

ments using this antibody in

animal models that estab-

lished the primacy of VEGF in

tumor angiogenesis—Ferrara

showed that the antibody

could strongly inhibit tumor

growth by limiting tumor-

induced angiogenesis, not

only providing the first con-

vincing evidence that block-

ing tumor angiogenesis could

indeed prevent tumor growth

but simultaneously establish-

ing VEGF as the critical target

in the process (Kim et al.,

1993); importantly, the results

were reproduced in many

laboratories using an assort-

ment of VEGF-blocking re-

agents, including a clinical

candidate termed the VEGF Trap that

was developed in our laboratory.

Despite the results with VEGF blockade

reported by Ferrara and others, the phar-

maceutical industry did not immediately

jump on VEGF as an exciting cancer

target. In part, this had to do with prevail-

ing views in the field that there were

myriad potential targets to attack, and

that no target was more important than

others. Ferrara pressed on and next

humanized A.4.6.1 so that it could be

used in human trials. This humanized

antibody, given the generic name bevaci-

zumab and the brand name Avastin, first

entered clinical trials in 1997. Bevacizu-

mab ultimately achieved FDA approval in

2004 as a first-line treatment for meta-

static colorectal cancer in combination

with chemotherapy, based on its statisti-

cally and clinically meaningful benefits

on progression-free survival and overall

survival (Ferrara et al., 2004), and has

since garnered additional approvals. The

Figure 1. Anti-VEGF Therapy for Wet Age-Related Macular Degener-

ationSwelling of the central retina in a patient with age-related macular degenera-tion, as seen by optical coherence tomography, is reduced by treatmentwith anti-VEGF therapy. Prior to treatment this individual could read 35 letterson a specialized ‘‘ETDRS’’ eye chart. After treatment, this improved to 66.


bevacizumab story provides the definitive

demonstration that, in man, specific

antiangiogenesis blockade can provide

useful tumor control in multiple cancer

settings and is a testimonial to the efforts

and persistence of Ferrara, and it still

remains the standard for angiogenesis-

based therapeutics.

Kinase inhibitors that target the VEGF

receptor signaling pathway have since

been approved in cancer but do not

display as widespread activity while also

exhibiting broader toxicities. There appear

to be several reasons for this. Biologics-

based therapies such as bevacizumab

are naturally selected to have high affinity

and great specificity for their target and

also have the benefit of long-circulating

half-lives following injection, allowing for

rather complete and long-term blockade

with little if any off-target activity, which

has proven more difficult to achieve with

small-molecule kinase inhibitors. Prob-

ably due to the confusion that marked

the field a few years ago, few biologics-

based VEGF-targeted therapies are in

late-stage clinical trials in cancer; it re-

mains to be seen whether either of the

two biologicals in phase III trials (that is,

the VEGF Trap or Lilly’s ramucirumab

that targets the VEGF receptor) will pro-

vide similar or even greater benefit than

bevacizumab.

Anti-VEGF Therapy for EyeDiseasesFerrara played a key role in the develop-

ment of anti-VEGF therapies for eye

diseases, an endeavor that depended on

the contributions and influence of several

key collaborators as well as independent

groups. First of all, it should be pointed

out that most believe it is the perme-

ability-inducing activity of VEGF, first

described by Dvorak, that leads to the

retinal swelling and edema that cause

vision loss in wet AMD; other eye diseases

(such as proliferative diabetic retinopathy)

do exhibit the profound pathologic neo-

vascularization that we now know is also

driven by VEGF. It was in the latter type

of settings that the first definitive link

between VEGF and human eye disease

was made, simultaneously in 1994 by

Adamis and colleagues as well as Aiello

and King working in collaboration with

Ferrara (Adamis et al., 1994; Aiello et al.,

1994); both groups showed marked

increases in VEGF levels in the eyes of

patients suffering from intraocular neo-

vascularization. Shortly thereafter, both

groups worked in collaboration with Fer-

rara to show the benefit of blocking

VEGF in animal models of ocular neovas-

cularization; Ferrara provided the critically

required anti-VEGF blocking reagents for

these seminal studies.

The introduction of anti-VEGF therapies

into the clinic for eye diseases came from a

completely unexpected source, a small

company named NeXstar Pharmaceuti-

cals. This company was based on Larry

Gold’s ‘‘aptamer’’ technology, which was

being used to develop small synthetic

RNAs as a new class of drugs, and one

of their scientists, Nebojsa Janjic, was

developing an anti-VEGF aptamer with

cancer in mind; however, this aptamer

was ineffective when systemically admin-

istered in animal tumor models. Stimu-

lated by Adamis’ paper, Janjic reasoned

that his aptamer might work better if

directly injected into the eye. Toward this

end, Janjic met in 1996 with Adamis and

Guyer, who helped Janjic design a clinical

development plan for AMD. The aptamer,

termed Macugen, entered clinical trials in

1999. In the meantime, Adamis and Guyer

decided to try to start their own venture

and searched for the best available VEGF

inhibitor they could license for use in the

eye; it was at this point that I met the pair

as they became interested in our VEGF

Trap, and I became convinced by their

compelling rationale. Unfortunately, the

VEGF Trap was then entangled in a collab-

oration with the Proctor & Gamble Health

Care group, which was not interested in

either developing it or out-licensing it for

the eye, and thus Adamis and Guyer had

to look elsewhere; several years later, we

were independently able to progress the

VEGF Trap into the clinic for eye diseases.

By 2000, Adamis and Guyer had started

a company called Eyetech and, not having

other options, licensed Macugen and

continued its clinical development. In

phase III, Macugen produced rather

modest results, somewhat slowing the

progressive visual decline of AMD but

was nevertheless approved by the FDA

in 2004; Pfizer entered into the mix and

paid a huge premium to obtain rights to

this innovative therapeutic.

Although temporally behind the Macu-

gen story, and certainly spurred by the

competition, Ferrara and Genentech had

far superior VEGF blockers at their

disposal. Because of concerns that a

full-length antibody might not diffuse effi-

ciently into the retina when injected into

the vitreous, Ferrara and his colleagues

decided to engineer a humanized Fab

variant of A.4.6.1 for use in the eye that

was ultimately given the generic name

ranibizumab and the brand name Lucentis

(Ferrara et al., 2006). Ranibizumab had

other advantages over bevacizumab,

most notably a much higher affinity that

allowed it to be active at lower concentra-

tions, which Ferrara felt might be impor-

tant in terms of allowing for maintained

activity when the drug would drop to low

levels between monthly injections into

the eye. Genentech initially dosed

patients with ranibizumab in 2000 and

received FDA approval for the treatment

of wet AMD in 2006. The efficacy results

were quite stunning, especially when

compared to those obtained with the

poorer blocker, Macugen. Instead of

merely slowing vision loss, patients on

average gained vision and maintained

these gains if dosed on a monthly

schedule. Ranibizumab has since been

studied in other eye diseases and recently

gained approval for retinal vein occlusion.

Worldwide, Lucentis is now being used

to treat about a quarter million patients

a year. It perfectly fits the definition of

pharmaceutical blockbuster, in terms of

providing enormous clinical benefit to

many patients while simultaneously pro-

ducing enormous revenues. However,

there are emerging issues. In part frus-

trated by the cost of ranibizumab, clini-

cians explored off-label use of intravitreal

injection of bevacizumab for eye diseases

and claimed to see similar benefit (Rose-

nfeld, 2006). While there are certainly

concerns in terms of safety risks to

patients of such off-label use, the National

Eye Institute decided that the potential

pharmacoeconomic value of a lower-

priced alternative warranted running

clinical trials directly comparing ranibizu-

mab and bevacizumab in AMD; results

are expected in 2011. In addition, be-

cause patients and physicians are very

interested in decreasing the frequency of

eye injections, there have been many

attempts to study less frequent dosing

paradigms; despite these efforts, current

evidence supports the need for regular if


not monthly injection of ranibizumab to

optimize its benefit. Early studies with

other biologics blockers raise the possi-

bility that an even higher-affinity blocker,

perhaps at higher doses, could provide

further visual gains or allow for longer

interval dosing.

In many ways, Ferrara’s career repre-

sents the fulfillment of every drug discov-

erer’s dream, and the Lasker Award could

not be going to a more worthy recipient.

Ferrara not only made a seminal scientific

discovery, but then he and his colleagues

at Genentech built on this discovery to

spearhead the development of an entirely

new class of therapeutics with major

applications in two previously distinct

clinical arenas—vascular eye diseases

and cancer. Although Ferrara’s VEGF

antibody is now being used to treat

about 250,000 cancer patients a year,

the current award may have avoided

specifically acknowledging Ferrara’s

contribution to the cancer field because

of questions regarding the degree of clin-

ical benefit of bevacizumab in cancer.

Because bevacizumab represents an

entirely new way of attacking cancer, utili-

zation of this approach is still a work in

progress and may require new treatment

paradigms to optimize benefit. Traditional

treatment paradigms in which the anti-

cancer therapy is stopped after a short

treatment period when tumor killing is

thought to be completed, or after tumor

progression when the tumor is thought to

have become chemo-resistant, make little

sense for an antiangiogenesis approach:

the point is not to try to wipe out the tumor

initially but instead to provide ongoing

control by limiting host support; any

benefit would be expected to dissipate

as soon as such therapy is stopped. Ferra-

ra’s colleagues at Genentech have nicely

demonstrated this point in very recent

animal studies (Bagri et al., 2010), as well

as in recent clinical studies including one

in ovarian cancer using an innovative

‘‘maintenance design’’ carried out by the

Gynecological Oncology Group (GOG-

0218). Data from this study can be used

to make several important points. First,

this study shows that, at least in this

setting, bevacizumab does not primarily

work by allowing more efficient delivery

of chemotherapy (as had been proposed

by others), given that the gained benefit is

at least as good during the monotherapy

maintenance stage as during the prior

combination stage. Moreover, the study

convincingly shows that continued main-

tenance with anti-VEGF therapy is neces-

sary to prevent loss of clinical benefit.

In addition to maintenance approaches or

treatment-through-progression strate-

gies, the benefit of anti-VEGF therapy

may also be improved by combining with

agents targeting other angiogenic path-

ways; notably, several companies are in

trials combining anti-VEGF agents with

other antiangiogenic agents, such as those

targeting Angiopoietin-2. Chemothera-

peutics may also be developed that work

better on tumors made hypoxic via antian-

giogenic therapy. Although antiangiogene-

sis approaches in cancer are likely to be

further optimized as the community learns

better how to take advantage of this

approach, there is little doubt that anti-

VEGF treatments pioneered by Ferrara

and his colleagues will long remain the

foundation of such efforts. Thus, it can be

hoped that this well-deserved Lasker

award for the discovery of VEGF and the

development of a treatment for AMD is

a harbinger of prestigious accolades to

come that would also include specific

recognition of Ferrara’s contributions to

tumor biology and cancer treatment.

ACKNOWLEDGMENTS

G.D.Y. works at Regeneron, which is developing

anti-VEGF therapeutics.

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Leading Edge

BenchMarks

A Life-Long Quest to Understandand Treat Genetic Blood DisordersDavid G. Nathan1,*1Robert A Stranahan Distinguished Professor of Pediatrics and Professor of Medicine Harvard Medical School, President Emeritus

Dana-Farber Cancer Institute, Physician-in-Chief Emeritus Children’s Hospital, Boston, MA 02115, USA*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.015

This year’s Lasker-Koshland Special Achievement Award in Medical Science is conferred on SirDavid Weatherall for his 50 years of dedication to biomedical research, his groundbreaking discov-eries about genetic blood diseases, and his life-long passion for bringing improved medical care tothe developing world.

Sir David J. Weatherall is surely in the

center of the front row of the first-ranked

hematologists in the world. His impact

on medical genetics is second to none.

It is no surprise that he has received the

2010 Lasker-Koshland Special Achieve-

ment Award in Medical Science.

He adds this considerable honor

to a long list of distinguished career

awards, medals, and honorary

degrees from an international host of

universities, learned societies, and

most particularly, in the view of frus-

trated anglophiles who fruitlessly

yearn for royal recognition, the British

Crown itself.

Weatherall was born, raised, and

educated in Liverpool, that port city

where the Mersey River meets the

Irish Sea. At its peak, 40% of Eng-

land’s trade, huge numbers of immi-

grants, and many British subjects

migrating to the west and the east

passed through Liverpool. Weatherall

comes from a long line of ‘‘Liverpudli-

ans.’’ As a youngster, he became

infused by interests in science and

music and by that city’s first love,

football. His father was a laboratory

technician who went to college at

night and rose to become the chief

of the analytical chemistry laboratory

in a large Liverpool company as well

as a council member of the Royal

Society of Chemistry, but his first love

was music. He was the organist and choir

master of St. Nicholas Church on the Liv-

erpool waterfront. Weatherall’s mother

was also devoted to music and was

blessed with a beautiful contralto voice.

Hence the strains of Bach in the back-

ground of so many calls to the Weatherall

home in Oxford.

David Weatherall wanted to be a physi-

cian for as long as he can remember.

Whether Liverpool’s distinguished history

of tropical medicine, orthopedics, and

anesthesia was of any influence is

unknown. Whatever the reason, he

became the first in his family to go to

college and medical school: the results

of that decision proved fortunate. Even

more salutary was the national require-

ment for military service once he had

graduated with an MB (Bachelor of Medi-

cine) in 1956. Assigned to the British Army

as a medical officer, he was posted to

Singapore and then to Malaya, where in

1960 he reported his first cases of

the blood disease thalassemia, an

inherited hemoglobin disorder that

provides a measure of protection

against malaria. His interest in con-

genital disorders of the red cell,

particularly thalassemia, and their

interactions with malaria has never

left him. Fascinated by the role of

gene mutations in human disease

and immediately after he completed

his military commitment, he joined

the genetics-oriented Johns Hopkins

hematology training program. The

program at that time was led clinically

by the late C. Lockard Conley, and

Weatherall was inspired to pursue

genetics by the broad influence of

the late Victor McCusick.

From the very beginning of his

training, Weatherall demonstrated an

uncanny capacity to associate with

excellent scientists. He worked with

the late Ned Boyer on hemoglobin

genetics and collaborated with the

late Corrado Baglioni, then at the

Massachusetts Institute of Tech-

nology, on hemoglobin fingerprinting

to prove that the alpha chains of fetal

and adult hemoglobin are derived from

the same genetic loci (Weatherall and

Baglioni, 1962). Weatherall and Baglioni

then added further evidence that the

fetal-to-adult hemoglobin switch involves

Sir David J. WeatherallImage courtesy of L. Rose.


a change in the expression of non-alpha

chains during development.

During his training program at Johns

Hopkins, Weatherall plunged into the

details of thalassemia. The mysterious

disease had been greatly clarified by the

classic 1959 review article by Ingram

and Stretton, who correctly predicted

the occurrence of both alpha and beta

thalassemia and proposed that point

mutations in the beta globin gene might

be responsible for reduced synthesis of

beta globin. But there were many unan-

swered questions, and Weatherall was

determined to master the literature and

combine it with his own experience.

In 1965, as the sole author, he published

the first edition of The Thalassaemia

Syndromes, a uniquely valuable reference

text and critical appraisal of the field.

In the subsequent three editions, he was

joined first by his long-time colleague

John Clegg and subsequently by several

coeditors. The last edition of this monu-

mental contribution to hematology and

clinical genetics was published in 2001.

The four editions are heavily cited land-

marks in medical education and are

magnificent examples of interweaving of

literature with personal experience. They

reveal Weatherall’s understanding of

Darwin’s precept that disorders due to

gene mutations are heavily modified by

environmental circumstances. Finally,

they established Weatherall as one of

the founders of molecular medicine and

attracted many basic scientists into the

field. As a result, thalassemia led the

way toward the clinical applications of

molecular biology.

In addition to his scientific training,

Weatherall had two very important

encounters in Baltimore that were to be

extremely influential in his personal and

professional life. In 1960, he met Stella

Mayorga-Nestler in the Johns Hopkins

biochemistry department of the then

School of Hygiene, where she was work-

ing with Roger Herriott of DNA transfor-

mation fame. They were married in

Stella’s California home in 1962. A second

critically important set of encounters

included Mike Naughton, an excellent

protein chemist who was working in

the Howard Dintzis laboratory at Johns

Hopkins, and John Clegg, who had joined

Naughton after a brief (and stormy)

sojourn in Hans Neurath’s laboratory in

Seattle. Weatherall asked the two protein

chemists for help with a critical question

on which he had been working without

great success for months. Can the ex-

pected depression of beta globin chain

synthesis be reliably detected biosynthet-

ically in the reticulocytes of patients

with beta thalassemia? Clegg suggested

that a carboxymethylcellulose column

and a buffer containing 8 molar urea

and 6-mercaptoethanol might keep the

alpha, gamma, and beta globin chains

separated, prevent their aggregation,

permit their independent isolation, and,

hence, allow the determination of their

specific activities after incubation of

blood from thalassemia patients with a3H- or 14C-labeled amino acid (Weatherall

et al., 1965). Though the method was

malodorous and the fraction collector

permanently encrusted with crystals of

urea, it worked and clearly documented

that thalassemia is a disorder of unbal-

anced globin synthesis. Though almost

entirely replaced by modern DNA-based

methods, it remains a valuable if unwieldy

approach to the diagnosis of microcytic

anemias of unknown etiology. Clegg and

Weatherall have been colleagues ever

since.

Following his remarkably productive

sojourn in Baltimore, Weatherall returned

to the University of Liverpool where, with

his colleagues Clegg and Bill Wood,

a young trainee, he established a superb

clinical research program in hematology.

He rose to the rank of Professor of Hae-

matology and remained in Liverpool until

1974 when he moved, again with his two

close colleagues, to the University of

Oxford to be the Nuffield Professor and

then the Regius Professor of Medicine

and where he founded a research institute

now named the Weatherall Institute of

Molecular Medicine. The institute, the first

of its kind in Europe, opened in 1989 and

now has a staff of over 400. It is devoted

to biomedical research with a strong clin-

ical component. He retired from the

Oxford faculty in 2000 but remains

a distinguished participant in the institute,

now directed by his former student,

Douglas Higgs, a superb physician

scientist.

In addition to his many book chapters

and The Thalassaemia Syndromes,

Weatherall has been a coauthor of over

500 articles, most of which focus on thal-

assemia, malaria, and the hemoglobinop-

athies. In the process of studying thalas-

semia, he has traveled the world many

times over and has trained a substantial

cadre of investigators who direct impor-

tant clinical and clinical research pro-

grams particularly in Southeast Asia.

Much of his most original clinical research

effort has illuminated the alpha thalas-

semia syndromes, conditions particularly

prevalent in Southeast Asia.

In 1974, when reverse transcriptase

permitted the development of isotopically

labeled cDNA probes, both Weatherall’s

group (Ottolenghi et al., 1974) and a group

assembled by Y.W. Kan (Taylor et al.,

1974) demonstrated that complete alpha

globin gene deletion plays a critical role

in the development of severe (and usually

fatal) hydrops fetalis with Bart’s hemoglo-

binemia. The two papers were published

back to back in the same issue of Nature.

Later it was shown that unusual point

mutations may also inhibit or even arrest

alpha globin gene expression. In fact,

in 1975, Weatherall and Clegg demon-

strated that a termination codon mutation

in one of the four alpha genes can lead to

an abnormally elongated alpha chain and

an unstable messenger RNA producing

alpha + thalassemia, but deletion is the

predominant genetic lesion in alpha 0

thalassemia.

The development of reasonably spe-

cific beta globin cDNA probes that

permitted interpretable Southern blots

was somewhat more difficult than that of

alpha globin cDNA probes because of

overlap of beta globin DNA sequences

with delta and gamma sequences. In

1976, a group assembled by Weatherall

and headed by Sergio Ottolenghi demon-

strated that both delta-beta thalassemia

and the form of hereditary persistence of

fetal hemoglobin (HPFH) found in Africans

are due to extensive gene deletions (Otto-

lenghi et al., 1976). The subtle but impor-

tant differences between the two that

lead to considerably higher gamma gene

expression in HPFH were detected later

by several groups. Only 2 years later

such a probe was utilized by Orkin and

his coworkers to exclude homozygous

delta-beta thalassemia in a first trimester

Turkish fetus at risk (Orkin et al., 1978).

The alpha thalassemias continued

to capture Weatherall’s interest and

attention, and when Douglas Higgs joined


his laboratory as a budding physician

scientist, that interest blossomed into

major findings. By this time, Weatherall’s

research unit had become a reference

laboratory for clinicians throughout Great

Britain, southern Europe, and Southeast

Asia. Among these referrals were three

blood samples from male patients of

northern European origin, each of whom

had both mental retardation and hemo-

globin H disease, a form of alpha thalas-

semia usually due to three alpha gene

deletions. Analysis of the alpha genes of

the patients and their parents revealed

that one parent did indeed have two alpha

gene deletions (as expected), but the

other had an entirely normal complement

of four alpha genes. The patients had only

two deletions. Clearly another mutation

must have been present to suppress the

expression of the intact alpha genes,

and that mutation was likely to cause the

mental retardation as well. That was

a puzzle to be solved considerably later

in a brilliant series of studies by Higgs

and his colleagues. These studies dem-

onstrated an X-linked helicase deficiency

in the male patients and subtelomeric

deletions on chromosome 16 in others

that were shown to be responsible for

reduced alpha globin gene expression

and were presumably responsible for the

mental retardation (Gibbons and Higgs,

2000).

The remarkable copresentation of

mental retardation and alpha thalassemia

stimulated Weatherall and Higgs to focus

on the molecular anatomy of the alpha

globin gene cluster. They provided the

first RFLP map of the cluster and showed

that it offered an excellent site for linkage

analysis (Higgs et al., 1986). Along the

way, they defined the alpha globin gene

locus control region. The experience

launched Higgs’ fine career.

Weatherall is a broadly interested

hematologist. Though he made many

important contributions to the genetic

basis of thalassemia, he never lost an

opportunity to explore its treatment and

prevention. Immediately after Propper

and his coworkers suggested that daily

continuous subcutaneous administra-

tion of deferoxamine might prolong the

lives of multiply transfused thalassemia

patients with consequent iron overload

(Propper et al., 1977), Pippard and

Weatherall showed that a 5 day overnight

regimen would eliminate iron nearly as

well but be much more acceptable to

patients (Pippard et al., 1977). They were

correct, but the long gaps in which no

chelator could be present in the blood

diminished the efficacy of the treatment.

On the other hand, many more patients

could accept the regimen. It became the

standard of care until very recently when

deferisirox, an orally active chelator with

a long plasma half-life, became available.

Though Weatherall was rightly doubtful

that the globin chain synthesis system

that he had developed with Clegg and

Naughton (Weatherall et al., 1965) could

be reliably applied in prenatal diagnosis

using blood obtained from the placenta,

he changed his mind when he saw the

initial results of the efforts of Kan and Alter

and their colleagues (Kan et al., 1972). He

moved aggressively to establish a highly

successful prenatal detection system in

England that became a model of its kind

(Old et al., 1982) and then adopted more

practical molecular methods when they

became available.

As Weatherall began to pass the

torch of leadership of laboratory-based

research to Higgs, he directed his consid-

erable energy to his first interest, the

plight of poor patients in malaria zones

who endure high rates of both malarial

and nonmalarial infections and of in-

herited hemoglobinopathies. His publica-

tions in this important area are many, but

one of the most interesting is his finding

in Papua, New Guinea that a single alpha

gene deletion and particularly two such

deletions provide high protection from

both malarial and nonmalarial infections

(Allen et al., 1997). How a mild inherited

disorder of hemoglobin synthesis, limited

in its expression to the red cell and

manifested only as microcytosis (unusu-

ally small red blood cells), can influence

nonmalarial infection rates requires much

more understanding of host defense than

we have currently. In another fascinating

study, Weatherall and his colleagues

demonstrated that HbE/thalassemia, a

very common disorder in Southeast

Asia, provides very little protection from

malaria caused by the parasite Plasmo-

dium vivax. In fact vivax malaria infection

is one of the factors that increases the

severity of that particular thalassemia

syndrome (O’Donnell et al., 2009). Finally,

Weatherall’s efforts have provided stu-

dents of thalassemia with insights into

the clinical course of the disease as

patients age (O’Donnell et al., 2007). His

clinics in Sri Lanka are invaluable ‘‘class-

rooms’’ for young North American and

British students of the disease, particu-

larly for those who wish to find better

treatments, to learn quickly about its

manifestations and for those who intend

to contribute to the care of patients

desperately in need. Even more important

is Weatherall’s creation of an Asian Thal-

assaemia Network in which experts in

India and Thailand give technical assis-

tance to their colleagues in less devel-

oped countries such as Bangladesh and

Cambodia.

Meanwhile, Weatherall continues to

travel to major sites of the thalassemia

syndromes, urge world health authorities

and private foundations to pay attention

to the inherited hemoglobinopathies, tell

anyone who will listen about the impend-

ing world impact of the disorders, and

try to do his best to relieve the suffering

that these common inherited diseases

bring to those who can least afford to

deal with them. He does all this with

gem-like intelligence and indefatigable

determination, both mixed with mar-

velous humor and deep interest in what

his colleagues are doing. Indeed, life in

academic medicine is really all about

working with great colleagues. I have

been blessed with many, none more

enjoyable or admirable than Sir David

J. Weatherall.

REFERENCES

Allen, S.J., O’Donnell, A., Alexander, N.D., Alpers,

M.P., Peto, T.E., Clegg, J.B., and Weatherall, D.J.

(1997). Proc. Natl. Acad. Sci. USA 94, 14736–

14741.

Gibbons, R.J., and Higgs, D.R. (2000). Am. J. Med.

Genet. 97, 204–212.

Higgs, D.R., Wainscoat, J.S., Flint, J., Hill, A.V.,

Thein, S.L., Nicholls, R.D., Teal, H., Ayyub, H.,

Peto, T.E., Falusi, A.G., et al. (1986). Proc. Natl.

Acad. Sci. USA 83, 5165–5169.

Kan, Y.W., Dozy, A.M., Alter, B.P., Frigoletto, F.D.,

and Nathan, D.G. (1972). N. Engl. J. Med. 287, 1–5.

O’Donnell, A., Premawardhena, A., Arambepola,

M., Allen, S.J., Peto, T.E., Fisher, C.A., Rees,

D.C., Olivieri, N.F., and Weatherall, D.J. (2007).

Proc. Natl. Acad. Sci. USA 104, 9440–9444.

O’Donnell, A., Premawardhena, A., Arambepola,

M., Samaranayake, R., Allen, S.J., Peto, T.E.,

Fisher, C.A., Cook, J., Corran, P.H., Olivieri, N.F.,


and Weatherall, D.J. (2009). Proc. Natl. Acad. Sci.

USA 106, 18716–18721.

Old, J.M., Ward, R.H., Petrou, M., Karagozlu, F.,

Modell, B., and Weatherall, D.J. (1982). Lancet 2,

1413–1416.

Orkin, S.H., Alter, B.P., Altay, C., Mahoney, M.J.,

Lazarus, H., Hobbins, J.C., and Nathan, D.G.

(1978). N. Engl. J. Med. 299, 166–172.

Ottolenghi, S., Lanyon, W.G., Paul, J., Williamson,

R., Weatherall, D.J., Clegg, J.B., Pritchard, J., Poo-

trakul, S., and Boon, W.H. (1974). Nature 251,

389–392.

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Russo, G., Musumeci, S., Schillro, G., et al.

(1976). Cell 9, 71–80.

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Weatherall, D.J. (1977). Lancet 2, 737–739.

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A.W., Anderson, W.F., Bunn, H.F., Rosenthal, A.,

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(1965). Nature 208, 1061–1065.


Leading Edge

Essay

MicroRNAs and Cellular PhenotypyKenneth S. Kosik1,*1Neuroscience Research Institute, Department of Molecular Cellular Developmental Biology, University of California, Santa Barbara, Santa

Barbara, CA 93106, USA*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.008

This Essay explores the notion that specialized cells have unique vulnerabilities to environmentalcontingencies that microRNAs help to counteract. Given the ease with which new microRNAsevolve, they may serve as ideal facilitators for the emergence of new cell types.

Invariant laws of nature impact the

general forms and functions of

organisms; they set the channels

in which organic design must

evolve. But the channels are so

broad relative to the details that

fascinate us! The physical channels

do not specify arthropods, anne-

lids, mollusks, and vertebrates,

but, at most, bilaterally symmetrical

organisms based upon repeated

parts . When we set our focus

upon the level of detail that regu-

lates most common questions

about the history of life, contin-

gency dominates and the predict-

ability of general form recedes to

an irrelevant background.

Stephen Jay Gould, Wonderful Life: The

Burgess Shale and the Nature of History.

Penguin Books, 1989. (pp. 289–290).

IntroductionMuch is puzzling about microRNAs

(miRNAs). They are highly accurate mar-

kers of cell identity; their profiles unam-

biguously distinguish among cellular

phenotypes, including embryonic stem

cells, a vast variety of precursor cells,

terminally differentiated cells, and tumor

types, even among closely related

cancers (Lu et al., 2005). Furthermore, in

surveying many miRNA profiling studies,

the expression differences among certain

miRNAs in various cell types are often

orders-of-magnitude in contrast to the

low variation of most miRNAs following

environmental influences that do not

change cell identity. Although there is

a strong correlation between cell identity

and patterns of miRNA expression, this

does not mean that there are strong

phenotypic effects when an individual

miRNA is suppressed or knocked out. In

fact the effects of miRNAs on protein

levels are generally modest (Guo et al.,

2010), and short-circuiting nearly all

miRNA biogenesis by inactivating Dicer

can have surprisingly modest effects on

differentiation and patterning; however,

contrary experiments have also been

reported (reviewed in Fineberg et al.,

2009). Although many miRNAs are highly

conserved, some over the entire period

of bilaterian evolution, other miRNAs are

only found along a single evolutionary

branch, indicating the ease with which

new miRNAs are invented (Kosik, 2009).

Finally, among the puzzling features of

miRNAs are the overall increase in their

variety as a function of evolutionary time,

the lack of conservation of some targets,

and the poorly understood relationship

between targets and phenotypes.

The perspective put forth here is that

miRNAs serve as a reservoir to assist cells

in coping with environmental contin-

gencies. For instance, cells may at times

face short-term oxygen deprivation, but

a cell that is more dependent on aerobic

respiration will require its own adaptive

response. If miRNAs are available for envi-

ronmental contingencies, then their

response must be honed for the needs of

specific cell types. Evolutionary change

begins with mutations—not specialized

cells. The ease of miRNA invention

suggests that new miRNAs will create

conditions for expanding cell diversity

because the presence of a specific miRNA

may offset vulnerabilities of specialized

cells to environmental contingencies.

MicroRNA Profiles Correlatewith Cell IdentityThe complete list of constituent mole-

cules within a cell—its transcripts,

proteins, lipids, metabolites, and a host

of other molecules—occupy a parameter

space within a range of values, which

define the ‘‘cell state.’’ As markers of cell

identity, miRNAs encode a representation

of multiple cell states that all correspond

to a single identity. That is, many different

states comprise a single identity because

cells must retain their identities in the face

of both environmental changes and

internal noise that can result in large

variations in molecular composition.

Presumably, protein levels in cells fall

within certain boundaries below which

there is an insufficient amount of the

protein to achieve function and above

which toxicity emerges. miRNAs are

good candidates for setting boundary

conditions upon coding transcripts to

restrict protein levels within a range of

values that maintain cell identity in the

face of homeostatic compensatory

changes. Thus, miRNAs have properties,

which can hierarchically link the many

parameter settings of the cell state to

a phenotypic singularity known as cell

identity.

Cells undergoing developmental or

malignant transformation reset their

boundary conditions across a specified

collective threshold of multiple parame-

ters, which define a new identity. Shifting

the miRNA profile during development or

relaxing controls over onco-miRNAs and

tumor suppressor miRNAs are associated

with morphing a cell toward a new identity

(Figure 1). Changes in cell identity usually

occur in the context of mitosis during

stem cell differentiation, reprogramming,

oncogenesis, metaplasia, or pathological

response to injury. Usually controls over

the cell cycle are closely linked to the

emergence of a new identity, a point

most recently confirmed in several


studies that enhance the generation of

induced pluripotent stem cells by modu-

lating cell-cycle regulators p53, p21, and

p16(Ink4a)/p19(Arf) (reviewed in Puzio-

Kuter and Levine, 2009). The reverse

and forward arrows of change in cell iden-

tity are not symmetric. Reprogramming

a somatic cell to a stem cell is a rare event

but potentially possible in any cell. On the

other hand, pluripotency is easily lost.

Beyond a defined set of growth factors

required for sustaining stem cells, pluripo-

tency exists as a state of ‘‘freedom’’ from

other extrinsic factors (Silva and Smith,

2008) that promote differentiation.

To maintain pluripotency, the cell must

minimize not only the effects of extrinsic

signals but also intrinsically random fluc-

tuations that can initiate unintended

differentiation.

The intermediate states through which

cells travel to reach new identities are

lined with traps. The concept of steering

between these danger zones is called

‘‘canalization’’ and was introduced by

C.H. Waddington, and it has been

proposed that miRNAs guide a cell past

epigenetic traps toward its phenotype in

the face of environmental variation (Horn-

stein and Shomron, 2006). Although chro-

matin organization may account for the

height of the barriers to identity changes

(Chi and Bernstein, 2009), relatively subtle

balances in the constituents of a protein

complex accompany differentiation. An

example of this shift mediated by miRNAs

occurs in vertebrate nervous system

development. The development of the

vertebrate nervous system provides an

example of the influence of miRNAs over

epigenetic factors. As precursor cells

lose multipotency, a subunit switch

occurs in the mammalian SWI/SNF com-

plex, which mediates ATP-dependent

chromatin remodeling (Yoo et al., 2009).

During development, the BAF53a and

BAF45a subunits within the neural-

progenitor-specific complexes swap out

in favor of the homologous BAF53b and

BAF45b subunits to form neuron-specific

complexes found in postmitotic neurons.

miR-9* and miR-124 mediate this dy-

namic shift in subunit composition by

binding to sequences in the 30 untrans-

lated region of BAF53a mRNA, repressing

protein expression, and presumably

changing the kinetic balance of subunits

that drive complex assembly.

miRNA NetworksThe control elements over gene expres-

sion and the networks that link them are

often discussed in terms of their role in

sharpening the output and making the

system robust. Because miRNAs target

multiple mRNAs, they can exert distrib-

uted control over broad target fields of

functionally related mRNAs as opposed

to focusing their control on a small

number of genes in a ‘‘final common

pathway.’’ These networks are often

specialized for specific cell types. For

example, miR-21 regulates diverse

mRNAs that collectively control apoptosis

and proliferation, and the dysregulation of

miR-21 is associated with many types of

cancer (Papagiannakopoulos et al.,

2008). miRNAs, including nonhomolo-

gous miRNAs, are often physically clus-

tered in the genome, and these sets of

miRNAs may target mRNAs with related

biological functions at short distances in

their protein-protein interaction map

(Kim et al., 2009). The mouse miRNA

cluster, mmu-mir-183-96-182, targets

Irs1, Rasa1, and Grb2, all of which are

located in the insulin-signaling pathway,

and these miRNAs coordinate the control

of this signal transduction process

(Xu and Wong, 2008). The wide variation

in the glucose needs of cells suggests

that the specific workings of this pathway

probably differ among cell types. These

specific examples have been generalized

to show that coordinated miRNA targeting

of closely connected genes is prevalent

across pathways (Tsang et al., 2010).

Target capture by an miRNA depends

on the expression level of the miRNA,

the levels of all the target mRNAs,

including pseudogene decoy targets

(Poliseno et al., 2010), and the affinities

between them. Thus the network effects

of miRNAs can only be interpreted in

a particular cell if the copy numbers of

all mRNA targets are known. Small

changes within an miRNA/mRNA target

network may broaden random variation

Figure 1. Cell Identity and miRNA ProfilesThe cell state is the complete list of constituent molecules within a cell each at a specific number of copiesat one particular moment in time. The levels of all transcripts are one component of the cell state and eachtranscript is expressed at a range of levels with some maxima and minima depicted as boundaries. Withinthese boundaries the cell maintains a discrete identity, for example a specific type of differentiated cell.When a cell changes its identity—for example by reprogramming to a stem cell or undergoing malignanttransformation—new boundaries are established for the transcriptome. Transcription factors drive cellsacross boundaries to new identities and operate in feedback and feedforward loops with microRNAs(miRNAs). miRNA profiles reflect cell identity with very high accuracy and therefore reduce high-dimen-sional cell state values to a single profile.


around a threshold and, as described for

the intestinal specification network in

C. elegans (Raj et al., 2010), give rise to

a variable ON/OFF expression pattern of

a ‘‘master’’ regulatory gene within a popu-

lation of cells. Disrupting a network in this

manner thus leads to cell population

variation and has the potential to expand

the phenotypic repertoire of an organ-

ism’s cells.

miRNAs often operate in feedforward

and feedback loops. Genome-scale

mapping in C. elegans has revealed 23

such loops within the transcription

circuitry (Martinez et al., 2008) including

a miRNA/transcription feedback loop

that sets up left-right asymmetry (John-

ston et al., 2005). The mediation of pluri-

potency exit by miR-145 operates as

a double-negative feedback loop with

the transcription factor Oct4 (Xu et al.,

2009). The operation of this loop may

generate bistability through which the

cell reaches a single identity unless it

crosses a barrier at which point it inevi-

tably transitions to an alternative identity.

Identity transitions via bistable states

achieve discrete identities and avoid

intermediate states. miR-145 continues

to operate in differentiation at further

stages of mesoderm development in

regulating smooth muscle cell fate

(Cordes et al., 2009). Interestingly, miR-

145 in smooth muscle cells maintains its

functional vector toward differentiation

but switches some targets through which

it acts. Whether degraded or maintained

as a stable duplex the miRNA is

consumed, and thus its action is distinct

from the catalytic effects of many protein

regulators of gene expression. Thus the

two limbs of the transcriptional feedback

loops operate quite differently: transcrip-

tion factors regulate transcription of the

primary miRNA and miRNAs stoichiomet-

rically regulate the translation of the

mRNA that encodes the transcription

factor.

Wu and colleagues (Wu et al., 2009)

have proposed that miRNAs keep the

system close to the mean and set expres-

sion boundaries of transcription factors,

which are otherwise noisy. The mean

number of copies of different proteins in

a cell might have a set point, which lies

at different distances from the level of

toxicity. When the range of protein levels

in a cell fluctuates far from the point of

toxicity, the fluctuation is better tolerated

and miRNA regulation becomes extra-

neous. Only the extremes of protein

copy number variation within an infre-

quently occurring long tail jeopardize the

cell. However, if the mean copy number

of the protein is close to the point of

toxicity—and indeed, optimal function

may require that the protein set point is

close to the toxic level—then tight regula-

tion is necessary, and this might be

achieved by miRNAs. In this context,

a modest effect of miRNAs on protein

levels (Guo et al., 2010) will be highly

significant. PTEN appears to be an

example of a gene under exquisitely fine

regulation—it is targeted by numerous

miRNAs—and fine changes in its dosage

are critical to its cancer-forming potential

(Alimonti et al., 2010).

Information on the turnover of miRNAs

is just emerging. Often the pairing of the

prokaryotic small RNAs with a target

mRNA exposes both molecules to rapid

degradation (Masse et al., 2003). Some

miRNA/mRNA duplexes appear to be

highly stable as long as the identity of

the cell is stable. On the other hand, in

neurons (and perhaps other specialized

settings will show similar phenomena),

miRNA turnover is rapid. For example,

the miR-183/96/182 cluster, miR-204,

and miR-211 decay rapidly during dark

adaptation and are transcriptionally upre-

gulated in light-adapted retinas (Krol

et al., 2010). Indeed, the specialized

requirements of neurons, particularly

with regard to plasticity, may utilize the

miRNA system for regulation at a faster

timescale than in other cells. When a small

number of mRNAs are locally activated,

the RISC through its component protein,

MOV10 (also known as Armitage in

Drosophila and SDE3 in Arabidopsis thali-

ana), can derepress otherwise silenced

local translation (Banerjee et al., 2009).

The adaptation of miRNAs for rapid local

regulation contributes to fundamental

neuronal properties such as control over

local translation at the synapse and hence

has facilitated cell specialization.

The RISC allows both the constitutive

maintenance of cell identity by silencing

mRNAs that are not part of the specialized

cell’s repertoire as well as the holding of

mRNAs of an alternative identity in

reserve (Lim et al., 2005), perhaps for

less frequent contingencies. Maintaining

a large pool of stable miRNA/mRNA

duplexes rather than triggering duplex

degradation at the moment of binding

allows an entire control layer to lie poised

for the rapid release of a networked set of

mRNAs to undergo translation and

achieve a smooth and coordinated iden-

tity transition. Like apoptosis, in which

the cell systematically destroys itself in

a highly controlled sequence of events

to prevent triggering inflammatory reac-

tions, changes in cell identity require an

orderly transition so that residua from

a parental cell do not create toxic

interactions with an emerging daughter

cell while sustaining cell function during

the transition.

miRNA Levels Reset duringan Identity ChangeThe mapping of an miRNA profile onto cell

identity—a many onto one mapping—

corresponds to a phenotypic singularity

within the repertoire of all possible cellular

identities that the organism is capable of

producing. How the miRNA profile

undergoes the sweeping coordinated

changes associated with a new cell iden-

tity is poorly understood. Is there a global

disassembly of RISCs and loss of pre-ex-

isting miRNAs while new miRNA tran-

scription ramps up to fill RISCs or induce

their assembly with a distinct set of miR-

NAs? XRN is a candidate for mediating

this transition. In C. elegans, active turn-

over is mediated by the 50 to 30 exoribonu-

clease XRN-2 to modulate activity of the

mature miRNA (Chatterjee and Gros-

shans, 2009) and XRN is necessary for

regeneration in planarian (Rouhana et al.,

2010). Heuristically, an entry point to this

issue is cell transition states. Because

nature is so effective in establishing

discrete identities for cells, such states

are not always easy to observe.

Developmentally, cells have two strate-

gies by which they can morph into another

cell type. These strategies are distin-

guished by ‘‘mitosis required’’ or ‘‘mitosis

optional’’ properties. The mitosis required

option utilizes precursors that travel

through stages that progressively narrow

the potential of the cell within a lineage

tree until a terminal identity is achieved.

Reaching a terminal identity requires

passage through each discrete precursor

in a Waddington landscape. Progression

toward terminal differentiation through


a set of precursors can scale the number

of cells produced to the morphology of

the organism and position them correctly.

For example, the kinetics of neuron

generation in the development of the

mouse cerebral cortex can be modeled

by determining the proportion of neuroe-

pithelial cells that exit versus re-enter the

cell cycle over the 6 day neuronogenetic

interval of 11 cell cycles (Caviness et al.,

2003). In Drosophila, neuroectodermal

cells have a single fate decision at the

time of cell division: differentiate into neu-

roblasts, which specify neural fate

through their progeny, the ganglion

mother cells, or specify epidermal differ-

entiation (Doe, 2008). In the case of re-

programming one can reverse the arrow

of differentiation; however, mitosis

remains a requirement for successful re-

programming. The many control points

over mitosis operate within a complex

circuitry that includes multiple miRNAs

as is apparent in many studies that impli-

cate miRNAs in cancer.

Changes in cell identity also occur

without cell division or very limited cell

division through transition states without

discrete precursors. For example, when

zebrafish endothelial cells egress from

the aortic ventral wall they become hema-

topoietic stem cells (Kissa and Herbomel,

2010). Direct conversion of cells has been

achieved repeatedly in the laboratory: the

transcription factor CEBP can convert B

lymphocytes to macrophages (Xie et al.,

2004), Math1 can reprogram inner ear

support cells to hair cells (Izumikawa

et al., 2005), and MyoD, a transcription

factor that specifies the skeletal muscle

lineage, can convert cultured embryonic

fibroblasts, chondroblasts, and retinal

epithelial cells into contracting muscle

cells (Vierbuchen et al., 2010). A method

known as direct reprogramming or lineage

reprogramming introduces sets of tran-

scription factors into differentiated cells

that determine the identity of the reprog-

rammed cell. Three factors—Ascl1, Brn2

(also called Pou3f2), and Myt1l—are suffi-

cient to convert fibroblasts into neurons

(Zhou et al., 2008). In addition to in vitro

approaches, pancreatic exocrine cells

have been converted to beta-cells in vivo

by the addition of three factors, Ngn3,

Pdx1, and Mafa (Lessard et al., 2007).

Changes in cell identity are closely

linked to transcription factors, and there-

fore, within the many feedback loops

involving miRNAs, transcription factors

have a ‘‘dominant’’ role. Oncogenic

changes in cell identity are also domi-

nated by transcription factors that oper-

ate in feedback or feedforward loops

with miRNAs. For example, activation of

the c-Myc oncogenic transcription factor

induces Lin-28 and Lin-28B, which nega-

tively regulate let-7 biogenesis by pre-

venting both Drosha- and Dicer-mediated

let-7 processing (Chang et al., 2009).

Thus, a Myc-Lin-28B-let-7 regulatory

circuit appears to reinforce Myc-medi-

ated oncogenesis. The Lin-28-let-7 core

circuitry also operates in a positive feed-

back loop through NF-kB, which activates

Lin-28 to create a link between inflamma-

tion and cell transformation (Iliopoulos

et al., 2009).

The two strategies for increasing the

variety of specialized cells during devel-

opment have important differences.

Lineage reprogramming may reduce the

dangers of the mitotic state with its risk

of cancer and directly preserve the epige-

netic marks of the starting cell type. But

without expansion in cell number, growth

of the organism is restricted. Importantly,

growth of the organism is not strictly

a matter of size; in the case of the brain,

for example, massively parallel neuronal

networks confer emergent properties to

the organism including sapience. The

widespread developmental strategy of

utilizing precursor pools as discrete

cellular intermediates toward the genesis

of a mature organism requires the estab-

lishment of a series of precursor cell

identities along a path of progressively

narrowing potential until the cell reaches

a terminal identity. The ability of miRNAs

to capacitate cellular phenotypy permits

the emergence of large numbers of

precursor cell types capable of honing

developmental processes toward highly

specialized identities and precise cell

numbers.

miRNAs as a Reservoir forEnvironmental Contingencies andthe Expansion of Animal PhenotypyMany of the puzzling features of miRNAs

could be explained if they adapt cells to

environmental contingencies. The envi-

ronment that cells face is many times

more complex than the biological adapta-

tions available within the genome. Among

the adaptive responses of cells to an envi-

ronmental contingency is the up- or

downregulation of proteins. The proper-

ties of miRNAs to adjust protein levels,

their dispensability under basal condi-

tions, their conservation, as well as the

ease with which new miRNAs appear

over evolutionary time all suggest that

they are suited for environmental contin-

gencies. Among the many contingencies

organisms face is famine. The response

to limited glucose is mediated by insulin,

which lies in a pathway that is highly inter-

connected to miRNAs (Xu and Wong,

2008). One developmental response to

limited glucose at the organismal level is

a reduction in body size, and in Drosophila

this adaptation appears to be mediated

by miR-8 and its target USH (u-shaped)

(Hyun et al., 2009). Flies lacking miR-8

are both defective in insulin signaling in

the fat body (the counterpart of liver and

adipose tissue) and smaller in size.

In humans, a miR-8 homolog, miR-200,

and a USH homolog, FOG2, mediate the

same pathway. Another example is the

response of the heart to stress and hypo-

thyroidism through expression of the

cardiac-specific miR-208 (van Rooij

et al., 2007).

The miR-143/145 locus nicely illus-

trates the paradox that specific miRNAs,

which are part of a cell’s unique profile,

do not result in the loss of the cell’s iden-

tity when knocked out, but they do impair

the cell under certain contingencies. miR-

143/145 knockout mice have impaired

neointima formation in response to

vascular injury and have reduced vascular

tone (Xin et al., 2009). Hornstein and

Shomron (2006) point to the example of

miR-1 in D. melanogaster in the context

of a discussion on canalization. miR-1

is a highly conserved muscle-specific

miRNA that does not affect muscle

differentiation in D. melanogaster when

knocked out. The phenotype only

emerges during a rapid growth phase

(Sokol and Ambros, 2005). This example

also makes the point that different cells

require different responses to the same

environmental contingency. In this case,

rapid growth in muscle requires different

regulatory circuits than rapid growth in

other cell types.

Cells adapted to an environmental event

retain a genetic memory of the event.

When the frequency of an environmental


contingency falls below a certain level, the

selection pressure on the adaptive

response is diminished. However, genetic

memory is extended by weakly embed-

ding the miRNA contingency response

within a genetic circuitry (that is, a network

in which a single miRNA targets multiple

mRNAs to tune a complex function).

Whereas purifying selection operates on

the miRNA’s role in the genetic circuitry,

the miRNA remains in the absence of the

contingency and is available to facilitate

variation (Kirschner and Gerhart, 2005).

miRNAs, as part of modular networks,

can potentially speed evolutionary

processes and facilitate novelty (Parter

et al., 2008).

Given the very different cell responses

to the same contingency, one can pose

the ‘‘chicken and egg’’ question. Did

specialized cells give rise to miRNA

diversification or did miRNAs permit cell

specialization? Although framing of the

question as an either/or belies the

complexity of the answer, miRNAs have

many properties that are consistent with

a role in fostering cell specialization. Chief

among these properties is the ease with

which they can be invented through

a reservoir of 70 nucleotide hairpin struc-

tures in the genome, duplication at

different chromosomal loci, and formation

of miRNA families with different expres-

sion levels. Thus, miRNAs may underlie

the vast expansion of specialized cells

during early metazoan evolution and

support the numerous discrete precursor

cell types that have accompanied cell

specialization.

At the base of the animal kingdom lies

the phylum Porifera, a sister group to the

animal kingdom with an approximately

650 million year fossil record. The few

generic cell types in the largest class of

sponge species, the Demosponges,

bear little homology to cells found in the

rest of the animal kingdom. On the other

hand, cnidaria, an extraordinarily diversi-

fied phylum whose members, like the

sponge, are also derived from two germ

layers, has acquired many metazoan cell

types including neurons.

Thus, the common ancestor of the

sponge and all other animals represents

a critical evolutionary node when animal

phenotypy arose. At this same node,

miRNAs characteristic of animals also

arose (Christodoulou et al., 2010). Inter-

estingly, the role of miRNAs in evolution

of complex multicellularity may extend

beyond animals. Among the eukaryotic

groups that evolved complex multicel-

luarity, miRNAs are also present in red/

green algae and brown algae (Cock

et al., 2010).

The miRNA machinery exists in the De-

mosponge, Amphimedon queenslandica;

however, only eight miRNAs have been

detected, none of which bear any ortho-

logy to those in bilateria, and the size of

both the mature miRNA and its precursor

is distinct from other metazoans (Grimson

et al., 2008). In contrast, the cnidarian

Nematostella vectensis (starlet sea

anemone) possesses a larger repertoire

of more conventional miRNA genes, at

least one of which is conserved in bilateria

(Prochnik et al., 2007).

The ‘‘long fuse’’ transition to metazoan

cell diversity rests upon a core gene set

present in the sponge ancestor (Sakarya

et al., 2007). Although sponges lack the

phenotypic features of cell types seen in

the animal kingdom as well as many of

the corresponding subcellular features of

animal cells such as synapses and adhe-

rens junctions, they do have gene sets

that characterize animal cell types, and

many of these genes are expressed (Con-

aco and K.S.K., unpublished data). Pori-

feran gene sets were exapted (Sakarya

et al., 2007) in a manner that gave rise to

an extraordinary diversity of cells and

a variety of organisms over vast differ-

ences in scale. Positioned within the

biological hierarchy at a point where

phenotypes emerge from gene networks,

miRNAs, acting broadly on numerous

transcription factors and other genes

already present in the metazoan ancestor,

very likely contributed to the emergence

of animal phenotypy.

ACKNOWLEDGMENTS

My thanks go to T. Papagiannakopoulos, M.

Srivastava, B. Shraiman, M. Khammash, S. Goyal,

P. Neveu, and K. Foltz, whose comments greatly

improved this manuscript.

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Leading Edge

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How to Survive AneuploidyBulent Cetin1 and Don W. Cleveland1,*1Ludwig Institute for Cancer Research and Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla,

CA 92093, USA*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.030

Aneuploidy, or an abnormal number of chromosomes, adversely affects cell growth, but it is alsolinked with cancer and tumorigenesis. Now, Torres et al. (2010) help to resolve this paradox bydemonstrating that aneuploid yeast cells can evolve mutations in the proteasome protein degrada-tion pathway that alleviate imbalances in protein production and increase the cell’s proliferativecapacities.

During mitosis, duplicated chromosomes

are equally distributed to daughter cells

so that the total number of chromosomes

is preserved through many generations.

Errors in chromosomal segregation can

lead to the loss or gain of chromosomes

in daughter cells, a condition known as

aneuploidy. Aneuploidy is a hallmark of

cancer cells (Albertson et al., 2003), but

the causality of the relationship between

aneuploidy and tumorigenesis remains

highly complex and controversial

(Schvartzman et al., 2010). Aneuploidy

can either promote or suppress tumor

formation, and the outcome depends on

the genetic and cellular context, including

the specific genes on the abnormal chro-

mosome, the extent of the aneuploidy, the

already accumulated genetic errors, and

specific features unique to the cell type

(Holland and Cleveland, 2009).

Paradoxically, despite its association

with uninhibited cell growth in cancer,

aneuploidy itself has adverse effects on

the growth of organisms and their indi-

vidual cells. The most straightforward

reconciliation of these contrasting proper-

ties is that aneuploidy initially inhibits

growth, but then the acquisition of addi-

tional mutations or chromosomal shuffling

increases the fitness of cells. In this issue

of Cell, Torres et al. (2010) demonstrate

that this is indeed true for aneuploid yeast

cells. The authors find that a general

feature of aneuploidy is proteomic stress

caused by an imbalance in protein syn-

thesis for the genes encoded on the extra

chromosome; in several cases, mutations

in a deubiquitination enzyme can alleviate

this stress and enhance cellular growth

and fitness.

Earlier work by Torres and colleagues

(2007) described the physiological con-

sequences of yeast cells having an extra

copy of one or more chromosome. The

authors generated these disomic strains

by attempting to mate haploid yeast

cells carrying a mutation that prevents

fusion of the nuclei (i.e., karyogamy), lead-

ing to unsuccessful or abortive matings

(Hugerat et al., 1994). In these experi-

ments, one chromosome of the parental

yeast strains also contained a selection

marker, such as a gene that supports

growth in the absence of an essential

amino acid histidine (HIS) or one that

confers resistance against G418 (also

known as Geneticin), an aminoglycoside

that interferes with protein synthesis

elongation (Bar-Nun et al., 1983). During

the abortive matings, the marked chro-

mosomes were occasionally transferred

between two nuclei, and the chromo-

somal markers allowed for the selection

of disomic clones on G418-containing

and histidine-deficient media. Most of the

aneuploid strains isolated possessed a

growth defect on a nonselective medium,

and this deficiency was enhanced on

the selective medium. Furthermore, the

growth defects were due primarily to

a delay in the G1 phase of the cell

cycle.

As anticipated, analysis of the tran-

scripts in these disomic yeast strains

revealed that most genes on the extra

chromosome are transcribed at twice

the rate as the rest of the genome. On

the other hand, expression levels of a

small number of proteins, especially those

that are subunits of multiprotein com-

plexes, are not elevated. All of the disomic

strains also displayed increased energy

requirements and enhanced sensitivity to

conditions that interfere with protein syn-

thesis, folding, and degradation. These

findings led the authors to propose that

proteotoxic stress due to imbalanced pro-

tein expression might be responsible for

the reduced fitness of disomic yeast cells

(Figure 1, top). Furthermore, the cells’

enhanced sensitivity to proteasome inhib-

itors may reflect an increased reliance on

protein degradation to restore proteomic

balance in the disomic yeast cells.

Now, in their new study, Torres and

colleagues (2010) examined 13 different

haploid yeast strains, each with an extra

copy of one of the 16 yeast chromo-

somes. They grew the disomic strains

over several generations in the selective

medium. Initially, the doubling times of

these strains were significantly longer

than the control cells. However, after

a variable number of generations, 11 of

the cultures sped up their doubling

times. The authors isolated individual

clones from these ‘‘evolved’’ cultures to

identify the basis of their improved growth

rates (Figure 1, bottom). Comparative

genome hybridization analyses showed

that descendants of three disomic strains

had lost large parts of their additional

chromosome. These deletions alone may

have accounted for the improved pro-

liferation of the descendants. Of interest,

however, three independent clones pos-

sessed the same duplication of a 183 kb

fragment from the short arm of chromo-

some XVIII, suggesting that genes located

in this fragment may also play a role in

increasing the proliferative ability of these

aneuploid yeasts.


To identify point mutations that

increased the fitness of the aneuploid

yeast, Torres and colleagues then

sequenced several of the evolved isolates

from six of the disomic strains that

retained the extra chromosome. Strik-

ingly, they found that four genes of the

ubiquitin/proteasome pathway, UBP6 (a

deubiquitinase), RPT1 (an ATPase of the

proteasome), RSP5 (E3 ubiquitin ligase),

and UBR1 (E3 ubiquitin ligase), were

mutated in the descendents of five dif-

ferent disomic strains. Two independent

strains (disome V and disome IX) con-

tained distinct truncations in a gene

encoding the deubiquitinating enzyme

Ubp6 that interacts with the proteasome.

Both truncations impair the deubiquiti-

nase catalytic activity of Ubp6, but not

its association with the proteasome (Leg-

gett et al., 2002).

The authors next tested whether muta-

tions in the Ubp6 deubiquitinase alone

could directly help aneuploid yeast

recover more normal growth rates.

Indeed, in some cases, it did. Mutating

UBP6 increased the fitness of two

disomic strains in selective medium and

two strains (disome V and disome XI) in

both selective and nonselective media.

This latter finding is especially important

because a gain of fitness in only the selec-

tive medium could reflect a suppressive

function of the UBP6 mutation against

the action of the elongation inhibitor

G418. A final cautionary note is that the

effect of mutating UBP6 was not consis-

tent across the different disomic strains;

in fact, it decreased the fitness of two

disomic strains.

How could losing the deubiquitinating

activity of Ubp6 increase the growth rate

of aneuploid yeast cells? Ubp6 has been

shown to reduce the activity of the protea-

some, although this function of Ubp6

apparently does not require the deubiqui-

tinase catalytic activity (Hanna et al.,

2006). Nevertheless, mutating Ubp6 may

restore proteomic balance in the cell

by generally boosting protein degrada-

tion by the proteasome or by increasing

the proteasome’s activity on selective

substrates.

To distinguish between these two pos-

sibilities, Torres and colleagues deleted

UBP6 in the disomic strains and then

used a combination of mass spectrom-

etry and SILAC (i.e., stable isotope

labeling with amino acids in cell culture)

to analyze the effects of the deletion on

the yeast proteome. They chose two

disomic strains for these experiments:

disome V, in which deletion of UBP6

improves fitness, and disome XIII, in

which the mutation has no effect.

As expected, adding the extra chromo-

some increased the average abundance

of proteins encoded on the chromosome

by nearly 2-fold. Disomy also caused a

significant change in the relative abun-

dance of a number of proteins across

the whole proteome; whereas some

proteins increased in concentration by

nearly 2-fold, others decreased to nearly

half the levels of haploid cells. For disome

V, deleting UBP6 substantially attenuated

these changes in protein abundance, and

protein levels approached those of

haploid cells. In particular, loss of UBP6

in disome V downregulates proteins with

relatively high expression levels without

affecting their transcription but transcrip-

tionally upregulates proteins with rela-

tively low expression levels. Curiously,

deleting UBP6 in disome XIII does not

increase transcription of proteins with

relatively low expression levels, and this

difference may explain why mutating

UBP6 does not enhance the fitness of

disome XIII.

The implication from the new findings

by Torres and colleagues is that extra

chromosomes generally increase proteo-

mic stress by elevating the cost of protein

synthesis, folding, and degradation due to

the imbalance of proteins produced

(Figure 1). Thus, although each additional

chromosome creates an altered abun-

dance of a different set of encoded pro-

teins, any extra chromosome leads to

a growth disadvantage.

As the authors note, these new results

raise the possibility that aneuploid cancer

cells are under profound proteotoxic

Figure 1. Aneuploidy Induces Proteotoxic Stress(Top) An extra copy of an individual yeast chromosome, or disomy, causes imbalanced expression of theproteins encoded on that chromosome. Adding an inhibitor of protein synthesis, such as G418 (Geneticin),increases the errors in translation and enhances the proteotoxic stress. This stress reduces fitness andinhibits cell growth primarily during the G1 phase of the cell cycle.(Bottom) Suppressers of proteotoxic stress, including mutations in components of the ubiquitin/protea-some pathway, can ameliorate the proteomic imbalance and restore fitness (Torres et al., 2010). Forexample, disrupting the deubiquitinase UPB6 can increase the growth rate of aneuploid cells by triggeringmore rapid protein degradation by the proteasome.


stress and thus must rely on the increased

activity of the ubiquitin/proteasome path-

way to maintain their proliferative state.

This hypothesis provides an elegant ratio-

nale for extending the use of proteasome

inhibitors (such as Velcade) to treating

many types of cancers with aneuploid

cells; currently, these inhibitors are clini-

cally approved for treating only the over-

production of immunoglobulin synthesis

in multiple myeloma. In this regard, the

next step is to determine the extent to

which tumor cells with chromosomal

instability experience proteotoxic stress

and then to test whether increasing this

stress with proteasome inhibitors controls

their growth.

REFERENCES

Albertson, D.G., Collins, C., McCormick, F., and

Gray, J.W. (2003). Nat. Genet. 34, 369–376.

Bar-Nun, S., Shneyour, Y., and Beckmann, J.S.

(1983). Biochim. Biophys. Acta 741, 123–127.

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(2010). Nat. Rev. Cancer 10, 102–115.

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Torres, E.M., Dephoure, N., Panneerselvam, A.,

Tucker, C.M., Whittaker, C.A., Gygi, S.P., Dunham,

M.J., and Amon, A. (2010). Cell 143, this issue,

71–83.

Auxin Paves the Wayfor Planar MorphogenesisStefano Pietra1 and Markus Grebe1,*1Umea Plant Science Centre, Department of Plant Physiology, Umea University, SE-90 187 Umea, Sweden

*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.029

The coordinated growth of epidermal cells in plant leaves creates the characteristic jigsaw puzzleappearance of the pavement cells. Now, Xu et al. (2010) report that AUXIN-BINDING PROTEIN 1mediates auxin activation of two GTPase pathways that antagonistically control planar morphogen-esis of leaf epidermal cells to create this distinctive pattern.

Multicellular organisms rely on cell mor-

phogenesis within tissue layers to shape

organs during development. One striking

example is the growth of pavement cells

in the epidermis of plant leaves. As the

leaves expand, alternations in lobes and

indentations between cells give the layer

of pavement cells a characteristic jigsaw

puzzle appearance (Figure 1, left) (Yang,

2008). Although in animals cell morpho-

genesis within the plane of a tissue layer

relies on signaling through the planar

cell polarity pathway (named after the

receptor mutant ‘‘frizzled’’), plants have

different strategies for signaling planar

morphogenesis (Fischer et al., 2006). The

plant hormone auxin is known to coordi-

nate cell morphogenesis within the plane

of a tissue layer, and an array of specific

Rho-of-plant (ROP) small GTPases dir-

ectly reorganizes the cytoskeleton during

cell morphogenesis (Yang, 2008). How-

ever, it is unknown how auxin is perceived

and how its signal is transduced to

responding ROP-GTPases to direct cyto-

skeletal rearrangements. Two auxin

receptor systems could be involved: the

TIR1/AFB family of receptors, which

directly modulate gene expression in

response to auxin (Mockaitis and Estelle,

2008), or AUXIN-BINDING PROTEIN 1

(ABP1), which is located in the secretory

pathway and is secreted in some plant

species (Tromas et al., 2010). Disrupting

the ABP1 gene causes early death of plant

embryos, making it difficult to characterize

the roles of ABP1 in plant development

(Tromas et al., 2010). Thus, the ABP1

signaling pathway is still quite enigmatic.

Now, in this issue of Cell, Xu et al. (2010)

report that ABP1 senses auxin and

then rapidly activates two antagonizing

ROP-GTPase pathways in the cytoplasm,

which orchestrate planar morphogenesis

of pavement cells.

Xu et al. first demonstrate that auxin

modulates the shape of pavement cells

in the model plant Arabidopsis thaliana;

the external application of auxin increases

the lobing of the pavement cells, whereas

mutating four genes required for the

synthesis of auxin reduces interdigitated

growth (i.e., the lobes decrease in num-

ber). In a previous study, interfering with

the expression of two ROP-GTPases,

ROP2 and ROP4, decreased the lobing

of the pavement cells (Fu et al., 2005).


Now, Xu et al. find that application of

auxin does not rescue this phenotype,

indicating that ROP2 and ROP4 probably

act downstream of auxin. Indeed, the

authors then show that auxin rapidly acti-

vates ROP2 in leaf protoplasts (i.e., plant

cells without their cell walls). Conversely,

partially disrupting the function of ABP1

abolishes both cell morphogenesis in

response to auxin and rapid activation of

ROP2 in protoplasts.

These new findings by Xu et al. indicate

that auxin sensing by ABP1 is upstream of

the ROP-GTPases during cell morpho-

genesis of pavement cells. However, it is

still unknown where in the leaf tissue and

where in the cell ABP1 perceives the auxin

signal. Data from other plant species and

Arabidopsis protoplasts suggest that

a fraction of ABP1 is secreted and associ-

ates with the outer surface of the plasma

membrane (Figure 1, right) (Tromas

et al., 2010). Hence, ABP1 may act as an

auxin receptor at the plasma membrane

of pavement cells, but direct evidence

for this hypothesis is still lacking.

In plants, the auxin efflux carrier PIN-

FORMED1 (PIN1) generates directional

flow of auxin in cells by polarly localizing

to one end of the cell in the plasma mem-

brane (Kleine-Vehn and Friml, 2008).

Strikingly, Xu and colleagues find that

reducing the function of ABP1 or ROP2/

ROP4 diminishes the localization of PIN1

at the lobes of pavement cells. Therefore,

the authors hypothesize that a positive

feedback loop between PIN1 localization

and ROP2/ROP4 activity ensures auxin

flow through the lobe and auxin accumu-

lation in the cell wall. Interestingly a similar

positive feedback loop was recently pro-

posed to facilitate auxin transport by

auxin-induced transcriptional activation

of the scaffold protein ICR1 (INTERAC-

TOR OF CONSTITUTIVE ACTIVE ROP 1),

which directly interacts with ROP-

GTPases and mediates polar PIN protein

localization in root cells (Hazak et al.,

2010). In further support of such a feed-

back loop, Xu and colleagues find that

the activity of ROP2 is diminished in

pin1 mutant plants, which display re-

duced lobing of pavement cells.

Morphogenesis of pavement cells is not

only about lobing, but it also requires the

coordination of indentations in adjacent

cells (Figure 1, right). ROP6 controls

indentations by organizing the microtu-

bule cytoskeleton at the plasma mem-

brane within indentations (Fu et al.,

2009). Indeed, Xu and colleagues find

that a mutation in ABP1 impairs ROP6

activation in protoplasts and reduces

indentations in Arabidopsis plants,

demonstrating that ABP1 also contributes

to the production of indentations.

Interestingly Xu and colleagues show

that, at saturating concentrations of auxin

in protoplasts, the activation of ROP6

reaches higher levels than that of ROP2,

suggesting that the activation kinetics of

these two ROPs is significantly different.

Figure 1. Interdigitated Growth of Plant Pavement CellsIn the model plant Arabidopsis thaliana, epidermal cells within the plane of the leaf, called pavement cells, contain alternating lobes and indentations. The auxinefflux carrier PIN1, which localizes polarly in the plasma membranes of lobes, is proposed to facilitate auxin accumulation in the cell wall between lobes andindentations. This auxin is believed to activate two Rho-of-plant (ROP) small GTPases that antagonistically control morphogenesis of the two pavement cells(Xu et al., 2010). At the lobe of one cell, AUXIN-BINDING PROTEIN 1 (ABP1) senses the auxin and switches on ROP2, which then promotes assembly of corticalF-actin microfilaments through the ROP2 effector RIC4. In the adjacent cell, auxin signaling through ABP1 activates ROP6, which then triggers the association ofthe effector RIC1 with cortical microtubules. This results in the formation of well-ordered bundles of microtubules that restrict expansion of the cell and generatean indentation. The two pathways antagonize each other; ROP2 suppresses RIC1 activity, whereas well-ordered microtubules repress the interaction of ROP2and RIC4.


This led the authors to propose a model

for how auxin coordinates the formation

of an indentation and a lobe in adjacent

pavement cells (Figure 1, inset). In this

working model, PIN1 exports auxin into

the cell wall of the lobe, where it stimu-

lates ABP1 signaling. At steady-state

concentrations of auxin, ROP2 seques-

ters the ROP6 effector RIC1 in the lobe,

but RIC1 represses the activation of

ROP2 in the adjacent cell by stimulating

the organization of microtubules (Fu

et al., 2005). In this way, two antagonistic

ROP signaling pathways, which both

depend on ABP1, determine actin-medi-

ated lobe formation in one cell and

tubulin-driven indentation in its neighbor

(Figure 1, inset). The proposed positive

feedback loop with auxin-ABP1, ROP2,

and PIN1 could enforce and maintain

this growth asymmetry.

The findings by Xu and colleagues are

certainly exciting because they elegantly

integrate ABP1 function into a conceptual

framework of signaling in planar morpho-

genesis. The authors’ model describes

a possible scenario for steady-state main-

tenance of interdigitated growth at uni-

form auxin concentrations in pavement

cells. However, it does not yet address

the event that breaks the symmetry

between adjacent cells and whether auxin

is the original polarizing cue. Interestingly,

auxin can orchestrate planar polarization

in the root epidermis, where a concentra-

tion gradient of auxin provides vectorial

information for the polar positioning of

hairs close to one end of the cell (Fischer

et al., 2006). Young leaves, too, display

an asymmetry in auxin distribution

(Yang, 2008), and it will be interesting to

see whether this asymmetry may play

a role in pavement cell morphogenesis.

At first glance, it seems as if auxin acts

differently on planar morphogenesis in

the root versus the shoot. Whereas

a gradient of auxin directs planar polarity

in roots, the coordination of planar

morphogenesis in pavement cells relies

on a self-organizing design in which auxin

triggers differential activity of ROPs.

Nevertheless, it will be interesting to deter-

mine whether the signaling network

uncovered by Xu et al. will help to decipher

how auxin is sensed during the formation

of planar polarity in other tissues. For

example, a second intriguing study in

this issue of Cell (Robert et al., 2010)

reports a role for ABP1 in the endocytosis

of PIN proteins in the roots of Arabidopsis.

Clathrin-mediated endocytosis is known

to be required for internalization of several

PIN proteins (Kleine-Vehn and Friml,

2008). The new study by Robert and

colleagues suggests that ABP1 is neces-

sary for correctly placing the vesicle coat

protein clathrin at the plasma membrane

of root cells. Furthermore, their findings

support the hypothesis that auxin can

inhibit PIN1 internalization mediated by

ABP1. To what extent this new function

of ABP1 in roots connects to ABP1’s role

in planar morphogenesis of pavement

cells remains an exciting question for

future studies.

Another question that remains unan-

swered is whether ABP1 is the sole auxin

receptor required during pavement cell

morphogenesis or whether it acts in

concert with the TIR1/AFB receptor

system. In addition, the study by Xu and

colleagues now allows for the exploration

of components in the auxin signaling

pathway upstream of ROP. The identifica-

tion of additional factors that interact with

ABP1 may also help to pinpoint the exact

subcellular locations where ABP1 senses

auxin in leaves and possibly other tissues.

Clearly, the findings by Xu and colleagues

show that ABP1-mediated auxin signaling

is a corner piece in the jigsaw puzzle of

planar morphogenesis in plants, and it

will be thrilling to watch the next pieces

fall into place.

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Fischer, U., Ikeda, Y., Ljung, K., Serralbo, O.,

Singh, M., Heidstra, R., Palme, K., Scheres, B.,

and Grebe, M. (2006). Curr. Biol. 16, 2143–2149.

Fu, Y., Gu, Y., Zheng, Z., Wasteneys, G., and Yang,

Z. (2005). Cell 120, 687–700.

Fu, Y., Xu, T., Zhu, L., Wen, M., and Yang, Z. (2009).

Curr. Biol. 19, 1827–1832.

Hazak, O., Bloch, D., Poraty, L., Sternberg, H.,

Zhang, J., Friml, J., and Yalovsky, S. (2010).

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Paciorek, T., Baster, P., Vanneste, S., Zhang, J.,

Simon, S., Hayashi, K., et al. (2010). Cell 143, this

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Tromas, A., Paponov, I., and Perrot-Rechenmann,

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Leading Edge

Previews

Cell Sorting during RegenerativeTissue FormationRudiger Klein1,*1Department of Molecular Neurobiology, Max-Planck-Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.018

Regeneration of transected peripheral nerves is a complex process involving the coordinatedaction of neuronal axons, glial cells, and fibroblasts. Using rodent models of nerve repair, Parrinelloet al. (2010) find that ephrin signaling between fibroblasts and Schwann cell progenitors, involvingthe stemness factor Sox2, is required for nerve regeneration.

Many open wounds in the extremities

involve peripheral nerve injuries. Al-

though simple nerve crushes generally

recover without surgical interference,

complete or partial nerve transections

lead to degeneration of the axonal

segment distal to the lesion, and nerves

often fail to regenerate. To facilitate the

regeneration of cut nerves, the two nerve

stumps are surgically realigned. In spite

of this surgical treatment, the transected

nerve stumps tend to retract and the

resulting gap needs to be filled with

new tissue (a ‘‘nerve bridge’’). Schwann

cells (the glial cells that normally en-

sheath and myelinate peripheral axons)

dedifferentiate to a progenitor/stem cell

state, proliferate, and migrate into the

nerve wound forming an environment

that is supportive for axonal growth;

they produce trophic factors to support

the injured axons and prevent the

neurons from undergoing apoptosis

(Heumann et al., 1987). Fibroblasts accu-

mulate at the nerve wound and secrete

proteins that promote scar formation,

angiogenesis, and inflammation. How

the different cell types communicate

with each other to orchestrate the forma-

tion of a regenerative microenvironment

is poorly understood. In this issue, Parri-

nello and colleagues (Parrinello et al.,

2010) show that ephrin signaling

between fibroblasts and Schwann cells

is a key mediator of this process.

To study the early stages of peripheral

nerve repair, the authors perform

complete transections of the rat sciatic

nerve. The sciatic nerve is a mixed

motor/sensory nerve that originates in

the sacral plexus and branches in the thigh

region into smaller nerves innervating

several hindleg muscles and parts of the

hindleg skin. In contrast to neurons in the

central nervous system, the axons of

muscle-innervating motoneurons in the

periphery and those of skin-innervating

sensory neurons have a high capacity to

regenerate. A temporal analysis of cell

migration and axon behavior during the

first 7 days after the nerve cut reveals

that nonmyelinating Schwann cells collec-

tively migrate into the nerve bridge from

both stumps as discrete cell cords, which

eventually meet in the middle of the gap.

There they are surrounded and contacted

by fibroblasts but do not appear to inter-

mingle, suggesting a cell sorting event.

Migrating Schwann cells are closely fol-

lowed by regenerating axons from the

proximal stump, consistent with the model

that Schwann cells guide regenerating

axons across the injury site (McDonald

et al., 2006) (Figure 1).

Parrinello and coworkers reasoned that

the sorting between Schwann cells and

fibroblasts may be a key event for

successful nerve repair. Their analysis

reveals that cell sorting depends on two

processes: the repulsion of Schwann cells

by fibroblasts and the attractive adhesion

of Schwann cells to one another. In ex vivo

cocultures, primary rat Schwann cells and

nerve fibroblasts sorted into mutually

exclusive cell clusters, and this cell

behavior required signaling via ephrin

and its receptor Eph between the two

cell types. Ephs are a large family of

receptor tyrosine kinases that bind to eph-

rin ligands presented on the surface of

apposing cells. Ephrin/Eph interactions

in the nervous system induce a wide

range of cellular behaviors including re-

pulsive cell and axon guidance, synapse

formation, and neuronal plasticity (Klein,

2009), and ephrin/Eph signaling had

previously been implicated in regenera-

tive processes (Pasquale, 2008). Ephrin

ligands come in two flavors: A-type

ephrins are anchored in the membrane

by glycophosphatidylinositol (GPI) post-

translational modification and preferen-

tially bind EphA receptors, and B-type

ephrins are transmembrane proteins that

preferentially bind EphB receptors. In the

current study, cultured nerve fibroblasts

are found to express high levels of

ephrin-B2, which interacts with EphB

receptors (mostly EphB2) expressed on

Schwann cells. By manipulating the levels

of ephrin-B2 and EphB2, the authors

convincingly demonstrate that ephrin-B/

EphB2 signaling between fibroblasts and

Schwann cells is necessary and sufficient

for cell sorting and cluster formation

in vitro.

Although ephrin/Eph signaling is

thought to primarily induce rapid cell

responses by controlling actin dynamics,

Parrinello and coworkers speculate that

Eph-mediated cell sorting may involve

long-term changes in cell behavior by

regulating gene expression. They find

that the transcription factor Sox2, which

plays important roles in the biology of

stem and progenitor cells (Chambers

and Tomlinson, 2009), including Schwann

cell progenitors (Le et al., 2005), mediates

ephrin-B2-induced Schwann cell clus-

tering. The treatment of Schwann cells


with soluble ephrin-B2 ligand increases

the abundance of Sox2 proteins in

culture, and knockdown of Sox2 using

small-interfering RNAs greatly reduces

cell clustering in the coculture assay with

nerve fibroblasts. Sox2 overexpression

rescues the cell sorting deficiency of

Schwann cells derived from EphB2

knockout mice, indicating that Sox2 acts

downstream of EphB2. Moreover, EphB

signaling via Sox2 relocalizes the cell-

surface adhesion molecule N-cadherin

to Schwann cell-cell contacts, providing

an explanation for the increased attrac-

tion between Schwann cells and the

formation of cell cords in the nerve bridge

(Figure 1). By manipulating the abun-

dance of N-cadherin in Schwann cell

cultures, the authors provide compelling

evidence that N-cadherin is necessary

and sufficient for cell sorting downstream

of EphB2 and Sox2.

After having worked out the mecha-

nism of Schwann cell-fibroblast commu-

nication, Parrinello and coworkers asked

whether regenerating axons also respond

to ephrins. After all, many populations of

axons are guided by ephrin/Eph signaling

during development (Egea and Klein,

2007). In the nerve bridge, regenerating

axons grow in close interaction with

Schwann cells and segregate away

from fibroblasts. However, unlike

Schwann cells, the axons of sensory

neurons are not repelled by ephrin-B2

protein, suggesting that they do not

directly interact with the fibroblasts.

When sensory neurons are instead ex-

planted onto Schwann cells that had

been cultured in the presence of stripes

of ephrin-B2, the axons grow out onto

the Schwann cells, forming fascicles

that avoid the stripes of ephrin-B2. These

findings demonstrate that ephrin/Eph

signaling can influence axonal outgrowth

indirectly by modulating Schwann cell

behavior.

Finally the authors provide some

evidence that EphB2 signaling mediates

collective cell migration in vivo. To inter-

fere with EphB2 function, sciatic nerve

regeneration was observed in mice lack-

ing EphB2 or in wild-type rats in which an

inhibitory EphB2-Fc fusion protein is deliv-

ered to the nerve wound via miniature

osmotic pumps. In both cases, axonal

regrowth is reduced and appears less

organized compared to controls. Given

that regrowing axons almost completely

overlap with Schwann cell cords, the

authors conclude that EphB2 signaling

directs the migration of Schwann cells

and axons during the early phases of nerve

repair in vivo.

Nerve repair is a very complex process,

and despite these new and interesting

findings, many questions remain unan-

swered. How important is ephrin/Eph

signaling for nerve regeneration in

general? Previous work has implicated

the EphA4 receptor as an inhibitor of

regeneration in the central nervous

system (Pasquale, 2008). Hence, ephrin/

Eph signaling may be both beneficial

and detrimental to nerve repair depending

on the specific context. A recent study

also finds that Schwann cell migration is

inhibited by ephrins, this time implicating

GPI-anchored ephrin-As and their

cognate EphA receptors (Afshari et al.,

2010). These observations suggest that

multiple members of this large family of

ligands and receptors may play important

roles by regulating complex cell sorting

behaviors among several cell types. The

present study only investigated the

response of sensory, not motor, axons

to ephrins in ex vivo preparations. Given

that hindleg-innervating motoneurons

respond to both ephrin-As and -Bs during

development (Luria et al., 2008), it would

be important to elucidate the ephrin

responsiveness of regrowing motor axons

of the sciatic nerve. The requirement of

the transcription factor Sox2 for EphB-

dependent formation of Schwann cell

clusters is intriguing and suggests that

Eph signaling may regulate gene expres-

sion in development and disease.

This aspect should be further explored in

other Eph-dependent morphogenetic

functions. The underlying intracellular

signaling pathways may reveal new

mechanisms of cell regulation.

In summary, the elegant work presented

by Parrinello and colleagues establishes

new insight into how nerve fibroblasts

and Schwann cells interact in the nerve

wound to form cords of Schwann cells

that then provide a favorable microenvi-

ronment and a direct substrate for

regrowing axons. They also uncover

a new signaling pathway downstream of

EphB2 via Sox2 and N-cadherin that at

least partially mediates the cell sorting

process, which ultimately leads to the

formation of Schwann cell cords in the

nerve bridge. These findings will undoubt-

edly stimulate further work on ephrin/Eph

signaling in tissue regeneration.

Figure 1. Early Events in Peripheral Nerve RepairAfter transection of the sciatic nerve (the edge of the proximal stump is shown on the left), Schwann cellsthat normally form the myelin sheath dedifferentiate and migrate into the nerve wound. Here, they come inclose contact with fibroblasts that also populate the nerve wound. Activation of ephrin-B/EphB signalingbetween these two cell types activates a signaling cascade in the Schwann cell that leads to accumulationof Sox2 in the nucleus. Sox2-dependent transcription causes the relocalization of N-cadherin to Schwanncell contacts and promotes the formation of Schwann cell cords in the nerve wound. Regrowing sensoryaxons (in red) grow out onto the Schwann cells and form parallel axon fascicles.


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opment 136, 2311–2322.

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and Kania, A. (2008). Neuron 60, 1039–1053.

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chodne, D. (2006). Neuron Glia Biol. 2, 139–147.

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Myogenin and Class II HDACsControl Neurogenic Muscle Atrophyby Inducing E3 Ubiquitin LigasesViviana Moresi,1 Andrew H. Williams,1 Eric Meadows,4 Jesse M. Flynn,4 Matthew J. Potthoff,1 John McAnally,1

John M. Shelton,2 Johannes Backs,1,5 William H. Klein,4 James A. Richardson,1,3 Rhonda Bassel-Duby,1

and Eric N. Olson1,*1Department of Molecular Biology2Department of Internal Medicine3Department of Pathology

University of Texas Southwestern Medical Center, Dallas, TX 75390, USA4Department of Biochemistry and Molecular Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA5Present address: Department of Cardiology, University of Heidelberg, 69117 Heidelberg, Germany


DOI 10.1016/j.cell.2010.09.004

SUMMARY

Maintenance of skeletal muscle structure and func-tion requires innervation by motor neurons, suchthat denervation causes muscle atrophy. We showthat myogenin, an essential regulator of muscledevelopment, controls neurogenic atrophy. Myoge-nin is upregulated in skeletal muscle following dener-vation and regulates expression of the E3 ubiquitinligases MuRF1 and atrogin-1, which promote muscleproteolysis and atrophy. Deletion of myogenin fromadult mice diminishes expression of MuRF1 andatrogin-1 in denervated muscle and confers resis-tance to atrophy. Mice lacking histone deacetylases(HDACs) 4 and 5 in skeletal muscle fail to upregulatemyogenin and also preserve muscle mass followingdenervation. Conversely, forced expression ofmyogenin in skeletal muscle of HDAC mutant micerestores muscle atrophy following denervation.Thus, myogenin plays a dual role as both a regulatorof muscle development and an inducer of neurogenicatrophy. These findings reveal a specific pathway formuscle wasting and potential therapeutic targets forthis disorder.

INTRODUCTION

Maintenance of muscle mass depends on a balance between

protein synthesis and degradation. Innervation of skeletal

muscle fibers by motor neurons is essential for maintenance of

muscle size, structure, and function. Numerous disorders,

including amyotrophic lateral sclerosis (ALS), Guillain-Barre

syndrome, polio, and polyneuropathy, disrupt the nerve supply

to muscle, causing debilitating loss of muscle mass (referred to

as neurogenic atrophy) and eventual paralysis.

Loss of the nerve supply to muscle fibers results in muscle

atrophy mainly through excessive ubiquitin-mediated proteo-

lysis via the proteasome pathway (Beehler et al., 2006). Other

pathologic states and systemic disorders, including cancer,

diabetes, fasting, sepsis, and disuse, also cause muscle atrophy

through ubiquitin-dependent proteolysis (Attaix et al., 2008;

Attaix et al., 2005; Medina et al., 1995; Tawa et al., 1997). The

muscle-specific E3 ubiquitin ligases MuRF1 (also called

Trim63) and atrogin-1 (also called MAFbx or Fbxo32) are

upregulated during muscle atrophy and appear to represent final

common mediators of this process (Bodine et al., 2001; Clarke

et al., 2007; Gomes et al., 2001; Kedar et al., 2004; Lecker

et al., 2004; Li et al., 2004; Li et al., 2007; Willis et al., 2009).

However, the precise molecular mechanisms and signaling

pathways that control the expression of these key regulators of

muscle protein turnover have not been fully defined and it

remains unclear whether all types of atrophic signals control

these E3 ubiquitin ligase genes through the same or different

mechanisms. Further understanding of the molecular pathways

that regulate muscle mass is a prerequisite for the development

of novel therapeutics to ameliorate muscle-wasting disorders.

Myogenin is a bHLH transcription factor essential for skeletal

muscle development (Hasty et al., 1993; Nabeshima et al.,

1993). After birth, myogenin expression is downregulated in

skeletal muscle but is reinduced in response to denervation

(Merlie et al., 1994; Tang et al., 2008; Williams et al., 2009).

Upregulation of myogenin in denervated skeletal muscle

promotes the expression of acetylcholine receptors and other

components of the neuromuscular synapse (Merlie et al., 1994;

Tang and Goldman, 2006; Williams et al., 2009). However, it

has not been possible to address the potential involvement of

myogenin in neurogenic atrophy because myogenin null mice

die at birth due to failure in skeletal muscle differentiation (Hasty

et al., 1993; Nabeshima et al., 1993).

Histone acetylation has been implicated in denervation-

dependent changes in skeletal muscle gene expression, and

histone deacetylase (HDAC) inhibitors block the expression of

Cell 143, 35–45, October 1, 2010 ª2010 Elsevier Inc. 35

myogenin in response to denervation (Tang and Goldman, 2006).

In this regard, the class IIa HDACs, HDAC4 and HDAC5, which

act as transcriptional repressors (Haberland et al., 2009; McKin-

sey et al., 2000; Potthoff et al., 2007), are upregulated in skeletal

muscle upon denervation and repress the expression of Dach2,

a negative regulator of myogenin (Cohen et al., 2007; Tang et al.,

2008).

To investigate the potential involvement of myogenin, HDAC4,

and HDAC5 in neurogenic atrophy, we performed denervation

experiments in mutant mice in which these transcriptional

regulators were deleted in adult skeletal muscle. We show

that adult mice lacking myogenin fail to upregulate the E3 ubiq-

uitin ligases MuRF1 and atrogin-1 following denervation and

are resistant to neurogenic atrophy. We demonstrate that myo-

genin binds and activates the promoter regions of the MuRF1

and atrogin-1 genes, in vitro and in vivo. Similar to adult mice

lacking myogenin, mice lacking Hdac4 and Hdac5 in skeletal

muscle do not upregulate myogenin following denervation and

are resistant to muscle atrophy. Conversely, overexpression of

myogenin in skeletal muscle is sufficient to upregulate the

expression of MuRF1 and atrogin-1 and promote neurogenic

atrophy in mice lacking Hdac4 and Hdac5. These findings reveal

a key role of myogenin and class IIa HDACs as mediators of

neurogenic atrophy and potential therapeutic targets to treat

this disorder.

RESULTS

Adult Mice Lacking Myogenin Are Resistantto Muscle Atrophy upon DenervationTo bypass the requirement of myogenin for skeletal muscle

development and investigate its functions in muscle of adult

mice, we used a conditional myogenin null allele (Knapp et al.,

2006), which could be deleted in adult muscle with a tamox-

ifen-regulated Cre recombinase transgene (Hayashi and McMa-

hon, 2002; Knapp et al., 2006). Tamoxifen was administered to

mice at 2 months of age, and 89% deletion of the conditional

myogenin allele occurred as measured by PCR genotyping

from genomic DNA 1 week after tamoxifen injection (see

Figure S1 available online). Hereafter, we refer to these mice

with deletion of myogenin during adulthood as Myog�/� mice.

To examine the role of myogenin in denervated skeletal

muscle, the sciatic nerve was severed one month following

tamoxifen administration, and muscle atrophy was assessed

14 days later by weighing denervated and contralateral tibialis

anterior (TA) muscles. Wild-type (WT) denervated TA showed

approximately a 40% decrease in weight following denervation

in comparison to the contralateral TA (Figure 1A). In contrast,

denervated TA from Myog�/� mice showed a minimal decrease

in muscle weight (�20%) compared to the contralateral

TA (Figure 1A), suggesting that Myog�/� mice were partially

resistant to muscle atrophy. Because we deleted myogenin in

adult mice, muscle development and growth occurred normally

prior to tamoxifen administration. As expected, the muscle

weights of the nondenervated contralateral TA in Myog�/� and

WT mice were similar (WT TA = 37.82 ± 0.87 mg; Myog�/�

TA = 36.27 ± 0.54 mg; t test = 0.19). Comparable resistance to

atrophy was observed in the gastrocnemius and plantaris (GP)

weight of Myog�/� mice (Figure 1A).

Immunostaining for laminin of TA cross-sections clearly delin-

eated a decrease of muscle fiber size in the WT denervated TA in

comparison to the contralateral muscle, indicative of muscle

atrophy (Figure 1B). In contrast, the decrease in fiber size was

less evident in the Myog�/� denervated TA (Figure 1B). Morpho-

metric analysis of TA cross-sections highlighted a significant

difference in myofiber size between WT and Myog�/� muscles

following denervation, confirming the latter were resistant to

muscle atrophy (Figure 1C).

As expected, seven days after denervation, MuRF1 and

atrogin-1 expression was dramatically upregulated in the GP of

denervated WT mice (Figure 1D). Remarkably, this upregulation

was significantly reduced in Myog�/� denervated GP (Figure 1D),

suggesting that the lack of upregulation of MuRF1 and atrogin-1

in denervated Myog�/� muscles was responsible for resistance

to atrophy. Deletion of myogenin mRNA from adult Myog�/�

muscle was confirmed by real-time PCR (Figure 1D). Of note,

expression of MyoD (Myod1), another bHLH myogenic regula-

tory factor (Davis et al., 1987), was highly upregulated in both

the contralateral and denervated GP of the Myog�/� mice, seven

days after denervation (Figure 1D). These data show that myoge-

nin does not regulate Myod1 expression following denervation.

The dramatic upregulation of Myod1 following denervation of

Myog�/� mice, which are resistant to atrophy, also argues

against a major role of Myod1 in promoting neurogenic atrophy.

Accordingly, Myod1 null mice are not resistant to muscle atrophy

following denervation (Jason O’Rourke and E. Olson, unpub-

lished data).

Denervation is known to affect skeletal myofiber composition

(Herbison et al., 1979; Midrio et al., 1992; Nwoye et al., 1982;

Patterson et al., 2006; Sandri et al., 2006; Sato et al., 2009).

To determine whether the resistance to muscle atrophy ob-

served in mice lacking myogenin was due to differences in

fiber type composition, we performed fiber type analysis of

soleus muscles 2 weeks after denervation. Our findings re-

vealed no difference in fiber type composition between WT

and Myog�/� mice (Figure S2). These findings suggest that

myogenin, which is upregulated following denervation, is

required for maximal induction of E3 ubiquitin ligase genes

and neurogenic atrophy.

We next tested whether myogenin was necessary for medi-

ating other forms of atrophy, such as occurs in response to

fasting. As shown in Figure 1E, the GP muscles of WT and

Myog�/� mice displayed comparable loss in mass following a

48 hr fast. We observed the upregulation of MuRF1 and

atrogin-1 upon fasting in both WT and Myog�/� mice and vali-

dated the deletion of myogenin in Myog�/� mice (Figure 1F).

These data clearly demonstrate that myogenin is not required

for starvation atrophy, but rather is a specific mediator of

neurogenic atrophy.

Myogenin Activates MuRF1 and Atrogin-1 TranscriptionBecause upregulation of MuRF1 and atrogin-1 was impaired in

Myog�/� mice, we analyzed the promoter regions of the

MuRF1 and atrogin-1 genes for E boxes (CANNTG) that might

confer sensitivity to myogenin. Indeed, three E boxes are located

36 Cell 143, 35–45, October 1, 2010 ª2010 Elsevier Inc.

in the promoter of the MuRF1 gene, E1 (�143 bp), E2 (�66 bp),

and E3 (�44 bp), and one conserved E box is located 79 bp

upstream of the atrogin-1 gene (Figure S3A). The E boxes

upstream of MuRF1 are contained in a genomic region near

the binding site for FoxO transcription factors (Waddell et al.,

2008), but several kilobases away from a region shown to be

regulated by NFkB (Cai et al., 2004). The E box upstream of atro-

gin-1 is embedded in a region containing multiple FoxO-binding

sites (Sandri et al., 2004).

To confirm the binding of myogenin to the MuRF1 and atrogin-1

promoters, we performed chromatin immunoprecipitation (ChIP)

assays using differentiated C2C12 myotubes, as Myogenin

Figure 1. Adult Mice Lacking Myogenin

Are Resistant to Muscle Atrophy upon

Denervation

(A) Percentage of TA or GP muscle weight of

WT and Myog�/� mice 14 days after denervation,

expressed relative to contralateral muscle.

*p < 0.05 versus WT. **p < 0.005 versus WT.

n = 4 for each sample. Data are represented as

mean ± standard error of the mean (SEM).

(B) Immunostaining for laminin of contralateral and

denervated TA of WT and Myog�/� mice, 14 days

after denervation. Scale bar = 20 microns.

(C) Morphometric analysis of contralateral and

denervated TA of WT and Myog�/� mice, 14 days

after denervation. Values indicate the mean of

cross-sectional area of denervated TA fibers as

a percentage of the contralateral fibers ± SEM.

**p < 0.005 versus WT. n = 3 cross-sections.

(D) Expression of MuRF1, atrogin-1, Myogenin and

Myod1 in contralateral (�) and denervated (+) GP

of WT and Myog�/� mice, 7 days after denerva-

tion, detected by real-time PCR. The values are

normalized to WT contralateral GP. Data are rep-

resented as mean ± SEM. *p < 0.05; **p < 0.005

versus WT. n = 4 for each sample.

(E) Weight of GP muscle of WT and Myog�/� mice

fed (�) or fasted (+) for 48 hr. Data are represented

as mean ± SEM. **p < 0.005 versus fed GP.

NS = not significant. n = 6 for each sample.

(F) Expression of MuRF1, atrogin-1 and Myogenin

in fed (�) and 48 hr fasted (+) GP of WT and

Myog�/� mice, detected by real-time PCR. The

values are normalized to WT fed GP. Data are

represented as mean ± SEM. zp < 0.005 versus

WT. **p < 0.005 versus fed. NS = not significant.

n = 6 for each sample.

See also Figure S1 and Figure S2.

expression correlates with MuRF1 and

atrogin-1 expression during muscle cell

differentiation (Figure S3B) (Spencer

et al., 2000). After six days of differentia-

tion, chromatin from C2C12 myotubes

was immunoprecipitated with antibodies

against myogenin or immunoglobulin G

(IgG) as a control. Using primers flanking

the E boxes in the MuRF1 and atrogin-1

promoters, DNA was amplified by PCR

(Figure 2A and Figure S3C). Clear enrich-

ment of the corresponding promoter sequences in the DNA

immunoprecipitated with antibodies against myogenin com-

pared to IgG was indicative of myogenin binding to the endoge-

nous MuRF1 and atrogin-1 promoters.

We validated in vivo binding of myogenin to the endogenous

MuRF1 and atrogin-1 promoters by performing ChIP assays

using sonicated chromatin extracts from TA muscles harvested

from mice at 3 days and 7 days after denervation (Figure 2B

and Figure S3D). Direct binding of myogenin as a heterodimer

with E12 proteins to the E boxes E2 and E3 in the MuRF1

promoter and to the E box in the atrogin-1 promoter was shown

by gel mobility shift assays (Figure S3E).


We further tested the ability of myogenin to activate the

MuRF1 and atrogin-1 promoter regions in vitro by constructing

luciferase reporter plasmids containing the 600 bp genomic

DNA fragment upstream of the MuRF1 gene (MuRF1-Luc) or

712 bp upstream of the atrogin-1 gene (atrogin-1-Luc) upstream

of a luciferase reporter. Mutant versions of these promoter

regions were generated by mutating the myogenin-binding sites

in the promoters. By transfecting C2C12 cells, activation of lucif-

erase was detected in response to myogenin using the wild-type

promoters (Figure 2C). This activation was blunted by mutation

of the E boxes in the promoters (Figure 2C), indicating that the

MuRF1 and atrogin-1 promoter regions contain responsive myo-

genin-binding sites. Similar results were obtained in transfected

COS1 cells (Figure S3F).

Figure 2. Myogenin Directly Regulates

MuRF1 and Atrogin-1

(A) ChIP assay performed in C2C12 myotubes

showing myogenin binding to MuRF1 and atro-

gin-1 promoters. Chromatin was immunoprecipi-

tated with antibodies against immunogloblulin G

(IgG), or myogenin. Primers flanking the E boxes

on the MuRF1 and atrogin-1 promoters were

used for amplifying DNA by real-time PCR. Values

indicate the mean of fold enrichment over chro-

matin immunoprecipitated with antibodies against

IgG ± SEM. n = 3.

(B) ChIP assays performed using denervated TA

muscle at 3 and 7 days following denervation

show myogenin binding to the MuRF1 and

atrogin-1 promoters. Values indicate the fold

enrichment over chromatin immunoprecipitated

with antibodies against IgG.

(C) Luciferase assays performed on cell extracts of

C2C12 myoblasts transfected with luciferase

reporter plasmids ligated to the WT (MuRF1-Luc)

(atrogin-1-Luc), or the mutant constructs of

MuRF1 and atrogin-1 genes, with myogenin (+)

or empty (�) expression plasmid. Data are repre-

sented as mean ± SEM.

(D) b-galactosidase staining of contralateral and

denervated GP muscles isolated from transgenic

mice containing a lacZ transgene under the

control of the WT (MuRF1-WT-lacZ) (atrogin-1-

WT-lacZ) or the mutant (MuRF1-Emut-lacZ)

(atrogin-1-Emut-lacZ) constructs of the MuRF1

or atrogin-1 promoters. Upper panels show

whole muscles. Lower panels show muscle

sections. Scale bar = 20 microns.

See also Figure S3.

To test the responsiveness of the E3

ligase gene promoters to atrophic signals

in vivo, transgenic mice were generated

harboring the same upstream regions of

the genes ligated to a lacZ reporter

(Kothary et al., 1989; Williams et al.,

2009). Transgenic mice with the mutated

versions of these promoter regions

were also generated (MuRF1-Emut-lacZ

and atrogin-1-Emut-lacZ). Seven days

following denervation, b-galactosidase

expression controlled by the wild-type promoters was upregu-

lated in denervated GP muscle fibers compared to the inner-

vated contralateral leg muscles (Figure 2D). The expression of

lacZ in only a subset of myofibers likely reflects the mosaicism

of F0 transgenic mice and, perhaps, variable upregulation of

the E3 ubiquitin ligase genes in different myofibers in response

to denervation (Moriscot et al., 2010). In contrast to the obvious

upregulation of the wild-type transgenes following denervation,

mutation of the E boxes in these promoters abrogated b-galac-

tosidase expression, revealing an essential role for myogenin in

denervation-dependent activation of MuRF1 and atrogin-1

in vivo (Figure 2D). These results show that the MuRF1 and

atrogin-1 genes are targets of myogenin transcriptional activa-

tion in response to denervation.


Mice Null for Class II HDACs Are Resistant to MuscleAtrophy upon DenervationPrevious studies showed that the class II HDACs, HDAC4 and

HDAC5, are upregulated in skeletal muscle in response to dener-

vation (Bodine et al., 2001; Cohen et al., 2007; Tang et al., 2008)

and are responsible for the repression of Dach2, a negative regu-

lator of Myogenin (Cohen et al., 2007; Tang et al., 2008). In light of

the role of myogenin in promoting muscle atrophy, we hypothe-

sized that mice lacking HDAC4 or HDAC5 in skeletal muscle

would be resistant to atrophy following denervation owing to

a block of Myogenin expression via Dach2. Mice with global dele-

tion of Hdac4 display lethal bone abnormalities (Vega et al., 2004),

so we deleted Hdac4 specifically in skeletal muscle using a condi-

tional allele and a myogenin-Cre transgene (Hdac4fl/fl; myog-Cre;

hereafter referred to as Hdac4 skKO) (Potthoff et al., 2007). The

absence of HDAC4 protein upon Hdac4 gene deletion was

confirmed by western blot analysis (Figure S4). Since mice null

for Hdac5 do not display a phenotype (Chang et al., 2004), we

used Hdac5�/� mice (hereafter referred to as Hdac5 KO) for these

experiments. Fourteen days following denervation, WT dener-

vated TA showed approximately a 50% decrease in weight in

comparison to the contralateral TA (Figure 3A). In contrast, dener-

vated TA muscles from Hdac4 skKO or Hdac5 KO mice showed

a decrease of about 30% in muscle weight in comparison to

the contralateral muscles (Figure 3A), suggesting that these

mice were partially resistant to muscle atrophy. The weight of

the contralateral TA was similar among the mice (data not shown).

HDAC4 and HDAC5 display functional redundancy in different

tissues and in a variety of developmental and pathological

settings (Backs et al., 2008; Haberland et al., 2009; Potthoff

et al., 2007), so we generated double knockout (dKO) mice by

crossing Hdac4 skKO with Hdac5 KO mice to further investigate

the role of HDAC4 and HDAC5 in skeletal muscle atrophy.

The dKO mice were viable and fertile and showed no obvious

phenotype under normal conditions (data not shown). Strikingly,

Figure 3. HDAC4 and HDAC5 Redundantly

Regulate Skeletal Muscle Atrophy

(A) Percentage of TA muscle weight of mice of

the indicated genotype 14 days after denervation,

expressed relative to the contralateral muscle.

Data are represented as mean ± SEM.

**p < 0.005 versus WT. n = 5 for each sample.

(B) Immunostaining for laminin in contralateral and

denervated TA of mice of the indicated genotype,

14 days after denervation. Scale bar = 20 microns.

(C) Morphometric analysis of contralateral and

denervated TA of indicated genotype, 14 days

after denervation. Values indicate the mean of

cross-sectional area of denervated TA fibers as

a percentage of the contralateral fibers ± SEM.

*p < 0.05 and **p < 0.005 versus WT. n = 3

cross-sections.


fourteen days after denervation, the

TA of denervated dKO mice showed

a decrease in weight of only �10%

compared to the contralateral TA

(Figure 3A), revealing that the dKO mice were more resistant to

muscle atrophy compared to Hdac4 skKO or Hdac5 KO mice.

The weight of the contralateral TA was comparable among the

mice (data not shown). Similar differences were also observed

among GP muscles between WT and dKO mice (Figure S5).

Immunostaining for laminin 14 days after denervation clearly

demonstrated that the denervated TA fibers from Hdac4 skKO

and Hdac5 KO mice were larger than the denervated WT fibers

and that the denervated TA from dKO mice had a minimal

decrease in muscle fiber size compared to the contralateral dKO

TA (Figure 3B). Morphometric analysis on TA sections revealed

that, although WT mice showed a reduction of �70% in the myo-

fiber cross-sectional area between denervated and contralateral

TA, Hdac4 skKO denervated TA displayed �30% reduction in

myofiber cross-sectional area. Hdac5 KO denervated TA also

showed a substantial reduction in myofiber area (�50%) when

compared to the contralateral TA, whereas in dKO mice this

reduction was only �25% (Figure 3C). From these results, we

conclude that HDAC4 and HDAC5 redundantly regulate skeletal

muscle atrophy and mice lacking these HDACs in skeletal muscle

are resistant to muscle atrophy upon denervation.

Aberrant Transcriptional Responses to Denervationin HDAC Mutant MiceWe compared the transcriptional responses to denervation in

WT and dKO mice by real-time PCR analysis of denervation-

responsive transcripts. As reported previously (Cohen et al.,

2007; Tang et al., 2008), Dach2 expression was dramatically

downregulated upon denervation in WT mice. However, Dach2

was only modestly downregulated in the dKO mice (Figure 4).

Consistent with the repressive influence of Dach2 on Myogenin

expression, in WT mice, Myogenin and Myod1 were strongly

upregulated three days after denervation, as were MuRF1 and

atrogin-1 (Figure 4). In contrast, neither Myogenin nor Myod1

transcripts were upregulated following denervation of dKO


mice (Figure 4). The upregulation of MuRF1 and atrogin-1 was

also completely abolished in dKO denervated GP (Figure 4), sug-

gesting that the lack of upregulation of MuRF1 and atrogin-1 in

denervated dKO muscles was in part responsible for resistance

to atrophy.

Myogenin Overexpression in dKO Muscle RestoresNeurogenic AtrophyTo examine whether forced expression of myogenin was suffi-

cient to overcome the resistance of the dKO TA muscle to dener-

vation-induced atrophy, we electroporated the TA of dKO mice

with either a myogenin expression plasmid or an empty expres-

sion plasmid. Gene delivery efficiency was monitored by coelec-

troporation with a GFP vector (Dona et al., 2003; Rana et al.,

2004). Three days after electroporation, which is sufficient time

for the electroporated plasmids to be expressed in skeletal

muscle (Dona et al., 2003), we denervated one leg of the dKO

mice by cutting the sciatic nerve; the TA muscles were harvested

10 days after denervation. As seen in Figure 5A, laminin immu-

nostaining of dKO TA muscles clearly revealed a decrease in

Figure 4. dKO Mice Show Altered Gene Expression upon Denervation

Expression of the indicated mRNAs was detected by real-time PCR in WT and dKO denervated GP and normalized to the expression in the contralateral muscle.

Data are represented as mean ± SEM. **p < 0.005 versus dKO. n = 6 for each time point.

Figure 5. Ectopic Expression of Myogenin Induces Muscle Atrophy in dKO Mice Following Denervation

(A) Immunostaining for laminin (red) of cross-section of contralateral and denervated dKO TA electroporated with GFP expression plasmid and control plasmid

(HDAC4/5 dKO Control) or GFP plasmid and myogenin (HDAC4/5 dKO + Myogenin), 10 days after denervation. Histology shows that the dKO denervated

GFP-positive fibers coelectroporated with myogenin are smaller than denervated GFP-positive fibers coelectroporated with control plasmid. Scale

bar = 20 microns.

(B) Morphometric analysis performed on GFP-positive fibers of contralateral (�) and denervated (+) dKO TA muscles electroporated with GFP expression plasmid

and control plasmid (Control) or GFP plasmid and myogenin (Myogenin), 10 days after denervation. Values indicate the mean of cross-sectional area of

GFP-positive muscle fibers as a percentage of the contralateral control fibers ± SEM. *p < 0.05 versus control. n = 7 for each condition.

(C) Expression of Myogenin, MuRF1, and atrogin-1 in contralateral (�) and denervated (+) dKO TA muscles electroporated with GFP plasmid and a control

plasmid (Control) or GFP plasmid and myogenin (Myogenin), 10 days after denervation. Values are normalized to the expression in the contralateral control

muscles. Data are represented as mean ± SEM. *p < 0.05 versus control. n = 3 for each sample.

See also Figure S6.


myofiber size in the denervated TA of dKO mice overexpressing

myogenin compared to the denervated dKO TA electroporated

with the control vector. Morphometric analysis performed on

GFP-positive myofibers showed a significant decrease in the

size of myofibers of the denervated dKO TA electroporated

with myogenin versus control vector (Figure 5B). Real-time

PCR analysis validated the overexpression of Myogenin in elec-

troporated TA muscle of dKO mice and showed an upregulation

of the expression of MuRF1 and atrogin-1 (Figure 5C), confirming

the myogenin-dependent regulation of the E3 ubiquitin ligases.

The potential role of myogenin in driving muscle atrophy was

further investigated by overexpressing myogenin in the TA

muscle of WT mice. Morphometric analysis performed on

GFP-positive myofibers showed no significant size difference

between myofibers electroporated with control or myogenin

expression plasmid (Figures S6A and S6B). Real-time PCR anal-

ysis validated the overexpression of myogenin in electroporated

TA muscle of WT mice and showed an upregulation of the

expression of MuRF1 and atrogin-1 (Figure S6C). Taken

together, thesefindings demonstrate that overexpression of myo-

genin is necessary but not sufficient to induce muscle atrophy.

DISCUSSION

The results of this study demonstrate a key role of myogenin, well

known for its function as an essential regulator of myogenesis, in

controlling neurogenic atrophy. Myogenin promotes muscle

atrophy upon denervation by directly activating the expression

of MuRF1 and atrogin-1, which encode E3 ubiquitin ligases

responsible for muscle proteolysis. Upregulation of Myogenin

in response to denervation is controlled by a transcriptional

pathway in which HDAC4 and 5 are initially induced and, in

turn, repress the expression of Dach2 (Tang and Goldman,

2006), a negative regulator of Myogenin (Figure 6).

It is generally accepted that muscle atrophy occurs when

proteolysis exceeds protein synthesis (Eley and Tisdale, 2007;

Glass, 2003; Mammucari et al., 2008; Sandri et al., 2004). Up-

regulation of myogenin in response to denervation has been

proposed as an adaptive mechanism to prevent muscle atrophy

Figure 6. Model for Neurogenic Atrophy

Denervation of skeletal muscle results in the upregulation

of HDAC4 and HDAC5, which represses Dach2, a negative

regulator of myogenin, resulting in Myogenin expression.

Myogenin activates the expression of MuRF1 and atro-

gin-1, two E3 ubiquitin ligases that participate in the

proteolytic pathway resulting in muscle atrophy. Myoge-

nin also regulates miR-206, which establishes a negative

feedback loop to repress HDAC4 expression and promote

reinnervation.

(Hyatt et al., 2003; Ishido et al., 2004). On the

contrary, we demonstrate here that myogenin

directly regulates MuRF1 and atrogin-1, which

promote the loss of muscle mass in response

to denervation, revealing a mechanistic basis

for neurogenic muscle atrophy and a previously

unrecognized function for myogenin in this

pathological process.Recently, we showed that microRNA (miR) 206 is also upregu-

lated in denervated skeletal muscle via a series of conserved E

boxes that bind myogenin (Williams et al., 2009). miR-206, in

turn, represses expression of HDAC4 and controls a retrograde

signaling pathway that promotes reinnervation of denervated

myofibers (Figure 6). Thus, skeletal muscle responds to denerva-

tion by activating an elaborate network of transcriptional and

epigenetic pathways, involving positive and negative feedback

loops, which modulate nerve-muscle interactions and muscle

growth and function (Figure 6).

Dual Roles of Myogenin in Muscle Developmentand AtrophyOur findings reveal the gene regulatory circuitry for muscle

development is redeployed in adulthood to control aspects of

muscle disease and stress responsiveness. Thus, myogenin

can exert opposing effects on skeletal muscle—either promoting

differentiation or degradation—depending on the developmental

or pathological setting. These contrasting activities of myogenin

likely reflect differential modulation by signaling pathways and

cofactors that enable myogenin to regulate distinct sets of target

genes.

Similar to myogenin, Dach2 is a transcription factor involved in

both muscle development and muscle atrophy. Dach2 is

expressed in the developing somites prior to the onset of

myogenesis and has been shown to regulate myogenic specifi-

cation by interacting with the Eya2 and Six1 transcription factors

(Heanue et al., 1999; Kardon et al., 2002). Indeed, Dach proteins

are required for activation of Six1 targets (Li et al., 2003), sug-

gesting a possible role of Dach proteins in the Six1-mediated

regulation of muscle development (Laclef et al., 2003) or fiber

type specification (Grifone et al., 2004). Following denervation,

Dach2 plays a role in connecting neuronal activity with myogenin

expression (Cohen et al., 2007; Tang and Goldman, 2006; Tang

et al., 2008).

The finding that forced expression of myogenin in HDAC4/5

mutant mice is sufficient to restore muscle atrophy following

denervation indicates that myogenin is a key downstream

mediator of the proatrophic functions of these HDACs. It is


noteworthy, however, that the blockade to muscle atrophy and

E3 ligase expression imposed by the combined deletion of

HDACs 4 and 5 is more pronounced than in Myog�/� mice.

This suggests the existence of additional downstream targets

of these HDACs that promote neurogenic atrophy. We also

note that forced overexpression of myogenin in innervated skel-

etal muscle was not sufficient to induce muscle atrophy

(Figure S6) (Hughes et al., 1999). These findings indicate that

myogenin is necessary, but not sufficient, to regulate the genetic

program for muscle atrophy and imply the existence of additional

denervation-dependent signals that potentiate the ability of

myogenin to promote atrophy.

MyoD, like myogenin, is upregulated in response to denerva-

tion (Figure 4 and (Charge et al., 2008; Hyatt et al., 2003; Ishido

et al., 2004). In Myog�/� mice, Myod1 expression is dramatically

elevated compared to WT muscles and is super-induced in

response to denervation (Figure 1D). The observation that

Myod1 null mice are not resistant to muscle atrophy following

denervation (Jason O’Rourke and E. Olson, unpublished data)

demonstrates a negligible role for Myod1 in neurogenic atrophy

and points to myogenin as the major myogenic bHLH factor

involved in this process. This is consistent with the finding that,

although MyoD and myogenin bind the same DNA consensus

sequences, they regulate distinct sets of target genes (Blais

et al., 2005; Cao et al., 2006).

A Myogenin-Dependent Transcriptional Pathwayfor Muscle AtrophyWe show, both in vivo using denervated muscles and in vitro

using differentiated C2C12 cells, that myogenin binds the

endogenous MuRF1 and atrogin-1 promoters. We observed

a decrease in myogenin expression and binding to these E3

ubiquitin ligase promoters between days 3 and day 7 after dener-

vation (Figure 2B and Figure 4), suggesting an especially impor-

tant role of myogenin in triggering the transcriptional cascade

leading to atrophy. Consistent with our finding that myogenin

regulates MuRF1 and atrogin-1 expression, these E3 ubiquitin

ligases are upregulated upon C2C12 differentiation (Figure S3B)

(Spencer et al., 2000), a process known to be regulated by

myogenin. Although it is well established that MuRF1 and atro-

gin-1 function in driving skeletal muscle atrophy (Bodine et al.,

2001; Clarke et al., 2007; Gomes et al., 2001; Kedar et al.,

2004; Lecker et al., 2004; Li et al., 2004; Li et al., 2007; Willis

et al., 2009), their potential roles in myogenesis have not been

explored. Considering the important role of ubiquitination in

regulating proteolysis, endocytosis, signal transduction (Hicke,

2001), and transcription (Salghetti et al., 2001), it will be inter-

esting to investigate the potential involvement of MuRF1 and

atrogin-1 in muscle development and regeneration.

Therapeutic ImplicationsNumerous disorders, including motor neuron disease, fasting,

cancer cachexia, and sarcopenia, cause muscle atrophy and

the E3 ubiquitin ligase genes are thought to function as final

common mediators of different atrophic stimuli. Myogenin is

upregulated upon denervation and spinal cord isolation (Hyatt

et al., 2003), but is not induced in response to other forms of

atrophy, such as fasting, cancer cachexia, or diabetes (Lecker

et al., 2004; Sacheck et al., 2007). In this regard, we have found

that Myog�/� mice display a normal loss of skeletal muscle mass

in response to fasting, further demonstrating that myogenin is

dedicated to neurogenic atrophy and sensing the state of motor

innervation. The fact that MuRF1 and atrogin-1 are upregulated

in other atrophy conditions in the absence of myogenin upregu-

lation (Lecker et al., 2004; Sacheck et al., 2007) strongly

suggests that other transcription factors known to regulate the

expression of these ubiquitin ligases, such as the FoxO family

or NFkB (Bodine et al., 2001; Sandri et al., 2004; Waddell

et al., 2008), play a role in driving muscle atrophy in a myoge-

nin-independent manner.

Our finding that myogenin, in addition to HDAC4 and HDAC5,

acts as a regulator of neurogenic muscle atrophy through the

activation of E3 ubiquitin ligases provides a new perspective

on potential therapies for muscle wasting disorders. Class II

HDACs are regulated by a variety of calcium-dependent

signaling pathways that control their nuclear export through

signal-dependent phosphorylation (Backs et al., 2008; McKinsey

et al., 2000). In a pathological condition such as muscle denerva-

tion, HDAC4 and HDAC5 are upregulated, shuttle into the

myonuclei adjacent to neuromuscular junctions (Cohen et al.,

2007), and are critical regulators of muscle atrophy. Modulation

of the activity of class II HDACs, through pharmacologic inhibi-

tion compatible with the maintenance of steady-state transcrip-

tion of genes regulated by class II HDACs, may represent a new

strategy for ameliorating muscle atrophy following denervation.

EXPERIMENTAL PROCEDURES

Mouse Lines

Mice used in this study are described in the Extended Experimental Proce-

dures.

Denervation

In anaesthetized adult mice, the sciatic nerve of the left leg was cut and a 3 mm

piece was excised. The right leg remained innervated and was used as control.

Mice were sacrificed after 3, 7, 10, or 14 days.

DNA Delivery by Electroporation

For gene delivery by electroporation, adult dKO mice were anesthetized; TA

muscles exposed, injected with 30 mg of DNA in a solution of 5% mannitol,

and immediately subjected to electroporation. Electroporation was performed

by delivering 10 electric pulses of 20 V each (five with one polarity followed by

five with inverted polarity). A pair of 3 3 5 mm Genepaddle electrodes (BTX,

San Diego, CA) placed on opposite sides of the muscle was used to deliver

the electric pulses. pCMV-Snap25-GFP (provided by Tullio Pozzan, University

of Padua, Padua, Italy) was used in a 1:1 ratio with pcDNA3.1 (Invitrogen) or

EMSV-myogenin plasmid (Rana et al., 2004).

Immunohistochemistry

Cryosections of TA or soleus were fixed in 4% paraformaldehyde in PBS for

10 min at 4�C and washed in PBS. After incubating 30 min with 0.1%

Triton X-100 in PBS, the samples were fixed for 1 hr in 15% goat serum in

PBS supplemented with M.O.M. Mouse IgG blocking reagent (Vector Labora-

tories) (BB) at room temperature. Primary antibodies were incubated overnight

at 4�C (1:100 dilution of rabbit polyclonal anti-laminin antibody; 1:16000

anti-type I myosin heavy chain (MHC) (Sigma). Primary antibodies were

detected by Alexa Fluor-488 or -555 goat anti-rabbit antibody (Invitrogen)

diluted 1:800 in BB. DAB staining (Vector Laboratories) was used on soleus

muscle for detecting type I MHC. Soleus muscles were used for metachro-

matic ATPase staining as described elsewhere (Ogilvie and Feeback, 1990).


Staining of transgenic lines positive for b-galactosidase was performed on GP

muscles, as previously described (Williams et al., 2009).

Morphometric Analysis

Myofiber area was assessed on TA cryosections using ImageJ software

(http://rsb.info.nih.gov/ij/) (NIH). Three H&E-stained cross-sections from three

different mice for each genotype were analyzed. Between 100 and 350 GFP-

positive fibers were analyzed for each electroporated TA muscle. The values

are calculated as the percentage of the average of the cross-sectional area

of each TA over the average cross-sectional area of the contralateral TA fibers.

RNA Isolation and RT-PCR

Total RNA was isolated from GP muscles using Trizol reagent (Invitrogen)

following the manufacturer’s instructions. Three micrograms of RNA was con-

verted to cDNA using random primers and Superscript III reverse transcriptase

(Invitrogen). Gene expression was assessed using real-time PCR with the ABI

PRISM 7000 sequence detection system and TaqMan or with SYBR green

Master Mix reagents (Applied Biosystems). Real-time PCR values were

normalized with glyceraldehyde-3-phosphate dehydrogenase (GAPDH).

A list of Taqman probes and Sybr Green primers are available in the Extended

Experimental Procedures.

Plasmid Constructs

A list of the plasmids used in this study is available in the Extended Experi-

mental Procedures.

Cell Culture

COS cells were grown in DMEM supplemented with 10% fetal bovine serum

(FBS) and antibiotics (100 U/ml penicillin and 100 mg/ml streptomycin).

C2C12 myoblasts were grown in DMEM supplemented with 20% FBS and

antibiotics and differentiated in DMEM supplemented with 2% horse serum

and antibiotics.

Chromatin Immunoprecipitation Assay

ChIP assays were performed using C2C12 myotubes at day six of differentia-

tion or using TA muscles three and seven days after denervation with the ChIP

assay kit (Upstate) following the manufacturer’s instructions. Chromatin was

immunoprecipitated with antibodies against immunogloblulin G (Sigma) or my-

ogenin (M-225; Santa Cruz). The sequences of the ChIP primers are available

in the Extended Experimental Procedures.

Luciferase assay

C2C12 transfections were performed using Lipofectamine 2000 (Invitrogen) as

previously described (Mercer et al., 2005). COS cells were plated and trans-

fected 12 hr later using FuGENE (Roche Applied Science) following the manu-

facturer’s instructions. The MuRF1 and atrogin-1 reporter plasmid cloning

strategy is described in the Extended Experimental Procedures. Luciferase

assays were performed with the Luciferase Assay kit (Promega) according

to the manufacturer’s instructions.

Site-Directed Mutagenesis

Mutations were introduced into E boxes E2 and E3 of the MuRF1 promoter

region and in the E box of the atrogin-1 promoter by using the QuikChange II

Site-Directed Mutagenesis Kit (Stratagene). The same E box mutations as

those used in electrophoretic mobility shift assays were introduced within

each E box site in the promoters.

Statistical Analysis

Data are presented as mean ± standard error of the mean (SEM). Statistical

significance was determined using two-tailed t test with a significance level

minor of 0.05.

SUPPLEMENTAL INFORMATION

Supplemental Information includes Extended Experimental Procedures and

six figures and can be found with this article online at doi:10.1016/j.cell.

2010.09.004.

ACKNOWLEDGMENTS

We thank Marco Sandri for scientific input, Cheryl Nolen and Svetlana

Bezprozvannaya for technical assistance, Jose Cabrera for graphics, and

Jennifer Brown for editorial assistance. Work in the laboratory of E.N.O. was

supported by grants from the National Institutes of Health and the

Robert A. Welch Foundation (grant number I-0025). W.H.K. was supported

by a grant from the Muscular Dystrophy Association and the Robert A. Welch

Foundation. J.B. was supported by the Deutsche Forschungsgemeinschaft

(BA 2258/1-1).

Received: April 20, 2010

Revised: June 1, 2010

Accepted: August 20, 2010

Published: September 30, 2010

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Long Noncoding RNAswith Enhancer-like Functionin Human CellsUlf Andersson Ørom,1 Thomas Derrien,2 Malte Beringer,1 Kiranmai Gumireddy,1 Alessandro Gardini,1 Giovanni Bussotti,2

Fan Lai,1 Matthias Zytnicki,2 Cedric Notredame,2 Qihong Huang,1 Roderic Guigo,2 and Ramin Shiekhattar1,2,3,*1The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104, USA2Centre for Genomic Regulation (CRG), UPF, Barcelona, Spain3Institucio Catalana de Recerca i Estudis Avancats (ICREA), Barcelona, Spain*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.001

SUMMARY

While the long noncoding RNAs (ncRNAs) constitutea large portion of the mammalian transcriptome, theirbiological functions has remained elusive. A few longncRNAs that have been studied in any detail silencegene expression in processes such as X-inactivationand imprinting. We used a GENCODE annotation ofthe human genome to characterize over a thousandlong ncRNAs that are expressed in multiple cell lines.Unexpectedly, we found an enhancer-like functionfor a set of these long ncRNAs in human cell lines.Depletion of a number of ncRNAs led to decreasedexpression of their neighboring protein-codinggenes, including the master regulator of hematopoi-esis, SCL (also called TAL1), Snai1 and Snai2. Usingheterologous transcription assays we demonstrateda requirement for the ncRNAs in activation of geneexpression. These results reveal an unanticipatedrole for a class of long ncRNAs in activation of criticalregulators of development and differentiation.

INTRODUCTION

Recent technological advances have allowed the analysis of the

human and mouse transcriptomes with an unprecedented reso-

lution. These experiments indicate that a major portion of the

genome is being transcribed and that protein-coding sequences

only account for a minority of cellular transcriptional output (Ber-

tone et al., 2004; Birney et al., 2007; Cheng et al., 2005; Kapranov

et al., 2007). Discovery of RNA interference (RNAi) (Fire et al.,

1998) in C. elegans and the identification of a new class of small

RNAs known as microRNAs (Lee et al., 1993; Wightman et al.,

1993) led to a greater appreciation of RNA’s role in regulation

of gene expression. MicroRNAs are endogenously expressed

noncoding transcripts that silence gene expression by targeting

specific mRNAs on the basis of sequence recognition (Carthew

and Sontheimer, 2009). Over 1000 microRNA loci are estimated

to be functional in humans, modulating roughly 30% of protein-

coding genes (Berezikov and Plasterk, 2005).

While microRNAs represent a minority of the noncoding tran-

scriptome, the tangle of long and short noncoding transcripts is

much more intricate, and is likely to contain as yet unidentified

classes of molecules forming transcriptional regulatory networks

(Efroni et al., 2008; Kapranov et al., 2007). Long ncRNAs are tran-

scripts longer than 100 nts which in most cases mirror the

features of protein-coding genes without containing a functional

open reading frame (ORF). Long ncRNAs have been implicated

as principal players in imprinting and X-inactivation. The

imprinting phenomenon dictates the repression of a particular

allele, depending on its paternal or maternal origin. Many clus-

ters of imprinted genes contain ncRNAs, and some of them

have been implicated in the transcriptional silencing (Yang and

Kuroda, 2007). Similarly, the X chromosome inactivation relies

on the expression of a long ncRNA named Xist, which is thought

to recruit, in a cis-specific manner, protein complexes establish-

ing repressive epigenetic marks that encompass the chromo-

some (Heard and Disteche, 2006). There is also a report indi-

cating that a long ncRNA expressed from the HOXC locus may

affect the expression of genes in the HOXD locus which is located

on a different chromosome (Rinn et al., 2007). More recently, a set

of long ncRNAs has been identified in mouse, through the anal-

ysis of the chromatin signatures (Guttman et al., 2009). There

has also been reports of divergent transcription of short RNAs

flanking transcriptional start sites of the active promoters (Core

et al., 2008; Preker et al., 2008; Seila et al., 2008).

In search of a function for long ncRNAs, we used the

GENCODE annotation (Harrow et al., 2006) of the human

genome. To simplify our search we subtracted transcripts over-

lapping the protein-coding genes. Moreover, we filtered out the

transcripts that may correspond to promoters of protein-coding

genes and the transcripts that belong to known classes of

ncRNAs. We identified 3019 putative long ncRNAs that display

differential patterns of expression. Functional knockdown of

multiple ncRNAs revealed their positive influence on the neigh-

boring protein-coding genes. Furthermore, detailed functional

analysis of a long ncRNA adjacent to the Snai1 locus using

reporter assays demonstrated a role for this ncRNA in an RNA-

dependent potentiation of gene expression. Our studies suggest


a role for a class of long ncRNAs in positive regulation of protein-

coding genes.

RESULTS

Noncoding RNAs Are Expressed and Respond to CellularDifferentiating SignalsTo assign a function to uncharacterized human long ncRNAs, we

identified unique long noncoding transcripts using the annota-

tion of the human genome provided by the GENCODE (Harrow

et al., 2006) and performed by human and vertebrate analysis

and annotation (HAVANA) group at Sanger Institute. Such

genomic annotation is being produced in the framework of the

ENCODE project (Birney et al., 2007). At the time of our analysis,

the GENCODE annotation encompassed about one third of the

human genome. Such an annotation relies on the human expert

curation of all available experimental data on transcriptional

evidence, such as cloned cDNA sequences, spliced RNAs and

ESTs mapped on to the human genome.

We focused on ncRNAs that do not overlap the protein-coding

genes in order to simplify the interpretation of our functional anal-

ysis of ncRNAs. This included the subtraction of all transcripts

mapping to exons, introns and the antisense transcripts overlap-

ping the protein-coding genes. We also excluded transcripts

within 1 kb of the first and the last exons as to avoid promoter

and 30-associated transcripts (Fejes-Toth et al., 2009; Kapranov

et al., 2007), that display a complicated pattern of short tran-

scripts (Core et al., 2008; Preker et al., 2008; Seila et al., 2008).

Furthermore, we excluded all known noncoding transcripts

from our list of putative long ncRNAs. This analysis resulted in

3019 ncRNAs, which are annotated by HAVANA to have no

Fibroblasts976

HeLa937

Keratinocytes690

576

222

38

24

126

91

52

A

B

C

Gen

eID

cod

ing

po

ten

tial

AR LongncRNAs

Protein-codinggenes

0

100

200

D

Normalized phastCons score

Cum

ulat

ive fr

eque

ncy

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

0.0 0.2 0.4 0.6 0.8 1.0Normalized phastCons score

Cum

ulat

ive fr

eque

ncy

Protein-coding genes

long ncRNAs

AR

Protein-coding genes

long ncRNAs

AR

Transcripts

Promoters

Figure 1. Identification of Novel Long

ncRNAs in Human Annotated by GENCODE

(A) Analysis of coding potential using Gene ID for

ancestral repeats (AR), long ncRNAs annotated

by GENCODE and protein-coding genes.

(B) Conservation of the genomic transcript

sequences for AR, long ncRNAs, protein-coding

genes, and (C) of their promoters.

(D) Expression analysis of 3,019 long ncRNA in

human fibroblasts, HeLa cells and primary human

keratinocytes, showing numbers for transcripts

detected in each cell line and the overlaps

between cell lines. All microarray experiments

have been done in four replicates. See also

Figure S1 and Table S1 and Table S2.

coding potential, expressed from 2286

unique loci (some loci display multiple

alternative spliced transcripts) of the

human genome (Experimental Proce-

dures, Table S1 available online). The

average size of the noncoding transcripts

is about 800 nts with a range from 100 nts

to 9100 nts. Interestingly, the long

ncRNAs display a simpler transcription

unit than that of protein-coding genes

(Figure S1A). Nearly 50% of our long

ncRNAs contain a single intron in their primary transcript (Fig-

ure S1A). Moreover, analysis of their chromatin signatures indi-

cated similarities with protein-coding genes. Transcriptionally

active ncRNAs display histone H3K4 trimethylation at their

50-end (Figure S1B) and histone H3K36 trimethylation in the

body of the gene (Figure S1C).

Analysis of protein coding potential of the ncRNAs using

GeneID (Blanco et al., 2007; Parra et al., 2000) shows ncRNAs

coding potential comparable to that of ancestral repeats (Lunter

et al., 2006), supporting the HAVANA annotation of these tran-

scripts as noncoding (Figure 1A). Moreover, comparison of

ncRNAs with protein-coding genes and control sequences corre-

sponding to ancestral repeats (Lunter et al., 2006) reveals that

ncRNA sequence conservation is lower than that of protein-

codinggenes,buthigher than thatofancestral repeats (Figure1B).

A similar case is seen with the promoter regions (Figure 1C). These

results are in concordance with previous observations in the

mouse genome (Guttman et al., 2009; Ponting et al., 2009).

Next we used custom-made microarrays (Experimental

Procedures) which were designed to include an average of six

probes (nonrepetitive sequences) against each ncRNA transcript

to detect their expression. We analyzed the expression pattern

of ncRNAs using three different human cell lines (Figure 1D).

Overall, we detected 1167 ncRNAs expressed in at least one

of the three cell types and 576 transcripts common among the

three cell types (Figure 1D). We validated the expression of 16

ncRNAs that mapped to the 1% of the human genome investi-

gated by the original ENCODE study (Birney et al., 2007) using

quantitative polymerase chain reaction (qPCR) in three different

cell lines (Table S2). Furthermore, we could find evidence for

expression of 80% of our noncoding transcripts in at least one


human tissue in a recent high throughput sequencing of the

human transcriptome (Wang et al., 2008).

To assess whether ncRNAs respond to cellular differentiating

signals, we induced the differentiation of human primary kerati-

nocytes using 12-O-tetradecanoylphobol 13-acetate (TPA). We

monitored the expression of ncRNAs using custom microarrays.

Expression of protein-coding genes was monitored using

conventional Agilent arrays containing nearly all human mRNAs.

We prepared RNA from human primary keratinocytes before

and following treatment with TPA. As shown in Figure 2A and

Table S3, we could detect 687 ncRNAs in keratinocytes, where

104 (or 15.1%) respond to TPA treatment by over 1.5-fold. Simi-

larly, 21.3% of protein coding-genes display a change in expres-

sion of over 1.5-fold (Figure 2B). While around half of the

TPA-regulated protein-coding genes increase and a similar

proportion decrease their expression following differentiation,

70% of the TPA-regulated ncRNAs increase their expression

whereas only 30% show a decrease (Figures 2A and 2B). Further-

more, analysis of the protein-coding genes in the 500 kb window

surrounding the TPA-regulated ncRNAs indicates a significant

enrichment in genes involved in differentiation and morphogen-

esis (Figure 2C). An example of such change in expression of an

important gene involved in extra-cellular matrix is shown in

Figure 2D. Extracellular Matrix Protein 1 (ECM1) gene and an

ncRNA adjacent to it displayed a 5 and 1.7 fold induction following

TPA treatment, respectively. (Figure 2D, upper panel). qPCR anal-

ysis shows the TPA-mediated induction of ECM1 and the ncRNA

as 14 and 4 fold, respectively (Figure 2D, bottom panel). Taken

together, we found that many of the GENCODE annotated tran-

scripts are expressed in multiple cell lines and that they display

gene expression responsiveness to differentiation signals.

Noncoding RNAs Display a TranscriptionalActivator FunctionTo assess the function of our set of long ncRNAs, we reasoned

that similar to long ncRNAs function at the imprinting loci, our

collection of ncRNAs may act to regulate their neighboring

genes. To test this hypothesis, we used RNA interference to

deplete a set of ncRNAs. We initially chose ncRNAs that showed

a differential expression following keratinocyte differentiation.

However, to obtain a reproducible knockdown we had to use

cell lines that are permissive to transfection by siRNAs. We

used five different cell lines for our analyses in which the candi-

date ncRNAs display a detectable expression (Figure 3).

We validated the expression of our experimental set of

ncRNAs and the absence of protein-coding potential using rapid

amplification of 50 and 30 complementary DNA ends (50 and 30

RACE), PCR and in vitro translation (Figure S3). These experi-

ments confirmed the expression of ncRNAs and showed that

they do not yield a product in an in vitro translation assay (Figures

S3A and S3B), supporting the noncoding annotation of our set of

ncRNAs. In two cases, the ncRNAs adjacent to Snai2 and TAL1

loci, we found evidence of a longer ncRNA transcript than that

annotated by HAVANA (Figure S3).

We began by examining small interfering RNAs (siRNAs)

against the ncRNA next to ECM1 in order to assess its functional

role following its depletion (for reasons that will follow, this class

of RNA is designated as noncoding RNA-activating1 through 7,

ncRNA-a1-7). HEK293 cells were used for these experiments

because of the ease of functional knockdown and the detectable

amounts of ncRNA-a1 and ECM1 in this cell line. We compared

the results obtained using two siRNAs against ncRNA-a1 to data

obtained following the transfection of two control siRNAs (for the

visual simplicity only one siRNA is shown (Figure 3A), the values

for both siRNAs can be seen in Table S4). The two siRNAs

produced comparable results. We interrogated a 300 kb window

around the ncRNA-a1 containing six protein-coding genes using

qPCR.

Surprisingly, unlike the silencing action of long ncRNAs in

imprinting and X-inactivation, depletion of ncRNA-a1 adjacent

to ECM1 resulted in a concomitant decrease in expression of

the neighboring ECM1 gene (Figure 3A). This effect was specific,

as we did not detect any change in the other protein-coding

genes surrounding ncRNA-a1 (Figure 3A). To ascertain that

ncRNA-a1 is not a component of the ECM1 30 untranslated

region, we used primer pairs spanning the ECM1 and ncRNA-a1

genes. We were not able to detect a transcript comprised of the

two genes in HEK293 cells, supporting the contention that the

two transcripts are independent transcriptional units (Fig-

ure S2A). Furthermore, published ChIP experiments (Euskirchen

et al., 2007) show the presence of RNA polymerase II and tri-

methyl H3K4 peaks at the transcription start site of ncRNA-a1

in several cell lines, further attesting to an independent transcrip-

tional start site for ncRNA-a1. Moreover, knocking down the

ECM1 gene did not affect the expression level of ncRNA-a1 or

any of the other protein-coding genes analyzed in the locus,

further supporting the independence of ECM1 transcript from

that of ncRNA-a1 (Figure S2B).

Next we analyzed ncRNA-a2 flanking the histone demethylase

JARID1B/KDAM 5B which also shows increased expression

following keratinocyte differentiation. These experiments were

performed in HeLa cells as they showed detectable expression

of ncRNA-a2. Interestingly, while depletion of ncRNA-a2 did

not change JARID1B/KDAM 5B levels, the KLHL12, a gene

known for its negative regulation of the Wnt-beta catenin

pathway, on the opposite strand displayed a significant reduc-

tion (Figure 3B). Although the decrease in KLHL12 was small

(about 20%), no other protein-coding gene in the locus displayed

a difference in expression (Figure 3B).

To extend our findings and to determine whether regulation of

neighboring protein-coding genes is a common function of

ncRNAs, we interrogated the ncRNA-a3 flanking the stem cell

leukemia gene (SCL, also called TAL1). TAL1 is a basic helix-

loop-helix protein which serves as the master regulator of hema-

topoiesis (Lecuyer and Hoang, 2004). This locus contains two

ncRNAs on different strands of DNA. We used MCF-7 cells to

assess the depletion of ncRNA-a3, since the expression of

ncRNA-a3 and TAL1 could be readily detected in these cells.

However, neither PDZK1IP1 nor ncRNA-a4 could be detected

by qPCR in MCF-7 cells. Depletion of ncRNA-a3 resulted in

a specific and potent reduction of TAL1 expression (Figure 3C).

While depletion of ncRNA-a3 did not affect either STIL or CMPK1

genes, a significant reduction in CYP4A11 gene on the opposite

strand of the DNA was detected (Figure 3C).

We next turned our attention to ncRNA-a4 which was not ex-

pressed at a detectable level in MCF7 cells. We could reliably


detect ncRNA-a4 in Jurkat cells. While we could not efficiently

knockdown ncRNA-a3 in Jurkat cells, siRNAs specific to

ncRNA-a4 reproducibly reduced its levels by about 50%

(Figure 3D). Importantly, reduced levels of ncRNA-a4 resulted

in a consistent and significant decrease in the level of the gene

CMPK1 which is over 150 kb downstream of ncRNA-a4

TARS2

ECM1

ncRNA-a

1

ADAMTSL4

MCL1

ENSA

A

C

19275

687

104

4107

15.1%

21.3%

0

20

40

60

80

100

120

0

1000

2000

3000

4000

5000

52.3%

47.7%

56.5%43.5%

70.2%

29.8 %

66.7%

33.3%

> ±1.5 > ±2

Long ncRNAs

mRNA

Nu

mb

er o

f tra

nsc

rip

tsN

um

ber

of t

ran

scri

pts

> ±1.5 > ±2

Long ncRNAs

mRNA

B

0 5 10 15 20 25 30 35 40

cell differentiation

epidermal cell differentiation

keratinization

keratinocyte differentation

ectoderm development

endoderm development

epidermis morphgenesis

tissue morphogenesis

tissue development

Number of genes

Array quantification

qPCR quantification

0

5

0

5

10

15Control

+ TPA

Repressed

Induced

Repressed

Induced

D

Protein-coding genes arounddifferentiallyexpressed long ncRNAs

Protein-coding genes aroundrandom positions

Figure 2. Long ncRNAs Display Responsiveness to Differentiation Signals in Human Primary Keratinocytes

(A and B) Distribution of differentially expressed transcripts (dark colors) following TPA treatment for long ncRNAs (A), and mRNAs (B). Lighter colors show total

number of transcripts, darker colors and percentage show number of differentially expressed transcripts. Bar-plots show number and fractions of transcripts

induced (red) or repressed (green) at different fold-change cut-offs.

(C) Gene onthology analysis of genes flanking the differentially expressed long ncRNAs (red) compared to genes flanking random positions (black).

(D) Graphic representation of a locus with induction of the long ncRNA ncRNA-a1 and the adjacent ECM1 gene, with expression values from microarrays (upper

panel) and qPCR quantification of transcripts (lower panel). Microarray experiments and qPCR validation are done in four replicates. Data shown are mean ± SD.

See also Figure S2 and Table S3.


(Figure 3D). We do not detect any changes in the other protein-

coding genes surrounding ncRNA-a4. Next we depleted

ncRNA-a5 which is adjacent to the E2F6 gene, an important

component of a polycomb-like complex (Ogawa et al., 2002).

Knockdown of ncRNA-a5 did not affect the E2F6 gene.

However, depletion of ncRNA-a5 resulted in a specific reduction

in ROCK2 expression levels in HeLa cells, which is located

upstream of ncRNA-a5 (Figure 3E).

Finally, we examined the Snai1 and Snai2 loci in A549 cells

(Figure 3F and Figure 4). The Snail family of transcription factors

are implicated in the differentiation of epithelia cells into mesen-

chymal cells (epithelial-mesenchymal transition) during embry-

onic development (Barrallo-Gimeno and Nieto, 2005; Savagner,

2001). Snai2 shows a significant reduction in expression when

the adjacent ncRNA-a6 is depleted, an effect that is not seen

on EFCAB1, the only other protein-coding gene within 300 kb

of the ncRNA-a6 (Figure 3F). In total, we have examined 12 loci

where we were able to efficiently knockdown the ncRNAs using

siRNAs (Table S5). We were able to show that in 7 cases, the

ncRNA acts to potentiate the expression of a protein-coding

gene within 300 kb of the ncRNA. It is possible that the remaining

ncRNAs which did not display a positive effect on the neigh-

boring genes within the 300 kb window, exert their action over

longer distances which was not assessed in our analysis. Taken

100 kb

JARID

1B

ncRNA-a

2

LOC641515

AX711218

NR_002929

RABIF

KLHL12

ADIPOR1

CYP4A11

ncRNA-a

3

ncRNA-a

4

PDZK1IP1

TAL1

STILCM

PK1

RPRD2

TARS2

ECM1ncR

NA-a1

ADAMTSL4

MCL1

ENSA

***

PQLC3

ROCK2

ncRNA-a

5

E2F6

N.D. ****

Snai2EFCAB1

ncRNA-a

6

*** **N.D.N.D.

CYP4A11

ncRNA-a

3

ncRNA-a

4

PDZK1IP1

TAL1

STILCM

PK1

A

B

C

D

E

F

*

* *

control siRNAncRNA-a1 siRNA






****

OTTHUMT00

0000324050

HEK293

HeLa

MCF-7

Jurkat

HeLa

A549

Figure 3. Stimulation of Gene Expression by Activating RNAs

The thick black line representing each gene shows the span of the genomic region including exons and introns. The targeted activating RNAs are shown in red.

Bar-plots show RNA levels as determined by qPCR.

(A) ncRNA-a1 locus in HEK293 cells.

(B) ncRNA-a2 locus in HeLa cells.

(C) ncRNA-a3 locus in MCF-7 cells.

(D) ncRNA-a4 locus in Jurkat cells.

(E) ncRNA-a5 locus in HeLa cells.

(F) ncRNA-a6 locus in A549 cells. All values are relative to GAPDH expression and relative to control siRNA transfected cells set to an average value of 1. The scale

bar represents 100 kb and applies to all figure panels. Error bars show mean ± SEM of at least three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001

by two-tailed Student’s t test. See also Figure S3 and Table S4. The results represent at least six independent experiments. See also Figure S3 and Table S4.


together, our results indicate that a subset of ncRNAs has acti-

vating functions and therefore we have named them ncRNA-

activator (ncRNA-a) followed by a number to distinguish each

activating long ncRNA.

ncRNA-a7 Is a Regulator of Snai1As mentioned above, Snai1 is a member of the Snail zinc-finger

family, which comprises transcription factors with diverse func-

tions in development and disease (Barrallo-Gimeno and Nieto,

2005; Nieto, 2002). The Snail gene family is conserved among

species from Drosophila to human and has been shown to func-

tion as mesodermal determinant genes (Barrallo-Gimeno and

Nieto, 2005; Nieto, 2002). Snail genes are the regulators of cell

adhesion, migration and epithelial-mesenchymal transition

(EMT) (Barrallo-Gimeno and Nieto, 2005; Nieto, 2002). Analysis

of the ncRNA close to the Snai1 gene provided us with an oppor-

tunity to combine our gene expression analysis with analysis of

changes in cellular migration. Knockdown of ncRNA-a7 resulted

Snai1ncR

NA-a7

UBE2VI

TMEM189

CEBPB

RNF114

100 kb

0

0.5

1.0

A

Con

trol s

iRN

A

ncR

NA

-a7

siR

NA

B

C

** **

control siRNA

ncRNA-a7 siRNA

A549

Sna

i1 s

iRN

A

Num

ber o

f cel

ls m

igra

ted

Control si

RNA

Snai1 siRNA

ncRNA-a7 siR

NA

5000

4000

3000

2000

1000 ******

0

Figure 4. Knockdown of ncRNA-a7 Specifi-

cally Targets Snai1 Expression

(A) As in Figure 3, the ncRNA-a7 locus is depicted

showing effects on RNA levels for the surrounding

genes with and without knockdown of ncRNA-a7.

The results represent mean ± SEM of at least six

independent experiments. **p < 0.01 by one-tailed

Student’s t test.

(B) Migration assay of A549 cells with control (right

panel) or ncRNA-a7 (left panel) siRNA transfec-

tions.

(C) Quantification of the data shown in (B).

Experiments in (B) and (C) are done in three repli-

cates and are shown as mean ± SEM. ***p <

0.001 by two-tailed Student’s t test. See also

Figure S4 and Table S5.

in a specific reduction in Snai1 levels (Fig-

ure 4A). The expression of the four other

protein-coding genes in this locus does

not change following the depletion of

ncRNA-a7. Concomitantly, knockdown

of ncRNA-a7 has a significant phenotypic

effect in cell migration assays, reducing

the number of migrating cells to about

10% of that of the control (Figures 4B

and 4C), consistent with the phenotypic

changes following the depletion of Snai1

(Figures 4B and 4C).

Since the knockdown of ncRNA-a7 or

Snai1 had similar consequences on

cellular migration, we assessed their

depletion on gene expression in A549

cells using Agilent arrays. We could not

detect the basal level of Snai1 on the

array, while Snai1 was readily detectable

using quantitative PCR. Interestingly,

depletion of Snai1 or ncRNA-a7 resulted

in similar changes in gene expression

profiles (Figure 5A and Table S6). Not

only did we observe a similar trend in

genes that were affected upon the knockdown of either gene

but also a significant number of genes that were upregulated

were in common in both treatments (Figures 5A and 5B). Since

Snai1 is a known transcriptional repressor, depletion of Snai1

or ncRNA-a7 should result in an upregulation of Snai1 target

genes. Indeed, a number of genes that were commonly upregu-

lated were direct targets of Snai1 (Figure 5C, upper panel) (De

Craene et al., 2005). Depletion of either ncRNA-a7 or Snai1

also resulted in downregulation of a set of genes with a partial

overlap between the genes downregulated following the two

treatments (Figure 5B). Interestingly, Aurora-kinase A a gene

that is 6 MB down-stream of ncRNA-a7 was specifically downre-

gulated following the depletion of ncRNA-a7, suggesting a long

range effect for ncRNA-a7 (Figure 5C). Taken together, these

results indicate that while the depletion of ncRNA-a7 partially

mimic the gene expression profile observed following Snai1

depletion, there are a number of gene expression changes

resulting from the ncRNA-a7 depletion that occur independently


of changes in Snai1. Therefore, it is likely that depletion of

ncRNA-a7 may have other effects on gene expression which

may be mediated through other targets in trans.

To specifically address whether ncRNA-a7 may exert its

effects in trans, we assessed the gene expression changes in

Snai1 locus as well as some of the targets that were changed

by depletion of ncRNA-a7 or Snai1 following the overexpression

of ncRNA-a7 (Figure 5D). Overall, we did not observe changes in

gene expression for any of the ncRNA-a7 targets following its

overexpression (Figure 5D, ncRNA-a7 was overexpressed 150

fold). While these results suggest that ncRNA-a7 exerts its local

gene expression changes in cis, it is likely that other targets may

be influenced in trans. Taken together, these experiments reveal

a role for ncRNA-a in positive regulation of expression of neigh-

boring protein-coding genes and show that this effect is not

specific to any one locus and may represent a general function

for ncRNAs in mammalian cells.

ncRNA Activation of Gene Expression of a HeterologousReporterPrevious studies have shown that distal activating sequences/

enhancers can stimulate transcription when placed adjacent

to a heterologous promoter, a methodology widely used to vali-

date potential enhancers (Banerji et al., 1983, 1981; Gillies

et al., 1983; Heintzman et al., 2009; Kong et al., 1997). To func-

135

Snai

1 si

RNA

ncRN

A-a

7 si

RNA

Snai

1 si

RNA

ncRN

A-a

7 si

RNA

Expression > 1.5 fold

42

Expression < 0.6

124 206

168 112

Cont

rol s

iRN

A

Snai

1 si

RNA

ncRN

A-a

7 si

RNA

-2 +2

Log

A B C

D

2

0

1

0

1

0

1

0

1

Snai1 ncRNA-a7 RNF114 AURKA

ControlncRNA-a7

Control siRNASnai1 siRNAncRNA-a7 siRNA

Rela

tive/

Gap

dh

0

1

2

3

4

0

1

2

3

4

0

1

2

3

4

CDH1 PKP2 PLOD2

Rela

tive/

Gap

dh

Diff

eren

tially

exp

ress

ed in

Sna

i1 o

r ncR

NA

-a7

knoc

k-do

wn

Snai1ncR

NA-a7

UBE2VI

TMEM189

CEBPB

RNF114

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

0

0.5

1.0

1.5

2.0

AURKA CDH1 PKP2 PLOD2

200

100150

500

Figure 5. Microarray Analysis of Snai1 and

ncRNA-a7 Knockdown

Snai1 or ncRNA-a7 were knocked down using

siRNA in A549 cells and the isolated RNA analyzed

on microarrays in duplicate experiments.

(A) All genes differentially expressed (>1.5-fold or

<0.6-fold compared to control) in either Snai1 or

ncRNA-a7 knockdown, or both, are shown clus-

tered in a heat map according to expression

profile. Numbers are log(2) transformed and color

scale is shown below the heat map.

(B) Analysis of genes showing upregulation (>1.5

fold) or downregulation (<0.6 fold) in both Snai1

and ncRNA-a7 knockdown. Numbers represent

number of genes regulated in the indicated

condition.

(C and D) (C) Validation of microarray data by

qPCR and (D) analysis of the Snai1 locus

and targets of Snai1 upon overexpression of

ncRNA-a7. ncRNA-a7 was overexpressed from

a vector in A549 cells and expression of select

genes were measured by qPCR. Y-axes show

expression value relative to GAPDH of the indi-

cated gene. Values are normalized to those of

control siRNA transfected cells, set to 1. **p < 0.01,

***p < 0.001 by one-tailed Student’s t test. See also

Table S6.

tionally dissect the influence of the

ncRNA activation on the expression of

an adjacent gene, we constructed

vectors with inserts containing either

ncRNA-a3 and -a4 from a bidirectional

promoter, ncRNA-a5 or ncRNA-a7, and placed them down-

stream of Firefly luciferase driven by a thymidine kinase (TK)

promoter in a reporter vector (pGL3-TK-ncRNA-a), (Figure 6A).

We included 1–1.5 kb upstream of the ncRNA-as to contain

their endogenous promoters and 500 bps downstream in the

reporter vector. We also produced a control vector (pGL3-

TK-control) in which 4 kb of DNA without transcriptional poten-

tial was cloned down-stream of Firefly luciferase similar to the

ncRNA activation reporters (Figure 6B). A vector containing Re-

nilla luciferase was used to control for transfection efficiency.

Importantly, inclusion of either of the three ncRNA-a inserts

result in an enhancement of transcription ranging from 2- to

7-fold (Figures 6C–6E). This effect is specific as pGL3-TK-

control vector do not enhance the basal TK promoter activity

(Figures 6C–6E). To demonstrate that the observed potentiation

of gene expression is mediated through the action of ncRNA-a,

we knocked down the ncRNA-a in question for each reporter

construct using specific siRNAs (Figures 6C–6E). Interestingly

while depletion of ncRNA-a7 and ncRNA-a5 completely abol-

ished the increased transcription, depletion of ncRNA-a3

and/or ncRNA-a4 resulted in a partial decrease in transcrip-

tional enhancement (Figures 6C–6E). These results suggest

that while ncRNA-a play a major role in transcriptional activa-

tion, other DNA elements in the cloned ncRNAa-3/4 region

may also contribute to increased transcription.


Dissection of the ncRNA-a7 in a Reporter ConstructAn important property of enhancing sequences is their orienta-

tion independence (Imperiale and Nevins, 1984; Khoury and

Gruss, 1983; Kong et al., 1997). We designed reporter constructs

(Figure 7A) in which the ncRNA-a7 sequence is reversed (pGL3-

TK-ncRNA-a7-RV) in order to assess its orientation indepen-

dence. The ncRNA-a7-RV construct displayed a similar tran-

scriptional enhancing activity as the construct containing the

A

pGL3-TK-ncRNA-a reporter

B

C

ncRNA insert

TK promoter Firefly luciferase SV40p(A)

1 20 3FL/RL

(normalized units)

pGL3-TK-ncRNA-a7

pGL3-TK-control

pGL3-TK

pGL3-TK-ncRNA-a7

pGL3-TK-control

pGL3-TK

ControlsiRNA

ncRNA-a7siRNA

****

D

pGL3-TKNo insert

FL/RL(normalized units)

ncRNA-a3siRNA

ncRNA-a4siRNA

ControlsiRNA

******

0 8

pGL3-TK

pGL3-TK-Control

pGL3-TK-ncRNA-a3/4

pGL3-TK

pGL3-TK-Control

pGL3-TK-ncRNA-a3/4

pGL3-TK

pGL3-TK-Control

pGL3-TK-ncRNA-a3/4

pGL3-TK-ncRNA-a3/4 siRNA ncRNA-a3 and ncRNA-a4

2 4 6

pGL3-TK-Control

4 kb insert with no known transcription

pGL3-TK-ncRNA-a3/4

ncRNA-a3 ncRNA-a4

2.7 kb insert including ncRNA-a3 and ncRNA-a4

4 kb insert including ncRNA-a5

ncRNA-a5

pGL3-TK-ncRNA-a5

ncRNA-a72.7 kb insert including ncRNA-a7

pGL3-TK-ncRNA-a7

E


ncRNA-a5siRNA

ControlsiRNA

*

0 2

pGL3-TK

pGL3-TK-Control

pGL3-TK-ncRNA-a5

pGL3-TK

pGL3-TK-Control

pGL3-TK-ncRNA-a5

1

*

Figure 6. ncRNA-Activators Potentiate Transcription of a Reporter Gene(A) ncRNA-a 3/4, 5 and 7 were cloned and inserted downstream of luciferase driven by a TK-promoter in a reporter plasmid as shown.

(B) Graphical representation of the inserts in the various vectors used. The pGL3-TK-Control vector contains an insert of approximately 4 kb containing no anno-

tated evidence of transcription. The depicted inserts show exons and transcriptional direction of the ncRNA-a.

(C–E) Luciferase reporter assays. The Firefly luciferase vectors were cotransfected with a Renilla luciferase vector (pRL-TK) for transfection control. (C) The vector

containing ncRNA-a3 and ncRNA-a4 from a bidirectional promoter, with control siRNA or siRNAs toward either of the two ncRNA-a, or both. (D) Reporter with

ncRNA-5, and (E) the reporter with the ncRNA-a7 inserted downstream of luciferase. X axes show relative Firefly (FL) to Renilla (RL) luciferase activity. Cotrans-

fected siRNAs are indicated to the right of the bars. All data shown are mean ± SE from six independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001 by one-

tailed Student’s t test.


ncRNA-a7 insert

TK promoter Firefly luciferase SV40p(A)

Exon 2 Exon 1

B

A

C

E

D

pGL3-TK-ncRNA-a7

F


0 1 2 3

pGL3-TK-ncRNA-a7

pGL3-TK-control

pGL3-TK

pGL3-TK-ID1

pGL3-TK-GTSF1L

****** ***

No insert

ORF

ORF


pGL3-TK

pGL3-TK-ncRNA-a7

pGL3-TK-delta(ncRNA-a7)

pGL3-TK-ncRNA-a7-p(A)

0 1 2 3 4

****** ***

No insert

SV40 p(A)

pGL3-TK

pGL3-TK-ncR

NA-a7

pGL3-TK-ncR

NA-a7 + ncRNA-a7 siR

NA

pGL3-TK-ncR

NA-a7-p(A

)

PCR

ncRNA-a7

pGL3-TK-ncRNA-a7

pGL3-TK-ncRNA-a7-RV

pGL3-TK-control

pGL3-TK

0 1 2 3 4FL/RL

(normalized units)*** ***

No insert

200 10FL/RL

(arbitrary units)

pGL3-Basic-ncRNA-a7

pGL3-Basic-ncRNA-a7-RV

pGL3-Basic

pGL3-TK

No prom

oter

Figure 7. RNA-Dependent Activation of a Reporter

Gene by ncNRA-a7

(A) Properties of the ncRNA-a7 containing luciferase

reporter vector. (B, C, E, and F) Luciferase reporter assays.

The Firefly luciferase vectors were cotransfected with

a Renilla luciferase vector (pRL-TK) for transfection

control. (D) Semiquantitative PCR of ncRNA-a7. (B)

Reporter experiments with the ncRNA-a7 insert reversed

as indicated in the left panel. (C) The TK-promoter driving

luciferase expression was deleted from the construct and

expression values are shown relative to the pGL3-TK

control plasmid as a reference. (E) Truncated reporter

constructs containing the ncRNA-a7 promoter and down-

stream sequences, but not the ncRNA-a7 sequence

[pGL3-TK-delta(ncRNA-a7)], or one with a poly(A) signal

in the beginning of the ncRNA-a7 to induce premature pol-

yadenylation [pGL3-TK-ncRNA-a7-p(A)]. See also (D) for

analysis of expression from these plasmids. (F) Protein

coding sequences were inserted in place of ncRNA-a7

downstream of the ncRNA-a7 promoter. Full-length

GTSF1L or ID1 sequences are used. X axes show relative

Firefly (FL) to Renilla (RL) luciferase activity. All data shown

are mean ± SE from six independent experiments. ***p <

0.001 by one-tailed Student’s t test.


ncRNA-a7 insert in its endogenous orientation with respect to

the regulated gene (Figure 7B).

To show that luciferase expression requires a promoter and

that ncRNA-7a cannot act as a proximal promoter, we deleted

the TK promoter from the reporter vectors. As shown in

Figure 7C, ncRNA-a7 cannot drive transcription of the Firefly

luciferase in the absence of a proximal TK promoter. These

experiments demonstrate that sequences corresponding to

ncRNA-a7 transcription unit can function to activate expression

of a heterologous promoter in an orientation-independent

manner, but cannot act as a promoter itself.

To further verify that ncRNA-a7 is the active component of the

transcriptional enhancement, we constructed two reporters in

which ncRNA-a7 sequences are either deleted or shortened by

placing a strong polyadenylation signal within the ncRNA-

a genomic sequence but close to the transcriptional start site,

to induce premature polyadenylation (Figures 7D and 7E). Both

modifications result in loss of the increased gene expression

(Figure 7E) compared to constructs where ncRNA-a7 is ex-

pressed. Finally, to assess whether the RNA corresponding to

ncRNA-7a is critical for increased gene expression, we devel-

oped constructs where DNA sequences corresponding to two

different protein-coding genes were positioned in the place of

ncRNA-a7 (Figure 7F), keeping the endogenous ncRNA-a7

promoter. Neither of these constructs displayed an increased

gene expression compared to that of the control constructs

(Figure 7F). Taken together, these experiments demonstrate

that the potentiation of gene expression is signaled by the

ncRNA-a and is not merely the result of the transcription of the

ncRNA.

DISCUSSION

We used the annotation of the human genome performed by

GENCODE to arrive at a collection of long ncRNAs that are ex-

pressed from loci independent of those of protein-coding genes

or previously described nc RNAs. GENCODE annotation encom-

passes both protein-coding and noncoding transcripts and relies

on experimental data obtained through the analysis of cDNAs,

ESTs and spliced RNAs. Our collection of �3,000 transcripts

correspond to the manual curation of about a 1/3 of the human

genome. Analysis of the GENCODE data indicates that nearly

all of their noncoding annotated transcripts are spliced

(Figure S1A).

Importantly, the median distance of an ncRNA transcript to

a protein-coding gene is over a 100 kb making it an unlikely

scenario for the ncRNA to be an extension of protein-coding

transcripts (Figures S2C and S2D). Moreover, transcriptionally

active ncRNAs display similar chromatin modifications seen

with expressed protein-coding genes (Figures S1B and S1C).

Furthermore, the analyzed ncRNAs display RNA pol(II), p300

and CBP occupancy at levels similar to those of the surrounding

protein coding genes, consistent with their transcriptional inde-

pendence (Figure S4). Although our analysis is focused on

understanding the function of a set of ncRNAs annotated by

GENCODE, the human transcriptome includes other forms of

ncRNAs with important regulatory functions that have not been

included in our study. These include the antisense transcripts

arising from protein-coding genes, precursors of microRNAs

as well as a wealth of unspliced transcripts described in multiple

studies (Guttman et al., 2009; Kapranov et al., 2007; Rinn et al.,

2007).

Taken together, the novelty of our work lies in the following.

First, we show that at multiple loci of the human genome deple-

tion of a long ncRNA leads to a specific decrease in the expres-

sion of neighboring protein-coding genes. Previous studies

analyzing the function of long ncRNAs in X-inactivation or the

imprinting phenomenon point to their role in silencing of gene

expression (Mattick, 2009). Second, we show that the enhance-

ment of gene expression by ncRNAs is not cell specific as we

observe the effect in five different cell lines. Third, this enhance-

ment of gene expression is mediated through RNA, as depletion

of such activating ncRNAs abrogate increased transcription of

the neighboring genes. Fourth, through the use of heterologous

reporter assays, we suggest that activating ncRNAs mediate

this RNA-dependent transcriptional responsiveness in cis. Fifth,

we show that similar to classically defined distal activating

sequences, ncRNA-mediated activation of gene expression is

orientation independent. Sixth, we present evidence that similar

to defined activating sequences, ncRNAs cannot drive transcrip-

tion in the absence of a proximal promoter. Finally, we demon-

strate that the activation of gene expression in the heterologous

reporter system is mediated through RNA as multiple

approaches depleting the RNA levels lead to abrogation of the

stimulatory response. Therefore, we have uncovered a new bio-

logical function in positive regulation of gene expression for

a class of ncRNAs in human cells.

There are previous reports of individual ncRNAs having a posi-

tive effect on gene expression. The �3.8 kb Evf-2 ncRNA was

shown to form a complex with the homeodomain-containing

protein Dlx2 and lead to transcriptional enhancement (Feng

et al., 2006). Similarly, the ncRNA HSR1 (heat-shock RNA-1)

forms a complex with HSF1 (heat-shock transcription factor 1),

resulting in induction of heat-shock proteins during the cellular

heat-shock response (Shamovsky et al., 2006) and an isoform

of ncRNA SRA (steroid receptor RNA activator) functions to coac-

tivate steroid receptor responsiveness (Lanz et al., 1999). Our

findings that activating ncRNAs positively regulate gene expres-

sion extend these previous studies and demonstrate that the acti-

vation of gene expression by long ncRNA may be a general func-

tion of a class of long ncRNAs. Moreover, whether ncRNA effects

seen in our study are mediated through association with specific

transcriptional activators is not known. However, this is a likely

scenario given previous examples of an RNA-mediated respon-

siveness. Other possibilities include a formation of an RNA-DNA

hybrid at the locus of the ncRNA or the protein-coding gene which

may result in enhanced binding of the sequence specific DNA

binding proteins or chromatin modifying complexes.

A recent study uncovers a set of bidirectional transcripts

(termed eRNA) that are derived from sites in the human genome

that show occupancy by CBP, RNA polymerase II and are deco-

rated by monomethyl Histone H3 lysine 4 (H3K4) (Kim et al.,

2010). Moreover, they show that the expression of such tran-

scripts is correlated with their nearest protein-coding genes.

There are fundamental differences between their collection of

�2000 transcripts and our GENCODE set of transcripts. First,


while all their eRNAs are bidirectional, only about 1% of our

ncRNAs show evidence of bidirectionality (see the example

shown in the TAL1 locus). Second, our analysis of the histone

modifications of a subset of ncRNAs that are expressed in lymph

(Barski et al., 2007) indicates the presence of H3K4 trimethyla-

tion at the transcriptional start sites and H3K36 trimethylation

at the body of the gene (Figures S1B and S1C). This is in stark

contrast to eRNA loci where there is an absence of H3K4 tri-

methyl marks and the predominant chromatin signature is the

monomethyl H3K4. Third, eRNAs are reported to be predomi-

nantly not polyadenylated. The majority of our collection of

ncRNAs show evidence of polyadenylation as they were ampli-

fied using oligo-dT-primed reactions and furthermore 41%

display the presence of a canonical polyadenylation site. Anal-

ysis of the protein-coding transcripts revealed that a similar

proportion (52%) to that of our ncRNAs contain the canonical

polyadenylation sites. Finally, while we show that a set of our

ncRNAs function to enhance gene expression, there is no

evidence provided for eRNAs exerting a biological function. While

we believe that eRNAs designate a different class of ncRNAs than

ncRNA-a described in our study, it is temping to speculate that

many of the ncRNA-a and their promoters may correspond to

mammalian enhancers or polycomb/trithorax response elements

(PRE/TREs). In such a scenario, binding of polycomb or trithorax

proteins to proximal promoters of ncRNA-a will regulate the

expression of ncRNA-a which in turn impact the expression of

the protein-coding gene at the distance.

Another set of recently published ncRNAs were termed long

intervening noncoding RNA or lincRNAs (Guttman et al., 2009).

The comparison of our ncRNAs and the lincRNAs show that

about 13% of the ncRNAs defined by ENCODE overlap the

broad regions encoding a set of recently identified human

lincRNAs (Khalil et al., 2009). The overlap between our ncRNAs

and lincRNAs are even smaller (�4%) if one considers only the

exons corresponding to lincRNAs. Importantly, the studies with

lincRNAs did not reveal any transcriptional effects in neighboring

genes (Khalil et al., 2009). Therefore, it is likely that lincRNAs

describe a distinct set of ncRNAs compared to those annotated

by GENCODE. Similar to the diverse functions for proteins,

ncRNAs such as lincRNAs may play other roles in regulating

gene expression.

The GENCODE annotation used in this study encompasses

only a third of the human genome. Therefore, the number of

ncRNAs in human cells is likely to grow and may equal or even

surpass the number of protein-coding genes. Our considerations

for selection of ncRNAs excluded all ncRNAs associated with

protein-coding genes and their promoters, as well as known

ncRNAs. Therefore, the repertoire of the noncoding transcripts

in human cells contains many more transcripts than those cata-

loged in this study. Specifically, there have been reports of

pervasive amount of antisense transcription as well as transcrip-

tion mapping to promoter regions of protein-coding genes (Core

et al., 2008; Denoeud et al., 2007; Kapranov et al., 2007; Preker

et al., 2008; Seila et al., 2008). Whether such transcripts will have

biological functions similar to those described for activating

ncRNAs in our study is not known. However, it is clear that future

genome-wide genetic analysis of ncRNAs in mammalian cells

will begin to shed light on different classes of the ncRNAs.

The precise mechanism by which our ncRNAs function to

enhance gene expression is not known. We envision a mecha-

nism by which ncRNAs by virtue of sequence or structural

homology targets the neighboring protein-coding genes to bring

about increased expression. Our experimental evidence using

a heterologous promoter point to the mechanism of action for

activating ncRNAs operating in cis. However, genome-wide

analysis following depletion of ncRNA-a7 suggested changes

in gene expression that may not be related to the action of

ncRNA-a7 on its local environment and may be a result of wider

trans-mediated effects of ncRNA-a7. Such regulatory functions

of ncRNAs could be achieved through an RNA-mediated recruit-

ment of a transcriptional activator, displacement of a transcrip-

tional repressor, recruitment of a basal transcription factor or

a chromatin-remodeling factor. While we favor a transcriptional

based mechanism for ncRNA activation, effects on RNA stability

cannot be excluded. Taken together, the next few years will bring

about new prospects for the long ncRNAs as central players in

gene expression.


Extracting Long ncRNA Data

The HAVANA annotation has been downloaded using the DAS server provided

by the Sanger institute (version July,16th 2008). We removed all annotated

biotypes or functional elements belonging to specific categories such as pseu-

dogenes or protein-coding genes. We excluded all transcripts overlapping

with known protein coding loci annotated by HAVANA, RefSeq or UCSC. Tran-

scripts falling into a 1 kb window of any protein-coding gene were also

removed. Finally, we excluded all transcripts covered by known noncoding

RNAs such as miRNAs (miRbase version 11.0 April 2008).

To estimate the evolutionary constraints among mammalian sequences we

constructed the cumulative distribution of PhastCons scores for ancestral

repeats (ARs), RefSeq genes and long ncRNAs. The cumulative distributions

of these transcripts or repeats are plotted using a log-scale on the y axis.

Cell Culture and siRNA Transfections

Human primary keratinocytes from four different biological donors were grown

in Keratinocyte medium (KFSM, Invitrogen). Differentiation was induced by

2.5 ng/ml 12-O-tetradecanoylphorbol-13-acetate (TPA) during 48 hr.

HEK293, A549, HeLa, and MCF-7 cells were cultured in complete DMEM

media (GIBCO) containing 10% FBS, and 13 Anti/Anti (GIBCO). Jurkat cells

were cultured in complete RPMI media (GIBCO) containing 10% FBS and

13 Anti/Anti (GIBCO). Migration assays were performed as previously

described(Gumireddy et al., 2009).

For transfections of 293, HeLa, A549, and MCF-7 cells we used Lipofect-

amine 2000 (Invitrogen) according to the manufacturer’s recommendations

and an siRNA concentration of 50 nM. Jurkat cells were transfected using

HiPerFect (QIAGEN) according to the manufacturer’s recommendations and

an siRNA concentration of 100 nM.

RNA Purification, cDNA Synthesis, and Quantitative PCR

Cells were harvested and resuspended in TRIzol (Invitrogen) and RNA ex-

tracted according to the manufacturer’s protocol. cDNA synthesis was done

using MultiScribe reverse transcriptase and random primers from Applied Bio-

systems. Quantitative PCR was done using SybrGreen reaction mix (Applied

Biosystems) and an HT7900 sequence detection system (Applied Biosys-

tems). For all quantitative PCR reactions Gapdh was measured for an internal

control and used to normalize the data.

Cloning of pGL3-TK Reporters and Luciferase Assay

pGL3-Basic was digested with BglII and HindIII and the TK promoter from

pRL-TK was inserted into these sites. Inserts were amplified from genomic


DNA and cloned into the BamHI and SalI sites 50 to the luciferase gene. Lucif-

erase assays were performed in 96-well white plates using Dual-Glo (Promega)

according to the manufacturer’s protocol.

Microarrays

Custom-made microarrays (Agilent) were designed based on the library of

3019 long ncRNA sequences, with on average six probes targeting each tran-

script. Human whole genome mRNA arrays were from Agilent (G4112F). Total

RNA samples were converted to cDNA using oligo-dT primers. Labeling of the

cDNA and hybridization to the microarrays were performed according to Agi-

lent standard dye swap protocols. Data analysis was done using the AFM 4.0

software. All microarrays were done in four biological replicates.


Supplemental Information includes Extended Experimental Procedures, four

figures, and six tables and can be found with this article online at doi:10.

1016/j.cell.2010.09.001.

ACKNOWLEDGMENTS

Thanks to the HAVANA team for use of their genome annotation. We also thank

the CRG Genomic Facility and the Functional Genomics Core Facility at Wistar

and UPenn for expertise in microarray analysis. We thank Dr. Ken Zaret for

helpful discussions. U.A.O. is supported by a grant from the Danish Research

Council; M.B. is supported by an HFSPO fellowship; A.G. was supported by

a fellowship from the American Italian Cancer Foundation; R.G. was supported

through Spanish ministry, GENCODE U54 HG004555-01, and NIH; and R.S.

was supported by a grant from NIH, GM 079091.


Revised: July 1, 2010



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Molecular Basis of RNA Polymerase IIITranscription Repression by Maf1Alessandro Vannini,1,3 Rieke Ringel,1,3 Anselm G. Kusser,1,3 Otto Berninghausen,1 George A. Kassavetis,2

and Patrick Cramer1,*1Gene Center and Department of Biochemistry, Center for Integrated Protein Science Munich (CIPSM), Ludwig-Maximilians-Universitat

Munchen, Feodor-Lynen-Strasse 25, 81377 Munich, Germany2Division of Biological Sciences, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0634, USA3These authors contributed equally to this work


DOI 10.1016/j.cell.2010.09.002

SUMMARY

RNA polymerase III (Pol III) transcribes short RNAsrequired for cell growth. Under stress conditions,the conserved protein Maf1 rapidly represses Pol IIItranscription. We report the crystal structure ofMaf1 and cryo-electron microscopic structures ofPol III, an active Pol III-DNA-RNA complex, anda repressive Pol III-Maf1 complex. Binding of DNAand RNA causes ordering of the Pol III-specific sub-complex C82/34/31 that is required for transcriptioninitiation. Maf1 binds the Pol III clamp and rearrangesC82/34/31 at the rim of the active center cleft. Thisimpairs recruitment of Pol III to a complex ofpromoter DNA with the initiation factors Brf1 andTBP and thus prevents closed complex formation.Maf1 does however not impair binding of a DNA-RNA scaffold and RNA synthesis. These resultsexplain how Maf1 specifically represses transcrip-tion initiation from Pol III promoters and indicatethat Maf1 also prevents reinitiation by binding PolIII during transcription elongation.

INTRODUCTION

The eukaryotic genome is transcribed by the multisubunit

enzymes Pol I, II, and III, which catalyze DNA-dependent

RNA synthesis. Pol III transcribes genes encoding short,

untranslated RNAs, including transfer RNAs, 5S ribosomal

RNA (rRNA), the spliceosomal U6 small nuclear RNA (snRNA),

and the signal recognition particle 7SL RNA. Pol III genes are

essential and involved in fundamental processes such as ribo-

some and protein biogenesis, RNA processing, and protein

transport. Pol III transcription is coregulated with Pol I activity,

accounting together for up to 80% of nuclear gene transcription

in growing cells (Paule and White, 2000; Grummt, 2003; Willis

et al., 2004). Pol III activity is a critical determinant of cell

growth.

Pol III is the most complex of the nuclear RNA polymerases.

It has a total molecular weight of around 700 kDa and comprises

17 subunits (Schramm and Hernandez, 2002). Five of its

subunits, Rpb5, 6, 8, 10, and 12, are common to Pol I, II, and

III. Subunits AC40 and AC19 are common to Pol I and III and

are homologous to Pol II subunits Rpb3 and Rpb11, respectively.

The two largest Pol III subunits C160 and C128 are homologous

to Pol II subunits Rpb1 and Rpb2, respectively, and form the

active center of the enzyme. Subunits C17 and C25 form

a subcomplex with homology to the Pol II subcomplex Rpb4/7

(Ferri et al., 2000; Jasiak et al., 2006; Sadhale and Woychik,

1994), whereas subunit C11 shares homology with Pol II subunit

Rpb9. The Pol III-specific subunits C82, C53, C37, C34, and C31

form two subcomplexes. The C53/37 subcomplex shows weak

homology to the Pol II initiation factor TFIIF and is involved in

promoter opening, elongation, termination, and reinitiation

(Cramer et al., 2008; Carter and Drouin, 2009; Kassavetis et al.,

2010; Landrieux et al., 2006), whereas the C82/34/31 subcom-

plex is involved in promoter recognition and initiation. C34 inter-

acts with TFIIIB, which recruits Pol III to promoters (Thuillier et al.,

1995; Wang and Roeder, 1997; Werner et al., 1993) and is

involved in open complex formation (Brun et al., 1997).

To date, structural information on Pol III is limited to a cryo-elec-

tron microscopic (cryo-EM) map that revealed the approximate

location of the two Pol III-specific subcomplexes (Fernandez-

Tornero et al., 2007), a homology model for the 10-subunit

core enzyme, and the crystal structure of C25/17 (Jasiak et al.,

2006).

Rapid repression of Pol III transcription ensures cell survival

during stress (Warner, 1999). Pol III repression is mediated by

Maf1, a protein that is conserved from yeast to human (Pluta

et al., 2001; Upadhya et al., 2002). Maf1 represses Pol III in

response to DNA damage, oxidative stress, growth to

stationary phase, treatment with rapamycin or chlorpromazine,

and blocking of the secretory pathway (Upadhya et al., 2002;

Willis et al., 2004). In growing yeast, Maf1 is phosphorylated

and localized in the cytoplasm. Stress conditions lead to

Maf1 dephosphorylation and nuclear import (Oficjalska-Pham

et al., 2006; Roberts et al., 2006), which is directed by two

nuclear localization signal (NLS) sequences (Lee et al., 2009;

Moir et al., 2006). In the nucleus, Maf1 binds Pol III to prevent

its interaction with TFIIIB and promoters (Desai et al., 2005;

Moir et al., 2006; Roberts et al., 2006). Maf1 also binds Brf1,

a subunit of TFIIIB that resembles the Pol II initiation factor


TFIIB (Desai et al., 2005). Maf1-mediated repression is associ-

ated with reduced Brf1 and Pol III occupancy at Pol III genes

(Oficjalska-Pham et al., 2006; Roberts et al., 2006). Similar

results have been obtained with human cells, establishing

Maf1 as a conserved global repressor of Pol III transcription

(Reina et al., 2006).

Here, we report cryo-EM structures of Pol III in its free form

and in complex with a DNA-RNA scaffold, assign the locations

of Pol III subunits, present the Maf1 crystal structure, and

combine the resulting information with a cryo-EM structure of

a Pol III-Maf1 complex. Together with functional studies, these

results establish the mechanism for Pol III transcription repres-

sion by Maf1.

RESULTS AND DISCUSSION

Pol III EM Structure Reveals C82/34/31 MobilityWe established a protocol for large-scale purification of Pol III

from the yeast Saccharomyces cerevisiae (Experimental

Procedures). Pure Pol III samples comprised all 17 subunits

(Figure 1A), were monodisperse, and appeared homogeneous

in EM with negative stain (Figure 1B). We collected high-quality

cryo-EM data after vitrification under native conditions. A recon-

struction of Pol III from 20,480 single particles led to a map at

21 A resolution (Figure 1E; Figure S1 available online; Experi-

mental Procedures) that generally agrees with the previously

published map (Fernandez-Tornero et al., 2007).

C160C128

C82

C53

C37/AC40C34C31

C25/Rpb5

Rpb8

C11

Rpb10Rpb12

C17/AC19/Rpb6

A B C

E

Frontview

Topview

90°

Rpb4/7(C25/17)

C53/37

C53/37

C82/34/31

C82/34/31

C82/34/31

D

RNA

DNA non-template

DNA template

Elongation

Pol II X-raystructure

C82/34/31

DNA-RNA

Active center cleftPol III Pol III-DNA-RNA

Rpb5 jawRpb9 (C11)

Rpb8 foot C160 foot

Rpb4/7(C25/17)

Protrusion

Rpb5 jaw

Lobe

ClampProtrusion

Rpb4/7(C25/17)

Rpb5jaw

Rpb9 (C11)

Pol II X-raystructure

Rpb4/7(C25/17)

Figure 1. Cryo-EM Structures of Pol III and Pol III-DNA-RNA Complex

(A) SDS-PAGE of pure yeast Pol III. The identity of the 17 subunits was confirmed by mass spectrometry.

(B) EM micrographs of Pol III in negative stain (left) and vitrified ice (right). Scale bars represent 10 nm.

(C) Views of the Pol III reconstruction (first row) with corresponding raw single-particle images (second row), low pass-filtered single-particle images (third row),

class averages (forth row), and reference-free averages (fifth row).

(D) DNA-RNA scaffold used in complex formation.

(E) Cryo-EM reconstruction of Pol III (green) and Pol III-DNA-RNA complex (blue). The Pol II X-ray structure (Armache et al., 2005) was fitted to the Pol III map and is

shown as a ribbon model. White dashed lines indicate additional densities between the lobe and Rpb9 (C11), attributed to the C53/37 subcomplex, and between

the clamp and Rpb5, attributed to the C82/34/31 subcomplex, that gets ordered in the DNA-RNA complex.

See also Figures S1 and S4 and Movie S1.


The 12-subunit Pol II crystal structure (Armache et al., 2005)

was unambiguously fitted to the EM map (Figure 1E). After that,

two densities remained that could not be assigned to Pol III-

specific insertions or residues lacking from the Pol II structure,

one at the polymerase lobe and one on top of the clamp

(Figure 1E). Densities at the lobe and clamp were attributed to

subcomplexes C53/37 and C82/34/31, respectively (Fernan-

dez-Tornero et al., 2007). The density at the lobe was fitted with

a homology model of the C53/37 dimerization module based on

the structure of the related A49/34.5 module in Pol I (Geiger

et al., 2010) (Figure 2). The location of C53/37 agrees with the

previously reported association of C53/37 with C11 (Chedin

et al., 1998) and with the location of the TFIIF dimerization domain

on the Pol II lobe (Chen et al., 2010; Eichner et al., 2010). The addi-

tional density at the clamp accounts only for part of the 138 kDa

subcomplex C82/34/31, indicating flexibility (Figure 1E).

Nucleic Acid Binding Restricts C82/34/31To see how nucleic acid binding influences the Pol III structure,

we determined the cryo-EM structure of a Pol III complex with

a minimal DNA-RNA scaffold (Figure 1D; Experimental Proce-

dures). This complex mimics an active elongation complex

(Brueckner et al., 2007). A reconstruction at 19 A resolution

was obtained from 11,965 single particles (Figure 1E). The recon-

struction revealed density for nucleic acids in the cleft, but also

a structural ordering of the C82/34/31 subcomplex, giving rise

to an extended density between the top of the clamp, the

Rpb5 jaw, and C25/17 (Figures 1E and 2A; Figure S2).

A continuous density between the clamp and the jaw could be

fitted with the crystal structure of the human C82 homolog

(S. Fribourg, personal communication) (Figure 2). A prominent

density remained, forming a suspension over the cleft from the

clamp to the protrusion (Figures 1E and 2A–2C). This density

C

Pol II X-ray structure

C82

C34

Frontview

Rpb4/7(C25/17)

C82

C34

C31

Zn8

Outline view from the C25/17 side

D

C82

1 654

WH1 WH2 Leu-ZipperWH3

C34

1 317

WH1 WH2

1 251

C31

1 282

C37 DimerizationC53

1 422

E

Topview

C82

C53/37dim. module

Pol III-DNA-RNAenvelope

C34

Rpb4/7(C25/17)

A B

C53/37dim. module Dimerization

Zn-bdg.

WH4

Protrusion

Jaw Clamp

C31Zn8 Rpb4/7(C25/17)

C53/37dim. module

C53 N-term.extension

C37 N-term.extension

C37 C-term.extension

C53/37

C34

C82

Figure 2. Subunit Architecture of Pol III

(A) Pol III-specific subunits were placed into the cryo-EM envelope of the Pol III-DNA-RNA complex. A homology model of the C53/37 dimerization domain (green)

(Geiger et al., 2010), the human C82 homolog crystal structure (blue; S. Fribourg, personal communication), and the two C34 WH domain crystal structures

(purple) are shown as molecular surfaces. Fitted structures are shown low-pass filtered to the same resolution than the EM map. The 12 subunit Pol II X-ray struc-

ture (Armache et al., 2005) is shown as a green ribbon.

(B) Close-up views of Pol III-specific subunits fitted into the cryo-EM envelope of the Pol III-DNA-RNA complex. Terminal extensions of the C53/37 dimerization

module are highlighted in red.

(C) Location of Pol III-specific subunits on the Pol II structure. The view is related to the one in (A) by a 90� rotation around a horizontal axis.

(D) Location of subunits of the C82/34/31 subcomplex within Pol III.

(E) Domain organization of Pol III-specific subunits. Based on homology modeling (C53, C37), crystallography (C34), or HHPred and secondary structure predic-

tion (C82).

See also Figures S2 and S4 and Movie S1.


was assigned to subunit C34 since its two lobes fitted the struc-

tures of two winged helix (WH) domains in C34 (PDB codes 2dk5

and 2dk8), and since C34 crosslinks to promoter DNA around

position �21 (Bartholomew et al., 1993), which is adjacent in

the homologous Pol II promoter complex model (Kostrewa

et al., 2009). The remaining globular density between the clamp

and C25/17 (Figure 2; Figure S2) was assigned to C31 since this

position explains the known interactions of C31 with subunits

C160, C82, C34, and C17 (Chedin et al., 1998; Geiduschek

and Kassavetis, 2001; Schramm and Hernandez, 2002), the

requirement of the adjacent zinc site Zn8 in C160 for C82/34/

31 binding (Werner et al., 1992), and association of C31 with

Pol III after dissociation of the C82/34 heterodimer (Lorenzen

et al., 2007). Thus, all Pol III subunits were assigned to EM densi-

ties consistent with known subunit interactions.

Globular Structure of Maf1To elucidate Pol III repression by Maf1, we determined the Maf1

structure by X-ray crystallography (Experimental Procedures).

Limited proteolysis of recombinant S. cerevisiae and human

Maf1 revealed two flexible regions, a mobile insertion and an

acidic C-terminal tail (Figure 3A). A human variant that lacked

both mobile regions crystallized. The structure was solved by

bromide phasing and refined to a free R factor of 21.2% at

1.55 A resolution (Table 1). Maf1 forms a globular structure

with a central five-stranded antiparallel b sheet that is flanked

by one helix on one side and three helices on the other

(Figure 3B). The Maf1 fold is frequently observed, but not in

proteins involved in transcription (Holm and Park, 2000; Krissinel

and Henrick, 2004). The structure shows that the previously

defined conserved sequence boxes A, B, and C (Desai et al.,

2005; Pluta et al., 2001; Reina et al., 2006) do not correspond

to structural modules or defined surface patches (Figure 3C).

Thus, functional data for Maf1 deletion variants must be re-eval-

uated in light of the structure. The Maf1 structure is conserved

among eukaryotes, since hydrophobic core residues are

conserved from yeast to human (Figure 3A).

Regulated Maf1 LocalizationThe Maf1 crystal structure reveals that the two NLS sequences

(yeast residues 205–208 and 328–332; Moir et al., 2006) are

surface accessible (Figure 3B). The C-terminal NLS (Ct-NLS) is

located between strands b4 and b5, and the N-terminal NLS

(Nt-NLS) is part of the directly adjacent mobile region

(Figure 3B). The adjacent location suggests that phosphorylation

of the mobile insertion regulates nuclear localization by masking

the NLS sequences (Lee et al., 2009; Moir et al., 2006). This

mechanism is apparently conserved from yeast to human,

although the phosphorylation sites within the mobile insertion

differ (Dephoure et al., 2008; Lee et al., 2009; Moir et al., 2006;

Shor et al., 2010). The Ct-NLS and adjacent residues form the

only positively charged region on Maf1 (Figure 3F). Several point

mutants that lead to defects in phosphorylation, growth on glyc-

erol at 37�C, or Pol III repression (Moir et al., 2006; Roberts et al.,

2006) are exposed around the mobile insertion (Figure 3E, resi-

dues labeled in red and pink).

Maf1 Rearranges C82/34/31To investigate how Maf1 binds yeast Pol III, we prepared full-

length recombinant yeast Maf1 and a variant that lacked both

mobile regions (residues 36–224 and 346–395) and corresponded

to the crystallized human protein. Both variants formed a complex

with Pol III that could be purified by size-exclusion chromatog-

raphy (Figure 3D, lanes 3 and 4). Maf1 binding was specific, as

human Maf1 did not bind yeast Pol III (data not shown).

Thus, the two mobile regions are not required for Pol III binding,

and the human Maf1 crystal structure is relevant for under-

standing the Pol III-Maf1 interaction in the yeast system. We

collected cryo-EM data of the pure Pol III-Maf1 complex and

used 16,974 particles to obtain a reconstruction at 18.5 A resolu-

tion (Figure 4; Figure S3; Experimental Procedures). The structure

revealed a continuous density for C82/34/31, similar to the density

in the Pol III-DNA-RNA complex (Figure 4C; Figure S5).

Maf1 was assigned to a new density on top of the clamp with

the help of difference maps (Figure 4; Figure S3). The Maf1 X-ray

structure fitted this density well (Figures 4A and 4C; Figure S3).

To provide additional support for the Maf1 location, we labeled

the C-terminal hexahistidine tags on Maf1 and the Pol III subunit

C128 with Ni-NTA-Nanogold and located the labels by 2D cryo-

EM image analysis (Experimental Procedures). The locations of

the labels were consistent with Maf1 binding on top of the clamp

domain (Figure 4B). This location also agreed with published

biochemical and genetic interactions of Maf1 with the N-terminal

region of C160, which forms most of the clamp (Boguta et al.,

1997; Oficjalska-Pham et al., 2006; Reina et al., 2006)

(Figure 4D). Further consistent with this location, C160, C82,

and C34 are the key interacting partners of Maf1 in the yeast

interactome (Gavin et al., 2006).

Maf1 partially overlapped with the assigned locations of the

second WH domain in C34 and with C82 and C31 in the Pol III-

DNA-RNA complex (Figures 4C and 4E). Consistently, the C82/

34/31 density in the Pol III-Maf1 complex differed from that in

the Pol III-DNA-RNA complex. Most of the density assigned to

the C34 WH domains in the Pol III-DNA-RNA complex was

absent in the Pol III-Maf1 complex, indicating a Maf1-dependent

displacement of these domains (Figure 4F; Figure S3). The densi-

ties assigned to C31 and C82 apparently shifted toward the

Rpb5 jaw (Figures 4C and 4F; Figure S3). The differences in

the EM structures are visualized in a side-by-side comparison

and a movie (Figure S4; Movie S1).

Maf1 Impairs Closed Promoter Complex FormationTo analyze how the structural changes induced by Maf1 could

repress Pol III transcription, we modeled the Pol III-Brf1-TBP

closed promoter complex. Brf1 resembles the Pol II initiation

factor TFIIB in its N-terminal region but contains a specific

C-terminal extension that binds TBP (Figure S5) (Khoo et al.,

1994). We combined the Pol II-TFIIB-TBP closed promoter

complex model (Kostrewa et al., 2009) with the structure of

TBP bound to the Brf1 C-terminal residues 437–507 (Juo et al.,

2003). Comparison of the resulting model with the EM densities

revealed that C34 was well positioned for interacting with the

Brf1 N- and C-terminal regions (Figure 5A), consistent with

published data (Khoo et al., 1994, Andrau et al., 1999; Brun

et al., 1997; Kassavetis et al., 2003). In the Pol III-Maf1 complex,


C34 adopts a different position that is apparently incompatible

with Brf1 interaction, suggesting that Maf1 impairs Pol III recruit-

ment to Brf1-containing promoters (Figures 5A and 5B).

To test this model, we investigated by size-exclusion chroma-

tography whether the Pol III-Maf1 complex can bind to

a preassembled functional Brf1-TBP-DNA promoter complex

180°

Ct-NLS Ct-NLS

negative positive

F

C

A

N

2 aaacidictail

C

mobile insertion (Nt-NLS)

Ct-NLS

β1

β2β3

β4β5

α1α3

α4

α5

N

2 aa


β1

β2 β3

β4β5

α1 α3

α4

α5

C

acidictail

Ct-NLS

β1 α1 α3

α4 β3 β4 β5

β2N

α5

A-box B-box

C-box

K331AK329A

R232H

D248A

D250A

E5A

E10A

D30N

E314

D298

D258

K261

K233A

A240R

R280A

G316E

Ct-NLS

{33}

{51}{41}{49}

{26}{174}

acidic tail


B


B-box

C-box

C

acidictail

N

A-box

C

E180°

C160C128

C82

C53

C37/AC40C34C31C25/Rpb5

Rpb8

C11

Rpb10Rpb12

C17/AC19/Rpb6

Sc Maf1 fl

1 2 3 4

Sc

X-t

al M

af1

D

180°

Figure 3. Maf1 Crystal Structure

(A) Amino acid sequence alignment of Maf1 from Homo sapiens (H.s.), Schizosaccharomyces pombe (S.p.), and Saccharomyces cerevisiae (S.c.). Secondary

structure elements are indicated (cylinders, a helices; arrows, b strands). Identical and conserved residues are highlighted in green and orange, respectively.

The mobile insertion (human residues 36–82, yeast residues 36–224) includes proteolytic cleavage sites (this work), phosphorylation sites (Dephoure et al.,

2008; Lee et al., 2009; Moir et al., 2006), and the N-terminal NLS (Nt-NLS). The C-terminal NLS (Ct-NLS) is indicated. Dashed lines indicate regions absent

from the crystal structure. The crystallized protein is a human Maf1 variant comprising residues 1–35 and 83–205.

(B) Two views of a ribbon model of the Maf1 crystal structure. Secondary structure elements are labeled according to (A).

(C) Maf1 ribbon model with the conserved boxes A, B, and C highlighted in blue, purple, and rose, respectively.

(D) Purification of Pol III-Maf1 complexes. Two hundred microrams of Pol III and a 5-fold molar excess of full-length yeast Maf1 or a variant comprising residues

1–35 and 225–345 (lane 1) were incubated for 20 min at 20�C, subjected to gel filtration, and analyzed by SDS-PAGE. Lanes 2, 3, and 4 show Pol III, the Pol III

complex with the Maf1 variant, and the Pol III complex with full-length Maf1, respectively.

(E) Surface conservation of Maf1. Identical and conserved residues are highlighted in green and yellow, respectively. Mutations at residues labeled in red, pink,

and wheat show severe, mild, or no phenotypes, respectively (Dephoure et al., 2008; Moir et al., 2006; Roberts et al., 2006).

(F) Surface charge distribution of Maf1. Red, blue, and white areas indicate negative, positive, and neutral charge, respectively.


(Kassavetis et al., 2005). We used U6 snRNA promoter DNA from

position �40 to +20 relative to the transcription start site +1

(Figure 6A, closed scaffold). Whereas free Pol III stably bound

the Brf1-TBP-DNA complex, the Pol III-Maf1 complex did not,

even when a 5-fold molar excess was used (Figure 6B, lanes

3, 5). When we repeated the experiment with a mismatched

bubble region at positions –11 to +2 (Figure 6A, bubble scaffold),

the same result was obtained (Figure 6E, lanes 6, 7). Further,

preassembled Pol III-Brf1-TBP-DNA complex did not bind

Maf1, even when a 5-fold molar excess was used (Figure 6B,

lane 4). Thus, the interactions of Pol III with Maf1 and a Brf1-

TBP-DNA complex are mutually exclusive, showing that Maf1

impairs formation of a closed promoter complex. This is consis-

tent with evidence that Maf1 prevents Pol III promoter interaction

(Desai et al., 2005; Moir et al., 2006; Roberts et al., 2006).

Maf1 Does Not Inhibit Pol III ActivityThe above model predicts that Maf1 inhibits binding of promoter

DNA over the active center cleft, but not in the cleft. To test this,

we compared pure Pol III and Pol III-Maf1 complexes in an initi-

ation factor-independent transcription assay using a 30-tailed

DNA template and a priming RNA dinucleotide (Bardeleben

et al., 1994). Consistent with the model, both complexes were

equally active in RNA synthesis, and an excess of Maf1 or DNA

did not change activity (Figure 6C). We also performed RNA

extension assays using a minimal DNA-RNA scaffold (Damsma

and Cramer, 2009). The presence of Maf1 neither prevented

scaffold binding nor elongation to the end of the template, and

this was independent of the order of factor addition (Figure 6D).

To rule out that nucleic acids displace Maf1 from Pol III or

prevent its binding, we tested by size-exclusion chromatography

whether Pol III binds Maf1 and nucleic acids simultaneously. Pol

III-Maf1 complexes with tailed template or bubble scaffold could

be purified, independent of the order of addition (Figure 6E).

Thus, Maf1 prevents neither nucleic acid binding in the active

center nor RNA synthesis. The observation that Pol III can simul-

taneously bind Maf1 and nucleic acids suggests that the

increased Maf1 occupancy at Pol III genes under repressive

conditions (Geiduschek and Kassavetis, 2006; Oficjalska-

Pham et al., 2006; Roberts et al., 2006) is due to Maf1 binding

to elongation complexes. Pol III in such Maf1-containing elonga-

tion complexes would be unable to reinitiate, explaining the

observation that Maf1 represses multiple-round transcription

by Pol III (Cabart et al., 2008).

ConclusionsOur results converge with published data on the mechanism of

Pol III-specific transcription repression by Maf1. Cellular stress

leads to dephosphorylation of a mobile surface region in Maf1

that unmasks adjacent NLS sequences, leading to nuclear

import of Maf1. In the nucleus, Maf1 binds free Pol III at its clamp

domain and rearranges the C82/34/31 subcomplex. This impairs

Pol III binding to a TBP-Brf1-promoter complex and specifically

abolishes initiation from Pol III promoters, which require Brf1.

Maf1 also binds Pol III that is engaged in transcription elongation,

leaving activity intact but preventing reinitiation. Since Pol III

genes are short and elongation is fast, this leads to rapid shut-

down of all Pol III transcription.


Pol III Preparation

The Saccharomyces cerevisiae strain NZ16 (Lannutti et al., 1996), carrying the

gene for an N-terminally His6-FLAG4-RET1-tagged C128 subunit on the parent

plasmid pYE(CEN3)30 was grown to OD600 = 6–7 at 30�C in YPD media in

a 200 L fermenter (Infors ABEC). Cells were lysed by bead beating in ice-

cooled buffer A [200 mM Tris-HCl (pH 8.0), 500 mM (NH4)2SO4, 10 mM

MgCl2, 10% glycerol, 10 mM b-mercaptoethanol, 1 mM PMSF, 1 mM benza-

midine, 200 mM pepstatin, 60 mM leupeptin]. Subsequent steps were per-

formed at 4�C. Glass beads were separated by filtration, and the lysate was

cleared by centrifugation (60 min, 8000 g, Sorvall SLA-1500). A whole-cell

extract was obtained after centrifugation at 125,000 g for 90 min (Beckman

Ti45) by separation of the clear upper-middle phase from the turbid lower

phase. The supernatant was processed by step-wise ammonium sulfate

precipitation. Thirty-five percent (NH4)2SO4 was added, and the sample was

stirred for 30 min and cleared by centrifugation (60 min, 8000 g, Sorvall

SLA-1500). The supernatant was precipitated over night after addition of

70% (NH4)2SO4. The pellet was recovered by centrifugation (60 min, 8000 g,

Sorvall SLA-1500) and resuspended in 3 liters of buffer B (40 mM HEPES

[pH 7.8], 5 mM MgCl2, 10% glycerol, 1 mM EDTA, 10 mM b-mercaptoethanol,

Table 1. Maf1 X-Ray Diffraction and Refinement Statistics

Data Set NaBr Soak Native

Data Collection

Space group P 212121 P 212121

Unit cell axis:

a, b, c (A)

48.1, 48.3,

80.5

48.4, 48.8,

79.3

Peak Remote Inflection

Wavelength (nm) 0.9196 0.9211 0.9200 0.91870

Resolution (A)a 26.83–1.9 26.83–1.9 26.83–1.9 25.974–1.55

Rmerge (%)a 7.7 (50.7) 6.0 (39.2) 7.0 (51.3) 5.2 (58.9)

I/s (I)a 22.0 (2.5) 22.7 (3.0) 22.0 (2.4) 22.3 (1.2)

Completeness (%)a 99.0 (99.5) 98.8 (99.4) 98.9 (99.5) 94.3 (87.4)

Redundancya 3.9 (4.0) 3.8 (3.9) 3.8 (4.0) 3.0 (1.9)

Refinement

Resolution (A) 1.55–25.97

Number of reflections 26,183

Rwork (%) 18.81

Rfree (%) 21.15

Number of atoms

Protein 1313

Water 142

B factors (A2)

Protein 33.64

Water 43.95

Rmsd from ideal

Bond lengths (A) 0.006

Bond angles (�) 0.959

Rmerge = S jI � < I > j/S j where I is the integrated intensity of a given

reflection.

R = S kFobsj � jFcalck/S j Fobsj. Rfree was calculated with 5% of data

excluded from refinement.a The highest-resolution shell is shown in parentheses.


C82

C34Maf1 X-ray

ED

Maf1 X-ray

Clamp domain

Pol IIX-ray

B

Maf1 X-ray

Topview

Rpb4/7(C25/17)

Clamp

Rpb5 JawLobe

Protrusion

Layer ofcross-section

in (A)

C

A

Front view(cross-section)

Rpb4/7(C25/17)

C160 foot

LobeMaf1 density

Protrusion

Pol III-DNA-RNAPol III-Maf1

70°

F

Layer of cross-section in (F)

Maf1 X-rayProtrusion

Rpb5 Jaw

Lobe

Rpb5 Jaw

Clamp

Maf1 X-ray (background)

Side view (C128 side, cross-section)

Front view (close-up)

Maf1 X-ray

G

Protrusion

Density for the C34 WH domains

Shifted densitiesin Pol III-Maf1

Frontview

Figure 4. Cryo-EM Structure of the Pol III-Maf1 Complex

(A) Comparison of cross-section of EM structures of the Pol III-Maf1 complex (red) and the Pol III-DNA-RNA complex (blue) reveals an additional density for Maf1.

(B) Different views of reference projections of the Pol III-Maf1 3D reconstruction (top row), corresponding Nanogold-labeled particles used for alignment (second

row), raw Nanogold-labeled particles (third row), Nanogold locations (circles) on the Pol III-Maf1 structure (forth row), and surface representations of reconstruc-

tions with the C128 N terminus and the location of Maf1 indicated by white and yellow dots, respectively (bottom row).

(C) Fit of the Maf1 X-ray structure (red surface, low-pass filtered to the resolution of the EM map) to the Pol III-Maf1 EM map (red grid). For comparison, the cryo-

EM map of the Pol III-DNA-RNA complex is shown (blue).

(D) Ribbon representation of the Pol III-Maf1 complex. The Pol II X-ray structure (Armache et al., 2005) is shown in green, and the Maf1 structure in red. The clamp

C160 residues 1–245 are yellow. The Pol III-Maf1 cryo-EM map is shown as a red mesh.

(E) Steric clash of Maf1 (red ribbon) with C34 (purple) and C82 (cyan) as observed in the Pol III-DNA-RNA complex.

(F) Comparison of cross-sections of EM structures of the Pol III-Maf1 complex (red) and the Pol III-DNA-RNA complex (blue) reveals a shift of the C82/34/31

subcomplex upon Maf1 binding.

(G) Close-up view of the region above the clamp. Parts of the C34 densities in the Pol III-DNA-RNA complex (blue) are absent in the Pol III-Maf1 complex (red).

See also Figures S3and S4 and Movie S1.


1 mM PMSF, 1 mM benzamidine, 200 mM pepstatin, 60 mM leupeptin). The

sample was applied to a 250 ml Biorex resin column (Biorad). Bound proteins

were eluted with buffer C (buffer B + 500 mM KCl + 5 mM imidazole [pH 8.0]).

The eluting proteins were loaded onto a 12 ml Ni-NTA Agarose (QIAGEN)

column. Subsequent washing steps were performed with buffer C containing

10 mM imidazole and buffer D [40 mM HEPES (pH 7.8), 5 mM MgCl2, 250 mM

(NH4)2SO4, 10% glycerol, 10 mM imidazole, 10 mM b-mercaptoethanol, 1 mM

PMSF, 1 mM benzamidine, 200 mM pepstatin, 60 mM leupeptin]. Proteins

were eluted with buffer D containing 250 mM imidazole and loaded onto

a HiTrap Heparin 5 ml column (GE Healthcare) and fractionated by application

of a salt gradient from 250 to 1000 mM (NH4)2SO4 with buffer E (40 mM HEPES

[pH 7.8], 5 mM MgCl2, 20% glycerol, 0.5 mM EDTA, 10 mM b-mercaptoetha-

nol, 1 mM PMSF, 1 mM benzamidine, 200 mM pepstatin, 60 mM leupeptin).

Pooled fractions eluting at 500 mM (NH4)2SO4 were diluted 5-fold with buffer

E, loaded onto an anion exchange column (Mono Q 10/100 GL, GE Health-

care), and fractionated with a salt gradient from 50 to 1000 mM (NH4)2SO4 in

buffer F (40 mM HEPES [pH 7.8], 1 mM MgCl2, 5 mM DTT). Pol III-containing

fractions eluted at 600 mM (NH4)2SO4, were pooled, diluted to a concentration

of 50 mM (NH4)2SO4, supplemented with a 10-fold molar excess of recombi-

nant full-length C53/37 heterodimer, and incubated for 60 min. The sample

was concentrated to 1 ml with an Amicon Ultra-4 centrifugal filter unit

(MWCO 10 kDA, Millipore) and applied to gel filtration chromatography on

a Superose 6 column (Superose 6 10/300 GL, GE Healthcare) with buffer G

[20 mM HEPES pH 7.8, 50 mM (NH4)2SO4, 100 mM MgCl2, 10 mM ZnCl2,

5 mM DTT]. Pol III-containing fractions were pooled, concentrated to

1 mg/ml with an Amicon Ultra-4 centrifugal filter unit (MWCO 10 kDA, Millipore)

and flash frozen in liquid N2 after addition of 10% glycerol.

Cryo-EM Structure Determinations

Purified Pol III was diluted to 0.1 mg/ml in buffer G and applied to glow-dis-

charged precoated carbon holey grids (Quantifoil R3/3, 2 nm carbon on top).

Samples were flash frozen in liquid ethane with a semiautomated controlled-

environment system (Vitrobot, FEI Company) at 4�C, 95% humidity, and stored

in liquid nitrogen until transfer to the microscope. Micrographs were recorded

under low dose conditions of �15 e/A2 on a FEI Tecnai Spirit microscope

operating at 120 kV, equipped with a LaB6 filament and a Gatan side entry

A

DNA non-template

DNA template

Brf1 C-term.

TBPBrf1 N-term.

C34

Top view

Pol III-Brf1-TBP closed promoter complex model

C

Pol II X-ray

B Pol III-Brf1-TBP closed promoter complex model

(schematic outline)

Active site

C34

Brf1 C-term.

Brf1 N-term.

Brf1 C-term.

TBP

Brf1 N-term.

C34

DNA non-template

DNA template

C

Pol II X-ray

90° 90°

&

Side view(C128 side)

Maf1 initiationrepression model

C34

TB

P

Brf1 C-term.

Brf1 N-term.

Active site

Side view(C128 side)

Outline ofPol III-DNA-RNA

Outline ofPol III-DNA-RNA

Maf1TBP

Rpb4/7(C25/17)

Figure 5. Mechanism of Pol III Repression by Maf1

(A) Model of the Pol III-Brf1-TBP-DNA closed promoter complex. The Pol II structure is silver, the C34 WH domains are magenta, the Brf1 N-terminal domain is

green, the Brf1 C-terminal domain is orange, TBP is dark purple, and the closed promoter DNA is cyan/blue. The model is based on the homologous Pol II-TFIIB-

TBP-DNA closed promoter complex model (Kostrewa et al., 2009) and the Brf1-TBP-DNA structure (Juo et al., 2003).

(B) Schematic view of Maf1-dependent repression of the formation of a Pol III-Brf1-TBP-DNA closed promoter complex. Colors are as in (A).

See also Figure S5.


cryoholder. Images were acquired at underfocus values in the range of 1.5–

4 mm on a 2k 3 2k FEI Eagle CCD camera applying a pre-exposure of

100 ms at a magnification of 90,0003, resulting in a pixel size of 3.31 A/px

on the object scale. Image-processing operations were carried out with

SPIDER (Frank et al., 1996). Initial particle selection was performed with

EMAN (Ludtke et al., 1999). Reference particles were picked manually to avoid

discrepancies due to defocus and ice differences. Automatically selected

particles were verified visually. Windowed particles were aligned to 83 projec-

tions of the Pol II X-ray structure (1Y1W, Gaussian low-pass filtered to 35 A),

which lacked the mobile OB and HRDC domains of Rpb4/7. Particle assign-

ment to the reference projections was evenly distributed, barring few overrep-

resented outliers that were limited to prevent predominant views (Figure S1).

Backprojection of the particle images with the angles from reference-based

alignment resulted in a reconstruction that showed additional densities at

the clamp and C25/17 and was used as a reference for 20 rounds of angular

refinement. Images were backprojected in real space with the refined angles.

The resulting reconstruction was Gaussian low-pass filtered to 25 A and used

as reference for another round of alignment and refinement, and this proce-

dure was iterated until convergence. A 21 A reconstruction of Pol III from

a data set of 20,480 particles was obtained. During early stage of refinement,

density for a complete C25/17 complex and other additional densities ap-

peared that could be confirmed by an independent 23 A reconstruction from

12,174 particles (data not shown). Projections of the 20,480 particle Pol III

reconstruction, as well as their corresponding particle averages, were

compared to averages resulting from a reference-free 2D alignment method

with the program refine2d (Ludtke et al., 1999). A high portion of similar aver-

ages showed that the alignment and refinement based on the reference struc-

ture was not significantly biased. A cryo-EM data set of Pol III, prepared as

above, incubated with a 3-fold molar excess of DNA-RNA scaffold, was

collected, and a reconstruction at 19 A resolution was obtained with 11,965

particles. A 18.5 A reconstruction of a size-exclusion purified Pol III-Maf1

complex (see preparation for interaction assays) was obtained from 16,974

particles. The resolution of the structures could not be improved when

96,944 particles collected on film at 200 keV with a FEI Polara microscope

were used.

Maf1 Crystal Structure Determination

DNA encoding S. cerevisiae or human Maf1 was PCR-amplified from genomic

DNA and cloned into pET-28b vector (Novagen) with the NdeI/NotI restriction

sites, resulting in a N-terminal hexahistidine tag. E. coli BL21 (DE3) RIL cells

Maf1 add.Sc Maf1 fl

Pol III

NTP

- - --

- -

+ +

+

++

+

+

++15

0+1+2+3

+

pre post

1 2 3 4 5

D

no P

ol III

no N

TPs

+ 5x

Maf

1

+ 10

x Maf

1

Pol III Pol III-Maf1

+ 2x

Sca

ffold

+ 5x

Sca

ffold

+ 10

x Sca

ffold

1 2 3 4 5 6 7 8

no M

af1

C

A

RNA

DNA non-template

DNA template

86 bp

Elongation

B

Sc Maf1 fl

Pol III

-Brf1

-TBP B

ubble

sc. +

Maf

1

Pol III

-Maf

1 +

Brf1-T

BP Clos

ed sc

.

Pol III

-Brf1

-TBP C

losed

sc. +

Maf

1

Pol III

-Brf1

-TBP C

losed

scaf

fold

Pol III

Brf1-T

BP

1 2 3 4 5 6 7

Pol III

-Maf

1 +

Brf1-T

BP Bub

ble sc

.

Sc Maf1 fl

Pol III

-Maf

1 +

Taile

d te

m.

Pol III

-Bub

ble sc

. + M

af1

Pol III

-Maf

1 +

Bubble

sc.

Pol III

Bubble

scaf

fold

Taile

d te

mpla

te

1 2 3 4 5 6

E

Bubblescaffold

24 bp9 bp

Closedscaffold

24 bp10 bp

Elongationscaffold

Tailedtemplate

Figure 6. Maf1 Impairs Closed Promoter Complex Formation but Not Pol III Activity

(A) Nucleic acid scaffolds.

(B) Competition assays reveal that Maf1 impairs binding of Pol III to a Brf1-TBP-DNA complex. Preassembled Pol III-Brf1-TBP-DNA or Pol III-Maf1 complexes

were incubated with a 5-fold molar excess of competing factor or complex as indicated and subjected to gel filtration, and the peak fraction was analyzed by

SDS-PAGE. In lanes 3, 4, and 6, the presence of DNA was revealed by the high A260/A280 ratio (�1) compared to the A260/280 ratio (�0.6) in lanes 2, 5, and 7.

(C) Factor-independent Pol III transcription assays. Preincubated Pol III-DNA (lanes 3–5) and Pol III-Maf1 complexes (lanes 6–8) efficiently transcribe the tailed

template (A). Addition of increasing amounts of Maf1 to preincubated Pol III-DNA complexes does not impair transcription (lanes 4 and 5). Increased amounts of

scaffold have no effect (lanes 6–8).

(D) RNA extension assay. The elongation scaffold (A) was efficiently transcribed to produce run-off product (+15) by Pol III upon addition of NTPs (lane 3).

Preincubation or addition of Maf1 (lanes 4 or 5, respectively) did not impair activity.

(E) Pol III can simultaneously bind Maf1 and nucleic acids. Preassembled Pol III-Maf1 and Pol III-DNA complexes were incubated with 5-fold molar excess of DNA

or Maf1, respectively, and subjected to gel filtration, and the peak fraction was analyzed by SDS-PAGE and silver staining. Staining of a Pol III-Maf1 complex

(without DNA) is identical to that in lanes 4, 5, and 6.


(Stratagene) were transformed with the plasmid and grown in LB medium at

37�C to an OD600 of 0.6. Expression was induced with 0.5 mM IPTG for

16 hr at 18�C. Cells were lysed by sonification in buffer H (50 mM HEPES

[pH 7.8], 0.5 M NaCl, 10 mM imidazole, 5 mM MgCl2, 10 mM EDTA, 10% glyc-

erol, 10 mM b-mercaptoethanol). After centrifugation, the supernatant was

loaded onto a 3 ml Ni-NTA column (QIAGEN) equilibrated with buffer H, but

20 mM imidazole. The column was washed with 20 column volumes (CVs)

and eluted with buffer H, but 300 mM imidazole. Proteins were purified by

anion exchange chromatography (Mono Q, GE Healthcare). The column was

equilibrated with buffer I (50 mM HEPES [pH 7.8], 5 mM MgCl2, 100 mM

EDTA, 10 mM b-mercaptoethanol, 10% glycerol), and proteins were eluted

with a linear gradient of 20 CVs from 10 mM to 1 M NaCl. After concentration,

the sample was applied to a Superdex-75 size-exclusion column (GE Health-

care) equilibrated with buffer L (25 mM HEPES [pH 7.0], 25 mM NaCl, 5 mM

DTT) for crystallization experiments or buffer M [50 mM HEPES (pH 7.8),

40 mM (NH4)2SO4, 100 mM MgCl2, 10 mM ZnCl2, 5 mM DTT] for binding exper-

iments. For partial proteolysis, 100 ml purified Maf1 at 1 mg/ml were mixed with

1 mg trypsin or chymotrypsin. The reactions were carried out at 37�C in buffer R

containing 1 mM CaCl2. Aliquots of 10 ml were taken at 1, 3, 5, 10, 30, and

60 min, and the reaction was stopped by addition of 5 3 SDS sample buffer

and incubation at 95�C for 5 min. Samples were analyzed by SDS-PAGE.

The N termini of digestion products were analyzed by Edman sequencing.

For crystallization, human Maf1 variant 1–35;83–205 was concentrated to

40 mg/ml. Crystals were grown within 2 days at 20�C in hanging drops over

a reservoir solution containing 50 mM MES (pH 6.0) and 175 mM sodium

oxalate. Native crystals were transferred into reservoir solution containing

25% glycerol and were flash cooled in liquid nitrogen. Crystals were soaked

for 0.5–2 min in a reservoir solution containing 25% glycerol and 0.5 M NaBr

and flash frozen in liquid nitrogen. Diffraction data were collected at 100 K

on a PILATUS 6M detector at the Swiss Light Source (SLS), Villigen,

Switzerland (Table 1). Three-wavelength anomalous diffraction data were

collected from a bromide-soaked crystal. Data were processed with MOSFLM

(Leslie et al., 1986) and scaled with SCALA (Evans, 2007), and data quality was

assessed with Phenix.Xtriage (Adams et al., 2010). Program Phenix.HySS

(Adams et al., 2010) identified six bromide sites that were used for phasing

with program SOLVE (Terwilliger and Berendzen, 1999). Density modification

was carried out with RESOLVE (Terwilliger, 2003). The model was built with

COOT (Emsley and Cowtan, 2004) and refined with Phenix.Refine (Adams

et al., 2010) to a free R factor of 21% (Table 1).

Nanogold Labeling

Size exclusion-purified Pol III was incubated for 60 min at 4�C in buffer N (buffer

M + 15 mM imidazole) with a 10-fold molar excess of recombinant full-length

Maf1. The complex was then incubated with a 20-fold molar excess of

Ni-NTA-Nanogold (Nanoprobes, INC) for 30 min. The sample was concentrated

to 1 ml with an Amicon Ultra-4 centrifugal filter unit (MWCO 10 kDA, Millipore)

and applied to gel-filtration chromatography on a Superose 6 column (Super-

ose 6 10/300 GL, GE Healthcare) with buffer G. Fractions were pooled and

samples prepared for cryo-EM as above. Cryo-EM data were collected as for

free Pol III but at an underfocus range of 3–4 mm to obtain high image contrast.

A large portion of particles showed both His tags bound with Nanogold clusters.

These were picked from the micrographs and aligned to projections of the Pol

III-Maf1 reconstruction. The strong signal of the Nanogold was dampened in

the images by manually applying a threshold to the histograms. The in-plane

rotation parameters resulting from the alignment were applied to the original

images, and the rotated images were compared to corresponding 2D surface

views with the location of Maf1 and the N terminus of C128 indicated (Figure 4).

The length of the His6-tag and the �0.9 nm linker between the gold cluster and

the nickel-NTA group of the Nanogold reagent give an expected mean vari-

ability of �2 nm radius that was taken into account. The gold signal on the

N terminus of C128 displayed more apparent variability, which is explained

by the presence of four additional tandem FLAG sequences.

Interaction and Transcription Assays

Brf1-TBP complex was obtained as a triple fusion protein as described (Kassa-

vetis et al., 2005). Pol III-Brf1-TBP-DNA and Pol III-Maf1 complexes were

preassembled with 5-fold molar excesses of Brf1-TBP-DNA and Maf1, respec-

tively, in buffer M for 60 min at 4�C and purified by gel filtration (Superose 6 10/

300 GL, GE Healthcare) in buffer M. Purified complexes were then incubated

with a 5-fold molar excess of the competing factors, incubated in buffer M for

60 min at 4�C, applied again to gel filtration, and analyzed by SDS-PAGE. For

the nucleic acid binding assay, size exclusion-purified complexes were

analyzed by silver-stained gels. For factor-independent transcription assays,

1.5 pmol Pol III or Pol III-Maf1 complex were incubated for 30 min at 20�Cwith 2 pmol or variable amounts of a pre-annealed tailed-template scaffold

(nontemplate DNA: 50-GGCTACTATAAATAAATGTTTTTTTCGCAACTATGTGT

TCGCGAAGTAACCCTTCGTGGACATTTGGTCAATTTGAAACAATACAGAGA

TGATCAGCAGT-30; template DNA: 50-ACTGCTGATCATCTCTGTATTGTTTC

AAATTGACCAAATGTCCACGAAGGGTTACTTCGCGAACACATAGTTGCGAA

AAAAACATTTATTTATAGTAGCCTGCA-30) in the presence of 0.5 mM GpG

RNA primer. Complexes were incubated for 30 min at 20�C in the presence

of 0.3 mM ATP, GTP, CTP, NS [a-32P]UTP in 20 ml reaction mixtures containing

40 mM Tris-HCl (pH 8.0), 60 mM NaCl, 7 mM MgCl2, 7% glycerol, 5 mM DTT.

Reactions were stopped by addition of an equal volume of 23 loading buffer

(8 M urea, 23 TBE) and incubation for 5 min at 95�C. RNA products were sepa-

rated by denaturing gel electrophoresis and visualized with a Typhoon 9400

phosphoimager (GE Healthcare). For RNA extension assays, 5 pmol of Pol III

or Pol III preincubated (10 min at 20�C) with a 5-fold molar excess of Maf1

was incubated for 30 min at 20�C with 5 pmol of a preannealed minimal nucleic

acid scaffold (template DNA: 30-TTACTGGTCCGGATTCATGAACTCGA-50;nontemplate DNA: 50-TAAGTACTTGAG-30; RNA: 50-FAM-UGCAUUUCGAC

CAGGC-30). Maf1 was added at a 5-fold molar excess, followed by incubation

for 5 min at 20�C. For RNA elongation, complexes were incubated for 10 min

with 1 mM NTPs at 28�C in transcription buffer (60 mM ammonium sulfate,

20 mM HEPES [pH 7.6], 8 mM magnesium sulfate, 10 mM zinc chloride, 10%

glycerol, 10 mM DTT). Reactions were stopped and RNA products were

separated and visualized as above.

ACCESSION NUMBERS

The coordinate file and structure factors for the Maf1 crystal structure were

deposited in the Protein Data BBank under accession code 3NR5. The EM

structures of Pol III, the Pol III-DNA-RNA complex, and the Pol III-Maf1

complex have been deposited in the EMDB database under accession codes

EMD-1753, EMD-1754, and EMD-1755, respectively.


Supplemental Information includes five figures and one movie and can be

found with this article online at doi:10.1016/j.cell.2010.09.002.

ACKNOWLEDGMENTS

We thank R. Beckmann, T. Becker, C. Ungewickel, J. Burger, and T. Mielke for

help with E.M. We thank A. Imhof (Zentrallabor fur Proteinanalytik) and T. Froh-

lich (Laboratory for Functional Genome Analysis) for mass spectrometry. We

acknowledge the crystallization facility at the department of E. Conti at the

Max Planck Institute of Biochemistry, Martinsried. We thank D. Deak for help

with figure preparation. A.V. was supported by a European Molecular Biology

Organization long-term fellowship and by the European Union training

program Marie Curie (MEIF-CT-2006-040653). P.C. was supported by the

Deutsche Forschungsgemeinschaft, the SFB646, the TR5, the Nanosystems

Initiative Munich, the Elitenetzwerk Bayern, and the Jung-Stiftung.

A.V. prepared Pol III complexes, A.V. and A.G.K. determined EM structures,

R.R. prepared and crystallized Maf1, R.R. and A.V. determined the Maf1

X-ray structure, R.R. and A.V. conducted functional assays, G.A.K. advised

on Pol III preparation, A.V., R.R., A.G.K., and P.C. wrote the manuscript, and

P.C. designed and supervised research.

Received: May 3, 2010





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Identification of Aneuploidy-Tolerating MutationsEduardo M. Torres,1,2 Noah Dephoure,3 Amudha Panneerselvam,1 Cheryl M. Tucker,4 Charles A. Whittaker,1

Steven P. Gygi,3 Maitreya J. Dunham,5 and Angelika Amon1,2,*1David H. Koch Institute for Integrative Cancer Research2Howard Hughes Medical Institute

Massachusetts Institute of Technology, Cambridge, MA 02139, USA3Department of Cell Biology, Harvard University Medical School, Boston, MA 02115, USA4Lewis-Sigler Institute, Princeton University, Princeton, NJ 08540, USA5Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA


SUMMARY

Aneuploidy causes a proliferative disadvantage in allnormal cells analyzed to date, yet this condition isassociated with a disease characterized by unabatedproliferative potential, cancer. The mechanisms thatallow cancer cells to tolerate the adverse effects ofaneuploidy are not known. To probe this question,we identified aneuploid yeast strains with improvedproliferative abilities. Their molecular characteriza-tion revealed strain-specific genetic alterations aswell as mutations shared between different aneuploidstrains. Among the latter, a loss-of-function mutationin the gene encoding the deubiquitinating enzymeUbp6 improves growth rates in four different aneu-ploid yeast strains by attenuating the changes inintracellular protein composition caused by aneu-ploidy. Our results demonstrate the existence ofaneuploidy-tolerating mutations that improve thefitness of multiple different aneuploidies and highlightthe importance of ubiquitin-proteasomal degradationin suppressing the adverse effects of aneuploidy.

INTRODUCTION

Aneuploidy, defined as any chromosome number that is not a

multiple of the haploid complement, is associated with death

and severe developmental abnormalities in all organisms

analyzed to date (reviewed in Torres et al., 2008; Williams and

Amon, 2009). Aneuploidy is the leading cause of miscarriages

and mental retardation in humans and is found in 90% of human

cancers (Hassold and Jacobs, 1984; Holland and Cleveland,

2009). Despite the high incidence of aneuploidy in tumors, its

role in tumorigenesis remains uncertain (Holland and Cleveland,

2009; Schvartzman et al., 2010).

To shed light on the relationship between aneuploidy and

tumorigenesis, we previously determined the effects of aneu-

ploidy on normal cells. Twenty strains of budding yeast, each

bearing an extra copy of one or more of almost all of the yeast

chromosomes (henceforth disomic yeast strains), display

decreased fitness relative to wild-type cells and share traits

that are indicative of energy and proteotoxic stress: metabolic

alterations, increased sensitivity to conditions that interfere

with protein translation, folding, and turnover (Torres et al.,

2007), a cell proliferation defect (specifically a G1 delay), and

a gene expression signature known as the environmental stress

response (Gasch et al., 2000). These shared traits are due to the

additional gene products produced from the additional chromo-

somes. Primary aneuploid mouse cells exhibit similar pheno-

types (Williams et al., 2008). On the basis of these findings, we

proposed that aneuploidy leads to an ‘‘aneuploidy stress

response.’’ In this response, cells engage protein degradation

and folding pathways in an attempt to correct protein stoichiom-

etry imbalances caused by aneuploidy. This puts a significant

burden on these protein quality-control pathways, resulting in

increased sensitivity to compounds that interfere with protein

degradation and folding. Synthesis and neutralization of the

proteins produced from the additional chromosomes also lead

to an increased need for energy.

The increased sensitivity of many aneuploid yeast strains to

cycloheximide and proteasome inhibitors suggests that ubiqui-

tin-mediated protein degradation is one of the protein quality

control pathways as being affected in aneuploid cells. During

ubiquitin-mediated protein degradation, multiple ubiquitin

molecules are covalently linked to a substrate, which allows

recognition by the 26S proteasome (Varshavsky, 2005). Upon

recognition, ubiquitin chains are removed, and substrates are

fed into the catalytic cavity of the proteasome. Two deubiquiti-

nating enzymes, Rpn11 and Ubp6, remove ubiquitin from

substrates (Chernova et al., 2003; Hanna et al., 2003; Verma

et al., 2002; Yao and Cohen, 2002). Both of these proteases

are associated with the proteasome and are essential for ubiqui-

tin recycling. In the absence of either protein, levels of free

ubiquitin rapidly decline as a result of degradation of ubiquitin

chains by the proteasome. In addition to a role in ubiquitin recy-

cling, Ubp6 regulates proteasomal degradation. In its absence,

proteasomal degradation of several substrates is accelerated

(Hanna et al., 2006; Peth et al., 2009). The results described


here indicate that Ubp6, through its role in protein degradation

control, affects the proliferative abilities of several aneuploid

yeast strains.

The consequences of system-wide aneuploidy of only a single

chromosome are severe in all organisms analyzed to date

(reviewed in Torres et al., 2008). In striking contrast, in most

cancer cells, aneuploidy is common, typically involving many

chromosomes, but proliferation potential in these cells is high

(reviewed in Albertson et al., 2003). To resolve these contradic-

tory observations, we hypothesized that genetic alterations

must exist that allow cancer cells to tolerate the adverse effects

of aneuploidy. To test this idea, we isolated aneuploid yeast

strains with increased growth rates and characterized their

genetic alterations. This analysis revealed strain-specific genetic

changes and mutations shared between different aneuploid

strains. We characterized further one of these shared genetic

alterations, a loss-of-function allele in the gene encoding the

deubiquitinating enzyme Ubp6. Our studies show that inactiva-

tion of UBP6 improves the proliferation rates of four different

disomic yeast strains and suggest a mechanism for this suppres-

sion. Deletion of UBP6 attenuates the effects of aneuploidy on

cellular protein composition. Our results demonstrate the

existence of aneuploidy-tolerating mechanisms. Enhanced

proteasomal degradation appears to be one of them.

RESULTS

Isolation of Aneuploid Yeast Strainswith Increased Proliferative AbilitiesTo identify genetic alterations that suppress the adverse effects

of specific aneuploidies or perhaps even multiple different

aneuploidies, we sought variants of 13 different disomic yeast

strains that proliferate well despite the presence of a disomic

chromosome. To isolate variants of disomic yeast strains

with decreased doubling time, we used continuous growth

under conditions that select for the presence of the disomic

chromosome rather than a traditional mutagenesis approach

to keep the number of genetic alterations low (Experimental

Procedures).

Environmental conditions such as media composition greatly

influence the outcome of evolution experiments (Gresham

et al., 2008; Zeyl, 2006). Therefore, we initially chose two sets

of disomic yeast strains, one that required growth in medium

lacking uracil and histidine (�Ura�His medium) to select for

the presence of the extra chromosome, and another that

required growth in medium lacking histidine and containing the

antibiotic G418 (�His+G418 medium). The doubling time of the

disomic yeast strains was significantly longer in �His+G418

medium than in �Ura�His medium (data not shown). We

suspect that this is due to G418’s ability to cause frameshifts

during translation (Davies and Davis, 1968; Davies et al., 1964).

The increase in frameshifts further enhances the burden on the

protein quality-control pathways that help aneuploid cells deal

with the proteins produced from the additional chromosomes.

The greater difference in doubling time between wild-type

and aneuploid cells in �His+G418 medium together with the

finding that some disomic strains (e.g., disome V) appeared

to lose large parts of the additional chromosome more readily

in �Ura�His medium (data not shown) prompted us to perform

the selection for disomic strains with increased proliferative rates

in �His+G418 medium. Passaging of cells in this medium initially

led to an increase in doubling times in many strains (Figure 1A;

Table S1 available online). We do not yet understand the molec-

ular basis for this transient slowing of cell proliferation, but we

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00.2- 33.1- 76.0-

00.0 76. 0 33.1 00. 2

Figure 1. Evolution of Aneuploid Yeast

Strains

(A) Doubling times of disome V (open squares), dis-

ome VIII (open triangles), disome XI (open circles),

and wild-type cultures (open diamonds) were

measured at the indicated times. The arrows indi-

cate the generation when growth rates increased.

(B) Doubling times of wild-type cells (black bar),

parental disomes (red bars), and evolved isolates

(open bars) were determined in �His+G418

medium at room temperature (n = 3, error bars

represent ± standard deviation [SD], *p value <

0.01, Student’s t test). Nomenclature: The Roman

numerals describe the identity of the disomic chro-

mosome. The number after the dash indicates

when the clone was isolated (after 9 or 14 days

of continuous growth), and the number after the

period describes the identity of the clone.

(C) Gene expression analysis of wild-type,

parental, and evolved disomic strains grown in

batch culture, ordered by chromosome position.

Experiments (columns) are ordered by the number

of the chromosome that is present in two copies.

Data were normalized to account for the extra

chromosome present in disomic strains. Upregu-

lated genes are shown in red and downregulated

ones in green.

See also Tables S1, S2, and S3 and Figures S1

and S2.


note that it is reminiscent of the crisis period observed during

serial passage of primary mammalian cells in culture (Todaro

and Green, 1963). Populations with decreased doubling times

emerged shortly thereafter (Table S1).

We isolated single colonies after 9 days (37–66 generations;

Table S1) and 14 days (64–105 generations; Table S1).

Doubling-time measurements confirmed that 11 out of 13

disomic yeast strains had produced clones with significantly

increased proliferation rates (Figure 1B) and changed the cell-

cycle distribution to be more similar to that of wild-type cells

(i.e., Figure S1A). We predicted that we would obtain two types

of suppressor mutations: mutations that improve the growth of

disomic yeast strains only in �His+G418 medium in which the

cells are coping with the additive stresses of G418 and aneu-

ploidy and are therefore more sensitive to suppressor mutations

with milder effects, and mutations that improve proliferation irre-

spective of which medium cells are cultured in. This appeared to

be the case. All evolved isolates obtained from disomes IX, XI,

XIII, and XVI (the disomic strains whose proliferation is only mini-

mally affected in YEPD medium to begin with) showed fitness

gain only in �His+G418 medium but not in YEPD (Figure S1B).

This phenomenon of genomic alterations being condition

specific has been observed previously (i.e., Dettman et al.,

2007). We conclude that aneuploidy-tolerating mutations exist

that are growth condition specific and that improve proliferation

more generally.

Evolved Isolates Obtained from Four Disomic StrainsExhibit Gross Chromosomal RearrangementsTo determine the basis for the decrease in doubling time in the

evolved disomic strains, we first examined their karyotypes.

Comparative genome hybridization (CGH) analysis revealed

that the overall chromosomal composition was not altered in

the majority of disomic strains (Table S2). Thus, the improved

growth rates of these isolates must be caused by alterations

that are undetectable by CGH analysis.

Descendants of strains disomic for chromosome IV experi-

enced loss of the entire additional chromosome and most

diplodized (Table S2). Isolates obtained from strains disomic

for chromosome XII, XIV, or XV had lost large parts of one

copy of the duplicated chromosome but also carried a duplica-

tion of a region of the left arm of chromosome XIII (TEL13L–

YML046W; 183 kb, 345 genes; Table S2). It is highly likely that

loss of all or part of the chromosome present in two copies is

in large part responsible for the increase in proliferation rate

seen in the evolved strains, but we speculate that genes exist

in region TEL13L–YML046W, whose 2-fold increase in copy

number improves proliferation of three different disomic yeast

strains.

Truncations of the duplicated chromosome occurred in or next

to Ty elements, retrotransposons that are scattered throughout

the yeast genome. This correlation indicates that homologous

recombination between these repeated elements was respon-

sible for the loss of these regions. The ends of regions

TEL13L–YML046W were also at or near Ty elements. Given

that region TEL13L–YML046W does not carry a centromere

but is nevertheless stably inherited, it is highly likely that the

duplicated region TEL13L–YML046W represents a translocation

caused by Ty element-mediated recombination. Our results

indicate that cells carrying an extra chromosome rapidly evolve

and acquire genomic alterations. These include point mutations

(see below), truncations, amplifications, and whole-genome

duplications.

Expression of the Genes Encoded by the DuplicatedChromosomes Is Not Attenuated in the Evolved IsolatesWe showed previously that the majority of genes present on the

disomic chromosome are expressed according to gene copy

number exhibiting an average increase in gene expression of

approximately 1.82-fold (Torres et al., 2007). Downregulation of

gene expression of the disomic chromosome, like loss of large

parts of the additional chromosome, could lead to increased

proliferation rates. Gene expression analysis of the evolved

strains that retained both copies of the disomic chromosome

showed that gene expression of the chromosome present at

two copies was not attenuated even though proliferation rates

were increased (Figure 1C). Average expression of genes

present on the disomic chromosome was increased an average

of 1.84-fold compared to the rest of the genome. Thus, attenua-

tion of gene expression of the disomic chromosome is not

responsible for the improved proliferation rates.

Our previous analysis of the disomic strains revealed a

transcription profile shared by different disomes (Torres et al.,

2007). This aneuploidy signature was only seen under conditions

that eliminated the differences in growth rate between aneuploid

strains (cells were grown in the chemostat under phosphate-

limiting conditions). Gene expression analysis of the evolved

isolates grown under these conditions confirmed that global

gene expression patterns were maintained, with each evolved

strain clustering most closely with its parental disomic strain

(Figure S2A). Interestingly, the gene expression patterns of

the two evolved disomic strains that we analyzed were more

similar to each other than to the parental disomic strain

(Figure S2A). This result suggests that the genetic alterations in

the different isolates affect the same pathways and lead to a

similar transcriptional response in the evolved strains.

To determine whether the evolved strains share a transcrip-

tional profile that is distinct from that shared by the parental

strains, we subtracted the original disome expression values

from that of the evolved strains. This analysis revealed a common

expression pattern among the evolved strains (Figure S2; Table

S3). Ion transport, especially iron, and a subset of ribosomal

proteins were significantly enriched in the decreased expression

cluster (Table S3). Genes with increased expression were

enriched for genes involved in amino acid metabolism (p value =

9.69 3 10�20). This group includes many of the genes respon-

sible for biosynthesis of aromatic amino acids, branched chain

amino acids, and arginine (Table S3). The significance of this

expression signature is at present unclear, but we speculate

that increased protein synthesis as a result of the presence of

an additional chromosome (see below) may bring about the

need for increasing production of amino acids. Strain-specific

expression changes also occurred. For example, a small group

of genes increased in expression in both isolates from disome

IX (Figure S2B). However, these gene groupings were rarely

enriched for particular classes of genes, although they may be


more informative when combined with knowledge of the muta-

tions carried by these strains. We conclude that descendants

of disomic strains with improved growth share a gene expression

signature.

Identification of Point Mutations Associated withIncreased Proliferation Rates in Aneuploid Yeast CellsEvolved aneuploid strains that proliferate faster yet have main-

tained both copies of the disomic chromosome probably harbor

heritable alterations not detectable by CGH. We selected 14

strains in which to identify these genetic alterations because

their proliferation rates were significantly improved compared

to the parent strain (Figure 1B). Tiling arrays or deep sequencing

identified 43 single-nucleotide polymorphisms (SNPs) that led to

nonsynonymous changes (Table 1) and four SNPs that led to

synonymous genetic alterations that were verified by Sanger

sequencing (Table S4, part A). In two evolved isolates of disome

XIII, we could not detect any nonsynonymous genetic changes.

A 1 base pair deletion, ten synonymous alterations, and 21

nonsynonymous alterations were present in the parental disomic

strains (Table S4, part B). We note that the mutations already

present in the parental disomic strains were probably acquired

during their construction and could also confer a growth

advantage.

Each evolved strain contained between two and seven SNPs,

and little overlap was detected among descendants from the

same parent strain (Table 1), indicating that different alterations

lead to improved proliferation in the different disomic strains.

Identical point mutations were only isolated among different

descendants of disomes XI and XIV, indicating that a selective

sweep had not occurred in the evolution experiments. Interest-

ingly, all three evolved disome XVI strains contained unique

mutations in the poorly characterized SVF1 gene (Table 1). The

emergence of mutations in this gene in three independent

isolates of disome XVI with improved growth properties

suggests that inactivation or hyperactivation of this factor (we

do not know how the identified point mutations affect SVF1

function) confers a selective advantage on strains disomic for

chromosome XVI.

Mutations in two genes were identified in descendants of

different disomes. Point mutations in the gene encoding the

vacuolar-targeting factor Vsp64 were identified in descendants

of disome IX and XI (Table 1). Mutations (premature stop codons)

in the gene encoding the deubiquitinating enzyme Ubp6 were

identified in descendants of disome V and IX. This finding raises

the interesting possibility that mutations exist that improve

growth rates of more than one disome.

Genes involved in chromatin remodeling, stress response, and

protein folding, as well as ribosomal RNA (rRNA) processing,

were among those mutated in the evolved disomic strains and

could contribute to the improved proliferative abilities of the

evolved disomic strains. Striking, however, was the fact that

fast growing descendants of strains disomic for chromosomes

V, VIII, IX, XI, and XIV harbored mutations in genes encoding

proteins involved in proteasomal degradation (UBP6, RPT1,

RSP5, UBR1). These results suggest that changes in protein

degradation lead to an improvement in fitness in multiple

aneuploid yeast strains.

Loss of UBP6 Function Suppresses the ProliferationDefect of Several Disomic Yeast StrainsWe decided to test whether a causal relationship exists between

mutations in UBP6 and improved proliferation rates of the

evolved strains, because sequence analysis identified prema-

ture stop codons in UBP6 in two different evolved disomic

strains. Ubp6 contains an ubiquitin-like (UBL) domain in its N

terminus that mediates binding to the proteasome and a pepti-

dase domain in the C-terminal half of the protein (Figure 2A).

Strain Dis V-14.1 carries a nonsense mutation resulting in the

conversion of glutamic acid 256 to a stop codon (ubp6E256X;

Figure 2A). Strain Dis IX-14.1 harbors an UBP6 allele that carries

a premature stop codon at position 404 (Figure 2A). Both muta-

tions leave the UBL domain of the protein intact but cause

enough of a truncation to inactivate Ubp6’s protease activity.

To determine whether the expression of this truncated version

of UBP6 was at least in part responsible for the decrease in

generation time of strains Dis V-14.1 and Dis IX-14.1, we

analyzed disome V cells carrying the ubp6E256X mutation.

To assess the effects of this mutation on fitness, we performed

a competition assay. In this assay, strains disomic for chromo-

some V carrying a GFP-PGK1 fusion integrated at URA3

were cocultured with disome V cells carrying the ubp6E256X

mutation also marked with URA3. We then monitored the

fraction of GFP positive cells in the cultures over time by flow

cytometry. Control experiments showed that, with the exception

of strains disomic for chromosome XIV, the GFP-PGK1 fusion

did not affect the proliferation rate of the different disomic strains

(data not shown).

Disome V cells carrying the ubp6E256X mutation proliferated

significantly better than disome V cells wild-type for UBP6

(Figure 2B; Figure S3). A truncation mutation in UBP6 was also

identified in disome IX strains with improved proliferative

abilities. In this strain too, replacement of the UBP6 locus with

the ubp6E256X allele led to an increase in fitness (Figure 2B;

Figure S3). Remarkably, the same allele also led to an increase

in proliferation rates in strains disomic for chromosome VIII and

XI (Figure 2B). The ubp6E256X allele did not improve the prolifer-

ative abilities of wild-type cells or of five other disomes (disome I,

XII, XIII, XV, XVI) that we analyzed (Figure S3) and had adverse

effects only in disome II and disome XIV cells (Figure 2B;

Figure S3). Deletion of UBP6 had similar effects on disomic

strains as expression of the UBP6 truncation. An increase in

fitness was observed in coculturing assays and in doubling-

time measurements (Figures 2C and 2D; Figure S4; data not

shown). Analysis of cell-cycle progression of disome V and dis-

ome XI cells lacking UBP6 revealed that the deletion suppresses

the G1 delay of these two disomic strains (Figure S1A). Finally,

we found that inactivation of UBP6 led to an increase in fitness

of strains disomic for chromosome XI, and V in YEPD medium

but not of strains disomic for chromosome VIII or IX (Figure 2E).

We conclude that inactivation of UBP6 improves the growth

rates of four different disomic strains in the presence of the

translation inhibitor and proteotoxic compound G418. In two

disomic strains, growth improvement was also seen in the

absence of the drug. Inactivation of UBP6 did not significantly

influence the growth of otherwise wild-type cells in YEPD

(Figure 2E) or �His+G418 (Figure 2C; Figures S3 and S4).


Table 1. Nonsynonymous Genetic Changes in the Evolved Disomic Strains

Straina Gene Mutation Methodb Protein Function

Dis V-14.1 SNT1 L431R S, T Subunit of the Set3C deacetylase complex

Dis V-14.1 RAD3 (het) D148N S, T 50 to 30 DNA helicase, involved in nucleotide excision repair

Dis V-14.1 UBP6c E256X S, T Ubiquitin-specific protease

Dis V-14.1 DYN1 L526R S Cytoplasmic dynein heavy chain

Dis V-14.1 TSL1 N127D S Subunit of trehalose 6-phosphate synthase

Dis V-14.1 Chr X, 31906 C to G S, T Intergenic region

Dis V-14.1 Chr XIII, 442441 A to C S, T Intergenic region

Dis VIII-14.1 RPT1 Q281K T ATPase part of the 19S regulatory particle of the proteasome

Dis VIII-14.1 Chr V, 140399 C to G T Intergenic region

Dis IX-14.1 VPS64c Q23X T Vacuole targeting factor

Dis IX-14.1 UBP6c E404X T Ubiquitin-specific protease

Dis XI-9.1 VPS64c E103G S Vacuole targeting factor

Dis XI-9.1 SRC1 I721V S Inner nuclear membrane protein

Dis XI-9.1 Chr IX, 338123 C to T S Intergenic region

Dis XI-9.1 Chr XIII, 818616 G to T S Intergenic region

Dis XI-9.2 SAS10 G311V S Subunit of processome complex

Dis XI-9.2 RSP5d V591M S, T Ubiquitin-protein ligase

Dis XI-9.2 Chr IX, 183614d G to A S, T Intergenic region

Dis XI-14.1 RSP5d V591M S, T Ubiquitin-protein ligase

Dis XI-14.1 Chr IX, 183614d G to A S, T Intergenic region

Dis XIV-9.1 YGR266W D450Y S Protein of unknown function

Dis XIV-9.1 Chr VII, 827547 C to T S Intergenic region

Dis XIV-9.1 LAG2d D644E S Protein involved in determining longevity

Dis XIV-9.1 YNL234Wd D16N S Heme-binding protein involved in glucose signaling

Dis XIV-9.1 Chr XIV, 623023d C to S S Intergenic region

Dis XIV-9.2 UBR1 F951C S Ubiquitin-protein ligase

Dis XIV-9.2 DCS2 H269Y S Stress induced protein

Dis XIV-9.2 CCT7 P114R S Subunit of the chaperonin Cct ring complex

Dis XIV-9.2 Chr XIV, 148095 A to W S Intergenic region

Dis XIV-9.2 LAG2d D644E S Protein involved in determining of longevity

Dis XIV-9.2 YNL234Wd D16N S Heme-binding protein involved in glucose signaling

Dis XIV-9.2 Chr XIV, 623023d C to S S Intergenic region

Dis XIV-14.2 PRR2 E260X T Serine/threonine protein kinase

Dis XIV-14.2 BUD9 E499D T Protein involved in bud-site selection

Dis XIV-14.2 Chr XVI, 572683 C to G T Intergenic region

Dis XVI-9.1 SAS3 S689R S Histone acetyltransferase catalytic subunit of NuA3 complex

Dis XVI-9.1 SVF1e W178X S Protein with a potential role in cell survival pathways

Dis XVI-14.1 SEC31 S1116T S Essential component of the COPII coat of secretory pathway vesicles

Dis XVI-14.1 UTP10 P173S S Subunit of processome complex involved in production of 18S rRNA

Dis XVI-14.1 SVF1e A320P S Protein with a potential role in cell survival pathways

Dis XVI-14.2 GRX4 F188L S Glutathione-dependent oxidoreductase

Dis XVI-14.2 SVF1e E220X S Protein with a potential role in cell survival pathways

Dis XVI-14.2 Chr I, 71729 T to C S Intergenic regiona 9.1 and 9.2 refer to isolates 1 and 2 from day 9, respectively. 14.1 and 14.2 refer to isolates 1 and 2 from day 14, respectively.b S, solexa sequencing; T, tiling arrays.c This gene is mutated in descendants of different disomes.d This mutation is present in more than one isolate.e Three different mutations of SVF1 are present in three isolates of disome XVI.


Next, we wished to determine the degree to which loss of

UBP6 function contributes to the increased fitness of evolved

Dis V-14.1 cells. We compared the doubling times of evolved

Dis V-14.1 cells with that of disome V cells deleted for UBP6.

Deletion of UBP6 did not affect cell-cycle progression or

doubling time in wild-type cells (Figure S1A). However, it led to

A D E

B

C

Figure 2. Loss of UBP6 Function Increases the Fitness of Strains Disomic for Chromosome V, VIII, IX, or XI

(A) Schematic of the Ubp6 domain structure. The N terminus contains an ubiquitin-like domain (UBL, amino acids 1–83), and the C terminus harbors the ubiquitin

hydrolase domain (amino acids 83–499). The positions of the catalytic cysteine 118 and the two early stop codons at positions 256 and 404 identified in evolved

disome V-14.1 and disome IX-14.1, respectively, are shown.

(B) The percentage of cells in cocultures of strains carrying PGK1 fused to GFP (open squares) and strains harboring a C-terminal truncated version of ubp6

(E256X, closed triangles) was determined at the indicated times. All strains were grown in �His+G418 medium.

(C) The percentage of cells in cocultures of strains carrying PGK1 fused to GFP (open squares) and strains harboring a UBP6 deletion (ubp6D, closed triangles)

was determined at the indicated times. All strains were grown in �His+G418 medium.

(D) Doubling times of the WT, disome V, evolved disome V-14.1, and disome V ubp6D strains grown in �His+G418 medium (n = 3, error bars represent ± SD).

(E) Doubling times of the WT, disome V, disome VIII, disome IX and disome XI strains either wild-type for UBP6 or carrying a UBP6 deletion grown in YEPD medium

(n = 3, error bars represent ± SD; *p value < 0.01, Student’s t test).

See also Figures S3, S4, and S5.


a significant decrease in doubling time in disome V cells (4.2 ±

0.2 hr compared to 5.8 ± 0.8 hr; Figure 2D), but doubling times

were not as short as those of the evolved Dis V-14.1 strain

(3.8 ± 0.1; Figure 2D). Conversely, restoring UBP6 function to

the evolved Disome V-14.1 isolate reduced the proliferative

potential of these cells (Figure S5). We conclude that loss of

UBP6 function contributes to the increased proliferative abilities

of Dis V-14.1 cells but other genetic alterations found in this

strain also contribute to the increased proliferation rates of this

isolate.

Ubiquitin Depletion Is Not Responsible for the IncreasedProliferation Rates of Disomic Strains Lacking UBP6

Loss of Ubp6 function causes ubiquitin depletion. This leads to

cycloheximide sensitivity that can be suppressed by overex-

pression of ubiquitin (Hanna et al., 2003). Ubiquitin depletion

was also observed in disome V ubp6D cells (Figure 3A). To deter-

mine whether ubiquitin depletion was responsible for the

increased growth rate of disome V ubp6D cells, we examined

the consequences of increased ubiquitin expression. Disome V

and XI cells were cocultured with disome V ubp6D and disome

XI ubp6D cells, respectively. All strains carried a multicopy

plasmid expressing the ubiquitin-encoding gene, UBI4, under

the control of the copper inducible CUP1 promoter. Addition of

100 mM CuSO4 significantly increased the steady state levels

of free ubiquitin in all strains (Figure 3B). As expected, deletion

of UBP6 suppressed the subtly adverse effects of overexpres-

sion of ubiquitin in wild-type cells (Figures 3C and 3F). However,

high levels of ubiquitin did not abolish the growth rate improve-

ments of disomic strains brought about by the inactivation of

UBP6 (Figures 3D and 3E; Figure S6A). Similar results were

obtained in disome VIII or XI strains harboring the ubp6E256X

truncation allele (Figures 3G and 3H; Figure S6B) and in compe-

tition experiments where only the UBP6 deleted strains overex-

pressed ubiquitin (Figure S6C). Our results indicate that low

levels of ubiquitin are not responsible for the improved fitness

of disomic strains lacking UBP6.

Aneuploid Yeast Cells Show an Increased Relianceon Proteasomal Degradation for SurvivalUbp6 deubiquitinates substrates at the proteasome. This activity

serves two purposes: recycling of ubiquitin and rescue of protea-

somesubstrates from degradation.UBP6 antagonizes the protea-

some not only through its deubiquitinating activity but also through

a noncatalytic mechanism (Hanna et al., 2006; Peth et al., 2009).

To determine whether the catalytic or noncatalytic function of

Ubp6 was involved in modulating the fitness of disomic yeast

strains, we examined the consequences of replacing the catalytic

cysteine 110 with alanine (ubp6CA). Expression of the ubp6CA

allele did not affect the proliferative abilities of wild-type cells

(Figure 4A; Figure S7). In contrast, coculture of disome VIII, IX,

and XI cells with disomic cells carrying the ubp6CA allele showed

that strains harboring the catalytic dead version of the protein

quickly outcompete disomes carrying the wild-type UBP6 allele

(Figures 4B–4D). Our results demonstrate that Ubp6’s protease

activity antagonizes proliferation in several disomic yeast strains.

Inhibition of the catalytic activity of the mammalian homolog of

Ubp6, Usp14, leads to accelerated degradation of a number of

A B

EDC

F G H

Figure 3. Ubiquitin Depletion Is Not

Responsible for the Aneuploidy Tolerance

Caused by Loss of UBP6 Function

(A) Wild-type, ubp6D, disome V, and disome V

ubp6D cells were grown in �His+G418 medium

to an OD600 of 1.0 when 100 mg/ml cycloheximide

(time = 0 min) was added. Free ubiquitin and ubiq-

uitin conjugates were analyzed by immunoblotting

with an anti-ubiquitin antibody at the indicated

times.

(B) Ubiquitin levels in the presence (+) or absence

(�) of 100 mg/ml CuSO4.

(C– H) The percentage of cells in cocultures of

strains carrying PGK1 fused to GFP (open

squares) and strains harboring a UBP6 deletion

(closed triangles) was determined at the indicated

times. All strains carry a CUP1-UBI4 multicopy

plasmid whose expression was induced with

100 mg/ml CuSO4. The following strains were

compared: wild-type and UBP6 deletion cells (C),

disome V PGK1-GFP and disome V ubp6D cells

(D), disome XI PGK1-GFP and disome XI ubp6D

(E), wild-type and ubp6E256X truncation strains

(F), disome VIII PGK1-GFP and disome VIII

ubp6E256X cells, (G) and disome XI PGK1-GFP

and disome XI ubp6E256X cells (H). All strains

were grown in �His+G418 medium.

See also Figure S6.


proteins (Lee et al., 2010). These findings lead us to hypothesize

that increased proteasomal degradation of an unknown number

of proteins improves the fitness of disomic yeast strains. A

prediction of this hypothesis is that lowering of proteasomal

activity decreases the fitness of disomic yeast strains. This

appears to be the case. We previously showed that several

disomic strains exhibit increased sensitivity to the proteasome

inhibitor MG132 (Torres et al., 2007). Furthermore, a conditional

loss-of-function allele in the proteasome lid subunit Rpn6 encod-

ing gene (Ben-Aroya et al., 2008) was synthetic lethal with dis-

omy XII and disomy XIV (data not shown) and decreased the

proliferative abilities of almost all disomic strains tested

(Figure 4E). Finally, we found that the ubiquitin profile in strains

disomic for chromosome V, VIII, or XI resembles that of hypo-

morphic proteasome mutants: the levels of free ubiquitin are

slightly reduced (Figures 3A and 3B). Our results indicate that

proteasomal degradation is a rate-limiting pathway in most, or

perhaps all, disomic yeast strains.

Consequences of Chromosome V or XIII Disomyon Cellular Protein CompositionTo test the idea that increased protein degradation leads to

improved fitness of disomic strains, we examined the effects of

0 10 20 30 40 500

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100 Dis XI GFP

Time (h)0 10 20 30 40 50

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Dis IX ubp6CA

Time (h)

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Time (h)0 10 20 30 40 50

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ubp6CA

Time (h)

A B

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cent

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lsP

erce

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ells

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cent

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lsP

erce

nt C

ells

Dis VIII ubp6CA

Dis XI ubp6CA

WT

Dis V

rpn6-ts

Dis V rpn6-ts

Dis IDis I rpn6-ts

Dis IIDis II rpn6-ts

25oC 30oC 35oC

Dis VIII

WTrpn6-ts

Dis VIII rpn6-tsDis IX

Dis IX rpn6-tsDis X

Dis X rpn6-ts

25oC 30oC 35oC

Dis XI

Dis XVI

WTrpn6-ts

Dis XI rpn6-ts

Dis XVI rpn6-ts

25oC 30oC 35oC

Figure 4. Disomic Strains Exhibit an

Increased Reliance on the Proteasome for

Survival

(A–D) The percentage of cells in cocultures of

strains carrying PGK1 fused to GFP (open

squares) and strains harboring a catalytic dead

version of UBP6 (ubp6CA, closed triangles) was

determined at the indicated times. The following

strains were compared: wild-type and ubp6CA

cells (A), disome VIII PGK1-GFP and disome VIII

upb6CA cells (B), disome IX PGK1-GFP and dis-

ome IX ubp6CA cells (C), and disome XI PGK1-

GFP and disome XI ubp6CA cells (D). All strains

were grown in �His+G418 medium.

(E) Proliferation capabilities of WT, rpn6-ts,

parental disomes and disomes harboring the

rpn6-ts allele cells on YEPD medium at 25�C,

30�C, and 35�C; 10-fold serial dilutions are shown.

See also Figure S7.

deletion of UBP6 on the proteome of a

yeast strain whose fitness is improved

by the deletion of UBP6 (disome V) and

one that is not (disome XIII). To measure

relative protein abundance in disomic

and wild-type cells, we utilized stable

isotope labeling with amino acids in cell

culture (SILAC)-based quantitative mass

spectrometry (Extended Experimental

Procedures).

SILAC analysis of disome V and XIII

relative to wild-type cells revealed quanti-

tative information for 2953 proteins

(60.7% of all verified open reading frames

[ORFs]) and 3421 proteins (70.3% of all

verified ORFs), respectively (Figures 5C and 5E; Table S5). The

analysis of the average abundance of proteins encoded by the

genes located on chromosome V and XIII demonstrated that

the average protein levels of chromosome V-located and chro-

mosome XIII-located genes were increased by 1.8-fold and

1.9-fold compared to the nonchromosome V or XIII encoded

proteins, respectively. This correlation is best seen when

proteins are sorted with respect to the chromosomal position

of their encoding genes (Figures 5C and 5E). To control for arti-

facts caused by growth in medium containing heavy lysine, we

performed a reverse labeling experiment, growing disome V cells

in light medium and wild-type cells in heavy medium and

compared the results of both analyses. We obtained quantitative

information on 2755 proteins, of which 2433 were detected in

both forward and reverse experiments (r2 = 0.59). Of these,

431 proteins show significant up- or downregulation in disome

V with high reproducibility (0.49 < log2 ratio < �0.49; r2 = 0.78,

n = 431; Extended Experimental Procedures).

An interesting additional aspect of the quantitative assess-

ment of the protein composition of the disomic strains is that

we are able to determine whether there are proteins whose levels

do not increase according to gene copy number. A comprehen-

sive analysis of multiple disomic strains will be presented


elsewhere, but several general conclusions are summarized

here. We previously analyzed the abundance of a small number

of proteins in disomic yeast strains and found that the levels of

several of these, especially subunits of macromolecular

complexes such as ribosome subunits, did not exhibit a coordi-

nate increase between gene copy number and protein levels

(Torres et al., 2007). Consistent with these observations, we

find that a considerable fraction of proteins located on chromo-

some V, 30 of a total 135 proteins detected in both disome V

experiments, were not upregulated according to gene copy

number. Ninety percent of the proteins that exhibit this property

are part of macromolecular complexes. Similar results were

obtained with disome XIII cells. Twenty-one percent of proteins

(65 of 312) did not show coregulation of protein levels with

gene copy number. Sixty-eight percent of these proteins func-

tion in large macromolecular complexes. A discrepancy between

gene copy number and protein levels was most evident for

ribosomal subunits, but was also observed for subunits of

ribonucleotide reductase and the vacuolar ATPase. The enrich-

ment of protein complex subunits in the group of disome-

encoded proteins that does not show a coordinate upregulation

with gene copy number is of high statistical significance, when

compared to all proteins encoded by chromosome V or XIII

that are part of protein complexes (p value = 1.1 3 10�10 for

disome V; p value = 3.8 3 10�3 for disome XIII). Analysis of

RNA and protein levels indicates that downregulation of gene

expression occurred either at the level of transcription (14 genes

A BB

DC

E F

Figure 5. Quantification of the Proteome of

Disome V and Disome XIII Strains

The plots show the log2 ratio of the relative protein

abundance compared to wild-type. Protein levels

are shown in the order of the chromosomal loca-

tion of their encoding genes: wild-type/wild-type

ratios (A), Dubp6/wild-type ratios (B), disome

V/wild-type ratios (C), disome V Dubp6/wild-type

ratios (D), disome XIII/wild-type ratios (E), and dis-

ome XIII Dubp6/wild-type ratios (F). SD, standard

deviation; n, number of proteins quantified. See

also the Extended Experimental Procedures. The

number in the graphs shows the fold increase in

protein levels of proteins encoded by genes

located on the disomic chromosome relative to

the rest of the proteome.

in disome V and 22 genes in disome XIII)

or posttranscriptionally (16 genes in dis-

ome V and 43 genes in disome XIII).

Characterization of the feedback mecha-

nisms that ensure accurate stoichiome-

tries of these proteins will be an important

aspect of understanding the effects of

aneuploidy on cell physiology.

Deletion of UBP6 Attenuatesthe Effects of Disomy Von Cellular Protein CompositionHaving established the effects of disomy

V on the yeast proteome, we next wished

to test the hypothesis that loss of UBP6 function improves the

fitness of aneuploid cells such as disome V cells by increasing

the degradation of proteins that are in excess in this strain. If

this was the case, the protein composition of disome V ubp6D

cells should be more similar to wild-type cells than that of disome

V cells is to wild-type cells. This appears to be the case.

We obtained quantitative information on 2895 proteins for

disome V ubp6D cells (Figure 5D; Table S5) and on 3491 proteins

for cell lacking UBP6 (Figure 5B; Table S5). For the analysis of the

effects of UBP6 on protein composition, we only included

proteins for which quantitative information was obtained in all

four strains (2352 proteins). To determine whether deletion of

UBP6 attenuates the effects of disomy V on the intracellular

protein composition, we rank-ordered all of the proteins accord-

ing to their relative protein abundance levels in the strain disomic

for chromosome V and then asked how the expression of these

proteins changes in disome V cells lacking UBP6. To quantify

a potential attenuating effect, we created three bins: one that

encompasses all the proteins whose levels fall within one

standard deviation (SD) of the distribution (between �0.49 and

0.49, 1947 proteins; Figure 6A), one that encompasses proteins

whose relative abundance was low in disome V cells (log2 ratio <

�0.49; 141 proteins Figure 6A), and one that encompasses

proteins whose relative abundance was high in the disome V

strain (log2 ratio > 0.49; 264 proteins; Figure 6A). We then calcu-

lated the mean of the protein abundance changes for each strain

for all three categories and compared them with each other.


The mean of proteins whose levels fall within one SD of

the distribution (�0.49 and 0.49) was similar between wild-type,

ubp6D, disome V, and disome V ubp6D cells (disome V = �0.02;

disome V ubp6D = 0.00; n = 1947; Figure 6A). In contrast,

deletion of UBP6 led to the attenuation in expression levels

of proteins whose relative abundances were low (log2 ratio <

�0.49) in disome V cells (disome V = �0.81; disome V

ubp6D = �0.44; p value = 3 3 10�19; n = 141; Figure 6A). The

effects of deletion of UBP6 were most dramatic among the

proteins with the highest relative expression levels in disome V

cells (ratio > 0.49). Whereas the mean of this bin was 0.96

for the disome V strain, it was 0.34 for disome V ubp6D cells

(n = 264; p value = 3 3 10�35; Figure 6A).

The attenuating effects of deletion of UBP6 were also

observed for proteins encoded by genes located on chromo-

some V, although the effects were not as dramatic, which is

most likely due to the limited number of proteins that could be

analyzed. The standard deviation we used for this analysis was

that of the distribution of proteins located on chromosome V,

which was 0.60. The average log2 expression level of chromo-

some V proteins was 0.84. The mean of proteins whose levels

fall within one SD of the distribution (0.24 and 1.44) was the

same between disome V and disome V ubp6D cells (disome

V = 0.84; disome V ubp6D = 0.84; n = 105; Figure 6C). For

proteins with low relative expression levels in disome V cells

(log2 ratios below 0.24), some attenuation was seen as a conse-

quence of UBP6 deletion (disome V = �0.25; disome V ubp6D =

0.16; n = 16; p value = 6 3 10�3; Figure 6C). The attenuation seen

for chromosome V proteins with the relative highest levels (ratios

above 1.44) was striking. Whereas the mean of this bin was 1.93

for disome V strain, it was 0.93 for disome V ubp6D cells (n = 15;

p value = 4 3 10�5; Figure 6C).

A

B

D

C

E

F

H

G

Log 2

ratio

Log 2

ratio

Log 2

ratio

Log 2

ratio

Log 2

ratio

Log 2

ratio

Log 2

ratio

-0.49 < ratio < 0.49n = 1,947Dis V = -0.02Dis V ubp6Δ = 0.00WT = 0.00ubp6Δ = 0.00

ratio > 0.49n = 264Dis V = 0.96 Dis V ubp6Δ = 0.34WT = 0.13ubp6Δ = -0.09

ratio < -0.49 n = 141Dis V = -0.81Dis V ubp6Δ = -0.44WT = -0.15ubp6Δ = -0.07 Disome V/WT

Disome V ubp6Δ /WTWT/WTubp6Δ //WT -0.51 < ratio < 0.51

n = 2,171Dis XIII = 0.00Dis XIII ubp6Δ = 0.00WT = 0.01ubp6Δ = -0.01

ratio > 0.51n = 371Dis XIII = 1.04Dis XIII ubp6Δ = 0.63WT = -0.16ubp6Δ = 0.07

ratio < -0.51 n = 112Dis XIII = -0.87Dis XIII ubp6Δ = -0.95WT = 0.19ubp6Δ = -0.36

Disome XIII/WTDisome XIII ubp6Δ /WTWT/WTubp6Δ /WT

n = 1,947Dis V = -0.13Dis V ubp6Δ = 0.08WT = 0.10ubp6Δ = -0.19

n = 264Dis V = 0.46 Dis V ubp6Δ = 0.49WT = 0.15ubp6Δ = -0.25

n = 141Dis V = -0.53Dis V ubp6Δ = -0.26WT = 0.07ubp6Δ = -0.08

Disome V/WTDisome V ubp6Δ /WTWT/WTubp6Δ //WT n = 2,171

Dis XIII = -0.04Dis XIII ubp6Δ = -0.04WT = 0.09ubp6Δ = 0.06

n = 371Dis XIII = 0.76Dis XIII ubp6Δ = 0.72WT = 0.15ubp6Δ = 0.18

n = 112Dis XIII = -0.64Dis XIII ubp6Δ = -0.83WT = 0.15ubp6Δ = -0.17


0.24 < ratio < 1.44n = 105Dis V = 0.84Dis V ubp6Δ = 0.84WT = -0.02ubp6Δ = -0.01

n = 105Dis V = 0.68Dis V ubp6Δ = 0.93WT = 0.13ubp6Δ = -0.24

ratio > 1.44n = 15Dis V = 1.93 Dis V ubp6Δ = 0.93WT = 0.31ubp6Δ = -0.47

n = 15Dis V = 0.90 Dis V ubp6Δ = 1.01WT = 0.20ubp6Δ = -0.40

ratio < 0.24 n = 16Dis V = -0.25Dis V ubp6Δ = 0.16WT = -0.10ubp6Δ = -0.06

n = 16Dis V = 0.32Dis V ubp6Δ = 0.67WT = 0.07ubp6Δ = -0.19

Disome V/WTDisome V ubp6Δ /WTWT/WTubp6Δ //WT

0.36 < ratio < 1.55n = 190Dis XIII = 0.94Dis XIII ubp6Δ = 0.91WT = -0.01ubp6Δ = -0.02


ratio > 1.55n = 23Dis XIII = 2.54Dis XIII ubp6Δ = 1.39WT = -0.50ubp6Δ = 0.26


ratio < 0.36 n = 16Dis XIII = 0.01Dis XIII ubp6Δ = -0.05WT = 0.13ubp6Δ = -0.13



Disome V/WTDisome V ubp6Δ /WTWT/WTubp6Δ //WT Disome XIII/WT

Disome XIII ubp6Δ /WTWT/WTubp6Δ /WT

1.5

1

-1

-1.5

0.5

-0.5

0

1.5

1

-1

-1.5

0.5

-0.5

0

Log 2

ratio

1

-1

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All Proteins All Proteins

All RNAs All RNAs

Chr V Proteins Chr XIII Proteins

Chr V RNAs Chr XIII RNAs

P = 3*10-35

P = 4*10-5

P = 8*10-5

P = 2*10-22

P = 3*10-19

P = 2*10-10

P = 6*10-3

P = 8*10-3

Figure 6. Loss of UBP6 Function Preferen-

tially Affects Proteins Overproduced in

Disome V and Disome XIII Cells Relative to

the Wild-Type

(A) Comparison of the means of the log2 ratios of

relative abundance of proteins. Proteins are binned

based on their relative levels in disome V cells. Bin 1

(left bars) contains proteins whose levels are lower

than one SD of the mean (ratio < �0.49, n = 141).

Bin 2 (middle bars) contains proteins whose levels

fall within one SD of the mean (�0.49 < ratio < 0.49,

n = 1947). Bin 3 (right bars) contains proteins whose

levels are greater than one SD (ratio > 0.49, n =

264). Only proteins that were detected in all four

experiments were used for this analysis: disome

V compared to the wild-type (black bars), disome

V ubp6D compared to the wild-type (dark gray),

ubp6D compared to the wild-type (light gray), and

the wild-type/wild-type comparison (white bars)

are shown.

(B) RNA levels of the same genes analyzed in (A).

(C) The same analysis as in (A) was performed for

proteins encoded by genes located on chromo-

some V. The SD was that of the distribution of

chromosome V-encoded proteins. The bins are

as follows: ratio < 0.24, n = 16; 1.44 > ratio >

0.24, n = 105; and ratio > 1.44, n = 15. Nomencla-

ture is as in (A).

(D) RNA levels of the same proteins analyzed in (C).

(E) Comparison of the means of the log2 ratios of

relative abundance of proteins. Proteins are binned

based on their relative levels in disome XIII cells as

described for disome XIII cells: bin 1 (left bars),

ratio < �0.51, n = 112; bin 2 (middle bars), �0.51 <

ratio < 0.51, n = 2,171; bin 3 (right bars), ratio > 0.51,

n = 371. Only proteins that were detected in all four

experiments were used for this analysis: Disome

XIII compared to the wild-type (black bars), disome

XIII ubp6D compared to the wild-type (dark gray),

ubp6D compared to the wild-type (light gray), and

the wild-type/wild-type comparison (white bars)

are shown.

(F) RNA levels of the same proteins analyzed in (E).

(G) The same analysis as in (E) was performed for proteins encoded by genes located on chromosome XIII. The SD was that of the distribution of chromosome XIII

encoded proteins. The bins are: ratio < 0.36, n = 16; 1.55 > ratio > 0.36, n = 190; and ratio > 1.55, n = 23. Nomenclature is as in (E).

(H) RNA levels of the same proteins analyzed in (G).

Error bars represent ± standard error of the mean. p, p value paired Student’s t test.


To determine whether transcriptional or posttranscriptional

mechanisms were responsible for the attenuating effects of

deletion of UBP6, we measured RNA levels in these strains.

Microarray analysis showed that deletion of UBP6 caused an

upregulation of transcription of proteins with low relative expres-

sion levels in disome V cells (Figure 6B). This finding indicates

that transcriptional effects are responsible for the attenuating

effects of UBP6 deletion on proteins underrepresented in

disome V cells. In contrast, decreased transcription was not

responsible for the attenuating effects of the UBP6 deletion on

proteins with high relative expression levels in disome V cells

(Figures 6B and 6D). These data show that inactivating UBP6

attenuates the effects of disomy V on the proteome in at least

two ways: (1) Inactivation of the ubiquitin protease promotes

the downregulation of proteins with high relative expression

levels in disome V cells by a posttranscriptional mechanism.

We presume that increased protein degradation is this mecha-

nism. (2) Deletion of UBP6 promotes the upregulation of proteins

with low relative expression levels in disome V cells by increasing

their transcription, most likely by affecting the abundance of

proteins that regulate transcription of these genes.

Are the attenuating effects of deleting UBP6 specific to disome

V cells? Deletion of UBP6 had a similar effect on the proteins with

high relative expression levels in disome XIII cells, even though

the proteins whose levels are increased in disome XIII cells

relative to wild-type are different than in disome V cells (Fig-

ures 6E and 6G; p value = 2 3 10�22). Transcriptional profiling

indicated that this attenuating effect occurred at the posttran-

scriptional level (Figures 6F and 6H). In contrast to disome V

cells, deletion of UBP6 did not increase the abundance of

proteins with low relative expression levels in disome XIII cells

(Figure 6E).

Our results indicate that deletion of UBP6 causes attenuation

of proteins with high relative expression levels in disomic cells by

posttranscriptional mechanisms, most likely by increasing

protein degradation. We propose that in disome V cells this

effect on the protein composition increases growth rates,

because proteins that inhibit proliferation of disome V cells are

among the proteins whose levels are lowered by the deletion

of UBP6. This is not the case in disome XIII cells. We further

suggest that the attenuation of low expressed proteins, which

occurs in disome V cells but not disome XIII cells, contributes

to the differential effect of the UBP6 deletion on the two disomic

strains.

DISCUSSION

Aneuploidy-Tolerating MutationsThis study is to our knowledge the first to describe genetic

alterations that allow cells to tolerate the adverse effects of

aneuploidy. Our analysis of 13 evolved disomic strains identified

gross chromosomal rearrangements, chromosome loss, poly-

ploidization, and point mutations associated with increased

proliferation rates. Their characterization revealed a surprising

diversity in genetic alterations leading to improved growth rates.

We suspect that this is, to some extent, due to the experimental

design. The number of evolved strains that we analyzed was

small, and clones with improved growth properties were isolated

soon after cultures experienced a decrease in doubling time.

Nevertheless, it appears that many different types of genetic

alterations can lead to improved growth in aneuploid yeast

strains. Conversely, most strains appeared to share a common

set of gene expression changes, perhaps indicating similar

phenotypic consequences.

Although our analysis is far from comprehensive, it was never-

theless striking that different types of genetic alterations pre-

dominate in different aneuploid strains. This observation raises

the possibility that different disomic yeast strains evolve by

different pathways. What determines this difference is not yet

clear, but perhaps different forms of genomic instability exist

among the disomes that lead to the favoring of one form of

evolution over another.

The genetic alterations we identified as causing aneuploidy

tolerance fall into two classes: (1) genetic changes unique to

a specific isolate or a disomic strain and (2) alterations found in

descendants of several disomic strains. Of special interest are

genetic alterations that affect the proliferation of multiple

aneuploidies. We identified three potential cases: a duplication

of 183 kb on chromosome XIII and mutations in VPS64 and

UBP6. The UBP6 mutations indeed led to increased proliferation

in four different disomes. It will be interesting to determine

whether and how the other genetic alterations affect multiple

different disomes.

Modulation of the Ubiquitin-Proteasome PathwayAffects Growth Rates in Aneuploid Yeast CellsWe have demonstrated that inactivation of UBP6 improves

proliferation of strains disomic for chromosome V, VIII, IX, and

XI. This effect was especially striking in –His+G418 medium,

where we believe the combination of frameshifts induced by

G418 and disomy places an especially high burden on the

proteasome. How does inactivation of UBP6 improve the fitness

of some aneuploid strains? Our analysis of UBP6 mutants

indicates that Ubp6’s proteasome-antagonizing function is

responsible for the increase in fitness of the aneuploid strains.

Quantitative proteomic approaches further indicate that deletion

of UBP6 reverts the overall protein composition of disome V and

XIII cells to a state that is more similar to that of wild-type cells.

This appears to be mediated by direct posttranscriptional effects

on high abundance proteins in disome V and XIII cells and

through indirect transcriptional effect on low-abundance

proteins in disome V cells.

Inactivation of UBP6 attenuates protein levels in both disome

V and XIII cells, so why does this improve fitness in disome V but

not disome XIII cells? Attenuation of downregulated proteins,

which we observe in disome V cells but not disome XIII cells,

could be responsible for the differential effects of the UBP6

deletion. Another not mutually exclusive possibility is that the

proteins that antagonize proliferation in disome V cells are

more efficiently degraded in the absence of UBP6 because

they are proteasome substrates. In contrast, proteins respon-

sible for decreasing the fitness of disome XIII cells are not. The

transcription factor Gcn4 illustrates this point. GO search termi-

nology revealed that genes encoding proteins involved in amino

acid metabolism were significantly enriched among the genes

most highly expressed in disome V cells and downregulated


when UBP6 was deleted in these cells (49 out of 175, p value =

3 3 10�33). Eighty-four of the 175 attenuated genes contain

binding sites for the Gcn4 transcription factor in their promoters

(http://rsat.ulb.ac.be/rsat/). The GCN4 gene is located on chro-

mosome V and the levels of the protein are increased in disome

V cells. We did not obtain quantitative information on Gcn4

protein levels from disome V ubp6D cells, but previous work

showed that Gcn4 degradation is accelerated in the absence

of UBP6 (Hanna et al., 2006). Deletion of GCN4 did not improve

the fitness of disome V cells (E.T., unpublished data), but

scenarios such as the one described for Gcn4 could be the

reason for why deletion of UBP6 affects the growth properties

of some aneuploids but not others.

The identification of mutations that accelerate protein degra-

dation as conferring aneuploidy tolerance and the observation

that several disomic cells harbored mutations in components

of the ubiquitin-proteasome system highlight the importance of

ubiquitin-mediated protein degradation in the survival of aneu-

ploid cells. Based on the observations that yeast strains carrying

additional yeast chromosomes show synthetic interactions with

mutations that affect proteasome function and exhibit an

increased sensitivity to conditions that interfere with protein

turnover and folding (and strains harboring non-yeast DNA do

not), we previously proposed that aneuploid cells are more

dependent on these pathways for survival than wild-type cells

(Torres et al., 2007). Excess proteins produced by the additional

chromosomes place an increased burden on the cell’s protein

quality control systems. The results presented here support

this idea. The quantitative assessment of the cellular protein

composition of disome V and XIII cells revealed that the addi-

tional chromosomes are indeed producing proteins. Although

the proteins that engage the protein degradation and folding

machineries will be different for each additional chromosome,

the necessity to degrade and fold excess proteins compromises

the cell’s ability to fold and degrade proteins whose excess

presence in the cell interferes with essential cellular processes.

Well-known examples of such proteins are a- and b-tubulin

(Anders et al., 2009; Katz et al., 1990) and histones (Gunjan

and Verreault, 2003; Meeks-Wagner and Hartwell, 1986). We

propose that in the absence of UBP6, clearance of excess

proteins is increased. This improves the fitness of strains, in

which the proteasome neutralizes the excess proteins that

impair growth. It is important to note that the increased reliance

on protein folding and degradation for survival and enhancement

of these pathways to improve fitness will not apply to the

condition of polyploidy. In polyploid cells, the entire genome is

duplicated and protein stoichiometries are not affected.

Aneuploidy-Tolerating Mutations— Implicationsfor CancerIn humans, more than 90% of all solid tumors are aneuploid.

Whether and how aneuploidy promotes tumor formation remains

controversial (Holland and Cleveland, 2009; Schvartzman et al.,

2010). Irrespective of aneuploidy’s role in tumorigenesis, it is

clear from our studies that for tumor cells to acquire high

proliferative potential and to become malignant, they must over-

come the antiproliferative effects associated with aneuploidy.

Obtaining a comprehensive list of genes that modulate the

fitness of specific aneuploidies or the aneuploid state overall

could provide key insights into how cancer cells evolve to

escape the adverse effects of aneuploidy. Interestingly, 12 of

the 29 genes found mutated in the evolved yeast strains have

human homologs, some of which have been found to be upregu-

lated in tumors.

Finally, our results raise the possibility that aneuploid cancers

are under profound proteotoxic stress. This increased reliance of

aneuploid tumor cells on the ubiquitin-proteasome pathway

could provide the framework for the development of new cancer

therapeutics with a broad application spectrum and provide the

rational for the use of already approved proteasome inhibitors

such as Velcade in the treatment of aneuploid tumors in general.


Yeast Strains

All strains are derivatives of W303 (A2587) and are listed in Table S6. The UBP6

deletion, UBP6 truncation alleles, and PGK1-yEGFP-CaURA3 were created

with the PCR-based method described in Longtine et al. (1998). The

ubp6C110A allele was provided by D. Finley. The temperature-sensitive

rpn6-ts allele is described in Ben-Aroya et al. (2008). Disomy of all strains

was confirmed by CGH analysis (Torres et al., 2007) and is available at

http://puma.princeton.edu/ and in the Gene Expression Omnibus under

accession number GSE20464. Microarray gene expression data are also

deposited under this accession number.

Evolution of Aneuploid Yeast Cells

After inoculation from frozen stock directly into selective media, batch cultures

of wild-type and disomic strains were kept in exponential phase by manual

dilutions twice a day into fresh selective medium (�His+G418) for 14 days

at room temperature. Optical densities varied between OD600nm of �0.1

and �1.0. Doubling times were calculated daily.

Competition Experiments

Approximately equal amounts of cells with and without PGK1-GFP were mixed

in selective medium at OD600nm = 0.2 and maintained in exponential growth

phase. Relative cell populations in the cultures were measured by flow cytom-

etry as cells containing PGK1-GFP exhibit three orders of magnitude higher

green fluorescence than the non-GFP cells.

Solexa Sequencing

DNA libraries were generated with the Illumina DNA preparation kit. A

summary of the number of reads, total number of bases sequenced, and

coverage are presented in Table S7. We used the assembled genome of

S288C (http://downloads.yeastgenome.org/) and aligned our wild-type strain

(W303, A2587) sequences with the Maq software package (http://maq.

sourceforge.net/). We found 1396 SNPs in W303 compared to S288C. Using

the assembled S288C genome and taking into account the SNPs found in

W303, we created a reference genome. The methods of SNP identification

are described in detail in the Extended Experimental Procedures.

Other techniques are described in the Extended Experimental Procedures.

ACCESSION NUMBERS

The Gene Expression Omnibus accession number for all the microarray data

including CGH and gene expression analysis reported in this paper is

GSE20464.


Supplemental Information includes Extended Experimental Procedures, seven

figures, and seven tables and can be found with this article online at

doi:10.1016/j.cell.2010.08.038.


ACKNOWLEDGMENTS

We are grateful to Daniel Finley, Philip Hieter, and Juergen Dohmen for

reagents and to Daniel Finley, John Hanna, Frank Solomon, and members of

the Amon lab for suggestions and their critical reading of this manuscript.

This work was supported by National Institutes of Health grant GM56800

and a Charles King Trust postdoctoral Fellowship to ET. M.J.D. and C.M.T.

were supported in part by National Institutes of Health grant P50

GM071508. A.A. is also an Investigator of the Howard Hughes Medical

Institute.

Received: February 10, 2010



Published online: September 16, 2010

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Store-Independent Activation of Orai1by SPCA2 in Mammary TumorsMingye Feng,1 Desma M. Grice,3,6 Helen M. Faddy,3,6 Nguyen Nguyen,2,6 Sharon Leitch,1 Yingyu Wang,5 Sabina Muend,1

Paraic A. Kenny,4 Saraswati Sukumar,2 Sarah J. Roberts-Thomson,3 Gregory R. Monteith,3 and Rajini Rao1,*1Department of Physiology2Department of Oncology

School of Medicine, The Johns Hopkins University, Baltimore, MD 21205, USA3School of Pharmacy, The University of Queensland, Brisbane, QLD 4072, Australia4Department of Developmental and Molecular Biology, Albert Einstein Cancer Center, Albert Einstein College of Medicine, Bronx,

NY 10461, USA5Department of Mechanical Engineering, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA6These authors contributed equally to this work


DOI 10.1016/j.cell.2010.08.040

SUMMARY

Ca2+ is an essential and ubiquitous secondmessenger. Changes in cytosolic Ca2+ trigger eventscritical for tumorigenesis, such as cellular motility,proliferation, and apoptosis. We show that an isoformof Secretory Pathway Ca2+-ATPase, SPCA2, is upre-gulated in breast cancer-derived cells and humanbreast tumors, and suppression of SPCA2 attenuatesbasal Ca2+ levels and tumorigenicity. Contrary toits conventional role in Golgi Ca2+ sequestration,expression of SPCA2 increased Ca2+ influx bya mechanism dependent on the store-operatedCa2+ channel Orai1. Unexpectedly, SPCA2-Orai1signaling was independent of ER Ca2+ stores orSTIM1 and STIM2 sensors and uncoupled from Ca2+-ATPase activity of SPCA2. Binding of the SPCA2amino terminus to Orai1 enabled access of itscarboxyl terminus to Orai1 and activation of Ca2+

influx. Our findings reveal a signaling pathway inwhich the Orai1-SPCA2 complex elicits constitutivestore-independent Ca2+ signaling that promotestumorigenesis.

INTRODUCTION

Basal Ca2+ concentrations are tightly controlled within a narrow

submicromolar range by an array of Ca2+ channels and pumps

that are susceptible to dysregulation in cancer. Transient

changes in cytosolic Ca2+ induce downstream signaling events,

which regulate a wide range of cellular functions (Berridge et al.,

2003; Clapham, 2007; Roderick and Cook, 2008). Ca2+ signaling

is required for every stage of the eukaryotic cell cycle, including

activation and expression of transcriptional factors and cyclin-

dependent kinases that are necessary for cell-cycle progression

(Hogan et al., 2003; Roderick and Cook, 2008), as well as centro-

some duplication and separation (Fukasawa, 2007; Matsumoto

and Maller, 2002). Crosstalk with other signaling mechanisms,

such as the Ras pathway, regulates cell-cycle transition and

cell proliferation (Cook and Lockyer, 2006; Cullen and Lockyer,

2002). Dynamic regulation of Ca2+ signaling is achieved by coop-

eration of various cellular components including receptors,

channels, transporters, buffering proteins, and downstream

effectors (Berridge et al., 2003). Thus, inappropriate activation

of Ca2+ influx channels or downregulation of Ca2+ efflux

and sequestration mechanisms could increase basal Ca2+ to

augment Ca2+ signaling and tumor cell proliferation. Alterna-

tively, changes that deplete the endoplasmic reticulum (ER)

Ca2+ store can confer cellular resistance to apoptosis (Monteith

et al., 2007).

In most nonexcitable cells, depletion of ER stores elicits sus-

tained Ca2+ influx by store-operated Ca2+ (SOC) entry, defining

the major Ca2+ influx pathway. Upon the stimulation of cell-

surface receptors, depletion of ER Ca2+ results in release of

Ca2+ from lumenal EF hand domains of ER-localized STIM

proteins, triggering their translocation to ER-plasma membrane

junctions where they bind and activate Orai1, the pore subunit

of the Ca2+ release-activated Ca2+ (CRAC) channel, and result-

ing in refilling of ER stores (Cahalan et al., 2007; Gwack et al.,

2007; Lewis, 2007; Vig and Kinet, 2007). Store-operated Ca2+

influx is essential for maintaining ER Ca2+ content at a precise

level and functions in various physiological processes such

as gene transcription, cell-cycle progression, and apoptosis

(Parekh and Putney, 2005). Dysfunction of store-operated Ca2+

signaling mediated by STIM and Orai1 leads to inhibition of phys-

iological and pathophysiological activities including breast tumor

cell migration and tumor metastasis (Yang et al., 2009), vascular

smooth muscle cell proliferation and migration (Potier et al.,

2009), and T cell activation and tolerance (Oh-Hora et al., 2008).

The Secretory Pathway Ca2+-ATPases (SPCA) are ATP-pow-

ered pumps that deliver Ca2+ and Mn2+ ions into the Golgi lumen

for protein sorting, processing, and glycosylation (Durr et al.,

1998). In higher vertebrates, including human, this essential

function is carried out by the ubiquitously expressed SPCA1 iso-

form, with orthologs in lower eukaryotes including yeast, nema-

tode, and fruit fly (Missiaen et al., 2007). A closely related second


isoform, SPCA2, shares similar transport characteristics and

appears at first glance to have a redundant role, given its

absence in lower eukaryotes (Vanoevelen et al., 2005; Xiang

et al., 2005). The limited tissue distribution of SPCA2 includes

mammary epithelium, where it is sharply upregulated during

lactation. Whereas SPCA1 showed a modest 2-fold induction

upon lactation, SPCA2 increased by 35-fold and was localized

to the lumenal secretory cells of the mammary gland (Faddy

et al., 2008).

We hypothesized that transformation of mammary epithelial

cells to a cancerous phenotype would be accompanied by dys-

regulation of Ca2+ transporters and their downstream signaling

pathways, augmenting proliferation and tumor formation.

Furthermore, localized, inappropriate secretion of Ca2+ in the

absence of calcium buffers could result in microcalcifications

that appear as radiographic ‘‘signatures’’ on mammograms

used in diagnosis of breast cancer (Morgan et al., 2005).

Although microcalcifications have been extensively used to

characterize abnormalities in the breast tissue, a mechanistic

understanding of the source of calcium and the specific path-

ways that lead to their deposition has remained elusive.

In this study, we show that SPCA2 elicits constitutive Ca2+

signaling, mediated by Orai1, which correlates with oncogenic

activities of mammary tumor cells. Unexpectedly, SPCA2-

induced Ca2+ signaling was independent of its Ca2+ pump

activity, and not regulated by store depletion or STIM proteins.

SPCA2 interacted with Orai1 by its N terminus and activated

Ca2+ influx by the C terminus. These findings reveal a Ca2+

signaling mechanism in which Orai1 mediates store-indepen-

dent Ca2+ influx, and dysregulation of SPCA2 constitutively acti-

vates this pathway leading to oncogenic activity of tumor cells.

RESULTS

Upregulation of SPCA2 Induces Oncogenic Signalingin Mammary Tumor CellsWe used quantitative RT-PCR to investigate the expression of

SPCA isoforms in a range of breast cancer-derived and nonma-

lignant mammary epithelial cells. In contrast to comparable

mRNA levels of SPCA1, SPCA2 was highly upregulated in

lumenal-like breast cancer-derived cell lines (Figure 1A). Exami-

nation of mRNA levels in breast tissue from a small pool of breast

cancer patients confirmed this upregulation (Figure 1B) and

prompted us to mine data from microarray profiles of 295

primary human breast tumors: highest levels of SPCA2 were

found in ERBB2+ tumors, among five transcriptional subtypes

(Figure S1 available online). Consistent with mRNA levels,

protein expression of SPCA2 was higher in MCF-7 cells, a human

breast adenocarcinoma cell line, relative to MCF-10A, a nonma-

lignant human mammary epithelial cell line; in contrast, there was

no increase in SPCA1 expression in MCF-7 (Figure 1C). We used

lentiviral delivery of shRNA constructs to knock down expression

of endogenous SPCA proteins in MCF-7 cells (Figure 1D). Prolif-

eration was inhibited in SPCA2KD cells, with growth rates slower

than mock-transduced cells, and similar to cells growing in low

extracellular Ca2+ (�0.1 mM). In contrast, SPCA1KD did not

cause this growth phenotype (Figure 1E). The RAS-RAF-MEK-

ERK1/2 pathway is known to play an essential role in cell

proliferation and survival. Phosphorylation of ERK1/2 drives acti-

vation of transcriptional factors and expression of downstream

proteins such as cyclin D1, which is essential for completion of

the G1/S transition (Coleman et al., 2004; Roderick and Cook,

2008). Levels of phospho-ERK and cyclin D1 reduced dramati-

cally in SPCA2KD cells, as well as in cells incubated in low extra-

cellular Ca2+, relative to control cells (Figure 1F).

We examined the effects of depleting endogenous SPCA2 on

the transformed phenotype of MCF-7 cells by monitoring growth

of cells in soft agar. Fewer and smaller colonies were observed in

soft agar seeded with SPCA2KD cells compared to control cells,

and normalized results showed a clear reduction of growth

in SPCA2KD cells (Figure 1G). Conversely, overexpression of

SPCA2 in nontumorigenic MCF-10A cells conferred the ability

to form colonies in soft agar (Figure 1H) and increased prolifera-

tion rate (Figure 1I). We also monitored tumor generation in

nude mice injected subcutaneously in the flank with control

or SPCA2KD MCF-7 cells. We show that SPCA2KD conferred

only sporadic and delayed tumor formation relative to control

(Figure 1J).

To determine whether oncogenic activity of endogenous

SPCA2 was mediated by Ca2+ signaling, we measured basal

cytoplasmic Ca2+ levels in control MCF-7 and SPCA2KD cells.

We showed significant reduction of intracellular Ca2+ levels in

SPCA2KD cells and in cells growing in low extracellular Ca2+,

but not in SPCA1KD cells (Figure 1K). On the other hand, overex-

pression of SPCA2 in MCF-10A cells significantly increased

basal Ca2+ concentration (Figure 1L). Although basal Ca2+ levels

varied between cell lines, these levels could be modulated by

SPCA2 expression levels. Thus, SPCA2 appears to play a role

in regulating basal Ca2+, and upregulation of SPCA2 results in

constitutive increase of basal Ca2+ and cell proliferation associ-

ated with oncogenesis.

SPCA2 Elicits Constitutive Ca2+ Signaling Independentof Transport FunctionTo investigate the molecular basis of SPCA2-induced Ca2+

signaling, we began by monitoring Ca2+-dependent localization

of the nuclear factor of activated T cells, NFAT (Crabtree and

Olson, 2002; Huang et al., 2006), in HEK293 cells where expres-

sion of SPCA2 is relatively low (Figure S2A). In resting cells, GFP-

tagged NFAT localized exclusively in the cytoplasm. Following

treatment with thapsigargin, a blocker of sarco/endoplasmic

reticulum Ca2+-ATPases (SERCA), depletion of ER Ca2+ resulted

in store-operated Ca2+ entry, elevation of basal Ca2+ level, and

nuclear translocation of NFAT-GFP in nearly 100% of cells, as

expected (Figures 2A and 2B). Whereas transient expression of

SPCA1 in HEK293 cells did not alter cytoplasmic localization

of NFAT-GFP under resting conditions, transient expression of

SPCA2 elicited nuclear translocation of NFAT-GFP in �75% of

cells. This was inhibited by store-operated Ca2+ channel

blockers, miconazole (Clementi and Meldolesi, 1996), and

2-APB (Parekh and Putney, 2005) at the reported concentra-

tions, and in low extracellular Ca2+, indicating Ca2+ entry through

plasma membrane Ca2+ channels. Inhibition of the Ca2+-acti-

vated Ser/Thr phosphatase calcineurin by FK506 also prevented

nuclear relocalization of NFAT-GFP in SPCA2-transfected cells

(Figures 2A and 2B). Accordingly, NFAT was predominantly


Figure 1. Upregulation of SPCA2 Induces Oncogenic Signaling in Mammary Tumor Cells

mRNA levels were measured by quantitative real-time RT-PCRs and normalized to 18S rRNA in (A) a panel of breast epithelial cell lines relative to 184A1 and (B) in

human breast tumor samples compared to matched normal surrounding breast tissue. n = 3 in (A).

(C) Immunoblot of SPCA expression in MCF-10A and MCF-7 cells.

Immunoblot (D) and normalized proliferation (E) of MCF-7 cells lentivirally transduced with shRNA against SPCA isoforms are shown. n = 3 in (E).

(F) Immunoblot of ERK 1/2 phosphorylation and cyclin D1 expression in MCF-7 cells transduced with shSPCA2.

Micrographs and normalized growth of (G) MCF-7 cells with SPCA2 knockdown or (H) MCF-10A cells with SPCA2 overexpression in soft agar are shown; n = 3.

Immunoblot showing relative SPCA2 expression levels is shown in (H).

(I) Normalized proliferation of MCF-10 cells with SPCA2 overexpression; n = 3.

(J) Tumor incidence in nude mice injected with MCF-7 cells; n = 6, p = 0.005 (log-rank test).

(K) Basal Ca2+ levels in MCF-7 cells with SPCA2 knockdown. From left to right: n = 80, 80, 77, 81, 69. **p < 0.01 (Student’s t test).

(L) Basal Ca2+ levels in MCF-10A cells with SPCA2 overexpression. Vector, n = 23; SPCA2, n = 23. **p < 0.01 (Student’s t test).

Error bars represent standard error (K and L) or standard deviation (A, E, G, H, and I).


dephosphorylated in TG-treated- or SPCA2-expressing cells but

remained phosphorylated in cells transfected with SPCA1 or

empty vector and in FK506-treated cells (Figure 2C).

These findings were unexpected, given the known function

of SPCA2 in pumping Ca2+ away from the cytoplasm into

Golgi/vesicular stores. To determine whether constitutive Ca2+

signaling elicited by SPCA2 was dependent on its Ca2+ pumping

ability, we generated two variants: mutant D379N lacks the

conserved and essential aspartate that is transiently phosphory-

lated by ATP in the catalytic cycle, and mutant D772A disrupts

Figure 2. SPCA2 Elicits Constitutive Ca2+ Signaling Independent of Transport Function

Representative live images (A) and quantification of nuclear localization (B) of NFAT-GFP in HEK293 cells transfected with SPCA1 or SPCA2, or treated with

drugs. n = 3 in (B).

(C) Immunoblot showing phosphorylation status of NFAT following expression of SPCA1or SPCA2 or treatment with thapsigargin (TG) or FK506.

(D) Alignments showing conserved aspartates in phosphorylation (P) domain (D379 in SPCA2) or transmembrane helix 6 (D772 in SPCA2) of P-type Ca2+-

ATPases.

(E) Immunoblot and normalized growth of yeast K616 expressing SPCA2 or mutants D379N and D772A in BAPTA medium; n = 4.

(F) Representative live images, quantification of NFAT translocation in HEK293 cells, and immunoblot showing expression of SPCA2 WT or mutants; n = 3.

(G) Basal Ca2+ levels in HEK293 cells expressing SPCA1, SPCA2, or D379A mutant. From left to right, n = 57, 47, 46, 44. **p < 0.01 (Student’s t test).

Error bars represent standard error (G) or standard deviation (B, E, and F).


Figure 3. SPCA2-Mediated Ca2+ Signaling Is Store Independent

(A) Localization of YFP-STIM1 in HEK293 cells following TG treatment or SPCA2 expression.

(B) Representative Ca2+ traces following emptying of stores with 2 mM Ionomycin in HEK293 cells with or without SPCA2 expression. Vector, n = 40; SPCA2,

n = 25. Cells were cultured in low Ca2+ medium (�0.1 mM) after transfection, followed by a 30 min incubation in normal Ca2+ (2 mM) immediately before calcium

imaging experiments to allow restoration of stores (as described in Extended Experimental Procedures—Calcium imaging).

(C) Representative images of GFP-SPCA1 and NFAT-mCherry following TG treatment or SPCA2 expression in HEK293 cells and (D) quantification of nuclear

NFAT-mCherry translocation. n = 3 in (D).

(E) Quantification of NFAT nuclear translocation following STIM1 knockdown or expression of dominant-negative STIM1 mutant in cells treated with TG or

expressing SPCA2; n = 3.


a conserved and essential Ca2+-binding site (Figure 2D) (Wei

et al., 2000). Both mutants failed to rescue growth of a yeast

strain lacking endogenous Ca2+ pumps in BAPTA-supplemented

medium, consistent with loss of Ca2+-ATPase activity

(Figure 2E), but retained ability to elicit constitutive NFAT trans-

location in HEK293 cells (Figure 2F). Also, mutant D379N

induced growth of MCF-10A in soft agar similar to wild-type

(WT) SPCA2 (Figure S2B). Furthermore, introduction of SPCA2,

either WT or D379N mutant, resulted in elevated basal cyto-

plasmic Ca2+ levels in HEK293 cells, relative to cells transfected

with empty vector or SPCA1 (Figure 2G). This was reminiscent of

the effect of upregulation of endogenous SPCA2 on basal Ca2+

levels in MCF-7 cells (Figure 1K). We conclude that SPCA2,

but not SPCA1, induces constitutive Ca2+ influx and signaling

by a mechanism that is independent of its known function as

a Ca2+-ATPase.

SPCA2-Mediated Ca2+ Signaling Is Store IndependentTo investigate the possibility that SPCA2 could elicit ER Ca2+

store depletion leading to constitutive store-operated Ca2+ entry

(SOCE), we examined the status of the ER Ca2+ store. YFP-

STIM1, the ER-localized Ca2+ sensor protein, was present in

a reticular, ER-like pattern in resting cells and redistributed to

punctae after store depletion with thapsigargin (Liou et al.,

2005), as expected (Figure 3A). Transient transfection with

SPCA2 did not elicit puncta formation of YFP-STIM1, suggesting

that the ER store was not Ca2+ depleted (Figure 3A). Next, we

directly measured the ER Ca2+ content by ionomycin treatment

to completely release Ca2+ from intracellular stores. In Ca2+-

free medium, peak levels of Ca2+ released by ionomycin were

identical in cells transfected with SPCA2 or empty vector

(Figure 3B and Figures S3A and S3B). In a different, independent

approach, we used a thapsigargin-insensitive, ER-localized

Ca2+-ATPase to ensure that intracellular ER stores were replete

with Ca2+. N-terminal GFP-tagged SPCA1 partially mislocalized

to the ER (Figure S3C) where it is functional in filling the stores

and preventing nuclear translocation of NFAT-mCherry after

thapsigargin treatment (Figure S3D and Figures 3C and 3D).

Despite coexpression with ER-localized GFP-SPCA1, SPCA2

was capable of eliciting nuclear translocation of NFAT-mCherry

(Figures 3C and 3D). HA-tagged SPCA1 localizes to the Golgi

(Figure S3C) and does not interfere with thapsigargin-induced

SOCE, nor with SPCA2-induced nuclear translocation of

NFAT-mCherry (Figure 3D), indicating that Ca2+ signaling by

SPCA2 is also independent of Golgi stores. It was previously

reported that knockdown of STIM1 or expression of the domi-

nant-negative mutant D76A DERM blocked SOC signaling

(Huang et al., 2006; Roos et al., 2005), as seen by the failure of

TG to elicit nuclear translocation of NFAT (Figure 3E and Figures

S3E and S3F). Also, knockdown of STIM2, the feedback regu-

lator of cytosolic and ER Ca2+ levels, was shown to lower basal

Ca2+ concentration (Brandman et al., 2007) (Figures S3E and

S3G). However, despite expression of dominant-negative

D76A DERM or knockdown of STIM1 and STIM2 expression,

either singly or in combination, SPCA2 retained the ability to

increase basal Ca2+ concentration and cause NFAT-GFP trans-

location to the nucleus, evidently by a STIM-independent Ca2+

signaling mechanism (Figure 3E and Figures S3F and S3G).

We showed that SPCA2 expression in HEK293 cells resulted in

Ca2+ influx from the extracellular medium, as shown by Mn2+

quench of intracellular preloaded Fura-2 as well as 45Ca2+

uptake (Figures S4A and S4B). Initial rates of uptake, monitored

within the first 60 s, were significantly increased by expression of

SPCA2 (Figure 3F and Figures S4D–S4I). Additionally, measure-

ment of 45Ca2+ efflux and Fura2 fluorescence confirmed that

SPCA2-induced elevation of intracellular Ca2+ did not result

from decreased rates of Ca2+ efflux (Figures S4C–S4F). Consis-

tent with these findings, knockdown of endogenous SPCA2 in

MCF-7 cells also diminished store-independent Ca2+ entry

without changing internal Ca2+ stores (Figures 3G–3I). Taken

together, our results reveal a mechanism for SPCA2-mediated

Ca2+ signaling that is independent of both ER and Golgi Ca2+

stores.

SPCA2 Interacts with Orai1 to Mediate Ca2+ EntryOur results suggested that SPCA2 elicited Ca2+ influx through

plasma membrane Ca2+ channels. Immunofluorescence and

cell-surface biotinylation showed partial localization of endoge-

nous SPCA2 to the plasma membrane in MCF-7 cells, where it

has the potential to elicit Ca2+ influx (Figures 4A and 4B). Next,

we sought evidence for physical interaction between SPCA2

and candidate Ca2+ channels. Although SPCA2-mediated Ca2+

influx was independent of ER stores, we observed coimmuno-

precipitation of the endogenous store-operated channel

Orai1 and native SPCA2 in MCF-7 cells (Figure 4C). We verified

and extended these findings using epitope-tagged proteins

expressed in HEK293 cells: we could document robust coimmu-

noprecipitation of Orai1-Myc and HA-SPCA2 (Figure 4D).

Consistent with the specificity of the Orai1-SPCA2 interaction,

HA-SPCA1 did not coimmunoprecipitate with Orai1 (Figure 4D).

Similar to endogenous protein, up to 10% of HA-SPCA2

could be labeled by cell-surface biotinylation, including both

WT and the pump-inactive D379N mutant; in contrast, SPCA1

was barely detectable (Figure 4E). Surface residence of SPCA2

correlated with total expression levels, and with elevation of

basal Ca2+ (Figure S5A). We also used cell-surface biotinylation

to confirm that a portion of SPCA2-complexed Orai1 was found

at the plasma membrane (Figures S5B and S5C). Although

SPCA2 preferentially interacted with lower molecular weight

bands of posttranslationally modified Orai1 as has been reported

for STIM1 (Park et al., 2009; Vig et al., 2006), we confirmed that

all forms of Orai1 reached the plasma membrane where they

could be biotinylated (Figure 4B). Epitope-tagged SPCA2 and

Orai1 also partially colocalized by confocal immunofluorescence

(F) Initial rates of Ca2+ influx in HEK293 cells with or without SPCA2 expression, calculated from the experiments shown in Figure S4, with 0.5 mM, 1.0 mM, or

2.0 mM extracellular Ca2+. Vector: n = 30 (0.5 mM), 25 (1.0 mM), 28 (2.0 mM); SPCA2: n = 28 (0.5 mM), 23 (1.0 mM), 25 (2.0 mM).

Representative Ca2+ traces (G) and average intracellular Ca2+ concentration representing store-independent Ca2+ influx (H) and internal Ca2+ store content (I) in

ControlKD and SPCA2KD MCF-7 cells. ControlKD, n = 36; SPCA2KD, n = 30. *p < 0.05 (Student’s t test).

Error bars represent standard error (B, F, G, H, and I) or standard deviation (D and E).


Figure 4. SPCA2 Interacts with Orai1 to Mediate Ca2+ Entry

(A) Confocal micrographs of immunofluorescence staining of endogenous SPCA2 in MCF-7 cells showing partial plasma membrane localization.

(B) Cell-surface biotinylation of endogenous SPCA2 and Orai1 in MCF-7 cells. T and B represent total lysate and biotinylated fraction, respectively.

(C) Coimmunoprecipitation of endogenous SPCA2 and Orai1 in MCF-7 cells.

(D) Coimmunoprecipitation of HA-SPCA with Orai1-Myc following expression in HEK293.

(E) Cell-surface biotinylation of HA-tagged SPCA1, SPCA2, or D379N SPCA2 expressed in HEK293.

(F) Basal Ca2+ in MCF-7 cells after knockdown of endogenous SPCA2 or Orai1. ControlKD, n = 47; SPCA2KD, n = 54; Orai1KD, n = 52. **p < 0.01 (Student’s t test).

(G) Normalized proliferation of MCF-7 cells with SPCA2 or Orai1 knockdown; n = 3.

(H) Immunoblot of ERK 1/2 phosphorylation and cyclin D1 expression in MCF-7 cells with SPCA2 or Orai1 knockdown.

(I) Normalized growth of MCF-7 cells with SPCA2 or Orai1 knockdown in soft agar; n = 3.

(J) Tumor incidence in nude mice injected with MCF-7 cells; controlKD, n = 10; SPCA2KD, n = 8, p = 0.007 (log-rank test); Orai1KD, n = 9, p = 0.045 (log-rank test).

Immunoblot (K) and normalized growth in soft agar (L) of MCF-10A cells with knockdown of Orai1 in control and cells overexpressing SPCA2. n = 3 in (L).

Error bars represent standard error (F) or standard deviation (G, I, and L).


microscopy (Figure S5D). Unlike STIM (Yeromin et al., 2006),

interaction between SPCA2 and Orai1 was not affected by store

depletion with thapsigargin, consistent with a store-independent

regulation of Orai1 function (Figure S5E). Supporting this possi-

bility, neither WT STIM1 nor the constitutively active STIM1

mutant (D76A) (Huang et al., 2006; Liou et al., 2005) was in the

same protein complex as SPCA2 (Figure S5F). These findings

point to Orai1 as a likely candidate for mediating SPCA2-regu-

lated, store-independent Ca2+ influx in breast cancer cells.

To evaluate this possibility, we suppressed the expression of

endogenous Orai1 in MCF-7 cells: Orai1KD lowered basal Ca2+

to levels comparable to those seen upon depleting endogenous

SPCA2 (Figure 4F). In addition, Orai1KD in MCF-7 cells sup-

pressed cell proliferation (Figure 4G) and inhibited the RAS

pathway, as did SPCA2KD (Figure 4H and Figure S5G). Further-

more, Orai1KD suppressed colony formation in soft agar, to

a similar extent as SPCA2KD (Figure 4I), and tumor generation

in nude mice (Figure 4J). Simultaneous knockdown of both

Orai1 and SPCA2 did not confer additive phenotypes (Figures

S5H, S5J, and S5K). In MCF-10A cells overexpressing SPCA2,

cell transformation and elevation of basal Ca2+ level were

reversed by knockdown of Orai1, consistent with a role for

Orai1 downstream of SPCA2 (Figures 4K–4L and Figure S5L).

As expected for a store-independent mechanism of Orai1 activa-

tion, depletion of STIM1 (Figures S5M–S5O) or STIM2 (Figures

S5I–S5K), the upstream activators of Orai1 in SOCE signaling,

did not confer comparable phenotypes in MCF-7 cells. Taken

together, our data point to promotion of tumorigenic pathways

by SPCA2 in breast cancer cells, mediated by interaction with

Orai1.

Amino Terminus of SPCA2 Interacts with Orai1To dissect the molecular determinants of the SPCA2-Orai1 inter-

action, we evaluated the efficiency of coimmunoprecipitation

between a series of SPCA chimeric proteins and Orai1. In each

case, the ability of a chimeric protein to coimmunoprecipitate

with Orai1 correlated with ability to elicit NFAT translocation,

suggesting that physical interaction between the two proteins

was required for Ca2+ signaling. Chimeras containing the

SPCA2 N terminus showed stronger binding with Orai1 and

more effective NFAT translocation (Figures 5A–5C).

Next, we examined physical interaction between Orai1 and

major intracellular soluble domains of SPCA2, including N and

C termini and the large intracellular loop, which contains the

iconic aspartate of P-type ATPases (D379). Of these, only the

N terminus was able to pull down Orai1 (Figure 5D). To further

map regions within the SPCA2 N terminus responsible for

binding to Orai1, we performed GST pull downs between Orai1

and a series of SPCA1 and SPCA2 fragments. The SPCA1

N terminus did not bind to Orai1, consistent with an absence

of functional interaction between SPCA1 and Orai1 (Figure 5E).

A region of 40 amino acids within the N terminus of SPCA2

was able to effectively interact with Orai1 (Figure 5E; construct

SPCA2N-8, aa 67–106). Surprisingly, this region was highly

conserved between the two isoforms, with �50% amino acid

identity (Figure S6A). We therefore conducted mutational

replacement of amino acids in the SPCA2 N terminus with the

equivalent residues in SPCA1 and identified four amino acids

that together were critical for interaction between the SPCA2

N terminus and Orai1 (Figure 5F). Three-dimensional structure

of the SPCA2 N terminus, predicted by I-TASSER server (Wu

et al., 2007), suggested that Val71, Thr75, and Ser78 were

spatially clustered, whereas Val95 was on the remote side

(Figure 5G, Figures S6B and S6C, and Table S1).

Finally, we evaluated the effect of Orai1 expression on the

intracellular localization of N-terminal fragments of SPCA1 and

SPCA2 in HEK293 cells. When expressed alone, both fragments

were localized intracellularly, with the SPCA1 N-terminal frag-

ment diffusely distributed in the cytosol, and the SPCA2

N terminus concentrated in the perinuclear region. Although

the coexpression of Orai1 did not change localization of the

SPCA1 N terminus, there was a redistribution of the SPCA2

N terminus to the cell surface, providing additional evidence

that the N-terminal domain of SPCA2, but not SPCA1, interacts

physically with Orai1 (Figure 5H).

Cooperation of SPCA2 N and C Termini in Ca2+ SignalingWe further investigated the molecular mechanism of SPCA2-

activated Ca2+ signaling. We noticed that the isolated N terminus

of SPCA2 did not elicit NFAT translocation despite being

able to interact directly with Orai1, while the C terminus was

sufficient to induce NFAT translocation when it was linked to

two or more transmembrane domains and targeted to the

membrane (Figure 6A and Figures S7A and S7B). Surprisingly,

a similar membrane-anchored construct containing the SPCA1

C terminus was also able to activate constitutive Ca2+ signaling

even though full-length SPCA1 could not (Figure 6A). In addition,

both SPCA1 and SPCA2 membrane-anchored C-terminal

domains physically interacted with Orai1 (Figure S7C). We

hypothesized that access of the SPCA C terminus to Orai1

was blocked in the full-length proteins, and binding of the

SPCA2 N terminus to Orai1 led to exposure of the C terminus

and activation of downstream Ca2+ signaling. Analysis of

deletion and point mutants of the SPCA2 C terminus identified

essential functional residues including several positive charges

(lysines and arginines) and a putative PDZ binding domain (Fig-

ure 6A and Figure S7D), conserved between human, rat, and

mouse SPCA proteins (Figure S7E). We then measured intracel-

lular Ca2+ concentrations upon expression of SPCA2 C-terminal

constructs in HEK293 cells. Basal Ca2+ level was elevated

dramatically by expression of the SPCA2 C terminus but

remained the same as GST control when lysines (arginines)

were mutated or the putative PDZ domain was deleted

(Figure 6B). The N-terminal domain of SPCA2, but not SPCA1,

had a dominant-negative effect, dramatically inhibiting NFAT

translocation induced by full-length SPCA2 or the C terminus

(Figure 6C), whereas SOCE was not blocked by the SPCA2

N terminus or full-length with the C terminus deleted (SPCA2

D924–946) (Figure S7F). Importantly, expression of the mem-

brane-anchored SPCA2 C terminus in MCF-10A cells was able

to induce cell transformation, consistent with the fact that it

was identified to be the functional domain of SPCA2 and elicited

constitutive Ca2+ signaling (Figure 6D). STIM1 CRAC activation

domain (Park et al., 2009) showed a similar effect, supporting

the role of Ca2+ signaling in cell transformation (Figures S7G

and S7H).


Figure 5. N-Terminal Domain of SPCA2 Interacts with Orai1

(A) Schematic of SPCA chimeras. N1 and C1 have the N and C termini of SPCA2 replaced by corresponding regions of SPCA1. N2 and C2 have N and C termini of

SPCA1 replaced by corresponding regions of SPCA2. ‘‘P’’ indicates the conserved aspartate that is transiently phosphorylated by ATP in the catalytic cycle. ‘‘L’’

represents intracellular loop.

(B) Interaction between Orai1 and SPCA chimeras was examined by coimmunoprecipitation in HEK293 cells.

(C) Quantification of NFAT nuclear translocation in HEK293 cells expressing SPCA chimeras described in (B). n = 3; error bars represent standard deviation.


We next expressed GST fusions of various Orai1 domains

including N and C termini, extra- and intracellular loops

together with full-length SPCA2 or the N-terminal fragment of

SPCA2. Both N and C termini, but not the loops of Orai1,

were able to pull down both full-length and N terminus of

SPCA2, revealing that SPCA2 and Orai1 interacted within the

cytoplasm (Figures 6E and 6F). We then mapped subregions

of Orai1 N and C termini to further explore SPCA2 interaction

domains (Figure 6G). GST pull-down experiments identified

a fragment (aa 48–91) of the Orai1 N terminus that bound

SPCA2 with a higher affinity than the full-length N terminus.

Mutation L273S, previously shown to disrupt the coiled-coil

domain of the C terminus of Orai1 (Muik et al., 2008), severely

reduced the interaction with SPCA2 (Figure 6G). Taken

together, we propose a model for SPCA2 interaction with

Orai1 and activation of Ca2+ signaling. We suggest that the N

terminus of SPCA2 binds Orai1, resulting in a conformational

change and exposure of the C terminus, which can interact

with Orai1 either directly or together with other proteins to acti-

vate Ca2+ influx (Figure S7I).

DISCUSSION

Role of SPCA2 and Orai1 in Breast TumorigenicityOur findings reveal a mechanism for activation of the so-called

SOCE channel Orai1 that is independent of ER and Golgi

Ca2+ stores and sensors. This store-independent mode of

endogenous Orai1 activation in breast cancer-derived MCF-7

cells underlies constitutive Ca2+ signaling, proliferation, and

anchorage-independent growth and implicates a hitherto unrec-

ognized role for Orai1 in breast tumorigenicity. We also identified

a role for SPCA2 in tumorigenicity and revealed a functional link

to RAS signaling. The RAS-ERK pathway regulates cell-cycle

progression and cell proliferation, and it is well known that

hyperactivation of the RAS gene family correlates with various

human cancers (Bos, 1989). GTP-exchange factors (GEFs) and

GTPase-activating proteins (GAPs) control activity of RAS by

regulating the balance of GTP binding and hydrolysis (Donovan

et al., 2002; Downward, 1996). Recent studies have suggested

that GEFs and GAPs can be regulated by different Ca2+ signals,

such as amplitude of the Ca2+ signals and frequency of Ca2+

oscillation (Cook and Lockyer, 2006). By monitoring activation

of ERK and expression of the downstream protein cyclin D1,

we revealed a correlation between SPCA2 and Orai1-mediated

increase of basal Ca2+ levels and constitutive activation of RAS

signaling in MCF-7 cells, placing the SPCA2-Orai1 pathway in

the RAS signaling network.

Mechanism of Orai1-Mediated Ca2+ SignalingInduced by SPCA2It has been reported that STIM1 and Orai1 mediate CRAC

currents in endothelial cells, and knockdown of either elicits

cell-cycle arrest (Abdullaev et al., 2008). Another recent study

implicated a store-dependent role for Orai1 in cell migration of

the metastatic breast cancer line MDA-MB-231, based on

a requirement for STIM1 (Yang et al., 2009). We note that

SPCA2 expression is very low in MDA-MB-231 (data not shown),

consistent with a Ca2+ signaling mechanism distinct from the

store-independent pathway reported here. Although the impor-

tance of SOC signaling is well established, the store independent

Ca2+ signaling described in our study suggests that multiple

mechanisms may invoke Orai1 activation. Interaction between

SPCA2 and Orai1 was not affected by ER store depletion and

activation of SOC signaling, and SOCE was not inhibited by

expression of SPCA2, supporting that SPCA-induced signaling

may function independently of the SOC pathway and different

pools or fine subdomains of Orai1 are involved in the two

pathways.

ER-localized Ca2+ sensor STIM proteins, which regulate

SOCE, did not physically interact with SPCA2 or participate in

regulation of the SPCA2-Orai1 signaling pathway. In addition,

internal Ca2+ store content was not depleted by suppression or

overexpression of SPCA2. Thus, it remains to be determined

how the store-independent, Orai1-mediated mechanism of Ca2+

influx is regulated. One possibility is that signaling activity of

SPCA2 is regulated by its trafficking between Golgi and plasma

membrane. Interaction with Orai1 at the cell surface may be

dependent on a specific conformation of SPCA2, which could

be regulated by kinase-mediated phosphorylation, Ca2+ binding,

or changes in pH between extracellular and Golgi lumen.

Removal of a potential PDZ-binding motif in the last four residues

of the C-terminal tail of SPCA2 abolished Ca2+ signaling, sug-

gesting that interaction with scaffold proteins may be important

for activation of this signaling pathway.

Based on the function of a series of chimeras and mutant

proteins, we propose a model in which cooperation of N and

C termini of SPCA2 is required for Orai1-mediated Ca2+

signaling. Whereas the N terminus of SPCA2 binds strongly to

Orai1, the C terminus elicits activation of Ca2+ influx. Although

the Orai1-binding domain within the SPCA2 N terminus is highly

conserved with the corresponding region of SPCA1, no interac-

tion was detected between the SPCA1 N terminus and Orai1.

Replacement of four residues within the minimal Orai1-binding

domain of the SPCA2 N terminus (Val71, Thr75, Ser78, and

Val95) to the corresponding less hydrophobic or charged resi-

dues in SPCA1 abolished the interaction with Orai1.

(D) Interaction between the SPCA2 N terminus (N: aa 1–106), intracellular loop (L: aa 353–733), C terminus (C: aa 923–946), and Orai1 was examined by GST pull-

down in HEK293 cells.

(E) Mapping of regions in SPCA1/2 that interact with Orai1. GST-SPCA1/2 N-terminal fragments were coexpressed with HA-Orai1 in HEK293 cells, and interac-

tion with Orai1 was examined by GST pull-down. Sequence conservation between SPCA1 and SPCA2 is shown on top, with black, gray, and white bars repre-

senting identical, similar, and different amino acids, respectively, as defined by ClustalW.

(F) Screening of SPCA2 N terminus for amino acids critical for the interaction with Orai1 in HEK293 cells. Point mutations in SPCA2 N terminus convert amino

acids to the equivalent residues in SPCA1 N terminus.

(G) Predicted 3D structure of the SPCA2 N terminus with residues essential for interaction with Orai1 shown in red.

(H) Localization of SPCA1/2 N termini, with or without coexpression of Orai1.


Interestingly, C-terminal constructs of both SPCA isoforms,

anchored to the membrane by a minimum of two transmem-

brane helices, were able to elicit Ca2+ influx and signaling.

Consistent with this, critical amino acids within the C terminus

were conserved in both isoforms from rat, mouse, and human.

Therefore, we propose a mechanism in which accessibility of

SPCA C termini is blocked in the full-length protein and binding

of the N terminus to Orai1 is required for functional availability

of the C terminus. Consistent with this hypothesis, we find that

expression of the soluble N-terminal domain from SPCA2, but

Figure 6. Cooperation of SPCA2 N- and C-Terminal Domains in Ca2+ Signaling

(A) SPCA2 C terminus was sufficient to activate Ca2+ signaling. Functions of deletion and point mutants of SPCA2 C-terminal domain were examined by NFAT

translocation assay in HEK293 cells. Full-length SPCA proteins were HA-tagged, and all C terminus fragments shown were GST-tagged; n = 3.

(B) Basal intracellular Ca2+ concentrations in HEK293 cells, with the expression of GST-tagged deletion and point mutants of the SPCA2 C-terminal domain

described in (A). From left to right, n = 49, 45, 46, 48, 40, 54, 59.

(C) Effects of N-terminal fragments of SPCA proteins on NFAT translocation induced by SPCA2 full-length or C-terminal fragment shown in (A). n = 3.

(D) Immunoblot and normalized cell growth in soft agar of MCF-10A cells transduced with vector, SPCA2, GST, and membrane-anchored SPCA2 C terminus

(GST-tagged); n = 3.

(E and F) Interaction between Orai1 N termini (N: aa 1–91), C termini (C: aa 255–301), intracellular loops (L1: aa 141–177), extracellular loops (L2: aa198-234), and

SPCA2 full-length or N terminus.

(G) Interaction between Orai1 full-length and subregions of N terminus (N: aa 1–91; N1: aa 1–47; N2: aa 48–91), C terminus (C: aa 255–301), C terminus mutation

(C-L273S), and SPCA2.

Error bars represent standard error (B) or standard deviation (A, C, and D).


not SPCA1, has a dominant-negative effect in blocking activa-

tion of Ca2+ signaling. Long-range conformational interactions

between the N terminus and other cytosolic domains have

been noted in SPCA and other P-type pumps, as well as changes

in accessibility of the C-terminal tail (Huster and Lutsenko, 2003;

Lecchi et al., 2005; Wei et al., 1999). Recently, Garside et al.

(2010) identified an alternative transcript of SPCA2, encoding

an �20 kDa membrane-anchored C-terminal fragment, in

tissues including brain, testes, salivary glands, and pancreas.

Expression of this transcript was under the control of MIST1,

a basic helix-loop-helix transcription factor, and appeared to

be independent of the full-length transcript. This suggests the

intriguing possibility that a C-terminal fragment of SPCA2 may

elicit Ca2+ signaling independent of the full-length transporter.

Physiological and Pathophysiological Perspectivesof SPCA2-Induced Ca2+ SignalingThe conventional role of ATP-powered Ca2+ pumps is to scav-

enge and extrude cytoplasmic Ca2+ in order to terminate a signal,

and as a prerequisite for additional signaling events. Unexpect-

edly, high levels of expression of the Ca2+ efflux pump SPCA2

increased rather than lowered basal cytoplasmic Ca2+ levels,

and conversely, attenuation of SPCA2 expression was accom-

panied by a decrease in basal Ca2+. We speculate that this

unconventional mechanism may be physiologically important

in eliciting high rates of transcellular Ca2+ flux during lactation

(Lee et al., 2006) and in other Ca2+-secreting tissues, including

salivary glands and intestinal epithelia, where SPCA2 is

expressed at high levels. Total calcium concentration in milk

can reach up to 100 mM, five to six orders of magnitude greater

than typical cytoplasmic concentrations (�0.1 mM). Thus,

there must be energy-dependent transport processes for

effective transcellular movement of Ca2+ from blood into milk.

In mammary gland, a 30-fold transcriptional increase in the

plasma membrane Ca2+ pump isoform, PMCA2, is accompanied

by apical efflux of Ca2+ into milk (Reinhardt et al., 2004).

Compared to modest changes in SPCA1 levels, SPCA2 was

found to be upregulated during pregnancy (�8-fold) and dramat-

ically upon lactation (�35-fold on day 1). Furthermore, SPCA2

expression was restricted to the lumenal cells of lactating glands

(Faddy et al., 2008). Our findings raise the possibility that SPCA2

traffics to the basolateral membrane where it can interact with

Ca2+ channels to elicit Ca2+ influx and promote transcellular

Ca2+ transport.

The unusual role of SPCA2 in activation of Ca2+ influx super-

sedes its ATP-dependent Ca2+ sequestering activity and may

be a raison d’etre for its redundant expression along with

SPCA1 in mammals and higher vertebrates. It is noteworthy

that in lower eukaryotes (yeast, worm, fly) and vertebrates (fish)

there is only a single ubiquitously expressed SPCA protein,

which functions in transporting Ca2+ and Mn2+ into the secretory

pathway. The advent of the SPCA2 gene in higher eukaryotes

including frog, mouse, rat, and human may correlate with a newly

required role in Ca2+ signaling. At the molecular level, a longer

and divergent N terminus appears to have endowed SPCA2

with the ability to interact with unique partners, and discrete

cell- and tissue-specific distribution would appear to regulate

its function. Whereas in lactation, an exquisitely orchestrated

developmental program ensures a coordinated regulation of

Ca2+ pumps, channels, receptors, and buffers, there is emerging

appreciation for a pronounced dysregulation of these processes

in breast-derived tumor cells. For example, an aberrant switch in

heterotrimeric G protein preference by the calcium sensing

receptor, CaSR, in breast cancer cells leads to stimulation of

cAMP signaling and increased secretion of PTHrP, which in

turn is believed to contribute to a ‘‘vicious cycle’’ or feedforward

loop of bone metastasis and osteolysis (Mamillapalli et al., 2008).

Thus, the upregulation of SPCA2 in the altered signaling environ-

ment of tumor cells may result in constitutive Ca2+ signaling and

cell growth. Inappropriate secretion of Ca2+ from these cells, in

the absence of calcium buffers, could lead to microcalcifications

that are diagnostic of breast cancer. Finally, the separation of

signaling function from transport activity in SPCA2, evidenced

by our findings, is highly unusual in pumps. An extreme case is

SUR1, an ABC transporter that lacks known transport activity

but is essential for conferring ATP sensitivity to KATP channels

in insulin-secreting pancreatic b cells (Aittoniemi et al., 2009).

In summary, we identified a store-independent SPCA2-Orai1

signaling pathway. Upregulation of SPCA2 led to constitutively

active Ca2+ signaling and correlated with oncogenic activity in

breast cancer. Both SPCA2 and Orai1 emerge as druggable

targets of therapeutic potential in the treatment of some breast

cancer subtypes.


Materials and additional experimental procedures are described in the Supple-

mental Information.

SPCA2 Analysis in Human Breast Tumors

A gene expression dataset consisting of the microarray profiles of 295 primary

human breast tumors (van de Vijver et al., 2002) was obtained from Rosetta

Inpharmatics (Seattle, WA, USA). Tumors were assigned to transcriptional

subtypes based on their gene expression profiles (Lumenal A [n = 88], Lumenal

B [n = 81], Normal-like [n = 31], Basal-like [n = 46], and ERBB2+ [n = 49]) as

described (Chang et al., 2005). One probe on the array (annotated as

KIAA0703) corresponded to SPCA2. Tumors were grouped by transcriptional

subtype and analyzed for SPCA2 expression. Statistical significance

between groups was assessed by comparing medians using the Kruskall-

Wallis test followed by Dunn’s Multiple Comparison Test (Prism version 5,

Graphpad Inc.).

NFAT Translocation Assay

Monitoring of nuclear translocation of NFAT was performed 24 hr post-trans-

fection in HEK293 cells. Fresh medium was added 2 hr before the start of the

experiment. Localization of NFAT-GFP and NFAT-mCherry in cells was exam-

ined by fluorescent microscopy. 100–300 cells were manually counted on each

coverslip, 3 wells for each condition, and the fraction of cells with nuclear NFAT

was calculated. Where indicated, 2 mM thapsigargin was added for 30 min,

10 mM miconazole was used for 1 hr, and 50 mM 2-APB was used for 1 hr.

Calcium Imaging and Mn2+ Quench

Cells were loaded with Fura-2 AM at 1 mg/ml in calcium recording buffer

(126 mM NaCl, 2 mM MgCl2, 4.5 mM KCl, 10 mM Glucose, 20 mM HEPES

pH 7.4, 2 mM CaCl2; no CaCl2 was added for the 0 Ca2+ buffer) for 30 min

at room temperature (RT). After loading, cells were rinsed in the same calcium

recording buffer without Fura-2 for 20 min. Cells were excited at 340 nm and

380 nm, and Fura AM emission at 505 nm was monitored. Intracellular Ca2+

concentration was calculated based on the ratio of 340/380 nm. For Mn2+

quench of Fura-2 fluorescence, 0.5 mM of Mn2+ was added to nominally

Ca2+-free buffer. Cells were excited at 360 nm, the isosbestic point of


Fura-2, and emission at 505 nm was monitored. The average fluorescence of

10 time points (50 s) before Mn2+ addition was set as 100%.

Construction, Production, and Infection of Lentiviruses

and Retroviruses

Replication-incompetent lentivirus was used to package shRNA for knock-

down in MCF-7 cells and HEK293 cells. Cells were incubated with viruses

for 48 hr and selected with puromycin (2-4 mg/ml).

Retroviral gene transfer and expression system (Clontech, Mountain View,

CA, USA) was used for stable expression of SPCA2 in MCF-10 cells. SPCA2

gene was cloned into pLXRN vector to package retroviruses. Viruses were

collected 48 hr after transfection and added to MCF-10A cells. Cells

were treated with G418 (400 mg/ml) after 48 hr infection and selected cells

were used to assay proliferation and colony formation in soft agar.

Cell Proliferation Assay

Proliferation was monitored using a Celltiter 96 Aqueous One Solution cell

proliferation assay kit (Promega, Madison, WI, USA) according to manufac-

turer’s instructions. Briefly, 0.5–1 3 104 cells were plated into a 96-well plate.

After every 24 hr, 20 ml of Celltiter 96 Aqueous One Solution reagent was added

to each well and incubated for 2 hr at 37�C, 5% CO2. The absorbance at

490 nM was recorded using a 96-well plate reader.

Colony Formation in Soft Agar

Colony formation in soft agar assay was performed using a CytoSelect

96-well cell transformation assay kit (Cell Biolabs, San Diego, CA, USA). In

a 96-well plate, 0.5–1 3 104 cells were resuspended in DMEM containing

0.4% agar and 10% FBS and layered onto a base agar consisting of

DMEM with 0.6% agar and 10% FBS. Following solidification, growth medium

was added on to the cell agar layer. One to two weeks later, colonies were

imaged under the microscope, the agar layer was solubilized, and cells

were lysed and quantified with CyQuant GR dye. The plate was read in a

FLUOstar Optima plate reader (BMG Labtechnologies) using a 485/520 nm

filter set.

Tumor Formation in Nude Mice

Female 4- to 6-week-old athymic nude mice (NCI) were received by the animal

facility personnel and acclimated at the facility for 2 weeks. Estrogen pellets

(SE-121, 0.72 mg/pellet, 60 days release) were obtained from Innovative

Research of America. For each animal, a pellet was implanted into the back

of the neck through a 1 cm cut and the wound was closed by a wound clip.

After 3 days of implantation, the animals were ready to be injected with cells.

MCF-7 cells transduced with control or SPCA2 shRNA or Orai1 shRNA were

trypsinized and diluted to 1.5–3 3 107 cells per ml in PBS. 3 3 106 cells per

animal were injected subcutaneously into the flank of each of 6–10 mice.

The incidence of tumor formation was recorded in each animal once per

week, starting 14–18 days after injection. Animal care was in accordance

with institutional guidelines. One animal with subsequent tumor necrosis

was euthanized, others were sacrificed after 10 weeks of observation.

Immunofluorescence

Cultured HEK293 and MCF-7 cells on coverslips were pre-extracted with

PHEM buffer (60 mM PIPES, 25 mM HEPES, 10 mM EGTA, and 2 mM

MgCl2, pH 6.8) containing 0.025% saponin for 2 min, then washed twice for

2 min with PHEM buffer containing 0.025% saponin and 8% sucrose. The cells

were fixed with a solution of 4% PFA and 8% sucrose in PBS for 30 min at room

temperature and blocked with a solution of 1% BSA and 0.025% saponin in

PBS for 1 hr. Primary antibodies were diluted 1:500 in 1% BSA and incubated

with the cells for 1 hr. Alexa-Fluor 488 goat anti-rabbit IgG (Invitrogen) and

Alexa-Fluor 568 goat anti-mouse IgG were used at a 1:1000 dilution for

30 min. Cells were mounted onto slides using Dako Fluorescent Mounting

Medium. Slides were imaged on a Zeiss LSM510-Meta confocal microscope.

In Figure 4A, anti-SPCA2 was used. In Figure 5H, anti-SPCA2, anti-SPCA1,

and anti-HA were used to detect SPCA2N, SPCA1N, and HA-Orai1. In

Figure S3C, anti-Myc, anti-SPCA1, and anti-Golgi97 were used to detect

Myc-STIM1, HA-SPCA1, and Golgi 97. In Figure S5D, anti-SPCA2 and anti-

HA were used to detect Myc-SPCA2 and HA-Orai1. In Figure S7B, anti-GST

and anti-HA were used to detect GST-SPCA2C and HA-Orai1.

Coimmunoprecipitation and GST Pull-Down

Coimmunoprecipitation (co-IP) and GST pull-down assay in HEK293 cells

were performed 24 hr after transfection. Co-IP in MCF-7 cells for endogenous

proteins was performed 24–48 hr after seeding cells. Cells were lysed in lysis

buffer (20 mM Tris-HCl, pH 7.4, 150 mM NaCl, 1 mM Na3EDTA, 1 mM EGTA,

5 mM Na4P2O7, 1 mM Na3VO4, 10 mM NaF, supplemented with 1% Triton

X-100 and protease inhibitor cocktail [Roche]). 1/10 of the lysate was saved

as ‘‘input.’’ For co-IP, cell lysate was incubated 1 hr with GammaBind Plus

Sepharose (GE Healthcare, Waukesha, WI, USA) for preclearance and 1–4 hr

with antibodies (anti-Myc or anti-SPCA2) at 4�C. GammaBind beads were

added and incubated for 1 hr at 4�C. For GST pull-down assay, cell lysate

was incubated 2 hr with glutathione Sepharose 4B. Beads were washed using

lysis buffer supplemented with 1% Triton X-100 before SDS-PAGE and immu-

noblotting. 1/2 of the ‘‘input’’ and 1/2 to 1/8 of the co-IP/pull-down fraction

were loaded to SDS-PAGE gels. To co-IP cell-surface Orai1 with SPCA2, cells

were biotin-labeled, lysed, and immunoprecipitated using anti-SPCA2 anti-

body. The proteins on the GammaBind beads were eluted with lysis buffer

containing 1% SDS and incubated with neutravidin resin overnight at RT.

Beads were washed in the same buffer. Only the portion of Orai1 that bound

to SPCA2 at the cell surface was detected using SDS-PAGE and immunoblot-

ting. 1/2 of the ‘‘input’’ and 1/2 of the biotinylated fraction were loaded to SDS-

PAGE gels.

Functional Complementation in Yeast

Yeast growth assays were performed as described before (Xiang et al., 2005).

The yeast strain K616 (pmr1Dpmc1Dcnb1D) was used as host for plasmids

expressing SPCA2. Freshly grown cells were inoculated into each well of

96-well plates at 0.05 optical density (OD) 600 nm. Plates were incubated over-

night at 30�C and resuspended by agitation, and OD600 nm was measured

using a FLUOstar Optima plate reader.

Three-Dimensional Structure Prediction

I-TASSER method was used to predict 3D protein structure from the primary

amino acid sequence of the SPCA2 N terminus. I-TASSER was ranked as

the No.1 server in recent CASP7 and CASP8 experiments (Critical Assessment

of Protein Structure Prediction).



figures, and one table and can be found with this article online at doi:10.1016/

j.cell.2010.08.040.

ACKNOWLEDGMENTS

We thank Dr. Paul Worley and Dr. Guo Huang (Johns Hopkins University) for

kind gifts of plasmids expressing Orai1, STIM1, and NFAT. This work was sup-

ported by grant GM62142 from the National Institution of Health to R.R.,

569644 from the National Health and Medical Research and Cancer Council

Queensland to G.R.M. and S.J.R.-T., Department of Defense-Center of Excel-

lence Grant W81XWH-04-1-0595 to S.S., laboratory startup funds from the

Albert Einstein College of Medicine to P.A.K., American Heart Association

Pre-doctoral fellowship 0815058E to M.F., and American Psychological Asso-

ciation scholarship to H.M.F. and D.M.G.

Received: December 28, 2009




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Cell Surface- and Rho GTPase-BasedAuxin Signaling Controls CellularInterdigitation in ArabidopsisTongda Xu,1 Mingzhang Wen,1 Shingo Nagawa,1 Ying Fu,1 Jin-Gui Chen,2 Ming-Jing Wu,2

Catherine Perrot-Rechenmann,3 Ji�rı Friml,4 Alan M. Jones,2,5 and Zhenbiao Yang1,*1Center for Plant Cell Biology, Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA2Department of Biology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA3Institut des Sciences du Vegetal, CNRS, UPR2355, 1 Avenue de la Terrasse, 91198 Gif sur Yvette Cedex, France4Department of Plant Systems Biology, VIB, and Department of Molecular Genetics, Ghent University, Technologiepark 927,

9052 Gent, Belgium5Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.003

SUMMARY

Auxin is a multifunctional hormone essential for plantdevelopment and pattern formation. A nuclear auxin-signaling system controlling auxin-induced geneexpression is well established, but cytoplasmic auxinsignaling, as in its coordination of cell polarization,is unexplored. We found a cytoplasmic auxin-signaling mechanism that modulates the interdigi-tated growth ofArabidopsis leaf epidermal pavementcells (PCs), which develop interdigitated lobes andindentations to form a puzzle-piece shape in a two-dimensional plane. PC interdigitation is compro-mised in leaves deficient in either auxin biosynthesisor its export mediated by PINFORMED 1 localizedat the lobe tip. Auxin coordinately activates twoRho GTPases, ROP2 and ROP6, which promote theformation of complementary lobes and indentations,respectively. Activation of these ROPs by auxinoccurs within 30 s and depends on AUXIN-BINDINGPROTEIN 1. These findings reveal Rho GTPase-based auxin-signaling mechanisms, which modulatethe spatial coordination of cell expansion acrossa field of cells.

INTRODUCTION

Auxin regulation of plant growth and development requires

a nuclear signaling mechanism, which involves auxin stabilizing

the interaction between the TIR1-family F box proteins and the

IAA/AUX transcriptional repressors, leading to IAA/AUX degra-

dation and changes in gene expression (Leyser, 2006; Parry

and Estelle, 2006; Dharmasiri et al., 2005a; Kepinski and Leyser,

2005; Mockaitis and Estelle, 2008; Tan et al., 2007). However,

this pathway cannot account for auxin-induced rapid cellular

responses occurring within minutes, such as cell expansion,

cytosolic Ca2+ increase, and proton secretion (Badescu and

Napier, 2006; Senn and Goldsmith, 1988; Shishova and Lind-

berg, 2004; Vanneste and Friml, 2009). AUXIN BINDING

PROTEIN1 (ABP1) has been proposed to be an auxin receptor

that rapidly activates cell expansion (Badescu and Napier,

2006; Chen et al., 2001a, 2001b; Jones, 1994). ABP1 knockout

causes lethality of early embryos due to their failure to polarize

(Chen et al., 2001b). Auxin is also implicated in the regulation

of cell polarization including polar distribution of the auxin efflux

facilitator PIN (PINFORMED) proteins to the plasma membrane

(PM) and determination of root hair initiation sites in the root

epidermal cells (Dhonukshe et al., 2008; Fischer et al., 2006;

Paciorek et al., 2005). However, signaling events downstream

of ABP1 and those underlying the control of cell polarization by

auxin are unknown.

Coordinated spatial control of cell expansion or asymmetry

across an entire field of cells in a tissue is important for pattern

formation and morphogenesis. In animals, this type of spatial

coordination is required for cellular intercalation that drives

convergent extensions during early embryogenesis (Green and

Davidson, 2007; Heasman, 2006). In plants, PIN proteins are

located to one cell end in a specific tissue to generate directional

flow of auxin (Petrasek et al., 2006; Wisniewska et al., 2006). In

addition, spatial coordination among epidermal cells is important

for patterning of the epidermal tissues such as the positioning of

root hairs and the jigsaw-puzzle appearance of pavement cells

(PCs) in the leaf (Fischer et al., 2006; Fu et al., 2005, 2002). The

molecular mechanisms underlying the spatial coordination in

these plant systems are poorly understood.

We used Arabidopsis leaf epidermal PCs as a model system to

investigate the mechanisms for the cell-cell coordination of inter-

digitated cell expansion (Fu et al., 2005, 2002; Settleman, 2005;

Yang, 2008). The jigsaw-puzzle appearance results from interca-

lary growth that produces interdigitated lobes and indentations

(Figure 1A). This cellular interdigitation resembles embryonic

cell intercalation required for convergent extension in animal

cells. Interestingly, these two distinct processes share common

mechanisms, including Rho GTPase signaling and its effect on


the cytoskseleton (Fu et al., 2005; Settleman, 2005; Yang, 2008).

ROP2 and ROP4, two functionally-overlapping members of the

Rho GTPase family in Arabidopsis, promote lobe development

(Fu et al., 2005, 2002). ROP2, locally active at the lobe-forming

site, promotes the formation of cortical diffuse F-actin and lobe

outgrowth via its effector RIC4 (Fu et al., 2005). In the lobe tips,

ROP2 suppresses well-ordered cortical microtubule (MT) arrays

by inactivating another effector, RIC1 (Fu et al., 2005, 2002), thus

relieving MT-mediated outgrowth inhibition. In the opposing

indenting zone, ROP6 activates RIC1 to promote well-ordered

MTs and to suppress ROP2 activation (Fu et al., 2005, 2009).

What activates the ROP2 and ROP6 pathways and how these

two pathways coordinate across cells to produce the cellular

interdigitation remains unknown.

In this report, we demonstrate that auxin promotes interdigi-

tated PC expansion by coordinately activating the antagonistic

ROP2 and ROP6 pathways in an ABP1-dependent manner and

that ROP2 is required for the targeting of PIN1 to the lobing

regions of the PM, which is crucial for the interdigitated PC

expansion. These findings establish a molecular framework

underpinning cellular interdigitation as well as an auxin-signaling

mechanism that is downstream of ABP1 and required for cyto-

plasmic events including cytoskeletal organization, PIN protein

targeting, and spatially coordinated cell expansion.

RESULTS

Auxin Promotes and Is Required for PC InterdigitationGiven the widespread role of auxin in plant pattern formation, we

evaluated its involvement in the interdigitated growth of PCs in

Arabidopsis. We first examined the effect of exogenous auxin

on the degree of PC interdigitation, which was measured by

the number of lobes per cell area in a two-dimensional plane of

the leaf surface (Figure S1A available online). Treatments of

wild-type (WT) seedlings with the synthetic auxin naphthalene-

1-acetic acid (NAA) significantly increased PC interdigitation in

a dose-dependent manner with an effective NAA concentration

as low as 5 nM and optimal concentration around 20 nM (Figures

1B and 1C and Figure S1C).The requirement of endogenous

auxin for PC interdigitation was investigated using mutants

defective in YUCCA gene family-dependent auxin biosynthesis

(Cheng et al., 2006; Zhao et al., 2001). The cotyledon PCs of

the yuc1 yuc2 yuc4 yuc6 quadruple mutant, which accumulates

a lower amount of auxin than the wild-type (Cheng et al., 2006),

Figure 1. Auxin Activation of PC Interdigitation Requires ROP2/4

(A) A schematic showing three stages of PC morphogenesis as described (Fu et al., 2005).

(B) Auxin increased interdigitation of WT PCs and suppresses the PC interdigitation defect in the yuc1 yuc2 yuc4 yuc6 (yuc 1/2/4/6) quadruple mutant but not in

the ROP2RNAi rop4-1. Seedlings were cultured in liquid MS with or without 20 nM NAA, and cotyledon PCs were imaged 4 days after stratification.

(C) Quantitative analysis of PC interdigitation. The degree of interdigitation in PCs shown in (B) was quantified by determining the density of lobes for each PC

(Figure S1A). Data are mean lobe number per mm2 ± SD (n > 400 cells from three individual plants). The yuc mutant had a significantly lower density of lobes than

Col-0 wild-type, and NAA significantly increased the mean density of lobes in Col-0 WT and the yuc mutant (t test, p < 0.001) but not in the ROP2RNAi rop4-1 line

(t test, p > 0.1). Nonbiased double blind analysis confirms all of the phenotypic differences between mutants and treatments (Figure S1B).

Also see Figure S1.


exhibited reduced interdigitation (Figures 1B and 1C). This yuc1

yuc2 yuc4 yuc6 PC phenotype resembled that of the ROP2RNAi

rop4-1 line (Figures 1B and 1C), in which ROP2 and ROP4

expression is reduced (Fu et al., 2005). Interestingly, NAA treat-

ment rescued the interdigitation defect of the yuc quadruple

mutant but not that of the ROP2RNAi rop4-1 line (Figures 1B

and 1C; Figures S1C and S1D). These results suggest that auxin

is a signal that induces lobe formation possibly by activating

ROP2 and ROP4.

Auxin Activates the ROP2-RIC4 Pathway at the PMTo test whether auxin activates ROP2, we first determined the

effect of auxin on ROP2 activity using an effector binding-based

assay (Baxter-Burrell et al., 2002) to measure active GTP-bound

GFP-ROP2 in protoplasts isolated from Arabidopsis leaves

stably expressing GFP-ROP2. We found that ROP2 activity

doubled by addition of as low as 1 nM NAA and reached satura-

tion at 20–100 nM NAA (Figures 2A and 2B), which is consistent

with the concentrations of NAA for the induction of PC interdig-

itation (Figures S1C and S1F). Time course analysis showed that

ROP2 activity doubled within 30 s after NAA treatment (Figure 2C

and 2D). This is one of the most rapid auxin responses known to

date, which suggests that auxin perception directly leads to

ROP2 activation at the PM.

Localization of GFP-RIC4 to the PM is a display of in vivo acti-

vation of ROP2, because RIC4 specifically binds the active form

of PM-delimited ROPs (Fu et al., 2005; Hwang et al., 2005). In

wild-type PCs, GFP-RIC4 was preferentially localized to the

PM domains associated with initiating or growing lobes where

ROP2 is activated. In the yuc quadruple mutant, GFP-RIC4 local-

ization to these PM domains was reduced, with a corresponding

increase of its level in the cytoplasm (Figures S2A and S2B).

Treatment with 20 nM auxin increased PM-associated GFP-

RIC4 in this mutant (Figures S2A and S2B), but not in the

rop2-1 rop4-1 double mutant (data not shown). Fine cortical

F-actin, a RIC4 signaling target, was also markedly reduced in

the yuc quadruple-mutant PCs as in the ROP2RNAi rop4-1

PCs (Fu et al., 2005) (Figure S2C). Taken together, our results

indicate that auxin is required for localized ROP2 activation in

the lobing region of PCs.

ABP1 Is Required for Auxin Promotion of PCInterdigitationThere are two well-characterized receptor families in Arabidop-

sis, ABP1 and TIR1 proteins. The TIR1-family of F box proteins

directly controls auxin-induced gene expression (Leyser, 2006;

Mockaitis and Estelle, 2008) and is unlikely to mediate ROP2

activation and other responses that are rapidly induced by auxin

within 30 s (Badescu and Napier, 2006), since the most rapid

auxin-induced changes in mRNA expression occur within

2-5 min after auxin treatments (Abel and Theologis, 1996).

ABP1 is partially localized to the outer surface of the PM by asso-

ciating with a GPI-anchored PM protein (Badescu and Napier,

2006; Jones, 1994; Shimomura, 2006; Steffens et al., 2001).

Because null alleles of abp1 are embryo lethal (Chen et al.,

2001b), we isolated a weak allele, abp1-5, containing a point

mutation (His94- > Tyr) in the auxin-binding pocket (Woo et al.,

2002) (Figure 3A). PCs of abp1-5 cotyledons showed a defect

similar to that observed in the yuc quadruple mutant (Figure 3B

and 3C; Figure 1B and 1C). This defect was rescued to WT

by transgenic expression of ABP1 (Figure S3A and S3B), con-

firming that the abp1-5 defect was due to the abp1-5 mutation.

The role of ABP1 in PC interdigitation was further confirmed

by inducible expression of an ABP1 antisense RNA and a

RNA encoding single-chain fragment variable 12 derived from

anti-ABP1 mAb12 antibody (Braun et al., 2008) (Figures 3D

and 3E and Figures S3C and S3D). Unlike PCs in the yuc

quadruple mutant, exogenous auxin did not induce lobe forma-

tion in PCs containing the abp1-5 mutation or expressing

ABP1 antisense RNA (Figures 3B–3E and Figure S1E). Thus,

Figure 2. Auxin Rapidly Activates ROP2 and ROP6

in a Dosage-Dependent Manner

(A and C) Auxin dosage responses of ROP2 and ROP6

activation. Protoplasts from leaves of transgenic GFP-

ROP2 or -ROP6 seedlings were treated with the indicated

concentrations of NAA for 2 min (A), or treated with 100 nM

NAA for the indicated times (C). GTP-bound active

GFP-ROP2 or -ROP6 and total GFP-ROP2 or -ROP6

(GDP and GTP forms) were analyzed as described

in text. Results from one out of five independent experi-

ments with similar results are shown. ROP2 and ROP6

experiments were conducted in parallel under identical

conditions.

(B and D) Quantitative analysis of data from (A) and (C). The

relative ROP2 or ROP6 activity level was determined as

the amount of GTP-bound ROP2 or ROP6 divided by

the amount of total GFP-ROP2 or ROP6. The relative

ROP activity in different treatments was standardized to

that from mock-treated control, which was arbitrarily

defined as ‘‘1.’’ Data are mean activity levels from five

independent experiments ± SD. We tested the significance of difference in ROP activity level between ROP2 and ROP6 at various auxin levels using F-test. All

the p values are less than 0.001 except at 0 and 1 nM of auxin. We also compared mean values of ROP activity level using Tukey pairwise mean comparisons

and found that ROP2 activity significantly increased at lower auxin levels, stabilized at median auxin levels, and significantly decreased at high auxin levels. In

contrast, ROP6 activity significantly increased at low and median levels and stabilized at high auxin levels.

Also see Figure S2.


we hypothesize that ABP1 perceives the auxin signal required for

PC interdigitation.

ABP1 Is Required for Auxin Activationof the ROP2-RIC4 PathwayWe next tested whether ABP1 is required for the auxin activation

of the ROP2 pathway. The abp1-5 mutation greatly reduced

GFP-RIC4 localization to the lobe tip and PM (Figures S4A and

S4B), as well as localized accumulation of diffuse cortical F-actin

(Figure S4C). Thus, ROP2 signaling is greatly compromised by

abp1-5. Furthermore, the defect in RIC4 localization in the

abp1-5 mutant could not be rescued by auxin (Figure S4A).

Finally, both the analysis of GFP-RIC4 localization and measure-

ment of GTP-bound ROP2 showed that the rapid auxin activa-

tion of ROP2 in protoplasts was abolished by the abp1-5

mutation and ABP1 antisense expression (Figures 4A and 4B

and Figures S4D–S4F). Hence, ABP1 acts upstream of ROP2

in the perception of auxin.

Figure 3. ABP1 Is Required for Auxin Perception that Promotes PC Interdigitation

(A) The abp1-5 mutation (His59- > Tyr) occurs within the auxin binding pocket (Woo et al., 2002). (Left) The crystal structure of maize ABP1 with bound NAA (PDB

1lrh). Maize ABP1 is a glycosylated homodimer that binds two NAA molecules (shown in red). Maize and Arabidopsis share 68% identity overall and 100% conser-

vation in the binding pocket. (Right) The auxin-binding pocket is highlighted to show how H59 (sphere format) interacts with the carboxic acid group of NAA shown

in red and with a zinc ion not shown (for clarity).

(B) Defect in PC interdigitation in the abp1-5 mutant was not rescued by auxin. Seedlings were cultured in liquid MS with or without 20 nM NAA, and cotyledon

PCs were imaged 4 days after stratification.

(C) PC interdigitation shown in (B) was quantitated as in Figure 1C (n > 400 cells from three individual plants). WT had significantly higher lobe intensity than abp1-5

(t test, p < 0.001). No significant difference was found between treatment with or without NAA (t test, p > 0.1).

(D) The defect in PC interdigitation in an inducible ABP1 antisense line was not rescued by auxin. An ABP1 antisense construct was expressed upon ethanol

treatment (Braun et al., 2008). Seedlings were cultured in liquid MS containing 0.5% ethanol with or without NAA, and cotyledon PCs were imaged 4 days after

stratification.Without ethanol treatment, the PCs in this line were similar to WT PCs (Figure S3C). Upon ethanol induction, ABP1 antisense PCs were similar to the

abp1-5 cells and were not altered by NAA.

(E) PC interdigitation in the antisense line shown in (C) was quantitated as in Figure 1C (n > 400 cells from three individual plants). WT had a significantly higher lobe

density than the ABP1 antisense line in the absence of NAA (t test, p < 0.001), which did not show significant difference with NAA treatment (t test, p > 0.1).

A double-blind analysis was performed and the results confirmed all of the phenotypic differences between mutants and treatments described in this figure (see

Figure S3E).


ROP2-Dependent Lobe-Localized PIN1 Is Requiredfor InterdigitationThe presence of ABP1 at the cell surface (Diekmann et al., 1995;

Jones and Herman, 1993; Leblanc et al., 1999) and ROP2 local-

ization to the lobe PM imply that the perception of extracellular

auxin leads to localized ROP2 activation. Thus, a mechanism

for local accumulation of extracellular auxin is expected. In

support of this notion, we found PIN1 preferentially localized to

the PM of PC lobe tips (Figure 5A). PCs of a PIN1 loss-of-function

mutant, pin1-1, showed a defect in interdigitation, and were long

and narrow (Figure 5B and Figures S5A and S5B), resembling the

ROP2RNAi rop4-1 line (Fu et al., 2005). Another allele, pin1-5,

showed a similar phenotype (Figures S5E and S5F). GFP-RIC4

localization to the PM was compromised in the pin1-1 mutant

with GFP-RIC4 diffusely distributed in the cytosol (Figures 5D

and 5E). Application of NAA failed to rescue the lobing defect

in the pin1-1 mutant (Figures 5B and 5C and Figures S5A and

S5B), supporting a critical role for PIN1-mediated localized auxin

export in lobe formation and localized ROP2 activation. This also

implies a role for PIN1 in a positive feedback, i.e., PIN1 localiza-

tion to the lobe tip may require ROP2 activation. Consistent with

this implication, PIN1 localization to the PM was compromised in

the ROP2RNAi rop4-1 line, the abp1-5 mutant, and the ABP1

antisense line, which all showed greatly enhanced PIN1 internal-

ization and reduced localization to the lobe PM (Figure 5A, right

panel and Figures S5G and S5H). Transient expression of a domi-

nant negative ROP2 mutant protein also increased PIN1-GFP

internalization, suggesting that PIN1 localization to the PM is

directly affected by ROP2 signaling, not indirectly through

ROP2/4-mediated cell shape changes (Figures S5C and S5D).

Taken together, these results support the hypothesis that a

PIN1-dependent positive feedback loop is required for localized

ROP2 signaling and lobe outgrowth. This also implies a role for

localized extracellular auxin in the regulation of interdigitation.

Auxin Also Activates the ROP6-RIC1 Pathwayin an ABP1-Dependent MannerPIN1-exported auxin in the lobing side is expected to

diffuse across the cell wall to the complementary side of the

neighboring cell, where the ROP6-RIC1 pathway operates (Fu

et al., 2009). We speculated that PIN1-exported auxin could

serve as a cross-cell signal to activate the ROP6-RIC1 pathway,

hence providing a mechanism for the cell-cell coordination of

lobe outgrowth with indentation formation. Interestingly, the

quadruple yuc and single abp1-5 mutants exhibited an additional

cell shape phenotype observed in rop6-1 and ric1-1 (Fu et al.,

2005, 2009), specifically, wider neck regions (Figures 6A and 6B).

The wide neck phenotype suggests that auxin and ABP1 may

also activate the ROP6-RIC1 pathway, which promotes indent-

ing. Thus we sought to test whether ABP1 perception of auxin

activates the ROP6-RIC1 pathway.

ROP6 is required for RIC1 decoration of cortical MTs like

beads on a string and for its function in promoting the ordering

of cortical MTs (Fu et al., 2009). If auxin is required for ROP6 acti-

vation, one would expect that RIC1’s association with cortical

MTs is disrupted in the abp1-5 and the yuc quadruple mutant,

as in the rop6-1 null mutant (Fu et al., 2009). Indeed, RIC1 asso-

ciation with cortical MTs was greatly abolished in both yuc

quadruple and abp1-5 single mutant PCs (Figure 6C and

Figure S6A). Consistent with the defect of RIC1 distribution,

the arrangement of cortical MTs in these mutants became mostly

random, similar to that seen in rop6-1 and ric1-1 mutants

(Figure S6B). This indicates that auxin and ABP1 are required

for the activation of the ROP6-RIC1 pathway.

We next tested whether auxin promoted RIC1 association with

cortical MTs. We previously showed that ROP2 inhibits RIC1

function by sequestering RIC1 from cortical MTs in PCs. To

circumvent the possible complication of the ROP2 effect on

RIC1 localization (Fu et al., 2005), we analyzed YFP-RIC1

Figure 4. Auxin Can Activate ROP2-RIC4 Pathway

through ABP1

(A) Measurement of GTP-bound GFP-ROP2 in protoplasts

isolated from a abp1-5 line stably expressing 35S::GFP-

ROP2 by coimmunoprecipitation assay described in

Figure 2. The seedlings expressing GFP and homozygous

for abp1-5 were pooled and used for protoplast isolation.

Auxin did not activate ROP2 in abp1-5 mutants compared

to in wild-type where auxin activates ROP2 within 30 s

(Figure 2C).

(B and C): Loss of auxin activation of ROP2 in the abp1-5

mutant and the induced ABP1 antisense line. GFP-RIC4

distribution to the PM in isolated protoplasts was used

to report ROP2 activation by auxin. (B) Representative

images of GFP-RIC4 distribution in protoplasts isolated

from different lines before and 5 min after auxin applica-

tion. The bright field images (left) show intact protoplasts

corresponding to the GFP-RIC4 fluorescent images at

time 0. See Figures S4D-S4F for representative images

from the complete time course analysis. (C) Quantitative

analysis of GFP-RIC4 distribution to the PM (as indicated

by relative GFP intensity in the PM standardized with the

cytosolic GFP intensity). Data are mean values from 10

protoplasts analyzed ± SD.

Also see Figure S4.


localization in the rop2-1 rop4-1 mutant, in which ROP2 function

is compromised. YFP-RIC1 appeared as beads lining cortical

MTs (Figures 6C and 6D) (Fu et al., 2005). Ten minutes after

the application of 10 nM NAA, the number of YFP-RIC1 associ-

ated MTs increased, and MTs became more ordered, especially

in the indented region of the PC (Figure 6D). Furthermore, both

the number of YFP-RIC1 beads and their intensity greatly

increased as rapidly as 4 min after NAA application (Figures 6E

and 6F). In abp1-5, auxin failed to change the localization pattern

of RIC1 (Figures 6D–6G), suggesting that ABP1 acts upstream of

ROP6. These results support the hypothesis that auxin activates

the ROP6-RIC1 pathway in an ABP1-dependent manner.

Figure 5. PIN1 Is Localized to the Lobe Tip and Is Essential for Auxin Promotion of PC Interdigitation

(A) Left: PIN1-GFP was preferentially localized to the tip of lobes in PC. Middle: Immunostaining of PIN1 in PCs. Arrows indicates the accumulation of PIN1 at

the lobe region. Right: Immunostaining of PIN1 in ROP2RNAi rop4-1 mutant. Arrows (yellow) indicates the accumulation of PIN1 at the lobe region was lost in

ROP2RNAi rop4-1. Arrowheads indicate internalized PIN1, which was greatly increased in the cytoplasm of ROP2RNAi rop4-1 cells. 75 cells from 3 repeats

are used for quantification (Figure S5H).

(B) PC shapes in wild-type (left) and pin1-1 mutant (middle). pin1-1 PCs were slender with few lobes, a phenotype similar to a rop2-1rop4-1 double knockout

mutant (data not shown). 20 nM NAA was unable to rescue pin1-1 phenotype in PCs (right).

(C) Quantitative data for (B). Lobe numbers per cell area in pin1-1 mutant and pin1-1 mutant treated with 20 nM NAA were quantified using double blind analysis as

described in Figure. S3. pin1-1 cells showed significantly reduced lobe formation compared to wide type (n = 400, t test p < 0.001), and 20 nM NAA did not rescue

this phenotype (n = 400, t test p > 0.1). Higher NAA concentrations had no effect on the pin1-1 phenotype either (Figures S5A and S5B).

(D) GFP-RIC4 distribution pattern in PCs of wild-type and pin1-1 mutant. GFP-RIC4 was localized to the cell cortex preferentially in lobe tips or lobe emergent

sites of wild-type PCs but was mostly diffuse in the cytosol in pin1-1 PCs.

(E) Quantitative analysis of the cortical GFP-RIC4 signal was performed as described in Figure. S2. Cortical signal of GFP-RIC4 dramatically decreased in pin1-1

mutant (n > 25, t test p < 0.001).

Also see Figure S5.


Figure 6. Auxin Activates the ROP6-RIC1 Pathway through ABP1

(A) PCs in both yuc1/2/4/6 and abp1-5 have wider neck regions than WT, similar to both rop6-1 and ric1-1 mutants (Fu et al., 2009, 2005), but different from

ROP2RNAi rop4-1, which has a narrower neck (Fu et al., 2005).

(B) Quantitative analysis of PCs phenotype showed that both yuc1/2/4/6 (t test, p < 0.01) and abp1-5 (t test, p < 0.001) had significantly wider neck regions than

WT. Data are mean neck width ± SD (n > 400 cells).

(C) YFP-RIC1 formed dot-like structures along cortical MTs in WT cells (left) (Fu et al., 2005, 2009). In yuc1/2/4/6 and abp1-5 cells, YFP-RIC1 lost its association

with MTs as in rop6-1 (n > 25). In rop6-1 mutants, YFP-RIC1 was mostly shifted to lobe regions (indicated by arrowheads) where ROP2 was presumably activated.

This YFP-RIC1 localization pattern is different from that in the yuc1/2/4/6 and abp1-5 mutants, where YFP-RIC1 became diffusely localized to the cytosol because

ROP2 is inactivated in these mutants.

(D) Auxin enhanced YFP-RIC1 association with cortical MTs in a rop2-1 rop4-1 mutant, but not in the abp1-5 mutant. PCs transiently YFP-RIC1 were treated with

NAA (10 nM) and imaged by confocal microscopy before and 10 min after treatment. In rop2-1 rop4-1 PCs, YFP-RIC1 was associated with MTs in a beads-on-a-

stringpattern. NAA enhanced this localization pattern as indicated by arrowheads. In abp1-5 cells, the weak YFP-RIC1association with MTs did not show the dotted

pattern and was not altered by NAA treatment. At least 15 cells were tracked for each mutant and showed similar response to NAA. The scale bar represents 10 mm.

(E) A time-course analysis of YFP-RIC1 association with MTs. At 4 and 8 min after NAA treatment, YFP-RIC1 dots gradually increased in both intensity and

number by auxin treatment in rop2-1 rop4-1 but not abp1-5 cells.

(F and G). Quantitative analysis of YFP-RIC1 dot number and intensity shown in (D) and (E). (F) YFP-RIC1 association with MTs was measured by the number of

YFP-RIC1 dots unit length of MTs. Data are mean dot number per mm ± SD (n = 50). (G) Average intensity of YFP-RIC1 dots was measured from 0 min to 8 min.

The intensity at time 0 was standardized as 1. Data are relative mean intensity compared to time 0 ± SD (n = 100).

(H). Auxin failed to increase ROP6 activity in abp1-5 muants. GTP-bound GFP-ROP6 in protoplasts isolated from a abp1-5 line stably expressing 35S::GFP-

ROP6 was analyzed as described in Figure 2.

Also see Figure S6.


Auxin Activates ROP6 RapidlyTo further confirm auxin activation of the ROP6-RIC1 pathway,

we determined the effect of auxin on ROP6 activity. Indeed,

auxin treatments increased the amount of active ROP6 in a

dosage-dependent manner (Figures 2A and 2B). The range of

NAA concentrations for ROP6 activation was similar to that for

ROP2 activation, but the saturation of ROP6 activation required

higher NAA levels. Like ROP2, ROP6 was rapidly activated within

30 s after 100 nM NAA treatment (Figures 2C and 2D), consistent

with a role for ABP1 in the perception of auxin that activates

ROP6. ABP1-dependent ROP6 activation by auxin was further

demonstrated by our finding that the auxin-dependent increase

in ROP6 activity was abolished by the abp1-5 mutation

(Figure 6H). The activation of two antagonizing ROPs (ROP2

and ROP6) by the same auxin perception system with a similar

auxin response range but distinct saturation kinetics may

provide a mechanism for the localized activation of ROP2 and

ROP6 in the complementary lobing and indenting sides by

uniformly applied auxin (see Discussion).

DISCUSSION

The findings here have several important implications. First,

these results establish a cytoplasmic auxin-signaling mecha-

nism that is distinct from the TIR1-based nuclear auxin-signaling

pathway and provides a perspective of auxin action at the

cellular level. Second, our findings give insights into hormonal

signaling leading to changes in the cytoskeleton and vesicular

trafficking, which is crucial for hormone action in plants yet

scarcely studied. Third, we show that ABP1 acts upstream of

ROP GTPase signaling, which gives an unprecedented under-

standing of signaling events downstream of the auxin perception

by ABP1, whose mode of action has been long sought for.

Finally, our results suggest that the ABP1- and ROP-dependent

auxin signaling plays a pivotal role in the spatial coordination of

cell expansion within and between cells during interdigitated

growth of PCs. Since auxin is a multifunctional hormone polarly

transported out of cells, this auxin-signaling mechanism could

serve as a common mode of intracellular and intercellular coor-

dination of cell growth, morphogenesis and polarity in plants.

An Auxin-Signaling Mechanism Regulates CytoplasmicPathwaysThe TIR1/AFB-dependent nuclear auxin-signaling system is

essential for auxin-mediated growth, development, and pattern-

ing that rely changes in gene expression (Dharmasiri et al.,

2005a, 2005b; Kepinski and Leyser, 2005; Mockaitis and Estelle,

2008). Previous work hints toward the existence of other auxin-

signaling mechanisms (Badescu and Napier, 2006), and our

findings here clearly establish a distinct auxin-signaling mecha-

nism that exists in the cell boundary/cytoplasm and is capable of

responding to auxin in seconds. Complementary to the TIR1

nuclear pathway impacting auxin-mediated gene expression,

the ABP1/ROP-dependent pathways directly regulate cytoplam-

sic events such as actin and microtubule organization and PIN

protein trafficking. Thus, our findings shed light into the dark

box of the mechanism by which auxin modulates cytoskeletal

reorganization and cell morphogenesis in multicellular tissues

of plants. Although our work here focuses on the roles of this

auxin-signaling mechanism in PC interdigitation, it is likely that

similar ABP1-ROP signaling pathways may operate in other plant

cells and tissues because of widespread expression and func-

tions of ABP1 and ROPs in plants (Braun et al., 2008; Chen

et al., 2001a, 2001b; Fu et al., 2005, 2002, 2009; Jones, 1994;

Jones and Herman, 1993; Jones et al., 1998).

Our findings here do not exclude the involvement of ROPs

in the regulation of TIR1/AFB-dependent auxin responses. In

fact, it was shown in tobacco and Arabidopsis protoplasts that

expression of dominant-negative or constitutively active forms

of the tobacco NtRac1 ROP affected auxin-induced gene

expression (Tao et al., 2002), and thus ROP may also regulate

the nuclear pathway in addition to the cytoplasmic pathways.

ABP1 May Be a Cell-Surface Auxin Receptorthat Activates ROP2 and ROP6 SignalingHere, we show ABP1 is required for the rapid activation of PM-

localized ROP2 and ROP6 by auxin. ABP1 is partially associated

with the outer surface of the PM through its binding to a GPI-

anchored protein (Shimomura, 2006), and the cell surface-asso-

ciated ABP1 mediates auxin activation of cell expansion (Chen

et al., 2001a; Jones et al., 1998). Hence we propose that ABP1

may be a cell surface receptor of auxin that controls PC interdig-

itation. This is also consistent with our finding that PIN1-

mediated auxin export is required for ROP2 activation. ABP1 is

not a transmembrane protein and likely works with a trans-

membrane partner or coreceptor, whose identification will be

crucial for understanding how auxin is perceived at the cell

surface and how it leads to ROP activation in the cytoplamic

side of the PM.

A Working Model for the Coordination of InterdigitatedCell Growth and BeyondWe propose a working model for the auxin signaling pathways

required for interdigitated growth (i.e., development of comple-

mentary lobes and indentations) in PCs (Figure 7). In this paper,

we demonstrate that ABP1-mediated auxin perception activates

both of the ROP2 and ROP6 pathways, which were previously

shown to be locally activated at opposing sides of the cell wall

but mutually exclusive along the PM within a PC (Fu et al.,

2005, 2009; Yang, 2008). At the steady state, therefore, simulta-

neous activation of ROP2 and ROP6 by localized extracellular

auxin must occur at the opposing sites (lobe and indentation

bordered by the cell wall) but not at the same site. A key aspect

of this working model is the existence of an auxin-ROP2-PIN1-

auxin positive feedback loop, which acts together with the

antagonizing ROP6 pathway to generate the presumed localized

extracellular auxin. Importantly, this working model can explain

how extracellular auxin coordinates lobe and indentation devel-

opment at the steady state, once the interdigitation pattern has

been initiated (i.e., the cell region for lobe formation or indenta-

tion has already been established).

Positive feedback loop initiated by a stochastic local change

in Rho GTPase signaling has been proposed to be a mechanism

for the establishment of self-organizing cell polarity in yeast

and animal cells (Altschuler et al., 2008; Hazak et al., 2010;

Paciorek et al., 2005; Van Keymeulen et al., 2006; Xu et al.,


2003). In neutrophil and other animal cells, the perception of

uniform concentrations of chemoattractants by a single receptor

leads to establishment of the frontness and backness polarity

by activating two antagonistic cytoskeleton-regulating Rho

GTPase pathways (Hazak et al., 2010; Paciorek et al., 2005;

Van Keymeulen et al., 2006; Xu et al., 2003). Similarly, the

activation of the antagonistic ROP2 and ROP6 pathways by

the ABP1 perception of uniform concentrations of auxin could

also explain how uniformly applied auxin leads to the establish-

ment of cell cortical regions that define lobe- or indentation-

forming sites to initiate the interdigitation pattern (Figures 1

and 7). Therefore the self-organization design principles for the

spatial coordination of cell growth and movement might be

conserved in both single and multicellular tissue across eukary-

otic kingdoms.

Our working model may serve as a unifying mechanism for the

coordination of cell morphogenesis and polarity within various

plant tissues. Auxin appears to orchestrate PIN polarization in

files of cells directing auxin flow (Paciorek et al., 2005; Sauer

et al., 2006) and in coordinating hair positioning in root-hair-

forming cells (Fischer et al., 2006). The position of root hair

formation can be predicted by the polar localization of ROP2 in

the hair forming cells (Jones et al., 2002), and ROP2 polar local-

ization is affected by auxin (Fischer et al., 2006; Yang, 2008),

raising the possibility that the auxin-mediated ROP signaling

may also underlie the coordination of polar cell growth among

root epidermal cells.

Our working model here could also be used to explain how

auxin may coordinate the polarization of PIN proteins to the

same cell end among a file of cells that direct auxin flow, i.e.,

auxin could activate a ROP2-like pathway that forms a positive

feedback loop at the end of PIN localization as well as

a ROP6-like pathway that antagonizes with the ROP2-like

pathway at the side lacking PIN localization. Auxin was shown

to inhibit PIN internalization in root cells (Dhonukshe et al.,

2008; Paciorek et al., 2005), which is also in agreement with

our finding in this report that PIN1 internalization is increased

when ROP2 function is compromised in PCs. In further support

of a role for ROP signaling in the modulation of PIN polarization,

Interactor of Constitutively active ROP 1 (ICR1), a likely ROP

effector protein, was recently found to regulate PIN polarization

both in Arabidopsis embryonic and root cells (Hazak et al., 2010).

Importantly, ABP1 is shown to affect PIN protein localization in

root cells and other types (Robert et al., 2010 [this issue of

Cell]), providing strong argument for a general role of the

ABP1-ROP signaling in the modulation of PIN polarization.

Therefore we anticipate that the elucidation of the ROP-based

cytoplasmic auxin signaling pathways in various auxin-mediated

processes will likely be an exciting and fertile area of research in

cell and developmental biology in the coming years.


Plant Materials and Growth Conditions

Arabidopsis plants were grown at 22�C on MS agar plates or in soil with 16 hr

light/8 hr dark cycles unless indicated otherwise. The DR5::GUS line and the

yuc1 yuc2 yuc4 yuc6 quadruple mutant were kindly provided by Tom Guilfoyle

and Yunde Zhao, respectively (Cheng et al., 2006; Hagen and Guilfoyle, 2002).

The double-mutant ROP2RNAi rop4-1 line was described previously (Fu et al.,

2005). The pin1-1 and pin1-5 mutants are T-DNA insertional lines obtained

from ABRC (SALK, CS8065, and 097144, respectively) and their genotypes

were confirmed by PCR analysis.

The abp1-5 allele contains a missense mutation of C/G in the 94 codon of

the coding sequence. Tilling mutant abp1-5 was backcrossed 6 times with

Col-0 and genotyped by restriction digestion of PCR fragments (see Supple-

mental Information for details). For genetic complementation, abp1-5 was

transformed with the Arabidopsis wild-type ABP1 cDNA driven by the 35S

promoter.

Conditional plants for ABP1 expression were obtained by expressing either

a full-length antisense construct or the recombinant single-chain fragment

variable 12 derived from the monoclonal anti-ABP1 antibody mAb12 under

the control of the ethanol inducible system as described (Braun et al., 2008;

David et al., 2007). Ethanol induction was obtained by exposure of siblings

to ethanol vapor generated from 500 ml of 5% ethanol in a microtube placed

at the bottom of sealed square plate.

Confocal and Imprinting Analysis of Leaf Arabidopsis PC Shape

PC shape from Arabidopsis cotyledons was imaged directly on confocal

microscopy (Leica SP2) or indirectly by an imprinting method (Mathur and

Figure 7. A Working Model for Auxin

Control of Interdigitated Cell Growth

(A) A model for coordination of two ROP signaling

pathways by localized extracellular auxin, which

results from a PIN1-mediated positive feedback

loop.

(B) A model for auxin control of interdigitated

growth through inter- and intra-cellular coordina-

tion of the ROP2 and ROP6 pathways. We surmise

that the PC intergditated growth is controlled by an

auxin-dependent self-organizing mechanism. In

this mechanism, localized extracellular auxin,

which is generated by self-activation via the

auxin/ROP2/PIN1/auxin feedback loop and

self-maintenance via the antagonizing ROP6

pathway, controls cell-cell coordination of lobing

and indentating by activating the complementary

ROP2 and ROP6 pathways in two adjacent cells,

which are mutually exclusive within each cell to

allow for the formation of alternating lobes and

indentations (Fu et al., 2005, 2009).


Koncz, 1997). Since PCs are auto-fluorescent, their cell outlines can be

imaged on confocal microscopy with the following settings: excitation

351 nm or 364 nm, 50% laser power and emission 400-600 nm. For some

treatments, the cotyledons were curved, so analyzing cell shapes by confocal

microscopy was difficult. In this case, an agarose imprinting method was used

(Mathur and Koncz, 1997), and .cell outlines imprinted on the agarose were

imaged on bright field microscopy (Nikon). Additional image analyses involved

use of Metamorph 4.5. The images are edited by photoshop 7.0 by adjusting

figure sizes and resolution and adding labels.

Ballistics-Mediated Transient Expression in Leaf Epidermal Cells

Subcellular localization of GFP-RIC4, YFP-RIC1 and F-actin was analyzed

by use of transiently-expressed pBI221:GFP-RIC4, pUC:YFP-RIC1 and

pBI221:GFP-mTalin constructs as described previously (Fu et al., 2005,

2002). We used 0.8 mg pBI221:GFP-mTalin, 1 mg pBI221:GFP-RIC4 and 1 mg

pUC:YFP-RIC1 for particle bombardment. GFP and YFP signal was detected

5 hr after bombardment by use of a Leica SP2 microscope (GFP: 488 nm exci-

tation, 25% power; excitation 520–600 nm, gain at 600; YFP: 514 nm excita-

tion, 25% power; excitation 530–600 nm, gain at 600). Cells at stage II showing

similar medium levels of GFP (Fu et al., 2005, 2002) were chosen for GFP

marker analysis. For 3D reconstruction, optical sections in 1.0 mm increments

were imaged for each cell by use of the Leica software.

Naphthalene-1-Acetic Acid Treatments

Naphthalene-1-acetic acid (NAA) (Sigma, St. Louis, MO) was dissolved in

DMSO as 0.5 M stock solutions, which were diluted to the indicated concen-

trations in liquid MS (for seedling treatments) or W5 media (for protoplast treat-

ments). Seeds were germinated in the liquid MS media containing NAA or NPA.

Each treatment was repeated at least three times with the corresponding

controls.

Protoplast Preparation and PEG-Mediated Transient Expression

Protoplast preparation and PEG-mediated transient expression were

described previously (Sheen, 2001). The 2nd or 3rd pair of rosette leaves

from 2- or 3-week-old seedlings was used to prepare protoplasts. Protoplasts

were counted by use of a hemacytometer (Hausser scientific, Cat # 1483). An

amount of 105–106 protoplasts were used for ROP2 activity assay, and104–105

protoplasts were used for transient expression.

ROP2 and ROP6 Activity Assays in Protoplasts

Two different methods were used to analyze auxin activation of ROP2 in proto-

plasts. The first method involves a biochemical assay, in which GFP-tagged

active ROP2 or ROP6 was pulled down by use of MBP-RIC1. Protoplasts

were isolated from leaves of 2- or 3-week old 35S::GFP-ROP2 or –ROP6 trans-

genic seedlings as described previously (Jones et al., 2002; Sheen, 2001).

Isolated protoplasts were treated with different concentrations of NAA, or

with 100 nM for various times and frozen by liquid nitrogen. Total protein

was extracted from 105–106 treated protoplasts. Twenty micrograms of

MBP-RIC1-conjugated agarose beads were added to the protoplast extracts,

and incubated at 4�C for 3 hr. The beads were washed three times at 4�C(5 min each). GTP-bound GFP-ROP2 or -ROP6 that was associated with

the MBP-RIC1 beads was used for analysis by western blotting with an anti-

GFP antibody (Santa Cruz Biotechnology, Santa Cruz, CA). Prior to the pull-

down assay, a fraction of total proteins was analyzed by immunoblot assay

to determine total GFP-ROP2 or -ROP6 (GDP-bound and GTP-bound). The

amount of GTP-bound ROPs was normalized to that of total ROPs. The

level of GTP-bound ROPs relative to the control (0 nM NAA at 0 min) was

calculated by dividing the amount of normalized GTP-bound ROP2 or ROP6

from each treatment by the normalized amount from the control, which is

defined as ‘‘1.’’

In the second method, changes in GFP-RIC4 localization to the PM were

monitored in isolated protoplasts. Protoplasts were isolated from leaves of

wild-type plants (Col 0) or mutants as described above. Two micrograms of

a 35S::GFP-RIC4 construct was introduced into 104-105 protoplasts by

PEG-mediated transformation. Typically, 70%–80% of the protoplasts were

transformed. Protoplasts were incubated at 23�C for 5 hr to overnight, treated

with NAA (1 mM final concentration), and imaged immediately by use of a Leica

SP2 confocal microscope. The earliest possible time for imaging was 2 min

after NAA application. Time-lapse images were taken every 2–3 min.

Quantitative Analysis of GFP-RIC4 and YFP-RIC1 Localization

The images of GFP-RIC4 localization in both PCs and protoplasts were taken

by Leica SP2, and image analysis were conducted by Metamorph 4.5 using

region function. First we created a region along cell cortex. The average inten-

sity of GFP for this was calculated by Metamorph. Then we created a region

just inside of the cell cortex, which included all cytoplasm signals, and the

average cytoplasmic signal was calculated. The average signals were then

used to calculate the ratio of PM/Cyto.

YFP-RIC1 was transiently expressed in PCs using the ballistics-mediated

method as described above. Four to five hours after bombardments, leaves

were treated with 10 nM NAA, and time-series YFP-RIC1 images are taken

using a Leica SP2 confocal microscope 2 min after treatement. The average

intensity of YFP-RIC1 dots along MT and the length of MT bundle were directly

measured by the Metamorph software, and the number of YFP-RIC1 dots was

counted by eyeballing. YFP-RIC1 dots No./mm indicates the number of YFP-

RIC1 dots divided by MT length.

Immunolocalization of PIN1, RIC1, and MT in PCs

Whole-mount immunostaining of Arabidopsis leaves was previously described

(Fu et al., 2005; Wasteneys et al., 1997). Fixed, shattered and permeabilized

leaves were incubated with primary antibody (anti-PIN1 1:200, anti-RIC1

1:100, anti-aTubulin 1:200) overnight at 4�C (Paciorek et al., 2005), and

then incubated with the second antibody (FITC conjugated anti-rabbit IgG

1:200, TRITC conjugated anti-mouse IgG 1:200) for 2 hr at 37�C. Stained

cells were observed in Leica SP2 confocal microscope. Cells at stage II

(Fu et al., 2005, 2002) were chosen for comparison between wild-type and

mutant cells.


Supplemental Information includes Extended Experimental Procedures and

six figures and can be found with this article online at doi:10.1016/j.cell.

2010.09.003.

ACKNOWLEDGMENTS

We are grateful to Veronica Grieneisen, Ben Scheres, Athanasius F. M. Maree,

Paulien Hogeweg, Xuemei Chen, and G. Venugopala Reddy for their stimu-

lating discussion and critical comments on this manuscript; and to Xinping

Cui for her assistance with the statistical analysis. We are grateful to Tom Guil-

foyle and Yunde Zhao for their generous supply of Arabidopsis mutant lines

used in this work. This work is supported by grants from the U.S. National Insti-

tute of General Medical Sciences to Z.Y. (GM081451) and to A.M.J.

(GM065989), by the National Science Foundation to A.M.J. (MCB-0718202)

and the Department of Energy to A.M.J. (DE-FG02-05ER15671) and to Z.Y.

(DE-FG02-04ER15555) and by the Research Foundation-Flanders (Odysseus)

to J.F.

Received: March 13, 2010


Accepted: July 30, 2010


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ABP1 Mediates AuxinInhibition of Clathrin-DependentEndocytosis in ArabidopsisStephanie Robert,1,2,11 Jurgen Kleine-Vehn,1,2,11 Elke Barbez,1,2 Michael Sauer,1,2,12 Tomasz Paciorek,1,2 Pawel Baster,1,2

Steffen Vanneste,1,2 Jing Zhang,1,2 Sibu Simon,3 Milada �Covanova,3 Kenichiro Hayashi,4 Pankaj Dhonukshe,5

Zhenbiao Yang,6 Sebastian Y. Bednarek,7 Alan M. Jones,8 Christian Luschnig,9 Fernando Aniento,10 Eva Za�zımalova,3

and Ji�rı Friml1,2,*1Department of Plant Systems Biology, VIB, 9052 Gent, Belgium2Department of Plant Biotechnology and Genetics, Ghent University, 9052 Gent, Belgium3Institute of Experimental Botany, ASCR, 165 02 Praha 6, Czech Republic4Department of Biochemistry, Okayama University of Science, Okayama 700-0005, Japan5Department of Biology, Utrecht University, 3584 CH Utrecht, The Netherlands6Department of Botany and Plant Sciences and Center for Plant Cell Biology, Institute for Integrative Genome Biology, University of California,

Riverside, Riverside, CA 92521, USA7Department of Biochemistry, University of Wisconsin, Madison, Madison, WI 53706-1544, USA8Departments of Biology and Pharmacology, University of North Carolina, Chapel Hill, NC 27599, USA9Institute for Applied Genetics and Cell Biology, University of Natural Resources and Applied Life Sciences, BOKU, 1190 Wien, Austria10Departamento de Bioquımica y Biologıa Molecular, Universidad de Valencia, 46100 Burjassot, Spain11These authors contributed equally to this work12Present address: Centro Nacional de Biotecnologıa Consejo Superior de Investigaciones Cientıficas Departamento de Genetica Molecular

de Plantas c/ Darwin n� 3, Lab. 316 Campus de Cantoblanco, 28049 Madrid, Spain


SUMMARY

Spatial distribution of the plant hormone auxin regu-lates multiple aspects of plant development. Theseself-regulating auxin gradients are established bythe action of PIN auxin transporters, whose activityis regulated by their constitutive cycling betweenthe plasma membrane and endosomes. Here, weshow that auxin signaling by the auxin receptorAUXIN-BINDING PROTEIN 1 (ABP1) inhibits the cla-thrin-mediated internalization of PIN proteins. ABP1acts as a positive factor in clathrin recruitment tothe plasma membrane, thereby promoting endocy-tosis. Auxin binding to ABP1 interferes with thisaction and leads to the inhibition of clathrin-mediatedendocytosis. Our study demonstrates that ABP1mediates a nontranscriptional auxin signaling thatregulates the evolutionarily conserved process of cla-thrin-mediated endocytosis and suggests that thissignaling may be essential for the developmentallyimportant feedback of auxin on its own transport.

INTRODUCTION

The plant signaling molecule auxin is an important regulator of

plant developmental processes, including embryogenesis,

organogenesis, tissue patterning, and growth responses to

external stimuli (Santner and Estelle, 2009; Vanneste and Friml,

2009). Current models on auxin signaling and action focus on

the paradigm that auxin regulates the expression of subsets

of genes, thus eliciting different cellular and, consequently,

developmental responses. Nuclear auxin signaling involves the

F box protein transport inhibitor response 1 (TIR1), which acts

as an auxin coreceptor (Kepinski and Leyser, 2005; Dharmasiri

et al., 2005a, 2005b; Tan et al., 2007), and downstream Aux/

IAA and ARF transcriptional regulators (Dharmasiri and Estelle,

2004). This pathway controls a remarkable number of auxin-

mediated processes, but some rapid cellular responses to auxin

are not associated with TIR1-based signaling (Badescu and

Napier, 2006; Schenck et al., 2010).

Decades ago, the plant-specific protein AUXIN-BINDING

PROTEIN 1 (ABP1) was proposed to be an auxin receptor (Hertel

et al., 1972; Lobler and Klambt, 1985). ABP1 in both monocot

and dicot plant species shows physiological affinities toward

natural and synthetic auxin ligands (Jones, 1994). ABP1, despite

carrying a KDEL-endoplasmic reticulum (ER) retention motif, is

secreted to some extent to the extracellular space where it is

active (Jones and Herman, 1993; Tian et al., 1995; Henderson

et al., 1997). ABP1 is essential for embryogenesis (Chen et al.,

2001) and postembryonic shoot and root development (Braun

et al., 2008; Tromas et al., 2009) and mediates auxin effect on

cell elongation, but the underlying mechanism remains unclear

(Jones et al., 1998; Leblanc et al., 1997).

An important regulatory level in auxin action is its differential

distribution within tissues (Vanneste and Friml, 2009). Such auxin

gradients result from local auxin biosynthesis and directional,


intercellular auxin transport (Petrasek and Friml, 2009) that

is triggered by a network of carrier proteins (Swarup et al.,

2008; Geisler et al., 2005; Petrasek et al., 2006; Vieten et al.,

2007; Yang and Murphy, 2009). The directionality of auxin flow

depends on the polar plasma membrane distribution of PIN-

FORMED (PIN) auxin efflux carriers (Wi�sniewska et al., 2006).

In addition to PIN phosphorylation that directs PIN polar target-

ing (Friml et al., 2004; Michniewicz et al., 2007), PIN activity can

be regulated by constitutive endocytic recycling from and to the

plasma membrane (Geldner et al., 2001; Friml et al., 2002;

Dhonukshe et al., 2007). Auxin itself inhibits the internalization

of PIN proteins, increasing their levels and activity at the plasma

membrane (Paciorek et al., 2005). The molecular mechanism of

this auxin effect remains unknown, but it has been proposed to

account for a feedback regulation of cellular auxin homeostasis

and for multiple auxin-mediated polarization processes (Leyser,

2006). Here, we show that auxin regulation of PIN internalization

involves the ABP1-mediated signaling pathway that targets cla-

thrin-mediated endocytosis at the plasma membrane.

RESULTS

Auxin Inhibits PIN Internalization by a Rapid,Nontranscriptional MechanismPIN proteins dynamically cycle between the endosomes and the

plasma membrane (Geldner et al., 2001; Dhonukshe et al., 2007).

Plasma membrane-localized PIN1 rapidly internalizes in

response to the vesicle trafficking inhibitor brefeldin A (BFA)

(Geldner et al., 2001), and this intracellular PIN accumulation is

inhibited by auxins (Paciorek et al., 2005). In addition, auxin

mediates with slower kinetics the degradation of PIN proteins

(Sieberer et al., 2000; Abas et al., 2006). The auxin effects on

PIN internalization and PIN degradation involve distinct mecha-

nisms (Sieberer et al., 2000; Paciorek et al., 2005; Abas et al.,

2006). These processes can be largely distinguished by BFA

treatments at 25 and 50 mM that inhibit preferentially recycling

or also vacuolar targeting for degradation, respectively (Sieberer

et al., 2000; Abas et al., 2006; Kleine-Vehn et al., 2008).

We addressed the characteristics of the auxin signaling mech-

anism for inhibiting PIN internalization. It is experimentally estab-

lished that the auxin regulation based on nuclear signaling

requires at least �10–15 min for execution (Badescu and Napier,

2006), whereas auxin inhibited the PIN2-GFP internalization

more rapidly (<5 min) (Figures 1A and 1B). This suggests that

this process does not involve auxin-dependent regulation of

gene expression. Consistently, chemical inhibition of transcrip-

tion (cordycepine or actinomycin D treatment) (Figure S1

available online) or de novo protein synthesis (cycloheximide

treatment) (Figure 1C) does not prevent the auxin-mediated inhi-

bition of PIN internalization.

Auxin Inhibits PIN Internalization by a TIR1-IndependentPathwayTo elucidate the molecular mechanism by which auxin inhibits

PIN internalization, we first tested the involvement of the TIR1-

mediated signaling by genetical or chemical interference with

different steps of this pathway. We analyzed (1) the quadruple

tir1/afb mutant deficient in most of the TIR1/AFB auxin receptors

function, (2) dominant lines conditionally expressing the stabi-

lized transcriptional inhibitor IAA17 (HS::axr3-1), (3) stabilized

mutations in other Aux/IAA-encoding genes (axr2-1, axr3-1,

shy2-2, and slr-1), and (4) silenced lines for multiple ARFs

(2X35S::miRNA160), as well as (5) seedlings treated with the pro-

teasome inhibitor MG132 that interferes with auxin-mediated

degradation of Aux/IAA repressors (Figures 1D–1H and

Figure S1). These manipulations have all been shown to strongly

inhibit TIR1-mediated transcriptional auxin responses (Timpte

et al., 1994; Fukaki et al., 2002; Tian et al., 2002; Knox et al.,

2003; Dharmasiri et al., 2005b). Moreover, interference with the

TIR1 pathway can be visualized (Figures 1I–1M and Figure S1)

by monitoring the activity of the synthetic auxin-responsive

promoter DR5, which is an indicator for TIR1-dependent gene

Figure 1. Auxin-Mediated Inhibition of

Endocytosis by Nontranscriptional, TIR1-

Independent Mechanism

(A–C) Time lapse showing BFA-induced increase

of PIN2-GFP endosomal signal and its intracel-

lular accumulation within minutes (A). NAA

treatment effectively and rapidly inhibits BFA-

induced PIN2-GFP internalization (B) also when

protein synthesis is inhibited by cycloheximide

(CHX) (C).

(D–H) BFA treatment for 90 min induces intracel-

lular accumulation of PIN1 (D). Auxins, such as

NAA (30 min pretreatment), inhibit BFA-induced

PIN1 internalization in the wild-type (E); in the

TIR1-mediated auxin signaling-deficient mutants,

such as overexpressors of stabilized IAA17

(HS::axr3-1; induced for 2 hr at 37�C) (F); in the

tir/afb quadruple mutant (G); and after MG132-

mediated inhibition of proteasome function (H).

See also Figure S1.

(I–M) Auxin treatments for 3 hr, such as NAA (J),

but not BFA alone (I), induce transcriptional auxin response monitored by DR5::GUS in the wild-type (J), but not in the HS::axr3-1 (K) and tir/afb quadruple

(L) mutants or after MG132 treatment (M). See also Figure S1.

Arrows mark PIN proteins internalized into BFA compartments. Arrowheads highlight PIN retention at the plasma membrane. Scale bar, 10 mm.


expression (Ulmasov et al., 1997). As expected, treatments with

different auxins increased the DR5::GUS expression in the wild-

type root, but following interference with the TIR1 pathway, auxin

was ineffective in inducing DR5 activity (Figures 1I–1M). In

contrast, all of these manipulations did not interfere with the

auxin inhibition of PIN internalization as monitored by BFA-

induced intracellular PIN1 accumulation (Figures 1D–1H and

Figure S1). In addition, the kinetics of the auxin effect on endocy-

tosis in the quadruple tir1/afb mutant was indistinguishable from

that of the wild-type (Figures 2A–2L and Figure S2). Together,

these findings show that the auxin effect on PIN internalization

does not require TIR1-mediated auxin signaling.

This conclusion is seemingly contradictory to a previous report

that proposed TIR1 involvement in auxin effect on BFA-induced

PIN internalization (Pan et al., 2009). However, given the experi-

mental conditions used (BFA at 50 mM), the Pan et al. report

primarily addressed the auxin effect on PIN vacuolar trafficking

that, in terms of kinetics and molecular mechanisms involved,

is distinct from the regulation of PIN internalization (Figure S2

and Figure S3).

Auxin Effects on Transcription and PIN InternalizationInvolve Distinct Perception MechanismsTo independently test whether auxin regulation of gene expres-

sion and inhibition of PIN internalization require independent

signaling pathways, we tested a number of structural analogs

of the natural auxin indole-3-acetic acid (IAA) for both effects.

As expected, most analogs tested affected both gene

expression and PIN internalization, albeit often at different effec-

tive concentrations. Importantly, we also identified auxin-like

compounds that were specific for one or the other process

only. For example, a-(phenyl ethyl-2-one)-indole-3-acetic acid

(PEO-IAA) (Figure S3) did not induce the expression of

DR5rev::GFP reporter (Figure 3C) nor transcription of auxin-

inducible genes related to the TIR1-dependent signaling

pathway (Figure S3). However, similar to classical auxins, PEO-

A

VV

D

2NIP-itna

+1

NIP-itna

B C E F

V

V

V

V

VV

G JH I K L

2NIP-itna

+1

NIP-itna 3,2,

1bf

a/1

rit

3,2,

1bf

a/1

r it

3 ,2 ,

1bf

a/1

rit

3 ,2,

1bf

a/1

rit

3,2 ,

1b f

a /1

rit

3 ,2 ,

1bf

a/1

rit

Col

-0

BFA[25] NAA[10] 5 min



BFA[25] NAA[10] 60 min BFA[25]

NAA[10] 120 min BFA[25]

Col

-0

Col

-0

Col

-0

Col

-0

Col

-0

Figure 2. Auxin Effect on BFA-Induced PIN

Internalization

Kinetics of auxin effect on 25 mM BFA-induced PIN

internalization with different time points of auxin

pretreatment (0, 5, 15, 30, 60, and 120 min) in the

wild-type (A–F) and in the quadruple tir/afb mutant

(G–L). Note the comparable sensitivity of the

quadruple tir/afb mutant and wild-type to auxin

effect on PIN internalization. Auxin effect on PIN

protein internalization was immediate (within

minutes) but transient: prolonged auxin treatments

from 1 to 2 hr resulted in reduced inhibition of PIN

internalization (arrows). Scale bar, 10 mm. See also

Figure S2.

IAA inhibited the BFA-induced PIN inter-

nalization (Figure 3H). In contrast, another

auxin analog, 5-fluoroindole-3-acetic

acid (5-F-IAA), activated DR5rev::GFP

already at 5 mM (Figure 3D and Figure S3)

but failed to inhibit PIN internalization,

even at 25 mM (Figure 3I). These nonover-

lapping effects of compounds structurally related to auxin

suggest that auxin perception upstream of either regulation of

gene expression or PIN internalization involves distinct auxin-

binding sites, confirming independently that auxin utilizes

different signaling pathways for mediating these effects.

abp1 Knockdown Lines Have Decreased PINInternalizationAs the effect of auxin on PIN internalization is not mediated by

TIR1-dependent signaling, we addressed the possible role of

the putative auxin receptor, ABP1 (Jones, 1994; Napier et al.,

2002). To test the involvement of ABP1 in PIN1 internalization,

we monitored PIN subcellular dynamics in conditional immuno-

modulation and antisense abp1 knockdown lines (Braun et al.,

2008; Tromas et al., 2009). Following downregulation of ABP1,

the intracellular accumulation of PIN proteins in response to

BFA treatment was diminished (Figures 4A–4D and data not

shown). Similarly, pulse-labeling and time-lapse monitoring intra-

cellular fluorescence revealed that uptake of the endocytic tracer

FM4-64 was clearly reduced in roots of both immunomodulated

and antisense abp1 knockdown lines as compared to the wild-

type (Figure S4 and data not shown). In addition, a genetic inter-

action between abp1 knockdown lines and pin mutants (pin1-1

or eir1-1) was demonstrated by the enhancement of the single

mutant phenotypes (Figure S4). Thus, the ABP1 function is

required for PIN internalization and overall endocytosis, indicating

that ABP1 plays a positive role in regulating endocytosis in plants.

ABP1 Gain-of-Function Alleles Have Increased PINInternalizationNext, we tested the effect of ABP1 gain of function on PIN inter-

nalization. ABP1 is predominantly located in the lumen of the ER

due to a C-terminal ER retention signal (KDEL), but some ABP1 is

secreted and has been shown to be closely associated with the

plasma membrane (Jones and Herman, 1993; Henderson et al.,

1997; Shimomura et al., 1999).


To investigate the potential role of ABP1 outside of the ER

lumen, tobacco (Nicotiana tabacum; Bright Yellow 2 (BY-2))

suspension-cultured cells were transfected with PIN1

(35S::PIN1-RFP) and the Arabidopsis ABP1 variant lacking

the KDEL ER retention signal (35S::ABP1DKDEL-GFP). When the

full-length ABP1 protein was expressed (35S::ABP1-GFP), the

PIN1-RFP localized largely to the plasma membrane, similarly

to the control experiments (Figures 4E, 4F, and 4H). In contrast,

coexpression of PIN1-RFP with the secreted ABP1DKDEL-GFP

version resulted in a strong internalization of PIN1-RFP (Figures

4G and 4H), indicating that ABP1 exported from ER regulates

endocytosis.

When introduced into Arabidopsis seedlings, ABP1DKDEL-GFP

expression led to auxin-related phenotypes, such as three coty-

ledons, shorter roots, and reduced apical dominance, but

frequently resulted into seedling lethality or sterile development

already in the T1 generation (Figure 4I and data not shown).

To further characterize the role of ABP1 gain of function in

PIN1 internalization, we monitored the subcellular dynamics

of PIN1 proteins in the seedlings moderately expressing

ABP1DKDEL-GFP. In accordance with the transient BY-2 assays,

the ABP1DKDEL-GFP expression increased PIN1 internalization in

Arabidopsis root cells treated with 25 mM BFA for 30 min (Figures

4J–4L). In summary, ABP1 gain of function induces PIN internal-

ization, whereas reduced expression of ABP1 leads to reduced

PIN internalization. These results strongly suggest that ABP1

acts as a positive effector of endocytosis in plants.

Auxin Negatively Regulates ABP1 Action on PINInternalizationTo study the potential role of ABP1 in mediating auxin inhibition

of PIN internalization, we tested the auxin effect in BY-2 cells

coexpressing PIN1-RFP and ABP1DKDEL-GFP (Figure 5). Of

note, NAA treatment counteracted the positive effect of secreted

ABP1 on PIN internalization, leading to a preferential retention of

PIN proteins at the plasma membrane (Figure 5E). In contrast,

the structurally similar auxin analog 5-F-IAA, which promotes

auxin-dependent gene transcription but does not inhibit PIN1

endocytosis (Figure 3 and Figure S3), showed also no detectable

effect on ABP1-mediated PIN internalization (Figure 5F). This

observation is consistent with the reported weak affinity for

5-F-IAA of the plasma membrane-associated auxin-binding

site, which is likely related to ABP1 (Za�zımalova and Kuta�cek,

1985). These results, as well as similarities between knockdown

lines and auxin treatment, suggested a model in which auxin

inhibits ABP1-mediated stimulation of PIN internalization.

To test this scenario, we used the abp1-5 mutant allele (Xu

et al., 2010) with a point mutation in the conserved auxin-binding

pocket (Napier et al., 2002). Conversion of the conserved

histidine to tyrosine (H94Y) weakens the Pi interaction between

the side-chain ring and the indole ring and is, therefore, pre-

dicted to reduce the auxin-binding affinity without major steric

hindrance or changes in domain structure (Woo et al., 2002). In

contrast to ABP1 knockdown lines that showed an ‘‘auxin-like’’

inhibitory effect on PIN internalization, the abp1-5 allele was

partially resistant to auxin with respect to its effect on PIN inter-

nalization. Auxins, such as NAA or IAA, in abp1-5 root cells were

much less effective in inhibiting BFA-induced internalization of

PIN proteins than the wild-type roots (Figures 5H–5L).

Next, we deleted the KDEL ER retention signal in the abp1-5

mutant sequence. Similarly to ABP1DKDEL-GFP, the overexpres-

sion of ABP1-5DKDEL induced the PIN1-RFP internalization in

tobacco BY-2-cultured cells. But, in contrast to ABP1DKDEL-

GFP, the ABP1-5DKDEL-promoted PIN1 internalization was not

NAA[5]/BFA[25]G

NAA[5]

BFA[25]F

Untr. PEO[25]5FIAA[5]

PEO[5]/BFA[25]H 5FIAA[25]/BFA[25]I

V

V

PF

G::v

er

5R

D2

NIP -it na+

1N IP-itna

15

25

20

10

5

0 5[AAN].rt n

U

52[OEP] 5[AAIF5]

* *

A B C D E

Figure 3. Distinct Auxin Perception Mechanisms for the Regulation

of Transcription and Endocytosis

(A–D) Activity of auxin-responsive promoter DR5rev::GFP (A) induced by treat-

ment with auxin analogs, such as NAA (B) and 5-F-IAA (D) at 5 mM for 3 hr, but

not by PEO-IAA even at concentrations up to 25 mM (C).

(E) Relative DR5rev::GFP signal of meristematic cells versus nonmeristematic

cells. n = 3 independent experiments with at least 21 roots analyzed for each

assay. See also Figure S3.

(F–I) BFA-induced internalization of PIN1 and PIN2 (F) inhibited by NAA (G) and

PEO-IAA (H) at 5 mM, but not by 5-F-IAA (all 30 min pretreated), even at

concentrations up to 25 mM (I).

Arrows mark PIN proteins internalized into BFA compartments. Arrowheads

mark the PIN retention at the plasma membrane. Scale bar, 10 mm. Error

bars represent standard deviation. *p < 0.05.


counteracted by exogenous auxin application, indicating an

auxin resistance due to a decreased affinity of auxin binding to

the auxin-binding pocket in the ABP1-5DKDEL modified version.

This result shows that mutations in the auxin-binding pocket of

ABP1 led to a decrease in auxin sensitivity of auxin-mediated

inhibition of PIN internalization, supporting our hypothesis that

auxin binding to ABP1 inhibits the positive action of ABP1 on

endocytosis.

Auxin Specifically Targets Clathrin-Based Mechanismof EndocytosisPrevious work using single cells suggested that PIN proteins are

cargos of endocytic mechanism involving the vesicle coat

protein clathrin (Ortiz-Zapater et al., 2006; Dhonukshe et al.,

2007). Thus, we examined the role of clathrin in PIN internaliza-

tion in planta by conditionally overexpressing the C-terminal

part of clathrin heavy chain (termed HUB1) that exerts a dominant

negative effect on clathrin function by binding and consequently

depleting clathrin light chains (Liu et al., 1995). This interference

with the clathrin function inhibited the BFA-induced PIN internal-

ization, confirming that PIN proteins are internalized in Arabidop-

sis root cells by the clathrin-based mechanism of endocytosis

(Figure S5).

To specifically test whether auxin inhibits clathrin-mediated

endocytosis, we monitored the internalization of a well-estab-

lished and specific cargo of clathrin-dependent endocytosis,

the human transferrin receptor (hTfR) and its ligand transferrin.

In Arabidopsis protoplasts, which heterologously expressed

hTfR, exogenously applied transferrin was efficiently internal-

ized (Figures 6A), as shown previously (Ortiz-Zapater et al.,

2006). As expected, this internalization was completely

blocked by tyrphostin A23, a known inhibitor of clathrin-medi-

ated processes (Banbury et al., 2003; Konopka et al., 2008)

(Figure 6B and Figure S5). Physiological levels of natural

(IAA; data not shown) and synthetic (NAA; Figure 6C) auxins

rapidly and efficiently inhibited transferrin internalization in

hTfR-expressing Arabidopsis protoplasts, demonstrating that

auxin-mediated inhibition of endocytosis targets a general

clathrin mechanism and is not cargo specific. In contrast,

NAA was ineffective in inhibiting the hTfR internalization in

HeLa cells (data not shown), suggesting that the effect of

auxin on the clathrin endocytotic pathway requires plant-

specific factors. These auxin effects on internalization of both

endogenous and heterologous cargos of the clathrin pathway

suggest that auxin targets the clathrin-mediated mechanism

of endocytosis.

A B C

F GE H

I J K

D

L

Figure 4. Positive ABP1 Role in PIN Internal-

ization

(A–D) Reduced BFA-induced PIN1 internalization in

inducible abp1 knockdown lines SS12S (B) and

SS12K (C) as compared to the induced wild-type

(A). Number of BFA compartments was reduced

after ABP1 downregulation in immunomodulation

(SS12S and SS12K) (D). Values in (D) represent

the relative mean surface area (pixels2) in compar-

ison with the wild-type for each individual experi-

ment. n > 3 independent experiments with a least

60 cells measured for each assay. See also

Figure S4.

(E–H) Cotransfection of tobacco BY-2 cells with

PIN1-RFP (0.05 mg) (in red) and ER marker HDEL-

GFP (0.05 mg) (E), full-length ABP1-GFP (0.5 mg)

(F), and ABP1 with deleted ER retention signal

(ABP1DKDEL-GFP) (0.05 mg) (G) (all in green). In

contrast to the full-length ABP1-GFP, the secreted

ABP1DKDEL-GFP induced pronounced PIN internal-

ization. Percentage of cells displaying severe

(green), mild (red), or no detectable (blue) PIN1-

RFP internalization (H). n > 3 independent experi-

ments and at least 60 cells counted for each assay.

(I–L) Phenotypes of 4-day-old 35S::ABP1DKDEL-

GFP stable transformed Col-0 seedlings. Primary

root growth defects and aberrant cotyledon

number observed in the primary transformants.

See also Figure S4. (I) BFA-induced internaliza-

tion of PIN1 within 30 min is promoted in

35S::ABP1DKDEL-GFP seedlings (K) versus the

Col-0 control (J). Relative number of BFA bodies

per cell (L). n = 3 independent experiments on

two different transformants and at least 150 cells

counted for each assay.

Arrows mark PIN protein internalization. Scale bar,

10 mm. Error bars represent standard deviation.

*p < 0.05; **p < 0.001.


Auxin Interferes with Clathrin Recruitmentto the Plasma MembraneTo address a possible mode of auxin action on clathrin-medi-

ated endocytosis, we tested for an auxin effect on clathrin

localization. As previously described (Konopka et al., 2008), cla-

thrin light chain fused to GFP (CLC-GFP) is associated with

intracellular endomembranes (presumably TGN) and with

dynamic foci at the plasma membrane (Figure 6D). The amount

of clathrin detected at the plasma membrane was variable and

strongly depended on growth conditions. Nonetheless, both

anti-CHC immunolocalizations (Figure S6) and time-lapse visu-

alizations of CLC-GFP revealed that auxin treatments led to

a decrease in the fluorescence associated with the plasma

membrane but had no detectable effect on clathrin association

with intracellular endomembranes (Figures 6D–6G and 6K and

Figure S6). The effect of auxin on clathrin recruitment to the

plasma membrane was rapid and transient and displayed

kinetics similar to those of the auxin-mediated inhibition of

PIN internalization (Figure S6). In contrast, auxin did not visibly

affect other regulators of the early and late endosomal traf-

ficking (Figure S5), including RabF2b (Rab5/Ara7) that is

required for PIN internalization, presumably at later steps of

endocytosis (Ueda et al., 2001; Dhonukshe et al., 2008). In

addition, PEO-IAA, the effective inhibitor of PIN protein internal-

ization, also showed an effect on clathrin incidence at the

plasma membrane (Figures 6I and 6K), whereas 5-F-IAA, which

is ineffective in the inhibition of PIN protein internalization,

showed no detectable effect on CLC incidence at the plasma

membrane (Figures 6J and 6K). These experiments demon-

strated that auxin specifically interferes with the clathrin

recruitment to the plasma membrane, providing a plausible

mechanism for auxin effect on the endocytosis of PIN1 and

other cargos.

Auxin Negatively Regulates ABP1 Actionon Clathrin-Dependent PIN InternalizationNext, we addressed the potential role of ABP1 in mediating auxin

effect on the clathrin-dependent endocytosis. First, we tested

the effect of the interference with the clathrin function on

ABP1-mediated PIN1 internalization. In BY-2 cells, the ABP1-

mediated internalization of PIN1 proteins was abrogated by the

inhibition of clathrin-mediated endocytosis either by expression

of the dominant-negative clathrin HUB1 (35S::HUB1-GFP) or by

treatment with tyrphostin A23 (Figures 7A–7D), indicating that

A B

D

H I J K

1NIP-itna

5-

1p

ba

5-1p

ba

NAA[5]/BFA[25]BFA[25]

V

E F

C5FIAA [10]

0

20

40

60

80

100

HDEL-GFPNAAUntr. 5FIAA NAAUntr. 5FIAA

Percentages of cells displaying PIN1 internalization

G

severe mild no PIN1 internalizationABP1ΔKDEL-GFP

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

L

BFA NAA/BFA

Number of B FA bodies per cell

Col-0 Col-0abp1-5 abp1-5

PFR-1

NIP PBA1

ΔPF

G-LEDK

PFR-1

NIPPF

G-LED

H

NAA [10]

PFR-1

NIP

M N

020406080

100

abp1-5 untr. abp1-5 NAAsevere mild no PIN1 internalization

Percentages of cells displaying PIN1 internalizationO

**

**

PFG-LE

DKΔ5-1P BA

Untr.

Untr.

0-loC

0-loC

NAA [10] Figure 5. ABP1 Involvement in Auxin-Medi-

ated Inhibition of PIN Protein Internalization

(A–G) Cotransfection of tobacco BY-2 cells with

PIN1-RFP (0.05 mg) (in red) (A-F) and ER marker

HDEL-GFP (0.05 mg) (A and B) or ABP1DKDEL-

GFP (0.05 mg) (D–F) (all in green). After transfection,

BY-2 cells were treated with NAA (B and E) or

5-F-IAA (C and F). NAA, but not 5-F-IAA, sup-

pressed the ABP1DKDEL-dependent effect on

PIN1 internalization. Percentage of cells displaying

severe (green), mild (red), or not detectable (blue)

PIN1-RFP internalization (G). n > 3 independent

experiments with at least 60 cells counted for

each assay.

(H–L) BFA-induced PIN internalization in wild-type

(H) and abp1-5 lines with mutation in auxin-binding

site of ABP1 (I). Whereas NAA (5 mM, 30 min

pretreatment) reduced the BFA-induced PIN

protein internalization in the wild-type (J), the

abp1-5 mutant seedlings were partially resistant

to this auxin effect (K). Average number of BFA

bodies per root cell in BFA- or NAA/BFA-treated

wild-type and abp1-5 mutant seedlings (L). n = 3

independent experiments with at least 150 cells

counted for each assay.

(M–O) Cotransfection of tobacco BY-2 cells with

PIN1-RFP (0.05 mg) (in red) (A–F) and mutated

ABP1-5DKDEL (0.05 mg) (in green) (M and N). After

transfection, BY-2 cells were treated with NAA (N).

NAA did not suppress the positive effect of ABP1-

5DKDEL with mutated auxin-binding site on PIN1

internalization.Percentageofcellsdisplayingsevere

(green), mild (red), or not detectable (blue) PIN1-RFP

internalization (O). n > 3 independent experiments,

and at least 60 cells counted for each assay.

Arrows mark PIN proteins internalized into BFA

compartments. Arrowheads mark the PIN reten-

tion at the plasma membrane. Scale bar, 10 mm.

Error bars represent standard deviation. *p <

0.05; **p < 0.001.


the functional clathrin machinery is required for ABP1 effect on

PIN internalization.

In addition, the effect of ABP1 downregulation on the clathrin

abundance at the plasma membrane was examined. The plasma

membrane association of clathrin was strongly reduced in both

immunomodulated (Figures 7E–7H and Figure S6) and antisense

abp1 knockdown lines (data not shown) when compared to wild-

type or noninduced controls. The auxin effect on clathrin abun-

dance at the plasma membrane was significantly lower in

abp1-5 mutant seedlings than in wild-type seedlings (Fig-

ures 7I–7M). Remarkably, these results correlate well with the

auxin resistance observed in the abp1-5 line for the effect on

PIN internalization.

These multiple lines of observation clearly linked ABP1 action

and clathrin mechanism of PIN internalization: (1) the positive

effect of ABP1 on PIN protein internalization requires the cla-

thrin-dependent endocytosis; (2) ABP1 action is required for cla-

thrin localization at the plasma membrane; and (3) a mutation in

the auxin-binding pocket of ABP1 conveys decreased auxin

sensitivity of auxin effect on clathrin abundance at the plasma

membrane. All of these results suggest that auxin binding to

ABP1 inhibits the positive action of ABP1 on clathrin-mediated

endocytosis.

DISCUSSION

Nonnuclear Auxin Signaling Targets Clathrin-Dependent Mechanism of Endocytosis in PlantsIn plants, the existence of endocytosis has been a matter of

debates for decades, but in recent years, its physiological impor-

tance has become increasingly obvious, and a number of endo-

cytic cargos have been identified (Robinson et al., 2008). The

pronounced inhibition of the bulk of the endocytic processes

after interference with the clathrin pathway (Dhonukshe et al.,

2007) and its accessory protein (such as dynamin-related

proteins) (Collings et al., 2008; Konopka et al., 2008) suggests

that most endocytic processes in plants depend on an evolution-

arily conserved mechanism involving clathrin.

We demonstrated through multiple approaches that clathrin-

mediated endocytosis is rapidly inhibited by auxin and that auxin

promotes the rapid disappearance of plasma membrane-asso-

ciated clathrin. Of note, this auxin signaling does not involve

the molecular components of the nuclear TIR1/AFB pathway

(Kepinski and Leyser, 2002; Dharmasiri and Estelle, 2004) and

does not require gene transcription or protein synthesis. This

auxin effect on endocytosis is not specific to PIN proteins but

regulates a number of endogenous and heterologous cargos.

V

V

Tyr23[350] NAA[10]FCA

nirrefsnarT

B

60 minD E F G

V

V V

V

Untr.

PFG-CLC

H

PFG- CLC

Untr.

V

V

I J

V

PEO[30]30 min

5FIAA[30]

0

20

40

60

80

100

Untr. NAA PEO 5FIAA

K Percentage of cellsshowing CLC-GFP at the PM

]NAA[30

V** **

30 min 120 min

Figure 6. Auxin Effect on Clathrin-Dependent

Endocytosis and Clathrin Recruitment to the

Plasma Membrane

(A–C) Heterologous expression of human transferrin

receptor in protoplast enabled Alexa633-labeled

transferrin internalization (A). Transferrin uptake was

blocked by both tyrphostin A23 (B) and auxin (NAA) (C).

See also Figure S5. Arrowheads mark internalized

proteins.

(D–K) Clathrin light-chain GFP (CLC-GFP) localization

at the trans-Golgi network (TGN) and the plasma

membrane (D). After auxin treatment for 30 (E) to 60 min

(F), the CLC-GFP transiently disappeared from the

plasma membrane but stayed at the TGN. After

longer auxin treatments (2 hr), CLC-GFP reappeared at

the plasma membrane (G). Arrowheads mark CLC-

GFP intensity at the plasma membrane. See also

Figure S5.

(H–J) PEO-IAA (30 mM for 30 min) inhibited the CLC-GFP

localization at the plasma membrane (I), whereas treat-

ment with 5-F-IAA (30 mM for 30 min) had no visible effect

(J, arrowheads).

(K) Percentage of cells showing CLC-GFP labeling at the

plasma membrane in untreated seedlings and treated

with NAA, PEO-IAA, and 5-F-IAA for 30 min. The

percentage of cells showing a plasma membrane localiza-

tion of CLC-GFP was calculated for at least 21 roots for

each condition. Arrowheads mark CLC-GFP intensity at

the plasma membrane.

Scale bar, 10 mm. Error bars represent standard deviation.

**p < 0.001.


These observations strongly suggest that nontranscriptional

auxin signaling interferes specifically with the general process

of clathrin-mediated endocytosis in plant cells.

ABP1 Acts as an Auxin-Sensitive, Positive Regulatorof Clathrin-Mediated EndocytosisTo identify the molecular mechanism underlying auxin effect on

endocytosis, we tested the involvement of the putative auxin

receptor ABP1 that is essential, but the mechanism of its action

remained unclear (Badescu and Napier, 2006). Our loss- and

gain-of-function analyses show that ABP1 acts as a positive

regulator of clathrin-mediated endocytosis. ABP1 seems to

be a plant-specific regulatory element of the evolutionarily

conserved clathrin-mediated endocytic mechanism. Because

ABP1 binds auxin with high affinity (Jones, 1994; Napier et al.,

2002), it is suggestive that auxin mediates its effect on clathrin-

mediated endocytosis via ABP1. In this scenario, given the

positive effect of ABP1 but the negative effect of auxin on endo-

cytosis, auxin binding to ABP1 inhibits rather than activates the

ABP1 action in endocytosis. This model (see Graphical Abstract)

is supported by several independent lines of evidence: (1) the

stereo-selectivity of auxins correlates with ABP1 binding

(Za�zımalova and Kuta�cek, 1985) and inhibition of endocytosis;

(2) both increasing auxin or decreasing the active pool of ABP1

diminishes the clathrin incidence at the plasma membrane and

inhibits the clathrin-dependent endocytosis; (3) increasing levels

of secreted ABP1 lead to enhanced endocytosis that can be

reversed by auxin treatment; and (4) an ABP1 with a mutated

auxin-binding site is less effective in mediating auxin effect on

clathrin incidence at the plasma membrane and on inhibition of

endocytosis.

These observations and, in particular, the remarkable differ-

ence between the knockdown abp1 and abp1-5 mutants provide

strong support for the model that auxin binding to ABP1 inter-

feres with its positive action on clathrin-mediated endocytosis.

However, it remains open by which mechanism this regulation

occurs.

Physiological Role of the ABP1 Pathway for Regulationof Clathrin-Dependent EndocytosisOur studies here have primarily focused on PIN auxin trans-

porters as targets for auxin- and ABP1-mediated regulation of

endocytosis. By this mechanism, auxin increases the incidence

of PIN proteins at the cell surface, stimulating auxin efflux

(Paciorek et al., 2005) and providing developmentally important

feedback of auxin on the rate of its intercellular flow. However,

a number of additional membrane proteins and other cargos of

clathrin-mediated endocytosis might be regulated in a similar

manner. A more general auxin effect on clathrin-dependent

endocytosis might be related to its phylogenetically ancient

role in the control of cell expansion (Lau et al., 2009), whereby

ABP1 also plays a crucial role (Jones et al., 1998). During this

process, when the cell surface rapidly increases, generally the

endocytosis rate is attenuated to retain the essential signaling

Figure 7. ABP1 Mediates Auxin Effect on

Clathrin-Dependent PIN Internalization

(A–D) Cotransfection of tobacco BY-2 cells.

ABP1DKDEL-GFP-dependent (green) promotion of

PIN1-RFP (red) internalization (A) is reduced

after inhibition of clathrin-dependent endocytosis

by HUB-GFP (green) (B) or tyrphostin A23 (C).

Percentage of cells displaying severe (green), mild

(red), or no detectable (blue) PIN1-RFP internaliza-

tion (D). n > 3 independent experiments and at least

60 cells counted for each assay. Arrows mark PIN

proteins internalization. Arrows indicate PIN inter-

nalization.

(E–H) Localization of clathrin as visualized by CLC-

GFP at the TGN and the plasma membrane

(E, arrowheads). In the abp1 knockdown immuno-

modulation lines, CLC-GFP labeling remained at

the TGN but decreased at the plasma membrane

(F and G). Percentage of the cells showing

CLC-GFP localization at the plasma membrane

(H). n = 3 independent experiments with at least

18 roots analyzed for each assay. See also

Figure S6. Arrowheads mark CLC-GFP at the

plasma membrane.

(I–M) Localization of clathrin as visualized by immu-

nodetection with an anti-CHC antibody at the TGN

and the plasma membrane in Col-0 and the abp-

1-5 lines mutated in the auxin-binding site. In the

abp1-5 mutant, depletion of clathrin from the

plasma membrane was less sensitive to NAA. (M)

Percentage of the cells showing CHC localization at the plasma membrane. n = 3 independent experiments with at least 15 roots analyzed for each assay. Arrow-

heads mark CHC immunolabeled intensity at the plasma membrane.

Scale bar, 10 mm. Error bars represent standard deviation. *p < 0.05; **p < 0.001.


and structural components at the cell surface. Of note, ABP1 has

also been connected to the ROP-GTPase pathway involved in

the interdigitating growth of epidermal pavement cells (Xu

et al., 2010), but the mechanistic link of this ABP1 function with

its role in the clathrin-mediated endocytosis is still missing.

Future work that builds on the proposed framework of the

ABP1 action in clathrin-mediated endocytosis is necessary in

order to understand how and with which components of the cla-

thrin machinery ABP1 communicates. The intriguing possibility

that the ABP1-mediated regulation of endocytosis is a part of

a long-looked mechanism for auxin-mediated cell expansion

and tissue polarization also remains open.


Material and Growth Conditions

Arabidopsis thaliana (L.) Heyhn. seedlings, Columbia ecotype (Col-0), were

grown on vertical half-strength Murashige and Skoog (0.5 MS) agar plates at

22�C for 4 days. BFA (Molecular Probes and Sigma), tyrphostin A23 (Sigma),

tyrphostin A51 (Sigma), cycloheximide (Sigma), cordecypin (Sigma), or actino-

mycin (Sigma) were used from 50 mM dimethylsulfoxide stock solutions and

added to the liquid 0.5 MS growth medium for the indicated times, if not

mentioned otherwise: 90 min with 25 mM BFA; 30 min with 5, 10, or 30 mM

of NAA; 30 min with 30 mM tyrphostin A23 or tyrphostin A51; and 30 min

with 50 mM cordycepin or actinomycin followed eventually by 90 min NAA or

NAA/BFA cotreatment. In control treatments, equal amounts of solvent were

used.

Transferrin Uptake Assays in Arabidopsis

Transferrin uptake in Arabidopsis protoplasts expressing hTfR was assayed

as described (Ortiz-Zapater et al., 2006) with transferrin-Alexa Fluor 546

(500 mg/ml, 28�C, 45 min). Tyrphostin A23 (350 mM) or auxin (10 mM NAA or

10 mM IAA) were added 15 min before transferrin and remained present during

the internalization period.

Immunodetection and Microscopy

Immunofluorescence in Arabidopsis roots was analyzed as described (Sauer

et al., 2006). The anti-PIN1 antibody (1:1000) (Benkova et al., 2003), the anti-

PIN2 antibody (1:1000) (Abas et al., 2006), and the anti-CHC antibody

(1:400) (Kim et al., 2001) were used, and the fluorochrome-conjugated

secondary antibodies Alexa488 and the anti-rabbit-Cy3 (1:600) (Dianova)

were used. Live-cell microscopy was done as described (Kleine-Vehn et al.,

2008).


Supplemental Information includes Extended Experimental Procedures, six

figures, and one table and can be found with this article online at doi:10.1016/

j.cell.2010.09.027.

ACKNOWLEDGMENTS

The authors thank the anonymous reviewer for helpful comments and Martine

De Cock for help in preparing the manuscript. We are very grateful to

X.Y. Chen, M. Estelle, T. Gaude, N. Geldner, O. Leyser, C. Perrot-Rechen-

mann, and J.W. Reed for sharing published materials and Drs. Jin-Gui Chen

and Ming-Jing Wu for generating abp1 mutants. This work was supported

by the Odysseus program of the Research Foundation Flanders, the Ministry

of Education of the Czech Republic (project LC06034), and the Ministerio de

Educacion y Ciencia (grant BFU2005-00071). E.B. is indebted to the Agency

for Innovation by Science and Technology for a predoctoral fellowship and

S.V. to EMBO for a long-term fellowship (ATLF 142-2007). M.S. was supported

by HFSP long-term and Marie Curie IEF fellowships. A.M.J is supported by

grants from The National Institute of General Medical Sciences (GM65989),

The Department of Energy (DE-FG02-05er15671), and The National

Science Foundation (MCB0718202, 0723515). P.D. is supported by NWO-

VENI grant.

Received: August 25, 2009

Revised: May 10, 2010

Accepted: September 14, 2010


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Activation-Induced Cytidine DeaminaseTargets DNA at Sites of RNA Polymerase IIStalling by Interaction with Spt5Rushad Pavri,1 Anna Gazumyan,1,2 Mila Jankovic,1 Michela Di Virgilio,1 Isaac Klein,1 Camilo Ansarah-Sobrinho,3

Wolfgang Resch,3 Arito Yamane,3 Bernardo Reina San-Martin,1,4 Vasco Barreto,1,5 Thomas J. Nieland,6 David E. Root,6

Rafael Casellas,3,* and Michel C. Nussenzweig1,2,*1Laboratory of Molecular Immunology2Howard Hughes Medical InstituteThe Rockefeller University, New York, New York 10065, USA3Genomics and Immunity, The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), and Center for Cancer Research,

National Cancer Institute (NCI), National Institutes of Health, Bethesda, MD 20892, USA4Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), INSERM U964 / CNRS UMR7104 / Universite de Strasbourg, 67404,

Illkirch, France5Laboratory of Epigenetics and Soma, Instituto Gulbenkian de Ciencia, P-2780-156 Oeiras Portugal6RNAi Platform, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA*Correspondence: [email protected] (M.C.N.), [email protected] (R.C.)

DOI 10.1016/j.cell.2010.09.017

SUMMARY

Activation-induced cytidine deaminase (AID) initiatesantibody gene diversification by creating U:G mis-matches. However, AID is not specific for antibodygenes; Off-target lesions can activate oncogenes orcause chromosome translocations. Despite itsimportance in these transactions little is knownabout how AID finds its targets. We performed anshRNA screen to identify factors required for classswitch recombination (CSR) of antibody loci. Wefound that Spt5, a factor associated with stalledRNA polymerase II (Pol II) and single stranded DNA(ssDNA), is required for CSR. Spt5 interacts withAID, it facilitates association between AID and PolII, and AID recruitment to its Ig and non-Ig targets.ChIP-seq experiments reveal that Spt5 colocalizeswith AID and stalled Pol II. Further, Spt5 accumula-tion at sites of Pol II stalling is predictive of AID-induced mutation. We propose that AID is targetedto sites of Pol II stalling in part via its associationwith Spt5.

INTRODUCTION

AID is a cytidine deaminase that initiates immunoglobulin

somatic hypermutation (SHM) and class switch recombination

(CSR) (Muramatsu et al., 2000, 1999; Revy et al., 2000). It does

so by deaminating cytidine residues in ssDNA (Bransteitter

et al., 2003; Chaudhuri et al., 2003; Dickerson et al., 2003;

Pham et al., 2003; Ramiro et al., 2003; Sohail et al., 2003). The

resulting U:G mismatches can be processed by several different

DNA repair pathways to produce mutations or DNA double-

strand breaks (Di Noia and Neuberger, 2007; Peled et al., 2008).

In addition to diversifying the antibody repertoire by SHM and

CSR, AID also contributes to malignant transformation by initi-

ating chromosome translocations (Ramiro et al., 2006; Ramiro

et al., 2004; Robbiani et al., 2008; Nussenzweig and Nussenz-

weig, 2010) and by producing mutations in non-Ig genes such

as Bcl-6 (Pasqualucci et al., 1998, 2001; Shen et al., 1998).

Although the comparative frequency of mutation at non-Ig genes

is low, AID mutates 25% of the genes transcribed in germinal

center B cells, where it is normally expressed (Liu et al., 2008).

Furthermore, even low levels of mutation are sufficient to

produce substrates for translocation (Robbiani et al., 2008; Rob-

biani et al., 2009). Consistent with the breadth of genes found

mutated by AID in germinal center B cells, AID overexpression

in transgenic mice leads to extensive translocation of non-Ig

genes and cancer (Robbiani et al., 2009). In addition, AID dereg-

ulation has been associated with H. pylori infection and gastric

cancer (Matsumoto et al., 2007), and with translocation in pros-

tate malignancy (Lin et al., 2009). Finally, AID is also of interest

because it has been implicated as a cytosine demethylase

involved in reprogramming pluripotent cells (Bhutani et al.,

2010; Morgan et al., 2004; Popp et al., 2010; Rai et al., 2008).

Although the precise mechanism which targets AID to Ig genes

is unknown, AID-induced mutations are associated with tran-

scription and are most prevalent in a 2 kb region beginning

downstream of the promoter (Di Noia and Neuberger, 2007;

Peled et al., 2008; Stavnezer et al., 2008; Storb et al., 2007).

Transcription is also required for CSR, suggesting that RNA

polymerase II (Pol II) might facilitate AID access to target DNA

(Di Noia and Neuberger, 2007; Peled et al., 2008; Stavnezer-

Nordgren and Sirlin, 1986; Stavnezer et al., 2008; Storb et al.,

2007; Yancopoulos et al., 1986). This idea was confirmed by

the observation that transcriptional regulatory elements are

essential to both hypermutation and CSR (reviewed in (Di Noia


and Neuberger, 2007; Peled et al., 2008; Stavnezer et al., 2008;

Storb et al., 2007)). Consistent with these findings, AID is associ-

ated with Pol II (Nambu et al., 2003). In E. coli and in in vitro

assays, transcription liberates ssDNA, the substrate for AID

(Bransteitter et al., 2003; Chaudhuri et al., 2003; Dickerson

et al., 2003; Pham et al., 2003; Ramiro et al., 2003; Sohail

et al., 2003). In more complex systems, transcription is also

required for AID to access chromatinized substrates (Shen

et al., 2009); however, the role of transcription in SHM and

CSR is not completely understood.

AID is a relatively small enzyme composed of 198 amino acids

(Muramatsu et al., 1999). It preferentially deaminates cytosine

residues embedded in WRCY consensus sequences (where

W = adenosine/thymine, R = purine, and Y = pyrimidine) (Rogozin

and Kolchanov, 1992). This preference is dictated in part by the

composition of the active site (Wang et al., 2010). However,

WRCY motifs are present throughout the genome and cannot

fully account for AID target choice. While several AID cofactors

have been reported, including replication protein A (RPA),

protein kinase-Ar1a, and CTNNBL1, none of these are known

to impart specificity to AID (Basu et al., 2005; Chaudhuri et al.,

2004; Conticello et al., 2008; McBride et al., 2006; Pasqualucci

et al., 2006).

Here we report that Spt5, a factor normally associated with

stalled or paused Pol II, is required for CSR. Spt5 is required

for AID recruitment to switch regions, for switch region mutation,

and for AID association with Pol II. Furthermore, genes that

accumulate Spt5 also accumulate AID and suffer AID-dependent

mutations.

RESULTS

shRNA Screen for CSR in CH12 CellsTo identify factors required for CSR, we developed a lentiviral-

based shRNA screening strategy using the murine B cell line,

CH12. This cell line expresses AID and undergoes CSR to IgA

in response to stimulation with interleukin 4 (IL-4), CD40 ligation

and transforming growth factor b (TGFb) (Nakamura et al., 1996).

AID is limiting for CSR in these cells because its knockdown by

specific shRNA results in reduction of CSR in a manner consis-

tent with the decrease in AID protein levels (Figures 1A and 1B).

In addition, shRNA-induced knockdown of other known regula-

tors of the reaction result in the expected decrease in CSR

(Figure 1C). Therefore, the level of CSR in CH12 cells is limited

by the amount of AID and its cofactors suggesting that CSR

can be used as an assay for additional factors that might be

required for AID function in these cells. To screen for such

factors, we developed an shRNA screen for CSR in CH12 cells.

We assembled an shRNA lentiviral library containing 8797

hairpins representing 1745 genes selected primarily on the basis

of their expression in CH12 cells (Table S1A available online) and

germinal center B cells (Klein et al., 2003; Moffat et al., 2006;

Root et al., 2006) (Table S1B). Factors directly involved in tran-

scription, or in cotranscriptional and posttranscriptional events,

such as mRNA processing, turnover and export, and DNA repair

factors, kinases and phosphatases were preferentially retained

(reviewed in (Di Noia and Neuberger, 2007; Peled et al., 2008;

Stavnezer et al., 2008; Storb et al., 2007)). Finally, we added

several DNA repair factors and transcription-associated factors

that were not selected based on their expression, but that might

be required based on the literature (Table S1B).

The recombinant lentiviruses were prepared and screened in

a 96-well format in triplicate (Moffat et al., 2006; Root et al.,

2006), and CSR and viability for each sample was evaluated by

flow cytometry (Figure 1D). Each plate contained three negative

control shRNAs (shLacZ, shGFP and shRFP) and a positive

control AID shRNA (Figure 1E, shAID). Positive hits were defined

as viable shRNA-expressing clones that exhibited at least 50%

reduction in CSR compared to the controls (Figures 1E). Positive

hits were rearrayed and rescreened in triplicate. The screen

uncovered 181 hits of which 28 were previously shown to be

involved directly or indirectly in CSR (Figure 1F and Table S2).

We tested the candidate hairpins for knockdown of the target

mRNA and their effects on AID mRNA, and m-and a�germline

transcripts (GLTs). We focused on those genes that did not alter

AID mRNA or m-and a�GLTs and assayed for association of the

corresponding protein with AID by coimmunoprecipitation.

Spt5 Is Required for CSR in CH12 and Primary B CellsSuppressor of Ty 5 homolog (Spt5), a transcription elongation

factor associated with paused Pol II, was selected for further

analysis (reviewed in Gilmour, 2009; Lis, 2007; Peterlin and Price,

2006). Two unique shRNAs targeting Spt5 decreased CSR

(Figure 2A), and the decrease was specific as determined by

complementation with an Spt5 cDNA lacking the sequence

targeted by shSpt5-1 (Spt5D), but not by a cDNA with intact

target sites (Figure S1). Spt5 knockdown also decreased switch

region hypermutation (Figure 2B), but did not alter the steady

state levels of AID, or m- or a�germline mRNA (Figure 2C), or

cell division as measured by CFSE dye dilution (Figure S2A).

Finally, CH12 cells expressing these shRNAs showed decreased

Spt5 protein, whereas AID protein levels were unaltered

(Figure 2D).

Similarly, primary B cells treated with LPS and IL-4 and in-

fected with retroviruses directing the synthesis of shRNAs

specific for Spt5 showed decreased Spt5 protein (Figure S2B)

and a concomitant decrease in CSR to IgG1 (Figure 2E). We

conclude that Spt5 is required for CSR in primary B cells.

Spt5 Associates with AID in Fibroblastsand Primary B CellsSince both Spt5 (Wada et al., 1998) and AID (Nambu et al., 2003)

associate with Pol II, we asked if Spt5 is also associated with

AID. Endogenous Spt5 was coprecipitated from 293T cells

transfected with Flag-tagged AID (F-AID) using anti-Flag anti-

bodies (Figure 3A). Conversely, F-AID was coprecipitated by

anti-Spt5 antibodies from the same cells under identical condi-

tions (Figure 3B). In contrast, APOBEC-2, a closely related

deaminase, did not coprecipitate with Spt5 in either direction

(Figures 3A and 3B). Finally, endogenous Spt5 was also coimmu-

noprecipitated with F-AID from activated B cells isolated from

F-AID knockin mice (AIDF/F mice) that express physiological

levels of AID, and undergo near-normal levels of CSR (Figure 3C

and Figure S3). DNA or RNA was not required for the Spt5-AID

interaction since the extracts were treated with Benzonase,

a nuclease that digests all nucleic acids. We conclude that


Spt5 is associated with AID in transfected fibroblasts and acti-

vated B cells.

AID and Spt5 Can Associate In VitroSince Spt5 can directly associate with Pol II in vitro (Yamaguchi

et al., 1999a), we asked if this was the case for the interaction

between Spt5 and AID. To test this idea, bacterially expressed

GST-AID was captured on glutathione sepharose beads and

incubated with purified recombinant Spt5. Only a fraction of

the Spt5 was specifically bound to GST-AID, but there was no

binding to GST-APOBEC2 or GST (Figure 3D). Thus, AID and

Spt5 can interact in vitro, but the association is weak and other

factors or posttranslational modifications likely facilitate this

association in vivo. Consistent with this idea, extracts prepared

in the presence of phosphatase inhibitors showed increased

AID-Spt5 association (Figure S4A). Although AID activity in vivo

is enhanced by phosphorylation of serine 38 (S38) or threonine

140 (T140) (Chaudhuri et al., 2004; McBride et al., 2006, 2008),

neither S38A nor T140A mutations alter the interaction of AID

with Spt5 (Figure S4B).

Pol II Association with AID Is Dependent on Spt5Spt5 binds to Pol II and induces stalling in vitro (Yamaguchi

et al., 1999a) and in vivo (Lis, 2007; Rahl et al., 2010). In addition,

Spt5 also functions as an adaptor that links several cotranscrip-

tional activities to the Pol II machinery (see Discussion). To

determine whether Spt5 is required for AID association with

Pol II, we depleted Spt5 from CH12 cells expressing F-AID

and examined the effects on the association between AID and

Pol II. Whereas both Pol II and Spt5 are normally coprecipitated

with F-AID, the association between AID and Pol II was

decreased in Spt5-depleted cells when compared to the

shLacZ control, suggesting that the AID-Pol II interaction

(Nambu et al., 2003) is dependent on Spt5 (Figure 3E). In

contrast, Pol II depletion did not alter the AID-Spt5 interaction

suggesting that Pol II is not essential for this association

Figure 1. Lentiviral-Based shRNA Screen

in CH12 Cells

(A) CSR is sensitive to AID depletion. Flow cytom-

etry plots of CH12 cells infected with five unique

shRNAs to AID (shAID1-5) and empty vector

control. Numbers indicate the percentage of IgA

positive cells.

(B) AID protein levels in whole cells extracts from

the same cells shown in (A). Western blots were

probed with an anti-AID antibody and anti-tubulin

as a loading control.

(C) Representative flow cytometry plots of CH12

cells infected with shRNAs against genes involved

in CSR: Nfkb1 (NFkB p50 subunit), Prkdc

(DNAPKcs catalytic subunit), Irf4, Runx3, and

Tgfbr1 (TFGb receptor 1) (Table S3).

(D) Schematic of the experimental approach used

for the screen.

(E) Representative data from a single plate of

shRNAs analyzed in triplicate. Error bars show

the standard deviation obtained from the three

replicate plates for %IgA+ cells (x axis) and cell

numbers (y axis). Negative (LacZ, GFP and RFP)

and positive (AID) controls shRNAs are indicated.

The dotted red line shows the position corre-

sponding to 50% of the averaged negative control

CSR value. Two sets of clones with < 50% CSR

are boxed. The upper box consists of viable clones

that are considered as positive hits. The lower box

contains clones that were discarded due to poor

viability.

(F) Pie chart showing the distribution of 181

selected hits as a function of the number of

shRNAs per gene and their effect on CSR as

calculated based on the percentage reduction of

CSR compared to the averaged negative control

values as shown in (E).

See also Table S1 and Table S2.


(Figure S4C). We conclude that Spt5 serves as an adaptor that

recruits AID to Pol II.

AID Recruitment to Ig Switch RegionsIs Dependent on Spt5To determine whether AID recruitment to the Ig switch region is

dependent on Spt5, we performed quantitative PCR-based ChIP

analysis with two different anti-AID antibodies (Chaudhuri et al.,

2004; McBride et al., 2006). Spt5 depletion resulted in significant

reduction of AID occupancy in the switch region (Figure 3F,

p = 1.4 3 10�6). We conclude that Spt5 is required for AID

recruitment to the Ig switch region in B cells undergoing CSR.

Spt5 Is Associated with Stalled Pol II in B CellsAID mutates Ig genes and up to 25% of the expressed genes in

germinal center B cells (Liu et al., 2008; Pasqualucci et al., 1998,

2001; Shen et al., 1998). To determine whether Spt5 localization

in the genome of activated B cells coincides with AID-dependent

mutation, we performed genome-wide chromatin immunopre-

cipitation and sequencing (ChIP-seq) with antibodies against

Spt5 and Pol II. Spt5 was found throughout the genome of

activated B cells undergoing CSR (Figure 4 and Table S3A). As

in other cell types that have been assayed for Spt5 localization,

this protein was also concentrated at promoter regions coinci-

dent with Pol II peaks in activated B cells (Gilmour, 2009; Lis,

2007; Peterlin and Price, 2006; Rahl et al., 2010) (Figures 4A–4C).

Spt5 is a stalling factor in vitro (Wada et al., 1998; Yamaguchi

et al., 1999b) and associated with stalled Pol II in various cell

types in vivo (Rahl et al., 2010; Zeitlinger et al., 2007). The amount

of Pol II stalling can be quantitated by calculating a stalling or trav-

eling index (Is), which is a ratio of the Pol II density at promoter

regions compared to the gene body (Zeitlinger et al., 2007; see

Experimental Procedures). Genes with Is > 3 are considered

stalled whereas those with Is < 1 are considered elongating genes

(Zeitlinger et al., 2007). Stalling is widespread in the B cell genome

(5594 genes, 61%, Table S3A), and in addition, the Pol II and Spt5

stalling indices were significantly correlated (Spearman’s corre-

lation coefficient, r = 0.8), consistent with previous observations

in other cell types (Nechaev et al., 2010; Rahl et al., 2010)

(Figure 4D, and A.Y. and R.C., unpublished data, accession

A B C

FSC

IgA48.4 16.7

21.9 12.2

shLacZ shSpt5-1

shSpt5-2 shAID

% Ig

A

0

20

30

40

10

50

D

shLacZ

shSpt5

-1

p = 0.02

0

1

2

3

4

5

Mu

tatio

n

freq

uen

cy (x10

-4

)Sμμ

shLacZ 26/73776

shSpt5-1 13/88418

p value 0.02

AID

Spt5

0

1

2

3

0.0

0.5

1.0

1.5

0.0

0.5

1.0

1.5

2.0

2.5

0.0

0.5

1.0

1.5

Igμ GLTs

Igα GLTs

1

1

0.94 0.38 0.32

0.2 0.96 0.9

E

14.1 10 23

2211.515.3

shSpt5-1 shSpt5-2 Vector

FSC

IgG1

% Ig

G1

shSpt5-1 shSpt5-2 Vector

p=0.002

p<0.0001

shLacZ

shAID

shSpt5

-1

shSpt5

-2

shLacZ

shAID

shSpt5

-1

shSpt5

-2

shLacZ

shAID

shSpt5

-1

shSpt5

-2

Spt5

AID

β-Actin

Spt5

AID

Figure 2. Spt5 Is Required for CSR and

Switch Region Mutation in CH12 Cells

(A) Upper panel shows representative flow cytom-

etry plots of CH12 infected with two unique

shRNAs to Spt5 (shSpt5-1 and shSpt5-2) and

controls (shLacZ and shAID) and stimulated to

undergo CSR. Numbers indicate percentage of

IgA positive cells. The graph in the lower panel

summarizes the data from four to six independent

experiments.

(B) Decreased switch region mutation after Spt5

knockdown in CH12 cells. Upper panel represents

the mutation frequency and corresponding p value

from control (shLacZ) and shSpt5-1 infected cells

stimulated to undergo CSR for 48 hr. The table in

the lower panel summarizes the mutation analysis

(represented as unique mutations/nucleotides

sequenced).

(C) Graphs show Q-PCR analysis for Spt5, AID, Iga

and Igm germline (GLT) mRNA levels in activated

CH12 cells infected as in (A) with the indicated

shRNAs. The data summarizes three independent

experiments with standard deviation indicated as

error bars. In all cases, shLacZ was assigned an

arbitrary value of 1.0.

(D) Western blot analysis of Spt5 and AID protein

levels in WCEs from activated CH12 cells infected

with the indicated shRNAs. Threefold serial dilu-

tions of WCEs were loaded. b-Actin was used as

a loading control. Numbers below the blots repre-

sent normalized band intensities for Spt5 and AID

with the shLacZ lanes assigned an arbitrary value

of 1.

(E) Spt5 is required for CSR in primary B cells.

Representative flow cytometry plots of B cells

stimulated with LPS + IL-4 and infected with retro-

viruses expressing shSpt5-1, shSpt5-2 or LMP

vector alone. Efficiency of switching was deter-

mined by gating on GFP-positive cells. Numbers

indicate percentage of IgG1 positive cells. The

graph in the lower panel summarizes the data

from three independent experiments.



number GSE24178). Most strikingly, AID occupancy in activated

B cells is also tightly correlated with Spt5 (see below and A.Y. and

R.C., unpublished data, accession number GSE24178).

To determine how Spt5accumulation relates to mRNAlevels, we

compared the density of Spt5 sequence reads to B cell mRNA-seq

levels (both measured as reads per kbp per million sequences

(RPKM) (Figure 4E, and (Kuchen et al., 2010)). Although there

was some correlation between Spt5 and mRNA levels (Figure 4E,

r= 0.55), there was a 1- to 2-log variation in mRNA levels for genes

accumulating similar levels of Spt5. Thus, in B cells, as in other

cells (Nechaev et al., 2010; Rahl et al., 2010), Spt5 (or Pol II)

accumulation is not necessarily equivalent to cellular mRNA levels.

Spt5 Genomic Occupancy Is Predictiveof AID-Dependent MutationUpon genome-wide analysis of Spt5 occupancy in the promoter

proximal region (�1–2 kb relative to the transcriptional start site

[TSS]), we found that Im bore the greatest tag count (Figure 5A

and Table S3B). The IgVH region could not be mapped because

each B cell has a unique rearrangement; however, a strong Spt5

signal was found from the IgH enhancer region through the

switch region (Figure 5A). Mir142, a robust AID target (Robbiani

et al., 2009), is also embedded in a region of high Spt5 accumu-

lation (Figure 5B and Table S3C). In contrast, Taci, Whsc1, H2Ea,

A20, Anxa4, and Wdfy3, all of which are expressed in activated B

cells (Kuchen et al., 2010), but are not mutated (Liu et al., 2008;

Robbiani et al., 2009), do not accumulate Spt5 (Figure 5C and

Tables S3A and S3B).

To determine whether Spt5 accumulation is predictive of

mutations, we sequenced 10 genes that ranked within the

top 5% of genes analyzed for Spt5 tag density (Spt5hi),

measured as the density of sequence tags or reads per million

base-pairs (TPM), in the promoter-proximal region (Table S3B,

Figure 5B and Figure 6, and Kuchen et al., 2010). As controls,

Input

shLa

cZ

Anti-Flag IPsh

Spt5

shLacZ shSpt5

Spt5

Pol II

E1 E2 E1 E2

IP

F-AID

Spt5

F-Apo2F-AID

Spt5

InputIP

anti-Blnk

pMX

IP anti-Spt5

A B C

E

Inpu

t

Elutions

GST

-AID

GST

-Apo

2

GST

GST

GST-Apo2GST-AID

Spt5

D

IgG anti-F

lag

Inpu

t

shLac

Z

shSpt5-

1

1.0

0.5

0

p = 1.4 x 10-6

Nor

mal

ized

A

ID C

hIP

F

F-AID

F-A

po2

F-A

ID

pMX

F-A

po2

F-A

ID

pMX

F-A

po2

F-A

ID

F-Apo2F-AID

Spt5

pMX

F-A

po2

F-A

IDpM

XF-

Apo

2F-

AID

InputIP

anti-Flag

Figure 3. Spt5 Interacts with AID in Fibroblasts and Primary B Cells

(A) Anti-Flag immunoprecipitates from whole cell extracts (WCEs) from 293T cells transfected with Flag-tagged AID (F-AID), or Flag-tagged Apobec2 (F-Apo2) or

pMX vector probed with anti-Flag or anti-Spt5 antibodies as indicated.

(B) Anti-Spt5 immunoprecipitates from WCEs from 293T cells transfected as in (A). Blots were probed as in (A). Anti-Blnk was used as an isotype control.

(C) Anti-Flag immunoprecipitates from WCEs from cultured splenic AIDF/F B cells. Blots were probed as in (A). E1 and E2 represent first and second elutions

with Flag peptide respectively.

(D) Bacterially expressed GST-AID, GST-APOBEC2 (GST-Apo2) or GST alone were bound to glutathione sepharose beads and incubated with purified recombi-

nant Spt5-Spt4 heterodimer (DSIF). Bound material was eluted and analyzed by SDS-PAGE and blotted using antibodies against Spt5 and GST. The input lane for

DSIF represents 1% of the amount used in the reaction.

(E) Anti-Flag immunoprecipitates from WCEs of CH12 cells transfected with F-AID and depleted of Spt5 by shSpt5-1. shLacZ is used as a control. Blots were

probed as in (A) and with anti-Pol II.

(F) ChIP analysis for AID occupancy in Sm regions of CH12 cells infected with shSpt5-1 or shLacZ control. Data represents a total of 7 experiments using two

different anti-AID antibodies (Chaudhuri et al., 2004; McBride et al., 2006). For each experiment, shLacZ was assigned an arbitrary value of 1. The p value is

indicated.



we sequenced 8 highly expressed genes (Kuchen et al., 2010)

that had a �4- to 6-fold lower Spt5 tag density (Spt5lo) in the

same region (Figure 5C and Figure 6 and Table S3B). For

each selected gene, a region starting around the TSS, corre-

sponding to the peak of Spt5, and extending �500–600 bp

downstream was sequenced (Figure 5, Figure 6, and Figure S5).

Because the rate of mutation at non-Ig genes is normally very

low unless repair is impaired (Liu et al., 2008; Pasqualucci

et al., 1998, 2001; Shen et al., 1998), we used B cells derived

from transgenic mice overexpressing AID from the Igk

promoter (IgkAID) (Robbiani et al., 2009). These mice display

elevated levels of AID protein with concomitant increases in

CSR and somatic mutation; nevertheless, they retain AID tar-

geting specificity (Robbiani et al., 2009). All 10 Spt5hi genes

(Table S3B) were mutated with frequencies from 4.6 3 10�4

for miR142 to 0.8 3 10�4 for H3f3b (Figure 6A and Fig-

ure S5). In contrast, none of the eight Spt5lo genes (Table S5)

were mutated above background levels (Figure 6A and

Figure S5).

To determine whether genes occupied by Spt5 correspond to

sites of AID recruitment, we compared Spt5 and AID ChIP-seq

data (Figure 6B and A.Y. and R.C., unpublished data, accession

number GSE24178). Strikingly, the tag density for AID per gene

(measured as reads per kilobase per million [RPKM]) was uniformly

and directly proportional to the tag density of Spt5 (r = 0.75,

Figure 6B and A.Y. and R.C., unpublished data, accession number

GSE24178). To determine if AID recruitment to non-Ig genes was

dependent on Spt5, we performed ChIP for AID localization at the

Gas5 gene, a stalled gene (Table S3A) which accumulates AID-

mediated mutation (Figure 6A). As shown in Figure 6C, AID recruit-

ment to Gas5 is impaired upon Spt5 depletion. We conclude that

Spt5 and AID accumulation coincide genome-wide and that high

density Spt5 occupancy is predictive of AID-mediated mutation.

DISCUSSION

Genetic and biochemical evidence indicate that AID initiates

SHM, CSR and chromosome translocation by deaminating

Figure 4. ChIP-Seq Analysis of Spt5 Genomic Occupancy

(A) Venn diagram showing overlap between genes recruiting Spt5 and Pol II using ChIP-Seq data from LPS+IL4 activated B cells (Table S4). There is a significant

association between the presence of Spt5 and Pol II at genes (Pearson’s Chi-square test; p < 0.0005).

(B) Correlation between Spt5 and Pol II density per gene. For each gene that recruited above-background amounts of Pol II and Spt5, the number of sequence

tags aligning between �1 Kb upstream of the transcriptional start site to its transcriptional termination site were normalized per gene length (in Kb), per million

aligned reads (reads per Kb per million, RPKM) and shown as a hexagonal binning plot. Spearman’s correlation coefficient (r) is indicated.

(C) Spt5 profile at all Spt5+ genes from �2 Kb to +5 Kb of the TSS. Data was normalized as reads per million per nucleotide. Dots represent densities at individual

nucleotides and the line a 10 nucleotide moving average.

(C) Correlation between the stalling index calculated based on Pol II or Spt5 occupancy (see Experimental Procedures). Spearman’s correlation coefficient (r) is

indicated.

(E) Comparative analysis of transcript levels (determined by mRNA-Seq, [Kuchen et al., 2010]) and Spt5 recruitment at all Spt5+ genes. Spearman’s correlation

coefficient (r) is indicated.

See also Table S3.


cytidine residues in ssDNA that are exposed during transcription

(Chaudhuri and Alt, 2004; Di Noia and Neuberger, 2007; Nus-

senzweig and Nussenzweig, 2010; Peled et al., 2008; Stavnezer

et al., 2008). AID initiated processes are therefore limited by

regulators of transcription initiation such as PTIP, which facili-

tates Pol II access to specific switch regions by regulating their

H3K4 methylation (Daniel et al., 2010). However, active tran-

scription is not sufficient to allow AID access to DNA, and cannot

explain why AID-mediated lesions are found primarily in the

promoter proximal region of only some transcribed genes. Since

Pol II stalling is a feature of promoter-proximal regions, the

observation that Spt5, a stalling factor, associates with AID

and is required for AID localization to target genes, provides

a molecular explanation for the pattern of mutation.

Inducible transcription of genes carrying paused Pol II is an

important mechanism for regulating gene expression (Gilmour,

2009; Lis, 2007; Peterlin and Price, 2006; Bai et al., 2010; Core

Figure 5. ChIP-seq Profiles of Spt5 on

Selected Genes

(A, B, and C) Pol II and Spt5 reads per million

plotted in 100 bp windows across (A) the Igm locus,

(B) Spt5hi, and (C) Spt5lo genes. The axes scales

are identical for all histograms. Tag mappability

(shown below) was calculated based on the

percentage of 36 nt sequences that uniquely

aligned to the genomic site with a 10 bp window

resolution. Only windows with a significant enrich-

ment compared to a random background model

are shown. The location of the TSS for each

gene is indicated. The histograms cover the length

of the gene. Whsc1 and Tnfaip3 were previously

sequenced (Robbiani et al., 2009). All profiles

were generated using the UCSC genome browser.

See also Table S3.

et al., 2008; Guenther et al., 2007; Lefeb-

vre et al., 2002; Muse et al., 2007; Zeitlin-

ger et al., 2007; Bentley and Groudine,

1986; Krumm et al., 1992;Raschke et al.,

1999;Kao et al., 1987). Pausing is typi-

cally found downstream of promoters

and is associated with permanganate

sensitivity, which is indicative of the pres-

ence of ssDNA (Giardina et al., 1992).

Spt5 Is Required for Pol II StallingIn Vitro and In VivoSpt5 was originally identified as an elon-

gation factor in a yeast suppressor

screen (Swanson et al., 1991). It was

subsequently purified biochemically as

a heterodimeric complex with Spt4

called 5,6-dichloro-1-b-d-ribofuranosyl-

benzimidazole (DRB) sensitivity inducing

factor (DSIF) (Wada et al., 1998; Yamagu-

chi et al., 1999b). DSIF, in association

with negative elongation factor (NELF),

binds to Pol II and induces pausing

in vitro (Wada et al., 1998; Yamaguchi et al., 1999a). Genome-

wide ChIP studies have established a strong correlation between

Spt5 and Pol II stalling in vivo (Rahl et al., 2010). These and

related studies showed that the presence of Pol II in promoter

regions does not necessarily correlate with transcription (Bai

et al., 2010; Gilmour, 2009; Lefebvre et al., 2002; Lis, 2007;

Nechaev et al., 2010; Peterlin and Price, 2006; Rahl et al.,

2010). Consistent with these studies, we find only a partial corre-

lation between Spt5 or Pol II occupancy and mRNA levels in

activated B cells (Figure 4E), and importantly, that shRNA knock-

down of Spt5 did not decrease AID mRNA, or Igm or Iga sterile

transcripts (Figures 2C and 2D).

Current models suggest that the stalled Pol II complex is reac-

tivated by inductive signals that recruit the P-TEFb kinase, which

phosphorylates Pol II and Spt5, thereby releasing NELF from the

complex and activating transcription (Kim and Sharp, 2001;

Marshall et al., 1996; Marshall and Price, 1995; Wada et al.,


1998; Yamada et al., 2006). Phosphorylated Spt5 remains asso-

ciated with Pol II throughout the elongation phase. Spt5 also

engages in interactions with various cotranscriptional factors

thereby serving as an adaptor linking these factors to the tran-

scriptional machinery. Spt5 links Pol II to splicing factors (Pei

and Shuman, 2002), capping enzyme (Wen and Shatkin, 1999),

the exosome complex (Andrulis et al., 2002), transcription

coupled repair factors (Ding et al., 2010), NFkB, and E-box

proteins (Amir-Zilberstein and Dikstein, 2008). Our data suggest

that Spt5 also facilitates the interaction of AID with Pol II

(Figure 3E) and thereby targets this enzyme to genomic loci accu-

mulating paused Pol II (Figure 3F, Figure 4D, Figure 6B, and A.Y.

and R.C., unpublished data, accession number GSE24178).

Stalled Pol II in the Ig LocusIn activated B cells, the Ig locus is unique in having a large

domain of densely packed Spt5 and Pol II molecules extending

several kilobases (Figure 5A and Tables S3A and S3B). The

idea that Pol II pausing might be linked to mutation (Peters and

Storb, 1996) was proposed based on the characteristics of Ig

hypermutation, and the position of hypermutation relative to

transcriptional start sites (reviewed in Di Noia and Neuberger,

2007; Peled et al., 2008; Stavnezer et al., 2008; Storb et al.,

2007). A mutator factor, MuF, was hypothesized to associate

with Pol II and generate mutations when Pol II is paused during

elongation (Peters and Storb, 1996). More recently, detailed

analyses of transcription and Pol II occupancy in the switch

regions have confirmed that transcription is indeed impeded

throughout the switch regions, most likely due to the presence

of G-rich repetitive sequence elements that facilitate DNA distor-

tion and formation of R loops (Daniels and Lieber, 1995; Rajago-

pal et al., 2009; Ronai et al., 2007; Tian and Alt, 2000; Wang et al.,

2009; Yu et al., 2003). Altogether, this makes the Ig locus an ideal

substrate for targeted mutation by AID because: (1) Spt5 facili-

tates association between AID and Pol II, (2) the stalled Pol II

molecules provide an abundance of ssDNA for AID, and (3) the

reduced rate of elongation provides AID with increased time of

residence at the target.

Finally, in addition to the switch region, several genes mutated

by AID were already known to have paused Pol II at sites corre-

sponding to regions that are somatically mutated including

c-myc (Bentley and Groudine, 1986; Krumm et al., 1992), Pim1

(Rohwer et al., 1996), and Igk (Raschke et al., 1999). Our exper-

iments provide a mechanistic explanation for the association

between Pol II stalling and AID-mediated somatic mutation. In

addition, they reveal the full spectrum of AID targets, including

genes such as Gas5, which also undergoes reciprocal transloca-

tion in B cell lymphomas (Nakamura et al., 2008).

Concluding RemarksAlthough our findings demonstrate a mechanism by which AID

gains access to the promoter proximal region of genes, several

questions remain about how antibody diversification is medi-

ated. In particular, AID recruitment is only the first of several

steps required to bring about CSR and SHM. Following its

recruitment to DNA, AID must gain access to target DNA.

Although Spt5 acts as an adaptor for AID, localizing it to paused

Pol II and associated ssDNA, this may not be sufficient. AID

mutates both DNA strands, and paused Pol II exposes only the

non-transcribed strand (Giardina et al., 1992; Gilmour, 2009;

Lis, 2007; Peterlin and Price, 2006). In addition, the association

between AID and paused Pol II does not explain why repair

differs between Ig and non-Ig genes, and between different

non-Ig AID targets (Liu et al., 2008). Hence, the mechanisms

governing post-AID recruitment events required for CSR and

SHM remain to be elucidated. AID and Spt5 can interact directly

Figure 6. Spt5 Occupancy Is Predictive of AID-Dependent Somatic Mutations

(A) Graphical representation of somatic mutation analysis for Spt5hi and Spt5lo genes from IgkAID and AID�/� splenic B cells (see Figures 5B and 5C). Mutations in

the AID�/� control is subtracted in each case (see Figure S5) and mutation frequencies indicated.

(B) Correlation between Spt5 and AID read density per gene. For each gene that recruited above-background amounts of AID and Spt5, the number of sequence

tags aligning between �1 Kb upstream of the transcriptional start site to its transcriptional termination site were normalized per gene length (in Kb), per million

aligned reads (reads per Kb per million, RPKM) and shown as a hexagonal binning plot. The Spearman’s correlation coefficient (r) is indicated.

(C) ChIP analysis for AID occupancy at the Gas5 gene in CH12 cells infected with shSpt5-1 or shLacZ control. Data represents a total of 4 experiments using two

different anti-AID antibodies. For each experiment, shLacZ was assigned an arbitrary value of 1. The p value is indicated.

See also Figure S5.


in vitro but the interaction is weak suggesting that additional

factors or posttranslational modifications may be required.

Nevertheless, our data suggests that Spt5 links Pol II and AID,

thereby providing a mechanistic explanation for the well-estab-

lished correlation between AID and transcription. The associa-

tion between Spt5 and AID also explains intrinsic features of

hypermutation and CSR, including the enrichment of mutation

in the promoter-proximal regions, which correspond to sites of

Pol II stalling (Nechaev et al., 2010; Rahl et al., 2010; Zeitlinger

et al., 2007).

In conclusion, we propose that AID utilizes the phenomenon of

Pol II stalling, which is widespread in the B cell genome, and is

particularly prominent on Ig loci, to gain access to its target

genes across the genome.


Library Preparation

The lentiviral shRNA library (Table S1B) was prepared, titered, arrayed and

validated as described (Moffat et al., 2006; Root et al., 2006; http://www.

broadinstitute.org/rnai/trc/lib).

Library Screening

The lentiviral library was screened in a 96-well plate format in triplicate, starting

from the infection stage through to flow cytometry analysis (schematically

represented in Figure 1C). Each plate contained negative control viruses

targeting LacZ, GFP and RFP and a positive control shRNA targeting AID. Cells

were infected, selected, and stimulated to undergo CSR followed by FACS

analysis (details in Supplemental Information).

shRNA Knockdown in Primary B Cells

The hairpin sequences for shSpt5-1 and shSpt5-2 (Table S1B) were cloned

into the LMP retroviral vector (Open Biosystems) and transfected into

BOSC23 cells to produce retrovirus (Robbiani et al., 2008). Primary B cells

stimulated with LPS and IL-4 were cultured as described (Robbiani et al.,

2008). After 24 hr in culture, B cells were infected with shRNA-expressing

retroviral supernatants as described (Robbiani et al., 2008) and cultured for

an additional 3 days with LPS and IL-4, followed by FACS analysis for IgG1

and Spt5 protein analysis by western blotting.

Immunoprecipitation

For Flag-IPs, 2 mg of WCE (prepared as described in Supplemental Informa-

tion) was incubated with 20 ml Flag Agarose resin (Sigma) for 2 hr at 4�C in

IP buffer (identical to WCE preparation buffers above adjusted to 150 mM

NaCl for fibroblasts assays, and 200 mM NaCl for B cells and CH12 assays).

This was followed by three washes in IP buffer and elution with 0.2 mg/ml

Flag peptide (Sigma) for 1 hr at 4�C. Eluates were subjected to SDS-PAGE

and western blot analysis. For anti-Spt5 IPs, 2 mgs of WCE were incubated

with 3 mg of anti-Spt5 (Santa Cruz Biotechnology) for 2 hr at 4�C followed by

capture of the immune complexes with 20 ml Protein A agarose (Roche) for

1 hr at 4�C. Beads were washed three times with IP buffer and bound material

was extracted by boiling in 100 ml of Laemmli sample buffer. Eluted material

was analyzed by SDS-PAGE and western blot. Antibodies used for probing

western blots were as follows: Flag (Sigma), Spt5 (H300) (SantaCruz Biotech-

nology), Pol II (4H8) (Abcam) and Phospho-Ser PKC Substrate (Cell Signaling).

AID-Spt5 Interaction In Vitro

GST fusion proteins were expressed in E. coli and immobilized on Glutathione

Sepharose 4 Fast Flow beads (GE Healthcare). Beads were incubated with

500 ng of purified DSIF (Spt5-Spt4) complex (a generous gift from Dr. Sohail

Malik, The Rockefeller University) in 200 ml final volume of binding buffer

(20 mM Tris [pH 7.5], 150 mM NaCl, 0.1% NP-40, 1 mM EDTA, Protease Inhib-

itor cocktail (Roche), 0.5 mM PMSF, 1 mM DTT, 0.5 mg/ml BSA) for 2 hr at 4�Cwith gentle rotation. After four washes with binding buffer, bound proteins were

eluted by boiling in NuPAGE LDS loading buffer (Invitrogen). Samples were

then subjected to SDS-PAGE followed by western blot analysis.

Chromatin Immunoprecipitation and Sequencing

ChIP-seq was performed exactly as described (Kuchen et al., 2010). In brief,

cells were fixed with 1% paraformaldehyde at 37�C for 10 min followed by

sonication. Chromatin fragments were then immunoprecipitated with anti-

bodies specific for Spt5 (Santa Cruz Biotechnology [H300] and BD Biosci-

ences [anti-DSIF]), RNA Pol II (Abcam, [4H8]) or Ser5-phosphorylated RNA

Pol II (Abcam, [phospho-S5]). Immunoprecipitates were processed following

Illumina’s protocol and sequenced on a Genome Analyzer. During analysis,

short sequence tags were trimmed to 32 nts and aligned to the mouse genome

(NCBI37/mm9) using Bowtie. Uniquely aligned reads were analyzed by SICER

(Zang et al., 2009) using an expectation value E of 0.05 in a random back-

ground model. The requirement for unique alignment was not applied for

IgSm or IgSg1 because of their high repetitive nature and low mappability

(Figure 5A). Reads on significant islands as defined by SICER were normalized

to the total number of reads on islands. Downstream analysis was carried out

in R and Python.

Quantitative AID ChIP

CH12 cells were infected with shRNAs to Spt5 as above and subjected to ChIP

analysis using two different anti-AID antibodies (Chaudhuri et al., 2004;

McBride et al., 2006). Assays were performed as described (Vuong et al.,

2009). The ChIP’d material was analyzed by Q-PCR and raw values were

normalized to the input signals for each sample (Vuong et al., 2009). Reactions

were performed in triplicate. Forward and reverse primers used for Sm ampli-

fication were 50 TAGTAAGCGAGGCTCTAAAAAGCAT 30 and 50 AGAACAGT

CCAGTGTAGGCAGTAGA 3‘ respectively. Forward and reverse primers

used for Gas5 amplification were 5‘ TATGGCTTCGGGCCTTGGA 3‘ and 5‘

CCTCCTAAAGTTTCCAGCTTGTGC 3‘ respectively.

Calculation of the Stalling Index

The stalling index was calculated based on Pol II ChIP-seq reads as described

(Rahl et al., 2010; Zeitlinger et al., 2007). Briefly, the Pol II and Spt5 stalling

indices are calculated in the same way and represent the ratio of read density

at the promoter to the average gene body density. The promoter was defined

as a 1 kb region extending from �0.5 kb to +0.5 kb relative to the TSS, and the

gene body was defined as the region from +1kb downstream of the TSS up to

the transcription termination site (TTS) (Rahl et al., 2010; Zeitlinger et al., 2007).

Additional experimental procedures can be found in the Supplemental

Information.

ACCESSION NUMBERS

The ChIP-seq data for Spt5, Pol II and AID are deposited in GEO under acces-

sion number GSE24178.


Supplemental Information includes Extended Experimental Procedures, five

figures, and four tables and can be found with this article online at doi:10.

1016/j.cell.2010.09.017.

ACKNOWLEDGMENTS

We thank members of the Nussenzweig lab for helpful discussions, Klara Ve-

linzon for FACS sorting, and Tom Eisenreich and David Bosque for animal

management. We thank Drs Jayanta Chaudhuri and Urszula Nowak for ChIP

protocols and anti-AID antibody, Dr. Sohail Malik for generously providing

purified recombinant DSIF and Dr. Alan Derr for assistance with informatics.

M.D.V. is a fellow of the American-Italian Cancer Foundation. R.P was a recip-

ient of The Irvington Institute Postdoctoral Fellowship of the Cancer Research

Institute. The work was supported by NIH grant (AI037526) to M.C.N. M.C.N. is

a Howard Hughes Medical Institute Investigator.


Received: May 22, 2010

Revised: August 2, 2010



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Intestinal Crypt Homeostasis Resultsfrom Neutral Competition betweenSymmetrically Dividing Lgr5 Stem CellsHugo J. Snippert,1 Laurens G. van der Flier,1 Toshiro Sato,1 Johan H. van Es,1 Maaike van den Born,1

Carla Kroon-Veenboer,1 Nick Barker,1 Allon M. Klein,2,3 Jacco van Rheenen,1 Benjamin D. Simons,3 and Hans Clevers1,*1Hubrecht Institute, KNAW and University Medical Center Utrecht, Uppsalalaan 8, 3584 CT Utrecht, The Netherlands2Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA3Department of Physics, Cavendish Laboratory, J.J. Thomson Avenue, Cambridge CB3 0HE, UK*Correspondence: [email protected]

DOI 10.1016/j.cell.2010.09.016

SUMMARY

Intestinal stem cells, characterized by high Lgr5expression, reside between Paneth cells at the smallintestinal crypt base and divide every day. We havecarried out fate mapping of individual stem cells bygenerating a multicolor Cre-reporter. As a population,Lgr5hi stem cells persist life-long, yet crypts drifttoward clonality within a period of 1–6 months. Wehave collected short- and long-term clonal tracingdata of individual Lgr5hi cells. These reveal thatmost Lgr5hi cell divisions occur symmetrically anddo not support a model in which two daughter cellsresulting from an Lgr5hi cell division adopt divergentfates (i.e., one Lgr5hi cell and one transit-amplifying[TA] cell per division). The cellular dynamics areconsistent with a model in which the resident stemcells double their numbers each day and stochasti-cally adopt stem or TA fates. Quantitative analysisshows that stem cell turnover follows a pattern ofneutral drift dynamics.

INTRODUCTION

Although invertebrate stem cells and their niches can be studied

with single-cell resolution, the size of mammalian tissues com-

bined with the infrequent occurrence of stem cells have compli-

cated the identification of individual stem cells in vivo (Morrison

and Spradling, 2008). The small intestinal epithelium presents

a unique opportunity to study mammalian adult stem cells. Not

only is it the fastest self-renewing tissue in mammals, it also

has a simple, highly stereotypical layout. It is essentially a two-

dimensional (2D) structure: a sheet of cells, bent in space to

form the crypts and villi. Cell compartments are easily identified

by location along the crypt-villus axis. And, importantly, all

cellular progeny remain associated with the stem cell compart-

ment of origin. Stem cells reside at the crypt base and feed

daughter cells into the TA compartment. TA cells undergo

approximately 4–5 rounds of rapid cell division (Marshman

et al., 2002). TA cells move out of the crypt and terminally differ-

entiate into enterocytes, goblet cells, and enteroendocrine cells.

These differentiated cells continue to move up the villus flanks

to die upon reaching the villus tip after 2–3 more days. A fourth

cell type, the Paneth cell, also derives from the stem cells but

migrates downwards and settles at the crypt base to live for

6–8 weeks (van der Flier and Clevers, 2009).

Recently we reported that small cycling cells located between

the Paneth cells, previously identified as crypt base columnar

cells (Cheng and Leblond, 1974a, b), specifically express the

Lgr5 gene (Barker et al., 2007). Using lineage tracing, we demon-

strated that these Lgr5hi cells generate all cell types of the small

intestinal epithelium throughout life. Similar data were obtained

using a CD133-based lineage tracing strategy (Zhu et al.,

2009). The Ascl2 transcription factor sets the fate of the Lgr5hi

cells (van der Flier et al., 2009). As further proof of stemness,

single Lgr5hi cells can generate ever-expanding epithelial orga-

noids with all hallmarks of in vivo epithelial tissue (Sato et al.,

2009). In the colon, stomach, and hair follicle, Lgr5hi cells have

also been identified as stem cells (Barker et al., 2007, Barker

et al., 2010; Jaks et al., 2008), whereas the Lgr6 gene marks

a population of primitive skin stem cells (Snippert et al., 2010).

Previously it was postulated that a cycling, yet DNA label-

retaining cell at position +4 represents a stem cell (Potten

et al., 1974). Multiple markers were published for this cell (He

et al., 2004, 2007; Potten et al., 2003). Using one of these

markers, Bmi1, long-term lineage tracing was observed with

kinetics that are surprisingly similar to that of Lgr5hi cells (San-

giorgi and Capecchi, 2008). As sorted Lgr5hi cells express the

highest levels of Bmi1 as assessed by qPCR analysis (Snippert

et al., 2009; van der Flier et al., 2009), Lgr5 and Bmi1 may

mark overlapping, if not identical, cell populations. Although a

rare, quiescent ‘‘reserve’’ Lgr5neg population may exist (Li and

Clevers, 2010), the Lgr5hi cells represent the workhorse of life-

long self-renewal of the healthy small intestine.

The most popular view on how stem cell populations accom-

plish homeostasis involves asymmetric cell division, which—at

the single stem cell level—results in two cells with unequal fates:

one new stem cell and one TA cell. This pattern of ‘‘invariant

asymmetry’’ in cell division can be controlled by cell-intrinsic

mechanisms best exemplified by the first division of the


C. elegans embryo (Cowan and Hyman, 2004) but also by

extrinsic niche signals as shown for Drosophila germ stem cells

(Fuller and Spradling, 2007). The asymmetric segregation of

molecules coupled with strictly oriented mitotic spindles can

herald an asymmetric fate outcome of the stem cell division, as

shown for the C. elegans embryo and the Drosophila neuroblast

(Neumuller and Knoblich, 2009). Only upon tissue expansion

or damage will stem cells divide symmetrically in this model.

We refer to mechanisms of stem cell maintenance that rely

upon invariant asymmetry of division as belonging to the class

of hierarchical models.

Another, less commonly considered model for homeostatic

stem cell maintenance states that the two cells that are gener-

ated from a stem cell division do not necessarily display intrinsi-

cally divergent fates. Such a stem cell division can lead to any of

three fate outcomes: two stem cells, one stem cell and one TA

cell, or two TA cells. In order to maintain stem cell number in

this model, homeostatic mechanisms have to act by necessity

at the stem cell population level, ensuring that—on average—

each stem cell division results in one stem cell and one TA cell.

Stem cell-supported tissues that exhibit this pattern of regulatory

control belong to the class of stochastic models. In contrast

Figure 1. Location and Number of Lgr5hi

Cells per Crypt

(A) E-cadherin knock-in strategy in which the fluo-

rescent protein monomer Cyan (mCFP) is fused to

the C terminus of Cdh1.

(B) Cellular localization of E-cadherin-mCFP

fusion protein (white) in crypts of small intestine.

(C) E-cadherin-mCFP mice crossed with Lgr5-

EGFP-Ires-CreERT2 mice. Left panel: whole-

mount intestine scanned from crypt bottom to

crypt-villus border (�125 mm); right panel: lateral

scan of semi-thick section (�50 mm). E-cadherin-

mCFP (white) allows 3D reconstruction of tissue

architecture, whereas Lgr5-GFP (green) visualizes

intestinal stem cells.

(D) FACS analysis of intestine of Lgr5-EGFP-Ires-

CreERT2 mice reveals three populations. GFPhi

represents Lgr5 intestinal stem cells.

(E) Whole-mount intestine from E-cadherin-mCFP

(white)/Lgr5-EGFP-Ires-CreERT2 (green) mice.

Lgr5-GFPhi population was visualized in red (false

color), whereas E-cadherin-mCFP (white) marks

cell borders. At the crypt base, all Lgr5+ cells

were GFPhi.

(F) Counting in 3D reconstructions yielded 14 ± 2

Lgr5hi cells per crypt in proximal small intestine.

Error bars represent standard deviation.

Scale bars: 50 mm. See also Figure S1.

to hierarchical models, the clonal fate of

individual stem cells in stochastic models

is unpredictable.

Unlike most other mammalian tissues,

the stem cells of the intestine are strictly

compartmentalized in crypts. Winton and

Ponder reported that the marking of indi-

vidual stem cells results in entirely clonal

crypts after 3 months and concluded that a single stem cell main-

tains each crypt (Winton and Ponder, 1990). Griffith et al. draw

comparable conclusions for colonic crypts (Griffiths et al.,

1988). In this view, crypt stem cell dynamics would represent

an extreme version of the hierarchical model. Potten and Loeffler

on the other hand proposed that crypts may harbor multiple stem

cells that are not strictly dividing asymmetrically (Potten and

Loeffler, 1990).

RESULTS

Lgr5hi Cells Occur as a Homogeneous PopulationLgr5hi stem cells in the small intestine divide approximately once

per day (Barker et al., 2007). Quyn and colleagues have demon-

strated that each Lgr5hi stem cell orients its mitotic spindle along

its apical-basal axis (Quyn et al., 2010). In order to visualize crypt

architecture at single-cell resolution, we generated an E-cad-

herin-mCFP fusion knock-in allele (Figures 1A and 1B and

Figure S1 available online) and crossed this into the Lgr5-

EGFP-Ires-CreERT2 KI mouse strain. E-cadherin-mCFP mice

were homozygous viable. The E-cadherin fusion protein allowed

visualization of 3D crypt architecture to depths of 125 mm


(Figure 1C), which revealed an almost perfect intermingling of

Lgr5hi cells and Paneth cells (Figure 1E).

Fluorescence-activated cell sorting (FACS) analysis demon-

strated the existence of three different Lgr5-expressing popula-

tions based on GFP level (Figure 1D), of which only the GFPhi cells

yield long-lived intestinal organoid structures in vitro (Sato et al.,

2009). We next counted Lgr5hi intestinal stem cells in duodenal

crypts of Lgr5-EGFP-Ires-CreERT2/E-cadherin-mCFP mice. In

the 3D reconstruction model (Figure 1E), essentially all non-Pan-

eth cells at the crypt base were Lgr5-GFPhi. Conversely, no Lgr5-

GFPhi cells were observed outside the crypt base. Crypts of the

duodenum were found to contain 14 ± 2 Lgr5hi cells (Figure 1F),

similar to the numbers of crypt base columnar cells as originally

reported (Cheng and Leblond, 1974b).

In our initial in vitro experiments, less than 5% of single sorted

Lgr5 intestinal stem cells could grow out into gut-like organoid

structures (Sato et al., 2009). Recently, we noted that sorted

heterotypic doublets (consisting of one Lgr5hi stem cell and

one Paneth cell) displayed 25% plating efficiency (H.C. and

T.S., unpublished data). After further optimization, we reached

a plating efficiency of approximately 60% when scored as expo-

nentially growing organoids after 7 days (Figure 2). In other

words, more than half of Lgr5hi cells could grow out into an intes-

tinal organoid when sorted together with a neighboring Paneth

cell. We interpreted this to imply that the majority of Lgr5hi cells

have stem cell properties, at least when associated with a Paneth

cell. Thus, we tentatively viewed each duodenal crypt to harbor

a homogeneous population of 14 Lgr5hi intestinal stem cells.

Multicolor Lineage Tracing of Individual Lgr5 Stem CellsTo address how homeostatic self-renewal is controlled, we

generated a Cre-reporter allele termed R26R-Confetti. We inte-

grated into the Rosa26 locus a construct consisting of the strong

CAGG promoter, a LoxP-flanked NeoR-cassette serving as tran-

scriptional roadblock, and the original Brainbow-2.1 cassette

(Livet et al., 2007) (Figure 3A). After Cre-mediated recombina-

tion, the roadblock was removed and one of the four fluorescent

marker proteins was stochastically placed under control of

the CAGG promoter, allowing discrimination between the clonal

progeny of neighboring stem cells within the same niche (Fig-

ure 3B). We validated fluorescent expression in multiple organs

using the b-naphtaflavone (bNF)-inducible Ah-Cre allele (Ireland

et al., 2004). Cre induction in small intestinal crypts occurs

at high efficiency, whereas less efficient induction of the Cre

transgene occurs in a variety of other organs. The R26R-Confetti

allele behaved as a stochastic multicolor Cre-reporter gener-

ating nuclear green, cytoplasmic yellow, cytoplasmic red, or

membrane-bound blue cells (Figure 3C). Whereas the other

three colors consistently appeared in near-equal ratios, nuclear

GFP cells occurred at varying frequencies, yet always lower

than the expected 25%.

Short-Term Clonal Tracing Analysis of IndividuallyLabeled Lgr5hi CellsCrypts drift toward clonality over time (Griffiths et al., 1988;

Winton and Ponder, 1990), yet the kinetics of this process have

not been documented at the single stem cell level. In the first

of two tracing strategies addressing this issue, we analyzed

the behavior of clones developing from single Lgr5hi cells,

stochastically initiated using the Lgr5-EGFP-Ires-CreERT2 allele

in conjunction with the R26R-Confetti reporter. Analysis of stem

cell clones was performed at various time points after Cre-

activation by tamoxifen in 10-week-old mice, after which the

progeny of these Lgr5hi cells were mapped in 3D-reconstructed

crypts. Labeling occurred at a frequency of approximately one

event per six crypts. All analyses were performed on crypts in

the proximal segment of the duodenum.

Clone size was determined as the number of cells marked by

a single fluorescent protein upon recombination of the R26R-

Confetti allele. Cytoplasmic GFP intensity derived from the

Lgr5 knock-in allele allowed the identification of Lgr5hi cells

within a clone. Invariably, the identification of Lgr5hi cells by cyto-

plasmic GFP was confirmed by their location between Paneth

cells. The first Confetti-marked stem cells were observed 24 hr

after Cre induction (Figure 4A). Most clones consisted of a sin-

gle cell, of which 90% (34/38) could be identified as an Lgr5hi

cell located between Paneth cells (Figure 4B). Around 10%

(5/43) of the marked stem cells had already undergone mitosis

(Figure 4B).

After 2 days, most cells had divided at least once (Figures 4C

and 4D). We scored 101 two-cell clones for the presence of

Lgr5 hi cells. Of these, 54 clones contained two Lgr5 hi cells, 10

contained a single Lgr5hi cell, and 37 contained no Lgr5hi cells

(Figure 4D). Alongside the 101 two-cell clones, there were a

further 37 larger clones with mixed Lgr5 expression, including

one seven-cell clone containing no Lgr5hi cells, and others with

four cells all of which were Lgr5hi. Apart from an overall expan-

sion of clone size, this general pattern of behavior (broad size

distribution and divergent fates) was maintained at day 3 with

the largest clone having as many as 10 cells (Figures 4E and 4F).

Figure 2. Lgr5hi Cells Constitute an Equipotent Stem Cell Population

(A) Confocal section at the crypt base with Lgr5 cells (green) and Paneth cells,

with large granules, stained for lysozyme (red). All cells at crypt bottoms are

either Lgr5hi cells or Paneth cells.

(B) Plating efficiency of Lgr5hi/Lgr5hi versus Lgr5hi/Paneth doublets as scored

after a 7 day culture shows outgrowth of �60% of Lgr5hi cells when paired with

a Paneth cell. Insets: confirmation of sorting strategy by confocal microscopy;

Lgr5hi in green and Paneth cell in red. Error bars represent standard deviation.

Scale bars: 50 mm.


These results were indicative of the intestinal stem cells following

seemingly divergent fates.

At later time points (day 7 and day 14), the rapid expansion and

transfer of cells through the TA cell compartment to the villus

made it challenging to reliably score their number. Therefore,

we scored the number of Lgr5hi cells in each clone at days

1, 2, 3, 7, and 14, while disregarding all other cell types within

the clone. Thus, a ten-cell clone comprised of four Lgr5hi cells

and six Lgr5lo cells translates to a clone of size 4, while a ten-

cell clone in which all cells are Lgr5lo was considered ‘‘extinct.’’

With this definition, the size distribution of surviving clones is

shown over the 14 day chase period (Figure 4G). The data reveal

a steady increase in the average clone size that compensates

for the ongoing extinction of clones. Indeed, by day 14, the

largest clone contained as many as 12 Lgr5hi cells, a figure

approaching the 14 Lgr5hi cell average found in duodenal crypts.

It was apparent that, even in the largest surviving clones, the

labeled Lgr5hi cells were largely grouped together suggesting

that, despite their rapid turnover, mixing of cells at the crypt

base was limited (Figure S2, Movie S1, and Movie S2). Further-

more, the morphology of these clones in the Lgr5hi compartment

Figure 3. R26R-Confetti; a Stochastic

Multicolor Cre-Reporter

(A) R26R-Confetti knock-in strategy. Brainbow2.1

encoding four fluorescent proteins (Livet et al.,

2007) was inserted into the Rosa26 locus.

Upstream, the strong CAGG promoter, a LoxP

site, and a neomycin resistance roadblock cas-

sette were inserted.

(B) Upon cre activation, the neomycin roadblock

is excised, while the brainbow2.1 recombines in

a random fashion to four possible outcomes.

GFP is nuclear, CFP is membrane associated,

and the other two are cytoplasmic.

(C) The R26R-Confetti knock-in line is a stochastic

multicolor Cre-reporter in multiple tissues. Scale

bars: 50 mm, except for pancreas, kidney, and

liver: 100 mm.

was consistent with a lateral expansion

around the circumference of the crypt

base, whereas few, if any, cell divisions

lead to clonal expansion through the

base to the opposite side of the crypt.

Long-Term Lineage TracingIn the second strategy, we aimed to mark

all stem cells in crypts to document the

drift toward clonality. The Lgr5 gene is

expressed at low levels and, as a con-

sequence, the Lgr5-EGFP-Ires-CreERT2

allele does not generate quantitative

Cre activation upon a single tamoxifen

induction. We therefore used the R26R-

Confetti allele in conjunction with the

Ah-Cre allele. The Ah-Cre transgene

recombines LoxP sites efficiently in most

cell types including the stem cells yet is

inactive in the long-lived Paneth cells (Ireland et al., 2004). Never-

theless, within the Paneth cell compartment, old unmarked

Paneth cells are replaced by marked precursor cells over time

(Ireland et al., 2005). Clonal analysis was performed at various

time points after Cre activation in 10-week-old Ah-Cre/R26R-

Confetti mice, using ‘‘side-view’’ and ‘‘bottom-view’’ imaging

of whole-mount intestine (‘‘xy plane’’ and ‘‘xz plane,’’ respec-

tively; Figure 5A). Thus, the composition of many crypts could

be captured in a single confocal image taken just above the crypt

base, and for each crypt displayed as the biological equivalent

of a ‘‘pie-chart.’’ Analysis of the crypts in the time course

provided visual snapshots of individual labeled domains of cells

within crypts (Figure 5B). Using these ‘‘bottom-view’’ images, we

were able to extract quantitative data from week 1 to week 30,

documenting the drift toward clonality (Figure 5B).

Although only a small fraction of cells acquired the nuclear

GFP label, 80% of the remaining cells were induced in approxi-

mately equal proportions, yellow:blue:red. At the earliest time

point taken at 4 days post-labeling, the confocal section at the

crypt base showed a striking, heterogeneous pattern of labeling

(Figure 5B). At day 7, there was a significant expansion and


coarsening of the labeled domains reflecting stem cell loss and

lateral expansion of neighboring clones (Figure 5B). At later

time points, we observed a continuing expansion of the aver-

age domain size alongside an ever-diminishing number of

domains until crypts became fully labeled with one color (mono-

chromatic) or fully unlabeled (Figure 5B). The first monochro-

matic crypts appeared as early as 2 weeks post-induction,

whereas around 75% had become fully labeled at 2 months

(Figure 5B). Although the drift toward monoclonality continued,

we noted the presence—albeit rare—of oligo-clonal crypts even

at 18 and 30 weeks post-labeling (Figure 5B, circles).

To describe quantitatively the drift toward clonality, we con-

verted the sections from the crypt base into a labeled domain-

size distribution (Figure 6A). Specifically, we divided the circum-

ference into 16 equal parts (‘‘sextadecals’’), reflecting the typical

number of TA cells in a section near, but above, the crypt base

(Potten and Loeffler, 1990). This assignment related proportion-

ately to the stem cell content of a clone. For example, if we

found a labeled domain of size 4 sextadecals—i.e., covering

one quarter of the crypt circumference—this translated to one

quarter of the crypt base stem cells being labeled in that color.

In this way, we could determine the labeled domain size distribu-

tion (Figure 6B) as well as the frequency of monochromatic

crypts (Figure 6C) over the 30 week chase period.

On day 7, the domain size distribution was tilted toward

smaller clone sizes with a peak around 3 to 4 sextadecals, i.e.,

clones covering 3/16 to 4/16 of the circumference (Figure 6B).

At 2 weeks, the weight of the distribution was gradually shifting

toward larger clone sizes (Figure 6B), with a small fraction of

crypts (ca. 5%) already fully labeled (Figure 6C). At 4 weeks,

the average domain covered around 8 sextadecals, the half-filled

crypt, in partially labeled crypts (Figure 6B), whereas about 45%

had become monochromatic (Figure 6C). This trend continued

out to the latest time point at 30 weeks when almost all crypts

were monochromatic. This behavior was consistent with compe-

tition between neighboring stem cells leading to ever fewer yet

larger clones and a steady progression toward monoclonality.

This phenomenon was age independent, as we observed the

same drift toward clonality, when lineage tracing was initiated

in 40-week-old mice (Figure S3).

Taken together, the short- and long-term clonal fate data rule

out a model in which all Lgr5hi cells are stem cells that segregate

cell fate asymmetrically (Figures 4B, 4D, and 4F). Such a model

would not be compatible with the previous observation—

confirmed here—that crypts drift toward clonality (Griffiths

et al., 1988; Winton et al., 1988). However, these early observa-

tions leave open the question of the functional homogeneity (i.e.,

equipotency) of the Lgr5hi population. Indeed, the divergence of

Figure 4. Short-Term Clonal Tracing Analysis of

Individually Labeled Lgr5hi Cells

(A) R26R-Confetti mice were crossed with Lgr5-EGFP-

Ires-CreERT2 mice. Tracing was sporadically induced in

single Lgr5hi cells (�1 Confetti color in 6 crypts). Cytosolic

GFP marks the Lgr5hi stem cell population. Panels from left

to right: (1) single plane-2D image of crypt with one YFP

(white, false color) labeled Lgr5hi cell. Background is DIC

image; (2) 3D reconstruction of the same crypt showing

Lgr5hi cells (green) and the traced cell (white); (3) same,

but GFP only; (4) same but YFP only. Arrowheads point

to Lgr5hi cells within a clone, arrows point to TA cells within

clone that lost Lgr5hi activity.

(B) For 43 labeled clones, the total number of cells and

numbers of Lgr5hi cells were scored. The matrix indicates

the absolute number of clones scored for each given clone

size and given number of Lgr5hi cells. Red hues represent

relative frequencies of all scored events for given time

point. 100% is red; 0% is white.

(C) As in (A), but after 48 hr of tracing. In this crypt, RFP

(red) revealed a tracing event. The red clone expanded

to three Lgr5hi cells. By contrast, CFP (blue) revealed

another tracing event in the same crypt, but where the

clone lost Lgr5 expression.

(D) As in (B), but after 48 hr of tracing.

(E) As in (A), but after 72 hr of tracing. One Lgr5hi cell was

labeled with YFP (white) and grown to a clone size of 6, of

which two cells remained Lgr5hi.

(F) As in (B), but after 72hr of tracing.

(G) Expansion of Lgr5hi cell numbers over time within

clones with at least one Lgr5hi cell. The average size of

these ‘‘surviving’’ clones gradually increases, yet the vari-

ability between individual clone sizes increases over time

as well. Red hues represent relative frequency of Lgr5hi

cell numbers per time point. 100% is red; 0% is white.

Scale bars: 25 mm. See also Figure S2, Movie S1, and

Movie S2.


clone fate seen in short-term lineage tracing and the progression

to monoclonality at longer times could be both accommodated

within two very different frameworks. In the hierarchical model

(1), the Lgr5hi cell compartment may be functionally heteroge-

neous with progenitor cells of limited proliferative potential sup-

ported by a single ‘‘dominant’’ stem cell following a strict pattern

of invariant asymmetry such as proposed previously. Alterna-

tively, in the stochastic model (2), tissue is maintained by an equi-

potent Lgr5hi stem cell population following a pattern of popula-

tion asymmetry in which stem cell loss is compensated by

symmetric self-renewal of a neighboring stem cell.

At present, no marker or unique location has been identified

that would distinguish a ‘‘dominant’’ Lgr5hi stem cell in the hier-

archical model from its Lgr5hi progeny. Although, the validity of

the model can thus not be addressed directly, several indirect

conclusions can be drawn. First, for the model to be valid, the

dominant stem cell has to be Lgr5hi, given that Lgr5-based

tracing eventually leads to the marking of entire crypts. Second,

the dominant stem cell has to divide in a strictly asymmetric

fashion as a crypt can only harbor a single such cell. Third,

because the kinetics of drift toward clonality differs from crypt

to crypt, the dominant Lgr5hi stem cell should yield Lgr5hi

progenitors, which can occur as relatively long-lived Lgr5hi

cells (which persist for many months) but should also occur

as short-lived Lgr5hi cells that disappear within days. Both

long- and short-lived Lgr5hi progenitors should still be multipo-

tent, again based on our previous tracing data (Barker et al.,

2007).

In the stochastic model the situation is much less complicated.

Only one type of Lgr5hi cell exists, 14 per crypt, all endowed

with the potential for long-term stemness. Cell fate is determined

after division of the Lgr5hi stem cell, potentially by competition

for available niche space at the crypt base. Thus, homeostasis

is obtained by neutral competition between equal stem cells

and occurs at the population level. To evaluate the possibility

that the stochastic model indeed underlies the homeostatic

self-renewal in crypts, we subjected our quantitative short- and

long-term tracing data to a theoretical analysis.

Mathematical Analysis of Short-Term Clonal EvolutionShows that Stem Cells Follow Neutral Drift DynamicsIn general, the ability to maintain tissue in long-term homeostasis

places significant constraints on the properties of a stem cell

population. In particular, it leaves open two patterns of stem

cell fate: invariant asymmetry in which every stem cell division

results in asymmetric fate (as exemplified by the hierarchi-

cal model), and population asymmetry in which the balance

between self-renewal and differentiation is achieved on a popula-

tion basis (as exemplified by the stochastic model) (Watt and

Hogan, 2000). For the latter, because the size of the intestinal

stem cell compartment remains roughly constant over time, it

follows that balance of stem cell fate in crypts must follow from

external regulation: the tissue responds to the loss of a nearby

stem cell by symmetric cell division or vice versa. As a result,

stem cells follow a stochastic pattern of behavior known as

‘‘neutral drift dynamics.’’ If, by chance, the last stem cell in a

clone is lost, that particular clone becomes extinct. As a conse-

quence, crypts inevitably drift toward clonality in the stochastic

model. Evidence for population asymmetry and neutral drift

dynamics has been reported recently for stem cells in mamma-

lian testis (Klein et al., 2010). Two of us (A.M.K. and B.D.S.) have

provided the theoretical underpinning for a study comparable to

that of Klein et al. on intestinal crypt-villus dynamics (Lopez-

Garcia et al., 2010). Both of these studies relied upon long-

term lineage tracing from which the ‘‘trails’’ of differentiating

spermatocytes, and the migration streams of intestinal cells on

the villi, were used to infer indirectly the dynamics of the under-

lying stem cell compartments.

With access to clonal fate data at single stem cell resolution,

the present study allowed for a critical, direct analysis of the

dynamics of the intestinal stem cell population. From the two

Figure 5. Long-Term Lineage Tracing

(A) R26R-Confetti mice were crossed with Ah-Cre. xy plane images are shown

at 1 week and 8 weeks after cre induction. Left panels are overview images.

Right panels zoom in on crypts. Over time, labeled cell domains expand

whereas neighboring domains become extinct. Note that Paneth cells are

long-lived and can reveal the ‘‘clonal history’’ of a crypt when derived from

a clone that is extinct at the time of analysis. Inset: schematic representation

of small intestine, indicating the two sectioning planes used for the analysis.

(B) xz-plane images of small intestine after R26R-Confetti activation reveal drift

toward clonality over time. Nonclonal crypts are marked with a white-dashed

circle.

Scale bars: 100 mm. See also Figure S3.


studies mentioned above, several generic and robust features

of neutral drift dynamics have emerged. First, after an initial

transient evolution, the clone size distribution was predicted to

acquire ‘‘scaling’’ behavior: Formally, denoting as Pn (t) the

fraction of surviving clones which host n (>1) Lgr5hi cells

at a time t post-induction, we can define a cumulative size distri-

bution, CnðtÞ= 1 �Pnm=1PmðtÞ, i.e., Cn(t) simply records the

chance of finding a clone with more than n stem cells after

a time t. For the latter, ‘‘scaling’’ implies that the cumulative

size distribution takes the form (Supplemental Information—

Theory),

CnðtÞ=Fðn=hnðtÞiÞ; (1)

where hn(t) i denotes the average number of stem cells in

a surviving clone, and F is the ‘‘scaling function.’’ From (1), it

follows that, when Cn (t) is plotted against n=hnðtÞi, the entire

family of size distributions at different times, t, collapses onto

a single curve. The scaling function, F, is ‘‘universal,’’ indepen-

dent of stem cell number and rate of loss or division, etc., and

dependent only on the coordination of stem cells in tissue (see

below). In crypts, because clone size cannot grow indefinitely,

scaling behavior will be lost when crypts become monoclonal

(Supplemental Information—Theory).

By contrast, if homeostasis relies upon a stem cell hierarchy,

clones derived from the dominant stem cell would increase

steadily in size, whereas those derived from shorter-lived Lgr5hi

cells would exhibit limited growth followed by loss. Significantly,

the mixture of these two behaviors cannot lead to scaling (Klein

et al., 2010). The growth, hn(t) i, and form of F, offer further insight

into the pattern of stem cell fate. If stem cells are organized into

a one-dimensional arrangement, with cell replacement effected

by neighboring stem cells, then the average size of surviving

clones is predicted to acquire a square root time dependence,

hnðtÞiz ffiffiffiffiffiffiffiplt

p, with l as the stem cell replacement rate, and the

scaling function taking the form (Supplemental Information—

Theory; Bramson and Griffeath, 1980),

FðxÞ= exp��px2=4

�: (2)

Referring to Figures 7A and 7B, we indeed found that the

cumulative clone size distribution from the short-term clonal

assay showed a rapid convergence onto scaling behavior,

whereas the average clone size followed a square root growth

over the same period. Such scaling behavior is consistent

with equipotency of all Lgr5hi cells, thereby arguing against

the hierarchical model. Furthermore, the coincidence of the

data with the universal (parameter-free) scaling function (2)

further established that intestinal stem cells follow a pattern of

neutral drift dynamics in which stem cell multiplication is

compensated by the loss of neighboring stem cells. This leads

to a lateral clonal expansion around the one-dimensional circum-

ference defined by the crypt base (Figure 6A) and consistent with

the images obtained from whole mounts (Figure 5B). A fit of the

predicted average clone size hnðtÞi (Figure 7A, solid line, Supple-

mental Information—Theory) to the experimental data over the

14 day chase period (Figure 7A, points) revealed a stem cell

replacement rate of 0.74 ± 0.04/day, a figure comparable with

the cell division rate of the stem cells. As a result of this coinci-

dence, we can conclude that, if asymmetric stem cell divisions

take place at all, they make a minimal contribution to tissue

homeostasis.

From the inferred rate of stem cell loss, we can use neutral

drift dynamics to predict the long-term evolution of the average

clone size and survival probability (Figures 7C and 7D). With

this result in hand, a further comparison of the clone size distri-

bution with a more detailed analysis that includes the approach

to scaling (Supplemental Information—Theory) revealed an

Figure 6. Progression toward Monoclonality

(A) Schematic representation of the translation

from actual data to quantitation of labeled domain

sizes. Left panel shows the crypt base with Lgr5hi

cells in false color red, Lgr5 expression in green,

and E-cadherin-mCFP in white. Second panel is

a schematic representation of the crypt base, in

which three hypothetical labeled cell domains

were visualized in red, yellow, and blue. The red

domain shows seven labeled cells and encom-

passes 7/16 of the crypt base circumference.

Two mitoses are shown; the first leads to the

displacement and loss of the blue single-cell clone,

and the second leads to the displacement of an

unlabeled cell and the expansion of the yellow

clone. The third panel illustrates the segregation

of the crypt base into 16 equally spaced segments

(sextadecals) corresponding approximately to the

cellular composition of the crypt base stem cells.

The process of Lgr5hi cell displacement following

the symmetric duplication of a neighboring Lgr5hi

cell is shown for two clones, with the outcome

shown in the final panel.

(B) The matrix indicates the absolute number of

clones scored for each given domain size at each time point post-induction. Red hues represent relative frequencies of all scored domain sizes per time point.

100% is red; 0% is white.

(C) Frequencies of monochromatic crypts after given time points post-induction.


excellent agreement of theory (Figure 7B, lines) with experiment

at intermediate times (Figure 7B, points).

Long-Term Clonal Evolution, Coarsening,and the Progression to MonoclonalityThe long-term lineage tracing data provided a vivid demonstra-

tion of the ‘‘coarsening’’ phenomenon (i.e., the drift toward

ever fewer, yet larger clones) predicted by neutral drift dynamics.

It also presented an opportunity to study quantitatively the pro-

gression to monoclonality. The size distribution of contiguous

labeled patches of stem cells generated in the R26R-Confetti

system provided a signature of neutral drift dynamics, which

can be compared to theory—a straightforward generalization

of the clonal dynamics considered in the previous section to

a multicolor mosaic system. Although the clone dynamics relates

to an, as yet, unsolved problem in nonequilibrium statistical

physics—the theory of a ‘‘coalescing random walk’’ (Ben-Naim

et al., 1996; Krapivsky and Ben-Naim, 1997; Wu, 1982)—the

evolution could be generated straightforwardly by computer

simulation, and the results compared with experiment (Figure S4

and Supplemental Information—Theory).

To extract quantitative insights from the experimental data, we

required one further parameter, the number of stem cells in the

crypt. Duodenal crypts harbor 14 ± 2 Lgr5hi cells per crypt. In

the following, we have assumed a figure of 16 stem cells per

crypt to match the average number of TA cells in a crypt section

near the base. However, within a relatively narrow range of

14–18, a variable stem cell number would not significantly influ-

ence the quality of the fits discussed below. Taking the same

stem cell loss rate from the short-term clonal analysis, Figure 7E

shows a favorable agreement of neutral drift dynamics (solid line)

with the measured average clone size (points) as well as the

Figure 7. Lgr5hi Cells Follow Neutral Drift

Dynamics

(A) A fit of the average number of Lgr5hi cells within

surviving clones as predicted by the stochastic model of

neutral drift dynamics (solid line, Supplemental Informa-

tion—Theory) to the experimental data (points, see

Figure 4G) leads to a stem cell loss rate of 0.74 ± 0.4/

day. The dashed curve shows a simple square root time

dependence, which provides an increasing good approxi-

mation to the exact result. Error bars denote the standard

error of the proportion.

(B) Cumulative clone size distribution, Cn(t), i.e., the chance

of finding a surviving clone with more than n stem cells, as

measured by the Lgr5hi content within surviving clones.

The lines show the size distribution as predicted by neutral

drift dynamics with the stem cell loss rate fixed by the fit in

(A) (Supplemental Information—Theory) while the points

show experimental data from days 1, 2, 3, 7, and 14

(Figure 4G). Inset: at these early times, theory predicts

that, if stem cell self-renewal follows from population

asymmetry (the stochastic model), the cumulative clone

size distribution, Cn(t), should collapse onto a universal

scaling curve when plotted as a function of n/ < n(t) > ,

where < n(t) > denotes the average size of the surviving

clones. Such behavior is recapitulated by the experimental

data, with the dashed curve representing the universal

scaling function (2). Error bars denote the standard error

of the proportion.

(C) The growth curve over time of Lgr5hi stem cell number

within surviving clones as predicted by neutral drift

dynamics with the stem cell loss rate of 0.74/day (obtained

from Figure 7A) and 16 stem cells per crypt.

(D) The corresponding frequency of monoclonal crypts

over time as a percentage of surviving clones as predicted

by neutral drift dynamics.

(E) Average size of labeled cell domains following long-

term fate mapping of intestinal stem cells. Once again,

with 16 stem cells per crypt, and an average stem cell loss

rate of 0.74/day, the line shows the prediction following

neutral drift dynamics (Supplemental Information—

Theory) while the points are obtained from experiment

at 4, 7, 14, 28, 61, 126, and 210 days post-induction

(Figures 6B and 6C). The corresponding frequency of monochromatic crypts (in which all progenitor cells are labeled with the same color) is shown in the inset.

Error bars denote the standard error of the proportion.

(F) Variability in clone size for partially labeled crypts at 4, 7, 14, and 28 days post-induction. The predictions made by neutral drift dynamics (lines, Supplemental

Information—Theory) match closely with the experimental data (points, Figure 6B). Error bars denote the standard error of the proportion.

See also Figure S4.


monochromatic crypt fraction (Figure 7E, inset). In particular,

the figure shows that, by 2 months, approximately 75% of the

crypts became monoclonal (Figure 7A, inset).

As with the short-term clonal assay, the average size depen-

dence represented just one facet of a rich data set associated

with the full clone size distribution. With the same two parame-

ters in hand, the stem cell loss rate and stem cell number, an

analysis of the size distribution showed an equally favorable

agreement (solid lines) with the experimental data (points) at 4,

7, 14, and 28 days post-labeling (Figure 7F). At longer times,

the data were fully consistent with theory, but the numbers

of nonclonal crypts had become too low to reach statistical

significance.

DISCUSSION

We have studied how homeostasis of intestinal stem cell

compartments is accomplished by following the fates of clonally

labeled Lgr5hi cells. Although we cannot rigorously rule out

the hierarchical model (as long as the model allows unlimited

complexity in the cellular composition of individual crypts), our

data favor the stochastic model based on the following argu-

ments: The stochastic model is the simplest model, as it postu-

lates the existence of only a single type of Lgr5hi cell. The model

endows every Lgr5hi cell with potential stemness, which agrees

with our observations that the majority of Lgr5hi cells can estab-

lish long-lived intestinal organoids. By contrast, the hierarchical

model would endow only 1 of 14 Lgr5hi cells with stemness.

And importantly, the stochastic model is in excellent agreement

with both the early-tracing data (Figure 4) and the drift-toward-

clonality data (Figure 6).

It has recently been reported that Lgr5hi cells orient their

spindle along the apico-basal axis (Quyn et al., 2010). This may

herald the generation of unequal daughter cells because, after

division, the individual daughters may find themselves in

different environments. This occurs in the Drosophila testis,

where the germ stem cell divides perpendicular to a niche struc-

ture, termed the hub. This ensures that one cell will continue as

a stem cell attached to the hub, while the other differentiates into

a gonial blast (Yamashita et al., 2003). Similarly, germ stem cells

and escort stem cells in the Drosophila ovary divide away from

the niche cells of the ovary, the cap cells (Deng and Lin, 1997).

Such an orientation ensures the generation of the downstream

daughter (the prospective cystoblast) and the generation of a

new cap cell-associated stem cell (Fuller and Spradling, 2007).

All Lgr5hi cells span the epithelial sheet, from basal lamina to

apical lumen. Their flanks uniformly touch Paneth cells. Thus,

even though the spindle is oriented perpendicular to the epithe-

lial sheet, the daughter cells do not end up in divergent locations.

We propose that spindle orientation in Lgr5hi cells results from

spatial constraints in these flattened polarized cells.

A stochastic model involving neutral competition (for instance

for niche space) between equal stem cells and leading to neutral

drift dynamics may be operative in other mammalian tissues.

Indeed, the stochastic model generates features of homeostatic

self-renewal that, without detailed scrutiny, would appear to

be exponents of the hierarchical model. For instance, the drift-

toward-clonality intuitively implies the ‘‘predetermined’’ pres-

ence of a single long-lived stem cell, the central characteristic

of the hierarchical model. Yet, our quantitative analysis shows

that it is also the inevitable outcome of the stochastic model.

Further, intuitively the wide diversity in life span of progenitors

would be indicative of the existence of a variety of long-lived

and short-lived progenitors, another feature of the hierarchical

model. Yet, the stochastic model of equal stem cells inevitably

generates a similar richness in life span.

For at least two cases, the long-lived keratinocyte progenitor

in the basal layer of the epidermis (Clayton et al., 2007) and the

germline stem cells in mammalian testis (Klein et al., 2010), it

has been shown that stochastic outcome of the division of

a single type of potentially long-lived progenitor maintains tissue

homeostasis. In both cases, only a single type of differentiated

cell is generated and one may therefore argue that the epidermis

and testis don’t represent examples of multipotent stem cell-

driven self-renewal. Although technically challenging, it would

be of great interest to perform clonal tracing in ‘‘classic’’ stem

cell models such as the bone marrow. More examples may be

unveiled in which homeostasis is obtained at the population level

by competition between equal stem cells, rather than at the

single stem cell level by strictly asymmetric cell divisions.


Mice

E-cadherin-mCFP mice were generated using the construct in Figure 1A. The

neomycin selection cassette was excised in vivo by crossing the mice with the

PGK-Cre mouse strain. For E-cadherin-mCFP genotyping PCR primers, see

Table S1. E-cadherin-mCFP mice were bred with Lgr5-EGFP-Ires-CreERT2

mice. Double heterozygous mice of 10 weeks were used for experiments.

R26R-Confetti mice were generated using the construct in Figure 3A. For

the brainbow 2.1 construct, refer to Livet et al. (2007). See Table S1 for the

R26R-Confetti genotyping PCR primers. R26R-Confetti mice were crossed

with Lgr5-EGFP-Ires-CreERT2 or with Ah-Cre mice. Cre induction: 10 week-

old mice were injected with 5 mg tamoxifen (single injection) or b-naphtofla-

vone (33 100 mg in one day), respectively.

Tissue Preparation for Confocal Analysis

For semi-thick sectioning of near-native tissue, organs were fixed in 4% para-

formaldehyde at room temperature for 20 min and washed in cold PBS. 1 cm2

of intestinal wall was put in a mold. Four percent low melting point agarose

(40�C) was added and allowed to cool on ice. Once solid, a vibrating micro-

tome (HM650, Microm) was used to make semi-thick sections (150 mm)

(velocity: 1 mm/s, frequency: 65 Hz, amplitude: 0.9 mm). Sections were

directly embedded in Vectashield (Vector Laboratories).

FACS Analysis of Lgr5 Populations and In Vitro Culture

Lgr5+ cells were FACS analyzed as previously described (van der Flier et al.,

2009). Crypts were dissociated with TrypLE express (Invitrogen) with

2000 U/ml DNase (Sigma) for 30 min at 37�C. Dissociated cells were passed

through 20 mm cell strainer (Celltrix) and washed with PBS. Cells were stained

with CD24-PE antibody (eBioscience) and Epcam-APC antibody (eBio-

science) for 15 min at 4�C and analyzed by MoFlo (DakoCytomation). Viable

epithelial single-cells or doublets were gated by forward scatter, side scatter

and pulse-width parameter, and negative staining for propidium iodide. Sorted

cells were embedded in Matrigel. Crypt culture medium (advanced DMEM/F12

supplemented with Penicillin/Streptomycin, 10 mM HEPES, Glutamax, 1x N2,

1x B27 [Invitrogen], and 1 mM N-acetylcysteine [Sigma] containing 50 ng/ml

EGF, 100 ng/ml noggin, 1 mg/ml R-spondin) was overlaid. Y-27632 (10 mM)

was included for the first 2 days to avoid anoikis. Growth factors were added

every other day and the entire medium was changed every 4 days. In three


independent experiments, organoid formation was analyzed 7 days after

plating.

Microscope Equipment

Images were acquired using a Leica Sp5 AOBS confocal microscope (Man-

nheim, Germany) equipped with the following lenses: 103 (HCX PL APO CS

NA0.40) dry objective; 203 (HCX PL FLUOTAR L NA0.40) dry objective; 403

(HCX PL APO NA0.85) dry objective; and a 633 (HCX PL APO NA1.30) glycerol

objective.


Supplemental Information includes Extended Experimental Procedures, four

figures, one table, and two movies and can be found with this article online

at doi:10.1016/j.cell.2010.09.016.

ACKNOWLEDGMENTS

We thank Stieneke van den Brink, Jeroen Korving, and the Hubrecht Imaging

Center for technical assistance. We thank J. Lichtman for the Brainbow2.1

cassette. A.M.K. and B.D.S. acknowledge insightful discussions with Douglas

Winton and Carlos Lopez-Garcia.

Received: July 15, 2010

Revised: September 7, 2010



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EphB Signaling Directs PeripheralNerve Regeneration throughSox2-Dependent Schwann Cell SortingSimona Parrinello,1 Ilaria Napoli,1 Sara Ribeiro,1 Patrick Wingfield Digby,1 Marina Fedorova,1 David B. Parkinson,2

Robin D.S. Doddrell,2 Masanori Nakayama,3 Ralf H. Adams,3 and Alison C. Lloyd1,*1MRC Laboratory for Molecular Cell Biology and the UCL Cancer Institute, University College London, Gower Street, London WC1E 6BT, UK2Peninsula College of Medicine and Dentistry, University of Plymouth, Plymouth PL6 8BU, UK3Department of Tissue Morphogenesis, Max Planck Institute for Molecular Biomedicine, and Faculty of Medicine, University of Munster,Munster D-48149, Germany


DOI 10.1016/j.cell.2010.08.039

SUMMARY

The peripheral nervous system has astonishingregenerative capabilities in that cut nerves areable to reconnect and re-establish their function.Schwann cells are important players in this process,during which they dedifferentiate to a progenitor/stem cell and promote axonal regrowth. Here, wereport that fibroblasts also play a key role. Uponnerve cut, ephrin-B/EphB2 signaling between fibro-blasts and Schwann cells results in cell sorting, fol-lowed by directional collective cell migration ofSchwann cells out of the nerve stumps to guideregrowing axons across the wound. Mechanistically,we find that cell-sorting downstream of EphB2 ismediated by the stemness factor Sox2 throughN-cadherin relocalization to Schwann cell-cell con-tacts. In vivo, loss of EphB2 signaling impairedorganized migration of Schwann cells, resulting inmisdirected axonal regrowth. Our results identifya link between Ephs and Sox proteins, providinga mechanism by which progenitor cells can translateenvironmental cues to orchestrate the formation ofnew tissue.

INTRODUCTION

The peripheral nervous system (PNS) differs from the central

nervous system (CNS) in that it is capable of remarkable regen-

eration even after severe injury. After an injury, both PNS and

CNS axons distal to the lesion degenerate, but only PNS axons

regrow and reconnect to their targets (Navarro, 2009; Zochodne,

2008). The distinct ability of peripheral nerves to regrow back to

their targets hinges on the regenerative properties of its glia, the

Schwann cells. Adult peripheral nerves lack a stem cell popula-

tion to produce new glia. Instead, mature differentiated Schwann

cells retain a high degree of plasticity throughout adult life and

upon injury shed their myelin sheaths and dedifferentiate en

masse to a progenitor/stem cell-like state (Kruger et al., 2002;

Scherer and Salzer, 2001). Dedifferentiated Schwann cells are

key to nerve repair for two main reasons. First, they can replenish

lost or damaged tissue by proliferating. Second, they produce

a favorable environment for axonal regrowth both by helping to

clear myelin debris and by forming cellular conduits or corridors,

known as bands of Buengner, that guide axons through the

degenerated nerve stump and back to their targets (Zochodne,

2008).

Regeneration is particularly successful after crush injuries,

because the basal lamina surrounding the axon/Schwann cell

nerve unit is maintained, preserving the integrity of the original

axonal paths and allowing highly efficient and accurate reinner-

vation (Nguyen et al., 2002). Regeneration also occurs after

more severe injuries that significantly disrupt nerve structure,

such as complete transection. However, the process is less effi-

cient as transection presents several additional hurdles for

successful repair (Nguyen et al., 2002). Upon cut, nerve stumps

on either side of the cut retract, generating a gap, which must be

bridged by new tissue; moreover, the regrowing axons from the

proximal stump must travel through this newly formed tissue

(referred to as the ‘‘nerve bridge’’) to reach the distal stump

and ultimately their target organs (McDonald et al., 2006;

Zochodne, 2008). While many studies have contributed to our

understanding of how peripheral nerves repair after crush

injuries, much less is understood about nerve regeneration after

full transection. In particular, little is known about the mecha-

nisms that control the formation and organization of new nerve

tissue or how regrowing axons successfully negotiate the nerve

bridge to rejoin the distal stump. Dissecting these events is key

not only to the development of therapeutic strategies for the

improvement of nerve regeneration but also to the under-

standing of basic principles governing the biology of stem cells

and tissue development.

Ephrin/Ephs are a large family of receptor tyrosine kinases that

function to convey positional information to cells (Lackmann and

Boyd, 2008; Pasquale, 2008). During development, they direct

cell migration, regulate tissue patterning, and help form tissue

boundaries. In adulthood, they participate in the control of tissue

homeostasis and, when aberrantly expressed, can contribute to


cancer development and progression. Eph receptors are

subdivided into two classes: type A, which preferentially

bind GPI-anchored ephrin-A ligands, and type B, which bind

transmembrane B-type ephrins, although crosstalk between

the two classes has been reported (Pasquale, 2008). Interaction

between ephrin ligands and Eph receptors triggers complex

bidirectional signaling, which modulates cell adhesion and repul-

sion, largely by reorganizing the actin cytoskeleton. A great deal

is known about how ephrin/Eph signaling controls actin

dynamics to cause rapid cell responses such as movement

(Arvanitis and Davy, 2008). In contrast, very little is known about

whether ephrin/Eph signaling can cause permanent changes in

cell behavior by regulating gene expression, in spite of the

potential importance of such mechanisms in development and

regeneration.

Here, we show that ephrin-B/EphB signaling directs the early

stages of peripheral nerve repair after transection. As Schwann

cells emerge from both nerve stumps, they come into direct

contact with fibroblasts, which accumulate at the injury site. In

this region, ephrin-B/EphB2-mediated cell sorting of these two

cell types orchestrates the collective cell migration of Schwann

cells in the form of multicellular cords to guide axons across

the injury site. The Schwann cell sorting downstream of EphB2

activation is mediated by Sox2-dependent relocalization of

N-cadherin to contacts between the Schwann cells. Importantly,

loss of EphB2 signaling in vivo in the context of a nerve cut

impairs both the directional migration of Schwann cells and

axonal regrowth.

RESULTS

Fibroblasts and Schwann Cells Sort at the Injury SiteTo analyze the early stages of peripheral nerve repair after

a severe injury, we initially performed a temporal analysis of

Schwann cell and axonal behavior after a complete transection

of the rat sciatic nerve (Figure 1A). We found that, by 2 days after

the cut, the majority of transected nerves had spontaneously

reconnected by formation of a nerve bridge, as judged by

their macroscopic appearance (Figure S1 available online). We

stained longitudinal frozen sections across the bridge site with

antibodies against p75NGFR to label Schwann cells and against

neurofilament to label the axons (whereas p75NGFR is only

expressed in nonmyelinating Schwann cells in intact nerves

[Figure 1A], its expression is induced in all Schwann cells upon

dedifferentiation). As has previously been reported, we found

that the nerve bridge between the two stumps was made up

of cells other than Schwann cells, which are thought to be mainly

inflammatory cells (see Hoechst staining in panels cut d2)

(McDonald and Zochodne, 2003; Schroder et al., 1993).

However, even at this early time point, dedifferentiated Schwann

cells could be detected at the tips of both nerve stumps, whereas

extensive axonal degeneration was only observed in the distal

stump. By day 5, however, Schwann cells had collectively

migrated into the nerve bridge from both stumps as discrete

cell cords, which eventually met in the middle of the bridge.

Regenerating axons from the proximal stump also entered the

bridge at this time, closely following the migratory path of

the Schwann cells. This comigration continued, until, by day 7,

the whole width of the bridge was filled with Schwann cell cords

and with axons, which had grown past the point of the initial

transection and traveled into the distal stump. In agreement

with previous studies (Chen et al., 2005; McDonald et al.,

2006), closer examination of the cords at the leading edge of

the migration front showed that Schwann cells apparently

preceded the axons, suggesting that Schwann cell cords guide

axonal regrowth across the injury site (Figure 1B).

Interestingly, the cords of migrating Schwann cells were sur-

rounded by large numbers of other cells (Figure 1B, p75NGFR-

negative nuclei). As it has previously been reported that fibro-

blasts accumulate at sites of nerve injury (Morris et al., 1972;

Schroder et al., 1993), we stained nerve bridges, 5 days after

Figure 1. Fibroblasts Organize Schwann Cells into Cords that Lead

Axons across the Injury Site after Nerve Cut

(A) Immunofluorescence staining for Schwann cell (SC) marker p75NGFR

(green) and axonal neurofilament RT97 (red) of transverse sections of contra-

lateral intact nerve (left panels, uncut) or cut nerve at time points after transec-

tion (middle and right panels, cut d2, d5 and d7). Nuclei were counterstained

with Hoechst (Hs, blue). Scale bars represent 250 mm.

(B) Immunofluorescence staining for p75NGFR (green) and RT97 (red) of

sections of nerve bridges 5 days after transection. The scale bar represents

25 mm.

(C) Immunofluorescence staining of sections of contralateral (uncut) and nerve

bridges 5 days after transection (cut d5) for the following markers: S100b

and p75NGFR for SC and fibronectin (Fibro) and 4-hydroxyprolyl (4PHL) for

fibroblasts (Fb). Scale bars represent 25 mm.

See also Figure S1.


cut, using two independent sets of fibroblasts markers (fibro-

nectin and prolyl-4-hydroxylase, 4PHL), together with Schwann

cell markers (S100b and p75NGFR), to determine whether the

cells surrounding the Schwann cell cords were fibroblasts

(Figure 1C). This analysis showed that the two major cell types

in the bridge at this point were Schwann cells and fibroblasts

in close proximity to one another. Importantly, the two cell types

did not appear to intermingle, but instead were clearly grouped

into discrete clusters of cells of the same kind, possibly indi-

cating a cell sorting event.

Fibroblasts Switch Schwann Cell Behavior in Cultureto Induce Cell SortingTo understand the cell and molecular events that control the

interaction between Schwann cells and fibroblasts in nerve

wounds, we cocultured primary rat Schwann cells and nerve

fibroblasts. Both cell types were derived from P7 sciatic

nerves and cultured according to previously established proto-

cols, which allow the indefinite subculture of pure populations

with intact cell-cycle checkpoints (Mathon et al., 2001). We

seeded Schwann cells either on their own or on an equal number

of fibroblasts; after 24 hr, we analyzed the behavior of the

Schwann cells by immunostaining them with antibodies against

S100b. As expected, when Schwann cells were plated alone,

they were randomly distributed, and this did not change over

Figure 2. Fibroblasts Mediate Schwann Cell Sort-

ing by Modifying Schwann Cell Behavior

(A) Immunofluorescence images of S100b-labeled SC

cultured in the absence (SC) or presence (SC+Fb) of Fb,

6 and 24 hr after seeding.

(B) Immunofluorescence staining for S100b (S100) and

fibronectin (Fibro) of SC monocultures (SC) or SC/Fb

cocutures (SC+Fb). Scale bars represent 50 mm.

(C) Still images from time-lapse microscopy experiments

of SC cultured alone (SC) or SC cocultured with Fb

(SC+Fb). Shown is one example of SC repelling each other

in the absence of Fb (top panels) and one example of SC

adhering to one another in the presence of Fb (bottom

panels). Numbers in white indicate elapsed time in

minutes after plating.

(D) Quantification of SC behavior in movies described in

(C). The bar graph represents the average number (±SD)

of repulsive and adhesive events per condition. Three

independent experiments were quantified by counting

a minimum of 20 cells per video.

See also Figure S2 and Movies S1, S2, and S3.

time. In stark contrast, Schwann cells cultured

with fibroblasts started to cluster together, and

these Schwann cell clusters became larger by

24 hr after seeding (Figure 2A). Immunofluores-

cence analysis of the cocultures with both

Schwann cell and fibroblast markers confirmed

the sorting of the two cell types: similar to what

we observed in vivo, Schwann cells and fibro-

blasts did not commingle, but instead organized

themselves into mutually exclusive groups

(Figure 2B). Similar results were obtained by

coculturing Schwann cells and fibroblasts iso-

lated from adult nerves (Figure S2), indicating that this is a general

response of both young and adult cells. To better understand

the cell behavior underlying the sorting of these cells, we per-

formed time-lapse video microscopy on cultures of Schwann

cells overexpressing GFP (SC-GFP)—either alone or seeded

on fibroblasts. As shown in Figure 2C and Movies S1 and S2,

SC-GFP cultured alone displayed contact inhibition of locomo-

tion, which resulted in the cells separating from each other

when they came into contact, a behavior predicted to result in

an even distribution of cells. Strikingly, the presence of fibro-

blasts dramatically altered the behavior of the cells: instead of

moving away, the Schwann cells adhered to one another, as

quantified in Figure 2D. Additionally, videos of lower density

cocultures of SC-GFP and fibroblasts (Movie S3) clearly showed

that fibroblasts repelled Schwann cells, causing them to move

away upon contact. These results indicate that the sorting of

Schwann cells into clusters in the mixed cultures depends on

two processes—the repulsion of Schwann cells by fibroblasts,

coupled with a switch in Schwann cell behavior from repulsive

to attractive.

Ephrin/Eph Signaling Mediates Schwann Cell/FibroblastSortingWe reasoned that fibroblasts might change Schwann cell

behavior by secretion of a soluble signal, secretion of an


extracellular matrix (ECM) component, or direct cell-cell contact.

To test the role of soluble factors, we separated the fibroblasts

and Schwann cells in transwell plates (SC+Sol). To test the

role of fibroblast-secreted ECM components, we plated

Schwann cells on top of ECM left behind by fibroblasts after

they were removed using nonenzymatic cell dissociation buffers

(SC+Mat). Finally, to test the role of cell-contact-dependent

signaling, we treated confluent fibroblasts with water for 1 hr to

kill the cells but preserve their membranes and cultured

Schwann cells on top of them. As this treatment also preserved

fibroblast-secreted ECM components, we refer to this condition

as Schwann cell on matrix and membranes (SC+Mat+Mem). We

analyzed Schwann cell sorting in these three conditions using

immunofluorescence staining for S100b and fibronectin and

quantified Schwann cell clustering (Figures 3A and 3B). Whereas

neither the soluble nor the insoluble secreted fraction of

fibroblast cultures induced Schwann cell clustering, the insol-

uble and membrane fractions in combination produced

clustering comparable to that produced by intact fibroblasts.

This result suggested that fibroblasts induce sorting through

direct cell-cell contact. To confirm this directly and rule out a

cooperative role for the ECM, we purified fibroblast membranes

by fractionation and added these to Schwann cell cultures. As

shown in Figure 3C, the fibroblast-membrane fraction alone

was sufficient to cluster Schwann cells, confirming that direct

contact between Schwann cells and fibroblasts mediates

Schwann cell sorting.

Ephrin/Eph signaling has been shown to be a major mediator

of cell-contact-dependent cell sorting. To address whether it has

a role in our system, we stained our cultures with an antibody that

recognizes most phosphorylated Eph receptors and found high

levels of phospho-Eph staining specifically in the Schwann cell

clusters formed in the presence of fibroblasts (Figure S3A). We

then treated Schwann cell cultures with preclustered soluble

recombinant class A or class B ephrins and found that all three

B-type ephrins induced significant Schwann cell clustering,

whereas A-type ephrins did not (Figure S3B), suggesting that

a B-type ephrin on nerve fibroblasts induces sorting. To confirm

that the sorting behavior was solely mediated by ephrin-B

signaling, independently of other membrane components of

the fibroblasts, we overexpressed ephrin-B2 in MDA-MB-435

breast cancer cells, which normally do not express ephrin-B2

(Figure S3C) (Noren et al., 2006). Consistent with the results

obtained with soluble ephrin-B ligands, coculture of Schwann

cells with MDA-MB-435-ephrin-B2 cells, but not MDA-MB-

435-GFP controls, induced Schwann cell clustering, indicating

Figure 3. EphB2 Signaling Mediates Fibro-

blast-Induced Schwann Cell Sorting

(A) Immunofluorescence staining for S100b (S100)

and fibronectin (FBN) of SC cultured alone (SC),

in direct contact with Fb (SC+Fb), in the presence

of Fb conditioned medium (SC+Sol), on Fb-

secreted ECM (SC+Mat) or on Fb membranes

and ECM (SC+Mat+Mem). Cells were fixed 24 hr

after seeding.

(B) Quantification of SC clustering in the condi-

tions depicted in (A). For this and all later experi-

ments, a minimum of 200 cells per coverslip

was counted across randomly selected fields of

view, and the percentage of SC found in clusters

of increasing size was calculated. Error bars indi-

cate the SD across repeats of each condition (n =

2–3). Shown is a representative experiment of

several that gave similar results. (*** p < 0.001).

(C) Quantification of SC clustering. Samples are

SC monocultures (SC), direct cocultures of SC

and Fb (SC+Fb) and SC monocultures in the pres-

ence of fibroblast membrane fractions (SC+mem).

(D) Quantification of clustering in SC cultures

without (SC) or with Fb (SC+Fb) pretreated with

control proteins (Ctl) or soluble recombinant

EphB2-Fc fusion proteins (SC EphB2-Fc).

(E) Quantification of clustering of scr siRNA-

treated SC in the absence (SC Scr) or presence

of Fb (SC+Fb Scr) and EphB2 siRNA-treated SC

cultured in the presence of Fb (SC+Fb EphB2).

Western blots show efficacy of knockdown with

two independent oligos.

See also Figure S3.


that ephrin-B2 is sufficient to induce Schwann cell sorting

(Figures S3C and S3D).

To determine which Eph and efn genes Schwann cells and

nerve fibroblasts express, we performed quantitative RT-PCR

(Table S1). We found that both Schwann cells and fibroblasts

expressed EphB receptors and ephrin-B ligands; however, the

expression levels were very different between the two cell types.

Specifically, fibroblasts expressed much higher levels of ephrin-

B2 ligand, which was low or undetectable in Schwann cells. In

contrast, Schwann cells expressed higher levels of EphB recep-

tors than fibroblasts, with the most significant difference found

for EphB2 expression (Figure S3E).

To test whether EphB2 mediates Schwann cell sorting, we

took two parallel approaches: (1) we inhibited EphB2 signaling

by preincubating fibroblast cultures with soluble recombinant

EphB2-Fc fusion proteins prior to seeding Schwann cells and

(2) we used two independent small interfering RNA (siRNA) oligos

to knock down EphB2 in Schwann cells, prior to coculturing

them with fibroblasts. In both cases, reduction of EphB2

signaling strongly inhibited Schwann cell clustering in the pres-

ence of fibroblasts (Figures 3D and 3E and Figure S3F). Impor-

tantly, the sorting defect of EphB2 knockdown cells was rescued

by concomitant transient transfection of siRNA-insensitive

mouse EphB2, confirming the specificity of the EphB2 pheno-

type (Figure S3G). Thus, ephrin-B/EphB2 signaling between

fibroblasts and Schwann cells mediates cell sorting.

Ephrin-B Signaling Results in Directional AxonalOutgrowthIt is known that ephrin/Eph signaling can promote the directional

movement of cells by constraining migrating cells to specific

areas through active repulsion. This has been shown, for

Figure 4. Schwann Cell Organization

Affects Axonal Outgrowth

Fluorescence images (A) and quantification (B) of

SC and axonal individual and cocultures in stripe

assays.

(A) Representative images of DRGs and SC

cultured alone (top and middle panels) or together

(bottom panels) on control or ephrin-B2-Fc

stripes. SC were labeled with phalloidin or visual-

ized by GFP fluorescence (middle and bottom

panels respectively), and axons were stained

with neurofilament. Scale bars represent 25 mm.

(B) Effects of ephrin-B2 on SC positioning and

axonal outgrowth were quantified by counting

the number of SC and axons on and off

the stripes. A minimum of 200 cells and axons

per coverslip was scored in duplicate per condi-

tion. Error bars denote the SD across repeats

(** p < 0.005).

example, to help guide the migration

of neural crest cells and axon growth

cones during development (Kuriyama

and Mayor, 2008; Lackmann and Boyd,

2008). Both the collective migration of

Schwann cells and the regrowth of axons

after nerve transection are also directional in that the majority of

cords and axons are parallel to one another and migrate along

the long axis of the nerve stumps (see Figure 1A). We therefore

asked whether EphB2/ephrin-B signaling might be responsible

for directing organized Schwann cell and/or axonal migration.

To do this, we performed stripe assays using microcontact

printing (von Philipsborn et al., 2006). We generated lines of pre-

clustered recombinant ephrin-B2 or control protein and seeded

Schwann cells at low density or explanted postnatal rat DRGs

onto the stripes. In the presence of NGF, axonal processes

migrate out of the DRG core, mimicking axonal regrowth after

injury. Remarkably, Schwann cells cultured on ephrin-B2 stripes,

but not on control stripes, accumulated between the stripes,

forming parallel lines of cells reminiscent of the Schwann cell

cords observed in transected nerves in vivo. In contrast, axonal

outgrowth from DRG explants was indistinguishable on control

and ephrin-B2 stripes, with most axons crossing the stripes at

multiple points, indicating that DRG axons are not repelled by

ephrin-B2 (Figures 4A and 4B). However, when DRGs were

explanted onto SC-GFP cells, which had previously been grown

for 4 days on ephrin-B2 stripes, the axons grew out onto the

Schwann cells, between the stripes, to form axon fascicles

(Figures 4A and 4B). These data demonstrate that ephrin

signaling can direct axonal outgrowth by modulating Schwann

cell behavior.

Fibroblast-Mediated Sorting Involves N-CadherinRelocalization to Schwann Cell ContactsWe have shown that EphB2 stimulation triggers Schwann cell

clustering, in part by promoting Schwann cell adhesion, sug-

gesting a possible change in cell-surface adhesion molecules.

Both N- and E-cadherins are expressed by Schwann cells and


have been reported to have roles in cell sorting (Halbleib and

Nelson, 2006). N-cadherin (N-cad) is expressed during develop-

ment, is downregulated in adult nerves, and is re-expressed in

dedifferentiated Schwann cells after nerve injury; in contrast,

E-cadherin (E-cad) is present only in differentiated Schwann

cells (Crawford et al., 2008; Wanner et al., 2006a). When we

stained Schwann cells cultured alone or in the presence of fibro-

blasts with antibodies against E- and N-cad, we could not detect

E-cad on the Schwann cells (data not shown). In contrast, N-cad

was readily detectable in Schwann cell monocultures with

expression detected throughout the cytoplasm and at the

membrane. However, the pattern of N-cad expression dramati-

cally changed in the Schwann cell/fibroblast cocultures with

a progressive increase in levels at cell-cell contacts as shown

in Figure 5A and Figure S4A and quantified in Figure S4B;

western analysis of N-cad levels showed that the shift in N-cad

distribution was accompanied by an increase in protein levels

at 24 hr after seeding, when cell sorting was fully established

(Figure 5B). We obtained similar results when we treated

Figure 5. N-Cadherin Relocalization to Cell

Junctions Mediates Cell Sorting

(A) Representative immunofluorescence images

of Schwann cells cultured on their own (SC) or

with fibroblasts (Fb) for 24 hr and stained for

N-cad (red) and S100b (green). Scale bars repre-

sent 25 mm.

(B) Western blot analysis of total protein lysates

from fibroblast membranes used as control or

GFP expressing Schwann cells cultured on fibro-

blast membranes for the indicated times. GFP

levels were used as loading control.

(C) Quantitative RT-PCR analysis of N-cad mRNA

levels in Schwann cells cultured on fibroblast

membranes for the indicated times. The average

of three independent experiments is shown ±

SEM.

(D) Quantification of clustering of scr siRNA-

treated Schwann cells in the absence (SC Scr) or

presence of fibroblasts (SC+Fb Scr) and of

N-cad knockdown Schwann cells cultured in the

presence of fibroblasts (SC+Fb N-cad). Western

blots show efficacy of N-cadherin knockdown

with two independent oligos. The mean is shown

as ± SD.

(E) Quantification of clustering of Schwann cells

infected with adenoviral vectors encoding control

GFP or N-cadherin in the absence of fibroblasts.

See also Figure S4.

Schwann cells with soluble ephrin-B2

(Figures S4C and S4D). Importantly, the

late increase in N-cad protein was not

accompanied by a rise in its messenger

RNA (mRNA), as judged by quantitative

RT-PCR (Figure 5C), suggesting that the

increase may have resulted from post-

transcriptional changes in protein levels.

Together, these results suggest that

relocalization of N-cad to junctions in

the absence of changes in expression is

sufficient to initiate Schwann cell sorting. However, we cannot

rule out the possibility that the late increase in N-cad levels might

be required for the stabilization and maintenance of sorting.

To test whether the redistribution of N-cad was necessary

for the cell sorting, we used two independent siRNA oligos to

knock down N-cad in Schwann cells and scored Schwann

cell clustering in the presence of fibroblasts (Figure 5D and

Figure S3F). Clustering was strongly reduced in N-cad-deficient

cells, suggesting that N-cad is a critical mediator of the sorting

process. Moreover, rescue experiments in which siRNA-resis-

tant N-cad was overexpressed in N-cad knockdown Schwann

cells confirmed the specificity of the knockdown (Figure S4E).

To determine whether higher levels of N-cad at cell junctions

were sufficient to induce clustering, we mimicked the relocaliza-

tion by overexpressing N-cad using adenoviral vectors, which

results in elevated N-cad levels throughout the cell (data not

shown). Remarkably, N-cad overexpression in Schwann cells

induced large clusters in the absence of fibroblasts (Figure 5E).

Thus, EphB2 signaling in Schwann cells induces cell sorting, at


least in part by causing the redistribution of N-cad to cell-cell

contacts.

EphB2-Induced Relocalization of N-Cadherin Is Sox2DependentEphB signaling was recently shown to mediate cell sorting of

colorectal cancer cells in an E-cadherin-dependent manner,

suggesting that crosstalk between Ephs and cadherins may be

a general mechanism for directing cell sorting (Cortina et al.,

2007). However, the mechanism of the crosstalk and the sorting

process itself are poorly understood. Cell sorting is a complex

process, requiring cell recognition, followed by cell movement,

an extensive process of fine-tuning, culminating in the establish-

ment of cell groups through the stabilization of cell-cell contacts

(Tepass et al., 2002). Moreover, once established, cell and tissue

boundaries both in culture and in vivo are maintained, suggest-

ing that sorting requires long-term modifications in cell behavior

and thus is likely to involve changes in gene expression. The

transcription factor Sox2 plays a pivotal role in the development

and maintenance of some stem and progenitor cells (Chambers

and Tomlinson, 2009). Consistent with these functions, it was

recently shown that Sox2 is expressed in progenitor Schwann

cells in developing nerves and is re-expressed in dedifferenti-

ated Schwann cells, where it is thought to promote proliferation

and suppress differentiation (Le et al., 2005). While studying the

function of Sox2 in Schwann cells, we observed that overexpres-

sion of Sox2 induced the formation of cell clusters, suggesting

that it might be involved in ephrin B-mediated Schwann cell sort-

ing. To test this idea, we overexpressed Sox2 in subconfluent

Schwann cells using an adenoviral vector, and quantified

clustering. As shown in Figure 6A, overexpression of Sox2 was

sufficient to cluster Schwann cells, mimicking the effect of

fibroblasts. Moreover, like fibroblast-induced Schwann cell

clusters, Sox2-induced clusters displayed an increase in junc-

tional N-cad staining (Figure 6B and Figure S5A), without an

increase in total N-cad protein levels or mRNA (Figures S5B

and S5C). To test the dependence of Sox2-mediated clustering

on N-cad-based cell-cell junctions, we infected Schwann cell

cultures with adeno-GPP or adeno-Sox2 viruses in normal or

low Ca2+ media, in which the extracellular domains of cadherins

cannot homodimerize to form junctions (Letourneau et al., 1991).

We found that Sox2-mediated clustering was abolished in

low Ca2+ culture conditions, confirming that Sox2 promotes

Schwann cell clustering by inducing the formation of N-cad junc-

tions (Figure S5D). To test whether Sox2 might be a target

of EphB2, we measured Sox2 protein levels in Schwann

cells cultured on fibroblasts membranes and Schwann cells

treated with soluble ephrin-B2 ligands by western blotting.

In both cases, Sox2 increased in amount and also increased

in apparent size, suggesting a posttranslational modification

(Figure 6C). These observations suggest that EphB2 might

induce cell sorting by modifying gene expression via the tran-

scription factor Sox2. Consistent with this suggestion, treatment

of fibroblast-Schwann cell cocultures with the transcriptional

inhibitor actinomycin D blocked the relocalization of N-cad

(data not shown). To address whether Sox2 is necessary for

fibroblast-induced Schwann cell sorting, we knocked down

Sox2 by siRNA in Schwann cells using two independent oligos

prior to culturing them with fibroblasts and found that clustering

was greatly reduced in the Sox2-deficient cells (Figure 6D and

Figure S3F). Importantly, the phenotype of rat Sox2-deficient

cells was rescued by adenoviral re-expression of siRNA-resis-

tant mouse Sox2 (Figure S5E), confirming that the sorting is

Sox2-dependent. Together, our results suggest the following

Figure 6. EphB2 Signals through Sox2 to

Induce N-Cadherin Remodeling

(A) Quantification of clustering of Schwann cell

cultures infected with adenoviruses encoding

GFP or Sox2-GFP.

(B) Representative immunofluorescence images

of GFP- and Sox2-GFP-overexpressing Schwann

cells stained for N-cadherin (red). Endogenous

GFP fluorescence is also shown. Scale bars

represent 25 mm.

(C) Top: western analysis of lysates of GFP-over-

expressing Schwann cells cultured on fibroblast

membranes for indicated times. GFP levels were

used for loading control. Bottom: western analysis

of lysates from Schwann cells treated with pre-

clustered recombinant ephrin-B2 for indicated

time intervals.

(D) Quantification of clustering of scr siRNA-

treated and Sox2 knockdown Schwann cells

cultured in the absence (SC Scr; SC Sox2) or pres-

ence (SC+Fb Scr; SC+Fb Sox2) of fibroblasts.

Insert shows western analysis of Sox2 knock-

down and loading control (b-tubulin).

See also Figure S5.


mechanism: activation of EphB2 receptor on Schwann cells by

ephrin-B on fibroblasts leads to the modification and stabiliza-

tion of Sox2 protein in Schwann cells, resulting in the relocaliza-

tion of N-cad to the cell-cell contact regions of these cells, which

in turn promotes their sorting. To validate this sequence of

events, we performed two complementary experiments: we

treated Sox2 knockdown cells with soluble ephrin-B2 ligands

and overexpressed Sox2 in EphB2 knockdown cells. As shown

in Figures S5F and S5G, we found that Sox2 loss impaired

ephrin-B2-dependent clustering, while Sox2 overexpression

rescued the phenotype of EphB2-deficient Schwann cells, con-

firming that EphB2 receptor acts upstream of Sox2. Importantly,

these findings identify a link between Eph signaling and Sox2,

providing a mechanism by which ephrin/Eph signaling can elicit

long-term transcriptional changes.

EphB2 Signaling Mediates Directional Collective CellMigration In VivoWe have shown that Schwann cells and fibroblasts are in direct

contact and undergo cell sorting in nerve wounds, suggesting

that the same molecular mechanisms that mediate Schwann

cell/fibroblast cell sorting in culture might be important for

orchestrating the changes in tissue structure seen in vivo. To

Figure 7. EphB2 Directs Early Nerve Regeneration

In Vivo

(A) Representative immunofluorescence staining for

axonal RT97 of sections of proximal nerve stumps of cut

nerves 4 days after half transection. Control proteins (Fc)

or recombinant EphB2 (EphB2-Fc) were delivered to the

cut nerve region via osmotic pumps. The bottom panels

show axonal tracings of images shown in the top panels

obtained with NeuronJ.

(B) Quantification of axonal length as a measure of

complexity. Values represent average length of axons

per animal group. Error bars represent the SD, n = 7

(*** p < 0.001).

(C) Quantification of axonal growth angles to long axis of

the nerves. Shown is the average of the percentage of

axons at angles <45� or >45� per animal group. Error

bars represent the SD, n = 7 (*** p < 0.001).

(D) Representative immunofluorescence staining for

axonal neurofilament of sections of proximal nerve

stumps of cut wild-type (WT) and EphB2�/� mice nerves

4 days after half transection and axonal tracings of images

shown in (E) obtained with NeuronJ (bottom).

(E and F) Quantification of WT and EphB2�/� samples as

in (C) and (D). n = 5 (*** p < 0.001).

See also Figure S6.

test this possibility more directly, we immuno-

stained frozen sections of cut nerve, on

day 5 after transection (or contralateral control

nerves), using antibodies against EphB2,

N-cad, or Sox2, together with Schwann cell-

specific markers (Figures S6A–S6C). Strikingly,

we found that dedifferentiated Schwann cell

cords in the nerve bridge, but not differentiated

Schwann cells expressed all three proteins. The

staining however revealed distinct patterns of

expression along the nerve. EphB2 and Sox2 were present

throughout the distal stump and in the most distal portion of

the proximal stump (as expected for Sox2; Le et al. [2005]),

consistent with the switch-on of these genes as part of the dedif-

ferentiation program of the Schwann cells. In contrast and

consistent with our results in culture, N-cad staining was

restricted to cords in the bridge region, which is where the

Schwann cells come into direct contact with the fibroblasts.

We next used two approaches to investigate the role of EphB2

in nerve regeneration in vivo: we inhibited EphB2 signaling

pharmacologically in rats and examined nerve regeneration

in EphB2�/� mice (Henkemeyer et al., 1996). For the former

approach, we employed mini osmotic pumps to deliver inhibitory

EphB2-Fc fusion proteins (or control Fc proteins) to the injury site

of cut sciatic nerves. In both types of experiments, we cut

halfway across the nerve in order to keep the stumps in close

proximity, thereby minimizing the variability in the speed of

regeneration. Four days after surgery, we immunostained frozen

sections of the nerves and analyzed axonal outgrowth from the

proximal stump (Figure 7). In all nerves, we found an almost

complete overlap between Schwann cell cords and axons

(Figure S6D) and therefore used axonal regrowth as a readout

of Schwann cell behavior. Remarkably, both EphB2-Fc-treated


and EphB2�/� nerves displayed a similar phenotype, which was

markedly different from Fc-treated or wild-type nerves (Figures

7A and 7D). In control nerves, axonal outgrowth was regular,

mostly parallel to the uncut region and remained within the plane

of the section. In contrast, in nerves that lacked EphB2 signaling,

regrowth appeared less organized, with axons growing in many

different directions and often disappearing out of the plane of the

section. We quantified this behavior by measuring axonal length

and the angles of axonal outgrowth with respect to the long axis

of the nerves (Figures 7B, 7C, 7E, and 7F). Compared to control

nerves, EphB2-deficient nerves presented significantly shorter

and more fragmented axons, which more often grew at angles

greater than 45� from the uncut region. We conclude that

EphB2 signaling directs the migration of Schwann cells and

axons during early nerve regeneration in vivo.

DISCUSSION

The development of a multicellular organism relies on the coor-

dinated and mass movement of groups of specialized cells.

The mechanisms that control these processes have been exten-

sively studied, and much insight has been gained into how posi-

tional cues orchestrate complex developmental processes such

as tissue patterning and boundary formation (Kuriyama and

Mayor, 2008; Tepass et al., 2002). What is less well understood

is how cell reorganization and movement may be reinitiated

in adult organisms to repair tissues after a major injury. In some

regenerative tissues, it appears that repair, after injury in the

adult, recapitulates developmental processes (Charge and

Rudnicki, 2004; Deschaseaux et al., 2009). However, in many

cases, the cell types responsible for repair are distinct from their

developmental counterparts and the positional cues are no

longer present, suggesting that different mechanisms must

also be involved. Peripheral nerve regeneration after severe

injury is an example of de novo postdevelopmental tissue forma-

tion. For successful nerve regeneration, migrating Schwann cells

and regrowing axons must both find their way through the bridge

region to close the nerve gap and integrate within the pre-

established geometry of the adult tissue (McDonald et al.,

2006). Most of the mechanisms whereby tissue organization is

established within the newly forming nerve bridge to promote

reinnervation of the distal stump are unknown. Here, we show

that ephrin/Eph signaling is a major mediator of this process.

We find that, after severe nerve trauma, large numbers of fibro-

blasts accumulate at the injury site. It is well established that

fibroblasts play a key role in wound healing by secreting new

ECM and promoting tissue contraction, both of which contribute

to scar formation. Additionally, they are thought to promote

angiogenesis and inflammation by secreting proangiogenic

and proinflammatory cytokines (Sorrell and Caplan, 2009). We

now identify an additional role for fibroblasts in wound repair—

initiating tissue reconstruction by orchestrating directed cell

migration. By recapitulating this behavior in vitro by the coculture

of Schwann cells and nerve fibroblasts, we show that this was

the result of fibroblasts triggering a highly efficient switch in the

behavior of the Schwann cells—from repulsion to adhesion.

This switch is induced by the activation of EphB2 receptors on

Schwann cells by ephrin-B on fibroblasts. We show that a similar

segregation of EphB2+ Schwann cells from fibroblasts occurs in

the nerve bridge in vivo, where the cells come into direct contact

with each other. These findings suggest that, through EphB2/

ephrin signaling, fibroblasts induce the Schwann cells to migrate

through the bridge as compact groups, or cords. Interestingly,

a study on CNS repair observed activation of Eph signaling at

astrocyte/fibroblast borders during glial scar formation, suggest-

ing that the re-establishment of tissue organization through Eph

signaling might be a general function of fibroblasts in wound

healing (Bundesen et al., 2003).

Our work also confirms that regenerating axons rely on their

interaction with Schwann cells for directional guidance. In agree-

ment with previous studies, we find that Schwann cells appear to

precede regrowing axons in the nerve bridge (Chen et al., 2005;

McDonald et al., 2006). Moreover, Schwann cells appear to be

required to guide axons across the bridge to the distal stump,

as disruption of Schwann cell interactions by loss of EphB2

results in aberrant axonal regrowth. This is in agreement with

our in vitro observations that DRG axons fail to respond to eph-

rin-B2 but are indirectly organized by tracks of Schwann cells

that form between stripes of ephrin-B2. These findings are also

consistent with a recent report that inhibition of Schwann cell

proliferation and migration in the nerve bridge using a mitotic

inhibitor resulted in misdirected axons (Chen et al., 2005). The

mechanisms that guide regenerating axons after nerve injury

therefore seem to be distinct from those that guide axons in

the developing PNS. In development, axons have been shown

to lead glial migration during limb formation and to respond

directly to guidance cues, including ephrin-B signaling (Gilmour

et al., 2002; Luria et al., 2008; Wang and Anderson, 1997).

However, it has also been reported that during the final stages

of limb innervation, as developing axons approach their targets,

the growth cones become almost completely surrounded by

Schwann cell progenitors (Wanner et al., 2006b). Moreover,

several lines of evidence from in vivo studies suggest that glial

cells, while dispensable for initial pathfinding, are necessary for

late axonal fasciculation and targeting, suggesting that at these

later stages of development, Schwann cells can influence axonal

growth (Gilmour et al., 2002; Morris et al., 1999; Nguyen et al.,

2002). Thus, regeneration processes might be partially recapitu-

lating late nerve development. It would therefore be of great

interest to explore whether ephrin-B/EphB signaling plays a

role in the migration of Schwann cell progenitors during limb

innervation.

It is commonly thought that Eph signaling elicits short-term

changes in cell behavior, mainly by modulating the actin cyto-

skeleton. Our findings suggest that it can also elicit longer-

term changes through the transcription factor Sox2. Intriguingly,

EphA4 receptor has been shown to directly activate the tran-

scription factor Stat3 in skeletal muscle, suggesting that modu-

lation of transcription might be a common property of Ephs (Lai

et al., 2004) and important for ephrin-directed, long term cell

responses. We also show that Sox2-dependent, EphB2-medi-

ated Schwann cell sorting is induced by the redistribution of

N-cadherin to cell-cell junctions and that this process is depen-

dent on transcription. Although we have not yet identified the

Sox2 target genes responsible, our unpublished observations

suggest that multiple changes in gene expression might be


involved. Whatever the mechanisms, this change in N-cadherin

distribution is likely to promote the regeneration process by

maintaining migrating Schwann cells in groups, thereby pro-

viding a favorable substrate for axonal regrowth (Scherer and

Salzer, 2001).

Sox2 is best known for its central role in the maintenance of

embryonic stem cell self-renewal and pluripotency (Chambers

and Tomlinson, 2009). It has also been shown to be one of the

transcription factors that can help reprogram somatic cells to

become induced pluripotent stem cells (Chambers and Tomlin-

son, 2009; Takahashi and Yamanaka, 2006). Our work uncovers

a novel function of Sox2 in progenitor cells—the coordination of

cell movement and tissue patterning by eliciting long-term

changes in cell behavior in response to extracellular positional

cues. Given the widespread expression of ephrins, Eph recep-

tors, and Sox transcription factors during development, the

regulation of Sox proteins by ephrin/Eph signaling may be a

general mechanism regulating progenitor cells during the forma-

tion of tissues and organs.


Cell Culture

Primary rat Schwann cells and fibroblasts were cultured from P7 animals as

previously reported (Mathon et al., 2001). For cocultures, fibroblasts were

seeded at 7.5 3 104 per cm2 on PLL-laminin in fibroblast medium. The next

day, Schwann cells were added at the same density in a 1:5 mixture of

Schwann cell medium and defined medium as described (Parrinello et al.,

2008). Cultures were analyzed 24 hr later unless otherwise specified. Clus-

tering was quantified by counting the number of Schwann cells found in

groups of 1, 2–5, 6–10 or >10 cells. Adenoviral infections were performed as

reported (Parrinello et al., 2008). For modifications of coculture protocols,

see the Extended Experimental Procedures.

Immunofluorescence, Immunohistochemistry and Western Blotting

Contralateral or cut sciatic nerves at d2, 4, 5, 7, 9, and 10 posttransection were

analyzed; only relevant stages are shown. Nerves were processed and stained

as reported (Wanner et al., 2006a). Sections for immunostaining (8–15 mm) or

for quantification of axonal outgrowth (40–60 mm) were cut with a cryostat

(Leica). For EphB2 staining on sections, signal was amplified using a TSA kit

(Invitrogen). Western blotting and immunostaining were performed as previ-

ously described (Parrinello et al., 2008). For description of antibodies, see

the Extended Experimental Procedures.

Recombinant Protein Treatments and Stripe Assays

Recombinant ephrin-Fc fusions (R&D systems) were preclustered with anti-

human Fc antibodies (Jackson Laboratory) at a 2:1 molar ratio and added to

Schwann cells at a final concentration of 8 mg/ml. For inhibition studies,

EphB2-Fc fusion proteins (R&D systems) were added at 10 mg/ml (culture)

and 200 mg/ml (in vivo). Fc fragments or anti-Fc antibodies alone were used

as negative controls with similar results. Stripes of preclustered ephrin-B2 or

control proteins (10–20 mg/ml) were stamped onto PLL-coated coverslips

generated by microcontact printing and later visualized with fluorescently

labeled anti-Fc antibodies as reported (von Philipsborn et al., 2006). After lam-

inin coating, Schwann cells or DRGs were seeded. For Schwann cell/DRG

coculture experiments, DRGs were plated onto pre-established GFP-express-

ing Schwann cells in the presence of 1 mg/ml aphidicolin to prevent outgrowth

of endogenous glia.

Statistics

For all clustering experiments, statistical analysis was performed by Fisher’s

exact test for rxq contingency tables. Significance was calculated with the

Wilcoxon rank-sum test for all qPCR data and with the Student’s t test for all

other experiments.

Surgeries

All animal work was carried out in accordance to the guidelines and regulations

of the Home Office. Adult (6- to 8-week-old) Sprague-Dawley male rats and

4- to 6-week-old EphB2�/� mice and littermate controls (Henkemeyer et al.,

1996) were used for all experiments. For immunohistochemical analysis, left

sciatic nerves were exposed, under general anesthesia in aseptic conditions,

and transected at midthigh. For inhibition studies, half of the nerve trunk was

cut, and the wounded region was inserted into a silicone tube connected later-

ally at a 90� angle to a smaller caliber tube to which a catheter was attached.

A mini osmotic pump (1007D; Alzet) implanted subcutaneously above the left

buttock was then used to deliver control or inhibitor proteins to the cut site

through the catheter. Wounds were closed using surgical clips. Four days after

surgery, nerves were collected and processed for immunohistochemistry.

EphB2�/� mice wounding experiments were performed in the same way

except that no tubing was used and wounds were reclosed immediately after

half transection. For details of quantification, see the Extended Experimental

Procedures.


Supplemental Information includes Extended Experimental Procedures, six

figures, three tables, and three movies and can be found with this article online

at doi:10.1016/j.cell.2010.08.039.

ACKNOWLEDGMENTS

S.P. is a Royal Society D.H. Research Fellow. This work was supported by

a Cancer Research UK program and an Association for International Cancer

Research project grant. We thank C.D. Nobes for advice and M. Raff and

B. Baum for critical reading of the manuscript, M. Herlyn, J. Milbrandt,

E. Battle, and D. Wilkinson for constructs and G. Parrinello, A. Mira, and J. Kris-

ton-Vizi for statistics.

Received: March 11, 2010



Published online: September 23, 2010

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Comparative Epigenomic Analysisof Murine and Human AdipogenesisTarjei S. Mikkelsen,1,4 Zhao Xu,1,2,4 Xiaolan Zhang,1 Li Wang,1 Jeffrey M. Gimble,3 Eric S. Lander,1 and Evan D. Rosen1,2,*1Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA2Division of Endocrinology and Metabolism, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02115, USA3Stem Cell Biology Laboratory, Pennington Biomedical Research Center, Louisiana University System, 6400 Perkins Road, Baton Rouge,

LA 70808, USA4These authors contributed equally to this work


DOI 10.1016/j.cell.2010.09.006

SUMMARY

We report the generation and comparative analysisof genome-wide chromatin state maps, PPARg andCTCF localization maps, and gene expressionprofiles from murine and human models of adipogen-esis. The data provide high-resolution views ofchromatin remodeling during cellular differentiationand allow identification of thousands of putativepreadipocyte- and adipocyte-specific cis-regulatoryelements based on dynamic chromatin signatures.We find that the specific locations of most suchelements differ between the two models, includingat orthologous loci with similar expression patterns.Based on sequence analysis and reporter assays,we show that these differences are determined, inpart, by evolutionary turnover of transcription factormotifs in the genome sequences and that this turn-over may be facilitated by the presence of multipledistal regulatory elements at adipogenesis-depen-dent loci. We also utilize the close relationshipbetween open chromatin marks and transcriptionfactor motifs to identify and validate PLZF and SRFas regulators of adipogenesis.

INTRODUCTION

Describing the gene regulatory networks (GRNs) that control

development, differentiation, and physiological processes is a

major goal of mammalian genome biology. A GRN consists of

trans-regulatory factors and cis-regulatory elements whose

interactions with each other and the environment govern the

expression of genes in the network and ultimately manifest as

a complex phenotype such as gastrulation, adipogenesis, or

glucose homeostasis (Arnone and Davidson, 1997). The core

trans-regulatory factors in a variety of GRNs have been identified

by expression profiling and genetic analysis, but the large size

and complex architecture of mammalian genomes have pre-

vented systematic identification of cis-regulatory elements.

Recent advances in high-throughput DNA sequencing have

led to the development of new experimental tools that greatly

enhance our ability to study genome function. In particular,

chromatin immunoprecipitation and sequencing (ChIP-Seq)

allows efficient genome-wide profiling of transcription factor

(TF) localization (Johnson et al., 2007; Robertson et al., 2007)

and chromatin state (Barski et al., 2007; Mikkelsen et al.,

2007a). Because different classes of cis-regulatory elements

display characteristic chromatin signatures when they are active

(Hon et al., 2009), ChIP-Seq has emerged as a powerful tool for

comprehensive discovery of these elements.

Identifying the components of a GRN that govern a specific

phenotype of interest from ChIP-Seq maps of a given cell type,

however, remains challenging for several reasons. First, these

maps typically identify tens of thousands of putative regulatory

elements, only some of which are likely to be directly relevant

to the phenotype. Second, whereas these maps appear to be

highly sensitive, their specificity toward biologically relevant

elements is less clear (Birney et al., 2007). For example, TF local-

ization analyses frequently reveal many binding sites that have

no discernable effect on the expression levels of nearby genes

(Johnson et al., 2007; Robertson et al., 2007; Zhang et al.,

2005). Third, practical considerations often necessitate the use

of in vitro cell culture models that might be subject to aberrant

genetic or epigenetic changes. This raises the possibility that

some chromatin state components observed in an in vitro

model may not be representative of the analogous cell type

in vivo (Noer et al., 2009).

We reasoned that comparative profiling of multiple cell culture

models that display similar, inducible phenotypes might help

shed light on these issues. Profiling closely related cell types

before and after induction should help identify regulatory

elements that are directly related to the phenotype. Classifica-

tion of these elements as either model-specific or shared should

then provide a foundation for understanding their relative impor-

tance and therefore help prioritize in-depth functional studies.

To explore this approach, we focused on adipogenesis.

Adipocytes play a central role in systemic metabolism, coordi-

nating lipid and glucose homeostasis (Rosen and Spiegelman,

2006). The burgeoning human and financial costs of obesity,

type 2 diabetes, and other metabolic disorders have therefore

thrust adipocyte biology into the forefront of biomedical research


priorities (Camp et al., 2002). Adipogenesis is also one of the

most intensively studied examples of cellular differentiation,

and several cell culture models that appear to closely approxi-

mate events that occur during adipogenesis in vivo are available

(Rosen and MacDougald, 2006).

Here, we report the generation and analysis of genome-wide

chromatin state maps, TF localization maps, and gene expres-

sion profiles from multiple stages of differentiation in two

established models of adipogenesis, murine 3T3-L1 cells (L1s)

and human adipose stromal cells (hASCs). 3T3-L1 is a cell line

originally subcloned from embryonic fibroblasts (Green and

Meuth, 1974), and hASCs are primary cells derived from adult

subcutaneous lipoaspirates (Aust et al., 2004). Undifferentiated

L1s and hASCs (‘‘preadipocytes’’) have similar fibroblast-like

morphologies. When induced to undergo terminal differentiation

in adipogenic media, both change into round cells that exhibit

properties typical of adipocytes in vivo, such as insulin-stimu-

lated glucose uptake, lipogenesis, catecholamine-stimulated

lipolysis, and adipokine secretion. These two models therefore

provide the opportunity to study GRNs that govern similar

adipogenic phenotypes against a background of phylogenetic,

ontogenetic and technical differences.

RESULTS

Comparative Epigenomic Profiling of AdipogenesisTo facilitate comprehensive epigenomic profiling of cells under-

going adipogenesis, we expanded L1 and hASC preadipocytes

and induced differentiation in adipogenic media. We selected

four matched time points that represented similar stages of

differentiation, as judged by morphology and lipid droplet

accumulation. These time points corresponded to proliferating

(day �2) and confluent (day 0) preadipocytes, immature adipo-

cytes (day 2 for L1s, day 3 for hASCs), and mature adipocytes

(day 7 for L1s, day 9 for hASCs).

We generated genome-wide chromatin state maps using

ChIP-Seq, profiling six histone modifications (H3K4me3/me2/

me1, H3K27me3/ac, and H3K36me3) and the CCCTC-binding

factor (CTCF) at all four time points. We also profiled the adipo-

genic TF peroxisome proliferators-activated receptor g (PPARg)

at the last time point. The resulting data consist of 60 ChIP-Seq

experiments and two negative controls. We also measured

mRNA and miRNA expression levels in both models using micro-

arrays. All data have been deposited in public databases.

To visualize the data, we generated histograms of normalized

densities of ChIP fragments across the genomes. Figure 1 shows

these densities near the murine Pparg gene, which is strongly

upregulated during adipogenesis (Figure S1, available online,

shows the human PPARG locus). The profiled histone modifica-

tions and TFs showed spatial and temporal density distributions

that are qualitatively consistent with their known functions (Hon

et al., 2009). For example, H3K4me3, which is associated with

transcriptional initiation, was primarily found near known

promoters. A case in point is the gain of H3K4me3 observed

near the adipocyte-specific alternative promoter of Pparg (P2,

Figure 1). H3K4me2/me1 and H3K27ac, which are associated

with ‘‘open’’ chromatin and cis-regulatory activity, showed

dynamic distributions in promoter, intronic, and intergenic

regions. H3K36me3, which is associated with transcriptional

elongation, was distributed across active gene bodies and

increased markedly across Pparg as it was upregulated.

H3K27me3, which is associated with Polycomb-mediated

repression, was distributed broadly across the inactive flanking

regions. The PPARg and CTCF densities showed sharp peaks,

consistent with individual TF binding sites.

To support quantitative analyses, we identified significant

clusters of ChIP fragments using a sliding window approach

for histone modifications and QuEST (Valouev et al., 2008) for

TF-binding sites. Each such region or binding site was assigned

an ‘‘enrichment score,’’ which represents the ratio of observed

over expected fragments. Their genome-wide distributions

are consistent with the qualitative patterns described above

(Table S1). mRNA and miRNA expression analyses revealed

correlated expression dynamics that are consistent with efficient

adipogenic differentiation (Figure S2, Table S2, and Extended

Experimental Procedures).

To compare data from the two models, we first attempted to

map each enriched region in the mouse genome to correspond-

ing regions of orthologous sequence in the human genome,

and vice versa, using previously computed whole-genome

alignments. About 80%–90% of these regions could be mapped

to the other genome. We then asked whether these orthologous

regions overlapped the same chromatin marks or TF-binding

sites in the other model (conservatively requiring an overlap

of R 1 bp). We will refer to such overlaps as ‘‘shared’’ marks

or binding sites and the remainder as ‘‘model-specific.’’

We conclude that the data provide a rich resource for studies of

chromatin remodeling and gene regulation in two key models of

adipogenesis. In the following sections, we focus on detection

and functional analysis of cis-regulatory elements in the adipo-

genic GRN and the sequence-specific TFs that interact with them.

Histone Modifications Associated with Distal EnhancersWe began our analysis by characterizing open chromatin marks

in regions distal to (>2 kb from) known promoters. H3K4me2/

me1 and H3K27ac were distributed in highly correlated patterns

at each time point and changed dynamically in thousands of

genomic regions in each cell culture model (Table S1). These

‘‘dynamic’’ regions were often clustered near genes with adipo-

genesis-dependent expression patterns, suggesting that they

represent cooperative or redundant distal enhancers. Ortholo-

gous genes with similar expression in L1s and hASCs frequently

showed similar chromatin marks, but the specific location of

these marks was often model specific; this suggests that the

expression pattern of genes is better conserved between the

models than the specific elements controlling the expression.

To identify putative distal enhancers, we focused on H3K27ac

because recruitment of histone acetyltransferases (HATs) is the

most specific signature known for these elements (Ghisletti

et al., 2010; Heintzman et al., 2009; Wang et al., 2008). We

detected 29,092 distal H3K27ac regions in L1 adipocytes

(day 7), with enrichment scores spanning an order of magnitude

(Table S3). Of these, 6096 (�21%) showed aR 5-fold increase in

enrichment scores relative to preadipocytes (days �2 and 0),

suggesting that they harbor regulatory elements that recruit

HATs during adipogenesis. Conversely, we identified 5159


Chr 6 (mm9): 115.1 Mb 115.2 Mb 115.3 Mb 115.4 Mb 115.5 Mb 115.6 Mb

Syn2

Timp4

Pparg Tsen2Mkrn2

Raf1

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CTC

FP

PA

Rγ

P1 P2

Figure 1. Chromatin State and TF Localization Near Pparg during L1 Adipogenesis

Histograms of ChIP fragments across the Pparg locus, normalized to fragments per 10 million aligned reads, for each of the profiled histone modifications and TFs

at four time points during L1 adipogenesis. All histograms are shown on the same scale, and high values were truncated as necessary. See also Figure S1 and

Figure S2 and Table S1 and Table S2.


H3K27ac regions in L1 preadipocytes (day �2) whose enrich-

ment scores decreased at least 5-fold. We observed similar

dynamics in hASCs (Table S3).

Dynamic changes in open chromatin marks were significantly

correlated with changes in the expression levels of linked genes.

For simplicity, we assumed that each H3K27ac region was

associated with the closest known gene (although there are

counterexamples, as described below). Roughly 15% of all

genes on our microarrays showed a R 2-fold change in expres-

sion between L1 adipocytes and preadipocytes. We found that

the more the expression level of a gene increased or decreased,

the more likely it was to be associated with adipocyte- or prea-

dipocyte-specific H3K27ac, respectively (Figure 2A). Con-

versely, the likelihood that the expression level of a gene

changed R 2-fold was positively correlated with both the enrich-

ment scores (Figure 2B) and the total number (Figure 2C) of

dynamic H3K27ac regions associated with it. By contrast, asso-

ciation with invariant H3K27ac (enriched in both adipocytes and

preadipocytes) had little predictive value with respect to

changes in expression. We observed similar patterns in hASCs

(Figures 2D–2F). Distal regions that show changes in open chro-

matin marks during adipogenesis are therefore likely to be en-

riched for cell type-specific enhancers. Moreover, genes with

dynamic expression patterns appear to frequently be located

near multiple such enhancers (see below and Figure S3).

Comparing open chromatin marks between L1s and hASCs,

we found that �15%–30% of marks identified in one model

were shared with the other model (that is, orthologous se-

quences contained the same chromatin marks). Given that

regions enriched for each open chromatin mark only covered

�2%–4% of each genome, this represents a highly significant

degree of overlap. Regions with the same size distributions

randomly placed across the two genomes would have an ex-

pected overlap of less than 0.5%. Nevertheless, the majority

(70%–85%) of distal open chromatin marks were model specific.

Orthologs that were only associated with dynamic open chro-

matin marks in one of the models often showed discordant

expression patterns. For example, orthologs whose expression

increased more in L1s than in hASCs were also more likely to

be associated with adipocyte-specific H3K27ac only in L1s

and vice versa (Figure 2G). This suggests that model-specific

open chromatin marks correlate with model-specific enhancers.

Of interest, orthologous genes with similar expression patterns

often had similar chromatin marks nearby, but the specific loca-

tions of these marks were typically model specific. For example,

at orthologous loci induced R 2-fold in both models, the majority

(84%) of adipocyte-specific H3K27ac regions in L1s were not

shared with hASCs and vice versa. Their expression patterns

therefore appear to be better conserved than the specific

enhancers that regulate them (below, we verify this observation

through functional analyses).

PPARg LocalizationWe next analyzed the distribution of binding sites for PPARg in

mature L1 and hASC adipocytes (day 7/9). PPARg is a nuclear

receptor that is recruited to PPAR response elements (PPREs)

during adipogenesis as a heterodimer with retinoid X receptors

(RXRs) (IJpenberg et al., 1997) and primarily functions as a

transcriptional activator (Lefterova et al., 2008; Nielsen et al.,

2008). We found that PPARg was largely localized to distal

regions enriched for open chromatin marks. The vast majority

of PPARg-binding sites were not shared between L1s and

hASCs, and this could be explained, in part, by turnover of its

motif in the genome sequences. Loci with PPARg-binding sites

in both L1s and hASCs were, however, highly enriched for genes

with functions relevant to known adipocyte biology.

We detected 7,142 and 39,986 PPARg-binding sites in L1s

and hASCs, respectively (1% FDR; Table S4), with enrichment

scores spanning two orders of magnitude. The excess number

of human sites primarily reflects the identification of more

weak binding sites (Extended Experimental Procedures). Per-

forming ChIP-Seq with a different PPARg antibody yielded

similar results, and the L1 sites reported here showed good

concordance with 5299 sites previously detected in this model

using ChIP-chip (Lefterova et al., 2008; Figure S4).

The PPARg-binding sites followed qualitatively similar

patterns in L1s and hASCs, with the vast majority (85%–95%)

overlapping open chromatin marks (Figure 3A). Ab initio motif

discovery recovered motifs that were similar to the canonical

PPARg/RXR DR1 motif (Figure 3B). There are, however, �1.5

million instances of these motifs in each genome; this implies

that we detected PPARg binding at only �1 in 200 motifs in

the mouse genome. Other factors must therefore contribute to

binding site selectivity. Of note, a motif instance was �15 times

more likely be bound by PPARg in L1 adipocytes if it overlapped

a region enriched for open chromatin marks in preadipocytes

(pFisher < 10�60). In fact, �77% of all PPARg-binding sites de-

tected in L1s were located in such regions. This suggests that

PPARg recruitment during adipogenesis is strongly influenced

by the preadipocyte chromatin state.

The majority (79%) of sites bound by PPARg in L1s were not

shared with hASCs, despite the larger number of sites detected

in the latter model. Of note, 34% of L1 PPARg-binding sites that

could not be mapped to the human genome resided within

rodent-specific transposable element insertions, which implies

that they evolved after the mouse and human lineages

diverged. If an L1-binding site could be mapped to an ortholo-

gous human sequence, the presence of PPARg binding in

hASCs correlated with the presence a conserved motif and

open chromatin marks (Figure 3C). Evolutionary turnover of

DR1-like motifs is therefore likely to contribute to the differential

recruitment of PPARg and open chromatin marks between the

two models.

To explore the correlation between PPARg recruitment and

gene expression, we again assumed that each binding site

was associated with the closest known protein-coding gene.

We found that genes associated with PPARg in L1s were

approximately three times more likely than nonassociated genes

to be upregulatedR 2-fold (pFisher < 10�60). The majority (84%) of

genes associated with PPARg-binding sites were not upregu-

lated, but the likelihood that a gene was upregulated increased

when an associated PPARg binding site had a higher ChIP

enrichment score; was shared with hASCs; or overlapped

adipocyte-specific H3K27ac (Figure 3D). The correlation

between upregulation and gain of H3K27ac is notable. It sug-

gests that, whereas PPARg binding is biased toward regions


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Pre-adipocyte-specificInvariant

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hASC AdhASC Pre





Figure 2. Histone Modifications and Distal cis-Regulatory Elements

(A) Fractions of genes associated with at least one adipocyte (Ad), preadipocyte (Pre), or invariant H3K27ac region in L1s, conditional on changes in expression

levels in adipocytes (max of days 2 and 7) relative to preadipocytes (max of days �2 and 0).

(B) Fractions of genes that showed R 2-fold upregulation (left) or downregulation (right) in L1s, conditional on the maximal enrichment score of associated

H3K27ac regions.

(C) Fractions of genes that showed R 2-fold upregulation (left) or downregulation (right) in L1s, conditional on the number of associated H3K27ac regions.

(D) Fractions of genes associated with at least one H3K27ac region in hASCs, conditional on their changes in expression levels in adipocytes (max [day 3/9])

relative to preadipocytes (max [day �2/0]).


that were already acetylated in preadipocytes, PPARg-binding

sites that recruit HATs to new locations are more likely to be

functionally relevant.

Concentrating on genes with ‘‘dynamic’’ PPARg-binding sites

that gain H3K27ac in L1s, we found that those for which the or-

thologous human gene was not associated with H3K27ac in

hASCs were significantly more likely to show greater upregula-

tion in L1s than in hASCs and vice versa (pFisher < 10�4; Fig-

ure 3E). Model-specific PPREs are therefore likely to contribute

to differential gene regulation in the two models. Annotation

enrichment analysis (Dennis et al., 2003) revealed, however,

that genes that were associated with PPARg-binding sites and

upregulated in both models were strongly enriched for compo-

nents of the classic PPARg signaling pathway, as well as

essential adipocyte functions related to lipid metabolism and

cellular respiration (Figure 3F). Of note, only �57% of these

concordantly upregulated genes actually shared orthologous

PPARg-binding sites. Thus, PPARg targeting of adipocyte genes

appears to be better conserved than the specific PPREs that

mediate PPARg recruitment to these genes.

CTCF LocalizationWe next analyzed the distribution of binding sites for CTCF, a

DNA-binding protein that plays a key role in higher-order organi-

zation of chromatin and is associated with insulator and

enhancer-blocking activities (Phillips and Corces, 2009). We

found that CTCF recruitment was relatively invariant during

differentiation in each model but that the specific binding sites

differed significantly between the two models. These differences

appear to be largely caused by evolutionary turnover of CTCF

motifs.

We detected�43,000 CTCF-binding sites at each time point in

each model (1% FDR). The sites followed largely intergenic

distributions similar to those described in other cell types (Barski

et al., 2007; Kim et al., 2007; Xi et al., 2007; Figure 3G). Ab initio

motif discovery recovered the known CTCF motif (Figure 3H),

and most (�84%) binding sites overlapped a good match to

this motif. Less than half overlapped H3K27ac or H3K4 methyl-

ation, suggesting that these open chromatin marks are not

directly linked to CTCF localization. Most CTCF-binding sites

detected at one time point were also detected at other time

points. For example, �84% of CTCF-binding sites in mature L1

adipocytes were also bound in L1 preadipocytes.

In contrast, among the �70% of binding sites in L1s that could

be mapped to orthologous regions in the human genome, only

about half (�53%) were also bound in hASCs. Shared CTCF

binding in hASCs was strongly correlated with the presence

of a conserved CTCF motif in the human genome (Figure 3I).

As was the case for PPARg, among the remaining �30% of

CTCF-binding sites in L1s that could not be mapped, �65%,

including thousands of the most strongly enriched sites, were

located within rodent-specific transposon insertions.

Functional and Comparative Analysisof the Cd36/CD36 LocusIn the previous sections, we largely relied on genome-wide

statistical analysis. To explore the relationships between open

chromatin marks, TF localization, and cis-regulatory elements

in greater depth, we focused on the Cd36/CD36 locus. This

PPARg-responsive gene encodes a long-chain fatty acid

receptor expressed in adipocytes and other cell types (Yu

et al., 2003) and was one of the most strongly induced genes

in both L1s and hASCs. We confirmed the activity of multiple

adipocyte-specific promoters and enhancers predicted by the

L1 chromatin state maps using functional assays. Consistent

with our genome-wide results, comparative analysis revealed

that, whereas the Cd36/CD36 expression pattern is similar

between L1s and hASCs, several cis-regulatory elements active

in L1s are not conserved in the human genome.

We first analyzed the murine Cd36 locus, which contains three

promoters (P1–P3, Figure 4A) and encodes five transcripts with

identical coding sequences. In preadipocytes, we detected

three CTCF-binding sites flanking the locus but little enrichment

for any of the histone modifications. In adipocytes, we detected

H3K4me3 at P2 and P3, suggesting that these are the major

promoters used in L1s. To confirm this, we quantified each

Cd36 isoform using RT-qPCR. As expected, the vast majority

(�99%) of transcripts originated from P2 and P3 (Figure S5A).

We detected six adipocyte-specific H3K27ac regions across

a �150 kb region upstream of the two active promoters, five of

which also contained PPARg-binding sites. We also detected

broad adipocyte-specific enrichment of H3K4me2/me1 across

this upstream region.

To test whether the distal open chromatin marks identified

adipocyte-specific enhancers, we performed transient reporter

assays in L1 preadipocytes and adipocytes. We cloned 21

�1 kb sequences that overlapped the six adipocyte-specific

H3K27ac regions, as well as most distal H3K4me2/me1 regions,

and 17 additional sequences without any ChIP enrichment as

negative controls (Table S5). Each cloned sequence was in-

serted into three different plasmids carrying a luciferase gene

downstream of P2, P3, or no promoter (114 distinct plasmids).

Plasmids with no promoter showed uniformly low reporter

expression, suggesting that the distal regions possess little

intrinsic promoter activity (Figure S5B). Plasmids with P2 or P3

showed reporter expression levels that were positively corre-

lated with the ChIP enrichment scores of the distal regions

from which they contained sequences (Figure S6). In particular,

sequences from six distinct regions (E1–E6) enhanced the

activity of P3 R 2-fold in adipocytes (Figure 4B). Of note, these

(E) Fractions of genes that showed R 2-fold upregulation (left) or downregulation (right) in hASCs, conditional on the maximal enrichment score of associated

H3K27ac regions.

(F) Fractions of genes that showed R 2-fold upregulation (left) or downregulation (right) in hASCs, conditional on the number of associated H3K27ac regions.

(G) Fraction of genes associated with at least one adipocyte-specific H3K27ac region in L1s or hASCs, conditional on the ratio of their changes in expression

levels during L1 and hASC adipogenesis.



G

H

I

C

A

D

E

F

B

ChIP Enrichment

L1 (d

ay 7

)n

= 42

,957

Promoterproximal

(%)

Motifmatch

(%)

H3K4me/H3K27ac(Ad, %)

Bound inPre(%)

Orthologousregion

found (%)

Detected in orthologousregion (%)

Human regions orthologous toL1 CTCF binding sites

Quartile Median

hAS

C (d

ay 9

)n

= 44

,717

4th 311.1 10.9 94.9 43.1 99.9 83.3 66.53rd 104.7 11.3 88.7 29.8 98.4 76.3 47.02nd 41.9 11.7 79.4 25.3 86.0 61.2 20.71st 20.0 12.5 70.1 27.8 51.4 52.1 10.9

4th 328.5 11.1 87.6 61.2 99.9 81.2 63.33rd 135.2 11.1 77.9 48.7 99.8 78.0 45.32nd 51.7 13.8 61.2 43.1 94.2 72.5 22.51st 20.5 17.6 39.8 47.1 68.4 69.7 10.3

CTCF

ChIP Enrichment

L1 (d

ay 7

)n

= 7,

142

Promoterproximal

(%)

PPARγOrthologousDynamic

YYY

YYN

YNY

YNN

NN

36729.7

76716.3

89618.4

1,92512.2

11,248-9

-5

-7

-3

-4

-4

N

Total (n)Up (%)

Motifmatch

(%)

H3K4me/H3K27ac(Ad, %)

H3K4me/H3K27ac(Pre, %)

Orthologousregion

found (%)

Detected in orthologousregion (%)Quartile Median

hAS

C (d

ay 9

)n

= 39

,986

4th 44.0 20.1 82.1 98.0 82.2 84.5 29.93rd 23.3 22.1 68.7 96.0 75.9 82.6 18.42nd 17.9 26.5 56.2 92.6 73.9 80.2 19.41st 13.2 30.2 48.9 91.3 75.2 80.0 17.4

4th 55.0 8.6 67.3 91.8 79.0 77.8 6.93rd 28.1 10.8 48.6 84.9 74.7 76.6 3.22nd 19.3 12.3 39.8 81.4 72.8 75.6 2.71st 13.8 16.3 31.9 84.1 77.3 75.8 2.8

PPARγ

ATCG

AGTCCTAGGATCT

CGTAC

GTC

ATG

CGCATCTAG

ATCGGACTA

GCATGGATC

0

1

2

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1

2

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1

2

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ATGC

AGCTCTAG

ATGCTAG

ACTG

ATGCTCGATCGACGATAG

CATG

ACGTATGCCTGA

TACGGCATTACGCGATCTAG

ACGTTCGAAGTCTACGAGA

AGCTG

ACGTATGCCTA

bits

bits

bits

12,840 1,961

2,787 11,769

Yes No

Yes

No

8,702 4,057

6,925 9,673

Yes

No

Human regions orthologous toL1 PPARγ binding sites

833 1,426

687 2,900

H3K4me/H3K27ac

Motifmatch

Yes

No

1,430 2,172

90 2,154

Yes

NoH3K4me/H3K27ac

Motifmatch

Bound in hASCs

Yes NoBound in hASCsEnriched Annotation Categories

PPARγ sites and up-regulated in L1 + hASC

PPARγ site and up in L1 only

PPAR signaling pathway (KEGG) 2x10

p-value

Lipid metabolism 1x10

Peroxisome 4x10Lipid homeostasis 3x10

Mitochondrion 6x10Regulation of inflammatory response 4x10

Oxioreductase 8x10

PPARγ site and up in hASC only

Glycoprotein 4x10Lipid synthesis 5x10

13536.3

31624.7

36926.8

50819.3

13,8756.5

Total (n)Up (%)

282 31.6

8489.6

91517.4

7,580 5.0

5,9581.4

Total (n)Up (%)

11135.1

42620.0

47222.0

3,687 8.3

10,9322.4

Total (n)Up (%)

L1hA

SC

All

Dynamic PPARγ site in

Both hASC only L1 only

19528.2

71411.1

80720.5

Total (n)Up in L1 (%)

36.4 18.9 7.2Up in hASC (%)

4thquartile

All

4thquartile

5.2

-4

-3

-3

Figure 3. PPARg and CTCF Localization in Adipocytes

(A) Summary of PPARg-binding sites in L1 and hASC adipocytes. For each quartile of ChIP enrichment scores, the columns show (from left to right) the

percentage of sites located% 2 kb from a known promoter; sites overlapping a PPARgmotif; sites overlapping H3K4me3/me2/me1 and/or H3K7ac in adipocytes

and in preadipocytes; sites that could be mapped to an orthologous region in the other genome; and mapped sites that were also bound by PPARg in the other

model.

(B) Motifs learned ab initio from sequences ± 100 bp from the top 800 PPARg-binding sites in L1s (ranked by enrichment scores). Virtually identical motifs were

learned from hASCs.

(C) Correlations between PPARg binding, the presence of a conserved motif instance, and open chromatin marks in human genomic regions orthologous to L1

PPARg-binding sites.

(D) Fractions of genes that were upregulated R 2-fold in L1s or hASCs, conditional on association with a PPARg-binding site. Orthologous PPARg-binding sites

could be mapped to an orthologous region also bound in the other model. Dynamic PPARg-binding sites increased H3K27ac enrichment R 5-fold.

(E) Fractions of genes that were upregulated R 2-fold in L1s or hASCs, conditional on association with dynamic PPARg-binding sites.

(F) Annotation enrichment analysis of orthologs associated with PPARg-binding sites and upregulated R 2-fold. p values are Benjamini corrected.

(G) Summary of CTCF-binding sites in L1 and hASC adipocytes.

(H) Motif learned ab initio from sequences ± 100 bp from the top 800 CTCF-binding sites in L1s (ranked by enrichment scores). A virtually identical motif was

learned from hASCs.

(I) Correlations between CTCF binding, the presence of a conserved motif instance, and open chromatin marks in human genomic regions orthologous to L1

CTCF-binding sites.



Chr 5 (mm9) 17.30 Mb 17.35 Mb 17.40 Mb 17.45 Mb 17.50 Mb 17.55 Mb

0

1

2

3

4

0

1

2

0

1

2

0

1

2

3

4

PPARG

CTCF

H3K36me3

H3K27ac

H3K4me1

H3K4me2

H3K4me3

CTCF

H3K36me3

H3K27ac

H3K4me1

H3K4me2

H3K4me3

L1 (d

ay -2

)L1

(day

7)

P1P2*

P3

Cd36 Gnat3

HindIII fragments

Distal fragments

Cd3

6-P

3C

d36-

P2

Rel

ativ

e cr

oss-

link

freq.

(d

ay 7

/day

-2)

Cd3

6-P

3C

d36-

P2

RLU

rela

tive

to

prom

oter

onl

y (d

ay 7

)C

hIP

-Seq

frag

men

t den

sitie

s

A

B

C

E1 E2 E3 E4 E5 E6

Figure 4. Identification of Adipocyte-Specific Cd36 cis-Regulatory Elements

(A) Chromatin state maps of the �300 kb Cd36/Gnat3 locus from L1 preadipocytes (day �2) and adipocytes (day 7). Cd36 has three known promoters (P1–P3).

(Asterisk) Start of the protein-coding sequence.

(B) Reporter assays. Each dot shows the ratio of normalized luciferase expression (RLU) from plasmids carrying distal fragments upstream of P2 or P3 over the

estimated basal activity of the promoter. Fragments from six distinct distal sites (E1–E6) showed R 2-fold mean enhancement of expression from P3 (orange

dots, top). Three of these (orange dots, bottom) also showed R 2-fold mean enhancement of expression from P2. E5 was present within two overlapping frag-

ments. Error bars show standard errors of the means.

(C) Chromosome conformation capture. Each dot shows the cross-linking frequency of a HindIII fragment to P3 (top) or P2 (bottom) in adipocytes relative to pre-

adipocytes. Error bars show standard errors of the means.

See also Figure S5, Figure S6, and Table S5.


corresponded to five of the six distal adipocyte-specific

H3K27ac regions, whereas the sixth (E3) was primarily enriched

for H3K4me1. Sequences from E4–E6 also enhanced the activity

of P2 R 2-fold in adipocytes. By contrast, only one plasmid (E5

upstream of P2) showed comparable enhancer activity in preadi-

pocytes. This confirms that dynamic H3K27ac enrichment is

a signature of cell type-specific enhancers.

To determine whether E1–E6 physically interact with P2 and

P3 in their native chromatin context (Ptashne, 1986), we used

chromosome conformation capture (Dekker et al., 2002). We

found that the frequency of interactions between the two

promoters and E3–E6, which are located 75–150 kb upstream,

increased �2-fold in adipocytes relative to preadipocytes

(Figure 4C and Table S5). E1 and E2, which are located much

closer to the promoters, also showed consistent but less-signif-

icant (�1.1-fold) changes. We conclude that Cd36 is regulated

by multiple distal enhancers, including three that are located

within introns of the neighboring gene Gnat3.

We next compared the murine Cd36 locus to human CD36

(Figure 5A). All three murine promoters were conserved in the

human genome. In contrast to L1s, however, we only detected

H3K4me3 at P3, indicating that this is the major promoter used

in hASCs.

Three of the six enhancers identified in L1s (E2, E4, and E6)

were shared with hASCs. Of the three L1-specific enhancers,

E1 and E3 were located in nonrepetitive sequences in the mouse

genome but had no recognizable orthologs in human. Most of

the E5 sequence could be mapped, but the chromatin marks

across this �1 kb region in L1s were not shared with hASCs.

Upon close inspection, we found that the PPARg motif in E5 in

the mouse genome was located in a small (�100 bp) fragment

of a rodent-specific LINE/L1 transposon (Figure 5B). Insertion

of this element therefore appears to have generated a species-

specific PPRE. Conversely, we detected at least two putative

enhancers/PPREs in hASCs (based on H3K27ac and PPARg

enrichment) that could not be mapped to the murine genome.

Two of the three distal CTCF-binding sites in L1s were also

shared with hASCs. The third site, located upstream of E6, could

be mapped to an orthologous region that was not bound in

hASCs (Figure 5C). CTCF did, however, bind to a site �5 kb

away in hASCs that was not shared with L1s. Inspection revealed

that the CTCF motif bound in L1s was not conserved in the

human genome and vice versa (Figure 5D). Thus, the approxi-

mate location of this putative insulator element appears to be

conserved even though the specific motif instances are not.

We conclude that, whereas the overall regulatory architecture

of the Cd36/CD36 locus is conserved, there has been substantial

turnover of specific cis-regulatory elements.

Identification of Previously Unidentifiedtrans-Regulatory FactorsFinally, we explored whether we could use the chromatin state

maps to identify trans-regulatory factors in the adipogenic

GRN. L1s and hASCs each express hundreds of sequence-

specific TFs, not all of which are likely to be directly involved

in adipogenesis. Whereas our data show that many active

cis-regulatory elements are not shared, the identities and

sequence specificities of the factors that interact with them are

likely to be better conserved (Weirauch and Hughes, 2010).

Accordingly, we enumerated instances of all known TF motifs

within regions that underwent chromatin remodeling in L1s or

hASCs and then ranked the motifs according to their relative

enrichment in adipocyte- or preadipocyte-specific regions.

Strikingly, many of the most enriched motifs from both models

corresponded to known pro- and anti-adipogenic regulatory

factors (Table S6).

Figure 6 shows the most enriched motifs in regions that (1)

gained or lost H3K27ac during L1 adipogenesis and (2) could

be mapped to orthologous regions with the same mark in hASCs.

Each of these motifs was enriched in both the mouse and the

orthologous human sequence. Among the motifs most enriched

within adipocyte-specific H3K27ac regions are those recognized

by PPARg/RXR and C/EBP proteins, which together form the

core adipogenic GRN. The list of motifs also contained other

known regulators of adipogenesis, such as the IRF, GATA,

NF-kB, and STAT families. The motifs most enriched within

preadipocyte-specific H3K27ac regions are recognized by

several mediators of growth factor responses and regulators of

cell proliferation, such as AP-1 (FOS/JUN), SRF, and MEF2A,

as well as a variety of developmental factors from the homeodo-

main and POU families.

The presence of multiple known regulators near the top of the

ranked motif lists suggested that other TFs with similar ranks but

no previous evidence of involvement in adipogenesis are good

candidates for follow-up. We selected two of these factors

for further analysis: promyelocytic leukemia zinc finger protein

(PLZF, encoded by Zbtb16) and serum response factor (SRF,

encoded by Srf). Expression of both of these factors was de-

tected in our L1 and hASC microarray data. We also confirmed

their expression in mouse adipose tissue and differentiating L1

cells using RT-qPCR (Figure S7). To assess whether these

factors regulate adipogenesis, we used gain- and loss-of-func-

tion assays. We found that independent overexpression of either

factor in L1 cells (Figure S7) was sufficient to repress adipogen-

esis, as evidenced by reduced lipid accumulation (Figure 7A)

and diminished markers of terminal differentiation (Figures 7B

and 7C). Conversely, RNAi-mediated knockdown of PLZF or

SRF (Figure S7) enhanced L1 adipogenesis, as assessed by

the same parameters (Figures 7D–7F). Similar effects were

obtained with two unique hairpins for each factor. These data

indicate that trans-regulatory factors in GRNs can be identified

by an integrated approach incorporating epigenomic profiling

and motif enrichment analysis.

DISCUSSION

We have generated comparative chromatin state maps, TF local-

ization maps, and gene expression profiles from differentiating

L1s and hASCs. Our initial analysis of the data demonstrates

their utility to studies of chromatin remodeling and gene regula-

tion in adipogenesis and cellular differentiation.

Comparisons between time points revealed a close correlation

between changes in gene expression and changes in distal

open chromatin marks. Whereas only a minority of regions

enriched for H3K27ac changed during adipogenesis, this

dynamic subset appeared to be highly enriched for adipocyte


Chr 7 (hg18)79.90 Mb79.95 Mb80.00 Mb80.05 Mb80.10 Mb80.15 Mb

Chr 5 (mm9)17.30 Mb 17.35 Mb 17.40 Mb 17.45 Mb 17.50 Mb 17.55 Mb

P1P2 E1 E2 E3P3

Cd36 Gnat3

GNAT3P1P2P3

CD36

XX

X XX

E4 E5 E6

PPARG

CTCF

H3K36me3

H3K27ac

H3K4me1

H3K4me2

H3K4me3

L1 (d

ay 7

)

PPARG

CTCF

H3K36me3

H3K27ac

H3K4me1

H3K4me2

H3K4me3

hAS

C (d

ay 9

)

ChI

P-S

eq fr

agm

ent d

ensi

ties

ChI

P-S

eq fr

agm

ent d

ensi

ties

A

B C

D

mm9 to hg18

hg18 to mm9orthology

17.505 Mb 17.510 Mb

79.940 Mb 79.945 Mb

17.549 Mb 17.551 Mb 17.553 Mb

79.895 Mb79.900 Mb

PPARGL1 (day 7)

PPARG motifs

Gnat3

Transposons

PPARGhASC (day 9)

PPARG motifs

GNAT3

Transposons

Chr 7 (hg18)

Chr 5 (mm9)

mm9 to hg18


CTCFL1 (day 7)

CTCF motifs

CTCFhASC (day 9)

CTCF motifs

Chr 7 (hg18)

Chr 5 (mm9)mm9 to hg18


X

E5 E6

GAAGGCGCCCCCTGGTGGTCAGGAAAATGGACTGTGGCTCTCAG

TGCATTGCTAATAACTACAGGATGTGCTGCTCCCTACTGGAGAA

MouseHuman

Figure 5. Comparison of Cd36/CD36 in L1 and hASC Adipocytes

(A) Genomic and chromatin state maps from L1 (top) and hASC (bottom) adipocytes. Orthology tracks show regions mapped from the mouse to the human

genome (pink) and vice versa (red). Gray vertical lines highlight orthologous sites, those terminated by X highlight sites that could not be mapped. Orange

dots show the E1–E6 enhancers identified in L1s.

(B) Expanded view of E5/E6 shows the locations of PPARg motifs (blue bars) and transposons (gray/black) in the genomic sequences. The PPARg motif

underlying the peak of the L1 ChIP-Seq signal lies within a rodent-specific LINE/L1 fragment (arrow).

(C) Expanded view of an upstream region shows CTCF ChIP-Seq signals at nonorthologous sites separated by �2.4–5 kb in L1s and hASCs.

(D) Alignments of the sequences underlying the two nonorthologous sites in (C) show that the underlying motifs (blue bars) are not conserved.


and preadipocyte-specific enhancers. Thus, profiling chromatin

states before and after induction of a phenotype of interest can

help pinpoint regulatory elements that are directly related to

that phenotype. Importantly, gain of histone acetylation might

help to distinguish functional PPREs from nonproductive

PPARg-binding sites. Similar observations were recently

reported for endotoxin- and androgen-responsive enhancers in

macrophages (Ghisletti et al., 2010) and prostate cancer cells

(He et al., 2010), respectively. We also found that dynamically

expressed genes were often associated with multiple distal

elements that showed coordinated changes in chromatin state.

Elucidating how these distinct elements interact with each other

and their target genes will be important to our understanding of

mammalian gene regulation.

Comparisons between the two models revealed significant

overlaps of chromatin marks in orthologous regions, which is

consistent with a previous study of mouse and human fibroblasts

(Bernstein et al., 2005). The majority of open chromatin marks

and TF-binding sites were, however, not shared. Strikingly,

differential recruitment of PPARg and CTCF was correlated

with turnover of their motifs. This suggests that many model-

specific TF-binding sites and associated chromatin marks reflect

genetic divergence between mouse and human, rather than

ontogenetic or technical differences between L1s and hASCs.

Similar turnover has recently been observed in hepatocytes

Figure 6. TF Motifs Associated with Chro-

matin Remodeling during Adipogenesis

TF motifs with the highest relative enrichment in

adipocyte- (right) and preadipocyte-specific (left)

H3K27ac regions. The top 400 L1 adipocyte and

preadipocyte H3K27ac regions (ranked by enrich-

ment scores) that could be mapped to ortholo-

gous locations with H3K27ac in hASCs were

used. Each mammalian TRANSFAC (M prefix)

and UniPROBE (U prefix) motif was matched and

assigned adipocyte/preadipocyte enrichment

ratios in the underlying mouse and human

sequences (corrected for length and composition).

The ‘‘ratio’’ columns show the maximal (left) or

minimal (right) enrichment ratio from mouse and

human for nonredundant motifs with consistent

enrichment ratios in the two genomes. The ‘‘candi-

dates’’ columns show genes or gene families

expressed in L1 cells that are known to recognize

each of the motifs. See also Table S6.

(Odom et al., 2007; Schmidt et al.,

2010). Of interest, many TF-binding sites

that could not be mapped between the

genomes were located within lineage-

specific transposon insertions, which is

consistent with transposons being a

major creative force in the evolution of

mammalian gene regulation (Lowe et al.,

2007; Mikkelsen et al., 2007b). A key

remaining question is to what extent

turnover of TF-binding sites reflects

adaptation, or simply GRN ‘‘drift,’’ that

may affect expression levels but has no significant biological

impact. Importantly, we found that orthologs targeted by PPARg

in both models were enriched for functions relevant to known

adipocyte biology. Moreover, analysis of the orthologous

Cd36/CD36 loci revealed multiple species-specific regulatory

elements, despite their similar expression patterns. The pres-

ence of multiple distal regulatory elements with similar activities

near a single gene might facilitate turnover of individual elements

by providing redundancy.

Finally, motif enrichment analysis revealed that the close

relationship between chromatin state and TF-binding sites can

be utilized to infer previously unidentified trans-regulators. We

previously identified roles for interferon regulatory factors

(IRFs) and the orphan nuclear receptor COUP-TFII in adipogen-

esis based on analysis of chromatin at a limited number of loci

(Eguchi et al., 2008; Xu et al., 2008). Using our genome-wide

data, we discovered two additional factors, PLZF and SRF,

with anti-adipogenic activity. PLZF is a member of the BTB/

POZ domain family of TFs (Kelly and Daniel, 2006) and appears

to function primarily as a repressor by recruiting nuclear receptor

corepressors (N-CoRs) and histone deacetylases (HDACs). SRF

is a MADS box TF originally named for its role in mediating the

effects of serum stimulation (Norman et al., 1988). We are

currently attempting to understand the specific functions of

PLZF and SRF in adipogenesis. In addition, we are using the


A

B C

D

EV

Day 0

SRFPLZF

shSRFshPLZFshLuc

Day 8

C/EBPαα

PPARγ

Adiponectin

Actin

Day 0 Day 4

Day 0 Day 8Day 4

C/EBPα

PPARγ

Adiponectin

Actin

FE

A di poq

E

Cebpa120

60

0 4 8Day

0 4 8Day

Pparg16

8

Adipoq Slc2a4

Dgat1 Fasn

300000

150000

18000

9000

16

8

6

3

Rel

mR

NA

Rel

mR

NA

Rel

mR

NA

200

100

0 4 8Day

0 4 8Day

2000000

1000000

20

10

30000

15000

20

10

8

4

Cebpa Pparg

Adipoq Slc2a4

Dgat1 Fasn

Rel

mR

NA

Rel

mR

NA

Rel

mR

NA

****** **

**

****** ***

***

******

******

***

***

*** ***

**

*****

***

***

***

***

***

***

***

***

******

***

**

***

***

** *

*****

***

***

***

**

***

***

***

**

*** ***

Day 4 Day 8

EV SRFPLZF EV SRFPLZF

Day 0 Day 4 Day 8

shSRFshPLZFshLuc shSRFshPLZFshLuc

EVPLZFSRF

shLucshPLZFshSRF

shLu

csh

PLZF

shSRF

shLu

csh

PLZF

shSRF

shLu

csh

PLZF

shSRF

EV PLZFSRF

EV PLZFSRF

EV PLZFSRF

Figure 7. PLZF and SRF Regulate Adipogenesis

(A) L1 preadipocytes were transduced with retrovirus expressing PLZF or SRF (pMSCV empty vector [EV] as control) and induced to differentiate. The cells were

subjected to oil red O staining at the indicated time points.

(B) mRNA levels relative to 36B4 were assessed by RT-qPCR (mean ± SD; n = 4) at the indicated time points. **p < 0.01; ***p < 0.001.

(C) Protein levels were assessed by western blotting at the indicated time points.

(D) L1 preadipocytes were transduced with a retrovirus expressing control shRNA (shLuc), PLZF (shPLZF), or SRF (shSRF). The cells were subjected to oil red O

staining at the indicated time points.

(E) mRNA levels relative to 36B4 were assessed by RT-qPCR (mean ± SD; n = 4) at the indicated time points. *p < 0.05; **p < 0.01; ***p < 0.001.

(F) Protein levels were assessed by western blotting at the indicated time points. See also Figure S7.


chromatin state maps to identify other factors in the adipogenic

GRN. This approach can be expected to become increasingly

powerful as the completeness and quality of TF motif databases

improve. More generally, we expect that it can be applied to

studies of a variety of other gene regulatory networks.


Oligonucleotides and Antibodies

All primers, hybridization probes, hairpin sequences, and antibodies used are

listed in Table S7 and the Extended Experimental Procedures.

Cell Culture

3T3-L1 cells were cultured and differentiated as described in Eguchi et al.

(2008). Human abdominal adipose tissue was obtained with informed consent

from a 33-year-old Caucasian female (BMI = 32.96 Kg/m2) undergoing lipoas-

piration (Pennington Biomedical Research Center Institutional Review Board,

Protocol PBRC24030). hASCs were isolated as described in Dubois et al.

(2008) and differentiated using a protocol modified from Hebert et al. (2009).

For additional details, see the Extended Experimental Procedures.

ChIP-Seq

L1 cells and hASCs were treated with 1% formaldehyde for 10 min at 37�C and

stored at �80�C. ChIP and Illumina sequencing library construction were

performed as described in Mikkelsen et al. (2007a). The computational

analysis is described in the Extended Experimental Procedures.

RNA Preparation and Expression Analysis

Total RNA was prepared using TRIzol (Invitrogen). mRNA expression data

were generated using GeneChip arrays (Affymetrix). miRNA expression data

were generated using BeadChips (Illumina). RT-qPCR were performed using

SuperScript III (Invitrogen) or RETROscript kit (Ambion), SYBR Green, and

the 7900HT Real-Time PCR system (Applied Biosystems). Annotation

enrichment analysis was performed using DAVID 6.7 (Dennis et al., 2003).

Reporter Assays

Cd36 P2, P3, and 38 distal sequences were PCR amplified from a BAC (RP23-

175A11; BACPAC Resource Center) and cloned into pGL4.10 (Promega)

using In-Fusion (Clontech). L1 cells were nucleofected with solution SE (Lonza)

and the FF-150 and DS-137 programs for preadipocytes and adipocytes,

respectively. Luciferase activities were measured using Dual-Glow (Promega)

and an EnVision 2103 multilabel reader (PerkinElmer).

Chromosome Conformation Capture

Chromosome conformation capture (3C) was performed using RT-qPCR

with FAM/IBFQ hybridization probes (IDT) and HindIII digestion as described

in Hagege et al. (2007). The normalization library was generated from the

RP23-175A11 BAC.

Sequence Analysis

All sequence analyses were performed on the hg18 (human) and mm9 (mouse)

reference genome sequences and annotations (http://genome.ucsc.edu).

Orthologous regions were mapped using liftOver (UCSC), requiring > 10%

nucleotide overlap. Motif discovery was performed using MEME 4.3 (Bailey

and Elkan, 1994). Motif instance matching was performed using FIMO with

a p value threshold of 10�4. The motif enrichment analysis was performed

using TRANSFAC 11.3 and UniPROBE (Oct 7, 2009), as described in the

Extended Experimental Procedures.

PLZF and SRF Overexpression and Knockdown

ORFs were PCR amplified and cloned into pMSCV (Clontech). shRNAs

were synthesized and cloned into pSIREN (Clontech). Retroviruses were

generated using Phoenix cells and CellPhect (Amersham Biosciences) and

were used to transduce L1 preadipocyte subclones that typically differentiate

at 30%–50% efficiency. For additional details, see the Extended Experimental

Procedures.

ACCESSION NUMBERS

All microarray expression and sequencing data have been deposited to the

NCBI GEO database (http://www.ncbi.nlm.nih.gov/geo/) under accession

number GSE20752.



figures, and seven tables and can be found with this article online at doi:10.

1016/j.cell.2010.09.006.

ACKNOWLEDGMENTS

The authors would like to thank the staff of the Broad Institute for assistance

with data generation and Gang Yu at the Tissue Culture Core Facility, Penning-

ton Biomedical Research Center, for isolating the hASCs. This project

was supported by funds from the Broad Institute, NIH DK63906 (E.D.R.), an

American Diabetes Association Career Development Award (E.D.R.), the

Pennington Biomedical Research Foundation (J.M.G.), and NORC Center

Grant #1P30 DK072476 (J.M.G.). J.M.G. declares that he has consulted for

companies focusing on adipose-derived adult stem cells (Toucan Capital,

Cognate Bioservices, Vet-Stem) and has cofounded companies involved in

developing these cells for clinical applications.





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Erratum

The In Vivo Patternof Binding of RAG1 and RAG2to Antigen Receptor LociYanhong Ji, Wolfgang Resch, Elizabeth Corbett, Arito Yamane, Rafael Casellas,* and David G. Schatz**Correspondence: [email protected] (R.C.), [email protected] (D.G.S.)

DOI 10.1016/j.cell.2010.09.020

(Cell 141, 419–431; April 30, 2010)

In the above article, Table S1 contained mistakes concerning the location of PCR products relative to the relevant gene segments for

eight of the PCR assays used in the ChIP analyses. For Vk24hf, VkX24, and Vk12–38, the PCR product was situated on the nonamer

side of the recombination signal sequence (RSS) rather than on the heptamer side as was stated in Table S1. For Jk4, the PCR

product was 172 bp downstream of the RSS rather than 12 bp; for Jh2 the PCR product was 40 bp from the RSS rather than spanning

the RSS; for TRBJ2-1, the PCR product was 4 bp from the RSS rather than 69 bp; whereas for DQ52, the PCR product spanned the

gene segment rather than residing 200 bp away from it. These were clerical errors made either during compilation of Table S1 or

during the process of calculating the distance between the PCR primers and RSSs. In the case of the Jk4 assay, the PCR product

was inadvertently located closer to Jk5 than to Jk4, and as a result, this assay should detect RAG binding to Jk5 and Jk4. This is very

unlikely to influence any aspect of our conclusions because similar RAG-binding results were obtained with a PCR assay located

upstream of Jk4 (85 bp 50 of the nonamer of the Jk4 RSS [not shown]). Finally, due to misidentification of the DFL16.1 gene segment

in GenBank AJ851868, the DFL16.1 PCR product was located 1032 bp 30 of DFL16.1 rather than spanning the gene segment, as was

intended. If the RAG proteins bound to DFL16.1, this mistake could have resulted in a failure to detect such binding. However, our

recent ChIP-sequence analyses of primary bone marrow B lineage cells demonstrate robust RAG1 binding to Jh gene segments but

no detectable binding at DFL16.1 (Teng et al., unpublished), supporting the conclusion in the paper that RAG1 does not bind to

DFL16.1.

We believe that the errors in Table S1 do not in any way alter the conclusions of our paper, and we apologize for any inconvenience

that these mistakes may have caused. The corrected Table S1 is now available online with the Supplemental Information.

170 Cell 143, 170, October 1, 2010 ª2010 Elsevier Inc.

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172 Cell 143, October 1, 2010 ©2010 Elsevier Inc. DOI 10.1016/j.cell.2010.09.032

SnapShot: NR CoregulatorsNeil J. McKenna and Bert W. O’MalleyBaylor College of Medicine, Houston, TX 77030, USA

Coregulator/Family* Symbols

Interactions (Nuclear Receptors) Functions

Disease Links

Interactions (Coregulators) Interactions (Others)

Steroid receptor coactivators*

SRC-1/NCOA1; SRC-2/NCOA2; (GRIP1, TIF2); SRC-3/NCOA3; (AIB1, ACTR, TRAM-1, RAC3)

SRC-1 AR, COUP-TFI, CAR, ERα, ERβ, ERRg, FXRα, GR, HNF4α, PPARα, PPARg, PXR, PR, RORβ, RARα, RARβ, RXRα, RXRβ, SF-1, TRα, TRβ, EAR

Coactivators for the NR superfamily and other transcription factors; roles in reproductive development and metabolism. Domains: PAS/bHLH, acetyltransferase

Up-regulated in cancer

SRC-1 ASC-1, ANCO-1, BCL-3, BAF57. BRG1, CBP, CyclinD1, p300, GRIP1, NCoR, PGC-1, p72, PRMT1, PRMT2, 14-3-3 η, P/CAF

SRC-1 AHR, ARNT, FOS, HIF1A, FOXA2, JUN, CIITA, NFKB1, SRF, STAT6, TEAD1, TITF1, YWHAQ

SRC-2 AR, ERα, ERRβ, LRH1, GR, HNF4α, PPARg, RORα. RARα, RXRα, SF1, TRβ, VDR

SRC-2 ANCO-1, BAF57, BRCA1, CARM1, p300, GMEB-1, PRMT1, SRC-1, 14-3-3η

SRC-2 AHR, ARNT, CCNT1, MAGEA11, TITF1, PPFIA1, SRCAP, tat

SRC-3 AR, COUP-TFI, ERα, ERβ, ERR-β, LRH-1, GR, PPARα, PXR, RARα, RXRα, RXRβ, TRβ, VDR, Nur77

SRC-3 ANCO-1, BAF57, BRCA1, CBP, CARM1, CyclinD1, p300, MMS19, P/CAF, PRMT1, PIAS1, TBP, 14-3-3η

SRC-3 BMP6, BMP7, E2F1, ERBB2, ETS1, ETS2, ETV1, GSK3B, IKBKB, MYC, NPAS2, EBAG9, YWHAQ, SUFU

Peroxisome proliferator receptor g coactivator 1

PGC-1/PPARGC1A

CAR, ERα, ERRg, FXRα, GR, HNF4α, LXRα, PPARα, PPARg, RXRα, TRβ

Critical roles in fat and carbohydrate metabolism and energy homeostasis. Domain: RNP-1

Metabolic, cardiovascular

FKHR, Sirt1, SRC-1, TRAP230, TRAP220, DRIP150

HCFC1, NRF1, USF2, SURB7, TRFP, G6PC, PCK1

Nuclear receptor corepressor

N-CoR/NCOR1 AR, ERα, GCNF, GR, PPARα, PPARg, PPARd, RARα, REVERBα, REVERBβ

Corepressor for the NR superfamily and other transcription factors; recruits histone deacetylases. Domain: SANT


GPS2, HDAC3, HDAC4, TBLR1, PTα, Sin3A, SHARP, SMRT, SAP30, Sirt1, SF3A1, TBL1, TIF1β

BCL6, RUNX1T1, CBFA2T3, CCND2, CDKN2A, CHD1, CLK1, DACH1, ERBB2, ETS1, ETS2, HD, HSPA4, CD82, KIF11, MECP2, MYOD1, NFKB1, PDCD2, PHB, PML, CCL3, SKI, SMARCB1, SMARCC1, SMARCC2, CORO2A, ZBTB16, RDBP, FBAP4, TRIM33

SMRT/HDAC1-associated repressor protein

SHARP/MINT PPARd, RARα Steroid-inducible corepressor; recruits histone deacetylases. Domains: RNP-1, SPOC


CyclinE1, HDAC1, HDAC2. MTA2, NCoR, RBBP4, SMRT, SRA

DLX5, RBPSUH, MSX2, PAK1, SOX9, Antp, Ras85D, E2f, MBD3, Hivep1

Thyroid receptor- associated protein 220

TRAP220/PPARBP; (DRIP205, MED1, CRSP200)

AR, CAR, ERα, ERβ, GR, HNF4α, PPARα, PPARg, RORα, RARα, RXRα, TRα, TRβ, VDR, Nur77

NR coactivator and member of MEDIATOR transcriptional complex. Domains: Phosphopantetheine attachment site, GHMP kinase

Neurological; cancer; metabolic

BRCA1, PGC-1, PIMT, 14-3-3η

CDKN1A, CTSD, TFF1, CRSP7, YWHAQ, Gata1, Gata2, Gata3, Gata4, Gata6, MED9, IXL, MED28, MED25, MED10, MED19

Activating signal cointegrator-2

ASC-2/NCOA6; (NRC, PRIP, RAP250, TRBP, AIB3)

AR, CAR, CARβ, ERα, ERβ, GR, LXRβ, PPARα, PPARg, RARα, RXRα, TRα, TRβ

Coactivator for NR superfamily and other transcription factors.

Mutated in cancers

Ku80, BCL-3, CBP, CoAA, CAPER, p300 NIF-1, PIMT, PARP-1, PRMT2

ASCL2, CD40, CEBPA, ATF2, CXADR, E2F1, FGR, FOS, XRCC6, GTF2A1, HSF1, JUN, NFKB1, NUMA1, RBBP5, SRC, SRF, TOP1, TUBA1, HBXIP, SRF, ASCC1, MLL3, TUBB

Silencing mediator of retinoid and thyroid receptors

SMRT/NCOR2 AR, ERα, GCNF, GR, PPARα, PPARg, RARα, TRβ, Nur77

Corepressor for NR superfamily and others; recruits histone deacetylases. Domain: SANT

Cancer, metabolic, bone

HDAC1, HDAC2, HDAC3, HDAC4, NCoR, Sin3A, SKIP, SHARP, SAP30, Sirt1, TBL1

BIRC3, BCL6, RUNX1T1, CCND2, CDKN2A, CHUK, FOS, RBPSUH, IL8, MYBL2, MYOD1, NFKB1, NFKBIA, PML

cAMP response element-binding protein (CREB) binding protein

CBP/CREBBP AR, ERα, GR, HNF4α Coactivator for NR superfamily and other transcription factors; closely related to p300. Domains: Bromodomain, KIX, PHD-type zinc finger

Neurological ASC-1, ASC-2, AIB1, BCL-3, BRG1, BRCA1, CtBP1, CITED1, CDC25B, Cyclin D1, Daxx, FKHR, JDP-2, MGMT, PIMT, p68, PELP1, PROX1, PIAS3, PT-α, RBBP4, RHA,

CDKN1A, CREB1, ATF2, CSK, E2F1, E2F3, FOS, GATA1, HOXB7, IRF3, JUN, SMAD1, MYB, MYOD1, NFATC2, SRF, and others

Receptor-interacting protein 140

RIP140/NRIP1 DAX1, ERα, GR, LXRα, PPARα, PPARg, RARα, RXRα, RXRβ, SF-1, TR2

Bimodal coregulator, shown to function as a coactivator or corepressor; roles in metabolism.

Reproductive CtBP1, CtBP2, HDAC1, HDAC3, 14-3-3η, P/CAF

AHR, FOXA1, JUN, POLR2A, MAP3K7, TRAF2, HDAC9, HDAC5, YWHAQ, LDOC1, TEX11, CEP70

Adenovirus E1A-associated 300kDa protein

p300/EP300 ERα, PPARα, PPARg, PPARd, RORα, RARβ, TRα, Nur77

Coactivator for NR superfamily and other transcription factors; closely related to CBP. Domains: Bromodomain, KIX, TAZ and PHD-type zinc fingers

Cancer, neurological

ASC-1, ASC-2, ADA3, AIB1, BCL-3, BRCA1, CtBP1, CITED1, CoAA, CARM1, Cyclin D1, p300, GPS2, GRIP1, JDP-2, MGMT, PIMT, PC2, PC4, p68, PELP1, PROX1, PIAS3, PT-α, SMAD3, SAF-A, STAT3, SRC-1, SYT,

Numerous

Coactivator-associated arginine methyltransferase1

CARM1/CARM1; (PRMT4)

NA Arginine methylase; required for pluripotency of stem cells. Domain: Methyltransferase


SRC-1, SRC-2, SRC-3 ELAV1, PABPN1, SRCAP

Steroid receptor RNA activator

SRA/SRA1 ERα, GR, MR, PR, AR RNA transcript and an AF-1-specific transcriptional coactivator.


PUS1, SHARP, SRC-1, SLIRP NA

Transcription intermediary factor-1α

TIF1α/TRIM24; (CCCP)

AR, COUP-TFII, ERα, ERβ, GR, HNF4α, MR, PR, RARα, RXRα, VDR

Associates with chromatin.Domains: RBCC, bromodomain, PHD finger


TIF1α, TIF1β GTF2E1, HSPA1A, PML, TAF7, TAF11, ZNF10, CBX1, CBX3, CBX5, TRIM33

CAPER CAPER/RBM39 ERα, ERβ, PR Processes NR-regulated genes. Domains: RNP-1, CC1

NA ASC-2 JUN, HSP70

Metastasis- associated 1

MTA1/MTA1 ERα Corepressor; part of the NURD histone deacetylase complex. Domains: ELM2, SANT, BAH


CDK7, HDAC1, HDAC2, MAT1, MTA2, MICoA, NRIF3, RBBP4, RBBP7, Sin3A, p53

ATR, CCNH, CHD4, FYN, GRB2, NCK1, MBD3L1

Coactivator activator

CoAA/RBM14 NA Coactivator with roles in RNA splicing. Domains RNP-1


Ku80, ASC-2, p300, PARP-1 TARBP2

See online version for legend and references.

OMalley_3_MD.indd 1 9/23/10 1:16 PM

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