Using proteomics to study sexual reproduction in angiosperms

REVIEW

Using proteomics to study sexual reproduction in angiosperms

Jan A. Miernyk • Anna Pretova • Adela Olmedilla •

Katarına Klubicova • Bohus Obert •

Martin Hajduch

Received: 14 April 2010 / Accepted: 21 August 2010 / Published online: 10 September 2010

� Springer-Verlag 2010

Abstract While a relative latecomer to the postgenomics

era of functional biology, the application of mass spec-

trometry-based proteomic analysis has increased exponen-

tially over the past 10 years. Some of this increase is the

result of transition of chemists, physicists, and mathemati-

cians to the study of biology, and some is due to improved

methods, increased instrument sensitivity, and better tech-

niques of bioinformatics-based data analysis. Proteomic

Biological processes are typically studied in isolation, and

seldom are efforts made to coordinate results obtained using

structural, biochemical, and molecular-genetic strategies.

Mass spectrometry-based proteomic analysis can serve as a

platform to bridge these disparate results and to additionally

incorporate both temporal and anatomical considerations.

Recently, proteomic analyses have transcended their initial

purely descriptive applications and are being employed

extensively in studies of posttranslational protein modifi-

cations, protein interactions, and control of metabolic net-

works. Herein, we provide a brief introduction to sample

preparation, comparison of gel-based versus gel-free

methods, and explanation of data analysis emphasizing

plant reproductive applications. We critically review the

results from the relatively small number of extant proteo-

mics-based analyses of angiosperm reproduction, from

flowers to seedlings, and speculate on the utility of this

strategy for future developments and directions.

Keywords Electrophoresis �Mass spectrometry � Pollen �Proteins � Proteomics � Seeds

Abbreviations

CM Central metabolism

CS Cell structure

1-DE One-dimensional electrophoresis

2-DE Two-dimensional electrophoresis

DIGE Difference in-gel electrophoresis

GelC- A 1-DE variant where after electrophoresis

the gel lane is cut into multiple slices

HS Hormones and signaling

LC- Liquid chromatography

MALDI- Matrix-assisted laser-desorption/ionization

MS Mass spectrometry

MS/MS Tandem MS

MudPIT Multi-dimensional protein identification

technology

MT Membrane transport

NA Nucleic acid metabolism

PF Protein folding

Communicated by Scott Russell.

J. A. Miernyk � A. Pretova � K. Klubicova � B. Obert �M. Hajduch (&)

Institute of Plant Genetics and Biotechnology,

Slovak Academy of Sciences, Akademicka 2,

P. O. Box 39A, 950 07 Nitra, Slovak Republic

e-mail: [email protected]

J. A. Miernyk

USDA, Agricultural Research Service,

Plant Genetics Research Unit, Department of Biochemistry,

Interdisciplinary Plant Group, University of Missouri,

Columbia, MO 65211, USA

Present Address:A. Pretova

Department of Botany and Genetics,

Faculty of Natural Sciences, The University of Constantine

the Philosopher, Trieda A. Hlinku, Nitra, Slovak Republic

A. Olmedilla

Department of Plant Biochemistry, Cell and Molecular Biology,

Estacion Experimental de Zaidın (C.S.I.C.), EEZ, Granada,

Spain

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Sex Plant Reprod (2011) 24:9–22

DOI 10.1007/s00497-010-0149-5

PMF Peptide mass fingerprint

PS Protein synthesis

PT Protein targeting

PTM Posttranslational modifications

PUF Proteins of unknown function

SDS–PAGE Sodium dodecyl-sulfate polyacrylamide gel

electrophoresis

SR Stress response

SSP Seed storage protein

TOF Time of flight

TOF/TOF In tandem MS, the first mass analyzer

determines the TOF for the precursor

(parent) ions then selected ions are diverted

to a collision cell fragmented, and the

second TOF mass analyzer determines

masses of the fragmented ions

Introduction

The angiosperm reproductive cycle begins with develop-

ment of the diploid flower, which governs breeding sys-

tems and the development of the reduced haploid sexual

stages. Pollen grains germinate on the stigma, and pollen

tubes grow down the style and into the ovary, penetrating

the ovule and triggering fertilization (Borges et al. 2008).

One sperm fuses with the egg to create a diploid zygote,

while the other sperm cell fuses with the two polar nuclei to

produce the endosperm (Dumas and Rogowsky 2008). The

main function of the typically triploid endosperm is to

provide nutrients to the developing, and later germinating,

embryo (Sabelli and Larkins 2009). The typically diploid

embryo develops inside the embryo sac, with integuments

of the ovule forming a protective seed coat, and the mature

ovary forming a protective fruit around the seed. Eventu-

ally, the seed is shed, and the embryo temporarily suspends

development and enters dormancy, synchronizing its later

development with favorable conditions. Seeds subse-

quently germinate with the embryo growing into a mature

diploid sporophyte that produces flowers to complete one

cycle of the alternation of generations. In addition to

genomic (Le et al. 2007) and transcriptomic (Borges et al.

2008) research strategies, in recent years there has been an

increasing application of proteomic approaches to study

plant reproduction (Hochholdinger et al. 2006).

The term ‘‘proteome’’, a chimera of ‘‘protein’’ and

‘‘genome’’, was first used in 1997 by Wilkins et al. The

proteome has been defined as the entire complement of

proteins, including posttranslational modifications (PTM),

found in a cell, tissue, or organ. The term proteomics is

typically used to describe the coupling of high-resolution

mass spectrometry (MS) with search-and-match algorithms

to identify a protein based upon accurate peptide mass

(peptide mass fingerprinting, PMF) or peptide mass plus

fragmentation (MS/MS) information (Ahn et al. 2007).

Analyses where target proteins are digested prior to MS

analysis are referred to as ‘‘bottom-up proteomics’’ (Gundry

et al. 2009). Proteins can be identified directly from SDS gels

by excising the stained band and performing in-gel digestion,

typically with trypsin (Shevchenko et al. 1996). If the sample

contains relatively few proteins, they can be separated by

SDS–PAGE. However, analysis of samples containing a

relatively large number of proteins requires SDS–PAGE

coupled with liquid chromatography plus tandem MS

(LC–MS/MS). If the samples are very complex (containing

hundreds of proteins), then a 2-dimensional electrophoretic

(2-DE) separation, especially when using immobilized pH

gradient strips, in conjunction with LC–MS/MS, is the cur-

rent state-of-the-art for gel-based protein identification

strategies (Fig. 1) (Friedman et al. 2009).

For proteomic analysis, protein isolation (Sheoran et al.

2009a) is a critical prelude to generation of consistent, high-

quality 2-DE separations. Subsequently, proteins can be

detected by staining with one of the variants of the classical

Coomassie Brilliant Blue G-250 (c.f., Pink et al. 2010).

Alternatively, the more-sensitive fluorescent dyes (Gallagher

and Chakavarti 2008) can be used either individually or

multiplexed in methods such as difference in-gel electropho-

resis (DIGE, Minden et al. 2009) (Fig. 2). While fluorescent

dyes are excellent for quantifying proteins separated by 2-DE,

they are often ‘‘too sensitive’’ for down-stream protein iden-

tification, and it is not unusual to have to over-stain gels

Fig. 1 Proteomic analysis strategy. After isolation, proteins can be

analyzed using either a ‘‘gel-based’’ or ‘‘gel-free’’ approach. In the

gel-based strategy, proteins are separated by either 1- or 2-DE, bands/

spots are excised from the gel and digested with trypsin. The resultant

peptides are analyzed by MS and the data were used for protein

identification. In the gel-free approach, the isolated proteins are

digested in solution with trypsin. In this approach, the resultant

peptides are separated by LC and analyzed by MS. In either case, the

acquired MS data are used to search databases using one or more

bioinformatics algorithms to identify the parent proteins

10 Sex Plant Reprod (2011) 24:9–22

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previously stained with a fluorescent dye with Coomassie

Blue prior to excising spots for proteomic analysis. If a 1-DE

strategy is employed, visible protein bands are typically

excised and then digested, and the resultant peptides analyzed.

In a variant of this method (GelC-MS; Rezaul et al. 2005),

after protein separation the entire gel lane is fragmented (often

into 20 pieces) each of which is subsequently analyzed.

Non-gel-based methods of analysis are increasingly

being used in proteomic studies. In multi-dimensional

protein identification technology (MudPIT), total protein

fractions are digested in solution and then separated by 2-D

LC. The LC system can be interfaced directly with the MS

ion source, decreasing sample loss and increasing sensi-

tivity (Yates et al. 2009). To date, there are a limited

number of reports where a MudPIT strategy has been used

for study of the flowering plant reproductive proteome

(Agrawal et al. 2008; Feng et al. 2009a), but it is likely that

this number will increase in the future.

A single LC–MS/MS run will acquire thousands of

spectra, which must then be interpreted. There are two

classes of peptide-identification algorithms: database sear-

ches and de novo searches. In the former, a database con-

sisting of all peptide sequences assumed to be present in

the sample is searched, while the latter can infer peptide

sequences without a prior genomic knowledge base. In the

absence of either an extensive EST database (Parkinson

and Blaxter 2009) or whole genome sequence information,

a de novo search strategy should be used. There are many

peptide-identification algorithms available in both the public

and private sectors, including X!Tandem (http://www.

thegpm.org/TANDEM/index.html) and OMSSA (http://

pubchem.ncbi.nlm.nih.gov/omssa/browser.htm), and SE-

QUEST (Yates et al. 1995) and Mascot (Perkins et al.

1999), respectively. Most instrument vendors also have

proprietary analysis algorithms. Information about many of

the non-proprietary programs can be found at http://www.

expasy.ch/. Herein, we present an overview of the results

obtained from studies of plant reproduction that have

employed a proteomics-based research strategy.

Results from organ/tissue-based studies

Flowers

By far the most comprehensive study to date is the

description of the A. thaliana floral proteome by Feng et al.

(2009a). Using a combination of 2-DE MALDI TOF–TOF

plus the gel-free MudPIT methods for their analysis, they

identified 2,446 proteins. The floral proteins were clustered

by a minor modification of the method of Bevan et al.

(1998). The clusters used are as follows: central metabo-

lism (CM), cell structure (CS), the stress response (SR),

nucleic acid metabolism (NA), protein synthesis (PS),

protein folding (PF), protein targeting (PT), hormones and

signaling (HS), membrane transport (MT), and the ubiq-

uitous proteins of unknown function (PUF). The distribu-

tion of the A. thaliana proteins among these categories is as

follows: CM, 38%; CS, 8; SR, 9, NA, 2; PS, 2; PF, 11; PT

8; HS, 8; MT, 2; and PUF, 11. The authors additionally

detected multiple different protein posttranslational modi-

fications including acylation, acetylation, and mono- and

tri-methylation. Unfortunately, in no case was the extent of

these modifications quantified to see whether/how they

changed during floral development. Among the proteins of

central metabolism, the A. thaliana floral proteome is

enriched with enzymes involved in C1 and secondary

metabolism, as might be expected of a tissue active in

pigment biosynthesis (Grotewold 2006).

The F-box protein COI1 is required for plant defense

and male fertility in jasmonic acid signal pathway. To

investigate the regulatory role of COI1 in male fertility,

Chua et al. (2010) compared the proteomic profiles of

A. thaliana WT flowers with coi1-1 mutant male-sterile

flowers. They used 2-DE coupled with MALDI-TOF MS

for protein identification. Nineteen proteins were less

abundant in WT versus coi1-1-mutant flowers, while four

were of increased abundance. All proteins that were more

abundant in the mutant flowers are in either the CM or SR

categories; three of the more abundant proteins were also in

Fig. 2 The use of 2-D Difference In Gel Electrophoresis (Minden

et al. 2009) to study protein dynamics in soybean (Glycine max (L.)

Merr. cv Jack) seeds. Total soluble proteins were isolated from seeds

harvested at Stage 3 and Stage 4 of development. The S3 proteins

were labeled with the fluorescent dye Cy3 and the S4 proteins with

Cy5. The samples were then combined and separated by 2-DE. When

the gel was imaged, proteins more abundant in the S3 sample are redspots, while proteins more abundant in the S4 sample are green spots.

Proteins that are approximately equal in abundance in the two

samples appear as yellow spots

Sex Plant Reprod (2011) 24:9–22 11

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http://www.thegpm.org/TANDEM/index.html

http://www.thegpm.org/TANDEM/index.html

http://pubchem.ncbi.nlm.nih.gov/omssa/browser.htm

http://pubchem.ncbi.nlm.nih.gov/omssa/browser.htm

http://www.expasy.ch/

http://www.expasy.ch/

CM, the fourth being the GroEL molecular chaperone. The

results by themselves fail to provide any significant insight

into flower development or regulation of gene expression.

Watson et al. (2003) used 2-DE coupled with MALDI-TOF

PMF plus LC–MS/MS to identify 304 proteins from barrel

medic (Medicago truncatula) flowers. The distribution

among functional groups was nearly identical to that of the

A. thaliana proteins (Feng et al. 2009a).

Raharjo et al. (2004) and Ahsan and Komatsu (2010)

used the 2-DE MALDI-TOF PMF approach to compare the

leaf and flower proteomes of Cannabis sativa L. cv Purple

Haze and Glycine max L. cv Enrei, respectively. Not

surprisingly, the proteomes of the different organs are

dissimilar, reflecting their specialized biological roles.

Unfortunately, in neither case was there any true flower-

specific information.

Using a 2-DE LC–MS/MS experimental strategy,

Dafny-Yelin et al. (2005) and Bai et al. (2010) analyzed the

onset of petal senescence in rose (Rosa hybrida cv. Fra-

grant Cloud) and petunia (Petunia x hybrida Mitchell

Diploid), respectively. In the two studies, a total of *100

proteins were identified, and patterns of increased or

decreased abundance were quantified. However, none of

the identified proteins was clearly flower- or senescence

associated or specific. Bar-Akiva et al. (2010), as part of a

comprehensive analysis of Brunfelsia calycina petals after

flower opening, reported using LC–MS/MS to identify

seven proteins. In contrast to the results of others, all seven

were enzymes involved in metabolism of either pigment or

scent compounds.

The male gametophyte

Temporal and spatial regulation of gene expression during

male gametophyte development in flowering plants has

been described (Suzuki 2009; Wilson and Zhang 2009);

however, only Kerim et al. (2003) have reported high-

quality 2-DE maps of developing male gametophytes (rice

(Oryza sativa L. cv. Doongara) at the pollen mother cell,

tetrad, early young microspore, early binucleate, late

binucleate, and heading stages. Using MALDI-TOF MS

and PMF analysis, they were able to identify 33 non-

redundant proteins but none of them appeared to have any

stage-specific or anther-specific roles.

There have been extensive ([100 proteins identified)

gel-based proteomic analyses of mature pollen from

A. thaliana (Noir et al. 2005; Holmes-Davis et al. 2005;

Sheoran et al. 2006), tomato (Lycopersicon esculentum)

(Sheoran et al. 2007), and rice (O. sativa L. ssp japonica;

Dai et al. 2006). Proteins were identified by LC–MS/MS.

In each study, the proportion of identified protein assigned

to each cluster was very similar; the majority of the pro-

teins were distributed among the CM, CS, SR, and PUF

clusters. The results of the meta-analysis (3 species, 654

proteins) can be seen in Fig. 3.

Pollen grains are rich in triacylglycerols and other

storage compounds (Piffanelli et al. 2003) that are used to

support the huge demand for energy and biosynthetic

intermediates during postgerminative pollen-tube growth

(Taylor and Hepler 1997). It is then not surprising that the

most populous class of pollen proteins includes the many

enzymes of CM (glycolysis, the Krebs cycle, and mito-

chondrial respiration). The next most abundant pollen

proteins are those assigned to CS and PF, followed by the

SR and HS clusters.

Sheoran et al. (2009a) employed 2-DE, DIGE, and

MALDI-TOF/TOF MS to identify 130 proteins from ger-

minating canola (Brassica napus) pollen. All of the pro-

teins identified were present in both mature pollen and

germinated grains. Similarly, Dai et al. (2006, 2007a, b)

used a combination of MALDI-TOF MS plus ESI Q-TOF

MS/MS to identify 120 non-redundant proteins from ger-

minating rice (O. sativa L. ssp. japonica cv. Zhonghua 10)

pollen. However, contrary to the claim apparently made in

the titles, they failed to identify any proteins specifically

associated with germination of pollen grains.

There are a handful of publications that present data

from more specialized pollen analyses. For example, Pertl

et al. (2009) isolated subcellular fractions (endoplasmic

reticulum, Golgi, mitochondria, and plasma membrane)

and then used LC–MS/MS to characterize the membrane

proteome. Unfortunately, in the absence of any other such

study in pollen, the only comparisons that can be made are

to the results from analyses of other organs.

The protein allergens present in pollen have been

extensively studied (Puc 2003; Mohapatra et al. 2008).

Virtually without exception, however, these publications

address the biomedical consequences of the allergens

rather than any aspect of their role(s) in plant reproductive

biology, and they will not be further addressed herein.

Fig. 3 The functional distribution of 654 pollen proteins (L. escu-lentum, A. thaliana, and O. sativa) (Noir et al. 2005; Holmes-Davis

et al. 2005; Sheoran et al. 2007; Dai et al. 2006). Percent: CS 12, NA3, PS 4, PF 9, PT 7, CM 37, MT 4, SR 10, HS 8, PUF 7


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The female gametophyte

Egg cells are differentiated for fertilization and subsequent

embryogenesis. The signals and events that underlie the

differentiation of egg cells remain obscure despite their

importance in the plant life cycle (Hiscock and Allen

2008). Hopefully, description of the egg cell proteome

will contribute to a better understanding of the mecha-

nisms of female gametogenesis, fertilization, and early

embryogenesis.

The very limited amount of starting material is a major

obstacle in attempting to characterize the egg cell prote-

ome, and only a few proteins have been identified thus far.

Rice egg cells were isolated from unpollinated ovaries by

making a transverse incision followed by applying pressure

with a glass needle (Uchiumi et al., 2007). The isolated egg

cells were washed and then lysed by direct transfer into

SDS–PAGE sample buffer. Using a GeLC–MS/MS strat-

egy, Uchiumi et al. (2007) identified four proteins: the

cytoplasmic glycolytic enzyme glyceraldehyde-3-phos-

phate dehydrogenase, histone H4, cytoplasmic ascorbate

peroxidase, and a member of the Hsp90 family of molec-

ular chaperones (Hsp82). The same research group isolated

and analyzed maize egg cell proteins (Okamoto et al. 2004)

by 2-DE plus LC–MS/MS. The identified maize egg

cell proteins are three cytoplasmic glycolytic enzymes,

GAPDH, 3-phosphoglycerate kinase, and triosephosphate

isomerase, mitochondrial ATP synthase ß-subunit, a

mitochondrial adenine nucleotide transporter, and annexin

p35 (Okamoto et al. 2004). All of the identified proteins are

known to be relatively abundant in plant cells, which

facilitated identification. Hopefully, technical improve-

ments in egg cell isolation, such as those described by

Hoshino et al. 2006), will lead to larger amounts of starting

material and a more comprehensive description of the egg

cell proteome.

Can any significance be attributed to the nine different

egg cell proteins identified from maize and rice? The

glycolytic pathway is common to all living cells, and the

individual glycolytic enzymes are well known to be

abundant cellular proteins (Plaxton 1996), so it seems

unlikely that the identification of GAPDH, PGK, and TPI is

of any egg cell-specific significance. However, it is also

well known that many of the glycolytic enzymes have

additional, non-catalytic functions (Sirover 1997; Pancholi

2001), so the possibility of egg cell-specific functions

should be at least considered. It has been recently reported

that the mitochondria of rice egg cells have an unusual

morphology (Takanashi et al. 2010). Perhaps then a change

in the abundance or biological role for the ATP synthase

ß-subunit and/or adenine nucleotide transporter is also

possible? The annexins are abundant multifunctional cal-

cium-dependent phospholipid-binding proteins (Talukdar

et al. 2009). Are there egg cell-specific roles for annexins?

Perhaps they are abundant because of the increase in pro-

tein and polysaccharide secretion that is stimulated by the

fertilization-induced increase in Ca2? levels in the zygote

(Dumas and Rogowsky 2008). Are these and the other egg-

cell proteins specifically important, or are they simply

abundant and easily identified? The answer to this awaits

the results from additional studies of the egg-cell proteome.

It is noteworthy that similar types of proteomic analyses

of animal reproduction have led to the identification and

quantification of dozens of ‘‘spermatogenesis’’, ‘‘zygote-

specific’’, and ‘‘gamete-associated’’ proteins (Karr 2007;

Huang et al. 2008; Roux et al. 2008). Presumably, similar

advancements in the understanding of plant reproductive

proteomics await development of better methods and

instrumentation, and more attention from plant biologists.

Changes after fertilization

Vyetrogon et al. (2007) used 2-DE with Sypro Ruby

staining to quantify changes in the wild potato (Solanum

chacoense) ovary proteome 30, 36, 42, and 48 h after

pollination. Proteins were identified by LC–MS/MS anal-

ysis of tryptic peptides using a hybrid quadrupole-TOF

instrument. Of the [600 proteins quantified from 2-DE

maps, 38 showed a significant change postfertilization.

Most of the proteins decreased in abundance over the 48 h,

and unfortunately the six proteins that increased in abun-

dance all belong to the PUF group.

In the same study, the authors also quantified changes in

the P-proteome, using three methods in parallel. The spots

separated by 2-DE were either stained with the phospho-

protein-specific fluorescent dye ProQ Diamond (Agrawal

and Thelen 2009) or transferred from gels onto membranes

and then probed with antibodies to P-Ser, P-Thr, or P-Tyr

(Sefton and Shenolikar 2001). The third method of detec-

tion involved metabolic labeling with 32Pi. In toto, 262

(42%) of the 619 Sypro Ruby staining proteins were

detected as P-proteins. Among these, use of P-amino acid

antibodies detected 184 proteins, of which 78 were also

detected with at least one of the other two methods.

Staining with Pro-Q Diamond detected 111 proteins, of

which 76 were also detected with one of the other two

methods. The 32P in vivo labeling method detected 90

spots, of which 78 were also detected with one of the other

two methods. Comparison of before and after fertilization

profiles, 38 P-proteins showed a reproducible change in

their abundance. Most of the identified P-proteins corre-

spond only to entries in potato EST libraries that them-

selves correspond to members of the PUF group. The

relatively small number of changes in the S. chacoense

ovary proteome after fertilization was unexpected, since

the results of previous transcript profiling analyses led to


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the conclusion that this system is highly dynamic at the

mRNA level (Germain et al. 2005; Vyetrogon et al. 2007).

It is, however, necessary to keep in mind that proteomic

analyses target only the more abundant components of the

proteome and furthermore that in most biological systems,

there is a high degree of discordance between transcript

and protein levels (c.f., Hajduch et al. 2010).

Self-incompatibility

Self-incompatibility is a genetically controlled mechanism

to prevent inbreeding. Feng et al. (2006) used 2-DE

LC–MS/MS strategy to compare pistil-protein differences

between self- and cross-pollination of a self-incompatible

apricot (Prunus armeniaca) but were able to identify only

four pistil proteins that were increased in abundance after

cross-pollination (actin-12, enolase, a MYB transcription-

factor-like protein, and Hsp70), and three proteins were

detected only in self-pollinated pistils (actin-7, actin-8, and

a fructose 1,6-bisphosphate aldolase–like protein). More

recently, the same group (Feng et al. 2009b) used the same

strategy to compare compatible and self-incompatible

apricot cultivars. Nine proteins, including a receptor-like

protein kinase, were detected only in the compatible pistils,

and another 9 proteins, including actin-7, a putative protein

Ser/Thr kinase, and an S-RNase, were detected only in the

self-incompatible pistils.

Cytoplasmic male sterility is not addressed herein

because it is unimportant, but rather because of the paucity

of publications that have employed a proteomics-base

approach for analysis. The recent paper by Sheoran et al.

(2009b) indicates that this oversight has been recognized.

Seed abortion

Seed abortion is one of the mechanisms by which plants

can respond to extremes in environmental conditions (c.f.,

Fang et al. 2010). Liu et al. (2010) used a 2-DE MALDI-

TOF/TOF strategy to study seed abortion in Dimocarpus

longan. They identified more than 40 proteins from aborted

seeds, most of which belong to the CM, PF, and PUF

categories. Among the identified proteins are three Cys-

proteases that the authors suggest might be linked to pro-

grammed cell death. No other studies of seed abortion have

used a proteomics approach, so testing this suggestion

awaits the results of future experiments.

Seed development

Post fertilization, the various tissues of the female game-

tophyte continue to develop and differentiate, becoming

the embryo and then, after further specialization, the

developing seed (embryo, endosperm, seed coat; Weber

et al. 2005; Le et al. 2007). Certain aspects of seed biology

simplify study; all cell division is completed within the first

few days after fertilization. This marks the line of demar-

cation between embryogenesis and seed development. All

subsequent cellular specialization takes place in the

absence of cell division (Chandler 2008). The bulk of

metabolic activity during seed development is directed

specifically at the synthesis and accumulation of storage

polymers (oils, polysaccharides, and proteins) (Gallardo

et al. 2003; Hills 2004). These compounds and the sub-

cellular structures that contain them are inert depots

awaiting the activities responsible for mobilizing them to

provide biosynthetic intermediates necessary until the

developing seedling becomes autotrophic (Le et al. 2007;

Gallardo et al. 2008). All seeds contain one or more groups

of proteins that are present in high amounts acting as

depots for reduced nitrogen that will subsequently be used

during germination and seedling growth, the seed storage

proteins (SSP, Shewry et al. 1995). While SSP can account

for as much as 60% of total seed protein, most of them are

otherwise inert, so they have been manually subtracted

from all of the analyses presented herein.

Endosperm development

The endosperm, a tissue unique to flowering plants, is

composed of a few specialized cell types that produce large

quantities of storage polymers. The amount of endosperm

in a mature seed is variable. For example, it comprises a

large portion of the whole seed mass in cereals, such as rice

(O. sativa), maize (Zea mays), and wheat (Triticum aes-

tivum), and it is prominent in the seeds of a few dicotyle-

dons, such as castor (Ricinus communis L). In other

species, for example A. thaliana, the endosperm is almost

completely absent in the mature seed. Whether the endo-

sperm persists or not, it is vital for embryo development in

much the same way the placenta is essential for mamma-

lian embryos (Wang et al. 2009).

Castor is an unusual example of an oil-rich endosperm-

dominant seed; most accumulate starch rather than oil.

Using a 2-DE plus LC–MS/MS strategy, Houston et al.

(2009) identified 522 proteins from developing castor

endosperm. Discounting the SSP, the 20 most abundant

castor proteins were involved in CM, PF, SR, and CS. The

total distribution of the castor proteins was very similar to

that of pollen proteins (Fig. 3). This similarity could reflect

that both are oil-rich organs and therefore have relatively

high levels of proteins involved in both biosynthesis and

catabolism of the oil.

Similar patterns of identified protein distribution were

seen among the endosperm-dominant starch-rich seeds of

wheat, barley, rice, and maize. Using a 2-DE plus either

MALDI-TOF PMF (Finnie et al. 2002; Vensel et al. 2005;


123

Finnie and Svensson 2009) or LC–MS/MS (Mechin et al.

2004; Mak et al. 2006; Xu et al. 2008; Kim et al. 2009)

experimental design, a total of 1,496 proteins were iden-

tified. When the proteins are separated into the same 10

functional classes that have been used throughout, the

distribution is as follows: CM, 34%; CS, 12; SR, 5; NA, 2;

PS, 2; PF, 5; PT, 7; HS, 2; MT, 2; and PUF, 29.

Larre et al. (2010) used a 2DE LC–MS/MS strategy to

study SSP of the ‘‘model cereal’’ Brachypodium distach-

yon. Electrophoresis of a urea extract of mature seeds

resolved 120 spots, 65 of which were excised for MS

analysis. Twenty-three well-resolved spots were identified

as members of the 11S storage protein family, encoded by

five genes. Two sets of minor spots were identified as 7S

globulins. In addition to the SSP, a xylanase inhibitor was

identified.

The results from separate proteomic analyses of devel-

oping wheat (Vensel et al. 2005) and rice (Xu et al. 2008)

endosperm, and wheat (Mak et al. 2006) and rice embryos

(Woo et al. 2002; Wang et al. 2008) highlight the differ-

ences in these two seed organs (Table 1). The CM proteins

were the most abundant in all instances; however, members

of the PF category were relatively more abundant in

endosperm, while proteins included in the SR and HS

categories were more abundant in embryos. The higher

proportion of proteins involved in signaling might reflect

the role(s) of the embryo in controlling metabolism in the

endosperm (c.f., Perata et al., 1997). Proportionally, there

are far more PUF proteins in endosperm than in embryos.

Amyloplasts are non-green plastids specialized for the

synthesis and accumulation of starch (Neuhaus and Emes

2000). Balmer et al. (2006) describe the isolation of amy-

loplasts from developing wheat endosperm and the use of a

2-DE LC–MS/MS strategy to identify 289 proteins. In

addition to all of the enzymes necessary for starch bio-

synthesis, they were also able to identify many proteins

involved in nitrogen and sulfur assimilation, and amino

acid and lipid biosynthesis. Overall, the composition of the

wheat endosperm amyloplast proteome is more similar to

that of castor endosperm leucoplasts (Campos et al. 2010)

or even green plastids (van Wijk 2004; van Wijk et al.

2007) than to the wheat endosperm cell cytoplasm.

Embryo development

Embryonic axes generally are removed before proteomic

analysis of embryo-dominant seeds. Alternatively, the

contributions of the axes are simply ignored as very minor

components. As a result, proteomic descriptions of

embryo-dominant seeds correspond almost entirely to the

cotyledonary proteome. Typically, embryo-dominant seeds

contain starch plus SSP as the storage polymers (peas,

beans, and lentils) or oil plus SSP (mouse-eared cress,

canola, and soybean/barrel medic/lotus). To date, the

cotyledons of legume seeds have received the most atten-

tion from ‘‘omics biologists,’’ in part due to their agro-

nomic importance (Weber et al. 2005; Le et al. 2007;

Gallardo et al. 2008; Thompson et al. 2009).

There have been extensive proteomic studies of devel-

oping G. max (Hajduch et al. 2005; Agrawal et al. 2008),

M. truncatula (Gallardo et al. 2003, 2007), and Lotus

japonicus (Dam et al. 2009) seeds. Experimental strategies

included 2-DE plus MALDI-TOF, 2-DE plus LC–MS/MS,

or GeLC–MS analysis of tryptic peptides. Seed proteome

data for G. max, M. truncatula, and L. japonicus have been

collected and analyzed and can be retrieved from: http://

bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/pathexpress

4legumes.php. A total of 1,723 proteins were identified.

Manual subtraction of 316 SSP gave 1,407 identified pro-

teins from the three legume species. When these proteins

were separated into 10 categories, the percent distribution

was CM, 49%; CS, 19; NA, 2; PS, 3; PF, 5; PT, 3; HS, 3;

MT, 4; SR, 3; and PUF, 10. In all three species, a relatively

large number of the late embryo abundant proteins were

identified.

Similar studies of A. thaliana (Hajduch et al. 2010) and

B. napus (Hajduch et al. 2006; Agrawal et al. 2008) seeds

yielded similar results. A total of 1,290 proteins were

identified by either 2-DE plus LC–MS/MS or MudPIT.

After manual removal of 241 SSP entries, this leaves 1,049

identified proteins. Once again, the CM category was by far

the most populous (36%), followed by CS (19%) and PUF

(17%).

Agrawal et al. (2006) used the phospho-protein-specific

fluorescent dye ProQ Diamond as a probe for analysis of

developing B. napus seeds. They were able to detect 234

Table 1 Percent distribution of wheat and rice seed proteins; endo-

sperm versus embryo

Wheat Rice

Functional group Endosperm Embryo Endosperm Embryo

Central metabolism 27 26 34 27

Cell structure 0 2 12 2

Stress response 9 22 5 19

Nucleic acid 0 8 2 10

Protein synthesis 9 10 5 9

Protein folding 15 4 9 2

Protein targeting 7 3 5 5

Hormones/signaling 9 21 2 17

Membrane transport 1 2 2 1

Proteins of unknown

function

23 2 29 8

Total proteins identified: wheat endosperm, 256 (Vensel et al. 2005);

wheat embryo, 347 (Mak et al. 2006); rice endosperm 274 (Xu et al.

2008) and; rice embryo 132 (Woo et al. 2002; Wang et al. 2008)


123

http://bioinfoserver.rsbs.anu.edu.au/utils/PathExpress/pathexpress4legumes.php



phospho-protein spots from 2-D gels, 103 of which were

identified by LC–MS/MS. Not surprisingly, most of the

identified proteins were in the CM and HS categories. It

was, however, somewhat surprising that many of the cru-

ciferin SSP subunits gave a positive phospho-protein stain

since these proteins had not been previously described as

phospho-proteins.

Jain et al. (2008) used MudPIT to identify 80 proteins

from plastids purified from developing B. napus embryos.

The plastid proteins complement was enriched with

enzymes of the CM grouping and was mid-way between

the non-green plastids from wheat and castor endosperm

(Balmer et al. 2006; Campos et al. 2010) and the chloro-

plasts isolated from green organs (van Wijk 2004; van

Wijk et al. 2007).

In contrast to the oil plus SSP embryo-dominant seeds,

the main starch plus SSP seeds that have been character-

ized are pea, Pisum sativum (Bourgeois et al. 2009), and

lentil, Lens culinaris (Scippa et al. 2010). A combination of

MALDI-TOF PMF and LC–MS/MS was used to identify

122 proteins from mature L. culinaris seeds. Manual sub-

traction of the SSP reduced this number to 25. Of these, 6

were grouped in CM, 4 each in CS and PT, and 3 each in

NA and SR. Similar results were obtained when Bourgeois

et al. (2009) used MALDI-TOF PMF to identify 156 pro-

teins from mature pea seeds. Manual subtraction of the SSP

left 39, mainly distributed among CM (16), PUF (8), CS

(7), and PF (4). A major problem with analysis of the starch

plus SSP legume seeds is the lack of good genomic or EST

resources.

Seed germination

Mature quiescent seeds are dispersed at low (5–15%)

moisture content and with metabolic activity at a standstill.

For germination, quiescent seeds need only be hydrated at

a suitable temperature in the presence of O2. Germination

begins with water uptake by the seed (imbibition), con-

tinues through the elongation the embryonic axis inside the

seed, and is visibly manifest by protrusion of the radicle

through the seed coat (Bove et al. 2003). The sum of these

events represents the transition of the quiescent embryo to

an autotrophic plant. Germination involves many cellular

and metabolic events, coordinated by complex regulatory

networks.

Herein, seed dormancy will be treated as a specialized

variant of quiescence (Finkelstein et al. 2008). Dormancy

is a process whereby germination is delayed in order to

avoid conditions adverse for seedling survival by opti-

mizing the timing of germination. Release from dormancy

is controlled by perception of a combination of environ-

mental signals (Bove et al. 2003; Finkelstein et al. 2008;

Holdsworth et al. 2008; Pawłowski 2010). Temperature,

light quality, and hormonal balance (abscisic acid and

gibberellins) all play key roles in release from dormancy.

The period between germination and assumption of

autotrophy is broadly referred to as postgerminative

growth. It is during this period that the seed storage poly-

mers (oil, polysaccharides, and SSP) are mobilized to

provide biosynthetic intermediates. In general, the enzymes

necessary for polymer degradation are synthesized de novo

during postgerminative growth. Thus, SSP proteases (endo-

and exo-), lipases and the glyoxylate cycle enzymes, and

starch-degrading enzymes can serve as markers to define

the period of postgerminative growth.

Endosperm-dominant seeds

Total endosperm proteins from germinating castor seeds

were analyzed using a 2-DE plus MALDI-TOF/TOF MS

strategy, and nearly 400 total proteins were identified

(Campos et al. 2010). Essentially, all of these proteins are

the same as were previously described from analysis of

developing castor endosperm (Houston et al. 2009). The

extremely high ‘‘background’’ of SSP and CM proteins

precluded identification of any proteins that could be spe-

cifically attributed to germination/postgerminative growth.

Castor endosperm plastidial and mitochondrial fractions

were also prepared and subjected to proteomic analysis

(Campos et al. 2010). The proteins identified are the same

as have been previously described for these organelles

from other plant species and organs (van Wijk 2004; Lee

et al. 2008; Huang et al. 2009). Maltman et al. (2007) used

2-DE, DIGE, MALDI-TOF PMF, and LC–MS/MS to show

that more than 100 proteins are differentially abundant

when comparing the endoplasmic reticulum (ER) from

developing castor endosperm with that from germinated

seeds. With the exception of a few contaminants from other

organelles (RuBisCO, plastids; malate synthase, and gly-

oxysomes) and PUF proteins, those identified were all

either SSP or members of the PF and PT groups.

A proteomics strategy employing 2-DE and MALDI-

TOF PMF analysis was used to identify nearly 200 proteins

from germinating barley seeds (Ostergaard et al. 2004).

Nearly all of the proteins identified are included in the CM,

PF, CS, and SR categories. By 3 days after imbibitions,

there were large increases in the enzymes involved in

starch breakdown and mobilization, such as the a- and

b-amylases.

Because barley is used extensively in the food and

brewing industries, there have been detailed analyses of a

few specific proteins: a-amylase, peroxidases, and thiore-

doxins (Finnie and Svensson 2009). Hynek et al. (2009)

used LC–MS/MS to analyze a plasma membrane-enriched

fraction isolated from germinating barley. Many of the

proteins identified appear to be contaminants from other


123

subcellular organelles, demonstrating how difficult it is to

obtain purified subcellular components. Despite the diffi-

culties, they also identified several bona fide plasma

membrane proteins including an H?-ATPase, a pyrophos-

phatase, and a voltage-dependent anion channel (Hynek

et al. 2009).

Analysis of germinating rice endosperm using a 2-DE

plus MALDI-TOF MS strategy allowed Yang et al. (2007)

to study proteins that changed in abundance. They found

that the SSP, along with members of the CM and CS

groups, decreased in abundance during germination, while

different members of the CM group increased, some of

which are involved in starch breakdown. Results similar to

those found with germinating rice and barley endosperm

proteins were also found during studies of wheat and

maize.

Evidence is accumulating that indicates the cellular

environment is increasingly oxidizing as seeds dehydrate

and approach quiescence. Formation of disulfide bonds is

one of the manifestations of the changing redox environ-

ment. Subsequently, in response to imbibition, the thiore-

doxin system, composed of NADPH, thioredoxin h, and

NADP-thioredoxin reductase, is activated (Hagglund et al.

2008). This system reduces disulfide bonds and in doing so

increases protein solubility, the rate of proteolysis, and

ultimately the extent of nitrogen and carbon mobilization

(Yano and Kuroda 2006). The endosperm-based thiore-

doxin paradigm was subsequently extended to include

dicotyledon seeds (Alkhalfioui et al. 2007).

Cotyledon-dominant seeds

Essentially all reported proteomic analyses of ‘‘germinat-

ing seeds’’ are actually from studies of postgerminative

growth. Inevitably, 2-DE-based LC–MS/MS analyses of

the postgerminative growth of cotyledon-dominant seeds

yield datasets identical to those of mature seeds and are

dominated by the presence of SSP (Fu et al. 2005; Sheoran

et al. 2005; Pawłowski 2007, 2009; Sghaier-Hammami

et al. 2009; Yang et al. 2009). If proteins are quantified,

then the major theme is the decrease in levels of SSP. In

some instances, this overall decrease is accompanied by

transient accumulation of SSP degradation intermediates.

In contrast to most ‘‘shotgun’’ proteomic analyses of

seeds, Muller et al. (2010) reported the results from anal-

ysis of a specific tissue, the endosperm cap, during ger-

mination of Lepisium sativum seeds. The cap is a specific

part of the endosperm surrounding the embryo radicle.

Using a 2-DE plus LC–MS/M strategy, 140 proteins were

identified. The largest group of proteins was the CM

cluster, followed by SR and PF. The endosperm cap pro-

teome was both qualitatively and quantitatively different

from the rest of the endosperm, but no proteins were

identified, which might be responsible for modification of

the endosperm structure in response to radicle protrusion.

Apomixis

Asexual reproduction of plants by female syngamy is

referred to as apomixis. Embryos that are genetically

identical to the maternal parent are produced without

meiosis or egg cell fertilization (Chen 2007). There are two

forms of apomixis: sporophytic and gametophytic. Apo-

mixis allows formation of clonal embryos, which has

recently stimulated interest among plant breeders because

it suggests the ability to fix heterosis.

Genetic mapping has been successfully used in a wide

variety of apomictic taxa to explore the genetics bases of

the trait. Employing a proteomic approach to analysis of

apomixis allows researchers to additionally consider epi-

genetic contributions, as well as the roles of a myriad of

protein posttranslational modifications. To date, there has

been only a single publication that focuses on the proteo-

mics of apomixis, a comparative study of interspecific

hybrids between diploid Beta vulgaris and tetraploid

B. corolliflora (Zhu et al. 2008). From this cross, the

monosomic addition line M14 was selected based upon an

apomictic phenotype.

Using a 2-DE plus MALDI-TOF MS strategy, a total of

27 protein spots that varied in abundance among lines were

identified. These included five protein spots that were

detected only in M14 and two protein spots found only in

B. vulgaris. Among the identified proteins, 13 were more

abundant in M14 than in B. vulgaris and seven were less

abundant.

The identified proteins could be separated into eight

clusters, the largest of which was once again CM. While no

mechanistic conclusions can be reached based upon a

sample size of 27, the results will contribute to a better

understanding of the genetic mechanisms underlying apo-

mixis and how they might be exploited.

Prospectus

To date, there have been relatively few studies where a

proteomics-based strategy has been applied to the study of

angiosperm reproduction. Of the studies that have been

conducted, a large majority have addressed seeds; either

developing or ‘‘germinating’’ (Fig. 4). One goal of this

review was to identify areas where there is a need for

increased application of proteomics-based methods.

Clearly, these include all aspects of floral biology, study of

the female gametophytes, self-incompatibility, environ-

mental and genetic contributions to seed abortion, and

study of the proteome changes that accompany seed after-

ripening and dormancy. There is additionally a need for


123

greater comparative analysis for all aspects of plant

reproductive biology, although in many cases this will

require parallel development of better genomic/EST

resources to facilitate protein identification.

Proteomics as a research area is increasingly moving

from gel-based to gel-free approaches for protein analysis.

Without question the latter strategy allows identification of

more proteins and is amenable to use with automated, high-

throughput platforms (Schulze and Usadel 2010). At the

same time, gel-free analyses require application of more

robust standards of statistical analysis (Nie et al. 2008). At

least in the foreseeable future, there will remain applica-

tions for gel-based proteomics, especially in targeted-pro-

teomic studies such as those involving DIGE. In all

likelihood, a combination of gel-based and gel-free meth-

ods will comprise the state-of-the-art for years to come

(c.f., Insenser et al. 2010).

The need for a transition from qualitative to quantitative

proteomics is without debate. In contrast, how to best

achieve this is virtually without agreement! There are

essentially two schools of thought: methods involving

protein labeling and label-free methods (Thelen and Peck

2007). Not surprisingly, there are a plethora of methods

proposed to achieve both ends (Schulze and Usadel 2010).

While this debate is likely to continue into the future, a

label-free method gaining some traction is spectral count-

ing (c.f., Stevenson et al. 2009; Huang et al. 2010;

Lundgren et al. 2010). Regardless of the final evolution of

analysis methods, it is clear that any future proteomics-

based studies of plant reproduction would benefit from

quantitative approaches.

One aspect of biology that cannot be addressed in any

other large-scale survey (e.g., transcript profiling) is protein

PTM, and much of the breadth of the proteome results from

a profusion of protein PTM (Farley and Link 2009). In

addition to the nature of the PTM, it is also important to

determine the specific residue that is modified and the

result of the modification (Møller et al. 2007). Do the PTM

affect protein turnover, activity, and interactions? In

addition to using bottom-up analysis strategies, it is

important that top–down proteomic analyses are included

in analysis of PTM (Siuti and Kelleher 2007). In only a

very few instances have analyses of plant reproduction

included systematic analysis of PTM, and these have only

addressed protein phosphorylation (Agrawal et al. 2006;

Agrawal and Thelen 2009). In addition to identification of

the nature of PTM, it is important to determine their stoi-

chiometry in the proteome. Changes in PTM stoichiometry

likely indicate a specific functional change, while increase

in protein amount with a parallel increase in the amount of

PTM means that the stoichiometry has not changed, and

there is unlikely to be an extensive functional change.

The other major aspect of biology that cannot be

addressed in any sort of high-throughput or computational

context is that of protein interactions (e.g., the interac-

tome). There are no extant publications addressing

MS-based analysis of protein interactions during angio-

sperm reproduction. There should be! The way that a

protein behaves in dilute solution after purification is

unlikely to be the same as it behaves in vivo. The next

wave of understanding of how proteins function involves

analysis of protein interactions in a cellular or subcellular

context (Gache et al. 2010; Sharon 2010).

Essentially all of contemporary proteomic analyses are

MS based. Any discipline that is largely or exclusively

instrument based will always be searching for improve-

ments (c.f., Olsen et al. 2009). The development of

instruments that are faster and more precise will be bene-

ficial for not only study of angiosperm reproduction but

also all proteomics research.

An exciting and relatively new application of MS in

proteomics studies is at the tissue- and sometimes even

cellular level of analysis; imaging MS or MALDI-imaging

(Heeren et al. 2009; Stauber et al. 2010). By gating the

detector to a specified mass (or range), it is possible to

detect the location of a protein in whole tissue/organ

mounts. Especially in conjunction with high-sensitivity

instruments, this method could have significant applica-

tions to analysis of either small floral structures or larger

structures with low protein concentrations (MacAleese

et al. 2009).

From the very beginning, analyses have been plagued by

the enormous dynamic range of proteins in biological

samples. The archetype of this problem has been human

serum. Until simple, inexpensive, and efficient methods

were developed to remove albumin and IgG proteins,

meaningful proteomic analyses of serum were impossible

(Steel et al. 2003). The situation is much the same in plant

leaves (RuBisCO) and seeds (SSP). Multiple strategies for

removal of abundant proteins are available, including

0

10

20

30L

iter

atu

re r

epo

rts

Fig. 4 Numerical analysis of literature reports describing use of a

proteomics-based strategy, as a function of reproductive tissue/organ/

stage


123

differential solubility, affinity chromatography, and

immuno-removal (Miernyk and Johnston, 2006; Li et al.

2008; Krishnan et al. 2009). Application of these methods,

further refinements, and ingenious experimental designs

will allow a much greater depth of analysis to studies of

plant reproduction and help us to better understand this

fascinating but extremely complex process.

Acknowledgments This investigation was supported by Seventh

Framework Program of the European Union—International Reinte-

gration Grant (MIRG-CT-2007-200165), COST Action FAO903,

Bilateral project CSIC-SAS (2007 SK 0001), Project APVV-0115-07,

VEGA 2/0005/08 (Study of the cell events in course of embryo for-

mation in situ and in vitro conditions in Arabidopsis and maize) and is

a joint publication within the action COST FA 0903, ‘‘Harnessing of

Plant Reproduction for Crop improvement,’’ a bilateral Spanish-

Slovak cooperation (2007–2009) and the Spanish MEC Project

(BFU2006-09876/BFI). Support for JAM was in part from the

National Scholarship Program of the Slovak Republic, administered

by the Slovak Academic Information Agency. The authors thank

B.A. McClure, J.J. Thelen, and two anonymous reviewers for their

constructive comments.

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Using proteomics to study sexual reproduction in angiosperms