Indian Journal of Biochemistry & Biophysics Vol. 37, December 2000, pp. 360-368

Minireview

yr~teomics: A powerful tool in the post-genomic era

Larysa Porubleva and Parag R Chitnis*

Department of Biochemistry, Biophysics and Molecular Bioiogy, Iowa State University, Ames , IA 500 II , USA

Accepted 23 Jllll e 2000

Genomics is having a profound impact on biological research, including photosynthesis investigations. Genomes of many photosynthetic organi sms have been sequenced. The information about ALL genes that govern and execute photo­au totroph ic metaboli sm provides many opportunities to understand genome function and details of known and uncharted pathways. Proteomics, analysis of the protein complement of the genome, is a powerful tool in understanding which proteins are present in a part icular tissue under given conditi ons. Proteomics also allows us to estimate re lat ive levels of proteins and to determine post- translational modifications of the gene products. In-this minireview, we discuss the technology and its ap­plications in plant sciences.

Genomics is one of the most influenti al fields in bi ol­ogy today . In an ed itorial in Science, Philip H. Abel­son call s genomics the " third technologica l revolu­ti on"). Recentl y, genomes of several bacteria, yeast and C. e/egans have been sequenced complete ly. Ge­nomes of severa l photosynthetic prokaryotes have been sequenced complete ly . Complete genome se­quences of Arabidopsis and rice will be known shortly . Extensive databases of ex pressed sequence tags (EST) are now available for almost every major crop spec ies. Thus plant biology has entered the ge­nomics era. These huge amounts of data provide many challenges and opportunities. Much of the in­formation in the sequenced genomes re mains un­charted. For example, 34-68% of the open read ing frames in the sequenced bacteria l genomes have un­known functions2

. Systematic approaches in func­tional genomics are required to identify roles of these genes. Another opportunity in functional genomics is the ability to examine global changes in the genome express ion in response to environmental or internal factors". Indeed, functional genomics is the next frontier4

, :; •

Almost all genes function after they are ex pressed as proteins. Therefore, proteomics, analysi s of the protein complement of the genome, is essential to

* Author for correspondence Phone: 1-5 I 5-294- 1657; Fax: 1-5 I 5-294-0453 Email: chitni s@iastate.edu Abbrevatiolls IIsed: 2D, two dimensional; 2DGE, two-dimensional gel electrophoresis ; MS, mass spectrometry; PMF, pepti de mass iingerprin ting.

understand the genome function. Proteome analys is involves identification of all proteins from an organ­ism and determination of the ir abundance6

. Due to rap id developments in the technology, proteomics is des tined to play an indi spensab le ro le in the post­genomic era?-'), In thi s minireview, we discuss the

proteomics technology and its appl icat ions, with an emphasis on photosynthetic organi sms.

What is a proteome? A proteome is the total protein complement of a

genome)O The sc ience of proteomics, in its broadest sense dea ls with the ex pression, structure and func­tion of the genome at the protein level. The most ac­tive area of proteomics (and the major emphas is in thi s minireview) is characterization of the functional proteome, which is defined as gene-products ex­pressed under spec ific environmental or intrinsic conditions. Other aspects of proteomics, such as ge­nome-wide prediction of tert iary structures and high throughput analysis of protein struc ture and bi o­chemical functions.

Analysis of a functional proteome provides a pow­erful tool for examining genome express ion. Prote ins are directl y responsible for the function and pheno­type of an organi sm. As Edmond H . Fischer, 1992 Nobel Laureate, points out, genome sequenc ing might enable us to predict the prote ins that can pote nti a ll y

)) be generated, but not where, when o r at what level . Nor can it take into account the enormous divers ity generated by gene rearrangements, RNA spli c ing and editing, and post-translational modifi cati ons of pro­teins, DNA sequences alone te ll us littl e about the

PORUBLEV A & CHITNIS: PROTEOMICS: A POWERFUL TOOL 361

physiological function of proteins . Proteome analysis provides a direct method for analyzing the complexity and diversity of proteins in a cell. Proteomics tells us what fraction of the genome is functional, and at what levels. Proteomics gives a global picture of metabolic and developmental changes in gene functions . Analy­sis of gene expression at the RNA level alone ignores translational and post-translational regulation. Re­cently, comparison of protein and transcript levels in yeast demonstrated that the correlation between mRNA and protein levels was insufficient to predict protein expression levels from quantitative mRNA data ' 2

. Thus, proteomics is needed to truly understand genome expressIOn.

How is a proteome studied? Traditional biochemistry involved protein separa­

tion, characterization and linking proteins to their corresponding genes. Proteomics is an extension of these protein mapping and protein identification tech­niques that have been used routinely for small-scale analysis . The proteins are separated by two­dimensional gel electrophoresis (20GE), estimated using image analysis and analyzed with mass spec­trometry. Once proteins are identified, a reference map of 20 display can be used for comparative analy­sis. This approach complements the genome analysis, EST sequencing and analysis of RNA using 'microar­ray techniques. The recent emergence of proteomics as a powerful tool is due to many improvements in the technology .

Like a typical biochemical purification procedure, preparation of protein samples remains a crucial start in protein separation. The quality of 2D gels is strongly dependent on purity and an extent of protein solubilization. Any contamination such as ionic com­pounds, small charged molecules, DNA, lipids, pig­ments, etc. increase conductivity and viscosity of the sample, thus interfering with protein migration in an electric field. Recently new chaotropcs and detergents have been introduced to overcome these problems '-1.

Solubilization of hydrophobic transmembrane pro­teins is still a very serious problem for proteomics".

The protein separation with 2DGE is a core tech­nology in proteomics . In the first dimension, isoelec­tric focusing is performed using immobilized pH gra­dient (IPG) strips, in which buffering and titrant groups are covalently bound to the polyacrylamide matrix '4a

. The consistent performance of gel strips avoids instability, discontinuity and variations in the

pH gradient '4b. Computer standardized pre-dried IPG

strips give run-to-run reproducibility. Thus the long awaited ideal of international rather than in-house reproducibility has become achievable ' 5. In the sec­ond dimension, proteins are separated according to their molecular mass. Such combination results in visualizing up to 10,000 proteins per a gel ' 6. An ex­ample of protein separation with 20GE is shown in Fig. I. Currently 20GE remains to be the most pow­erful technique for separating a few thousand proteins simultaneouslyl7·'8.

Another major advance in 20GE is development of computer software for comparison and quantitative analysis. The genome remains constant in an organ­ism and requires a single structural determination. Functional proteome varies and its analysis requires highly defined samples and highly reproducible ex­.perimentation. Researchers have used incorporation of radioactive isotopes for quantifying absolute amounts of proteins '9

.2o. Alternatively, chemically

tagged peptides have been used for simultaneous quantification of proteins using mass spectrometr/o. However, quantitative analysis of patterns in the stained gels remains the most widely used technique for analyzing proteomes. For analysis of complex 2D patterns, significant advances have occurred in com­puterized image analysis of 2D gels, spot detection, background subtraction, spot matching, database con-

. d . I d I' 2 1-24 structlOn, an numenca ata ana YSIS .

The most significant technological leap in pro­teomics comes from the application of mass spec­trometry (MS) as a sensitive, inexpensive and rapid tool for protein identi fication 25

. Despite the recent improvements in the sensitivity and automation of Edman protein microsequencing, thi s methodology has remained time and cost intensive to such an ex­tent as to preclude large-scale proteome analysi s26

.

Protein separation techniques yield several hundred to a few thousand resolved proteins. Hierarchical de­ployment of mass spectrometry is a promis ing solu­tion in achieving high-throughput screening. The quickest and most inexpensive technology is used first, followed by increasingly time and cost-intensive procedures .

In a typical proteomic analysis, gel spots are ex­cised and proteins in the gel are digested with prote­ases, trypsin being the most commonly used protease . Peptide mass fingerprints (PMF) are collected with a matrix-assisted laser desorption ionization - time of flight (MALO I-TO F) mass spectrometer. Fig. 2

362 IND IAN J. BIOC HEM. BIOPHYS., VOL. 37, DECEMB ER 2000

50

40

C 30 ~ .~ -... :E

20

10

7.0 6.5 6.0 5.5 5.0 4.5 4 .0

pi (pH)

Fig. I- Proteo me map for the C HAPS-solu ble proteins from maize leaves

100,

I 1

J 1 32~ .27 1492 .48

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Fig. 2-Typical peptide mass fingerpri nt ing data ubt ained by MALDI-TOF analys is of tryptic frag ment s of a protein spot. [The spot was excised, subjected to trypsin treatment and the peptides were eluted by di ffusion].

shows the typical mass spectrum obtained with MALDI-TOF MS . Many tools are ava ilable fo r pro­tei n identifi cati on and characteri zation using PMF data (see ExPaSy http://www.expasy.ch fo r a li st of tools that are ava il abl e on the web.). Accurate masses of as few as fo ur pept ides with one or more orthogo­na l data sets (e.g. pI, organi sm, express ion info rma­ti on) can be used to scan the ex isting prote in se-

quence databases to identi fy a prote in unambigu­ously27. PMF data can al so be used to predict post­translational modi fications28

. When combined w ith robotics for gel exc is ion, liquid-handli ng systems and automated data collection, one can obtain PMF on as many as 300 proteins in a da/'J.

The next step would invo lve add itiona l data such as fragmentation spectra, sequence tagging or a COI11-

PORUBLEVA & CHITNIS: PROTEOMICS : A POWERFUL TOOL 363

bination of one or more additional protease diges­tion30'33 . In general, the larger the genome, the more rigorous the requirements for identifying a protein by mass spectrometry or sequence analysis l8

. The use of peptide masses alone for identification can be com­promised by the presence of extensive post­translational modifications, an incomplete genome database, errors in the DNA sequence, incomplete EST sequences, and other issues. In cases where the peptide masses are insufficient to identify a protein, it will be necessary to obtain direct sequence informa­tion via fragmentation analysis30, While it is possible to obtain fragmentation information from MALDI mass spectrometry, thi s is not sufficiently reliable to be of routine use, An electrospray source on a tandem mass spectrometer or an ion trap is combined with HPLC or capillary electrophoresis and is used to ob­tain sequence information30'32. This process can be automated for increasing throughput of analysis" . Mass spectrometry has enabled researchers to char­acterize more than twice the number of yeast proteins in a few weeks than had previously been determined over a decade34.35 .

The elegant proteome studies in animal systems, E. coli and yeast have provided extensive information about changes in proteomes in response to di sease conditions, stress conditions, or drugs. Although proteomes of many bac teri a, yeast and animal sys­tems have been investigated in detail , plants have been studied with proteomic techniques only recently , Similarly, proteome analyses of the cyanobacterium SYllechocystis sp. PCC 6803 have commenced only in the last few years36'38. One difficulty in analysis of plant proteomes is that separation of plant proteins with 2DGE is complicated by relatively low content of proteins in ti ssues and presence of phenolic com­pounds39, Table I li sts some recent 2DGE studies de­scribing pl ant proteomes. In most studies so far , the plant proteomes were identified by amino-acid micro­sequencing. Consequently, very few proteins have been identified in the plant proteomes. Additionally, since most plant genomes have not been sequenced completely, a significant part of the analyzed proteins could not be identified using current databases (Table I ).

The technological challenges in the future research Proteomi cs is a sc ience in its infancy. The success

of this endeavor will be determined by the extent to which thi s technology-dri ven sc ience can overcome

its shortcomings. Here we di scuss the challenges for proteomics , Note that mRNA profiling with microar­rays also has simjlar weaknesses with normalized rep­resentation, variation, proper controls and reproduci­bility ,

(i), Variation: The genome remains constant in an organism and requires a single structural determina­tion. Functional proteome varies and its analysis re­quires highly defined samples and hi ghly reproduci­ble experimentation. Proteome analysis must depend upon rigorous experimental design and the need to examine several physiological states both ill vitro and 111 VIVO.

(ii) Sensitivity: A weakness of the current proteome technology is the poor detection threshold of 2DGE. Protein detection lacks the advantage of amplification that has revolutionized nucleic acid analysis, From current estimates, silver staining of a 2D gel can be used to detect proteins that are 1000 copies per an eukaryotic cell 15.29 , Thus, only 40%-70% of all ge­nome activity within a given system can be followed simultaneously and quantitativel/o.41. However, there are several ways to increase sensitivity. If antibodies are available, immunodetection with enhanced chemiluminescence can be used to increase sensiti v­ity by 10-100 fold over silver staining, Such level of sensitivity enhancement (as little as 125 picograms of single proteins) can also be reached with radioacti ve iodine and fluorescent dyes29.42, At present these dyes of various colours allow to analyze up to three differ-

I h · 4? 41 S If ' . ent samp es at t e time -, . , amp e ractlOnatlon based upon different cellular localization of the pro­teins, their relative solubilities, charges , sizes, affinity to ligands and use of narrow pH ranges in the first dimension increase detection sensitivity by up to 100 fold44.45, After analyzing multiple subproteomes, re­sults can be pooled to generate information about the complete proteome, Even when all proteins cannot be detected and identified in proteomic analysis, by placing points of reference on 2DGE maps, our un­derstanding of biological processes is destined to be­come more holi stic ,

(iii) Speed: Despite the recent improvements in the sensitivity and automation of Ed man protein microse­quencing, thi s methodology has remained time and cost intensive to such an ex tent as to prec lude large­scale proteome analysis26

. For organi sms with com­pletely sequenced genomes as well as for those lack­ing significant DNA sequence information, mass spectrometry has an essential ro le to play in achieving

Table I-Avai lable plant proteome maps

Plant species Subproteome Method of Number Number Number Proteins with Method of

2-D electro- of protein of spots of protein no assigned identification**

phoresis* resolved analysed identified functions

Barley (Hordeum vulgare L.) Seeds, endosperm CAJU/N no report 26 12 AAS

Spinach (Spinacea oleracea Thylakoid membrane CAJU/N about 100 spots 15 II 0 IB L.) Arabidopsis thailana Total proteins from five ti ssues IPG/Urr 4763 spots 125 48 27 AAS Rice (Oryza sativa L.) Total proteins from nine tissues IPG/Urr 4892 spots 144 36 24 AAS

Maize (Zea mays L.) Total coleoptile proteins *** IPG/u/CHAPS no report 56 12 2 AAS

Maize (Zea mays L. ) Total leaf proteins*** IPG/U/C HAPS no report 18 13 I AAS

Tobacco (Nicotiana tobacum Plasma membrane IPG/U/CHAPS, about 600 spots 16 0 6 AAS CAJU/N

Pine (Pinus pinaster AiL) Total needle proteins CAJUn- about 900 spots 28 19 3 AAS

Pine (Pinus pin aster Ait.) Total xylem proteins CAJUrr about 600 spots 35 16 3 AAS

Rice (OT)'za sativa L.) Total proteins from green and CAJU/N about 300 spots 85 30 16 AAS etiolated shoots

Arabidopsis thaliana Plasma membrane ***: IPG/U/CHAPS ,SB AAS IPG/U,TU/C8¢,

total proteins about 700 spots 104 52 3 1

specific in plasma membrane about 350 spots 22 8 12

fraction Pea (Pisul1l smiVUlI1 L. ) Peripheral thyl akoid membrane IPG/U,Tu/CHAPS , 200-230 proteins 400 51 10 MS, AAS

and soluble lumen proteins T,SB IPG/u/CHAPS 200-230 proteins

* Abbrevi ation s: lPG, immobili zed pH gradient ; CA, carrier ampholytes IEF; U, urea; N, NP-4 ; T, Triton X-I 00; TU , thi ourea; SB, sulphobetaine S8 3-10. ** AAS, amino-acid sequencing; IB, immunoblolling; MS, mass spectrometry.

*** 2-D Database were created

Reference

[71]

[72]

[73, 74] [74, 75]

[76]

[76]

[77]

[78]

[78]

[79]

[51 , 80]

[81]

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Z 0 ;; z !-t:O

0 () :r: m 3: t:O

0 "0 :r: -< en

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0 m () m 3: t:O m ~ N 0 0 0

PORUBLEVA & CHITNIS: PROTEOMICS : A POWERFUL TOOL 365

high-throughput screening. Sensitive high throughput screening of proteins can employ mass spectrometry in a hierarchical manner. Initial protein characteriza­tion can proceed rapidly, cost-effectively and in a manner that lends itself to automation and robotics . Accurate mass of four peptides with one or more or­thogonal data sets (e.g. pI, organism, expression in­formation) can be used to scan the existing prote in sequence databases to identify a protein unambigu­ousl/6. The next step could involve additional data such as fragmentation spectra, sequence tagging or a combination of one or more additional protease di­gestions. Such strategies have enabled researchers to characterize more than twice the number of yeast proteins in a few weeks than had previously been de­termined over a decade4

7.48. High throughput screen­ing has made large-scale proteome ana lysis a reality.

(iv) Membrane proteins: Membrane proteins con­stitute a major component of a proteome. Approxi­mately 30% of the bacterial genes code for integral membrane proteins49

. Membrane prote ins drive and mediate many essentia l cellular processes such as signal transduction, cell adhesion, hormone percep­tion and transport of proteins, metabolites, nutrients and ions across cell membranes. Unfortunately the integral membrane proteins are difficult to study us­ing current proteomic technology. Only 66 integral membrane proteins from bacteria, yeast, animals and pl ants have been identified in contrast with thousands soluble and peripheral membrane prote ins that have been identified on 2-D gels5o

.51

. Recently a consor­tium of European researchers has undertaken me­ticulous ana lys is of the plant pl asma membrane pro­teins (PPMdb) (ref. 51) . It contains comprehensive two-dimensional pol yacrylamide gel e lectrophoresis map, partial amino ac id sequences and expression data.

Applications in the Functional Genomics Genomi cs is moving now from a focus on genome

structure and compari sons of nuc leotide sequences to f f · 52 F . I . a ocus on gene unctIOn . unctlOna genomlcs en-

compasses the development and applicati on of global (genome-wide or system-wide) experimental ap­proaches to assess gene function by making use of the information and reagents provided by structural ge­nomics5

' . Proteomics provides a powerfu l problem­solving tool in functiona l genomics.

Proteome analysis can aid in genomic annotation The ability of proteomics to confirm the existence

of gene-products predicted from DNA sequence is a major contribution to genomic science. Proteomic analysis of very small prote ins « 5 kDa) will enable better annotation of genome sequences. Small open reading frames (ORFs) are generally not taken into account during genomic annotations. Proteomics will allow us to identify which of these small ORFs are functional genes. When DNA sequences are ava il­able, identification of proteins in a proteomic project could link a protein to a gene with known functi on or could show that a protein is a product of an unidenti­fied open reading frame. In the lat ter case, proteomics demonstrates that a putative ORF is indeed a func­tional gene. For example, of 129 abundant proteins identified in a study on thylakoids of the cyanobacte­rium Synechocystis sp. PCC 6803, 37% proteins were derived from unidentified open reading frames'6.

Regulation of genes can be understood by compara­tive proteomics

Proteomics tell s us what fraction of the genome is functional, and at what levels during development and under stress conditions'. Such analyses must not be limited to changes in the RNA level s alone. Fre­quently, plant gene expression is regul ated at transla­tional and post-translationa l levels. It is imperati ve to examine changes in the proteome if we want to obtain a true understanding of how a phenotype is altered by changes in the genome expression. Cluster analysi s of the expression patterns can reveal roles of the novel proteins in cellular physiology and metaboli sm. Cel­lul ar prote ins can be labe led in vivo and then used for protein analysis. Thus, proteome analysis can be used to understand dynamics of genome expression. Pro­teomics also provides a way to characterize mutan ts rapidly. The altered express ion pattern reveals poss i­ble interconnections in gene expression cascades and allows analysis of global effects due to mutati on in a specific gene. Subcellular fractionation prior to pro­teo me analysis demonstrates intracellular location of a gene-product and indicates possi ble function. Iden­tification of subcellul ar locat ion of a protein is a unique application of proteomics. Genomic sequences or mRNA profiling cannot demonstrate intrace llular localization . Thus, proteome ana lys is has several im­plications in functiona l genomics.

The resolving power of 2-D e lec trophores is has been used to study genetic variab ility in pl ants and to

366 INDIAN J. BIOCHEM. BIOPHYS., VOL. 37, DECEMBER 2000

Table 2-The changes in the protein composition in response on environmental stresses studied with 2-D electrophoresis

Stress Plant, organ Number of proteins changed Method of Reference

Total amount

Phosphate depri vation Tomato roots

Chilling acclimat ion Soybean

Salt ex<.:ess Barley root 2*

Drought Maize 78 (38)**

Jasmonic ac id Ri <.:e

UV Irrad iation Ri ce

Copper chloride Rice

Iron deficiency Maize root plasmalemma Ozone Arabidopsis leaves

Heat shock Maize

Annox ia Maize root

* The number of proteins increased most strikingly. ** The number of protei ns with different expression in two genotypes. *** The changes in the mutant against the wild type. **** Only 45 kDa heat shock protei n were studied

analyze mutant phenotypes54. For example, analysis

of the 2-D gels of total proteins extracted from devel­opmental mutants of Arabidopsis thai/ana (L.) Heyhn. and from wild-type plants grown in the pres­ence of various hormones allowed to find mutants overaccumulating cytokinins55

. The possibility of 2DGE to visualize hundreds of proteins at the time have been successfully applied for studying the pro­tein changes induced by diseases56

.57

. Comparative proteomics has also been used for identifying differ­entially expressed proteins under abiotic stress con­ditions (Table 2).

Epilogue The current microarray and proteome analyses fo­

cus on the absolute quantity of a gene-product (RNA and/or protein). This emphasis will shift to more rele­vant parameters, such as, molecular half-l ife; synthe­sis rate; the influence of the environment, cell cycle, stress and disease on gene-products; and the collec­tive roles of multigenic and epigenetic phenomena. Cellular proteins can be labeled in vivo and then used for protein analysis . Thus, proteome analysis can be used to understand dynamics of genome expression. Another emphasis needs to be on protein function and interactions. Several new developments hold promise in this arena. The traditional biochemical techniques for studying protein-protein interactions such as co-

Increase Decrease Unique identi ti<.:ation

2 NI [82]

2 AAS [83]

[84J

II 8 AAS [851

2 II AAS [86]

4 AAS [86]

5 AAS [86]

4*** NI [87] 2 NI [88)

3**** [89]

6 35 MS [901

immunoprecipitation, cross-linking, and cofractiona­tion are lab.or- and time-extensive. New approaches have been developed recently to make these in vesti­gations more amenable to a high throughput analysis. To define both indirect and direct protein interac­tions, protein complexes can be purified with a novel tandem affinity purification (TAP) tag from a re la­tively small number of cells without prior knowledge of complex composition, activity or fu nction58

. The component of isolated complex then can be identified with mass spectrometry. Biosensors that are based on surface plasmon-resonance biosensors are ideal for characterization and identification of protein-protein interactions in purified samples, as well as in com­plex mixtures59

-6 t

. Combination of SPR-biomolecular interaction analysis and MALDI-TOF provides a powerful approach in proteome analysis . Detection limits for both SPR-BIA and MALDI-TOF are at low­femtomole to subfemtomole leve l. Applying these tools in proteomics cou ld lead to ligand and protein­complex identification and to estimation of the ki­netic parameters of these interactions.

Since the pioneering work of O'Farrell some twenty five years ag062 protein analysis by 2DGE has come a long way. In the post-genomic era, several key improvements are driving proteomics: reproducible 2D gel technology, staining and scanning technology, mass spectrometry for identification, and bioinfor-

PORUBLEVA & CHITNIS : PROTEOMICS: A POWERFUL TOOL 367

matics for database construction and searching. In the future , many new developments in the technology and major investments from genomics industry are bound to propel proteomics to a sca le that will be compara­ble to the high throughput genomics projects63

. Mi­crofabrication at different steps will aid protein di s­play and analysis64

.66

. Some methods bypass the 20 electrophoretic separation. For example, a recently proposed method identifies intact proteins from ge­nomic databases using a combination of accurate molecular mass and partial amino acid content in a sample containing isotopically labeled proteins67

.

Similarly, chemical labeling in combination with mass spectrometry can be used to perform quantita­tive comparison68

. Inducti vely coupled plasma-mass spectrometry with a magnetic sector mass spec­trometer holds a promise for a hi gh throughput analy­sis of phosphorylated proteins69

.7o

. Thus, many inno­vative approaches are being examined to improve the proteomic technology. Genomic sequences when complemented with the information derived from mi­croarray hybridization assays and proteome analysis may herald a new era in holistic plant biology.

Acknowledgement The authors ' research on proteomics was supported

in part by grants from NSF-NATO and Iowa Corn Promotion Board. Journal Paper No. J-XXXXX of the Iowa Agriculture and Home Economics Experi­ment Station, Ames, Iowa, Project No. 3416 and sup­ported in part by Hatch Act and State of Iowa fund s.

References I Abelson PH (1998) Science 279, 2019 2 Chitnis P R, Sun J & Chitni s V P (1998) in: Crop IlI1lirolle·

ment throllgh Gene Transfer. pp In press ( ath P, ed) Klu­wer Academic, Dodrecht

3 Lander E S (1996) Science 274, 536·9 4 Heiter P & Boguski M (1997) Science 278, 601-2 5 Du boule D ( 1997) Science 278, 555 6 Gcisow M J (1998) Natllre Biotechnology 16, 206-208 7 James P ( 1997) Q Rev Riophys 30, 279-3:' I 8 Geisow M J (1998) Nat Biotechnol 16, 206 9 Persidi s A ( 1998) Nat Biotechnol 16, 393·4 10 Wasinger V C, Cordwell S J, Cerpa-Polj ak A, Yan J X,

Gooley A A, Wilkins M R, Duncan M W, Harris R, Will iams K L & Humphery-Smi th I (1995) Electrophoresis 16 . 1090·4

II Fischer E H ( 1997) in : Proteome Research: NelV Frontiers in Fun ctional Genolllics (Wilkins M R, Williams K L, Appel R D & Hoehstrasser D F eds) Springer-Verlag, Berlin

12 Gygi S P, Rochon Y, Franza B R & Acbersold R (1999) Mol Cell Bioi 19. 1720-30

13 Chevallet M, Santoni V, Poinas A, Rouqui e D, Fuchs A, Kieffer S, Rossignol M, Lunardi J, Garin J & Rabilloud T ( 1998) Electro/JllO resis 19, 190 1·9

14 (a) Sanchez J C, Rouge V, Pisteur M, Ravicr F, Tonell a L, Moosmayer M, Wilkins M R & Hochstrasser D F (1997) Electrophoresis Ill , 324-7

15 Herbert B R, Sanchez J·C & Bini L ( 1997) in: Proteollle Research: Nell' Frontiers in FIII/ ctional Genolliics pp 13-34 (Wilkins M R, Williams K L, Appel R D & Hochstrasser D F eds) Springer· Verlag, Berlin

16 Klose J & Kobalz U ( 1995) Electrophoresis 16 1034·59 17 Wilkins M R & Gooley A A ( 1997) in : Proteolll e Research:

New Frol1tiers in Fllnctional Genolllics pp 35-64 (Wilkins M R, Willi ams K L, Appel R D & Hochstrasser D F, cds) Springer-Verlag, Berlin

18 Aebersold R, Figeys D, Gygi S. Corth als G. Haynes P, Ri st B, Sherman J, Zhang Y & Goodlett D (1998) J Protein Chem 17,533-5

19 Gygi S P & Aebersold R (1999) Methods Mol Bioi 112, 417· 21

20 Gygi S P, Ri st B, Gerber S A, Turecek F, Gelb M H & Ae­bersold R ( 1999) Nat Bioteelll/ol 17 ,994-999

21 Appel R D (1997) in: Proteome Research: NelV Frontiers in Flln ctiO/wl Genomics pp 149- 176 (Wilkins M R, Willi ams K L, Appel R D and Hochstrasser D F, cds) Springer-Verlag, Berlin

22 Appel R D, Palagi P M, Walther D, Vargas J R, Sanchez J C, Ravier F, Pasqu ali C & Hochstrasser D F ( 1997) Electropho · resis 18, 2724-34

23 Appel R D, Vargas J R, Palagi P M, Walther D &. Hochstrasser D F (1997) Electrophoresis 18,2735-48

24 Hoogland C, Bauj ard V, Sanchez J C, Hochstrasser D F & Appel R D (1997) Electrophoresis 18 , 2755-8

25 Yates J R 3rd (2000) Trends Genet 16, 5-8 26 Gooley A A, Ou K, Ru ssell J, Wilkins M R, Sanchez J C,

Hochstrasser D F & Williams K L (1997) Electrophoresis 18, 1068-72

27 Wilkins M R, Willi ams K L, Appel R D & Hochstrasser D F (1997) pp 243 Springer Verl ag. Berli n

28 Wilkins M R, Gasteiger E, Gooley A A, Herbert B R, Molloy M P, Binz P A, Ou K, Sanchez J C, Bairoch A, Willi ams K L & Hochstrasser D F (1999), J Mol Bioi 289, 645·57

29 Harry J L. Wilkins M R, Herbert B R, Packer N H. Gooley A A & Willi ams K L (2000) ElectrOIJhoresis 2 1, 107 1·81

30 Figeys D. Gygi S p. Zhang Y, WallS J, Gu M & Aebersold R ( 1998) Electrophoresis 19, 18 1 1-8

3 1 Haynes P A, Fripp ' & Aebersold R (1998) Electrophoresis 19, 939-45

32 Figeys D & Aeberso ld R ( 1998) Electrophoresis 19.885·92 33 Ducret A, Van Oostveen I, Eng J K, Yates J R 3rd & Aeber­

sold R (1998) Protein Sci 7, 706-19 34 Costanzo M C, Hogan J D, Cusick M E, Davis B P. Fancher

A M, Hodges P E, Kondu P. Lengieza C, Lew-Smith J E, Lingner C, Roberg-Perez K J, Tillberg M, Brooks J E & Gar· rel s J I (2000) Nlleleic Acids Res 28, 73-6

35 Hodges P E, McKee A H, Davis B P. Payne W E & Garrel s J I ( 1999) Nllcleic Acids Res 27, 69-73

36 Wang Y, Sun J & Chitnis P (2000) Electrophoresis 21, 1746-1754

37 Sazuka T, Yamaguchi M & Ohara 0 (1999) Electrophoresis 20,2160-71

38 Sazuka T & Ohara 0 ( 1997) Electropho resis 18. 1252-8 39 Tsugita A & Kamu M ( 1999) Methods Mol BioI 11 2.95-7

368 INDI AN 1. BIOCHEM. BIOPHYS., VOL. 37, DECEMBER 2000

40 Humphery-Smi th I, Cord well S J & Blackstock W P ( 1997) Electrophoresis 18, 1217-42

4 1 Humphery-Smith I & Blackstock W (1997) J Protein Chelll 16,537-44

42 Patlon W F (2000) Electrophoresis 21 , 1123-44

43 Patl on W F (2000) Biotechniques 28 , 944-8, 950-7

44 Cordwell S J, Nouwens A S, Verrills N M, Basseal 0 J & Walsh B J (2000) Electrophoresis 21, 1094-1 03

45 Molloy M P, Herbert B R, Walsh B J , Tyler M I, Traini M, Sanchez J C. Hochstrasser 0 F, Willi ams K L & Gooley A A (1998) Electrophoresis 19,837-44

46 Wilkins M R & Wi ll iams K L(1997)JTheOl' BioI 186 , 7- 15

47 Wi nzeler E A & Davis R W (1997) Cllrr Opin Cenet Del! 7 , 77 1-6

48 Fey S J, Nawrocki A, Larsen M R, Gorg A, RoepstorfT P, Skews G N, Williams R & Larsen PM (1997) Electrophure­sis 18, 136 1-72

49 Wall in E & von Heijne G (1998) Protein Sci 7, 1029- 1038

50 Santoni V, Molloy M & Rabilloud T (2000) Electrophoresis 21. 1054-70

51 Santoni V, Ooumas P. Rouquie 0 , Mansion M, Rabi lloud T & Rossignol M ( 1999) Biochilllie l:! I , 655-6 1

52 Oliver S G ( 1996) Natllre 379, 597-600

53 Hi eter P & Boguski M ( 1997) Science 278, 601 -2

54 Oamerval C & Le Guilloux M (1998) Mol Ccn Cenet 257, 354-6 1

55 Santon i V, Oelarue M, Caboche M & Bellini C ( 1997) Planta 202 , 62-9

56 Takahash i H, Chen Z, Ou H, Liu Y & Kl ess ig 0 F (1997) Plallt J 11 ,993-1005

57 Kachroo P, Lee K H, Schwerdel C, 13::!iley J E & Challoo B B (1997) Electrophoresis 18, 163-9

58 Rigaut G, Shevchenko A. Rut z B, Wilm M, M,lI1 n M & Se­raph in B (1999) Nat Biotechllol 17. 1030- 1032

59 Szabo A, Sto lz L & Granzow R ( 1995) Cllrr Opin Stl"llct Bioi 5, 699-705

60 Rieh R L & Myszka 0 G (2000) Cllrr Opin Biotecllllol II , 54-61

6 1 Nelson R W, Nedelkov 0 & Tubbs K A (2000) Electrol'/IO-res is 2 1, I 1.55-63

62 O'Farrell P ( 1975) J Bio/ Chelll 250, 4007-4021

63 Service R F (2000) Science 287, 2 136-8

64 Figeys 0 & Aebersold R ( 1999) J Biolllech Ellg 12 1, 7-1 2

65 Figeys 0 & Aebersold R ( 1998) Anal Chelll 70, 3721-7

66 Figeys 0 , Gygi S P, McKinnon G & Aebersold R ( 1998) Anal Chelll 70, 3728-34

67 Veenst ra T 0, Marti novic S, Anderson G A, Pasa-Tolie L & Smith R 0 (2000) J A III Soc Mass Spectrolll II , 78-82

68 Goodlett 0 R, Bruce .J E, Anderson G A, Rist 13 , Pasa-Tolic L, Fiehn 0, Smith R 0 & Aebersold R (2000) Anal Chelll 72 111 2-8

69 Wang J, Houk R S, Dressen 0 & Wiederin 0 R ( 1999) J Bioi Inorg Chelll 4, 546-553

70 Bibak A, Stump S, Haahr V, Gundersen P & Gundersen V ( 1999) J Agric Food Chelll 47, 2678-84

7 1 Flengsrud R ( 1993) Electrophoresis 14, 1060-6 72 Yu S-G, Steffansson H, Romanowska E & Albertsson P-A

( 1994) Photosynthesis Res 4 1, 475-486 73 Kamo M, Kawakami T, Miyatake & TSlIgita A ( 1995)

Electrophoresis 16, 423-30 74 Tsugita A, Kamo M, Kawakami T & Ohki Y ( 1996) Electro­

phoresis 17, 855-65 75 Tsugita A, Kawakami T, Uchiyama Y, Kamo M, Miyatake N

& NoZli Y (1994) Electrophoresis 15,708-20 76 Touzet P, Ri ccardi F, Morin C. Oamerval C, Huet J-C, Per­

noll et J-C, Zivy M & de Vi enne 0 ( 1996) Theor Appl Cell et 93,997- 1005

77 Rouquie 0 , Peltier J 13, Marquis-Mansio n M, Tournaire C. Oou mas P & Rossigno l M (1997) Electrophoresis 18, 654-60

78 Costa P, Pionneau C, Bauw G, Oubos C, Bah rman n Kremer A, Frigerio J M & Plomion C (1999) Electropho resis 20, 1098-108

79 Komatsu S, Muhammad A & Rakwal R ( 1999) Electropho­resis 20, 630-6

80 Santoni V, Rouqui e 0, Ooumas P, Mansion M, Boutry M, Oegand H, Dupree T, Packman L. Sherrier J, Prime T, Bauw G, Posada E, Rouze P, Oehais p, Sahnoun I, Barlicr I & Ros­signol M ( 1998) Plallt.l 16,633-41

8 1 Peltier J B, Friso G, Kalu mc 0 E, RocpstorlT P, Ni lsson F, Adamska I & van Wijk K J (2000) Plant Cell 12, 319-41

82 Hawkesford M & Belcher A ( 1991) Plallla 1l:!5, 323-329 83 Cabane M, Cal vet P, Vincens P & Boudet A M (1993)

Planta 190, 346-53 84 Hu rkman W, Tanaka C & DuPont F ( 1988) Plant Ph\"Siol 88.

1263-1 273 85 Ri ccardi F, Gazeau P, de Vienne 0 & Zivy M (1998) Plant

PII )"Siol 117, 1253-63 86 Rakwal R, Agrawal G K & Yonek unl M ( 1999) Dectrop/IO­

resis 20, 3472-8 87 Wiren N V, Peltier J-B , Rouquie O. Rossignol M & Briat J-F

( 1997) Plant Physiol Biochelll 35 , 945-950 88 Tokarska-Schlatlner M, Fink A, Castillo F-J. Crespi P.

Crevecoeur M, Greppin H & P T ( 1997) Plant Cell En viroll 20, 1205- 121 1

89 Ri stic Z, Yang G & Bhadula S ( 1999) J Plant Physiol 15-l 264-268

90 Chang W W, Huang L, Shen M, Webster C, Burlingame A L & Roberts J K (2000) Plant Physiol 122, 295-3 18