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EXPLORING THE ROLES OF LYSINE DEACETYLASES IN SACCHAROMYCES CEREVISIAE
by
Supipi Wasana Kumari Kaluarachchi
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Molecular Genetics
University of Toronto
© Copyright by Supipi Kaluarachchi 2011
ii
Exploring the roles of lysine deacetylases in Saccharomyces cerevisiae
Supipi Wasana Kumari Kaluarachchi
Doctor of Philosophy
Molecular Genetics
University of Toronto
2011
Abstract
This work investigates two distinct roles of lysine deacetylases (KDACs) in the budding yeast
Saccharomyces cerevisiae. The first part focused on the classical, well characterized role of
KDACs as transcriptional regulators and deciphering their role in G1 transcription. I show that
two yeast KDACs, Rpd3 and Hos3 are recruited to G1 promoters through their interactions with
the negative regulator Whi5 and that these KDACs are necessary for proper Whi5-mediated
repression. The second part examines a newly discovered role for KDACs extending their role
beyond the chromatin as modifiers of proteins other than the histones. I present here the first
systematic approach that comprehensively examines these non-histone targets of KDACs in vivo.
I identified 73 non-histone proteins acetylated in vivo involved in diverse cellular processes.
Swi4, a component of the G1 transcription factor SBF, was identified in the Rpd3 screen and I
show that the interaction between Swi4 and its heterodimeric partner Swi6 was regulated by
acetylation. My findings significantly expand the scope of the yeast acetylome and demonstrate
the utility of systematic functional genomic screens to explore enzymatic pathways.
iii
Acknowledgments
I would like to extend my greatest appreciation and gratitude to my supervisor, Brenda Andrews,
for her support, guidance and encouragement throughout my graduate career. Thank you for
challenging me to grow and for being a true mentor. I thank all the members in the Andrews lab,
both past and present, for making it a fun and friendly environment. I especially thank Helena
Friesen for her insightful discussions and support over the years. I would also like to thank my
supervisory committee members, Lori Frappier, Marc Meneghini and Igor Stagljar, for their
constructive comments and criticisms.
Finally my deepest gratitude goes to my family, Mom and Dad for their love, guidance and belief
throughout my life and to my little sister Harini, for always keeping the competition alive. I
cannot imagine having completed this degree without the encouragement and support of my
husband and best friend Simon. Thank you for tolerating my impatience and my many, many ups
and downs over the past years.
I dedicate this thesis to my Mother whose courage, determination and perseverance has always
been my inspiration.
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Table of Contents
Abstract ........................................................................................................................................... ii
Acknowledgments .......................................................................................................................... iii
Table of Contents ........................................................................................................................... iv
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
Abbreviations ................................................................................................................................. xi
List of Appendices ....................................................................................................................... xiv
Chapter 1 Introduction .................................................................................................................... 1
1.1 The Cell Cycle ...................................................................................................................... 2
1.1.1 Cyclin-dependent kinases (CDKs) .......................................................................... 3
1.1.2 Regulating the cell cycle ......................................................................................... 4
1.1.3 G1 regulatory pathway ............................................................................................ 5
1.2 Transcription, chromatin modifications and acetylation .................................................... 7
1.2.1 Chromatin modifications and modifiers ................................................................. 7
1.3 Acetylation .......................................................................................................................... 9
1.3.1 Acetyltransferases ................................................................................................. 10
1.3.2 Deacetylases .......................................................................................................... 13
1.4 Acetylation and disease ..................................................................................................... 20
1.4.1 KAT and KDAC inhibitors ................................................................................... 21
1.5 Acetylation and non-histone targets .................................................................................. 24
1.5.1 Lysine acetylomes ................................................................................................. 27
1.5.2 Non-histone targets in S. cerevisiae ...................................................................... 28
1.6 Mapping the lysine acetylome - tools and techniques ...................................................... 32
1.6.1 In vitro KAT and KDAC assays ........................................................................... 32
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1.6.2 Protein microarrays ............................................................................................... 36
1.6.3 Mass spectrometry ................................................................................................ 36
1.6.4 Functional Genomics ............................................................................................ 41
1.7 Summary and significance ................................................................................................ 49
Chapter 2 Dual Regulation by Pairs of Cyclin-dependent Protein Kinases and Histone
Deacetylases Controls G1 Transcription in Budding Yeast ..................................................... 50
2 Abstract .................................................................................................................................... 51
2.1 Introduction ....................................................................................................................... 51
2.2 Experimental Procedures .................................................................................................. 53
2.2.1 Yeast strains, growth conditions and plasmids ..................................................... 53
2.2.2 Kinase assays ........................................................................................................ 59
2.2.3 Quantitative β-galactosidase assays ...................................................................... 59
2.2.4 Whi5 dissociation with SBF complex in vitro ...................................................... 59
2.2.5 Liquid Growth Assays .......................................................................................... 60
2.2.6 Whi5-GFP Localization ........................................................................................ 60
2.2.7 Chromatin immunoprecipitation ........................................................................... 60
2.2.8 Other materials and methods ................................................................................ 61
2.3 Results ............................................................................................................................... 61
2.3.1 A Synthetic Dosage Lethality screen identifies Whi5, as a putative substrate
for the cyclin-dependent kinase, Pho85 ................................................................ 61
2.3.2 Whi5 is a substrate for Pcl9-Pho85 phosphorylation. ........................................... 63
2.3.3 Pcl9-Pho85 regulates Whi5 function via phosphorylation. .................................. 68
2.3.4 CDC28 and PHO85 function in parallel pathways to regulate Whi5 function ..... 71
2.3.5 Pho85 does not regulate Whi5 localization or its interactions with G1-specific
transcription complexes ........................................................................................ 76
2.3.6 Mechanism for Whi5-mediated transcriptional repression by Pho85 ................... 78
2.4 Discussion ......................................................................................................................... 85
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Chapter 3 Exploring the global effects of Class I and II lysine deacetylases using functional
genomics .................................................................................................................................. 91
3 Abstract .................................................................................................................................... 92
3.1 Introduction ....................................................................................................................... 93
3.2 Experimental Procedures .................................................................................................. 94
3.2.1 Yeast Strains, Growth Conditions and Plasmids .................................................. 94
3.2.2 SDL Screens and confirmations ............................................................................ 96
3.2.3 Cell biology ........................................................................................................... 96
3.2.4 Pull-down of GST proteins and Acetylation Western blots .................................. 96
3.2.5 Mass spectrometry ................................................................................................ 97
3.2.6 Cell cycle synchronization, quantitative PCR and expression analysis ................ 97
3.2.7 Chromatin Immunoprecipitations ......................................................................... 97
3.3 Results ............................................................................................................................... 98
3.3.1 Systematic gene over-expression identifies 458 SDL interactions for Class I
and II KDACs ....................................................................................................... 98
3.3.2 Over-expression phenotypes reveal interactions that are unique from deletion
phenotypes .......................................................................................................... 105
3.3.3 Using SDL to identify previously uncharacterized functions for the HDA
complex ............................................................................................................... 109
3.3.4 The SDL dataset is enriched for in vivo acetylated proteins ............................... 115
3.3.5 Swi4 is regulated by acetylation ......................................................................... 117
3.4 Discussion ....................................................................................................................... 123
3.4.1 Exploration of the yeast lysine acetylation using genetic interactions ............... 123
3.4.2 Novel functions for the HDA complex ............................................................... 124
3.4.3 Non-histone proteins regulated by acetylation ................................................... 125
3.4.4 G1-transcription is controlled at multiple levels ................................................. 126
Chapter 4 Summary and Future Directions ................................................................................ 129
4 Summary and Future Directions ............................................................................................ 130
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4.1 Summary ......................................................................................................................... 130
4.2 Future Directions ............................................................................................................ 131
4.2.1 Barcode SDL ....................................................................................................... 131
4.2.2 Inhibitor Screens ................................................................................................. 133
4.2.3 Systematic cell biological screens in acetyltransferase/deacetylase mutants ..... 133
4.3 Overall significance ........................................................................................................ 136
References or Bibliography ........................................................................................................ 137
Appendices .................................................................................................................................. 158
viii
List of Tables
Table 1-1 Summary of lysine deacetylases in yeast and mammals and known transcriptional
roles for these enzymes
Table 1-2 Yeast and mammalian KDACs
Table 1-3 Diseases targeted by KATis and KDACis
Table 1-4 Non-histone proteins regulated by acetylation in S. cerevisiae
Table 2-1 Strains used in this Chapter
Table 2-2 Plasmids used in this Chapter
Table 3-1 Strains used in this chapter
Table 3-2 Gene enrichments for kdac∆ SDL screens with fold enrichment over the genome and
the associated significance values
Table 3-3 Genes identified in the SDL screens that are also up-regulated at the level of
transcription in the absence of RPD3 and HDA1. Proteins that are components of known protein
complexes are also shown
Table 3-4 Enrichments within the HDA complex SDL interactions for biological process
classified using biological processes annotated by Costanzo et al (2010).
Table 3-5 Peroxisome genes that are toxic when over-expressed in the absence of individual
HDA complex components
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List of Figures
Figure 1-1 Effects of acetylation of a variety of proteins…………………….…………….page 26
Figure 1-2 In vitro KAT and KDAC assays……………….………………………...……..page 33
Figure 1-3 Fluorescent KAT and KDAC assays …………….………………...…………..page 35
Figure 1-4 A schematic of HPLC/MS/MS experiment…...………………………………..page 38
Figure 1-5 Experimental approach to SILAC labelling………..…………………………..page 40
Figure 1-6 Negative genetic interactions………………….………………………………..page 43
Figure 1-7 Synthetic dosage lethality…………………………………………..…………..page 45
Figure 1-8 Mechanisms of synthetic dosage lethality ……………………………………..page 46
Figure 1-9 Synthetic dosage lethality screens using synthetic genetic array analysis……..page 48
Figure 2-1 WHI5 over-expression is toxic to strains compromised for Pho85 CDK
activity……………………………………………………………………………………...page 62
Figure 2-2 Whi5 is a substrate for Pcl9-Pho85 CDK-dependent phosphorylation….……..page 65
Figure 2-3 Pcl9 localizes to G1-specific promoters in a cell cycle-dependent manner.…...page 67
Figure 2-4 PHO85 affects growth and cell size defects associated with cln3∆…...…...…..page 69
Figure 2-5 Expression levels of epitope-tagged Whi5 and Pho85 cyclins…………......…..page 70
Figure 2-6 PHO85 regulates G1 transcription via WHI5.………………………………….page 73
Figure 2-7 Whi5-mediated transcriptional repression is antagonized by PHO85 and
CDC28…………………………………………………………………………….………..page 75
Figure 2-8 Pho85 does not affect known Whi5 regulatory mechanisms…………….……..page 77
Figure 2-9 Whi5 function is dependent on KDAC activity………………………….……..page 79
Figure 2-10 WHI5 toxicity is dependent on HOS3 and RPD3……………………………..page 81
Figure 2-11 Repression of gene expression by Whi5 is dependent on HOS3 and RPD3.....page 83
Figure 2-12 CDK activity antagonizes Whi5-KDAC interactions…………………..……..page 84
Figure 2-13 Model for CDK-dependent regulation of Whi5 activity and G1/S-specific
transcription………………………………………………………………………….……..page 87
Figure 3-1 Genetic interaction identified for Class I and II KDACs. ……………………..page 99
x
Figure 3-2 Enrichments within the rpd3∆ SDL interactions for biological process……...page 102
Figure 3-3 GO enrichments for two of the genomewide SDL screens.…………….……..page104
Figure 3-4 A network showing the correlation profiles between SDL data and digenic genetic
interaction data……………………………………………………….…………….……..page 108
Figure 3-5 SDL interactions for the HDA complex components……………….….……..page 110
Figure 3-6 Peroxisome biogenesis in the absence of HDA complex components.…...…..page 114
Figure 3-7 SDL identified in vivo acetylated proteins………………..…………….……..page 116
Figure 3-8 Swi4 is acetylated in vivo………...……………………………...………….……..page 118
Figure 3-9 Effects of Swi4 point mutations….…………….……………………………..page 120
Figure 3-10 Effect of acetylation on Swi4-Swi6 protein-protein interaction……………..page 122
Figure 3-11 Model for acetylation dependent regulation of Swi4 and transcriptional induction at
G1 …………….……………………………………………………………………...…..page 127
Figure 4-1 Strategy for condition-specific SDL screens in KDAC/KAT mutants in pooled
cultures……………………………………………………………………………..……..page 132
Figure 4-2 High-content screening pipeline………………………….…………….……..page 135
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Abbreviations
α……………………………..alpha
β……………………………..beta
ε……………………………..epsilon
∆……………………………..gene deletion
µg……………………………micrograms
µM…………………………..micromolar
Acetyl CoA………………....acetyl coenzyme-A
AcK…………………………acetyl lysine
AML………………………...acute myeloid leukemia
ATP………………………….adenosine triphosphate
CBP………………………….CREB-binding protein
CDK…………………………cyclin dependent kinase
ChIP…………………………chromatin immunoprecipitation
CTCL……………………….. cutaneous T-cell lymphoma
DNA…………………………deoxyribonucleic acid
DSB………………………….double stranded break
ERC………………………….extrachromosomal rDNA circle
ESI…………………………...electrospray ionization
FACS…………………………fluorescence associated cell sorting
xii
GST………………………….glutathione sepharose
H2A………………………….histone H2A
H2B………………………….histone H2B
H3……………………………histone H3
H4……………………………histone H4
HAST…………………..…... Hda1-affected subtelomeric
IGR…………………………..intergenic regions
K……………………………..lysine
KAT…………………………lysine acetyltransferase
KATi………………………...lysine acetyltransferase inhibitor
KDAC……………………….lysine deacetylase
KDACi………………………lysine deacetylase inhibitor
LC…………………………....liquid chromatography
MALDI…….……………….. matrix-assisted laser/desorption ionization
MBF…………………………MluI binding factor
MS…………………………..mass spectrometry
NAD…………………………nicotinamide adenine dinucleotime
ONPG……………………….. ortho-Nitrophenyl-β-galactoside
PHD………………………….plant homeodomain
PBS…………………………..phosphate buffered saline
xiii
PCR………………………….polymerase chain reaction
PTM………………………….post translational modification
R……………………………..arginine
RNA………………………....ribonucleic acid
RNAPII……………………...RNA polymerase II
RSTS…………………...…... Rubinstein-Taybi syndrome
S……………………………..serine
SBF…………………………. Swi4,6 cell cycle box binding factor
SDL…………………………..synthetic dosage lethal
SDS-PAGE…………………...sodium dodecyl sulphate poly acrylamide gel electrophoresis
SGA…………………………..synthetic genetic array
SILAC………………………..stable isotope labelling with amino acids in cell culture
SIR…………………………...silence information regulator
SL…………………………….synthetic lethal
SS…………………………….synthetic sick
TAP…………………………..tandem affinity purification
TF……………………………transcription factor
VPA………………………….valproic acid
xiv
List of Appendices
Appendix 1: Data from Chapter 3
Table 1 SDL interactions for the 5 Class I and II KDAC screens
Table 2 SDL interactions for the HDA complex components
Appendix 2:
Table 1 Proteins that changed in localization in the absence of RPD3
Table 2 Proteins that changed in abundance in the absence of RPD3
1
Chapter 1 Introduction
2
The traditional model of gene regulation focused on the idea that the DNA sequence itself
primarily contributed to alterations in gene expression. Since the discovery of a correlation
between histone acetylation and transcriptional activation more than four decades ago, it has
become clear that epigenetic modifications also play an important role in gene regulation
(Allfrey et al., 1964). A large number of proteins that acetylate, deacetylate, or otherwise
modify histones have been identified, adding to our understanding of the link between chromatin
modification and transcriptional output (Kurdistani and Grunstein, 2003; Vignali et al., 2000).
These discoveries have profound medical implications since altered gene expression can result in
disease states such as cancer (Huang, 2006; Shen et al., 2003; Somech et al., 2004). One of the
goals of my thesis research was to investigate the molecular mechanisms that control gene
expression in Saccharomyces cerevisiae, with a focus on the interplay between chromatin
remodeling enzymes and cell cycle-regulated transcription. The second part of my thesis work
focused on one group of chromatin remodeling enzymes, lysine deacetylases, and applying
functional genomic tools to identify novel targets of these enzymes.
S. cerevisiae is an excellent model system to evaluate global effects of chromatin modifications
since the availability of powerful genetic and functional genomic tools allow large-scale
systematic analyses. As well, many of the biological processes and pathways and the enzymes
that regulate these pathways such as the kinases, lysine acetyltransferases and deacetylases are
conserved from yeast to humans (Rubenstein and Schmidt, 2007; Yang and Seto, 2008). In this
Chapter, I will briefly introduce cell cycle regulation and cell-cycle dependent transcription in S.
cerevisiae with a focus on the role of chromatin-modifying enzymes. I will then discuss the
post-transcriptional role of lysine acetyltransferases (KATs) and deacetylases (KDACs), for
which little information is available, followed by applications and discoveries pertinent to the
identification of non-histone substrates of these enzymes.
3
1.1 The Cell Cycle
The mitotic cell cycle is an ordered series of events ultimately leading to the duplication of a cell
to generate two cells with identical DNA content (Mitchison, 1971; Morgan, 2006). In the case
of the budding yeast, cell division is asymmetrical and produces a large mother and a smaller
daughter cell that are genetically identical. Commitment to another round of division occurs in
late G1 (Gap phase 1) at a point called START, or the restriction point in mammalian cells, when
cells reach a certain size and achieve the required protein synthetic capacity (Pringle, 1981).
DNA synthesis and chromosome replication take place in the S phase of the cell cycle followed
by another gap phase (G2). Chromosome separation and cell division occurs during the mitotic
(M) phase of the cycle, after which each progeny cell reenters G1 phase (Kaizu et al., 2010).
Inputs such as cell size, nutrient availability, transcription, protein production and degradation
underlie the cell cycle (Jorgensen and Tyers, 2004). The molecular machinery and the signaling
cascades regulating crucial events of the cell cycle are highly conserved in eukaryotes.
1.1.1 Cyclin-dependent kinases (CDKs)
Progression through the cell cycle is primarily orchestrated by the cyclins, the regulatory
components of the cyclin dependent kinases (CDKs), where cyclin binding activates the CDKs
(Miller and Cross, 2001). There are six CDKs in S. cerevisiae, Cdc28, Pho85, Kin28,
Srb10/Cdk8, Sgv1/Bur1 and Ctk1 (Huang et al., 2007; Liu and Kipreos, 2000). Four of these,
Kin28, Srb10/CDK8, Sgv1/Bur1 and Ctk1, have a single, dedicated cyclin, and regulate mRNA
synthesis by phosphorylating the carboxyl-terminal domain of RNA Polymerase II. In contrast,
both Cdc28 and Pho85 have multiple cyclins and have roles in promoting cell cycle progression
(Liu and Kipreos, 2000). Cdc28 (Cdk1 in other eukaryotes), which is the main cell cycle CDK,
associates with 9 cyclins, each of which is specific to a cell cycle stage. The G1 cyclins Cln1,
Cln2 and Cln3, control early cell cycle progression by initiating bud emergence, spindle pole
duplication and the activation of subsequently required cyclins. Two B-type cyclins, Clb5 and
Clb6, ensure proper DNA replication and progression through S phase, while the other four B-
type cyclins, Clb1-4, are required for mitotic events that include spindle morphogenesis (Liu and
Kipreos, 2000).
4
The functional homologue of Cdk5, Pho85, associates with 10 Pho85 cyclins known as Pcls.
Like Cdc28, Pho85 has a clear regulatory role in regulating G1 progression, but also has many
non-mitotic roles in regulating cell polarity via the actin cytoskeleton, in gene expression,
phosphate and glycogen metabolism and environmental signaling(Carroll and O'Shea, 2002).
This division of labor is highlighted by the diversity of the Pcls associated with Pho85, which are
divided into two subfamilies based on sequence similarities within the cyclin-box region
(Measday et al., 1997). The Pcl1, 2 subfamily includes Pcl1, Pcl2, Pcl9, Clg1 and Pcl5 and the
Pho80 subfamily consists of Pho80, Pcl6, Pcl7, Pcl8 and Pcl10. Pcl1, Pcl2 and Pcl9 have roles
in the cell cycle (Measday et al., 1997) whereas the remaining Pcls play prominent roles in
regulating metabolism and sensing environmental changes (Carroll and O'Shea, 2002). Tight
control of CDK activity is achieved through several mechanisms including binding by activating
cyclins, binding by inhibitory cyclin-dependent kinase inhibitors and inhibitory and/or activating
phosphorylation events (Liu and Kipreos, 2000).
1.1.2 Regulating the cell cycle
Progression through the cell cycle in eukaryotes is characterized by and is dependent upon
successive waves of gene expression (Wittenberg and Reed, 2005). Two gene expression
microarrays were performed in the late 1990‟s to discover the complement of genes whose
transcripts are cell cycle regulated (Cho et al., 1998; Spellman et al., 1998). Samples were taken
from fixed time points of the cell cycle and RNA from these samples was analyzed using
expression microarrays to reveal that ~10% of the yeast genome (~400-800 genes) is cell cycle
regulated. Recently, cell cycle regulated transcripts were reexamined and the careful analysis of
additional time points revealed that over 1000 yeast genes are significantly cell cycle regulated
(Pramila et al., 2006). Similar experiments in human cells also uncovered more than 1000 genes
that are cell cycle regulated (Cho et al., 2001; Whitfield et al., 2002). About 26% of these
human genes have orthologues in yeast that are also periodically expressed, and the overlapping
genes are involved in basic processes such as DNA replication, repair, metabolism and mitosis,
highlighting the conservation between these systems (Whitfield et al., 2002). Genes that are
specifically cell-cycle regulated in humans or yeast appear to reflect the specific biology of the
system. For example, genes involved in bud emergence and bud growth biological processes not
shared with human cells are periodically regulated in yeast (Spellman et al., 1998), whereas
cytoskeletal proteins and adhesion factors that are needed for changes in cell shape during
5
mitosis, a function not shared with yeast are cell cycle regulated in humans (Whitfield et al.,
2002).
The importance of proper cycle regulation of gene expression was highlighted by the observation
that cell cycle-regulated genes are enriched among genes that caused significant growth defects
when over-expressed (Sopko et al., 2006b). Also, many cancers show aberrant expression of cell
cycle regulated genes. The G1-regulatory pathway provides one of the best characterized
examples of how the abnormal expression of cell cycle regulators gives rise to cancer phenotypes
such as uncontrolled proliferation, abnormal cell morphologies and developmental defects
(Dyson, 1998; Kaizu et al., 2010). Below, I review key conserved features of the G1 regulatory
circuitry in yeast and mammalian cells.
1.1.3 G1 regulatory pathway
As noted earlier, START signifies an irreversible commitment to a new round of cell division
that occurs toward the end of G1 phase and is characterized by the induction of a transcriptional
program that involves over 200 genes (Bahler, 2005; Wittenberg and Reed, 2005). START-
dependent transcription of genes, such as those encoding the G1 (CLN1, CLN2, PCL1 and PCL2)
and B-type cyclins (CLB5 and CLB6), is regulated by two heterodimeric transcription factors
SBF (Swi4,6 cell cycle box binding factor) and MBF (MluI binding factor). Activation of gene
expression by these transcription factors (TFs) initiates cell cycle events, including budding,
DNA synthesis and spindle pole body duplication.
SBF and MBF share a common regulatory subunit, Swi6, which is tethered to DNA through
interactions with its partner proteins, Swi4 and Mbp1, respectively (Wittenberg and Reed, 2005).
Swi4, the DNA binding component of SBF, binds the repeated upstream regulatory sequence
CACGAAA known as SCB (Andrews and Herskowitz, 1989; Andrews and Moore, 1992)
through its N-terminal DNA binding domain (Primig et al., 1992). The DNA binding component
of MBF, Mbp1, recognizes a distinct upstream sequence, ACGCGTNA, known as an MCB.
Swi6 has no DNA binding activity and interacts with both Swi4 and Mbp1, through the
carboxyl-terminal (C-terminal) regions of both proteins (Andrews and Moore, 1992; Moll et al.,
1992; Primig et al., 1992; Sidorova and Breeden, 1993). Due to their role in proper timing of the
cell cycle, the activity of SBF and MBF is controlled at multiple levels. The expression of SWI4
varies throughout the cell cycle with peak expression at the M/G1 boundary but the Whi5
6
repressor prevents SBF/MBF activation until later in G1 phase. A second mode of SBF/MBF
regulation involves changes in the subcellular localization of Swi6 where phosphorylation of
serine-160 of Swi6 leads to cytoplasmic retention during late G1, S and M phase of the cell cycle
(Harrington and Andrews, 1996; Koch et al., 1993; Sidorova and Breeden, 1993).
Although SBF and MBF bind their promoter targets throughout G1, SBF- and MBF-dependent
transcription does not occur until late in G1 phase. This restriction of SBF and MBF activity is
controlled by the repressor Whi5, which binds to the transcription factors early in G1 when
cyclin-dependent kinase activity is low (Costanzo et al., 2004; de Bruin et al., 2004).
Phosphorylation of Whi5 by the CDKs Cln3-Cdc28 and Cln2-Cdc28 promotes both the
dissociation of Whi5 from SBF/MBF and its nuclear export, thus allowing the initiation of G1-
specific transcription (Costanzo et al., 2004; de Bruin et al., 2004).
The Whi5-SBF/MBF transcriptional circuit is analogous to the regulatory pathway in
mammalian cells that features the E2F family of G1 transcription factors and the retinoblastoma
(Rb) tumor suppressor protein. Rb was the first tumor suppressor gene to be identified (Lee et
al., 1987) and its inactivation results in uncontrolled cell proliferation (Horowitz et al., 1990).
E2F, the functional analog of SBF/MBF, regulates G1-specific gene expression required for
passage through the restriction point (Schaefer and Breeden, 2004) and the activity of E2F is
restricted to late G1 phase by Rb. Rb associates with E2F to restrain its activity until late G1, at
which point stepwise phosphorylation of Rb by two CDKs, cyclin D-Cdk4/6 and cyclin E-Cdk2,
causes the dissociation of Rb from E2F (Hatakeyama et al., 1994). This process appears to be
regulated by a positive feedback loop in which phosphorylation of Rb by cyclinE-Cdk2 leads to
further dissociation of Rb from promoters and enhancement of G1-transcription. At the
molecular level, Rb interacts with both E2F and chromatin remodeling complexes such as
KDACs (Brehm et al., 1998; Luo et al., 1998; Magnaghi-Jaulin et al., 1998). Rb appears to
repress transcription through at least three distinct mechanisms: 1) Rb can bind directly to the
activation domain of E2F thereby blocking its activity (Flemington et al., 1993); 2) recruitment
of Rb can block the assembly of the pre-initiation complex, thereby inhibiting the activity of
adjacent transcription factors (Ross et al., 1999); and 3) Rb can recruit remodelers such as
KDAC1 and BRG1 to modify chromatin structure. BRG1 is one of the human Swi/Snf ATPases
that remodel nucleosomes by utilizing ATP to weaken the interactions between DNA and
histones (Brehm et al., 1998; Luo et al., 1998). My thesis work has extended the parallels
7
between regulation of G1 transcription in mammalian systems and yeast. In Chapter 2, I show
that, like Rb, Whi5 mediates repression through interactions with two KDACs, Hos3 and Rpd3
(Huang et al., 2009).
1.2 Transcription, chromatin modifications and acetylation
Until the late 1990‟s, regulation of transcription and chromatin structure were considered to be
largely separate fields of study. Even though the organization of chromatin and the composition
of a nucleosome were well-described (Felsenfeld and McGhee, 1986) and many of the co-
activators of transcriptional initiation were known (Featherstone, 2002), the functional interplay
between transcription and chromatin remained elusive. The study of gene expression was
revolutionized by the discovery of chromatin remodeling enzymes, specifically
acetyltransferases and deacetylases, and the proposal of the „histone code‟ hypothesis, unifying
transcription and DNA structure (Jenuwein and Allis, 2001; Kuo and Allis, 1998). Now it is
recognized that gene expression is regulated at many levels including the accessibility of the
transcription machinery as well as the activity and DNA-binding properties of transcription
factors.
In eukaryotes, transcriptional regulation occurs in the context of nucleosomes, whose position
and reversible covalent modifications modulate the accessibility of DNA to the transcription
machinery (Deckert and Struhl, 2002; Robert et al., 2004). A nucleosome is composed of an
octamer of two each of the four core histones, H2A, H2B, H3, and H4, with 147 base pairs of
DNA wound in two turns around the exterior of the octamer (Felsenfeld and McGhee, 1986).
Transcriptional initiation therefore is a multi-step process that requires the combinatorial effects
of many multi-subunit protein complexes that include transcription factors, chromatin
remodelers and co-activators (Cosma, 2002).
1.2.1 Chromatin modifications and modifiers
Histone tails are subject to an array of post-translational modifications (PTMs) such as
acetylation, methylation, ubiquitylation, sumoylation and phosphorylation. Lysine (K) residues
can be modified by acetylation, methylation and ubiquitylation, but only methylation takes place
at arginine (R) residues and serines (S) are modified by phosphorylation (Berger, 2002). Several
conserved enzymes including acetyltransferases, methyltransferases, ubiquitin ligases and
8
kinases are responsible for these modifications while deacetylases, demethylases,
deubiquitinases and phosphatases are responsible for their removal. According to the histone
code hypothesis, “multiple histone modifications, acting in a combinatorial or sequential fashion
on one or multiple tails, specify unique downstream function” (Strahl and Allis, 2000). Thus
combinations of acetylation, methylation and phosphorylation rather than each modification in
isolation will determine the activation of a gene. One such example from higher eukaryotes is
the combination of histone-4 (H4) K8 acetylation, H3 K14 acetylation, and H3 S10
phosphorylation, which is associated with active transcription, while tri-methylation of H3 K9
and the absence of H3 and H4 acetylation marks correlate with transcriptional repression
(Peterson and Laniel, 2004).
In addition to promoting structural alterations in histones, PTMs also provide favorable binding
surfaces for chromatin associated factors and facilitate their recruitment (Berger, 2002). Several
protein domains interact with specific PTMs in cells: the bromo-domain-containing proteins bind
acetylated lysines (Sanchez and Zhou, 2009), and methyl-lysines are recognized by chromo-
domain-containing proteins and by plant homeodomain (PHD) proteins (Baker et al., 2008;
Bannister et al., 2001). These domains are commonly found in co-activator and repressor
complexes as well as chromatin remodeling complexes and are thought to “read” the histone
code to produce specific biological outcomes (Strahl and Allis, 2000).
ATP-dependent chromatin remodelers are a second group of enzymes that modify chromatin by
facilitating structural changes of nucleosomes (Narlikar et al., 2002). Rather than covalently
modifying histone tails, these complexes rearrange the chromatin by sliding the nucleosomes
along DNA in cis and/or by displacing nucleosomes (octamer transfer) in trans, processes that
requires the hydrolysis of ATP (Armstrong and Emerson, 1998; Vignali et al., 2000). Conserved
remodeling complexes such as RSC and Swi/Snf displace nucleosomes in trans while the ISWI
complex moves nucleosomes in cis. It is postulated that while all three of these complexes are
capable of sliding nucleosomes, when sliding is not possible the Swi/Snf complex is utilized to
displace the nucleosomes (Vignali et al., 2000). Both covalent histone modifying enzymes and
ATP-dependent chromatin remodelers thus play important roles in transcription by facilitating
the structural changes required for recruitment and binding of transcription factors.
9
1.3 Acetylation
The link between acetylation and transcription was first described in 1964 when a correlation
between histone acetylation and RNA synthesis was observed (Allfrey et al., 1964; Allfrey and
Mirsky, 1964). A pioneering chromatin immunoprecipitation experiment performed in the early
1990s demonstrated an association between acetylated histones and transcribed regions of DNA
(Grunstein, 1997). In this study acetylated histones were localized to regions of DNA that are
sensitive to DNase I digestion, a hallmark of transcriptionally active chromatin (Grunstein, 1997;
Hebbes et al., 1992). Two distinct roles were proposed for histone acetylation: [1] to regulate
interactions between DNA and histones and; [2] to influence contact between histone tails and
chromatin proteins that modulated chromatin structure (Brownell et al., 1996). Subsequent
experiments have shown the histone acetylation indeed has both proposed roles (Kuo and Allis,
1998; Reid et al., 2000) and after four decades of continued research, acetylation is now the best
characterized histone PTM (Yang, 2004).
Lysine acetyltransferases (KATs) and lysine deacetylases (KDACs) were the first group of
chromatin remodelers to be identified (Kurdistani and Grunstein, 2003). KATs transfer an
acetate group from acetyl-CoA to the ε-amino (epsilon) group of a lysine in the N-terminal tail of
histones and KDACs are responsible for removing the acetyl moiety by hydrolysis. The action
of KATs neutralizes the positive charges on lysines, reducing the interactions between histone
tails and DNA, resulting in a hyperacetylated open chromatin structure associated with active
transcription. Conversely, KDACs remove these modifications, reintroducing positive charge on
lysines and increasing the interaction between histone tails and DNA. As a consequence,
KDACs produce closed chromatin structures associated with repression. Other cellular
processes that require structural alterations to the nucleosomes, such as DNA repair, replication
and recombination, also utilize KDACs and KATs to facilitate proper nucleosome assembly and
chromatin folding (Shahbazian and Grunstein, 2007). Given the basic biological processes
influenced by histone acetylation, it is perhaps no surprise that the lysine residues on histone tails
that are regulated by reversible acetylation are highly conserved (Kuo and Allis, 1998).
10
1.3.1 Acetyltransferases
Lysine acetyltransferases (previously known as histone acetyltransferases or HATs) have been
divided into two broad classes, according to their intracellular localization and substrate
specificity. A-type KATs (KAT A) are nuclear and can modify all four nucleosomal histones at
distinct sites. Cytoplasmic B-type KATs (KAT B) target only newly synthesized free histones to
acetylate lysines that are required for proper histone deposition (Brownell et al., 1996). Several
transcriptional co-regulators possess intrinsic acetyltransferase activity and many of these are
conserved from yeast to humans (Marmorstein and Roth, 2001). Gcn5, first identified in the
organism Tetrahymena thermophila (Brownell et al., 1996) is an A-type KAT that is functionally
conserved with homologues in yeast (Georgakopoulos and Thireos, 1992), Drosophila (Smith et
al., 1998), mouse (Xu et al., 1998) and humans (Candau et al., 1996). The Saccharomyces
cerevisiae genome encodes 12 lysine acetyltransferases, many of which are conserved in higher
eukaryotes (Table 1-1).
11
Table 1-1 Summary of lysine deacetylases in yeast and mammals and known transcriptional
roles for these enzymes
Mammalian
KATs
Yeast KAT
complexes
Known
transcription-
related function
Known native
KAT complex
Histones
acetylated
by
complex
GNAT
superfamily
Hat1 Hat1 Hat1 None (histone
deposition related) Yeast HAT-B H4
Gcn5/PCAF GCN5L Gcn5 Coactivator
Yeast ADA,
SAGA; human
GCN5,
STAGA, TFTC
H3, H2B
PCAF
Coactivator Human PCAF H3
Elp3 Elp3 Elp3 Elongation Elongator H3
Hpa2
Hpa2 -3 Unknown
MYST family
MYST TIP60 Esa1 p53 Tip60 H4, H2A
MOF Sas2
H4
NuA3 H3
HBO1
Cell cycle NuA4 H2A, H4
MOZ/ MORF Sas3 Leukemogenesis
H3
p300/CBP CBP
Global coactivator
p300
HBO1
HBO, ORC H3, H4
Nuclear
receptor
coactivators
p160 SRC-1 , ACTR
12
Basal
transcriptional
factors
Nut1
Nut1
Mediator H3>>H4
TFIIB TFIIB
TAFII250
TFIID
Other
CIITA CIITA
ATF2 ATF2
CDY CDY , CDYL
Eco1 Eco1 Eco1
ARD1 ARD1
Rtt109
H3K56
13
Many KATs function as multi-subunit complexes and show preference for specific lysine
residues on histone tails. The diversity of KAT complexes reflects the multiple steps of
transcription in which they participate, including initiation, promoter clearance and elongation.
Although much is known about KATs structurally and functionally, the mechanistic details of
how acetylation leads to transcriptional activation still remain a mystery.
1.3.2 Deacetylases
Lysine deacetylases (formerly known as histone deacetylases or KDACs) are grouped into four
classes on the basis of sequence similarity. Yeast contains 10 KDACs that belong to three of
these classes: Class I KDACs include Rpd3, Hos1 and Hos2; Class II contains Hda1 and Hos3;
Sir2 and Hst1-4 belong to Class III (Blander and Guarente, 2004; Rundlett et al., 1996).
Members of the classical family of KDACs, which consists of Class I and II KDACs, have a Zn
ion bound to the deacetylase domain that facilitates function. The silent-information regulator
(Sir)-related or the Sirtuin family of KDACs, on the other hand, utilize NAD (nicotinamide
adenine dinucleotide) as a cofactor (Blander and Guarente, 2004).
Human KDACs were discovered based on their sequence similarity to the yeast KDACs Rpd3,
Hda1 and Sir2 (Taunton et al., 1996). The classical family in humans includes KDAC1, -2, -3
and -8 (Class I); KDAC4, -5, -6, -7, -9 and -10 (Class II); and KDAC11 (Class IV) (Gregoretti et
al., 2004). The sirtuin family consists of seven members (SIRT1-7, Class III) and the human
sirtuins show no sequence resemblance to classical KDACs (Blander and Guarente, 2004) (
Table 1-2 )
14
Table 1-2 Yeast and mammalian KDACs
Mammalian KDACs
Yeast
KDAC
Histone
deacetylated
Class I HDAC1-3 HDAC8 Rpd3
H3, H4, H2A,
H2B
Hos1
Hos2
Class II
HDAC4-7, HDAC 9-
10 Hda1 H3, H2B
Hos3
Class III SIRT1-7 Sir2 H4
Hst1-4 H3
Class IV HDAC11
15
1.3.2.1 Rpd3
Rpd3 is perhaps the best studied KDAC in budding yeast and a role for Rpd3 (Reduced
phosphate dependency 3) in transcription was first identified in 1991, in a genetic screen aimed
to identify novel transcriptional regulators (Vidal and Gaber, 1991). Rpd3 exists in two large
multi-subunit complexes, Rpd3 Large (Rpd3L) and Rpd3 Small (Rpd3S), defined by their
molecular weight (Kasten et al., 1997; Rundlett et al., 1996). The core subunits Rpd3, Sin3 and
Ume1 are shared by both complexes (Carrozza et al., 2005). In addition to the core subunits
Rpd3S contains two extra subunits Eaf3 and Rco1 (Gavin et al., 2002; Ho et al., 2002) and
Rpd3L contains 11 other subunits including Sap30, Pho23, Cti6, Rxt2, Rxt3, Sds3, Dot6, Ash1,
Dep1, Tod6 and Ume6 (Shevchenko et al., 2008). While Rpd3L functions at promoters and has
a role in repressing transcription, Rpd3S is recruited to transcribed regions to remove acetylation
marks left by the RNA polymerase II (RNAPII) complex, thus inhibiting spurious initiation from
cryptic start sites within open reading frames (Carrozza et al., 2005).
The first group of genes whose expression was shown to be regulated by Rpd3 included genes
involved in meiosis and arginine catabolism (ie INO1, IME2, SPO13, CAR1, CAR2). Targeted
recruitment of Rpd3 to the promoters of these genes by Ume6, results in the deacetylation of
H4K5 and K12 (Kadosh and Struhl, 1997, 1998b; Rundlett et al., 1998). The catalytic activity of
Rpd3 is necessary for gene repression, since mutating a conserved histidine in the deacetylase
domain diminished its ability to repress transcription (Kadosh and Struhl, 1998a). A closer
examination of the PHO5 gene shed new light on global regulation of acetylation and
deacetylation, highlighting the fact that targeted modifications to histones occur in a background
of global acetylation events. In this scenario, deacetylation serves to reduce basal transcription,
which rapidly returns to its initial state of acetylation when targeting by KDACs is abolished
(Vogelauer et al., 2000). For example, the removal of RPD3 results in an increase in acetylation
levels of H4K12 not only at PHO5 but also at the two adjacent genes.
Several genome-wide studies such as expression microarrays, acetylation microarrays and
chromatin immunoprecipitation (ChIP) have been used to identify genes that are regulated by
Rpd3 as well as promoters occupied by Rpd3 (Bernstein et al., 2000; Fazzio et al., 2001; Hughes
et al., 2000; Kurdistani et al., 2002; Robert et al., 2004; Robyr et al., 2002; Sabet et al., 2004).
Acetylation microarrays couple chromatin immunoprecipitation to DNA microarrays (Ren et al.,
16
2000). In brief, formaldehyde cross-linked DNA-histone complexes are immunoprecipitated
with an antibody against H4K12 (known to be deacetylated by Rpd3) in a strain lacking RPD3,
after which the DNA is purified, amplified and hybridized to a microarray (Robyr et al., 2002).
In ChIP-DNA microarray or ChIP-chip experiments, tagged Rpd3 is immunoprecipitated, then
DNA bound by Rpd3 is purified and hybridized to a microarray (Kurdistani et al., 2002; Robert
et al., 2004). Acetylation microarrays revealed an enrichment for genes involved in sporulation,
germination, meiosis, carbohydrate transport, metabolism and energy reserves in the absence of
RPD3 (Robyr et al., 2002), suggesting that the expression of these groups of genes may be
repressed by Rpd3. Surprisingly, these functional categories were not significantly enriched
among genes bound by Rpd3 in ChIP-chip experiments, suggesting that Rpd3 may not be present
at these promoters (Kurdistani et al., 2002). Instead Rpd3 was reported to bind promoters of
genes involved in protein synthesis, cytoplasm organization, ribosomal protein synthesis and
rRNA transcription and processing. An independent ChIP-chip experiment failed to reveal an
enrichment of ribosomal protein genes among loci bound by Rpd3 (Robert et al., 2004). Instead
an enrichment for cell cycle regulated genes was discovered, consistent with gene expression
profiles of rpd3∆ mutants (Bernstein et al., 2000). According to Robert et al., (2004) the
recruitment of Rpd3 to ribosomal promoters observed by Kurdistani et al., (2002) was an
experimental artifact that was caused by cold-shock during the cold phosphate-buffered saline
(PBS) washes. The influence of technical difference between ChIP protocols on the results of
genome-wide Rpd3 binding surveys remains unresolved.
The genome-wide datasets summarized above emphasize the importance of combining
complementary approaches when attempting to decipher the function of a protein in vivo. While
each technique generates data to support or refute the specific hypothesis being tested, only by
using multiple approaches and by integrating data from these approaches can one obtain a
comprehensive understanding of how a protein may function within the cell.
1.3.2.2 Hda1
The tetrameric HDA complex is a Class II KDAC, composed of two catalytic subunits of Hda1
(Histone deacetylase 1) and two regulatory subunits, Hda2 and Hda3 (Carmen et al., 1996; Wu et
al., 2001a). This complex is recruited to promoters by the general repressor Tup1, where it
specifically deacetylates histone H3 and H2B (Wu et al., 2001a; Wu et al., 2001b). All three
17
components of the complex are necessary for proper deacetylase activity both in vitro and in vivo
(Wu et al., 2001a).
Genome-wide expression and acetylation microarrays indicate that Hda1 regulates groups of
genes that are distinct from Rpd3 (Bernstein et al., 2000; Robyr et al., 2002). Genes involved in
carbon metabolite and carbohydrate utilization and transport genes are up-regulated in the
absence of HDA1 and genes that show increased acetylation in an hda1∆ strain are enriched for
drug transport, detoxification, stress response and cell wall function. Some promoters targeted
by Hda1, such as carbohydrate utilization genes, are also targeted by Rpd3, but this group
represents only 23% of the Hda1-affected regions and 19% of the Rpd3-affected regions,
illustrating that most promoters are targeted by only one of these KDACs. Hda1 is also recruited
to HAST (Hda1-affected subtelomeric) domains, large contiguous chromosomal regions (4-34
kb) containing genes involved in gluconeogenesis, alternative carbon-source use and growth in
adverse conditions, such as osmotic shock, starvation, anaerobic growth and metabolic stress
(Robyr et al., 2002).
1.3.2.3 Hos1
Hos1 (Hda one similar) is the least characterized Class I lysine deacetylase and its inactivation
leads to hyperacetylation of the intragenic regions (IGRs) within the rDNA locus (Robyr et al.,
2002). Hos1 interacts with the Tup1-Ssn6 co-repressor complex and Tup1-Ssn6 mediated gene
repression is compromised in strains lacking RPD3, HOS1 and HOS2 (Davie et al., 2003;
Watson et al., 2000).
1.3.2.4 Hos2
Hos2 is a unique Class I KDAC since it is required for gene activation, unlike the other
deacetylases, and is recruited to the coding region of highly transcriptionally active genes (Wang
et al., 2002). Both Hos2 and the Class III KDAC Hst1 are subunits of the Set3 chromatin
remodeling complex (Set3C), a meiosis-specific repressor of sporulation genes (Pijnappel et al.,
2001). A recent mass spectrometry (MS) analysis of yeast chromatin proteins revealed a
physical interaction between the core Set3C (Set3, Hos2, Snt1 and Sift2) and the Rpd3L complex
(Shevchenko et al., 2008). This new protein complex was designated as Rpd3 Large Extended or
Rpd3LE.
18
Hos2 preferentially deacetylates histone H4 K16 and is found at the coding regions of genes with
high transcriptional activity (Wang et al., 2002). Removing HOS2 has no effect on basal
expression of the GAL1 and INO1 genes, but both genes display slower activation kinetics. In
contrast, removal of RPD3 results in an increase in the basal transcription levels of these genes.
It is proposed that Hos2 is required to reverse the acetylation marks generated by transcriptional
activation in the coding region (both initiation and elongation require acetyltransferase activity)
which returns the chromatin to a permissive state, allowing multiple rounds of transcription
(Wang et al., 2002). Several other groups of genes such as DNA-damage-inducible genes and
genes involved in secretory stress response also require Hos2 for activation (Cohen et al., 2008;
Sharma et al., 2007).
1.3.2.5 Hos3
Hos3 is the only KDAC with intrinsic deacetylase activity and, unlike other KDACs, appears to
function as a homo-dimer (Carmen et al., 1999). It is also insensitive to the small molecular
inhibitor of Class I and II KDACs, tricostatin A (TSA). Acetylation microarrays show
hyperacetylation of the rDNA loci in the absence of HOS3 (Robyr et al., 2002). The only
identified role for Hos3 thus far is in apoptosis following oxidative stress (Ahn et al., 2006)
which serves as a great example of the interplay between histone marks proposed by the “histone
code” hypothesis. Phosphorylation of H2B S10 is a hallmark of apoptotic cell death in yeast and
this serine residue is located adjacent to lysine 14 which is acetylated (Ahn et al., 2005). In the
absence of HOS3, K14 remains acetylated and inhibits the phosphorylation of S10. As a result
hos3∆ strains are resistant to hydrogen peroxide (H2O2) induced cell death (Ahn et al., 2006).
1.3.2.6 Sir2
The class III group of KDACs consists of Sir2 (Silence information regulator 2) and Hst1
(Homolog of SIR two 1), -2, -3 and -4, and the so-called sirtuins are conserved from bacteria to
humans (Frye, 2000). Unlike Class I and II KDACs, Class III KDACs require NAD+ as a co-
factor for proper catalytic activity. The acetyl group from the substrate is transferred to
adenosine diphosphate (ADP)-ribose to generate O-acetyl ADP-ribose and free nicotinamide in
the deacetylase reaction (Jackson and Denu, 2002). Class III KDACs mainly deacetylate
histones H3 and H4, to silence gene expression from mating-type loci, telomeres and rDNA and
influence genome stability (Guarente, 2000; Imai et al., 2000).
19
Gene expression microarrays demonstrate that Sir2 may repress genes involved in amino acid
biosynthesis since these genes are up-regulated in a sir2∆ strain (Bernstein et al., 2000). Several
amino acid biosynthesis genes are down-regulated in the absence of RPD3, suggesting that Rpd3
and Sir2 may exert opposing effects on this class of genes.
Silencing by the Sir complex involves the assembly of a higher order chromatin structure that
extends in a linear fashion along the chromosome, affecting multiple genes. Ten percent of the
yeast genome is packaged into silent chromatin which is found in three general regions: the silent
mating type loci, telomeres and the nucleolus (Gao and Gross, 2006). Sir2 forms a complex
with two other Sir proteins, Sir3 and Sir4, at the silent mating type loci to repress transcription at
HML and HMR (Rine and Herskowitz, 1987). The Sir complex is recruited by sequence-specific
DNA binding proteins, such as the origin recognition complex (ORC) and Rap1, to the cis-acting
silencers in HM loci. Spreading of Sir proteins occurs in a stepwise fashion and requires both H4
K16 deacetylation and interactions between the Sir complex and the amino terminal tails of
histone H3 and H4.
A similar sequence of events take place at telomeres to silence ribosomal DNA (rDNA) repeats
and this regulatory function may be linked to the role of Sir2 in longevity (Guarente, 2000).
SIR2 is required for the stability of the 100-200 tandem copies of rDNA in yeast (Gottlieb and
Esposito, 1989). rDNA recombination events produce extrachromosomal rDNA circles (ERCs)
which, once made, replicate and segregate preferentially to mother cell nuclei (Sinclair and
Guarente, 1997). The accumulation of ERCs ultimately leads to senescence. It is proposed that
by silencing telomeres, Sir2 slows down the appearance of the first ERC in mother cells thus
extending the replicative life span of cells (Chen and Guarente, 2007).
1.3.2.7 Hst1-4
Hst2 is the only KDAC known to be regulated by nuclear exclusion (Wilson et al., 2006). Many
of the mammalian Sirtuins contain either a demonstrated or a predicted nuclear export signal,
indicating that this may be a mechanism for regulating the activity of chromatin modifiers
(Wilson et al., 2006). Hst2 participates in the repression of FLO10 by directly binding to its
promoter (Halme et al., 2004) and the over-expression of HST2 in the absence of SIR2 influences
many of the processes regulated by Sir2 such as rDNA silencing, recombination and aging
(Lamming et al., 2005; Perrod et al., 2001).
20
HST3 and HST4 encode redundant deacetylases and hst3hst4 double mutant cells accumulate
large-budded cells with undivided nuclei (Brachmann et al., 1995). The double mutants also
show defects in chromosome condensation, sister chromatid separation, DNA damage and
temperature sensitivity and have transcriptional derepression at telomeres. Recently, a role for
Hst3 and Hst4 was discovered in negatively regulating H3 K56 acetylation (Maas et al., 2006;
Miller et al., 2006). H3 K56 acetylation is unusual since this lysine residue is located within the
histone core rather than in the tails that are normally regulated by acetylation (Ozdemir et al.,
2005). H3 K56 acetylation is only found in newly synthesized histones, thus accumulates in S
phase of the cell cycle and is required for recovery from DNA damage (Masumoto et al., 2005).
Silent information regulators are so named because of their role in silencing. However,
additional roles for Sirtuins are being uncovered. For example, Sir2 may play a role in caloric
restriction, longevity and aging (Guarente, 2000). It is safe to assume that, despite decades of
research on KDACs, the diversity of biological processes they regulate remains to be fully
deciphered.
1.4 Acetylation and disease
KATs and KDACs are responsible for dynamic histone modifications. Therefore, they must exist
in perfect balance to maintain normal cell proliferation, growth and differentiation, and the
abnormal functions of these enzymes result in disease. For example, hyperacetylation and
deacetylation play an important role in both the genesis and suppression of cancers (Archer and
Hodin, 1999). KATs and KDACs are also implicated in neurodegenerative diseases (Chuang et
al., 2009), cardiovascular disease (Borradaile and Pickering, 2009), inflammatory diseases and
diabetes (Khan and Khan, 2010).
p300 and CBP are two KATs whose mutation in humans is linked to a congenital disorder,
Rubinstein-Taybi syndrome (RSTS), which is characterized by mental and growth retardation,
congenital heart disease and a wide range of dysmorphic features (Bannister and Kouzarides,
1996; Roelfsema et al., 2005). Mutations of p300 and CBP are also found in patients with acute
myeloid leukemia (AML) (Yang, 2004) and in cancers such as glioblastomas and hepatocellular
carcinomas (Marks et al., 2001). In addition p300 and CBP proteins are inactivated in
neurodegenerative diseases such as Huntington disease and Kennedy disease (Kalkhoven, 2004).
Thus the p300/CBP example illustrates the multiple ways by which affecting KAT activity may
21
cause disease states. In general, KAT inactivation can lead to disease states at several levels: 1)
the absence of a KAT may cause reduced expression of tumor suppressor genes; 2) the KAT
activity may be required for the proper function of tumor suppressor proteins (in RSTS) (Petrij et
al., 1995) ; and 3) genes involved in differentiation may be directly regulated by KATs and be
down-regulated in their absence (Ait-Si-Ali et al., 2000).
Another example that demonstrates the importance of histone modification in the suppression of
tumorigenesis is Rb, whose interaction with the human deacetylase KDAC1 is necessary to
repress transcription mediated by the G1 transcription factor E2F (Archer and Hodin, 1999;
Brehm and Kouzarides, 1999; Brehm et al., 1998). The Rb gene is mutated in almost all cancers
and additional mutations in both E2F and co-repressor proteins that interact with Rb have been
mapped (Archer and Hodin, 1999). Most of these mutations abolish the interaction between Rb
and E2F, leading to uncontrolled cell proliferation.
Altered recruitment and aberrant expression of KDACs have been reported in many cancers. For
example, over-expression of KDAC1, KDAC2, KDAC3, KDAC6 and SIRT7 has been seen in
colon, breast, prostate, thyroid, cervical and gastric cancers respectively (Ma et al., 2009). In
leukemias and lymphomas, KDACs are recruited by the oncoproteins to repress transcription
(Marks et al., 2001). In neuroblastomas the altered expression of KDACs strongly correlates
with disease stage and prognosis (Chuang et al., 2009). Not surprisingly, KDAC inhibitors
(KDACi) are emerging as a new class of anti-cancer agents and KAT inhibitors (KATis) are
being investigated as treatment for Alzheimer‟s disease and diabetes (Manzo et al., 2009).
1.4.1 KAT and KDAC inhibitors
Sodium butyrate, the first KDACi to be identified, preceded the identification of KDACs, and
was characterized as a chemical that resulted in histone hyperacetylation (Riggs et al., 1977).
Vorinostat (Zolinza, formally known as SAHA, Merck) was the first KDAC inhibitor to be
approved by the FDA in 2006, followed by Romidepsin (Istodax injection, Gloucester
Pharmaceuticals) in 2009, and both drugs are currently used to treat cutaneous T-cell lymphoma
(CTCL) (Kavanaugh et al., 2010). Other KDACi, Tricostatin A (TSA), and Valproic acid
(VPA), are used in the treatment of epilepsy (Gottlicher et al., 2001; Yoshida et al., 1990). Many
other KDACis are currently being tested in clinical trials as monotherapy or in combination with
22
chemotherapy or radiation therapy to treat many types of cancers including leukemias (Table 1-
3) (Bolden et al., 2006; Minucci and Pelicci, 2006).
KATis have received comparatively little attention (Spange et al., 2009). Acetyltransferase
inhibitors are currently being investigated for the potential treatment of Alzheimer‟s disease and
diabetes (Manzo et al., 2009). Possible anti-tumor effects of KATis are less clear since: i)
KATis are less efficient that KDACis; ii) the molecular basis of their inhibition is not
understood; and iii) the inhibitory doses are too high to be used in biological models (Manzo et
al., 2009). Table 1-3 presents a summary of the inhibitors currently used for disease treatment.
23
Table 1-3 Diseases targeted by KATis and KDACis
Inhibitor Specificity Clinical trials Disease treated
KATi Curcumin p300 Phase I and II Colorectal cancer
Pancreatic cancer
Alzheimer disease
Osteosarcoma
Isothiozolone PCAF
Ovarian and Colon cancer cell lines
Anacardic acid p300, PCAF
Garcinol p300, PCAF Phase I and II hyperlipidaemia
KDACi TSA Class I & II
Breast, prostate, lung and stomach cancers,
neuroblastoma and leukaemia
Epilepsy
Valproic acid Class I & II Phase I and II
Butyrate Class I & II Phase I and II Leukaemia and
myelodysplastic disease
Vorinostat (SAHA) Class I & II
Breast, prostate, lung and stomach cancers,
neuroblastoma and leukaemia
Apicidin Class I & II
MS-275 Class I Phase I and II
Tacedinaline N/A Phase I, II and III
Trapoxin Class I & II a
Nicotinamide Class III
Sirtinol Class III
Splitomicin Class III
KDAC activator Resveratrol Sirtuins
Increase life span
24
KDACis often inhibit enzyme function in a competitive manner where the polar end interacts
with Zn+2
and the rest of the molecule occupies the tubular pocket of the KDAC effectively
blocking the active site (Bi and Jiang, 2006; Gray and Dangond, 2006). Several events involved
in tumorigenesis are affected by KDACis (Ma et al., 2009): [1] Death receptors are activated
specifically upon treatment with KDACis through initiation of apoptotic pathways; [2] KDACis
suppress angiogenesis by inducing the expression of anti-angiogenic factors such as p53 and
simultaneously down-regulating pro-angiogenic factors such as VEGF; [3] the expression of
metastatic suppressors such as RhoB is induced (Bolden et al., 2006). These regulatory events
ultimately retard tumour growth but the detailed molecular mechanisms by which KDACis
function remain to be uncovered.
Although KDACis have proven successful in clinical trials, optimal dose, duration and timing of
therapy, as well as agents that act in synergy with KDACis, must be considered. For future
KATi development, drugs with higher specificity, cell permeability and high potency must be
discovered. Another major challenge is to produce isoform-specific KATis and KDACis, since
KATs and KDACs are both differentially expressed in a tissue-dependent manner and are
differentially mutated in various types of cancers (Bradner et al., 2010; Khan et al., 2008).
1.5 Acetylation and non-histone targets
Clear roles for KATs and KDACs in regulating proteins other than histones creates an additional
layer of complexity when designing inhibitors and when interpreting the effects of KAT of
KDAC misregulation in cancer or other diseases (Kurdistani and Grunstein, 2003). Non-histone
targets of KATs and KDACs in humans influence multiple cellular processes including
transcription, signaling, DNA repair, recombination and metabolism (Glozak et al., 2005;
Polevoda and Sherman, 2002). Acetylation is now thought to be as prevalent as phosphorylation
in influencing enzymatic activity, DNA binding, protein stability and protein-protein interactions
(Kouzarides, 2000). Unlike phosphorylation, which occurs in unstructured regions such as loops
and hinges (Malik et al., 2008), acetylation sites are typically located within highly ordered
regions and appear to be modified in stretches (Choudhary et al., 2009). Although there are
fewer known acetyltransferases than kinases in humans, acetylation displays a broader spectrum
of substrates compared to phosphorylation (Spange et al., 2009). Also, unlike kinases, KATs
appear to associate with their substrates avidly. Given this tight association between the
25
KATs/KDACs and their substrates, KATs and KDACs may promote a strong and specific
interaction between the target enzyme and substrate (Kouzarides, 2000).
A KAT recognition motif has been identified for the conserved KAT Gcn5 in Tetrahymena, by
analyzing the crystal structure (Rojas et al., 1999). Histones, as well as non-histone KAT targets
share a common GKxxP motif, where the lysine is potentially acetylated. Non-histone KAT
targets can be discriminated on the basis that bulky side chains such as tyrosine and
phenylalanine are enriched in the -2 and +1 positions and positively charged amino acids are
excluded from the -1 position (Choudhary et al., 2009). While the recognition motifs for
nuclear and cytoplasmic proteins are similar they differ from the recognition motif for
acetylation of mitochondrial proteins. In general, specificity and site selection for KDACs are
not well characterized.
The biological consequences of acetylation appear to be protein-and context-dependent (Figure
1-1). While the acetylation of TFs, p53, E2F1, EKLF and GATA1 increases DNA binding
(Boyes et al., 1998; Gu and Roeder, 1997; Martinez-Balbas et al., 2000; Zhang and Bieker,
1998), acetylation of YY1 and HMG I(Y) reduces their ability to bind DNA (Munshi et al.,
1998; Yao et al., 2001). Similarly, acetylation of c-MYC and Smad7 increase protein stability
(Gronroos et al., 2002; Patel et al., 2004) whereas the stability of HIF-1α is decreased following
acetylation (Jeong et al., 2002).
26
Figure 1-1 Effects of acetylation of a variety of proteins.
Apart from histones, many non-histone proteins are regulated by acetylation, including transcription factors, nuclear
import factors and cytoskeletal proteins. The consequences of acetylation appear to be protein-specific; DNA
binding (HMGI(Y), p53), protein stability (E2F1), protein localization (importin-α) and protein-protein interactions
(TCF and β catenin) may be affected by acetylation. Figure adapted from Kouzarides et al., (2000). Abbreviations:
Ac – acetylation.
.
27
The first non-histone protein acetylation to be documented was on p53, a sequence-specific
DNA-binding factor that functions as a tumor suppressor (Gu and Roeder, 1997). Acetylation of
p53 adjacent to the DNA-binding domain by the KATs p300 and PCAF enhances DNA binding,
transactivation and stability of the protein (Gu and Roeder, 1997; Li et al., 2002). The
acetylation stabilizes p53 by inhibiting its ubiquitination (Li et al., 2002). Several other KATs
such as Tip60 and MOF are also able to acetylate p53 in a different context at residues distinct
from those acetylated by p300 and PCAF, and these acetylation events are necessary for gene
induction by p53 after DNA damage (Sykes et al., 2006). Four KDACs, KDAC1, KDAC3,
SIRT1 and SIRT7, remove the acetylation marks on p53 (Brooks and Gu, 2003; Zeng et al.,
2006). While deacetylation by KDAC1 decreases protein stability, deacetylation by SIRT1
reduces gene activation by p53. p53 is the best characterized example of how differential
regulation of protein function under various cellular conditions can be achieved through multiple
acetylation events.
The prevalence of non-histone targets of acetylation means that is necessary to consider the
effects of KATis and KDACis not only in the context of the chromatin, but also at the level of
non-histone targets of acetylation. Although much research has been done to determine the
effects of KATis and KDACis on gene expression patterns, little information is available about
alterations in the acetylated proteome due to inhibitor treatment (Spange et al., 2009). If a
rational basis for cancer therapy is to be developed, it is critical that global relationships
involving the “acetylome” be identified and the propensity of the network to lapse into malign
states evaluated in a genome-wide manner.
1.5.1 Lysine acetylomes
The discovery of p53 acetylation in 1997 prompted the study of acetylation of non-histone
proteins, revealing over 100 acetylated proteins in humans. These original studies employed a
candidate approach, which, although successful, was biased towards identifying transcription
factors and chromatin-associated proteins. The first unbiased genome-wide approach to detect
acetylation was performed in 2005 using mouse brain and skeletal muscle cells analyzed by 2D-
PAGE followed by immunoblotting with monoclonal anti-Acetyl lysine (Ack) antibodies to
locate acetylated proteins for mass spectrometry (Iwabata et al., 2005). Several lysine
acetylomes (K-acetylomes) have since been completed for HeLa cells (Kim and Yang, 2010),
28
mouse liver mitochondria (Schwer et al., 2009), MV4-11, A549 and Jurkat cells, human liver
cells (Choudhary et al., 2009), Escherichia coli (Yu et al., 2008; Zhang et al., 2009) and
Salmonella enterica (Wang et al., 2010). I discuss the techniques utilized in these studies in
section 1.6. A compendium of acetylated proteins and peptides has been assembled in a protein
lysine acetylation (CPLA) database generated by Liu et al. (http://cpla.biocuckoo.org/) (Liu et
al., 2010).
Together these acetylome surveys have revealed over 2000 acetylated proteins in human cells
and approximately 200 acetylated bacterial proteins (Kim and Yang, 2010). Acetylated proteins
are involved in diverse biological processes such as the cell cycle, RNA splicing, endocytosis,
vesicular trafficking, cytoskeletal reorganization and metabolism. However, there are several
notable characteristics of the K-acetylome. First, the use of protein acetylation as a regulatory
mechanism is widespread, given the extensive lysine acetylation found in E. coli, and acetylation
sites tend to be as conserved as phosphorylation sites. Second, unlike phosphorylation events,
acetylation appears to be concentrated in regions with ordered secondary structure, with the
exception of histone tails which are disordered (Choudhary et al., 2009). Third, many of the
proteins that undergo acetylation are components of large macromolecular complexes that
participate in splicing, nuclear transport, chromatin remodeling and cytoskeletal remodeling.
One possibility is that coordinated acetylation events regulate protein-protein interactions within
multiprotein complexes, affecting assembly and in turn their activity. Finally, many other PTM
enzymes, such as kinases, histone methyltransferases and ubiquitin ligases are acetylated. This
indicates that crosstalk between PTMs may further amplify the regulatory power of acetylation
events (Norris et al., 2009).
1.5.2 Non-histone targets in S. cerevisiae
Budding yeast has served as the pioneer model organism for virtually all genome-scale methods
including genome sequencing, DNA microarrays, gene deletion collections, and a variety of
proteomic platforms. Despite the availability of many functional genomic and proteomic
approaches and the fact that many of the yeast KATs and KDACs have clear human orthologues,
an in vitro protein acetylation microarray has been the only genome-scale approach utilized thus
far to explore the lysine acetylome in yeast (Lin et al., 2009). As noted above, while there are
over 2000 known acetylated proteins in mammals (Choudhary et al., 2009; Glozak et al., 2005;
29
Spange et al., 2009; Zhao et al., 2010) only 19 non-histone substrates have been characterized in
yeast (Beckouet et al., 2010; Borges et al., 2010; Choudhary et al., 2009; Heidinger-Pauli et al.,
2009; Ivanov et al., 2002; Kim et al., 2010; Lin et al., 2009; Lin et al., 2008; VanDemark et al.,
2007), emphasizing that the majority of the yeast acetylome remains unexplored.
Smc3, a component of the cohesin complex, was one of the first non-histone targets of
acetylation to be discovered in yeast. Smc3 acetylation is necessary for the establishment of
sister chromatid cohesion in S phase (Zhang et al., 2008). An essential KAT, Eco1, acetylates
Smc3 at lysine residues that are conserved in human Smc3. These lysines are deacetylated by
the KDAC Hos1 during anaphase (Beckouet et al., 2010; Borges et al., 2010). In the absence of
HOS1, Smc3 is unable to generate cohesion during the subsequent S phase, highlighting the
requirement for de novo acetylation during DNA replication for proper establishment of cohesion
(Beckouet et al., 2010). Thus both cell cycle-dependent acetylation and deacetylation are
necessary for proper Smc3 function. Mcd1, a second component of the cohesion complex, is
also acetylated by Eco1 in the context of DNA damage. Acetylation of Mcd1 inhibits its protein-
protein interactions with Wpl1, an inhibitor of cohesion, which is required for proper DSB-
induced sister chromatid cohesion (Heidinger-Pauli et al., 2009).
The acetylation site on Rsc4, a component of the RSC chromatin remodeling complex, was
discovered serendipitously during an examination of its crystal structure (Choi et al., 2008;
VanDemark et al., 2007). Acetylation of K25 in the first bromodomain of Rsc4 by Gcn5
antagonizes its binding to H3K14ac marks, removing Rsc4 from the chromatin (VanDemark et
al., 2007). The Snf2 subunit of the Swi/Snf chromatin remodeling complex is a second target of
Gcn5 and, similar to Rsc4 acetylation, promotes the dissociation of Swi/Snf from target
promoters (Kim et al., 2010). Two KDACs, Hst2 and Rpd3, reverses the acetylation of Snf2.
Acetylation of Snf2 and Rsc4 by Gcn5 and deacetylation of Snf2 by two KDACs highlights the
complex regulation of acetylation events that influence chromatin remodeling complexes in vivo.
A genome-wide genetic interaction network for KATs and KDACs identified Yng2 as a
substrate of Esa1, a second essential acetyltransferase in yeast (Lin et al., 2008). Both Esa1 and
Yng2 are components of the NuA4 KAT complex in yeast (Brownell et al., 1996). The stability
of Yng2 is reduced in the absence of ESA1 whereas the deletion of RPD3 stabilizes the protein.
The interplay between Rpd3 and Esa1 in regulating Yng2 levels is proposed to occur at DNA
30
double strand breaks (DSBs) where deacetylation by Rpd3 and the subsequent degradation of
Yng2 disrupts and evicts the NuA4 complex from DSBs.
Acetylation of the cyclin-dependent kinase Cdc28 was discovered during a search for conserved
acetylation sites in cell cycle proteins. Acetylation of cell cycle CDKs appears conserved since
one acetylome analysis in human cells identified a large number of acetylated cell cycle proteins
including the Cdc28 homologue, CDC2 (Choudhary et al., 2009). Mass spectrometry revealed
that lysine 40 in Cdc28 is acetylated as is the analogous reside in Cdc2, the human form of Cdk1
(Choudhary et al., 2009) .
The final set of 13 acetylated proteins in budding yeast was discovered in the protein acetylation
microarray experiment mentioned earlier. In vivo confirmation experiments confirmed that
Atg3, Atg11, Brx1, Cdc34, Gph1, Hsp104, Nnt1, Pck1, Prp19, Rpt5, Sip2, Sip5, and Tap42,
proteins involved in metabolism, transcription, cell cycle progression, RNA processing and stress
response, are acetylated in vivo in an Esa1-dependent manner (Lin et al., 2009). Acetylation of
Pck1 (Phosphoenolpyruvate carboxykinase), the key enzyme in gluconeogenesis, is required for
proper enzymatic activity, a regulatory mechanism that also extends to the mammalian Pck1,
PEPCK-C (Lin et al., 2009). Sir2, a Class III KDAC, is responsible for the deacetylation of
Pck1. The non-histone targets identified thus far in yeast, the cognate KAT and KDAC, as well
as the outcome of acetylation are summarized in Table 1-4.
It is clear that much of the yeast acetylome remains unexplored. In Chapter 3, I describe my
effort to use a genetic approach to comprehensively examine the lysine acetylome of Class I and
II deacetylases in yeast.
31
Table 1-4 Non-histone proteins regulated by acetylation in S. cerevisiae
Non-
histone
protein
KAT KDAC Outcome Reference
Smc3 Eco1 Hos1 Acetylation required for the
establishment of chromatid
cohesion
Beckouet et al., 2010; Borges et
al., 2010
Mcd1 Eco1 Acetylation antagonizes PPI
with Wpl1 in the presence of
DSB; Acetylation required to
establish DSB-induced
cohesion
Heidinger-Pauli et al., 2009
Rsc4 Gcn5 Acetylation inhibits binding
to histones
Choi et al., 2008; VanDemark et
al., 2007
Yng2 Esa1 Rpd3 Acetylation increases protein
stability
Lin et al., 2008
Cdc28 Acetylation required for
proper function
Choudhary et al., 2009
Snf2 Gcn5 Rpd3 Hst2 Acetylation inhibits binding
to histones
Kim et al., 2010
Pck1 Esa1 Sir2 Acetylation required for
proper enzymatic activity
Lin et al., 2009
Atg3 Esa1 Lin et al., 2009
Atg11 Esa1 Lin et al., 2009
Brx1 Esa1 Lin et al., 2009
Cdc34 Esa1 Lin et al., 2009
Gph1 Esa1 Lin et al., 2009
Hsp104 Esa1 Lin et al., 2009
Nnt1 Esa1 Lin et al., 2009
Prp19 Esa1 Lin et al., 2009
Rpt5 Esa1 Lin et al., 2009
Sip2 Esa1 Lin et al., 2009
Sip5 Esa1 Lin et al., 2009
Tap42 Esa1 Lin et al., 2009
32
1.6 Mapping the lysine acetylome - tools and techniques
Due to the clinical relevance and the myriad of biological processes that are regulated by
acetylation, many tools and techniques have been developed to map acetylation sites. These
approaches allow system-wide mapping of acetylation sites both in vitro and in vivo, as well as
the identification of cognate KATs/KDACs. Below, I review in vitro KAT and KDAC assays,
protein acetylation microarrays and identifying acetylated peptides using MS. I also introduce
genome-wide genetic screening techniques that can be adapted to examine functions of KATs
and KDACs.
1.6.1 In vitro KAT and KDAC assays
KAT and KDAC assays were originally developed to identify proteins that possessed either
acetyltransferase or deacetylase activity and were later adapted for to detect acetylated proteins.
In traditional KAT assays, purified KATs or cell extracts are incubated with radiolabeled (either
with 3H or with
14C) acetyl-coenzyme A (acetyl-CoA) and purified histones (Figure 1-2A). After
the reaction, radiolabeled acetylated histones are separated and radioactivity is measured by
scintillation counting (Sun et al., 2003). KDAC assays require an additional labeling step since
KDACs catalyze the removal of the acetyl group. Radiolabeled histones are generated either by
incubating histones with radiolabeled CoA and a KAT, or by incubating cultured cells with [3H]
acetate in the presence of KDAC inhibitors (Figure 1-2B). KDACs are then mixed with
radiolabeled histones and the amount of [3H] acetate released into the medium is determined
using scintillation counting. In both these assays, histones can be substituted with candidate non-
histone protein targets.
33
Figure 1-2 In vitro KAT and KDAC assays
(A) Either purified acetyltransferase enzymes or cell extracts are incubated with radiolabeled acetyl-coenzyme A
and purified histones. Radiolabeled histones produced in the reaction are separated using P81 phosphocellulose
paper and measured by scintillation counting. (B) Making tritium-labeled histones. Radiolabeled histones are
produced either using the KAT reaction shown in A or by incubating cultured cells with tritium-labeled acetate and
KDAC inhibitors. Labeled histones are purified and mixed with labeled KDACs. Radiolabeled acetate released into
the media is measured by scintillation counting.
34
Although useful, in vitro KAT and KDAC assays have several limitations which made them less
than desirable for high-throughput studies: (1) radiolabeled histones are difficult to generate; (2)
the radiolabeled product has to be separated from the substrate; and (3) the assays use
radioactivity. To overcome these limitations, fluorescent KAT/KDAC assays have been
developed (Figure 1-3A). One of the widely used quantitative fluorometric KAT assays uses a
sulfhydryl-sensitive dye, 7-diethylamino-3-(49-maleimidylphenyl)-4-methylcoumarin (CPM),
which reacts with CoA and fluoresces upon conjugation (Trievel et al., 2000). Fluorogenic
KDAC assays involve a peptide substrate which contains an acetylated lysine residue conjugated
to a 4-methylcoumarin-7-amide fluorophore moiety at the carboxyl terminus. Deacetylation
enables tryptic digestion of the conjugate and the resultant free fluorophore causes the reaction to
fluoresce (Figure 1-3B) (Wegener et al., 2003).
All KAT/KDAC assays require purification of active KATs and KDACs, most of which exist as
macromolecular complexes in vivo. It is often difficult to purify the desired complex, free of co-
purifying KATs/KDACs. Also the promiscuity of most purified recombinant KATs and KDACs
in the absence of in vivo regulatory constraints must be considered. While these in vitro assays
alone are not enough to distinguish bona fide protein targets they remain a valuable tool
especially in the preclinical screening stages for KATis and KDACis.
35
Figure 1-3 Fluorescent KAT and KDAC assays
A) In the fluorescent acetyltransferase assay Coenzyme A generated when the acetyl group from Acetyl-CoA is
transferred to the lysine and reacts with the dye CPM to yield an adduct that will fluoresce at 469 nm. Figure
adapted from Trievel et al., 2000. (B) The fluorescent KDAC assay involves two steps. The first step involves
deacetylation by the KDAC after which the substrate is cleaved by trypsin in a second step to remove the fluorescent
substrate that can be measured at 390 nm and at 460 nm. Adapted from Wegener et al., 2003.
36
1.6.2 Protein microarrays
Protein microarrays allow the proteome-wide study of the biochemical activities of proteins in
vitro. In these arrays, full-length proteins or protein domains are printed on a small glass slide
which enables assessment of the biochemical activity of an added enzyme on the entire proteome
in a single experiment. The first library used for systematic protein purification, to create the
„protein chips‟ was constructed in S. cerevisiae and contained 5800 full length proteins. All
ORFs were cloned into an expression vector and overproduced as GST-fusion proteins, which
were purified and printed on to nickel- or nitrocellulose-coated slides (Zhu et al., 2001). A
second protein microarray has since been constructed using a library of C-terminally TAP-tagged
yeast proteins (Gelperin et al., 2005). To date, proteome chips have been exploited to examine
protein-protein interactions (Zhu et al., 2000) and DNA-protein interactions (Hall et al., 2004), to
detect antibody specificity (Michaud et al., 2003) and to assay enzymatic reactions (Lin et al.,
2009; Ptacek et al., 2005).
The yeast GST-ORF proteome array was used to examine the function of the NuA4
acetyltransferase complex (Lin et al., 2009). Purified NuA4 complex was incubated with the
proteome array with [14C]-acetyl-CoA as a labeling agent and acetylated proteins were
identified with autoradiography. Of the 91 proteins that were readily acetylated by NuA4 in
vitro, 20 were also tested in vivo, confirming 13 acetylated proteins. Protein microarrays thus
allow rapid systematic screening for non-histone substrates of KATs and could also be adapted
to screen for KDAC targets. However, like KAT and KDAC assays, acetylation microarrays
have several limitations. The quality of the data is influenced by the quality of the proteins
spotted on the array as well as the chip-surface chemistry, requiring pilot studies to establish
optimal binding conditions for each protein. And as with other in vitro assays, enzyme
promiscuity in vitro must also be addressed.
1.6.3 Mass spectrometry
Over the past 50 years mass spectrometry (MS) has become a central technology in a protein
chemist‟s toolkit since it enables mapping of PTMs and quantification of chemical modifications
on proteins (Witze et al., 2007). MS has replaced Edman degradation, the conventional method
formerly used to map post-translational modifications. In mass spectrometry the mass-to-charge
ratio of proteins is measured by following the trajectories of the peptides derived from proteins
37
of interest in a vacuum system (Steen and Mann, 2004). Since it yields the molecular weight and
the fragmentation patterns for peptides, MS represents a general method that can be used to
detect modifications that change the molecular weight of a protein (Mann and Jensen, 2003).
Acetylation at a single residue shifts the molecular weight of a protein by 42Da, and this change
is readily detectable by MS (Dormeyer et al., 2005).
To effectively define the acetylome, a prior enrichment step for acetylated proteins is necessary
(Kim et al., 2006). Many pan-acetyl-lysine antibodies have been developed for this purpose
(Iwabata et al., 2005; Kim et al., 2006). In the first step of sample preparation, whole cell
extracts are treated with a protease, such as trypsin or chymotrypsin, to generate a mixture of
peptides to be fragmented by MS (Figure 1-4). Acetylated peptides are then immune-affinity
purified using anti-acetyl-lysine antibodies and introduced into a mass spectrometer via liquid
chromatography coupled to electrospray ionization (ESI), or by using matrix-assisted
laser/desorption ionization (MALDI). Fragmentation spectra obtained from the mass
spectrometer are then used to identify proteins from primary sequence databases. A differential
modification of 42Da to lysine residues is considered in search parameters to identify acetylated
peptides (Dormeyer et al., 2005). The affinity-based enrichment method is particularly
attractive since the enrichment step is a single experiment and the subsequent identification of
the protein mixture is reduced to a single liquid chromatography (LC) MS/MS experiment.
38
Figure 1-4 Schematic of an HPLC/MS/MS experiment.
Cell extracts are treated with a protease to generate peptides followed by immune-affinity purification using an
acetyl lysine specific antibody. Isolated peptides are analyzed by HPLC/MS/MS for peptide identification. Adapted
from Kim et al., 2006.
39
Due to the technical difficulties associated with mapping PTMs, many studies to date have
concentrated on detecting modifications rather than quantifying them. But biological events are
often a consequence of changes in the level of a modification rather than in the absolute presence
or absence of the PTM. To achieve a dynamic view of a PTM network such as the acetylome,
mass spectrometry must be coupled to an efficient quantification method such as SILAC. Stable
isotope labeling with amino acids in cell culture (SILAC) involves growing two populations of
cells, one in medium that contains a „light‟ (normal) amino acid and the other containing an
isotopically labelled „heavy‟ amino acid (Figure 1-5). The heavy amino acids can be 2H instead
of H, 13
C instead of 12
C or 15
N instead of 14
N. Incorporation of a heavy amino acid results in a
mass shift of peptides when compared to peptides that contain the „light‟ version of the amino
acid. Sample preparation following growth in appropriate media, is identical to the previously
described protocol, where extracts are digested, immune-affinity purified and introduced into the
MS. In SILAC experiments, peptides appear as a pair in the mass spectra, where masses reflect
the originating samples. If SILAC peptide pairs appear in a 1:1 ratio, there is no difference in
abundance for that particular protein between the two samples, whereas higher peak intensity for
one will indicate a difference in abundance. Because the amino acids are chemically identical,
the ratio of peak intensities directly defines the ratio of proteins between the two populations.
SILAC has been successfully used to map changes in acetylation upon KDAC inhibition
(Choudhary et al., 2009; Ong et al., 2002), where 3600 acetylation sites for 1750 proteins were
identified. SILAC itself is limited by the availability of „heavy‟ and „light‟ amino acids -
currently only three concurrent experiments can be performed.
40
Figure 1-5 Experimental approach to SILAC labelling.
Three populations of cells are grown in medium that contains either normal (control), 2H labeled or
13C-labeled
amino acids. Cell extracts are mixed, trypsinized, immune-affinity purified and analyzed by MS. Schematics of two
sample MS spectra are shown at the bottom of the figure. In this schematic, acetylation of protein X increased in
condition B while the acetylation of protein Y decreased under the same condition.
41
While MS has become a valuable approach to map and identify acetylated proteins, its limitation
lies in the affinity purification step of the sample preparation protocol. Even pan-acetyl-lysine
antibodies may have different specificities as well as different affinities for various lysine
acetylation sites. Developing enrichment techniques that complement affinity purification
methods is therefore crucial.
1.6.4 Functional Genomics
The proteomic techniques described above map acetylated proteins successfully but are
incapable of capturing the dynamic and/or biological effects of acetylation within a cell.
Functional genomics offers a powerful counterpoint to biochemical assays, especially since the
focus of functional genomics has shifted in the past decade from examining individual genes to
generating global networks of all genetic interactions within a cell. Below, I discuss systematic
screening methods for discovering genetic interactions in yeast, which I have used to
functionally explore the acetylome (Chapter 3).
1.6.4.1 Genetic interactions
A genetic interaction arises when the phenotype caused by combining two mutations in the same
cell or organism cannot be readily explained by combining the effects of the individual mutations
(Bateson et al., 1905). Genetic interactions can be broadly classified into two types: synthetic
enhancement and synthetic suppression. Synthetic enhancement results when the mutant
phenotype of one gene is enhanced by the mutation or increased dosage of another gene,
(Guarente, 1993). In contrast, synthetic suppression occurs when the phenotypic impact of one
mutation is relieved by mutation of a second gene. I have used synthetic enhancement genetics
in my studies of yeast KDACs, and I focus on this type of genetic interaction below.
1.6.4.1.1 Synthetic sick and synthetic lethal interactions
Negative genetic interactions include synthetic sick (SS) and synthetic lethal (SL) interactions,
and occur when the observed fitness defect of a double mutant is more severe than the expected
based on the fitness of each single mutant (Mani et al., 2008) (Figure 1-6A). SL is the extreme
case where the combination of two mutations results in cell death. Screening for SL interactions
with null alleles typically identifies genes participating in parallel or redundant pathways that
impinge on the same essential biological function (Kelly, 2005; Tong et al., 2001; Tong et al.,
2004) (Figure 1-6B). The genetic interaction of the KDACs Hda1 and Rpd3 is an example of
42
synthetic lethality, where neither gene is essential for cell viability but the deletion of both HDA1
and RPD3 results in cell death (Lin et al., 2008). Reduced cell viability can also result when
distinct, non-compensatory pathways are collapsed, and the additive defects retard a common
biological process. SL can also occur between non-null mutations such as partial loss-of-
function and over-expression alleles and, depending on the context, may be interpreted
differently. For example, SL that results from combining two partial loss-of-function alleles of
essential genes often reflects participation of the genes in the same biological pathway (Figure
1-6C).
The largest genome-scale genetic interaction map produced to date was published in 2010, and
examined 5.4 million gene pairs, generating interaction profiles for over 75% of yeast genes
(Costanzo et al., 2010a). A correlation-based network was created based on the principle that
genes that belong to the same pathway share similar genetic interactios profiles (Collins et al.,
2007; Tong et al., 2004). Thus genes with similar genetic interaction profiles formed distinct
clusters in the network (Costanzo et al., 2010a; Costanzo et al., 2010b). Not only did this map
enable prediction of functions for uncharacterized genes based on network connectivity, it also
produced a functional map of the cell, highlighting the inter-dependence between biological
processes at a global level. Several additional observations were made from this map: (1) single
mutant fitness defects correlated with the number of genetic interactions (GIs); (2) genetic
interaction hubs (highly connected genes with a large number of GIs) showed a high degree of
pleiotropy; and (3) only a small fraction of gene pairs with GIs were physically linked,
suggesting that GIs occur between complexes and pathways, connecting those that work together
or buffer each other.
43
Figure 1-6 Negative genetic interactions
(A) Negative genetic interactions occur when the expected fitness of two single mutants A and B deviates from the
expected fitness predicted for the double mutant AB by a multiplicative model. In this example, according to a
multiplicative model, the expected fitness of the double mutant is 0.35 (0.7 x 0.5). Synthetic enhancement
phenotypes show negative deviations from this value. The pink bar represents a synthetic sick interaction where cell
death, the extreme case of a negative GI, is termed synthetic lethall. Figure adapted from Costanzo et al., 2010. (B)
SL interactions resulting from the disruption of parallel nonessential pathways converging on the same biological
process are depicted. (C) Within pathway genetic interactions may occur when mutations combine to decrease the
activity of the same essential pathway or complex where a partial reduction of one essential component can be
tolerated but combining two partial loss alleles result in a SL interaction.
44
Correlation-based networks may be valuable in determining enzyme-substrate relationships
since they allow linking genotypes to phenotypes. Such interaction profiles for an enzyme or for
its positively regulated substrates should be highly correlated since the absence of either will
result in the same biological outcome. Even though GIs can be conserved from yeast to man, the
extent of this conservation is unclear. However it is possible that the properties of the network
may be highly conserved since they reflect the functional architecture of the cell.
1.6.4.1.2 Synthetic Dosage Lethality
Synthetic dosage lethality (SDL) is based on the idea that over-expression of a gene may cause a
clear phenotype, such as lethality, in a mutant with reduced activity of an interacting gene (Kroll
et al., 1996; Measday and Hieter, 2002; Measday et al., 2000). In contrast to SL interactions,
SDL relationships involve genes participating in the same pathway or in opposing pathways
(Figure 1-7). Typical SDL interactions are thought to take place when: 1) the over-expressed
gene product escapes regulation by the mutated gene product, mimicking a constitutively active
pathway (Figure 1-8A); 2) the over-expressed gene product and the mutated gene product
participate in a complex where stoichiometry is essential; 3) the over-expressed gene product
competes with or titrates out the mutated gene product further reducing its activity; or 4) the
over-expressed gene inhibits the function of the product of a third gene that is SL with the
mutated gene (Figure 1-8).
The first array-based SDL screen was performed by over-expressing 5800 yeast ORFs in the
absence of the CDK, PHO85 (Sopko et al., 2006b). From this screen, the transcription factors
Crz1 and Whi5, and the cell polarity proteins, Rga2 and Bni4 were identified as novel targets of
Pho85 (Huang et al., 2009; Sopko et al., 2006b; Sopko et al., 2007a; Zou et al., 2009). In another
example over-expression of CLB2, a cyclin regulated by the activity of the anaphase promoting
complex (APC), results in toxicity in a strain with reduced APC activity (Irniger et al., 1995).
Both examples highlight the potential of SDL to systematically identify novel enzyme targets.
SDL has also been used to identify genes encoding components of the yeast kinetochore and the
Origin Recognition Complex (Hyland et al., 1999; Kroll et al., 1996; Measday et al., 2005).
45
Figure 1-7 Synthetic dosage lethality
In this illustration X and Y represent two genes where either the over-expression of X or deletion of Y has no effect
on cell viability. When X is over-expressed in the absence of Y, cells are inviable, an interaction called dosage
lethality.
46
Figure 1-8 Mechanisms of synthetic dosage lethality
Synthetic dosage lethality, the enhancement of a mutant phenotype by increased dosage of another gene, may
reflect: (A) perturbed complex stoichiometry; (B) substrate escaping regulation by a PTM; (C) hyperactivation of an
opposing pathway. The left panel shows the wild-type scenario and the right panel shows the scenario resulting in
SDL.
47
1.6.4.2 Synthetic Genetic Array Analysis
To apply synthetic enhancement analysis at the level of entire genomes, techniques for
automated yeast genetics have been developed. Synthetic Genetic Array (SGA) analysis enables
the systematic assessment of genetic interactions in budding yeast (Tong et al., 2001). SGA
allows the high-throughput generation of yeast double mutants through a series of replica-
pinning steps that include mating, diploid selection, sporulation and selection for a haploid
output array where the two mutations are combined, all by gene-linked nutritional and drug
resistance markers.
SGA technology has arguably revolutionized yeast genomics since it permits the introduction of
any query mutation into any yeast array in an extremely high-throughput fashion. This approach
has been successfully used not only to generate double deletion mutants (discussed above) but
also to introduce fluorescently tagged proteins or transcriptional reporters to assess cell
biological changes or alterations in gene expression in specific deletion backgrounds
(Fillingham et al., 2009; Vizeacoumar et al., 2010). SGA analysis has also been adapted to
perform synthetic dosage lethal screens where deletion mutants are introduced into an array of
over-expression plasmids. In this array, each yeast ORF has been placed downstream of the
GAL promoter for inducible expression (Sopko et al., 2006b) (Figure 1-9). Through a series of
replica pinning steps onto selective media, a haploid output array can be generated where each
over-expression plasmid is now combined with a gene deletion. Here SDL coupled to SGA
effectively substitutes for thousands of transformations.
As noted earlier, systematic SDL screens have been used to identify targets of kinases (Sopko et
al., 2006b) and ubiquitin-binding proteins (Liu et al., 2009). I have extended this approach to
Class I and II KDACs in an attempt to map the lysine acetylome for these enzymes in yeast
(Chapter 3).
48
Figure 1-9 Synthetic dosage lethality screens using synthetic genetic array analysis
In the first step a MATα strain carrying a query mutation, in this case a lysine deacetylase deletion, is crossed to the
over-expression array, where each yeast ORF is under the control of the GAL promoter (MATa). The query mutation
is linked to a dominant selectable marker and each plasmid to another marker (URA3). Diploids are selected and
sporulated in the second and third steps. MATa haploids are selected in the next step utilizing a mating type-specific
reporter, after which over-expression is induced by pinning onto galactose-containing media. Figure adapted from
Sopko et al., 2006.
49
1.7 Summary and significance
The overall goal of my project has been to elucidate the interplay between chromatin remodeling
enzymes and cell cycle regulated transcription. In this Chapter, I provided an introduction to
yeast cell cycle-dependent transcription and the role of lysine acetyltransferases and deacetylases
in the context of transcription. The second part of my thesis involved a more general exploration
of the role of lysine deacetylases in yeast.
In Chapter 2, I describe my work that examined the conserved G1 transcriptional regulatory
pathway. I confirmed a second substrate of the CDK Pho85, Whi5, which had been identified in
the first array-based SDL screen (Sopko et al., 2006b). My work also revealed that, similar to its
mammalian counterpart Rb, Whi5 represses transcription by recruiting lysine deacetylases to G1
promoters. Multiple levels of regulation by a pair of kinases and a pair of KDACs highlight
mechanisms to guarantee the proper regulation of cell cycle transcription.
In Chapter 3, I extend array-based SDL screens to another group of conserved enzymes, Class I
and II KDACs, to examine their function in a more global fashion. I show that SDL uncovers
genetic interactions that are distinct from SL interactions and that, when integrated with SL data,
can predict novel functions for KDACs. Using Swi4 as an example, I illustrate that the initiation
of transcription at G1 is regulated not only by recruiting factors that activate and repress
transcription (Chapter 2) but is also by post-translational modification of the Swi4 transcription
factor itself to tightly regulate the G1-specific gene expression.
50
Chapter 2 Dual Regulation by Pairs of Cyclin-dependent Protein Kinases
and Histone Deacetylases Controls G1 Transcription in Budding Yeast
The work described in this chapter is published as:
Dongqing Huang*, Supipi Kaluarachchi*, Dewald van Dyk, Helena Friesen, Richelle Sopko,
Wei Ye, Nazareth Bastajian, Jason Moffat, Holly Sassi, Michael Costanzo, and Brenda J.
Andrews. Dual Regulation by Pairs of Cyclin-dependent Protein Kinases and Histone
Deacetylases Controls G1 Transcription in Budding Yeast. PLoS Biology September 9, 2009.
* These authors contributed equally to this work
Author contributions:
SK produced Figures 2-2B, 2-3B and C, 2-5, 2-6A, 2-9, 2-10, 2-12, 2-13 and wrote the
manuscript
DQH produced Figures 2-1, 2-2A and C, 2-4, 2-6B, 2-7, 2-8C, 2-11 and wrote the manuscript
HF produced Figures 2-8A and B and edited the manuscript
RS performed the genome-wide SDL screens identifying Whi5
JM produced Figure 2-3A
DVD WY NB and HS assisted with experiments
MC produced Figure 2-2D and assisted with writing of the manuscript
BA directed the project and writing of the manuscript
51
2 Abstract
START-dependent transcription in Saccharomyces cerevisiae is regulated by two transcription
factors SBF and MBF, whose activity is controlled by the binding of repressor Whi5.
Phosphorylation and removal of Whi5 by the CDK Cln3-Cdc28 alleviates the Whi5-dependent
repression on SBF and MBF, initiating entry into a new cell cycle. This Whi5-SBF/MBF
transcriptional circuit is analogous to the regulatory pathway in mammalian cells that features
the E2F family of G1 transcription factors and Retinoblastoma (Rb) tumor suppressor protein.
Here I describe genetic and biochemical evidence for the involvement of another CDK, Pcl-
Pho85, in regulating G1 transcription, via phosphorylation and inhibition of Whi5. A strain
deleted for both PHO85 and CLN3 has a slow growth phenotype, a G1 delay, and is severely
compromised for SBF-dependent reporter gene expression, yet all of these defects are alleviated
by deleting WHI5. The biochemical and genetic tests suggest Whi5 mediates repression in part
through interaction with two lysine deacetylases, Hos3 and Rpd3. In a manner analogous to
cyclin D/CDK4/6 which phosphorylates Rb in mammalian cells disrupting its association with
KDACs, phosphorylation by the early G1 CDKs Cln3-Cdc28 and Pcl9-Pho85 inhibits
association of Whi5 with the KDACs. Contributions from multiple CDKs may provide the
precision and accuracy necessary to activate G1 transcription when both internal and external
cues are optimal.
2.1 Introduction
CDKs act as molecular machines that drive cell division, and cell cycle progression. Three G1
cyclins, Cln1, Cln2 and Cln3, associate with Cdc28 to initiate events required for progression
through Start, a defined molecular program that initiates DNA replication, budding, spindle
maturation and chromosome segregation (Cross, 1995b).
As described in Chapter 1, a key feature of START is the induction of a transcriptional program
of over 200 genes facilitated by the TFs SBF and MBF (Bahler, 2005; Wittenberg and Reed,
2005). At the well-studied HO locus, prior recruitment and binding of the zinc-finger
transcription factor Swi5 followed by the recruitment of the Swi/Snf chromatin remodelling
complex and the SAGA lysine acetyltransferase complex are necessary to facilitate the
recruitment of SBF and the SRB/mediator complex to promoters (Bhoite et al., 2001; Cosma,
2002; Cosma et al., 1999). Subsequent recruitment of RNAPII and initiation of transcription is
52
dependent on CDK activity (Cosma et al., 2001). Although any one of the three G1 cyclins is
sufficient to drive Start, genetic studies indicate a key role for Cln3-Cdc28 in activating SBF and
MBF. Cln1 and Cln2 are also required for the proper execution of other Start-related events such
as budding and DNA synthesis. Cells lacking CLN3 are large and severely delayed for onset of
G1/S transcription, while ectopic induction of CLN3 in small G1 cells activates transcription and
accelerate passage through Start (Cross, 1995a).
In order to pass Start a critical cell size threshold, a barrier modulated by nutrient conditions,
among other regulatory inputs must be met (Jorgensen and Tyers, 2004). A systematic analysis
of cell size profiles for the entire set of yeast deletion mutants uncovered many new regulators of
Start including Whi5 and implicated it as an inhibitor of G1/S-specific transcription (Costanzo et
al., 2004; de Bruin et al., 2004). Whi5 occupies specific promoters early in G1 phase when CDK
activity is low. Phosphorylation of Whi5 by the CDKs Cln3-Cdc28 and Cln2-Cdc28 promotes
both the dissociation of Whi5 from SBF/MBF and its nuclear export, thus allowing the initiation
of G1-specific transcription (Costanzo et al., 2004; de Bruin et al., 2004). This Whi5-SBF/MBF
circuitry is analogous to the Rb-E2F pathway in mammalian cells (Refer to section 1.1.3 for
details).
A second yeast CDK, Pho85, originally discovered as a regulator of phosphate metabolism, has
since been shown to play numerous roles in the regulation of cell division and other processes
(Carroll and O'Shea, 2002; Moffat et al., 2000; Sopko et al., 2006a). Expression of three of the
Pho85 cyclins, PCL1, PCL2 and PCL9, is restricted to G1 phase of the cell cycle (Measday et al.,
1997). Specifically, PCL9 expression peaks early in G1 while maximal expression of PCL1 and
PCL2 is observed at Start and is dependent largely on SBF (Espinoza et al., 1994; Measday et
al., 1994; Tennyson et al., 1998). Although Pho85 is not essential for viability, it is required for
cell cycle progression in the absence of the Cdc28 cyclins, CLN1 and CLN2 (Measday et al.,
1994) and its absence leads to catastrophic morphogenic changes that culminate in a G2 arrest
(Moffat and Andrews, 2004). Consistent with this observation, inactivation of both Cdc28 and
Pho85 CDKs specifically inhibits expression of G1-regulated genes involved in polarized growth
(Kung et al., 2005).
As noted in Chapter 1, transcriptional repression by Rb has been linked to its interaction with
histone modification complexes, in particular KDACs. Many transcriptional activators interact
53
with KATs where as repressors are often associated with KDACs (Kadosh and Struhl, 1998b;
Krebs et al., 1999). Similar to their mammalian counterparts, Class I and II yeast KDACs are
recruited to promoters by sequence-specific regulatory factors to repress gene expression.
Recruitment of Rpd3 by Ume6 to the INO1 promoter (Kadosh and Struhl, 1998a, b; Rundlett et
al., 1998) and the recruitment of Hda1 by Tup1 are two such examples (Wu et al., 2001b).
In this Chapter, I provide detailed mechanistic insights into Whi5-dependent regulation of G1-
specific transcription and cell cycle progression. These experiments will identify Whi5 as the
first demonstrated physiological substrate for the G1-specific Pcl9-Pho85 CDK and provide
genetic and biochemical evidence supporting a direct role for Pho85 at Start. Also I will illustrate
that in a manner similar to Rb in mammalian cells, Whi5-mediated repression involves the
deacetylases, Rpd3 and Hos3. Dual phosphorylation of Whi5 by Cdc28 and Pho85 inhibits
Whi5 activity in at least two ways. Both kinases appear to regulate interaction of Whi5 with
different KDACs, while Cdc28 is also involved in disrupting Whi5 association with SBF and
promoting its nuclear export (Costanzo et al., 2004; de Bruin et al., 2004). G1-specific CDKs
thus are specialized to regulate different aspects of the same critical cell cycle event –inhibition
of Whi5 – resulting in definitive inactivation of the Whi5 repressor.
2.2 Experimental Procedures
2.2.1 Yeast strains, growth conditions and plasmids
The S. cerevisiae strains used are listed in Table 2-1. All gene disruptions and integrations were
achieved by homologous recombination at their chromosomal loci by standard PCR-based
methods and confirmed by PCR with flanking primers (Longtine et al., 1998). Standard methods
and media were used for yeast growth and transformation. Two percent of galactose in the
media was used to induce the expression of genes under GAL1 promoter. Synthetic minimal
medium with appropriate amino acid supplements was used for cells containing plasmids.
Appropriate amount of 3-aminotriazole (3-AT) was added to SD-HIS plates to assess the
expression of HIS3 reporter gene. Ten-fold serial dilutions of yeast cells were spotted onto
plates with appropriate nutrition conditions to assess growth. Plasmids used in this study are
listed in Table 2-2. In most cases, a DNA insert was amplified by PCR and inserted into a
linearized vector by homologous recombination in yeast.
54
Table 2-1: Strains used in this Chapter
Strain Genotype Source reference
BY186 BY263 MATa swi4∆HIS3 Baetz et al., 1999
BY263 MATa trp1 leu2 his3 ura3 lys2 ade2 Measday et al., 1994
BY391 BY263 MATa pho85∆LEU2 Measday et al., 1994
BY451 BY263 MATa pcl2∆LYS2 Measday et al., 1997
BY462 MATa leu2 his3 ura3 cdc28-13 M. Tyers
BY465 MATa leu2 his3 ura3 cdc28-4 M. Tyers
BY490 BY263 MATa pho80∆HIS3 Measday et al., 1997
BY628 BY263 MATa pcl1∆LEU2 Measday et al., 1997
BY653 BY263 MATa cln3∆URA3 This study
BY694 BY263 MATa pcl9∆HIS3 (Measday et al., 1997)
BY760 BY263 MATa pcl1∆LEU2 pcl9∆HIS3 Measday et al., 1997
BY764 BY263 MATa pcl1∆LEU2 pcl2∆LYS2 pcl9∆HIS3 Measday et al., 1997
BY867 BY263 MATa pho85∆TRP1 Measday et al., 1997
BY1502 Y2454 MATα pho85∆LEU2 Huang et al., 1999
BY2507 BY4741 MATa WHI5myc
::KANR M. Tyers
BY2948 BY4741 MATa cln3∆HPHR bck2∆NAT
R pGAL-CLN3 URA3 This study
BY4148 BY4741 MATa GALpr-HA-CDC20::KANR pho85∆NAT
R PCL9
myc This study
BY4151 BY4741 MATa GALpr-HA-CDC20::KANR This study
BY4152 BY4741 MATa WHI5myc
::KANR pho85∆NAT
R This study
BY4153 BY4741 MATa WHI5myc
::KANR cdc28-4 This study
BY4154 BY4741 MATa WHI5myc
::KANR cdc28-4 pho85∆NAT
R This study
BY4242 BY4741 MATa GALpr-HA-CDC20::KANRcln1∆NAT
R cln2∆HPH
R This study
BY4269 BY4741 MATα GALpr-HA-CDC20::KANRcln3∆LEU2 pho85∆NAT
R This study
BY4270 BY4741 MATα GALpr-HA-CDC20::KANRcln3∆LEU2 pho85∆NAT
whi5∆KANR
This study
55
BY4273 BY4741 MATa GALpr-HA-CDC20::KANRcln3∆LEU2 This study
BY4274 BY4741 MATa GALpr-HA- CDC20::KANR pho85∆NAT
R This study
BY4288 BY4741 MATa WHI5myc
::KANR cln3∆LEU2 This study
BY4289 BY4741 MATa WHI5myc
::KANR cln1∆NAT
R cln2∆ HPH
R This study
BY4290 BY263 MATa cln3∆TRP1 This study
BY4291 BY263 MATa cln3∆URA3 pho85∆LEU2 This study
BY4292 BY263 MATa cln3∆ URA3 pho85∆LEU2 whi5∆KANR This study
BY4293 BY263 MATa hos3∆KANR This study
BY4294 BY263 MATa rpd3∆NATR This study
BY4295 BY263 MATa hos3∆KANR
rpd3∆NATR This study
BY4296 BY263 MATa cln3∆TRP1 hos3∆KANR This study
BY4297 BY263 MATa cln3∆TRP1 rpd3∆NATR This study
BY4298 BY263 MATa cln3∆TRP1 hos3∆KANR rpd3∆NAT
R This study
BY4299 BY263 MATa pho85∆LEU2 hos3∆KANR This study
BY4300 BY263 MATa pho85∆LEU2 rpd3∆NATR This study
BY4301 BY263 MATa pho85∆LEU2 hos3∆KANR rpd3∆NAT
R This study
BY4302 BY4741 MATa ho∆::SCB:HIS3::URA3 This study
BY4303 BY4741 MATa ho∆::SCB:HIS3::URA3 cln3∆NATR This study
BY4304 BY4741 MATa ho∆::SCB:HIS3::URA3 pho85∆LEU2 This study
BY4305 BY4741 MATa ho∆::SCB:HIS3::URA3 cln3∆NATR pho85∆LEU2 This study
BY4306 BY4741 MATa ho∆::SCB:HIS3::URA3 cln3∆NATR pho85∆LEU2
whi5∆KANR
This study
BY4307 BY4741 MATa ho∆::SCB:HIS3::URA3 cln3∆NATR whi5∆KAN
R This study
BY4308 BY4741 MATa ho∆::SCB:HIS3::URA3 pho85∆LEU2 whi5∆KANR This study
BY4309 BY4741 MATa HOS1TAP
::HIS3 This study
BY4310 BY4741 MATa HOS2TAP
::HIS3 This study
BY4311 BY4741 MATa HOS3TAP
::HIS3 This study
56
BY4312 BY4741 MATa HDA1TAP
::HIS3 This study
BY4313 BY4741 MATa HDA2TAP
::HIS3 This study
BY4314 BY4741 MATa HDA3TAP
::HIS3 This study
BY4315 BY4741 MATa RPD3TAP
::HIS3 This study
BY4454 BY263 MATa whi5∆KANR This study
BY4455 BY263 MATa cln3∆URA3 pho85∆LEU2 hos1∆HIS5 This study
BY4456 BY263 MATa cln3∆URA3 pho85∆LEU2 hos2∆HIS5 This study
BY4457 BY263 MATa cln3∆URA3 pho85∆LEU2 hos3∆NATR This study
BY4458 BY263 MATa cln3∆URA3 pho85∆LEU2 rpd3∆NATR This study
BY4459 BY263 MATa cln3∆URA3 pho85∆LEU2 hda1∆HIS5 This study
BY4461 BY263 MATa cln3∆URA3 pho85∆LEU2 hos3∆KANR rpd3∆NAT
R This study
BY4462 BY2948 whi5∆KANR This study
BY4463 BY2948 hos1∆KANR This study
BY4464 BY2948 hos2∆KANR This study
BY4465 BY2948 hos3∆KANR This study
BY4466 BY2948 rpd3∆HIS5 This study
BY4467 BY2948 hda1∆HIS5 This study
BY4468 BY2948 hos3∆KANR rpd3∆HIS5 This study
BY4741 MATa leu2∆0 his3D1 ura3∆0 met15∆0 Tong et al., 2001
Y2454 MATα mfa1∆ MFApr-HIS3 can1∆ his3∆1 leu2∆0 lys2∆0 Tong et al., 2001
Of the wild-type strains used in this study, both BY263 and BY4741 are derived from S288C background. All the
other strains are derived from these two strains. BY263 is an ssd1-d strain; BY4741 is an SSD1-V strain and is the
parent strain for the yeast deletion consortium. Y2454 is congenic to BY4741 and is the parent for query strains used
in synthetic genetic array (SGA) experiments.
57
Table 2-2: Plasmids used in this Chapter
Name Relevant genotype Source
pEG-H pGAL1-GST URA3 2mm M. Snyder
pMT3164 pGAL-c-FLAG LEU2 CEN Y. Ho
pMT3446 GST-WHI5 in pGEX4T1 (E.coli Expression Vector) M. Tyers
pMT3586 pGAL-WHI5-FLAG LEU2 CEN Y. Ho
pBA230v pGPD TRP1 2mm M. Funk
pBA330v pGPD LEU2 2mm M. Funk
pBA1820 pGPD-HA-PCL1 LEU2 2mm This Study
pBA1821 pGPD-HA-PCL2 LEU2 2mm This Study
pBA1822 pGPD-HA-PCL9 LEU2 2mm This Study
pBA1823 pGPD-HA-PHO80 LEU2 2mm This Study
pBA1973 GST-WHI5 in pEG-H M. Snyder
pBA1974 pGAL-PCL9-FLAG LEU2 CEN Y. Ho
pBA1975 pMET-GST-WHI5 HIS3 CEN This Study
pBA1976 pGAL-8XLexAop-LacZ URA3 2mm This Study
pBA1977 pGPD-LexA TRP1 2mm This Study
pBA1978 pGPD-LexA-WHI5 TRP1 2mm This Study
pBA1979 pGPD-LexA-WHI512A
TRP1 2mm This Study
pBA1980 pGPD-WHI5 TRP1 2mm This Study
pBA1981 pMET-WHI5-GFP HIS3 CEN This Study
pBA2112 pGAL-HA-PCL9 URA3 2mm J. Moffat
pBA2239 GST-PCL1 in pGEX4T1 (E.coli Expression Vector) This study
pBA2240 GST-PCL2 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2241 GST-PCL9 in pAcGHLT (Baculovirus Transfer Vector) This study
58
pBA2242 GST-PHO80 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2243 GST-PHO85 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2244 GST-CLN2 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2245 GST-CLN3 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2246 GST-CDC28 in pAcGHLT (Baculovirus Transfer Vector) This study
pBA2247 pGAL-CLN2-FLAG LEU2 CEN Y. Ho
pBA2248 pGAL-CLN3-FLAG LEU2 CEN Y. Ho
pBA2249 pMET-GST-WHI512A
HIS3 CEN This Study
59
2.2.2 Kinase assays
The in vitro protein kinase assays monitored the incorporation of [32
P] transferred from α-32
P-
ATP to purified recombinant GST-Whi5. The reaction mixture for assays shown in Figure 2-2A
contained 50 mM Tris-HCl (pH7.5), 1 mM DTT, 10 mM MgCl2 and 1 µM ATP (including 20
µCi α-32
P-ATP ) and 0.2 µg GST-Whi5 in 20 µl of total volume. Two microliters of a purified
recombinant kinase (0.4 µg – 0.8 µg) was added to the mixture and incubated at 30oC for 30
minutes. Purification of Cln and Pcl CDKs from insect cell expression systems have been
previously described (Costanzo et al., 2004; Ptacek et al., 2005). Whi5 was then analyzed by
SDS-PAGE and autoradiography. Kinase assays on immunoprecipitated proteins from yeast cell
extracts were performed as described in Costanzo et al., 2004. Kinase assays preceding the
Whi5-SBF dissociation assay (Figure 2-8) were performed as described above except 200 µM of
α-32
P-ATP was used instead of 1 µM. The final concentration of Cln3 and Pcl9 was 3 µM and
the final concentration of Cln2 was 60 nM (50-fold less).
2.2.3 Quantitative β-galactosidase assays
Liquid β-galactosidase assays were performed as described in Measday et al., 1999. Strains
carrying appropriate plasmids were grown in synthetic minimal medium to mid-log phase,
transferred to synthetic galactose medium, and incubated for four hours. Cells were harvested
and lysed in buffer (100 mM Tris-HCl (pH8.0), 1 mM DTT and 20% glycerol with protease
inhibitors) with glass beads. The β-galactosidase activity was determined by adding 100 µl of
total cell extract to 0.9 ml of Z buffer (100 mM Na2PO4, 40 mM NaHPO4, 10 mM KCl, 1mM
MgSO4 and 0,027% β-mercaptoethanol) and 200 µl ONPG (4 mg/ml) (Sigma). Units of β-
galactosidase activity were determined as described (Measday et al., 1994).
2.2.4 Whi5 dissociation with SBF complex in vitro
The protein binding assay essentially followed the procedures described previously (Costanzo et
al., 2004). Briefly, 1 µl of insect cell lysate expressing SBF (Swi6-Swi4FLAG
) was mixed with 1
µl of purified GST-Whi5 (~0.1 µg) and 7 µl of M2 anti-FLAG resin (Sigma) in 8µl of kinase
buffer (50 mM Tris-HCl (pH7.5), 1 mM DTT and 10 mM MgCl2). The mixture was incubated at
4oC for one hour with mixing. The beads bound to the SBF-Whi5 complex were then washed
three times with kinase buffer, and mixed with various cyclin dependent kinases in kinase buffer
with 0.2 mM ATP in a 20 µl volume. The kinase reaction was incubated at 30oC for one hour.
60
The soluble portion was taken out and mixed with 20 µl of 2XSDS-PAGE loading buffer. The
beads in the tube were washed three times with kinase buffer before mixing with 15 µl of
2XSDS-PAGE loading buffer.
2.2.5 Liquid Growth Assays
Strains containing galactose-inducible plasmids were grown to saturation in 2% raffinose media
for 48hrs. Expression of plasmids were induced by transferring into 2% raffinose 2% galactose
media and liquid growth assays were performed as previously described over 36 hours using a
Tecan GENios microplate readers (Tecan) (Lee et al., 2005). Average doubling (AveG) for each
culture was calculated as previously described (Lee et al., 2005). Growth rate for each mutant
was calculated relative to the AvgG of the wild-type strain.
2.2.6 Whi5-GFP Localization
The localization of Whi5-GFP was monitored in wild type, cdc28-4 and pho85∆ strains. Cells
expressing pMET-GFP-WHI5 were grown to log phase in synthetic glucose medium without
methionine. Cells were observed at a magnification of 1000X using Nomarski optics and
fluorescence microscopy and photographed by a Cascade 512B high-speed digital camera
(Roeper Scientific) mounted on a Leica DM-LB microscope. Images were captured and analyzed
by MetaMorph software (Universal Imaging Media, PA).
2.2.7 Chromatin immunoprecipitation
The pho85∆ PCL9MYC
GALpr-CDC20 and pho85∆whi5∆PCL9MYC
GALpr-CDC20 cells were
grown in YP-Galactose (YPG) medium to an optical density (OD600) of 0.4, blocked at M phase
by growing in YPR medium for 3 hours, and released into YPG medium. Samples were taken
every 15 minutes after release and cross-linked with a final concentration of 1% formaldehyde.
Wild-type and swi4∆strains (for controls) were grown to OD600 of 0.6 in YPD. Formaldehyde
cross-linking and preparation of whole-cell extracts were performed as previously described
(Baetz et al., 2001). Immunoprecipitation were performed using 1:200 dilution of α-myc
monoclonal antibody (9E10) a α-Swi6 or α-Swi4 polyclonal antibodies. The precipitates were
washed twice with lysis buffer, once with LiCl detergent and once with Tris-buffered saline and
processed for DNA purification. Enrichment at the CLN2 promoter sequence was quantified
61
with real-time PCR, using a dual fluorogenic reporter TaqMan assay in an ABI PRISM 7500HT
Sequence Detection System as previously described (Costanzo et al., 2004).
2.2.8 Other materials and methods
Recombinant GST-Pcl1 and GST-Whi5 were produced in a BL21 bacterial expression strain;
other recombinant proteins were produced in insect cells infected with Baculovirus expression
vectors (Dasgupta et al., 2006; Jorgensen and Tyers, 2004; Ptacek et al., 2005). Proteins were
detected with 9E10 anti-Myc, 12C5 anti-HA and M2 anti-FLAG monoclonal antibodies. FACS
analysis of DNA content and cell size measurements were described previously (Jorgensen et al.,
2002).
2.3 Results
2.3.1 A Synthetic Dosage Lethality screen identifies Whi5, as a putative substrate for the cyclin-dependent kinase, Pho85
An SDL screen completed previously for pho85∆ identified known targets of Pho85 as well as
several novel substrates of this CDK (Sopko et al., 2006b; Sopko et al., 2007a; Zou et al., 2009).
The G1-specific transcriptional repressor, Whi5, was among this list of candidate Pho85
substrates. To further explore the role of Pho85 in G1 phase-specific transcription we examined
the WHI5-PHO85 SDL interaction in greater detail. Since Pho85 activity and substrate
specificity depends on its interaction with cyclin subunits (Measday et al., 1997) to implicate a
specific Pcl-Pho85 complex in modulating Whi5 function we examined the effects of WHI5
over-expression in cells lacking different Pho85 cyclins (Figure 2-1). Similar to effects
observed in cln3∆ and cln1∆cln2∆ mutants (Costanzo et al., 2004) the over-expression of WHI5
resulted in growth inhibition of pcl1∆ and pcl9∆ deletion strains and which was exacerbated in a
pcl1∆ pcl9∆ double mutant (Figure 2-1). Unlike pcl1∆ or pcl9∆ mutants, strains lacking PCL2
or PHO80 cyclins were not adversely affected by increased WHI5 dosage suggesting that the
WHI5-PHO85 genetic interaction is dependent on the PCL1,2 cyclin sub-family and more
specifically on PCL1 and PCL9 (Figure 2-1). This observation is consistent with the fact that
Pcl1 and Pcl9 (but not Pcl2) are the two G1-specific cyclins that localize to the nucleus (Moffat
and Andrews, 2004; Sopko et al., 2007a). Based on these results, Pcl1/9-Pho85 may contribute
to Whi5 regulation in a manner similar to Cln3-Cdc28.
62
Figure 2-1: WHI5 over-expression is toxic to strains compromised for Pho85 CDK activity.
Isogenic wild-type, pho85∆, pcl1∆, pcl2∆, pcl9∆, pcl1∆pcl9∆ and pho80∆ strains bearing either GAL1-WHI5 or
empty vector control (pEG-H) were spotted in serial 10-fold dilutions on galactose media and incubated for 72 hr at
30oC.
63
2.3.2 Whi5 is a substrate for Pcl9-Pho85 phosphorylation.
The genetic interactions described above suggest Whi5 may be a direct target of Pho85.
Evidence supporting this hypothesis is provided by protein chip assays where Whi5 is
phosphorylated in vitro by Pcl1-Pho85 (Ptacek et al., 2005). We characterized the Whi5-Pho85
(de Bruin et al., 2004; Wagner et al., 2009)CDK complexes and purified Whi5 as substrate
(Figure 2-2A). Incorporation of [32
P] into Whi5 was not detected in the absence of CDKs
(Figure 2-2A, lane 4). However, Whi5 phosphorylation was observed in the presence of Pcl1-
and Pcl9-Pho85 (Figure 2-2A, lanes 1, 2) and when compared to Cln2-Cdc28 kinase activity,
Pho85 and Cdc28 phosphorylate Whi5 at similar levels in vitro (Figure 2-2A, cf lanes 1-3).
Previous studies revealed multiple Whi5 slow-migrating isoforms that correlates with its
phosphorylation state (de Bruin et al., 2004; Wagner et al., 2009). I examined the effect of
various cyclin or CDK mutants on Whi5 mobility (Figure 2-2B). ). Due to genetic redundancy
of Pcls (Tennyson et al., 1998) I was unable to reproducibly detect changes in Whi5
phosphoforms in cyclin mutant strains. Therefore, a Pho85 mutant was used to assess the
phosphorylation status of Whi5. Consistent with previous findings (Costanzo et al., 2004; de
Bruin et al., 2004), slow migrating Whi5 isoforms present in asynchronous wild-type extracts
(Figure 2-2B, lane 1) were modestly reduced in cells lacking CLN3 (Figure 2-2B, lane 7) and
completely absent in a cln1∆cln2∆ double mutant (Figure 2-2B, lane 6), confirming that Whi5
phosphorylation depends on Cln-Cdc28 kinase complexes. Consistent with our SDL results and
in vitro kinase assays, I observed a significant reduction in Whi5 mobility in extracts from a
Pho85 mutant strain (Figure 2-2B, lane 2). Thus, similar to Cdc28, phosphorylation of Whi5
also depends on Pho85 in vivo. To determine if Whi5 physically associates with Pho85 in yeast,
we first assayed Whi5FLAG
immune complexes for kinase activity. A robust autophosphorylation
activity was recovered from Whi5FLAG
immunoprecipitates derived from wild-type cell extracts
when radiolabelled ATP was added to the immunoprecipitated sample. (Figure 2-2C, lane 2).
This activity was partially dependent on both CDC28 and PHO85 (Figure 2-2C, lane 3-5). We
also confirmed a physical interaction between Whi5 and Pho85 cyclins using a co-
immunoprecipitation assay (Figure 2-2D). Immunoprecipitation of Whi5MYC
from epitope-
tagged cyclin extracts revealed a specific association between Pcl9 and Whi5 (Figure 2-2D, lane
4). We failed to reproducibly detect a physical interaction between Whi5 and Pcl1 (Figure 2-
2D, lane 2) suggesting that Pcl9-Pho85 is the primary Whi5 CDK. Taken together, the
64
phosphorylation and co-immunopreciptiation assays strongly suggest that, in addition to Cdc28,
Pho85 also phosphorylates Whi5. Furthermore these results identify Whi5 as the first reported
substrate for Pcl9-Pho85, one of two Pho85 cyclins whose activity is restricted to early G1
phase.
65
Figure 2-2: Whi5 is a substrate for Pcl9-Pho85 CDK-dependent phosphorylation.
(A) In vitro phosphorylation of Whi5 by Pho85 kinase. Purified Whi5GST
and α-32
P-ATP were incubated alone (lane
4) or in the presence of recombinant Pcl1-Pho85 (lane 1), Pcl9-Pho85 (lane 2) or Cln2-Cdc28 (lane 3) kinases.
Phosphorylated Whi5 protein was resolved by SDS-PAGE and autoradiography. (B) Slower-migrating forms of
Whi5 are dependent on Cdc28 and Pho85. Cell extracts were prepared from wild-type, pho85∆ (lane 2) cdc28-4
(lane 4), cdc28-4 pho85∆ (lane 5), cln1∆cln2∆ (lane 6) and cln3∆ (lane 7) strains expressing WHI5MYC
along with a
whi5∆ control strain (lane 3). Cells were grown at 30oC (semi-permissive temperature for cdc28-4 strains) to log
phase (OD=0.6) before harvesting. cdc28-4 cells were placed at 37oC for 2 hours to inactivate Cdc28 before
harvesting. Whi5MYC
mobility was assessed by immunoblotting. (C) Whi5 associates with Pho85-dependent kinase
activity. Wild-type, cdc28-4, cdc28-13 or pho85∆ bearing a GAL-WHI5FLAG
plasmid (pMT3586) or control vector
control were grown at 30 oC (semi-permissive temperature for cdc28-4 and cdc28-13 strains) in galactose media for
3 hr. Whi5 complexes were recovered on anti-FLAG resin, incubated in kinase buffer with α-32
P-ATP at 30oC and
resolved by SDS-PAGE. Capture of Whi5 protein was detected with anti-FLAG antibody. (D) Whi5 interacts with
the Pho85 cyclin, Pcl9. Anti-MYC immune precipitates of WHI5MYC
strain lysates bearing either PCL1HA
(lane 2),
PCL2HA
(lane 3), PCL9HA
(lane 4), PHO80HA
(lane 5) or a vector control (lane 1) were probed with 9E10 anti-MYC
and 12CA5 anti-HA antibodies.
A B
66
Whi5 associates indirectly with G1 phase-regulated promoters through interaction with SBF and
MBF. Interactions with these transcription factors and subsequent promoter binding are disrupted
by CDK-dependent phosphorylation (Costanzo et al., 2004; de Bruin et al., 2004). Because
Whi5 appears to be a Pho85 substrate, we assessed the occupancy of SBF promoters by Pcl9. To
date, cyclins have not been detected at yeast promoters. Pcl9 is normally an unstable short-lived
protein (Tennyson et al., 1998); however, similar to other cyclins, Pcl9 turnover appears to be
catalyzed in part by its cognate CDK, Pho85 (Figure 2-3A) (Jackson et al., 2006). Therefore, to
test Pcl9 promoter localization in a more sensitive genetic background, I performed chromatin
immunoprecipitation experiments in a pho85∆ strain (Figure 2-3B). The highest levels of CLN2
promoter DNA were detected in Pcl9MYC
immune complexes 30 minutes following release from
a metaphase-anaphase arrest (Figure 2-3B). The Pcl9-chromatin association was no longer
detectable 45 minutes after GAL-CDC20 induction indicating that the interaction is short-lived
and transient as predicted for a regulator of Start. The association is Whi5-dependent since Pcl9
is not detected at the CLN2 promoter in a strain lacking Whi5 (Figure 2-3C). The localization of
Pcl9 to CLN2, a G1 promoter is consistent with a direct role for Pcl9-Pho85 in regulating G1
transcription.
67
Figure 2-3 Pcl9 localizes to G1-specific promoters in a cell cycle-dependent manner.
(A) Pho85 regulates Pcl9 protein stability. Wild-type and pho85∆ strains harboring a GAL1-PCL9HA
plasmid were
grown to exponential phase in galactose media (lane 1). PCL9 expression was repressed by addition of glucose to
final concentration of 2% and cells were harvested 10 (lane 2), 30 (lane 3) and 90 (lane 4) minutes after addition of
glucose. Pcl9 abundance was assessed by immunoblotting using 12CA5 anti-HA antibodies. (B) Pcl9 localizes to
SBF-dependent promoters. An exponentially growing GAL1-CDC20 pho85∆PCL9MYC
strain (lane 1) was arrested at
M/G1 phase in glucose-containing medium (lane 2). Cultures were harvested 15 (lane 3), 30 (lane 4), 45 (lane 5) and
60 (lane 6) minutes after release from CDC20-induced arrest in galactose medium. Cell cycle progression was
monitored by FACS analysis. Anti-MYC and anti-Swi6 chromatin immunoprecipitations from the indicated strains
were analyzed for CLN2 promoter sequences by quantitative RT-PCR. (C) In a strain lacking Whi5, GAL1-CDC20
pho85∆ whi5∆PCL9MYC
, Pcl9 no longer localizes to the CLN2 promoter. Anti-Swi4 chromatin immunoprecipitations
is shown as a positive control.
A B
C
68
2.3.3 Pcl9-Pho85 regulates Whi5 function via phosphorylation.
As mentioned above, cln3∆ mutants arrest in G1 phase as large unbudded cells in response to
increased WHI5 dosage, indicating that Whi5 is a dose-dependent regulator of Start. Therefore,
if Pho85 and Cdc28 function analogously to inhibit Whi5 activity, we predict that elevated
Pho85 kinase activity would antagonize the toxic effects of WHI5 overexpression and suppress
the growth defects observed in a cln3∆ mutant. To test this prediction, high copy plasmids
expressing PCL1, PCL2, PCL9 or PHO80 were introduced into a cln3∆ strain expressing WHI5
from a conditional MET25 promoter (Figure 2-4A). Plasmid-based expression of Pcls and Whi5
was confirmed by immunoblotting (Figure 2-5). Induction of WHI5 expression in a cln3∆
mutant resulted in cell death whereas overexpression of PCL1 or PCL9 partially suppressed this
toxicity and restored growth (Figure 2-4A). Consistent with results from SDL analyses (Figure
2-1), this suppression was specific to PCL1 and PCL9 since neither PCL2 nor PHO80 were able
to function effectively in the assay (Figure 2-4A). Furthermore, PCL1/9-mediated suppression
was dependent on phosphorylation since growth of a cln3∆ mutant expressing a non-
phosphorylatable form of WHI5 (Whi512A) (Costanzo et al., 2004) could not be restored
(Figure 2-4A). These genetic results corroborate the biochemical evidence that Pcl-Pho85
regulates Whi5 activity through phosphorylation.
Given its effect on WHI5 overexpression, we next examined PCL effects on other CLN3-
associated phenotypes. CLN3 is required to activate G1-specific transcription once cells have
achieved a critical size (Dirick et al., 1995; Stuart and Wittenberg, 1995; Tyers et al., 1993). A
cln3∆ mutant exhibits a large cell size phenotype due to its inability to inhibit Whi5 and activate
Start-specific transcription (Costanzo et al., 2004; de Bruin et al., 2004). Ectopic expression of
PCL1 or PCL9 reduced cln3∆ cell size to an intermediate level between that of wild type and
cln3∆ cells (Figure 2-4B). Conversely, deletion of PCL9, PCL1 and the partially redundant
cyclin, PCL2, resulted in a cell size increase (Figure 2-4C). These results suggest that Pcl-
Pho85 and Cln3-Cdc28 share a common role in cell cycle progression to regulate Whi5 activity
and promote passage through Start.
69
A
Figure 2-4: PHO85 affects growth and cell size defects associated with cln3∆.
(A) Ectopic PCL1 and PCL9 expression alleviates WHI5 toxicity in a cln3∆ strain. A cln3∆ strain bearing a
methionine-repressible WHI5GST
or WHI512A-GST
low-copy plasmid along with an additional vector control, PCL1HA
,
PCL2HA
(pBA1821, PCL9HA
(pBA1822) or PHO80HA
(pBA1823) construct were spotted in serial 10-fold dilutions
on media supplemented with or lacking methionine (WHI5 “OFF”, WHI5 “ON”, respectively) and incubated for 72
hr at 30oC. (B) PCL1 and PCL9 cyclins modulate cell size. Cell size distributions were analyzed for wild-type and
cln3∆ strains bearing vector control, PCL9HA
(pBA1822) or PCL1HA
plasmids. The median cell volume based on
three replicates was: 42.33 fl ± 1.13 (wild-type + vector control) ; 71.78 fl ± 1.43 (cln3∆ + vector control); 55.67 fl ±
1.66 ( + PCL1); 54.25 fl ± 1.21 (cln3∆ + PCL9). (C) Cells lacking PHO85 G1 cyclins exhibit an enlarged
cell size. Cell size distributions were analyzed for wild-type (BY263), pcl1∆ pcl2∆ pcl9∆ (BY764) and cln3∆strains
(BY653). The median cell volume based on three replicates was: 46.73 fl ± 0.63 (wild-type); 53.96 fl ±0.75 (pcl1∆
pcl2∆ pcl9∆); 72.72 fl ± 1.22 (cln3∆).
70
Figure 2-5: Expression levels of epitope-tagged Whi5 and Pho85 cyclins.
Whi5 and Pho85 cyclin abundance in the indicated strains was determined by immunoblotting. Cyclin proteins were
detected using 12CA5 anti-HA antibodies while Whi5 protein was detect using anti-GST antibodies.
71
2.3.4 CDC28 and PHO85 function in parallel pathways to regulate Whi5 function
To determine if Pcl-Pho85 and Cln3-Cdc28 might function in parallel to regulate Start, we first
tried to test whether pcl9∆ cln3∆ or pcl1∆ pcl9∆ cln3∆ strains showed any synthetic growth
defects. As expected, no growth defects were observed, probably due to the redundant effects of
other Pcls (Tennyson et al., 1998). Unlike the Cdc28 cyclins, which showed distinct cell cycle
expression pattern, most Pcls are expressed at all cell cycle stages (Measday et al., 1997). I then
examined the phenotype of a pho85∆cln3∆ double mutant. Cells lacking cln3∆ are larger than
wild type cells but do not display overt defects in growth rate while pho85∆ mutants are slow
growing (Figure 2-6A). However, pho85∆cln3∆ double mutants exhibit a more pronounced
growth defect compared to single mutants and analysis of DNA content revealed that the pho85∆
cln3∆ double mutant cells accumulate in G1 phase with predominantly unreplicated DNA
(Figure 2-6A). Importantly, deleting WHI5 overcame both the cell cycle progression and
growth defects observed in the absence of both CLN3 and PHO85. Notably, a
pho85∆cln3∆whi5∆ triple mutant exhibited a growth rate similar to a cln3∆ single mutant
indicating that Pcl-Pho85 and Cln3-Cdc28 function in separate yet converging pathways to
regulate Whi5 function and, by extension, G1 cell cycle progression (Figure 2-6A). These
observations also hold true under liquid growth conditions as shown. WHI5-dependent
suppression appears to be specific to the pho85∆cln3∆ phenotype because WHI5 deletion was
unable to rescue 53 additional synthetic lethal interactions involving PHO85.
Given that Whi5 represses SBF- and MBF-specific transcription, we asked whether PHO85
affects SBF-driven reporter gene expression. A reporter gene consisting of tandem SCB
consensus element repeats fused upstream of the HIS3 coding region was constructed and
integrated into wild-type, cln3∆ and pho85∆ strains. Previous work has shown that this reporter
provides a highly specific read-out for SBF-dependent transcription (Costanzo et al., 2004;
Costanzo et al., 2003). Growth on medium lacking histidine supplemented with 3-aminotriazole
(3-AT) was used to assess SBF transcriptional activity (Figure 2-6B). Even though cells lacking
PHO85 were moderately sensitive to higher concentration (5 mM) of 3-AT (data not shown),
both cln3∆ and pho85∆ mutants showed no growth in media containing 30mM 3-AT indicating
that SBF transcription is impaired in these mutants, whereas growth of wild-type cells was
unaffected (Costanzo et al., 2004). Furthermore, defects in SCB-driven gene expression were
72
more pronounced in the pho85∆ cln3∆ double mutant (at 10 mM 3-AT, Figure 2-6B). Consistent
with the genetic interactions described above (Figure 2-6A), SBF-dependent reporter activity
was restored in pho85∆cln3∆ mutants when WHI5 was deleted (Figure 2-6B). However, WHI5
deletion only partially rescued the growth defect in pho85∆ cells at 30 mM of 3-AT (Figure 2-
6B). The Whi5-independent 3-AT sensitivity of pho85∆ cells may be due to the unregulated
Gcn4 in the absence of PHO85, since GCN4 is induced by 3-AT and Pho85 has been shown to
regulate Gcn4 stability (Meimoun et al., 2000; Shemer et al., 2002). Nonetheless, these data
suggest that, like Cln3-Cdc28, Pcl-Pho85 modulates SBF activity through Whi5.
73
Figure 2-6: PHO85 regulates G1 transcription via WHI5.
(A) The G1 delay phenotype associated with a cln3∆pho85∆ strain is dependent on WHI5. Wild type, cln3∆,
pho85∆, cln3∆pho85∆ and cln3∆pho85∆whi5∆ strains were spotted in serial 10-fold dilutions on rich media
(YPED) and incubated for 24 hr at 30oC. DNA content of exponentially growing cultures was determined by FACS
analysis. Liquid growth assays were also performed for these strains and growth rate is reported relative to wild type
as shown in the bar graph. Graphical representations of growth rates are shown above the bar graph as line plots,
where the upper red line represents the growth of WT and the black line shows the growth of each mutant (B) A
cln3∆pho85∆ strain exhibits defects in SCB-driven gene expression. Wild-type, cln3∆, pho85∆, cln3∆pho85∆,
cln3∆pho85∆whi5∆, pho85∆whi5∆ and cln3∆whi5∆ strains harboring an integrated SCB-HIS3 reporter were spotted
in serial 10-fold dilutions on histidine-containing medium or media lacking histidine and supplemented with 10 or
30 mM 3-AT. Plates were incubated at 30oC for 48 hr. We note that the synthetic growth defect of a cln3 pho85
mutant is most pronounced on rich medium (A), and is not as evident when strains are grown on minimal medium.
AAA
B
74
We next interrogated the effects of CDK activity on Whi5-mediated transcriptional repression
(Figure 2-7). A construct expressing a LexA DNA binding domain fused to WHI5 was
introduced into a strain harboring a LacZ reporter gene containing LexA binding sites in its
promoter (Figure 2-7). Consistent with its role as a negative regulator of G1-specific
transcription, a ~10-fold reduction in β-galactosidase activity was observed in cells expressing
the LexA-Whi5 fusion protein compared to a vector control (Figure 2-7). Overexpression of
PCL9, CLN3 or CLN2 restored LacZ expression to intermediate levels indicating that activation
of either CDC28 or PHO85 was capable of antagonizing Whi5 function in this assay (Figure 2-
7). Consistent with suppression of WHI5-mediated growth defects (Figure 2-4), inhibition of
Whi5 activity was dependent on phosphorylation since LacZ expression could not be restored in
cells harboring an unphosphorylatable LexA-Whi512A
fusion protein (Figure 2-7).
75
Figure 2-7: Whi5-mediated transcriptional repression is antagonized by PHO85 and CDC28.
A reporter gene consisting of eight LexA binding sites flanked by the GAL1 promoter and the LacZ coding sequence
was constructed. β-galactosidase activity (upper histogram) was measured in a wild-type strain bearing the LacZ
reporter along with one of the following: a vector control; a LexA expressing plasmid; or a construct expressing a
LexA-Whi5 fusion protein. β-galactosidase activities were also assayed (lower histogram) in a wild-type strain
harboring the LacZ reporter construct alone (vector control) or over-expressing the G1 cyclins, PCL9, CLN2 or
CLN3 in the presence of LexA-Whi5 or LexA-Whi512A
fusion proteins.
76
2.3.5 Pho85 does not regulate Whi5 localization or its interactions with G1-specific transcription complexes
Cln2-Cdc28 activity was previously shown to disrupt recombinant Whi5-SBF complexes in vitro
(Costanzo et al., 2004) but Cln3-Cdc28 and Pho85 kinase had not been assessed for this activity.
A preassembled recombinant Whi5-Swi4FLAG
-Swi6 complex bound to anti-FLAG resin was
incubated with purified kinases in the presence of radiolabelled ATP and separated into soluble
(Figure 2-8B, labeled “S”) and bound fractions (Figure 2-8B; labeled “B”). Equivalent
amounts of kinase were approximated based on in vitro kinase activity (Figure 2-8A and
Experimental Procedures). As expected, Cln2-Cdc28 phosphorylation caused most of the SBF-
bound Whi5 to be released into the soluble fraction (Figure 2-8B, lanes 3-4). In contrast, we
failed to observe dissociation of Whi5 from SBF in the presence of Cln3- or Pcl9-CDK
complexes (Figure 2-8B, lanes 5-10). In addition to negatively regulating the interaction of
Whi5 with SBF, Cdc28 also controls its localization (Costanzo et al., 2004). Unlike Cln-Cdc28
phosphorylation which promotes Whi5 export from the nucleus, deletion of PHO85 did not
dramatically affect the sub-cellular localization of Whi5 (Figure 2-8C). Together, these results
suggest that Pho85 must regulate Whi5 function through alternate mechanisms.
77
A
B
C
Figure 2-8: Pho85 does not affect known Whi5 regulatory mechanisms.
(A) Determination of relative Cdc28 and Pho85 kinase activity. In vitro kinase assays using varying amounts of
recombinant Cln2-Cdc28, Cln3-Cdc28 and Pcl9-Pho85 in the absence (Lane 1, 2, 3) or presence of purified Whi5
(Lane 5, 6, 7, 8) were conducted and the degree of Whi5 phosphorylation was determined by SDS-PAGE and
autoradiography. Purified Whi5 and α-32
P-ATP were incubated in the absence of kinase in lane 8 and Lane 4 is
empty. A 3 µM final concentration of Cln3-Cdc28 and Pcl9-Pho85 and a 60 nM final concentration of Cln2-Cdc28
give similar amounts of 32
P-incorporation in Whi5, although phosphorylation by Cln2-Cdc28 caused Whi5 to
migrate more slowly than Whi5 phosphorylated by Cln3-Cdc28 or Pcl9-Pho85. The concentration of kinase used in
(B) was based on these experiments. (B) Cln3-Cdc28 and Pcl9-Pho85 do not influence Whi5-SBF complex
stability. A preassembled recombinant Whi5-Swi4FLAG
-Swi6 complex bound to anti-FLAG resin was incubated
with Cln2-Cdc28, Cln3-Cdc28, Pcl9-Pho85 or both Cln3-Cdc28 and Pcl9-Pho85 in the presence of radiolablled
ATP. After washing, proteins in the bound and supernatant fractions were identified by autoradiography. (C)
Subcellular localization of Whi5 in cdk mutant strains. Wild-type, pho85∆ and cdc28-4 strains expressing WHI5GFP
from a methionine-repressible promoter were examined for Whi5GFP
fluorescence. Representative fields are shown.
78
2.3.6 Mechanism for Whi5-mediated transcriptional repression by Pho85
I next explored what additional mechanism might explain Pcl- and Cln3-mediated regulation of
Whi5 activity. Functional conservation clearly extends to Whi5 and its metazoan analogue, Rb
(Schaefer and Breeden, 2004). Since Rb represses transcription, in part, through recruitment of
KDACs, I used a batch affinity chromatography assay to test for physical interactions between a
Whi5GST
ligand and tandem affinity tagged-KDACs (Figure 2-9A). Specific interactions
between Whi5 and Hos3, Rpd3 and, to a lesser extent, Hos1 were identified (Figure 2-9A; lanes
1, 5, 13) suggesting that, like Rb, Whi5-dependent transcriptional repression involves
recruitment of histone deacetylases. This observation is consistent with previous work which
detected Rpd3 at the PCL1 promoter using a ChIP assay (Robert et al., 2004). Furthermore,
HOS3 and RPD3 were required for WHI5 dose-dependent effects on cell size. Like wild-type
cells, strains lacking either HOS3 (Figure 2-9B; Panel 1) or RPD3 (Figure 2-9B; Panel 2) also
exhibited a dose-dependent increase in cell size in response to WHI5 over-expression. However,
additional cell size effects were not observed in strains lacking both KDACs suggesting that
Hos3 and Rpd3 regulate Whi5 function synergistically (Figure 2-9B; Panel 3).
79
Figure 2-9: Whi5 function is dependent on KDAC activity.
(A) Whi5 associates with Hos3 and Rpd3. Lysates prepared from the indicated epitope-tagged KDAC strains
harboring a vector control (pEG-H) or construct expressing WHI5GST
were incubated with glutathione sepharose
beads. Whi5GST
-KDAC interactions were detected by immunoblot using α-GST and α-PAP antibodies. (B) Hos3
and Rpd3 modulate Whi5 cell size effects. A plasmid expressing WHI5 or vector control were introduced into wild-
type, hos3∆, rpd3∆ and hos3∆ rpd3∆ strains and cell size distributions were measured. Each panel corresponds to a
specific mutant and wild-type distributions are superimposed in each panel. The median cell volume based on three
replicates was: 42.06 fl ± 1.09 (wild-type + vector control; blue); 73.12 fl ± 1.16 (wild-type + WHI5; black); 30.57 fl
± 1.23 (hos3∆ + vector control; panel 1, red); 71.35 fl ± 1.59 (hos3∆ + WHI5; panel 1, green); 51.20 fl ± 1.73
(rpd3∆ + vector control; panel 2, red); 69.75 fl ± 2.79 (rpd3∆ + WHI5; panel 2, green); 45.62 fl ± 1.22 (hos3∆rpd3∆
+ vector control; Panel 3, red); 50.26 fl ± 1.14 (hos3∆rpd3∆ + WHI5; Panel 3, green).
Rp
d3
Ta
p
Hd
a2
Ta
p
Hd
a1
Ta
p
Ho
s3T
ap
Ho
s2T
ap
Ho
s1T
ap
Hd
a3
Ta
p
Gst-W
hi5
72 KD
95KD
130KD
A
Vecto
r
Gst-W
hi5
Vecto
r
Gst-W
hi5
Vecto
r
Gst-W
hi5
Vecto
r
Gst-W
hi5
Vecto
r
Gst-W
hi5
Vecto
r
Gst-W
hi5
Vecto
r
IP-Western
HDAC-TAPs in
cell extracts
GST-Whi5 in
cell extracts
72 KD
95KD
130KD
56 KD
80
If KDACs are required for Whi5 function, then strains lacking KDAC function should be
resistant to toxic effects associated with WHI5 over-expression. Consistent with this prediction,
the growth defect caused by WHI5 overproduction in a cln3∆ was alleviated by the deletion of
HOS3 and RPD3 (Figure 2-10A). Deletion of HOS3 alone rescued WHI5 toxicity in a pho85∆
strain while a cln3∆ mutant required deletion of both HOS3 and RPD3 in order to tolerate
increased dose of WHI5 (Figure 2-10A).
Given that Whi5 appears to be acting through KDACs, I predicted that deletion of HOS3 and
RPD3 should phenocopy those genetic interactions seen in whi5∆ mutants. I first tested various
KDAC deletion strains for suppression of the slow growth phenotype of a pho85∆cln3∆ mutant.
As for WHI5, deletion of HOS3 and RPD3 partially suppressed the growth defect seen in the
pho85∆cln3∆ double mutant strain (Figure 2-10B). Suppression was specific to HOS3 and
RPD3 because deletion of other KDACs showed no suppression and, the growth rate of the
pho85∆cln3∆hos3∆ strain was not improved by subsequent deletion of RPD3 and vice versa
(Figure 2-10B).
I next asked if deletion of KDACs might overcome the Start arrest seen in cells lacking both
CLN3 and BCK2, another regulator of G1 transcription, that functions in parallel with CLN3
(Wijnen and Futcher, 1999). A cln3∆bck2∆whi5∆ triple mutant grows as vigorously as wild-
type, placing WHI5 downstream of both upstream activators of G1 transcription (Costanzo et al.,
2004). Interestingly, deletion of RPD3 partially restored growth in the cln3∆bck2∆ strain
providing further evidence for an KDAC requirement in Whi5-mediated transcriptional
repression (Figure 2-10C). Neither subsequent deletion of HOS3 nor deletion of other KDACs
affected growth appreciably (Figure 2-10C).
81
A
B
Figure 2-10: WHI5 toxicity is dependent on HOS3 and RPD3.
(A) cln3∆, cln3∆rpd3∆, cln3∆hos3∆ (BY4296) and cln3∆rpd3∆hos3∆ strains harbouring a methionine-repressible
WHI5 construct or vector control were spotted in serial 10-fold dilutions on medium lacking methionine. In a
similar experiment, pho85∆, pho85∆rpd3∆, pho85∆hos3∆, and pho85∆rpd3∆hos3∆ strains bearing a galactose-
inducible WHI5 plasmid or appropriate vector control (pEG-H) were spotted in serial 10-fold dilutions on galactose-
containing medium. Plates were incubated at 30oC for 48 hr. (B) Deletion of HOS3 partially restores growth of a
cln3∆pho85∆ strain. The indicated strains were spotted in serial 10-fold dilutions on rich medium (YPED) and
incubated at 30oC for 48 hr. (C) Deletion of RPD3 and HOS3 partially restore viability of a cln3∆bck2∆ strain. The
indicated strains were spotted in serial 10-fold dilutions on glucose-containing medium (YPED) to repress CLN3
expression. Strains were also spotted on medium containing galactose as a control. Plates were incubated at 30oC
for 72 hr.
82
We also employed the SCB-HIS3 assays used above to explore SBF-driven reporter gene
expression in the KDAC mutants (Figure 2-11). As expected, deletion of RPD3 rescued the
growth defects of cln3∆ SCB-HIS3 cells in the presence of both 10 mM and 30 mM of 3-AT,
whereas HOS3 gene knockout had a marginal but additive effect. In contrast, the growth of
pho85∆ cells was slightly rescued by deletion of HOS3 but not RPD3 providing further evidence
for Pho85 acting specifically through Hos3. Due to difficulties in detecting KDACs at promoters
we were unable to confirm these observations in vivo.
I also performed co-immunoprecipitation assays using affinity tagged RPD3 and HOS3 strains
and observed an obvious decrease in Rpd3 and Hos3 in Whi5 precipitates from strains
harbouring increased levels of Pcl9, Cln2 or Cln3 cyclins (Figure 2-12A and 2-12B). Together,
our genetic and biochemical results suggest that Pho85 may preferentially influence Whi5-Hos3
activity while Cln3-Cdc28 is required for inhibition of both Rpd3 and Hos3.
83
Figure 2-11: Repression of gene expression by Whi5 is dependent on HOS3 and RPD3.
The growth defects of cln3∆ and pho85∆ strains can be rescued by removing RPD3 and HOS3 in SCB-driven gene
expression. Wild-type, cln3∆, pho85∆, cln3∆rpd3∆, cln3∆hos3∆, cln3∆rpd3∆hos3∆, pho85∆rpd3∆, pho85∆hos3∆
and pho85∆rpd3∆hos3∆ strains harbouring an integrated SCB-HIS3 reporter were spotted in serial 10-fold dilutions
on histidine-containing medium or media lacking histidine and supplemented with 10 or 30 mM 3-AT. Plates were
incubated at 30oC for 48 hr.
84
A
B
Figure 2-12: CDK activity antagonizes Whi5-KDAC interactions.
(A) Pho85 and Cdc28 activity inhibits interaction between Whi5 and Rpd3. PCL9FLAG
, CLN2FLAG
, CLN3FLAG
or a
vector control were introduced into a strain harbouring RPD3TAP
at the chromosomal locus and a WHI5GST
plasmid.
Cyclin expression was confirmed by immunoblotting using anti-FLAG antibodies. Lysates were incubated with
glutathione sepharose beads. Whi5GST
-Rpd3TAP
interactions were detected by immunoblot using α-GST and α-PAP
antibodies, (B) Pho85 and Cdc28 activity inhibits interaction of Whi5 and Hos3. Experiments were conducted as
described in (A) but using a strain bearing HOS3TAP
at the chromosomal locus.
85
2.4 Discussion
Whi5 is a critical cell cycle regulator that links CDK activity in G1 phase to the broad
transcriptional program that accompanies commitment to cell division. We provide substantial
evidence that the multifunctional Pho85 CDK is an important regulator of Whi5 activity and G1
phase-specific transcription including; (1) Whi5 is phosphorylated and antagonized by Pho85
and is the first reported substrate for the G1-specific CDK complex, Pcl9-Pho85; ( 2) the activity
of an SBF-dependent promoter is influenced by PHO85 (3) the Pho85 cyclin, Pcl9, binds to
SBF-regulated promoters; (4) the repressor function of Whi5 is mediated through the KDACs
Hos3 and Rpd3, and KDAC-Whi5 association is regulated by G1-specific forms of both the
Pho85 and Cdc28 CDKs. We therefore conclude that timely and efficient release from Whi5
inhibition and subsequent G1/S cell cycle progression requires the concerted activity of both
Cdc28 and Pho85.
Several lines of evidence point to common roles for Pho85 and Cdc28. For example, a burst of
both G1-specific Cdc28 and Pho85 activity is essential for cellular morphogenesis. A strain
lacking the G1-specific cyclins, CLN1, CLN2, PCL1 and PCL2, undergoes a catastrophic
morphogenic change and fails to establish polarized cell growth and cytokinesis (Moffat and
Andrews, 2004). Consistent with these observations, a chemical genomic analysis demonstrated
that expression of genes involved in polarized cell growth was sensitive to simultaneous
inhibition of both kinases, but not either single kinase (Kung et al., 2005). A functional
connection between Pho85 and Cdc28 is further supported by independent genetic and
biochemical analyses that identify common targets phosphorylated by both kinases (McBride et
al., 2001; Measday et al., 2000; Nishizawa et al., 1998; Ptacek et al., 2005; Sopko et al., 2007a;
Wagner et al., 2009).
Despite the clear functional overlap for G1-specific forms of Cdc28 and Pho85 in controlling
morphogenesis, up to now, a direct role for Pho85 in cell cycle commitment and G1 phase-
specific transcription has remained unclear. We discovered that, like Cdc28, Pho85 activates G1
transcription through inhibition of the Whi5 repressor. While the two kinases collaborate to
control certain facets of Whi5 regulation, they are also specialized to modulate Whi5 function by
distinct mechanisms. I have defined a novel KDAC-dependent mechanism that impinges on
Whi5 function and implicates both Pho85 and Cdc28 as regulators of this process. Based on
86
these and other observations, we propose that Whi5 functional regulation involves perturbation
of specific KDAC-Whi5 interactions and requires the concerted activity of both Cdc28 and
Pho85 (summarized in Figure 2-13). Interestingly, our genetic observations support a model
whereby Pcl-Pho85 preferentially targets the Hos3-Whi5 interaction illustrating a functional
distinction between the two CDKs. While Pho85 associates with several cyclin subunits, only
Pcl9 exhibits temporal expression and localization patterns compatible with such a function.
PCL9 is expressed at the M/G1 phase transition and encodes a short-lived protein localized
exclusively to the nucleus in early G1 phase (McInerny et al., 1997; Miller and Cross, 2000;
Tennyson et al., 1998). Cln3 is also present in early G1 cells, but shows a complex localization
pattern, with significant retention to the ER in early G1 cells, followed by chaperone-mediated
release into the nucleus in late G1 phase (Verges et al., 2007). How the specific features of Pcl9
and Cln3 localization might influence the timing of KDAC inhibition remains to be explored.
87
Figure 2-13: Model for CDK-dependent regulation of Whi5 activity and G1/S-specific transcription.
Shown is a schematic of the disruption of interactions between Whi5 and the HDACs, Hos3 and Rpd3, by Cln3-
Cdc28 and Pcl9-Pho85-dependent phosphorylation, leading to transcription of G1 genes, including the CLN1 and
CLN2 cyclins. Whi5 is then further phosphorylated by Cln1- and Cln2-Cdc28 complexes leading to complete
disassembly of the Whi5-SBF complex, Whi5 nuclear export and a burst in gene expression necessary for the G1/S
phase transition.
88
The second component of Whi5 regulation is predicated on previous studies indicating that G1/S
gene expression is preceded by Whi5-SBF complex dissociation and subsequent nuclear export
of Whi5 (Figure 2-13) (Costanzo et al., 2004). Unlike early regulatory events, Cdc28 activity is
both necessary and sufficient to drive these events since neither SBF binding to Whi5 nor
nuclear localization of Whi5 was adversely affected in a pho85∆ mutant (Figure 2-8). Also, we
are able to detect binding of SBF in vivo to CLN2 promoters when PHO85 is deleted (Figure 2-
3C). However, both purified Cln3-Cdc28 and Pcl9-Pho85 failed to affect Whi5-SBF stability in
vitro, while complex disruption was effectively achieved in the presence of Cln2-Cdc28 kinases
(Figure 2-8). Cln3-Cdc28 and Pcl9-Pho85 may have a more pronounced effect on the Whi5-
SBF complex in vivo. Alternatively, Cln3- and Pcl9-CDKs may act primarily as agonists of
KDAC interactions while physical interactions with SBF and nuclear export are optimally
mediated by the late G1 CDKs, Cln1- and Cln2-Cdc28. Indeed, recent work reveals activation of
CLN2 expression while Whi5 remains bound to the promoter (Wang et al., 2009). Such a
mechanism may serve to sharpen the onset, as opposed to the timing, of G1/S gene expression
thus ensuring a sustained transcriptional burst and irreversible commitment to cell division
(Costanzo et al., 2004). Consistent with this idea, recent analysis of cyclin gene expression using
a single cell assay affirms that positive feedback involving the Cln1 and Cln2 cyclins induces the
G1/S regulon, and that this regulatory feedback is important for to maintaining coherence of
gene expression at Start (Skotheim et al., 2008).
SBF promoter recruitment depends on a series of well-organized chromatin remodelling events
(Cosma et al., 1999; Krebs et al., 1999). SBF, in turn, regulates the recruitment of the general
transcription machinery via a two-step process beginning with the mediator complex followed by
CDK-dependent recruitment of RNAPII, TFIIB, and TFIIH (Cosma et al., 2001). Previous
studies suggested that this CDK requirement stems from Whi5, which in its unphosphorylated
state, remains bound to SBF and occludes the basal transcription machinery from binding
specific promoters (Costanzo et al., 2004). I have extended this model to include a role for
KDAC activity. I predict that Hos3 and Rpd3 contribute to Whi5 repression by preventing
holoenzyme access to chromatin. During states of high CDK activity, Cdc28 and Pho85
abrogate Whi5-KDAC and Whi5-SBF interactions and initiate transcription. Consistent with our
model, Pcl9 and Cln3 cyclins localize to G1 promoters and Whi5 remains associated with G1-
specific promoters in the absence of KDAC-promoter interactions (Figure 2-3; (Wang et al.,
89
2009)). However, Whi5 may also repress transcription by additional mechanisms since its
activity is partially retained in hos3∆ rpd3∆ mutants (Figure 2-10).
As discussed in Chapter 1 Rpd3 is the best characterized KDAC in yeast and the Rpd3-Sin3
complex has been implicated as a cell cycle regulator required for silencing HO gene expression
to prevent mating type switching in newly budded cells (Sternberg et al., 1987; Stillman et al.,
1988). My observations that Whi5 associates with Rpd3 and the genetic data linking G1 Cdks,
Whi5 and Rpd3 reveal a more general role for Rpd3 in G1/S-phase specific transcription. This is
consistent with the observations from Wang et al., (2009) that Rpd3 can be detected at the CLN2
promoter and that these levels decreased when CLN3 was induced (Wang et al., 2009). The
Rpd3-Sin3 KDAC has also been connected to G1 transcription factors through the interaction of
Sin3 with Stb1, a Swi6-binding protein (de Bruin et al., 2008; Ho et al., 1999; Kasten and
Stillman, 1997). Both Stb1 and Sin3 are required for repression of G1 transcription early in G1
phase (de Bruin et al., 2008). An additional role for Rpd3 in regulating the interactions between
the two subunits of SBF Swi4 and Swi6 will be shown in detail in Chapter 3. As summarized in
Chapter 1 Hos3 is largely uncharacterized and here I have uncovered a novel role for Hos3 in
Whi5-mediated transcriptional repression.
A question that arises from our observations is what advantage does combinatorial kinase
regulation impart on specific biological processes such as G1/S cell cycle progression?
Contributions from multiple CDKs may provide the precision and accuracy necessary rapid
definitive decisions that irreversibly affect cellular fate. Indeed, distributive multi-site
phosphorylation mechanisms exhibit ultra-sensitivity with respect to kinase concentration,
thereby creating a “switch-like” behavior in biological circuits (Ubersax and Ferrell, 2007).
Since cell cycle transitions typically display switch-like attributes, multi-site phosphorylation by
various kinase combinations may prove to be a rule rather than the exception amongst CDK
targets, including key cell cycle regulators such as Whi5. In fact, a recent computational analysis
showed enrichment of multiple closely spaced consensus sites for Cdc28 substrates in yeast, a
pattern that proved predictive of likely CDK targets (Moses et al., 2007).
Similarities between metazoan and yeast cell cycle regulation are increasingly evident as we
continue to characterize Whi5 function. For example, similar to proposed Pcl9/Cln3 “early”
phase regulation (Figure 2-13), cyclinD-CDK4/6 phosphorylates Rb to promote KDAC
90
dissociation and E2F transcriptional activation. E2F activation then leads to cyclin E expression
which, similar to Cln1/2 “late” phase regulation, may establish a positive feedback loop whereby
cyclinE-CDK2 activity disrupts Rb-promoter interactions and stimulates G1-transcription further
(Hatakeyama et al., 1994). Despite these similarities, the importance of multiple regulatory
components in both yeast and mammalian systems remains poorly understood and may be most
fruitfully dissected using the yeast model.
In this chapter, I present a detailed analysis of the G1 regulatory pathway to show that the
precision and the accuracy necessary for initiating transcription through SBF is achieved by
orchestrating the activity of multiple CDKs. I have also elucidated the mechanism by which
Whi5 represses transcription through the recruitment of lysine deacetylases to G1 promoters. An
additional function for Rpd3 in regulating SBF will be discussed in Chapter 3.
91
Chapter 3 Exploring the global effects of Class I and II lysine deacetylases
using functional genomics
The enrichment analysis, the correlational analysis and Figures 3-1 and 3-2A were done by
Anastasia Baryshnikova.
92
3 Abstract
Lysine acetylation is a dynamic posttranslational modification and has a well defined role in
transcription as well as nuclear processes that require alterations to nucleosomes. However, the
impact of acetylation on other cellular processes remains largely uncharacterized. To explore the
yeast acetylome we used a functional genomics approach to systematically assess gene over-
expression phenotypes in the absence of lysine deacetylases (KDACs). A network of 458
synthetic dosage lethal (SDL) interactions was generated involving five Class I and Class II yeast
KDACs which revealed novel cellular pathways regulated post-transcriptionally by KDACs.
Genes that are SDL in the absence of RPD3 were involved in processes that are not
transcriptionally regulated by Rpd3, suggesting that our genetic screens detect a new type of
interaction for KDACs, that can be utilized to identify non-histone substrates. We identified 73
proteins acetylated in vivo involved in diverse cellular processes such as transcription, cell
organization and biogenesis, transport and protein metabolism. Swi4, a component of the G1
transcription factor SBF, was identified in our Rpd3 KDAC SDL screen and we found that
interaction of Swi4 with its heterodimeric partner Swi6 was regulated by acetylation and was
required for proper induction of G1 genes. Our findings significantly expand the scope of the
yeast acetylome and demonstrate the utility of systematic functional genomic screens to explore
enzymatic pathways.
93
3.1 Introduction
Lysine acetylation has broad influences on gene expression (Robert et al., 2004) where the
dynamic interplay between lysine acetyltransferases and lysine deacetylases maintains
appropriate levels of histone acetylation to promote normal cell proliferation, growth and
differentiation and abnormal KAT/KDAC function results in disease states such as cancer
(Archer and Hodin, 1999; Bradner et al., 2010; Chuang et al., 2009; Das and Kundu, 2005). As
described in Chapter 1, the budding yeast genome encodes ten KDACs, most of which have clear
human orthologs (Bradner et al., 2010; Ekwall, 2005; Kurdistani and Grunstein, 2003;
Marmorstein and Roth, 2001; Yang and Seto, 2008). This chapter will focus on the global
analysis of Class I and II lysine deacetylases in S. Cerevisiae. Class I includes Rpd3, Hos1 and
Hos2 and Class II contains KDACs Hda1 and Hos3.
In the past decade a role has emerged for acetylation in regulating proteins other than histones
(Glozak et al., 2005; Kurdistani and Grunstein, 2003). Proteomic surveys and other experiments
have identified more than 2000 acetylated proteins in mammalian cells, although we have a
limited view of how specific acetylation events are linked to cognate KATs/KDACs and the
biological effects of these (de)acetylation events (Choudhary et al., 2009; Glozak et al., 2005;
Spange et al., 2009; Zhao et al., 2010). In yeast, the acetylome remains relatively unexplored --
to date, a protein acetylation microarray has been the only genome-scale approach used to
discover potential KAT substrates (Lin et al., 2009) and only 19 non-histone substrates have
been characterized (Beckouet et al., 2010; Borges et al., 2010; Choudhary et al., 2009;
Heidinger-Pauli et al., 2009; Ivanov et al., 2002; Kim et al., 2010; Lin et al., 2009; Lin et al.,
2008; VanDemark et al., 2007). The availability of genomic tools in yeast provides an excellent
opportunity to use systematic genetics to explore the acetylome and to add functional
information to our view of KAT/KDAC regulation. In particular, I have made use of synthetic
genetic array technology, to introduce inducible overexpression alleles of yeast genes into
genetic backgrounds of interest, in an effort to systematically assess Synthetic Dosage Lethal
(SDL) interactions. As described in Chapter 1, SDL interactions result when increased gene
expression levels have no effect on the growth of a wild-type cell but produce a clear phenotype,
such as lethality, in a specific mutant background. SDL screens can identify interacting proteins
and enzyme targets (Kroll et al., 1996; Measday and Hieter, 2002; Sopko et al., 2006a). For
example, SDL screens have identified targets of kinases (Sharifpoor et al., 2011; Sopko et al.,
94
2006a); ubiquitin-binding proteins (Liu et al., 2009) and proteins involved in chromosome
segregation (Measday et al., 2005).
In this Chapter, I describe the SDL interaction network for Class I and II KDACs in
yeast. Analysis of the network combined with secondary biochemical tests has allowed me to
ascribe novel functions to Hda2 and Hda3 and to extend the list of known acetylated proteins in
yeast by ~4-fold. Using genetic and biochemical assays I analyzed one potential KDAC target
uncovered in my rpd3 SDL screen to show that acetylation of the cell cycle transcription factor
Swi4 regulates its function in vivo, uncovering a new level of regulation controlling G1
transcription and strengthening the analogy between G1 regulatory pathways in yeast and
mammalian cells. My study expands the role of KDACs beyond their effects on histones and
provides a valuable resource for predicting functional relationships in pathways regulated by
KDACs. I also validate systematic SDL screens as a useful tool for identifying new functions
and downstream targets for conserved enzyme families.
3.2 Experimental Procedures
3.2.1 Yeast Strains, Growth Conditions and Plasmids
The S. cerevisiae strains and plasmids used are listed in Table 3-1. Standard methods and media
were used for yeast growth and transformations. The expression of genes under the GAL1
promoter were induced for 8 hours by adding 2% galactose to synthetic media lacking uracil.
Synthetic minimal medium supplemented with appropriate amino acids was used for strains
containing plasmids. Site-directed mutagenesis of SWI4 in pDONR221 was performed using a
QuickChangeTM
kit (Stratagene) following the manufacturer‟s protocols. All clones were
confirmed by sequencing. All integrations were achieved by homologous recombination at their
chromosomal loci using standard PCR-based methods and confirmed by flanking primers
(Longtine et al., 1998).
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Table 3-1 Strains used in this chapter
Strain Genotype Source or Reference
BY185 BY263 MATα swi6∆HIS3 Baetz et al., 2001
BY186 BY263 MATa swi4∆HIS3 Baetz et al., 2001
BY1624
BY4741 MAT α his3Δ1 leu2Δ0 met15Δ0 ura3Δ0
Deletion consotrium
paper
BY4691 MAT a leu2Δ0 ura3Δ0 Swi4-myc::Ura3 This study
BY4826 BY 4741 MAT α ura3∆NAT Costanzo et al. (2010)
BY4827 BY 4741 MAT α rpd3∆NAT Costanzo et al. (2010)
BY4828 BY 4741 MAT α hda1∆NAT Costanzo et al. (2010)
BY4829 BY 4741 MAT α hda2∆NAT Costanzo et al. (2010)
BY4830 BY 4741 MAT α hda3∆NAT Costanzo et al. (2010)
BY4831 BY 4741 MAT α hos1∆NAT Costanzo et al. (2010)
BY4832 BY 4741 MAT α hos2∆NAT Costanzo et al. (2010)
BY4833 BY 4741 MAT α hos3∆NAT Costanzo et al. (2010)
BY4834 BY 4741 MAT α ura3∆NAT Swi4-MYC::Ura3 This study
BY4835 BY 4741 MAT α rpd3∆NAT Swi4-MYC::Ura3 This study
BY4836 BY 4741 MAT α hda1∆NAT Swi4-MYC::Ura3 This study
BY4837 BY 4741 MAT α hos1∆NAT Swi4-MYC::Ura3 This study
BY4838 BY 4741 MAT α hos2∆NAT Swi4-MYC::Ura3 This study
BY4839 BY 4741 MAT α hos3∆NAT Swi4-MYC::Ura3 This study
BY4840 MAT a Swi4-QQ (K1016Q:K1066Q) This study
BY4841 MAT a Swi4-RR (K1016R:K1066r) This study
BY4842 MAT a Swi4-Myc::KAN This study
BY4843 MAT a Swi4-QQ-Myc::KAN (K1016Q:K1066Q) This study
BY4844 MAT a Swi4-RR-Myc::KAN (K1016R:K1066R) This study
BY4858
MATa, ura3Δ::Natt, CAN1pr::RPL39pr-tdTomato::CaUra3,
can1Δ::STE2pr-LEU2, lyp1 Δ, ura3Δ0, his3Δ1, leu2Δ0, met15Δ0
TAT2-GFP::His3 This study
BY4859
MATa, rpd3Δ::Nat, CAN1pr::RPL39pr-tdTomato::CaUra3,
can1Δ::STE2pr-LEU2, lyp1 Δ, ura3Δ0, his3Δ1, leu2Δ0, met15Δ0,
TAT2-GFP::His3 This study
BY4860 URA3Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, PEX15-GFP::His3 This study
BY4861 hda1Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, PEX15-GFP::His3 This study
BY4862 hda2Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, PEX15-GFP::His3 This study
BY4863 hda3Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, PEX15-GFP::His3 This study
BY4864 ura3Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, POT1-GFP::His3 This study
BY4865 hda1Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, POT1-GFP::His3 This study
BY4866 hda2Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, POT1-GFP::His3 This study
BY4867 hda3Δ::Nat,ura3Δ0, his3Δ1, leu2Δ0, met15Δ0, POT1-GFP::His3 This study
96
3.2.2 SDL Screens and confirmations
Screens were performed as previously described (Sopko et al., 2006a). Briefly, kdac∆NAT
strains (Costanzo et al., 2010a) were crossed to an array of yeast, each containing a plasmid with
a single gene under the control of the GAL promoter (Sopko et al., 2006a). An output array
containing both the kdac deletion and the over-expression plasmids were generated using a series
of replica-pinning steps, after which expression of the plasmids was induced by pinning onto
galactose-containing media. Colony growth was assessed using automated software and a 20%
reduction in mean colony size compared to wild-type was considered a „hit‟ from the genome-
wide screens. Each screen was performed in duplicate using 1536-colony format, where each
colony was represented 4 times on the array, generating 8 replicate colonies per gene. Candidate
SDL interactions were confirmed by directly transforming the plasmid into both wild type and
mutant backgrounds, followed by serial spot dilutions. Spot assays were quantified by eye to
detect a difference in colony size observed in the kdac deletion strains.
3.2.3 Cell biology
For the vacuolar internalization experiments C-terminal GFP-tagged proteins from the yeast GFP
collection (Huh et al., 2003), were imaged in both the wild-type and rpd3∆ backgrounds and for
the peroxisomal experiments GFP-tagged proteins from the same collection were imaged in
wild-type, hda1∆, hda2∆ and hda3∆ backgrounds. Strains were grown to mid-log phase in low
fluorescence media (MP Biomedicals, France #4030-512) at 30°C, mounted on glass slides and
imaged at room temperature using a DMI 600B fluorescence microscope (Leica Microsystems,
Deerfield, IL) equipped with a spinning-disk head, an argon laser (458, 488, and 514 nm;
Quorum Technologies, Guelph, ON, Canada) and ImagEM charge-coupled device camera
(Hamamatsu C9100-13, Hamamatsu Photonics, Hamamatsu City, Japan). Sixteen-bit images
were analyzed using Velocity software (Improvision, Coventry, United Kingdom). Peroxisome
numbers were determined by eye using three independent experiments.
3.2.4 Pull-down of GST proteins and Acetylation Western blots
Wild-type cells carrying plasmids containing a N-terminally GST tagged over-expression
plasmid (Sopko et al., 2006a) were grown in 2% galactose for 8 hours to induce the expression
of GST-proteins, harvested and lysed using glass beads (Biospec) in lysis buffer (0.1% NP40,
1mM DTT, 250mM NaCl, 50mM NaF, 5mM EDTA, 50mM Tris-Cl pH7.5, 1mM PMSF).
97
Glutathione-Sepharose beads (GE Healthcare) were used to pull-down the GST-tagged proteins,
which were analyzed for acetylation using western blots and an antibody specific to acetylated
lysines (Cell Signaling, polyclonal #9441, monoclonal #9681). The polyclonal antibody was
produced by immunizing animals with a synthetic acetylated lysine-containing peptide. Presence
of the GST proteins was assessed using a HRP-conjugated anti-GST antibody (Santa Cruz).
3.2.5 Mass spectrometry
Protein purification and mass spectrometry analysis of acetylation sites on Swi4-TAP was
performed as previously described (Lambert et al., 2009).
3.2.6 Cell cycle synchronization, quantitative PCR and expression analysis
Cultures were grown to mid-log phase in YPD at 30°C and arrested by incubating with 5µM α-
factor (GenScript) for 2-3h. Cells were monitored by light microscopy to verify α-factor arrest.
Cells were then washed with cold YP and re-suspended in fresh YPD medium. Samples were
taken every 15 minutes. RNA was prepared using the RNeasy mini kit (Qiagen), following the
manufacturer‟s protocol for yeast cells. The QuantiTect Reverse Transcription Kit (Qiagen) was
used to synthesis cDNA from ~1ug of RNA and to eliminate contaminating genomic DNA.
qPCR reactions were performed on a ABI 500 Real-time PCR block (Applied Biosystems) using
SYBR green (Finnzymes) and primers specific to CLN2 (F 5'-AGCACATCCATTCCTTCG-3' R
5'-TATTGCTGTTAGGACCCG-3') and ACT1 (F 5'-ACGAAAGATTCAGAGCCC-3', R 5'-
CTTTCTGGAGGAGCAATG-3') (Haim et al., 2007). FACS analysis for the cell cycle
synchronized samples was performed as previously described (Huang et al., 2009).
3.2.7 Chromatin Immunoprecipitations
Cultures were synchronized using α-factor as described above. Samples were taken at 15 minute
intervals after release and cross-linked with a final concentration of 1% formaldehyde (Sigma).
Formaldehyde cross-linking and preparation of whole-cell extracts were performed as previously
described (Kim et al., 2004). Immunoprecipitations were performed using 1:200 dilution of α-
myc monoclonal antibody (9E10) and α-Swi6 or α-Swi4 polyclonal antibodies (Andrews and
Herskowitz, 1989; Ogas et al., 1991). Enrichment at the CLN2 promoter sequence was quantified
with real-time PCR, using a dual fluorogenic reporter TaqMan assay in an ABI PRISM 7500HT
Sequence Detection System as previously described (Costanzo et al., 2004).
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3.3 Results
3.3.1 Systematic gene over-expression identifies 458 SDL interactions for Class I and II KDACs
I performed whole-genome SDL screens by introducing deletions of genes encoding Class I and
II KDACs (rpd3∆, hos1∆, hos2∆, hos3∆, hda1∆) into an arrayed collection of 5280 yeast strains,
each conditionally over-expressing a unique yeast gene (Sopko et al., 2006a). Over-expression
phenotypes were measured using colony size as a proxy for cell fitness, an approach we have
validated in other large-scale genetic interaction screens (Baryshnikova et al., 2010; Costanzo et
al., 2010a; Sopko et al., 2006a). Colony size measurements were made using automated
software and genes whose over-expression resulted in a colony size reduction of greater than
20% compared to wild-type were considered to be candidate interactors. These candidates were
then confirmed using an independent growth assay to generate a list of high confidence
interactions. In total my screens identified 458 SDL interactions (Figure 3-1and Appendix 1
Table 1) involving 370 unique genes showing enrichment for roles in cell polarity and
morphogenesis, Golgi, endosome and vacuole sorting, nuclear-cytoplasmic transport,
peroxisome biogenesis, and drug/ion transport (Table 3-2).
The strains deleted for RPD3 and HDA1, which had the greatest fitness defects among the kdac
mutants, produced the highest number of SDL interactions (244 and 163 interactions
respectively), consistent with other large scale experiments showing an inverse relationship
between genetic interaction degree and the fitness of a mutant strain (Costanzo et al., 2010a).
Given that RPD3 and HDA1 regulate a number of common genes (Bernstein et al., 2000), I
expected overlap between the SDL hits in the rpd3 and hda1 screens. Indeed, 57 SDL
interactions were shared between the two KDACs, representing ~34% of HDA1 interactions and
~23% of RPD3 interactions (p<2.54x10-34
). However, the majority of SDL interactions were
unique to each KDAC, consistent with significant non-overlapping roles for each enzyme.
99
Figure 3-1 Genetic interaction identified for Class I and II KDACs.
A network diagram summarizing the genome-wide SDL data for Class I and II KDACs in yeast. Nodes represent
genes and the edges represent SDL interactions. This network shows 458 interactions that involves 370 unique
genes. Nodes are colored according to the biological processes annotated by Costanzo et al (2010). A complete list
of these interactions can be found in Table 1 in Appendix 1.
hos1∆
hos3∆
rpd3∆hda1∆
hos2∆
Multiple annotations Not annotated in Costanzo 2010
UnknownPolarity, cell wall, glycosylation, cytokinesis, endocytosis Metabolism, mitochondria
SecretionDNA synthesis, repair, dynamics G1-S, G2-M, meiosisRNA processing, translation
Chromatin, transcription Protein folding, degradation
Peroxisome
Drug/ion transport
100
Table 3-2 Gene enrichments for kdac∆ SDL screens with fold enrichment over the genome and
the associated significance values
Biological processes Fold enrichment P-value
cell polarity/morphogenesis 1.629 5.77E-03
drug/ion transport 1.853 2.77E-04
Golgi/endosome/vacuole/sorting 2.061 1.44E-04
nuclear-cytoplasic transport 1.783 4.84E-02
peroxisome 2.187 2.41E-02
101
Overall, I detected little functional overlap among the genes with SDL interactions with different
deacetylases; instead, the SDL hits in each KDAC screen were enriched for different biological
processes (Figure 3-2A), a property also observed in other experiments assessing chromatin
acetylation in the absence of KDACs (Robyr et al., 2002). The group of genes most significantly
enriched in the rpd3 screen included membrane proteins and receptors with annotated roles in
drug and ion transport (Figure 3-2A). I was intrigued by this observation since localization of a
membrane protein has been shown to be indirectly regulated by deacetylation in human cells:
KDAC6 regulates the localization of the epidermal growth factor receptor (EGFR) (Deribe et al.,
2009; Gao et al., 2010). To ask whether Rpd3 might similarly influence localization of
membrane proteins in yeast, I used fluorescence microscopy to assess localization of proteins
involved in drug/ion transport that were identified in my SDL screen using GFP-fusions of each
of the transporters. Of the 17 proteins tested, I saw a clear defect in localization for two
transporters in the absence of RPD3. Both Hnm1, a choline/ethanolamine transporter (Nikawa
et al., 1986) and Tat2, a tryptophan/tyrosine permease (Schmidt et al., 1994), were mislocalized
from their normal cell surface location in wild type to the vacuole in an rpd3 strain (Figure 3-
2B). These assays suggest that, as in mammalian cells, the localization of some cell surface
receptors may be regulated by acetylation in yeast.
102
Figure 3-2 GO enrichments for two of the genomewide SDL screens
A) Enrichment for rpd3∆ and hda1∆ SDL interactions for biological processes annotated by Costanzo et al., (2010).
Top panel shows the fold enrichment for genes in the categories listed and the lower panel shows the associated p-
values. B) Vacuolar internalization of drug transporters in the absence of RPD3. C-terminal GFP-tagged proteins
from the yeast GFP collection (Huh et al., 2003), were imaged in both the wild-type and rpd3∆ backgrounds using a
confocal microscope.
hda1∆
rpd3∆ Fold enrichment
p-values (-log10)hda1∆
rpd3∆
2 4 6 8
2 3 54
cell p
ola
rity
/mo
rph
ogen
esi
s
dru
g/i
on
tra
nsp
ort
ER
<->
Go
lgi
tra
nsp
ort
pero
xis
om
e
sign
al/
stre
ss r
esp
on
se
pro
tein
fo
ldin
g/g
lyco
syla
tio
n/c
ell w
all
bio
gen
meta
bo
lism
/mit
och
ron
dri
a
rib
oso
mes/
tra
nsl
ati
on
lip
id/s
tero
l/fa
tty
acid
bio
syn
au
top
hagy
/CV
T
ch
rom
ati
n tra
nsc
rip
tio
n
pro
tein
degra
da
tio
n/p
rote
aso
me
RN
A p
rocess
ing
DN
A r
ep
lic/r
ep
air
/HR
/co
hesi
on
ch
rom
seg/k
ineto
ch
ore
/sp
ind
le/m
icro
tub
ule
aa
bio
syn
thesi
s/tr
an
spo
rt/n
itro
gen
uti
liza
tio
n
G1
/S a
nd
G2
/M c
ell c
ycle
pro
gre
ssio
n/m
eio
sis
Go
lgi/
va
cu
ole
/en
do
som
e/s
ort
ing
nu
cle
ar-
cy
top
lasm
ic tra
nsp
ort
A
Wild type rpd3∆
Hnm1-GFP
Tat2-GFP
DIC
DIC
B
103
Given that KDACs are known to regulate transcription through deacetylation of histones, a
subset of SDL interactions may result from aberrant transcription in the absence of KDACs. To
address this point, I compared our KDAC-SDL profiles to the gene expression profiles of rpd3
and hda1 mutants (Bernstein et al., 2000). Less than 6% of the genes that caused toxicity when
over-expressed (244 genes in rpd3∆ and 163 genes in hda1∆) were differentially regulated at
the transcriptional level in the absence of the KDAC (Bernstein et al., 2000). Furthermore,
synthetic dosage interactors of RPD3 and genes transcriptionally regulated by Rpd3 were
enriched for distinct biological processes (Figure 3-3). These results suggest that few SDL
interactions are caused by indirect effects resulting from defects in gene expression caused by
the deletion of KDACs.
.
104
Figure 3-3 Enrichments within the rpd3∆ SDL interactions for biological process
Genes in the SDL data set (blue columns) and expression dataset (black columns) were classified by gene ontology
(GO) biological process by FunSpec (http://funspec.med.utoronto.ca/). Enrichments in the various categories
relative to the entire yeast genome (grey columns) are also shown.
0 5 10 15
1
2
3
4
5
6
7
8
9
10
Organelle fusion
Endocytosis
Intracellular protein transport
Transmembrane transport
GO
Bio
log
ica
l p
roce
ss
Percentage of genes in category
p < 10-6
p < 10-5
p < 10-4
p < 10-3
Genome
Genes that cause SDL in rpd3∆
DNA damage response
p < 10-6
p < 10-5
p < 10-4
p < 10-3
p < 10-3
p < 10-3
Meiosis
DNA recombination
Chromosome segregation
Genes up-regulated in rpd3∆
Mitotic cell cycle
Mitosis
105
3.3.2 Gene deletion and gene over-expression reveal distinct genetic interactions
In addition to synthetic dosage lethality, genetic interactions amongst loss-of-function alleles
have been extensively mapped (Costanzo et al., 2010a). Negative genetic interactions, such as
synthetic sickness (SS) or lethality (SL), occur when the observed fitness defect of a double
mutant is more severe than expected, given the fitness defects of the two single mutants (Mani et
al., 2008). In the largest genetic network published to date, Costanzo et al (2010) tested 5.4
million gene pairs for synthetic genetic interactions, generating profiles for ~75% of all genes in
budding yeast. The dataset includes 497 unique negative genetic interactions involving deletion
alleles of Class I and II KDACs. Of the 458 genes that were SDL in the absence of a KDAC, 15
were also SS/SLwith the KDAC (Table 3-3). Seven of the genes that caused a growth defect
when either over-expressed or deleted in a kdac mutant encode proteins that are components of
multi-subunit complexes, consistent with the balance hypothesis which predicts that perturbation
of protein complex stoichiometry gives rise to haploinsufficient phenotypes producing
concordance between deletion and over-expression phenotypes (Veitia, 2002). For example,
Hda1 functions in a tetrameric complex (Carmen et al., 1996; Wu et al., 2001) and either over-
expression or deletion of HDA1 caused lethality in the absence of RPD3. In this case, over-
expression of HDA1 may mimic the deletion phenotype by disrupting HDA complex
stoichiometry (Papp et al., 2003). In general, however, the small overlap between SDL and SL
datasets suggests that SL and SDL screens explore different facets of genetic interaction space,
consistent with previous studies (Kelley and Ideker, 2005; Measday et al., 2005; Sopko et al.,
2006b; Tong et al., 2004).
106
Table 3-3 Genes identified in the SDL screens that are also up-regulated at the level of
transcription in the absence of RPD3 and HDA1.
ORF Gene Participates in a
complex Complex
rpd3∆
YBR108W AIM3 No
YER048C CAJ1 No
YER111C SWI4 Yes SBF
YGL077C HNM1 No
YHR015W MIP6 Yes Nuclear pore
YHR161C YAP1801 Yes Clathrin cage
YJR043C POL32 Yes DNA polymerase delta
YNL021W HDA1 Yes HDA complex
YNL047C SLM2 Yes Forms a complex with Slm1
YNR018W AIM38 No
YPR024W YME1 No
YDL225W SHS1 Yes Septin complex
hda1∆
YEL036C ANP1 No
YAL048C GEM1 No
107
The set of genetic interactions associated with mutation of a gene, known as the genetic
interaction profile, is a rich phenotypic signature (Costanzo et al., 2010a; Costanzo et al., 2010b)
and genes that belong to the same pathway tend to have similar interaction profiles (Tong et al.,
2004). Genetic interaction profiles can be used to construct correlation-based networks, allowing
prediction of gene function, protein complexes and biological pathways (Costanzo et al., 2010a).
I examined the correlation between the SDL profiles of the KDACs and the SL profiles reported
by Costanzo et al. (2010) in an effort to predict novel pathways that may be controlled by
KDACs. My comparative analysis revealed some informative biological interactions. A
correlation between a gene pair in this analysis indicates that a set of genes that are toxic when
over-expressed in a kdac∆ are SL/SS when deleted in combination with the correlated gene
(Figure 3-4). For example, two components of the SAGA acetyltransferase complex (SPT3 and
TAF9) are SS/SL with a set of genes and this same set of genes are SDL with RPD3. Both Rpd3
and SAGA, regulate transcriptional elongation (Carrozza et al., 2005; Daniel and Grant, 2007;
Keogh et al., 2005; Li et al., 2007). A correlation between a KDAC and several components of a
complex that have SL/SS correlations among them strengthens the correlation (Figure 3-4-red
lines). The correlation between HDA1 and several components of the small ribosomal subunit is
one such example and supports a role for Hda1 in regulating this process. These networks may
be useful to predict non-chromatin substrates of KDACs.
108
Figure 3-4 This network shows the correlation profiles between SDL data and digenic genetic interaction
data.
Profile similarities were measured by computing Pearson correlation coefficients (PCCs). For more information
refer to Costanzo et al. (2010). An edge represents a set of common genes that are toxic when over-expressed in a
particular kdac∆ but are SL/SS when deleted in combination with the connected gene. Edges shown in black
represent correlations between SDL and SL/SS interactions. Red edges represent correlations between the digenic
interactions profiles of the connected gene pair. Nodes are colored according to the biological processes annotated
by Costanzo et al (2010).
Polarity, cell wall, cytokinesis, endocytosis Multiple annotations, Not annotated in Costanzo (2010)
Metabolism, mitochondriaSecretion DNA synthesis, repair, dynamicsG1-S, G2-M, meiosis
RNA processing, translationChromatin, transcriptionProtein folding, degradation
Peroxisome
Drug/ion transport
109
3.3.3 Synthetic dosage lethal screen with regulatory subunits uncover previously uncharacterized functions for the HDA complex
As noted earlier, Hda1 is the catalytic subunit of the HDA complex, while Hda2 and Hda3 are
regulatory subunits; physical interactions between subunits are thought to be necessary for
catalytic activity both in vivo and in vitro (Carmen et al., 1996; Wu et al., 2001). Since genes
encoding proteins that are part of a complex generally have similar genetic interaction profiles
(Collins et al., 2007; Tong et al., 2004), I reasoned that our SDL experiments would be an
unbiased genetic approach to explore whether Hda1, Hda2 and Hda3 function solely as part of
the HDA complex and to distinguish biological processes that are dependent on functional
regulatory subunits. To explore HDA function, I complemented our hda1∆ screen (see above)
with two additional genome-wide screens for SDL interactions in hda2∆ and hda3∆ mutant
strains. All interactions from each hda screen were cross-tested using serial spot dilutions in
strains deleted for each subunit of the complex (Figure 3-5A; Materials and Methods). Among
the approximately 16 000 interactions tested, we identified 327 unique interactions for the HDA
complex (Figure 3-5A and Appendix 1 Table2). Surprisingly, only ~ 7 % of the interactions
were shared among all three of the components whereas ~55% were unique to a single subunit
(Figure 3-5B). The subunit-specific interactions were enriched for distinct biological processes
indicating that Hda2 and Hda3 in particular may have previously unappreciated functions (Table
3-4).
110
Figure 3-5 SDL interactions for the HDA complex components
A) A network diagram summarizing the SDL interactions for hda1∆, hda2∆ and hda3∆. This network contains 326
unique interactions for the HDA complex. Nodes represent genes and the edges represent SDL interactions. Nodes
are colored according to the biological processes annotated by Costanzo et al (2010). A complete list of these
interactions can be found in Table 2 in Appendix 1. B) A Venn diagram highlighting the overlap between SDL
interactions between the HDA complex subunits. Only 7% of the interactions are shared between all three
complexes while 55% of the interactions are unique to one component of the complex.
Transcription
Multiple annotations, Not annotated in Costanzo (2010)
Signal transductionTransport
Sporulation
Vesicle-mediated transport
Homeostasis Lipid metabolismStress response Other
hda1∆
hda2∆
hda3∆
A
23
69
42
12
60
8240
hda1∆
hda2∆ hda3∆
B
111
Table 3-4 Enrichments within the HDA complex SDL interactions for biological process
classified using biological processes annotated by Costanzo et al (2010).
GO categories hda2∆ hda1∆ hda3∆
Fold P-value Fold P-value Fold P-value
protein folding/protein glycosylation/cell
wall biogenesis&integrity 0.674 8.73E-01 1.312 2.85E-01 0.752 7.70E-01
cell polarity/morphogenesis 1.227 2.84E-01 1.241 3.16E-01 1.659 1.08E-01
drug/ion transport 2.537 1.12E-05 1.552 9.55E-02 1.698 8.12E-02
metabolism/mitochondria 1.088 3.40E-01 1.147 2.73E-01 0.976 5.85E-01
G1/S and G2/M cell cycle
progression/meiosis 1.167 4.09E-01 1.623 1.64E-01 2.17 5.73E-02
ER<->Golgi traffic 1.725 1.33E-01 2.798 1.20E-02 1.069 5.63E-01
Golgi/endosome/vacuole/sorting 1.49 1.19E-01 1.884 3.85E-02 1.763 1.01E-01
ribosome/translation 0.443 9.91E-01 0.493 9.67E-01 0.659 8.67E-01
nuclear-cytoplasic transport 1.465 3.37E-01 2.036 1.82E-01 5.445 7.17E-04
lipid/sterol/fatty acid biosynth 1.522 1.36E-01 0.941 6.22E-01 1.572 2.12E-01
autophagy/CVT 0 1.00E+00 0 1.00E+00 0 1.00E+00
peroxisome 5.032 3.68E-04 3.997 1.69E-02 1.336 5.32E-01
signaling/stress response 0.644 9.13E-01 0.896 6.69E-01 0.399 9.65E-01
chromatin/transcription 0.53 9.75E-01 0.737 8.35E-01 0.657 8.68E-01
protein degradation/proteosome 0.817 7.18E-01 1.515 2.71E-01 2.025 1.34E-01
RNA processing 0.321 9.88E-01 0.67 8.33E-01 0.896 6.58E-01
DNA replication/repair/HR/cohesion 1.239 3.02E-01 0.383 9.71E-01 1.535 1.95E-01
chromosome
segregation/kinetochore/spindle/microtubule 0.535 9.25E-01 1.737 1.07E-01 1.327 3.56E-01
112
Many genes involved in peroxisome biogenesis or maintenance were identified in the SDL
screen for hda2 suggesting a previously underappreciated role for the HDA complex in
peroxisome biology. Of the 25 peroxisome genes that were present on the over-expression array,
8 were toxic in the absence of HDA1, 14 were toxic in the absence of HDA2 while only one was
toxic in the absence of HDA3. Six of the genes were toxic in the absence of both HDA1 and
HDA2 (Table 4S). These differences in the SDL profiles suggest the possibility that the HDA
subunits may have different roles in peroxisome biology. To explore possible defects in
peroxisome biogenesis in HDA complex mutants, I assessed the number of peroxisomes in the
cell using a GFP tagged version of Pex15, an integral peroxisome membrane protein (Elgersma
et al., 1997). No difference in the number of peroxisomes was observed between a wild-type
strain and strains mutated for the three components of the HDA complex (Figure 3-6A). To
examine transport of proteins into the peroxisomal matrix, we next assayed the localization of a
peroxisome matrix protein, Pot1-GFP (Erdmann, 1994), in the same strain backgrounds. In these
experiments we saw a reduction in translocation of Pot1-GFP into the lumen of the peroxisome
in the absence of HDA complex components compared to wild type (Figure 3-6B). The most
dramatic reduction was seen in the absence of HDA2 where Pot1 localizes to the peroxisomes in
only 33% of the cells compared to 84% in a wild type strain (Figure 3-6C). These experiments
unveil a novel role for the HDA complex in transport of proteins involved in beta oxidation into
the lumen of the peroxisome.
113
Table 3-5 Peroxisome genes that are toxic when over-expressed in the absence of individual
HDA complex components
hda1∆ hda2∆ hda3∆
PEX2 PEX2 PEX12
PEX13 PEX13
PEX15 PEX15
PEX25 PEX25
PEX27 PEX27
PEX10 PEX10
PEX8 PEX32
PEX30 PEX28
PEX12
PEX11
PEX29
PEX6
PEX3
PEX12
114
Figure 3-6 Peroxisome biogenesis in the absence of HDA complex components.
A) C-terminal GFP-tagged Pex15 from the yeast GFP collection (Huh et al., 2003) was imaged in wild type, hda1∆, hda2∆ and hda3∆ backgrounds using a confocal microscope. B) Pot1-GFP from the same collection was also
examined in wild type, hda1∆, hda2∆ and hda3∆ backgrounds C) Quantified data for the Pot1-GFP localization
phenotype generated from three independent experiments.
A Wild type hda1∆ hda2∆ hda3∆
Pex15-GFP
DIC
Wild type hda1∆ hda2∆ hda3∆
Pot1-GFP
DIC
B
0
10
20
30
40
50
60
70
80
90
1 2 3 4hda1∆ hda2∆ hda3∆Wild type
% c
ells
wit
h P
ot1
in t
he
per
oxis
om
eC
115
3.3.4 The SDL dataset is enriched for in vivo acetylated proteins
As noted earlier, SDL screens have been previously used to identify targets of kinases (Sopko et
al., 2006a) and ubiquitin-binding proteins (Liu et al., 2009). I used a secondary biochemical
assay to ask if genes encoding acetylated proteins, which are probable KDAC targets, were
enriched amongst the SDL interactions in our KDAC mutant screens. I chose the Rpd3 screen as
a test case since: [1] Rpd3 is the most extensively studied KDAC in S. cerevisiae (Bernstein et
al., 2000; Fazzio et al., 2001; Vogelauer et al., 2000); (Kurdistani et al., 2002; Robert et al.,
2004); (Robyr et al., 2002) and [2] the human homologue of Rpd3, HDAC1, deacetylates
multiple proteins in addition to histones in human cells (Glozak et al., 2005). I used a western
blot assay with an anti-acetyl-lysine antibody to ask if proteins encoded by genes SDL in rpd3
were acetylated in vivo. I tested 184 proteins whose over-expression was toxic in the absence of
RPD3 and identified 73 in vivo acetylated proteins (40% - Figure 3-7), two of which, Yng2 and
Rsc4, were known KDAC substrates (Choi et al., 2008; VanDemark et al., 2007). My
biochemical survey of RPD3 SDL hits substantially expands the list of known acetylated
proteins in yeast (from 19 to 90) and identified proteins involved in transcription, cell polarity
and budding, growth and morphogenesis, vesicle fusion and transmembrane transport. This
functional diversity is consistent with the many roles of acetylated proteins in mammalian cells
(Choudhary et al., 2009; Glozak et al., 2005; Zhao et al., 2010) and suggests that many
biological processes may also be regulated by acetylation in yeast. I also used our western blot
assay to test a random set of 95 proteins and detected acetylation of ~20% of the proteins tested.
Thus the KDAC-SDL roster is significantly enriched for acetylated proteins (~20% vs 40%; p-
value=1.5x10-14
).
116
Figure 3-7 SDL identified in vivo acetylated proteins.
Wild type strains were transformed with plasmids carrying genes identified in the rpd3∆ screen. GST-tagged
proteins were pulled down using Glutathione-sepharose beads. Western blots were performed using an antibody
against acetylated lysines to detect protein acetylation. Anti GST western blots were also performed to confirm
efficient pull down. This diagram summarizes the 73 in vivo acetylated proteins detected using the above assay.
Nodes were color coded according to their GO biological process. Yeast orthologues of mammalian proteins known
to be acetylated are circled in Red.
Sporulation
Homeostasis Lipid metabolism Transcription
Multiple annotations/not annotated in Costanzo (2010)
Signal transduction
TransportVesicle-mediated transport
Stress response
Other
117
3.3.5 Swi4 is regulated by acetylation
To prioritize genes for follow-up studies that would identify direct non-histone targets of
KDACs, I compared my SDL screens to the results of a high-sensitivity mass spectrometry
experiment that catalogued 1750 acetylated proteins in mammalian cells (Choudhary et al.,
2009). Fifty two percent (908) of the human proteins that are acetylated have yeast homologues
(O'Brien et al., 2005), 73 of which were toxic when over-expressed in the absence of KDACs
and ten were specifically SDL in the absence of rpd3 (Figure 3, circled in Red). One of these
genes encodes Swi4, the yeast analogue of the mammalian transcription factor E2F. Both Swi4
and E2F activate G1-specific transcription via a regulatory pathway that is well conserved
between budding yeast and higher eukaryotes (Costanzo et al., 2004; de Bruin et al., 2004;
Schaefer and Breeden, 2004). Acetylation of the E2F at sites adjacent to its DNA binding
domain augments its DNA binding, increases its stability and stimulates its transactivation
activity (Martinez-Balbas et al., 2000; Marzio et al., 2000). Swi4 is the DNA-binding component
of the transcription factor SBF and interacts with a heterodimeric partner Swi6 to regulate the
expression of cyclins and other genes expressed in late G1 (Wittenberg and Reed, 2005). As
described in Chapter 2, we and others have shown previously that the repressor of SBF, Whi5,
mediates repression in part through interaction with two KDACs, Hos3 and Rpd3 (Huang et al.,
2009; Wang et al., 2009). In fact, Rpd3 is recruited to G1 promoters, placing it in proximity to
Swi4 (Robert et al., 2004; Takahata et al., 2009; Wang et al., 2009).
These data, together with the SDL interaction between RPD3 and SWI4 (Figure 3-8A), suggest
that Swi4 may be directly regulated by acetylation. I used several assays to test this possibility.
First, consistent with an enzyme-substrate relationship between Rpd3 and Swi4, the levels of
Swi4 acetylation were increased in an rpd3∆ mutant (Figure 3-8B). Next, I identified acetylated
peptides in Swi4 using mass spectrometry and two of the acetylation sites, K1016 and K1066
(Figure 3-8C), were located in the C-terminal domain of Swi4 which is required for interaction
with its regulatory partner, Swi6 (Andrews and Moore, 1992). I mutated both residues to either
arginine (R), which mimics constitutive deacetylation (Swi4-RR), or glutamine (Q), which
mimics constitutive acetylation (Swi4-QQ) and replaced the wild-type gene with the mutated
derivatives at the endogenous locus (Figure 3-8D).
118
Figure 3-8 Swi4 is acetylated in vivo.
A) Over-expression of SWI4 causes a severe growth defect in the absence of RPD3. Wild type rpd3∆, hda1∆,
hos1∆, hos2∆ and hos3∆ bearing either pGAL1/10-GST-63His-SWI4 or vector (pEGH) were tested using liquid
growth assays. Growth rate is reported relative to the wild type strain bearing vector as shown. B) Swi4MYC
tagged at
the chromosomal locus and introduced to wild type. Swi4 expression was confirmed by western blot analysis using
anti-MYC antibody. Lysates were immunoprecipitated using the same antibody and Swi4 acetylation was detected
using an antibody against acetylated lysines. Acetylation of Swi4 is increased in the absence of RPD3 and HDA1. C)
Mass spectrometry was performed for full length Swi4 using two different enzymes to produce peptide. Peptides
highlighted in Red were identified in the first run following digestion with trypsin and the peptides underlined in
purple were detected upon digesting with GluC-AspN. The two acetylated lysines are shown in green and were
detected in both runs. D) A schematic of Swi4 show location of the relevant proteins domains (abbreviations DBD,
DNA binding domain) and the location of the acetylated lysines (K1016 and K1066; arrows).
Vecto
r
Vecto
r
Vecto
r
Vecto
r
Vecto
r
Vecto
r
GA
L-S
WI4
GA
L-S
WI4
GA
L-S
WI4
GA
L-S
WI4
GA
L-S
WI4
GA
L-S
WI4
WT rpd3∆ hda1∆ hos1∆ hos2∆ hos3∆
0
20
40
60
80
100
120A
Fit
ness
BSwi4Myc IP: MYC
WT
rpd3
∆
hd
a1∆
hos1
∆
ho
s2∆
hos3
∆
Ac-Swi4
Swi4-myc
Probe:
anti-Ac-
lysine
Probe:
anti-MYC
Red text - Observed in the MS after trypin digestion
- Observed following GluC-AspN digestion
K - Acetylated
C
Ankyrin Repeats
Swi6 Binding
DNA binding domain
1066
36 170 510 689 950
1016
1092
D
Acetylated lysine residues
119
I then assessed the Swi4 mutant strains for phenotypes associated with defects in Swi4 function.
The point mutations had little effect on cell growth (Figure 3-9A) or protein abundance (Figure
3-9B) and did not detectably alter the ability of Swi4 to bind to the CLN2 promoter in log-phase
cells (Figure 3-9C). To assess the potential effects of defects in Swi4 acetylation on G1
transcription, I synchronized wild-type cells and strains harboring the mutated derivative of Swi4
in G1 with pheromone, and then followed expression of a SWI4 target gene, CLN2, using
quantitative real-time PCR (Q-PCR) as cells progressed through the cell cycle. As expected,
expression of CLN2 was induced during the G1-S phase transition in wild-type cells, but was
constitutively expressed in the swi4∆ strain (Figure 4D (Cross et al., 1994)). Likewise, induction
of CLN2 was dramatically reduced in cells expressing Swi4-RR, which approximates
constitutive deacetylation. In contrast, cells expressing the Swi4-QQ protein showed no defect
in CLN2 expression. These results suggest that deacetylation of Swi4 is important for its role in
activating G1-specific transcription.
120
Figure 3-9 Effects of Swi4 point mutations.
A) Wild type, Swi4-QQ, Swi4-RR and swi4∆ were spotted in serial 15-fold dilutions on YPD and incubated at 30
°C. Point mutations have no effect on growth while a swi4∆ shows a slow growth phenotype. B) Cell extracts from
wild type, Swi4-QQ, Swi4-RR strains were probed with an antibody against Swi4 in a western blot to detect protein
levels. Point mutations have no effect on Swi4 expression levels. Equal loading is shown using an antibody against
hexokinase. D) Swi4 binding to the CLN2 promoter detected using chromatin immunoprecipitation (ChIP). Wild
type, Swi4-QQ, Swi4-RR and swi4∆ strains were cross-linked with formaldehyde followed by an
immunoprecipitation using an antibody specific to Swi4. ChIP from the indicated strains were analyzed for CLN2
promoter sequence by quantitative RT-PCR. D) cDNA was prepared from the strains containing wild type Swi4,
point mutant mimicking constitutive acetylation Swi4-QQ (lysine to glutamine substitution) and a point mutant that
mimics constitutive deacetylation Swi4-RR (lysine to arginine substitution). CLN2 expression levels were quantified
using Q-PCR normalized using transcript levels of ACT1. Each strain was synchronized using alpha factor (5µM)
and samples were taken every 15 minutes after release. FACS samples were taken to show progression through the
cell cycle.
Swi4-QQ
WT
Swi4-RR
swi4∆
A
Swi4
WT
Swi4
-RR
swi4
∆
Probe: anti-Swi4
Probe:anti-hexokinase
Cell Extract
B
Ch
IPef
fici
ency
Sw
i4
0
5
10
15
20
25
WT QQ RR swi4∆
C
0
1
2
3
4
5
6
log 0 15 30 45 60
Time
WT
RR
swi4∆
CL
N2/A
CT
1
D
121
Because the acetylated residues reside in the C-terminal domain of Swi4, which is required for
interaction with Swi6, I next tested the prediction that the Swi4-Swi6 interaction may be
regulated by Swi4 acetylation. I assessed binding of Swi6 or Swi4 to the CLN2 promoter using
chromatin immunoprecipitation (ChIP) with antibodies to the endogenous proteins. In both
asynchronous cells and G1-synchronized cells, the ratio of Swi6 to Swi4-RR at the CLN2
promoter was reduced relative to both wild-type Swi4 and Swi4-QQ (Figure 3-10A), suggesting
that acetylation of Swi4 may be needed for a stable association with Swi6 at G1 promoters.
Consistent with this observation, I saw reduced association between Swi4-RR and Swi6
interaction relative to the wild-type interaction in a co-immunoprecipitation experiment (Figure
3-10B). Conversely, deletion of rpd3 increased the Swi4-Swi6 interaction (Figure 3-10C),
suggesting a requirement for acetylation of Swi4 for proper association between Swi4 and Swi6.
These results establish a role for Swi4 acetylation in regulating G1 transcription, strengthening
the analogy between the SBF and E2F pathways.
122
Figure 3-10 Effect of acetylation on Swi4-Swi6 protein-protein interaction
A) Swi6 binding to the CLN2 promoter detected using chromatin immunoprecipitation (ChIP) in both asynchronous
samples and cell in G1 synchronized using alpha factor (5µM). Wild type, Swi4-QQ and Swi4-RR strains were
cross-linked and immunoprecipitations were performed using antibodies specific to Swi4 and Swi6. Presence of
CLN2 promoter sequence was analyzed using quantitative RT-PCR. ChIP efficiency is shown as a ratio between
Swi6:Swi4. B) Endogenously tagged Swi4MYC
was immunoprecipitated from wild type, Swi4-QQMYC
and Swi4-
RRMYC
strains. Amount of associated Swi6 was detected using an antibody specific to Swi6. Antibodies against the
MYC tag were used to ensure equal loading. C) Endogenously tagged Swi4MYC
was immunoprecipitated from wild
type, rpd3∆, hda1∆ and hos1∆strains. Amount of associated Swi6 was detected using an antibody specific to Swi6.
Antibodies against the MYC tag were used to ensure equal loading.
0
0.5
1
1.5
2
2.5
3
log 15
ChIP
Eff
icie
ncy
Sw
i6/S
wi4
Rat
ioWT WT QQ RRQQ RR
Log G1
A
Sw
i4-Q
Q
WT
Sw
i4-R
R
Probe:
anti-MYC
IP: MYC
Swi6
Swi4-myc
Probe:
anti-Swi6
B
Probe:
anti-MYC
Probe:
anti-Swi6
WT
rpd
3∆
hd
a1∆
ho
s1∆
Swi4Myc IP: MYC
Swi6
Swi4MYC
C
123
3.4 Discussion
3.4.1 Exploration of the yeast lysine acetylation using genetic interactions
Here I report the first systematic assessment of synthetic dosage interactions for Class I and II
KDACs in yeast, a family of conserved biological regulators. Although a role for lysine
acetyltransferases and deacetylases in regulating non-histone proteins has been appreciated in
higher eukaryotes for some time, little information is available about acetylation of the proteome
in yeast, a genetically accessible system. To date, a protein acetylation microarray has been the
only genome-scale approach used to explore the yeast acetylome (Lin et al., 2009). My
comprehensive genetic dataset provides a powerful counterpoint to these biochemical efforts by
systematically exploring protein acetylation.
Remarkably, the synthetic dosage lethal interactors of lysine deacetylases were not enriched for
genes involved in chromatin biology, but rather for genes involved in transmembrane transport,
endocytosis and cell polarity and morphogenesis (Table 3-2). Furthermore, only 25% of the
protein products localize to the nucleus. Similar enrichment for diverse cellular functions was
revealed in the proteomic studies that explored the human acetylome (Choudhary et al., 2009;
Kim et al., 2006; Zhao et al., 2010). A comparison of the SDL interaction data to available gene
expression data revealed that many genes that genetically interact with KDACs are not
transcriptionally regulated by KDACs (Bernstein et al., 2000), nor are they functionally related
to transcriptional targets of the KDACs (Figure 3-3). Together, these observations suggest that
analysis of KDAC-gene interactions using synthetic dosage lethality uncovers a new type of
interaction that may be informative in identifying pathways that are regulated by acetylation at a
post-transcriptional level. The SDL roster for each deacetylase was enriched for unique
biological processes, consistent with a „division of labor‟ among these enzymes (Robyr et al.,
2002). Similar observations were made in a study that examined promoters of genes that were
regulated by deacetylases: only ~23% of promoter regions affected by the removal of HDA1 and
~19% of RPD3-affected regions were shared (Robyr et al., 2002), suggesting that many genes
were uniquely regulated by one KDAC.
124
I examined my network for biological information that might reveal new functions for KDACs
and lysine acetylation, focusing on proteins involved in drug/ion transport, a biological process
enriched for in the rpd3∆ screen. I observed an increased vacuolar localization for Hnm1 and
Tat2 in the absence of RPD3, implying a role for Rpd3 for the proper localization of transporters
to the cell periphery. In humans, the removal of KDAC6 results in increased degradation of the
EGF receptor because vesicles containing EGFR are targeted to the vacuole (Deribe et al., 2009;
Gao et al., 2010). Acetylation of α-tubulin, a non-histone target of KDAC6, is not only required
for proper localization of EGFR but is also required for the efficient transport of JNK-interaction
protein 1, a kinesin-1-associated cargo protein (Reed et al., 2006) and for the transport of the
brain-derived neurotrophic factor (BDNF) involved in Huntington‟s disease (Dompierre et al.,
2007). Thus the mislocalization of Hnm1 and Tat2 may reflect their status as direct downstream
targets of Rpd3 or could be due to mis-regulation of a cytoskeletal component that is
deacetylated by Rpd3.
I show that by integrating the SDL data with other genetic interaction data and using correlation
analysis to infer novel biological processes regulated by KDACs. A known relationship between
SPT3 and TAF9, genes encoding components of the SAGA acetyltransferase complex, and
RPD3 was confirmed, validating the approach. Both the SAGA complex and the Rpd3(S)
complex facilitate transcriptional elongation (Carrozza et al., 2005; Daniel and Grant, 2007;
Keogh et al., 2005; Li et al., 2007). I suggest that the deletion of genes functioning in parallel to
SAGA will result in SL interactions and the over-expression of these same genes in the absence
of RPD3 will result in a toxic phenotype, possibly due to the hyperactivation of an opposing
pathway. Thus the correlation based network can be utilized to identifying opposing pairs of
enzymes that fine tune biological pathways and to identify biological pathways that buffer each
other in the context of the cell.
3.4.2 Novel functions for the HDA complex
Interestingly, although genes encoding proteins in the same protein complex are predicted to
have similar genetic interactions (Collins et al., 2007; Tong et al., 2004), more than half of the
dosage interactions identified for the HDA complex were unique to a given subunit. Most SL
interactions for hda1∆ and hda3∆ are also unique (hda2 has not been tested; Costanzo et al.,
2010a). Likewise, a dramatic difference in the number of SL interactions and a lack of overlap
125
between the complex components was observed for the NuA4 acetyltransferase complex
(Mitchell et al., 2008). Because I cross-tested all interactions identified in my HDA complex
screens, the SDL interactions that are unique to one component may reflect novel roles for Hda2
and Hda3, either alone, or as part of other protein complexes. Given the lack of catalytic activity
in both Hda2 and Hda3 (Wu et al., 2001) the most likely prospect is that Hda2 and Hda3
participate in other chromatin remodeling complexes to perform their functions.
HDA2 has several unique SDL interactions with genes whose products are involved in
peroxisome biogenesis. In a genome-wide study that examined genes involved in fatty acid
metabolism hda2∆ was shown to have a defect in metabolizing myristic acid, a C14 saturated
fatty acid (Smith et al., 2006). None of the peroxisomal genes is known to be transcriptionally
regulated by the HDA complex (Bernstein et al., 2000), and the number of peroxisomes is not
affected by the deletion of HDA complex components under standard growth conditions.
However, I observed mis-localization of Pot1-GFP, a marker for transport of proteins into the
peroxisomal matrix, in the absence of HDA components, suggesting that the inability to
metabolize fatty acids may be due to defective transport into the peroxisomal matrix. The
enhanced Pot1 localization phenotype in the absence of HDA2 along with the defect in
metabolizing myristic acids that was only observed in a hda2∆ mutant suggests that Hda2 may
be important for target recognition. These experiments highlight the importance of performing
genetic screens with the regulatory subunits of multi-subunit enzyme complexes in order to gain
a more comprehensive understanding of the function of these complexes in the cell.
3.4.3 Non-histone proteins regulated by acetylation
My synthetic dosage lethal interaction network and western blot analyses have expanded the
known yeast acetylome by approximately four-fold. As in human cells, the in vivo acetylated
proteins are involved in diverse cellular functions including cell organization and biogenesis,
metabolism, transcription and transport (Choudhary et al., 2009; Kim et al., 2006; Zhao et al.,
2010). My experiments suggest that the SDL dataset is enriched for acetylated proteins, and is
therefore a useful starting point for exploring the acetylome. We have successfully identified
several negatively regulated substrates of the cyclin-dependent kinase Pho85 using SDL (Huang
et al., 2009; Sopko et al., 2006a; Sopko et al., 2007; Zou et al., 2009), and systematic screens of
the kinome have identified targets for an number of other kinases as well (Sharifpoor et al:
126
submitted), In the case of kinase-substrate relationships, SDL interactions are thought to reflect
accumulation of unmodified substrates (Sopko et al., 2007) and I propose that many of acetylated
proteins that are SDL in our KDAC screens are targets of their cognate deacetylase.
3.4.4 G1-transcription is controlled at multiple levels
Swi4, a protein that interacts with Swi6 to form SBF, a G1 transcription factor analogous to the
E2F in human cells, was detected in my rpd3∆ screen. Rpd3 is known to bind chromatin at G1
promoters to repress gene expression through histone deacetylation and our work extends the
known role of Rpd3 in G1 regulation (Huang et al., 2009; Wang et al., 2009). I show that Rpd3
directly regulates Swi4 and the initiation of G1 transcription via deacetylation. I summarize my
model for Rpd3-dependent regulation of G1 transcription in Figure 3-11. In addition to
repressing transcription at G1 promoters by histone deacetylation, Rpd3 also post-translationally
modifies Swi4 in the early G1 phase of the cell cycle. Acetylation of Swi4 is necessary for
optimal binding of SBF to G1 promoters, as highlighted by the reduced levels of CLN2
transcription in a SWI4 mutant that mimics constitutive deacetylation. The phosphorylation and
removal of Whi5 and Rpd3 is necessary to initiate G1 gene expression (Huang et al., 2009;
Wang et al., 2009), which is followed by the recruitment of additional chromatin remodeling
factors to these promoters (Cosma et al., 1999). Acetylation of Swi4 by a lysine acetyltransferase
(possibly Gcn5) strengthens the interaction between Swi4 and Swi6 and is necessary for the
maximal induction of G1 transcription. The phosphorylation of Swi6 by Clb6-Cdc28, causing its
exclusion from the nucleus (Harrington and Andrews, 1996; Koch et al., 1996; Sidorova and
Breeden, 1993), shuts off G1 transcription. Our results reveal a role for acetylation of Swi4 in
promoting interaction with its partner Swi6 and consequently in regulation of G1 transcription.
127
Figure 3-11 Model for acetylation dependent regulation of Swi4 and transcriptional induction at G1
Shown is a schematic of how the acetylation of Swi4 facilitates the interaction between Swi4 and Swi6.
Deacetylation of the C-terminal domain of Swi4 reduces the interaction between Swi4 and Swi6 early on in the cell
cycle via the interaction between Whi5, the repressor of SBF, and the KDAC Rpd3. Phosphorylation and removal of
Whi5 allows the recruitment of a KAT which acetylates Swi4 strengthening the interaction between Swi4 and Swi6.
This acetylation is required for the proper induction of G1 transcription.
SCB
Whi5
Swi6
Swi4
Rpd3
G1 gene
KK
Early G1
Rpd3 is at the promoter keeping Swi4 deacetylated
SCB
Swi6
Swi4
KK
Whi5 and Rpd3 dissociate from SBF. Whi5 leaves the nucleus
Whi5
P
P
Rpd3
Late G1
Cdc28 and Pho85
SCB
Swi6
Swi4
K-AcK-Ac
KAT
Swi4 acetylation due to recruitment of a KAT enhances its interaction with Swi6
Rpd3
SCB
Swi4
K-AcK-Ac
Cln3
Swi6
Rest of the cell cycle
Clb6-Cdc28 phosphorylates Swi6 promoting cytoplasmic localization
PP
Clb6
Cdc28
Rpd3
The Swi4 Acetylation cycle
128
Conclusion
Results presented here suggest that synthetic dosage lethal screens can provide a powerful
counterpoint to biochemical efforts in systematically exploring protein acetylation. KDAC over-
expression is linked to poor prognosis in many cancers (Wang et al., 2001) and several KDAC
inhibitors are currently being used as chemotherapeutics (Kavanaugh et al., 2010) and as
treatment for neurodegenerative diseases such as Alzheimer‟s (D'Mello, 2009; Dietz and
Casaccia, 2010). Yet little information is available about changes in acetylation patterns of the
proteome (Spange et al., 2009). Thus studies linking specific acetylation events to cognate
KATs/KDACs and an examination of their biological effects are important. Due to the
conserved nature of KDACs and the pathways regulated by these enzymes (Bradner et al., 2010;
Yang and Seto, 2008), genome-wide genetic studies in yeast will enhance our understanding of
the global relationships between acetylation events, and the propensity of acetylation networks to
lapse into malign states in diseased cells.
129
Chapter 4 Summary and Future Directions
130
4 Summary and Future Directions
4.1 Summary
One of the goals of my thesis work was to understand the molecular mechanisms that control
gene expression in Saccharomyces cerevisiae, with a focus on the interplay between chromatin
remodeling enzymes and cell cycle-regulated transcription. Work described in Chapter 2
highlights the importance of this interplay through an examination of the molecular details that
govern the proper regulation of G1 transcription. I show that repression of G1 genes by the
repressor Whi5 requires the activity of two lysine deacetylases, Rpd3 and Hos3, and that
contributions from multiple CDKs, Cdc28 and Pho85, are required to relieve Whi5 inhibition to
ensure the precision and accuracy of the G1 transcriptional circuit. The G1 regulatory pathway
is well conserved from yeast to man and my work further extends the parallels between these two
systems. My work also substantiates the use of yeast as a model system to decipher molecular
mechanisms that regulate conserved pathways.
During this work on G1 transcription, I developed an interest in KDACs, and the second part of
my work diverged from the study of chromatin modifying in the context of the cell cycle to using
functional genomic techniques to identify novel protein targets of lysine deacetylases. Chapter 3
describes my survey of yeast KDACs using systematic synthetic dosage lethality screens, the
first in vivo genome-wide approach to map the yeast acetylome, and emphasizes the use of SDL
to discover enzyme targets. My study extended the yeast acetylome by approximately 4-fold and
identified a direct role for acetylation in regulating the G1 transcription factor, Swi4. I also
identify processes, such as the localization of several membrane proteins to the cell periphery
and the transport of proteins into the lumen of the peroxisome,that require the activity of
KDACs.
131
4.2 Future Directions
4.2.1 Barcode SDL
It has become apparent from previous studies in our lab on yeast protein kinases, that many
enzymes may only be required under certain environmental conditions (Harrison et al., 2007).
Since the KDAC SDL screens were performed under standard growth conditions we may be
missing many of their condition-specific interactions. This may hold true specifically for the less
well characterized KDACs Hos1, Hos2 and Hos3, whose screens generated only a small number
of interactions under standard growth. To effectively perform these screens in a high-throughput
fashion under many different conditions, we require tools that allow parallel analysis of SDL in
pooled cultures.
With this in mind, a previous graduate student in the lab, Alison Ralph, generated a second
inducible yeast over-expression array which is called the „barcoded pGAL-FLEX‟ or the b-
FLEX array. In this collection sequence-verified untagged yeast ORFs have been placed under
the GAL promoter (Brizuela et al., 2002). In addition, the FLEX array takes advantage of a key
feature of the yeast deletion collection where each knockout cassette is flanked by unique
sequences that can be used as strain identifiers or molecular “barcodes”. Each plasmid on the
FLEX array has been associated with a unique bar-code using a strategy developed by (Yan et
al., 2008) (Figure 4-1). The entire collection can now be pooled into a single culture and
exposed to a particular condition after which the DNA is prepared, PCR-amplified with universal
primers and hybridized to a microarray that contains the molecular barcodes, or profiled using
next generation sequencing. This barcode strategy has been used to quantitatively monitor the
deletion collection for strains that show a fitness defect when grown in rich medium or under
various conditions (Hillenmeyer et al., 2008).
132
Figure 4-1 Strategy for condition-specific SDL screens in KDAC/KAT mutants in pooled cultures
A KDAC deletion is introduced into the b-FLEX array using SGA. In the b-FLEX array each expression
plasmid is linked to a unique barcode. Following the selection for a haploid output array where each
plasmid is now combined with the gene deletion, strains are pooled in liquid cultures. These can now be
subjected to different stressors or environmental conditions, after which the DNA is extracted, amplified
using universal primers and hybridized to a microarray.
133
A pilot study to validate the approach has been performed with the b-FLEX collection using a
kinase involved in DNA damage. I would suggest that the next screens be performed with the
five Class I and II KDACs that were tested in the plate-based assay to establish a robust baseline
for interpreting the data from these barcode SDL experiments. Following these screens, I
propose that the Class III KDACs, the Sirtuins, be screened in order to complete the yeast lysine
deacetylome.
4.2.2 Inhibitor Screens
Once developed, the barcode SDL method will be a valuable tool for determining the global
effects of KDAC and KAT inhibitors. Many of the KDAC inhibitors currently in use have basal
toxicity, which limits their effectiveness in cancer treatment in the long term (Jeong et al., 2003).
The effects of these inhibitors on gene expression have been examined in detail but the impact
beyond the acetylation of chromatin, especially with regard to the effect on non-histone
substrates, is relatively unknown (Bradner et al., 2010). Thus yeast barcode SDL screens can be
utilized to examine the global impact of KAT/KDAC inhibitors in a comprehensive manner.
Many of the inhibitors currently in use are readily available from Sigma and other sources and
many of them are known to function in yeast (Hillenmeyer et al., 2008). The small volume of
the pooled cultures also makes this method amenable to screening of natural compounds, many
of which are limited in quantity.
I anticipate that these screens will reveal conditions under which KATs and KDACs may have a
phenotype and highlight biology that should be considered when administering particular
chemotherapeutic agents that consist of KAT/KDAC inhibitors. It will also be useful to mine the
expanding SL interaction matrix (Costanzo et al., 2010a) to discover genetic backgrounds in
which single deletions of KATs and KDACs will yield obvious phenotypes or that may sensitize
these mutants to defects in certain biological processes. The exploration of the „inhibitor‟
acetylome will provide the first comprehensive view of the global impact of KAT and KDAC
inhibitors.
4.2.3 Systematic cell biological screens in acetyltransferase/deacetylase mutants
The KDAC SDL screens to date only use a single metric, colony size, as a proxy for cell fitness
to assay genetic interactions. More interactions will be uncovered through a comprehensive
134
phenotypic analysis that will also provide more detailed mechanistic insight about gene and
pathways functions. For this purpose, several high-content screening platforms have been
developed in the Boone and Andrews group in the past five years (Vizeacoumar et al., 2009;
Vizeacoumar et al., 2010) with the goal of assaying specific biological processes systematically
and quantitatively in the physiological context of living cells. Although a collection of yeast
strains, where each ORF is fused with a fluorescent (GFP) tag, has been constructed (Huh et al.,
2003) this collection is underutilized due to the challenges associated with implementing systems
for high-content screening (HCS) in yeast. A post-doctoral fellow in the lab, Yolanda Chong,
has developed a HCS pipeline that allows the systematic tracking of genome-wide changes in
protein localization and abundance in various mutant backgrounds. I propose to use this
technology to examine the effects of KATs and KDACs on protein localization and stability.
Together with the SDL data, these microscopy screens will generate a comprehensive view of
the global effects of these enzymes will help prioritize potential non-histone targets for follow-
up.
The initial step in these experiments will consist of generating a collection of query strains that
carry either deletions or temperature-sensitive alleles of KATs and KDACs together with an
RFP-cytosolic marker. This marker is necessary to locate the yeast cell during automated image
analysis. Next, SGA will be used to introduce the query deletions into the GFP-ORF collection,
after which cells will be imaged using the HCS screening pipeline (Figure 4-2). Images can be
acquired and analyzed using CellProfiler, an open source software suite that allow acquisition of
measurements such as fluorescence intensity, shape, size and texture (Carpenter et al., 2006). An
image analysis pipeline has been generated to distinguish high quality images from low quality
images (slides with dust, etc) and several genome-wide wild-type screens have been used to
generate classifiers, for the computational identification of 18 different localization patterns.
Using this pipeline, proteins that change in localization under specific genetic and environmental
conditions can be easily identified.
I have completed a pilot HCS in the absence of RPD3 with encouraging results. I discovered 68
proteins that change in abundance and 48 proteins that change in localization in the absence of
RPD3. This data is summarized in Appendix 2. I propose to extend this analysis to the
remaining KDACs, thus combining SDL and HCS to scrutinize the entire yeast acetylome in an
attempt to understand the role of acetylation.
135
Figure 4-2 High-content screening pipeline
A query strain carrying a RFP-cytosolic marker and a kdac deletion is crossed to the yeast GFP collection using
SGA. Once haploids are selected, where the output array contains mutants where each ORF-GFP is now combined
with both the kdac deletion and the cytosolic RFP, cells are transferred to liquid culture and grown to saturation.
Cell are next subcultured and grown for 16-18hrs until they reach early log phase. Image acquisition is done in a
384 well format where each plate is imaged in less than an hour. The localization pattern in a mutant background is
compared to wild type to identify changes.
136
4.3 Overall significance
It is well established that the dynamic interplay of lysine acetyltransferases and lysine
deacetylases is required to maintain appropriate levels of histone acetylation and that abnormal
KAT/KDAC function results in disease states such as cancer (Archer and Hodin, 1999; Bradner
et al., 2010; Das and Kundu, 2005). Sequencing and other projects continue to reveal the
massive genetic variation that defines the „cancer genome‟ (Shah et al., 2009), and we are faced
with the challenge of not only relating many mutations in KATs and KDACs themselves to the
cancer phenotype, but also of understanding how myriad other mutations directly or indirectly
influence the global acetylation-based network (Bild et al., 2006). The complexity of this
challenge has been magnified in the past decade with an emerging role for KATs and KDACs in
regulating proteins other than histones (Kurdistani and Grunstein, 2003).
Although much research has determined the principle effects of KAT/KDAC inhibitors on gene
expression patterns, little information is available about changes in acetylation patterns for the
rest of the proteome (Spange et al., 2009). In order to appreciate the mechanism of action of
KAT inhibitors and KDAC inhibitors, and the roles of protein acetylation in cancer, we must
explore the acetylated proteins in the cell in a systematic fashion. My thesis work presents the
first systematic approach that comprehensively examines the yeast lysine deacetylome in vivo. I
have established a system that can now be exploited to assess global effects of KDAC inhibitors
and KAT inhibitors and can also be modified to identify individual KDAC-specific inhibitors.
Many components of the G1 transcriptional circuit that include KDAC1/Rb/E2F/Cdk4 are
universally mutated in many tumours. Both Rb and E2F are known to also be regulated by
acetylation (Martinez-Balbas et al., 2000; Pickard et al., 2010). While acetylation increases
protein stability, transactivation potential and DNA binding of E2F, my work with Swi4
demonstrates the possibility that E2F activity may also regulated at the level of its protein-
protein interaction with the heterodimeric partner DP1. The work described in this thesis, and
the experiments I have proposed, will lead to a greater understanding of the regulatory circuits
controlled by aceyltation in eukaryotic cells
137
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Appendices
Appendix 1: Data from Chapter 3
Table 1 SDL interactions for the 5 Class I and II KDAC screens
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
rpd3∆ YFL049W SWP82 rpd3∆ YAL022C FUN26 rpd3∆ YOR275C RIM20
YBL106C SRO77
YBR207W FTH1
YPL019C VTC3
YBR059C AKL1
YDR011W SNQ2
YPL232W SSO1
YBR108W AIM3
YGL006W PMC1
YGR142W BTN2
YCL014W BUD3
YGL255W ZRT1
YBR014C GRX7
YHR061C GIC1
YGR138C TPO2
YDR497C ITR1
YHR114W BZZ1
YHL040C ARN1
YGL077C HNM1
YHR135C YCK1
YJR040W GEF1
YGR157W CHO2
YHR161C YAP1801
YKR093W PTR2
YMR272C SCS7
YLR353W BUD8
YLL015W BPT1
YNR032W PPG1
YPR171W BSP1
YLR220W CCC1
YPL145C KES1
YKL043W PHD1
YPR124W CTR1
YAL008W FUN14
YOL112W MSB4
YDL210W UGA4
YAL048C GEM1
YCL048W SPS22
YKL146W AVT3
YBL098W BNA4
YLR206W ENT2
YOL020W TAT2
YBR183W YPC1
YML052W SUR7
YFL011W HXT10
YGL035C MIG1
YDR099W BMH2
YGR096W TPC1
YGL219C MDM34
YHR082C KSP1
YHR094C HXT1
YGR174C CBP4
YFR013W IOC3
YJR077C MIR1
YKL187C YKL187C
YGL096W TOS8
YJR152W DAL5
YMR030W RSF1
YGL244W RTF1
YKL217W JEN1
YMR261C TPS3
YHR006W STP2
YLR047C FRE8
YMR302C YME2
YKL005C BYE1
YNR072W HXT17
YNL070W TOM7
YMR039C SUB1
YBR172C SMY2
YPL134C ODC1
YNL021W HDA1
YJL123C MTC1
YPR024W YME1
YPR065W ROX1
YOR216C RUD3
YDR216W ADR1
YLR176C RFX1
YHL024W RIM4
YML051W GAL80
YBR158W AMN1
YER111C SWI4
YNL307C MCK1
YMR198W CIK1
YLR263W RED1
YHR015W MIP6
YBR223C TDP1
YNL047C SLM2
YMR153W NUP53
YCL016C DCC1
YGR100W MDR1
YOR185C GSP2
YJR035W RAD26
YGR106C VOA1
YDL091C UBX3
YJR043C POL32
YJR126C VPS70
YLR097C HRT3
YLR453C RIF2
YKR088C TVP38
YAL023C PMT2
YOR229W WTM2
YOR106W VAM3
YAL053W FLC2
YOR386W PHR1
YOR270C VPH1
YBR015C MNN2
159
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
rpd3∆ YEL036C ANP1 rpd3∆ YFR039C YFR039C rpd3∆ YDL145C COP1
YFR041C ERJ5
YGL080W FMP37
YDR038C ENA5
YGR032W GSC2
YGR249W MGA1
YDR189W SLY1
YHR030C SLT2
YHR017W YSC83
YDR231C COX20
YKL046C DCW1
YHR039C MSC7
YDR303C RSC3
YML117W NAB6
YHR162W YHR162W
YDR432W NPL3
YGR044C RME1
YIL087C LRC2
YDR499W LCD1
YLR207W HRD3
YJL051W IRC8
YEL009C GCN4
YDR312W SSF2
YJR054W ERM6
YER009W NTF2
YDR385W EFT2
YJR124C YJR124C
YER014W HEM14
YGR148C RPL24B
YKR075C YKR075C
YER027C GAL83
YLR185W RPL37A
YLR112W YLR112W
YER028C MIG3
YML068W ITT1
YLR352W YLR352W
YER125W RSP5
YOL093W TRM10
YMR073C IRC21
YFL038C YPT1
YPL079W RPL21B
YMR182C RGM1
YFL039C ACT1
YLR107W REX3
YMR195W ICY1
YGL075C MPS2
YMR285C NGL2
YMR295C IBI2
YGL122C NAB2
YDL134C PPH21
YNL046W YNL046W
YGL186C TPN1
YGL229C SAP4
YNL100W AIM37
YGL189C RPS26A
YHR076W PTC7
YNR018W AIM38
YGL233W SEC15
YLR433C CNA1
YOR271C FSF1
YGR056W RSC1
YOR360C PDE2
YOR283W YOR283W
YGR077C PEX8
YML007W YAP1
YOR378W YOR378W
YHL031C GOS1
YBL059W YBL059W
YPL105C SYH1
YHR056C RSC30
YBR047W FMP23
YPL246C RBD2
YHR062C RPP1
YBR054W YRO2
YPL250C ICY2
YHR090C YNG2
YDL119C YDL119C
YPR157W YPR157W
YJL023C PET130
YDL167C NRP1
YAL032C PRP45
YJL080C SCP160
YDL183C YDL183C
YBL050W SEC17
YJL143W TIM17
YDR132C YDR132C
YBR079C RPG1
YJL210W PEX2
YDR330W UBX5
YBR159W IFA38
YJR017C ESS1
YDR509W YDR509W
YBR192W RIM2
YJR093C FIP1
YDR538W PAD1
YCR028C FEN2
YKL049C CSE4
YER037W PHM8
YCR039C MATALPHA2 YKL126W YPK1
YER048C CAJ1
YDL084W SUB2
YKL154W SRP102
YER060W FCY21
YDL090C RAM1
YKL193C SDS22
160
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
rpd3∆ YKR002W PAP1 hda1∆ YBL007C SLA1 hda1∆ YML001W YPT7
YLR026C SED5
YBR059C AKL1
YOR275C RIM20
YLR060W FRS1
YDL225W SHS1
YPL232W SSO1
YLR071C RGR1
YDR507C GIN4
YDR100W TVP15
YLR117C CLF1
YHR061C GIC1
YDR213W UPC2
YLR191W PEX13
YOL112W MSB4
YGL077C HNM1
YML010W SPT5
YLR206W ENT2
YLR228C ECM22
YML086C ALO1
YBR158W AMN1
YAL048C GEM1
YMR197C VTI1
YNL153C GIM3
YBL098W BNA4
YMR229C RRP5
YLR227C ADY4
YGL219C MDM34
YMR239C RNT1
YBR274W CHK1
YGR174C CBP4
YNL026W SAM50
YJL047C RTT101
YIL006W YIA6
YNL039W BDP1
YBR203W COS111
YJL166W QCR8
YNL103W MET4
YGR138C TPO2
YKL085W MDH1
YNL137C NAM9
YHL040C ARN1
YKL187C YKL187C
YNL204C SPS18
YOL020W TAT2
YLR251W SYM1
YNL225C CNM67
YOR172W YRM1
YMR302C YME2
YNL256W FOL1
YFL040W YFL040W
YPL134C ODC1
YNL279W PRM1
YEL006W YEA6
YPR024W YME1
YOL130W ALR1
YFL011W HXT10
YPR128C ANT1
YOR212W STE4
YJR077C MIR1
YBR185C MBA1
YOR254C SEC63
YKL217W JEN1
YML120C NDI1
YOR257W CDC31
YPL270W MDL2
YFR034C PHO4
YOR329C SCD5
YBR172C SMY2
YAR002W NUP60
YOR335C ALA1
YGR284C ERV29
YMR153W NUP53
YPL112C PEX25
YJL123C MTC1
YDL175C AIR2
YPL254W HFI1
YOR307C SLY41
YDL091C UBX3
YPR133W-A TOM5
YBL078C ATG8
YLR097C HRT3
YHL024W RIM4
YGL003C CDH1
YLR263W RED1
YEL036C ANP1
YGR049W SCM4
YGR282C BGL2
YLR210W CLB4
YHR030C SLT2
YPL256C CLN2
YKL046C DCW1
YJL004C SYS1
YKR027W BCH2
YJR125C ENT3
YGR044C RME1
YKR030W GMH1
YDR312W SSF2
YLR262C YPT6
YNL292W PUS4
161
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
hda1∆ YHR076W PTC7 hda1∆ YLR366W YLR366W hda1∆ YOR116C RPO31
YDR259C YAP6
YBL050W SEC17
YOR160W MTR10
YDL062W YDL062W
YBL105C PKC1
YOR181W LAS17
YDR171W HSP42
YBR089C-A NHP6B
YPL112C PEX25
YDR249C YDR249C
YBR159W IFA38
YPL235W RVB2
YDR251W PAM1
YCR081W SRB8
YPR161C SGV1
YDR374C YDR374C
YDL160C DHH1
YGL068W MNP1
YGL083W SCY1
YDR188W CCT6
YLR403W SFP1
YHR017W YSC83
YDR323C PEP7
YGR002C SWC4
YIL055C YIL055C
YGL075C MPS2
YDR468C TLG1
YIL087C AIM19
YGL106W MLC1
YLR196W PWP1
YIL089W YIL089W
YGL186C TPN1
YNL279W PRM1
YIL156W UBP7
YGL201C MCM6
YEL017W GTT3
YIR024C YIR024C
YGR064W YGR064W
YDL028C MPS1
YJL162C JJJ2
YGR077C PEX8
YDR038C ENA5
YJL182C YJL182C
YGR098C ESP1
YJL193W YJL193W
YHL007C STE20
YJR100C AIM25
YHL031C GOS1
YJR124C YJR124C
YHR056C RSC30
YLR083C EMP70
YHR065C RRP3
YLR112W YLR112W
YHR089C GAR1
YLR224W YLR224W
YJL096W MRPL49
YLR428C YLR428C
YJL210W PEX2
YML035C-A YML035C-A YJR093C FIP1
YMR052C-A YMR052C-A YJR160C MPH3
YOL029C YOL029C
YKL126W YPK1
YOL092W YOL092W
YKL193C SDS22
YOR283W YOR283W
YML010W SPT5
YOR352W YOR352W
YML088W UFO1
YPL070W MUK1
YMR014W BUD22
YPL071C YPL071C
YMR032W HOF1
YPL245W YPL245W
YMR082C YMR082C
YPL250C ICY2
YNL225C CNM67
YPR098C YPR098C
YNR035C ARC35
YPR158W CUR1
YNR052C POP2
YOL084W PHM7
YOL034W SMC5
YJL152W YJL152W
YOR008C SLG1
162
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
hos1∆ YDL145C COP1 hos2∆ YLR366W YLR366W hos3∆ YPL134C ODC1
YDR028C REG1
YPR065W ROX1
YBR014C GRX7
YGL172W NUP49
YKL020C SPT23
YBR006W UGA2
YNL256W FOL1
YPL134C ODC1
YJL116C NCA3
YOR008C SLG1
YGL256W ADH4
YHR076W PTC7
YBL106C SRO77
YDL088C ASM4
YNL256W FOL1
YHR061C GIC1
YHR156C LIN1
YBR079C RPG1
YLR114C AVL9
YLR112W YLR112W
YBL105C PKC1
YHR082C KSP1
YLR057W YLR057W
YGL006W PMC1
YBL059W YBL059W
YGR096W TPC1
YGR064W YGR064W
YOL027C MDM38
YJL143W TIM17
YDR084C TVP23
YDL084W SUB2
YGR100W MDR1
YOL034W SMC5
YDR497C ITR1
YER014W HEM14
YGL256W ADH4
YDL067C COX9
YMR145C NDE1
YPL134C ODC1
YKL015W PUT3
YOR133W EFT1
YBL032W HEK2
YHR017W YSC83
YHR162W YHR162W
YIL055C YIL055C
YJL105W SET4
YNL028W YNL028W
YBR159W IFA38
163
Table 2 SDL interactions for hda2∆ and hda3∆ components
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
hda2∆ YCR027C RHB1 hda2∆ YNL065W AQR1 hda2∆ YBL098W BNA4
YDL131W LYS21
YOL020W TAT2
YBR024W SCO2
YBL007C SLA1
YNL101W AVT4
YGL219C MDM34
YBR059C AKL1
YBR180W DTR1
YLR251W SYM1
YDL225W SHS1
YFL040W YFL040W
YMR030W RSF1
YDR085C AFR1
YBR294W SUL1
YMR256C COX7
YHR061C GIC1
YEL006W YEA6
YNL070W TOM7
YHR114W BZZ1
YFL011W HXT10
YOR045W TOM6
YHR161C YAP1801
YJR077C MIR1
YPL134C ODC1
YHR161C YAP1801
YKL217W JEN1
YPR024W YME1
YLR353W BUD8
YLR047C FRE8
YPR128C ANT1
YPR171W BSP1
YOL027C MDM38
YLR395C COX8
YKL101W HSL1
YBR172C SMY2
YBR185C MBA1
YML052W SUR7
YGR284C ERV29
YKL187C YKL187C
YGL066W SGF73
YJL123C MTC1
YIR031C DAL7
YMR039C SUB1
YOR216C RUD3
YOR135C IRC14
YKL005C BYE1
YOR307C SLY41
YML051W GAL80
YBR274W CHK1
YHL024W RIM4
YMR110C HFD1
YHR031C RRM3
YLR263W RED1
YPR125W YLH47
YJR043C POL32
YLR210W CLB4
YIL045W PIG2
YML032C RAD52
YPL256C CLN2
YLR273C PIG1
YOL015W IRC10
YGR106C VOA1
YHR015W MIP6
YOR229W WTM2
YKL135C APL2
YMR153W NUP53
YDR279W RNH202
YLR262C YPT6
YDR192C NUP42
YBR043C QDR3
YML001W YPT7
YDL091C UBX3
YBR203W COS111
YOR270C VPH1
YLR097C HRT3
YFL054C YFL054C
YPL232W SSO1
YMR276W DSK2
YGR138C TPO2
YOR106W VAM3
YDL203C ACK1
YHL040C ARN1
YJL004C SYS1
YEL036C ANP1
YHR048W YHK8
YGR142W BTN2
YHR030C SLT2
YLR220W CCC1
YDR497C ITR1
YKL046C DCW1
YOR306C MCH5
YDR503C LPP1
YOR188W MSB1
YKR093W PTR2
YGL077C HNM1
YGL031C RPL24A
YDL210W UGA4
YLR228C ECM22
YGR148C RPL24B
YHL036W MUP3
YPL145C KES1
YLR059C REX2
YKL146W AVT3
YAL048C GEM1
YPR040W TIP41
164
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
hda2∆ YBR250W SPO23 hda2∆ YPL205C YPL205C hda2∆ YJL080C SCP160
YDL062W YDL062W
YPL245W YPL245W
YJL096W MRPL49
YDR249C YDR249C
YPL246C RBD2
YJL143W TIM17
YDR251W PAM1
YPL250C ICY2
YJL194W CDC6
YDR538W PAD1
YPR098C YPR098C
YJL210W PEX2
YER048C CAJ1
YPR158W CUR1
YKL082C RRP14
YER060W FCY21
YLR311C YLR311C
YKL122C SRP21
YGL080W FMP37
YKL039W PTM1
YKL126W YPK1
YHR017W YSC83
YMR155W YMR155W YKL193C SDS22
YIL054W YIL054W
YAL032C PRP45
YKL210W UBA1
YIL055C YIL055C
YBL050W SEC17
YLR055C SPT8
YIL087C AIM19
YBR159W IFA38
YLR191W PEX13
YIL089W YIL089W
YBR265W TSC10
YML013W UBX2
YIL166C YIL166C
YDL028C MPS1
YML086C ALO1
YIR020C YIR020C
YDL028C MPS1
YML088W UFO1
YJL108C PRM10
YDL198C GGC1
YMR026C PEX12
YJL152W YJL152W
YDL248W COS7
YNL175C NOP13
YJL162C JJJ2
YDR091C RLI1
YNL186W UBP10
YJL182C YJL182C
YDR188W CCT6
YNL203C YNL203C
YJR100C AIM25
YDR208W MSS4
YNL256W FOL1
YJR124C YJR124C
YDR350C ATP22
YNL305C YNL305C
YKR098C UBP11
YER022W SRB4
YNR052C POP2
YLR083C EMP70
YER027C GAL83
YOL034W SMC5
YLR112W YLR112W
YGL075C MPS2
YOL130W ALR1
YLR164W YLR164W
YGL106W MLC1
YOR008C SLG1
YLR224W YLR224W
YGL186C TPN1
YOR160W MTR10
YLR366W YLR366W
YGL233W SEC15
YOR181W LAS17
YMR052C-A YMR052C-A YGR064W YGR064W
YOR193W PEX27
YMR073C IRC21
YGR077C PEX8
YPL112C PEX25
YMR295C IBI2
YGR172C YIP1
YPR133W-A TOM5
YNL028W YNL028W
YGR280C PXR1
YGL247W BRR6
YNR018W AIM38
YHL031C GOS1
YHR072W ERG7
YOL092W YOL092W
YHR007C ERG11
YIL150C MCM10
YOR228C YOR228C
YHR056C RSC30
YEL064C AVT2
YOR283W YOR283W
YHR065C RRP3
YNL279W PRM1
YOR292C YOR292C
YHR089C GAR1
YGR056W RSC1
YOR354C MSC6
YLR262C YPT6
YNL292W PUS4
165
KDAC ORF Gene KDAC ORF Gene KDAC ORF Gene
hda3∆ YAL030W RHB1 hda3∆ YHR015W UPC2 hda3∆ YNL028W YER163C
YAL048C AIM3
YHR017W ADH4
YNL065W YHL037C
YBL007C BSP1
YHR031C ANT1
YNL070W YIL089W
YBL050W GIC1
YHR061C CBP4
YNL101W YIL166C
YBL105C MSO1
YHR084W COX8
YNL116W YMR209C
YBR108W SLA1
YHR161C GAD1
YNL203C YNL028W
YBR180W YAP1801
YIL087C GEM1
YNL225C YOL092W
YBR192W HSL1
YIL089W MGM1
YNL256W YOR228C
YBR274W ENT2
YIL166C TOM7
YNR049C YPL245W
YBR300C DMA2
YJL047C YME1
YOL015W YPR174C
YCR027C GIP3
YJL143W GAL80
YOL092W YSC83
YDL091C CHK1
YJL204C HFD1
YOR008C AIM19
YDL175C IRC10
YJR017C KAP122
YOR106W AVT2
YDL239C RAD52
YJR054W MIP6
YOR172W BPL1
YDR091C RRM3
YJR100C NUP42
YOR181W CDC6
YDR100W RTT101
YKL101W NUP53
YOR211C CNM67
YDR192C ARN1
YKL135C NUP53
YOR216C ENA5
YDR208W MCH5
YKL217W AIR2
YOR228C ESS1
YDR213W YHM2
YKR098C GSP2
YOR306C FOL1
YDR304C AQR1
YLR059C PCI8
YPL245W HAS1
YDR503C AVT4
YLR358C UBX3
YPL246C LAS17
YEL013W YRM1
YLR395C DSK2
YPR024W MPH3
YER022W DTR1
YLR433C ADY3
YPR072W MPS1
YER060W HXT10
YML013W RME1
YPR128C MPS2
YFL011W JEN1
YML032C CPR5
YPR133W-A MSS4
YGL016W RUD3
YML051W PIH1
YPR171W NOT5
YGL075C RIM4
YMR110C RPS18B
YPR174C PKC1
YGL256W SRL4
YMR153W REX2
YEL064C PRP24
YGR044C APL2
YMR153W CNA1
YDL141W PXR1
YGR100W MDR1
YMR165C AIM25
YDR458C RAD53
YGR142W SNC1
YMR209C ERM6
YDR123C RCY1
YGR172C TVP15
YMR221C FCY21
YIL071C RIM2
YGR174C VAM3
YMR241W FMP42
YHR034C RLI1
YGR280C BTN2
YMR250W HEH2
YPL153C SEC17
YHL024W INO2
YMR268C RBD2
YML026C SEC4
YHL037C LPP1
YMR276W UBP11
YER163C SLG1
YHL040C PAH1
YMR290C YBR300C
YJR160C SRB4
166
KDAC ORF Gene
hda3∆ YDL028C STE12
YDR038C TIM17
YFL005W TOM5
YJL194W UBX2
YLR206W VAC8
YOR185C YIP1
YPL033C YLR358C
YPL137C YNL203C
167
Appendix 2: Data from Chapter 4
Table 1 Proteins that changed in localization in the absence of RPD3
ORF Gene
ORF Gene
Localization YLR263W RED1
YDL076C RXT3
YOR059C YOR059C
YLR363W-A YLR363W-A
YGR149W YGR149W
YBR255W MTC4
YDL089W NUR1
YCR061W YCR061W
YBL060W YEL1
YKL140W TGL1
YLR138W NHA1
YDL091C UBX3
YDR040C ENA1
YDR270W CCC2
YGL077C HNM1
YIL015W BAR1
YBL042C FUI1
YOR292C YOR292C
YOR273C RSN1
YDR046C BAP3
YDR497C KTR4
YBR205W KTR3
YNL162W RPL42A
YLR196W PWP1
YAL054C ACS1
YFL021W GAT1
YBR195C MSI1
YJR008W YJR008W
YIL110W MNI1
YHR200W RPN10
YGL250W RMR1
YDR480W DIG2
YNL292W PUS4
YJR052W RAD7
YPR017C ITR1
YKL210W UBA1
YLR194C YLR194C
YLL055W YCT1
YJL080C SCP160
YHR110W ERP5
YBR176W ECM31
YGL057C GEP7
YJL131C AIM23
YNL100W YJL171C
YGR202C PCT1
YHR156C LIN1
YFR046C CNN1
168
Table 2 Proteins that changed in abundance in the absence of RPD3
ORF Gene
ORF Gene
ORF Gene
Abundance YJL104W PAM16
YMR225C MRPL44
YBR085C-A YBR085C-A
YOL052C-A DDR2
YKL169C YKL169C
YPR073C LTP1
YLR409C UTP21
YHR055C CUP1-2
YMR244C-A YMR244C-A
YGL234W YGL234W
YHR053C CUP1-1
YNL255C GIS2
YBL027W RPL19B
YFL014W HSP12
YLR388W RPS29A
YKR071C DRE2
YNL153C GIM3
YOL134C YOL134C
YDL092W SRP14
YDL184C RPL41A
YLR050C YLR050C
YER035W EDC2
YDL085C-A YDL085C-A YNL135C FPR1
YGR206W MVB12
YLR154C RNH203
YGR008C STF2
YLR384C IKI3
YPL047W SGF11
YOL048C RRT8
YBR208C DUR1,2
YEL027W CUP5
YGR271C-A EFG1
YDR258C HSP78
YER084W
YER084W
YLL014W EMC6
YIL078W THS1
YDR461W MFA1
YNL259C ATX1
YKR046C PET10
YDR496C PUF6
YLR327C TMA10
YJL121C RPE1
YOR244W ESA1
YLR413W YLR413W
YJR017C ESS1
YMR173W DDR48
YHR039C-A VMA10
YPL046C ELC1
YPR110C RPC40
YOR271C FSF1
YGR063C SPT4
YJR145C RPS4A
YHR072W-A NOP10
YDR059C UBC5
YGR269W YGR269W
YLR179C YLR179C
YGL226W MTC3
YLR390W-A CCW14
YBR233W-A DAD3
YDR156W RPA14
YJR067C YAE1
YJL011C RPC17
YIL057C RGI2
YLL048C YBT1
YOR210W RPB10
YER131W RPS26B
YMR123W PKR1
YMR251W-A HOR7
YKL096W-A CWP2
YDR525W-A SNA2
YOR286W AIM42
YBL029C-A YBL029C-A
YJR022W LSM8
YJR104C SOD1
YIL027C KRE27
YBL004W UTP20
YDL181W INH1
YPR052C NHP6A
YNR010W CSE2
YKL170W MRPL38
YEL048C YEL048C
YNL147W LSM7
YER053C-A YER053C-A
YBR089C-A NHP6B
YOR167C RPS28A
YDR510W SMT3
YDR322C-A TIM11
YBL071W-A KTI11