REVIEW ARTICLE

The application of proteomic approaches to the studyof mammalian spermatogenesis and sperm functionGraham MacLeod and Susannah Varmuza

Department of Cell & Systems Biology, University of Toronto, ON, Canada

Keywords

interactomes; phosphoproteomics; protein

phosphatase; proteomics; reproductive

biology; spermatogenesis

Correspondence

S. Varmuza, 25 Harbord Street, Toronto,

ON, Canada M5S 3G5

Fax: 416-978-8532

Tel: 416-978-2759

E-mail: s.varmuza@utoronto.ca

(Received 22 February 2013, revised 4 July

2013, accepted 26 July 2013)

doi:10.1111/febs.12461

Spermatogenesis is the process by which terminally differentiated sperm are

produced from male germline stem cells. This complex developmental pro-

cess requires the coordination of both somatic and germ cells through

phases of proliferation, meiosis, and morphological differentiation, to pro-

duce the cell responsible for the delivery of the paternal genome. With

infertility affecting ~ 15% of all couples, furthering our understanding of

spermatogenesis and sperm function is vital for improving the diagnosis

and treatment of male factor infertility. The emerging use of proteomic

technologies has played an instrumental role in our understanding of sper-

matogenesis by providing information regarding the genes involved. This

article reviews existing proteomic literature regarding spermatogenesis and

sperm function, including the proteomic characterization of spermatogenic

cell types, subcellular proteomics, post-translational modifications, interact-

omes, and clinical studies. Future directions in the application of proteo-

mics to the study of spermatogenesis and sperm function are also

discussed.

Introduction

Mammalian spermatogenesis is a precisely regulated

biological process resulting in the production of sper-

matozoa, one of the most unique and highly differenti-

ated cell types. Spermatogenesis consists of three

distinct phases within the seminiferous epithelium, all

of which are associated with the somatic Sertoli cells.

The first phase, the proliferative phase, refers to the

mitotic division of spermatogonia, which serves to pro-

vide an increased number of germ cells for differentia-

tion and to repopulate the stem cell niche. Next is the

meiotic phase, in which tetraploid spermatocytes

undergo meiotic division to produce haploid spermat-

ids. The final phase is the differentiation phase, known

as spermiogenesis, wherein the spermatids undergo a

series of dramatic morphological changes, leading to

functional sperm. Although the stages of spermatogen-

esis are well characterized at the cellular level, the pre-

cise biological mechanisms regulating this process are

not entirely understood. Enhancing our understanding

of spermatogenesis will prove useful in improving the

diagnosis and treatment of male factor infertility, a

condition that negatively affects the quality of life for

over 100 million couples worldwide.

To better understand the process of spermatogene-

sis, we must uncover which genes are involved, what

roles they play, and how they are regulated. To date,

targeted mutagenesis studies have produced ~ 400 dif-

ferent knockout mouse models with reproductive

defects [1], not limited to the ~ 4% of all mouse genes

revealed by transcriptome analysis to be specifically

Abbreviations

2DE, two-dimensional electrophoresis; AP-MS, affinity purification MS; HSP, heat shock protein; IMAC, immobilized metal ion affinity

chromatography; MRM, multiple reaction monitoring; PPP1, phosphoprotein phosphatase 1; PTM, post-translational modification;

SYCP, synaptonemal complex protein; TAP, tandem affinity purification.

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5635

expressed in the postmeiotic male spermatogenic cells

[2]; both testis-specific and ubiquitously expressed

genes can be found in the list of targeted mutations

that only affect spermatogenesis, the latter probably

reflecting functional redundancy in most tissues of par-

alogous genes. This collection of data underscores the

complex nature of spermatogenesis in mammals and

our need for an increased understanding of the pro-

cess. In contrast, numerous attempts over the past

10 years, since the publication of the human genome

sequence, to identify mutations linked to male infertil-

ity affecting ~ 5% of men have been unsuccessful in

uncovering good candidates for clinical genetic screen-

ing; the only tests routinely used in andrology clinics

are for Y microdeletions, chromosome abnormalities,

and cystic fibrosis transmembrane conductance regula-

tor mutations, which affect ~ 10% of patients [3,4].

Emerging proteomic technologies can provide a num-

ber of useful tools for studying mammalian spermato-

genesis. The use of proteomics is particularly

important for spermatogenesis, because the semiquan-

titative correlation between RNA and protein expres-

sion is lower in the testis than in other tissues [5],

indicating that oligonucleotide microarray and geno-

mic studies are less informative in this context. One

factor that complicates the comparison between RNA

and protein expression in the testis is the transcrip-

tional silencing found late in spermatogenesis, which

necessitates the storage of earlier-produced transcripts

for later use. This was illustrated in a recent isobaric

tags for relative and absolute qauntitation-based quan-

titative proteomics study that identified a large number

of proteins for which this is the case, especially during

the spermatocyte to round spermatid transition [6].

Compounding these difficulties further is the abun-

dance of tissue-specific alternative splicing observed in

the testis [7], one prominent example being the Ppp1 cc

gene, which is essential for the completion of sper-

matogenesis and encodes both the ubiquitous

PPP1CC1 and testis-specific PPP1CC2 isoforms [8].

Despite its importance, we have only recently begun to

scratch the surface of the potential of proteomic

research application to spermatogenesis. As an increas-

ing number of researchers have made use of such

technologies, it is not possible to discuss all of the

excellent research in the space available. Likewise, it is

not our aim to cover the technical details of proteomic

methodologies and data analysis. Many of the studies

described in this review have utilized model organisms,

most prominently the mouse and rat. The precise

level of conservation in the testis/sperm proteomes

between these species and humans remains unknown,

because complete proteome coverage has not been

accomplished. However, comparative studies have

revealed, that for many genes, there are spermatogene-

sis-associated homologs that have similar expression

patterns even over large evolutionary distances [9],

and, in general, conservation throughout mammals is

considered to be high. Comparative studies between

mouse and human reproductive proteins found good

correlations between mice and humans in general, but

also that proteins arising from the seminal vesicles

were showing a higher rate of divergence [10]. Another

comparison of published sperm proteome datasets

from a number of species revealed that a number of

functionally linked protein groups were conserved

throughout mammals [11]. This review will highlight

key studies that demonstrate the potential of

proteomic research in a number of different

contexts – including the proteomic characterization of

different spermatogenic cell types and subcellular com-

ponents, post-translational modifications (PTMs), clin-

ical studies, and protein–protein interaction networks.

Proteomic studies of spermatogenesis serve as an

important line of inquiry that complements genomic,

transcriptomic and epigenetic studies, which are

beyond the scope of this review but, together, hold the

key to understanding gene regulation during this pro-

cess. Furthermore, we hope that, by drawing attention

to the wide range of currently available datasets, this

review will serve as a useful resource for researchers

interested in the process of spermatogenesis.

Proteomic characterization ofspermatogenic cells

Spermatogenesis includes a number of different cell

types, many of which are in close contact in the semi-

niferous epithelium, the site of spermatogenesis within

the testis (Fig. 1). Each spermatogenic cell type repre-

sents a step towards the production of sperm, and

thus, by characterizing the proteome of the different

cell types, we can gain insights into the genes and pro-

teins involved in each step. Current estimates suggest

that the human sperm proteome contains approxi-

mately 2500–3000 proteins [11]; however, less differen-

tiated spermatogenic cells may contain a much higher

number [6], as much of the cytoplasmic material,

including organelles, is removed during the final stages

of spermiogenesis in order to streamline the cell for

motility and fertilization.

A number of studies have utilized whole testis pro-

tein extracts to examine protein expression throughout

the entire testis in a variety of species. In the mouse,

both fetal [12] and sexually mature whole testis

extracts [13] have been examined by two-dimensional

5636 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

electrophoresis (2DE) followed by MS. At least three

studies have examined the human testis proteome, with

varying methodologies [14–16]. Two of these studies

are from the laboratory of Sha and colleagues, where,

in 2008, with SDS/PAGE followed by LC-MS/MS,

1430 testis proteins were identified [14], and in 2010,

2DE followed by MALDI-TOF MS analysis identified

462 unique proteins [15]. In a more recent study, Li

et al. used 2DE and MALDI-TOF MS analysis to

identify 725 unique proteins in human testis protein

extracts [16]. Although these studies represent some of

the most extensive human testis proteome studies to

date, < 200 annotated proteins have been found in all

three datasets. This suggests not only that experimen-

tal variation can result in the generation of very differ-

ent datasets, but that we are probably very far from

reliably characterizing the entire testis proteome, as

these studies clearly do not approach the required

level of coverage. This highlights key limitations to

2DE-based approaches. Owing to more stringent pro-

tein size and dynamic range constraints, and lower

resolving power, they are less suitable for the identifi-

cation of large and diverse sets of proteins than

LC-MS/MS-based techniques, and are subject to a

greater degree of experimental variation. Conse-

quently, most laboratories are now using LC-MS/MS-

based methods for such studies, often in conjunction

with a suite of prefractionation and/or differential

labeling strategies [6,17].

Although studies of the whole testis proteome can

yield a considerable amount of data, they tell us little

about the roles of specific proteins in spermatogenesis,

as no information regarding the spatiotemporal pat-

tern of expression is obtained. To gain such informa-

tion, different approaches are needed, such as

following changes in expression during the first wave

of spermatogenesis at the onset of puberty, which is

synchronous, affording the opportunity to investigate

relatively homogeneous cell populations. In contrast,

in the adult testis, spermatogenesis has a wave-like

pattern along the seminiferous tubules, such that all

spermatogenic cell types are represented simulta-

neously in the testis. Thus, by examining gene expres-

sion patterns at different time points, we can gain

spatiotemporal information and insights into the

potential roles of genes in different aspects of sper-

matogenesis. Several groups have used such an

approach in a variety of different species. One recent

study, by Huang et al., used 2DE to analyze changes

in testis protein expression patterns in boar spermato-

genesis at three time points – 1 week (Sertoli cells and

spermatogonia only), 3 months (onset of spermatogen-

esis), and 1 year (maturity) [18]. The authors were then

able to identify 90 differentially expressed proteins via

MS. Several studies have used a similar approach in

mice, including one that utilized 2DE followed by

MALDI-TOF/TOF MS to identify 257 proteins that

were differentially expressed between six different time

points in the first wave of mouse spermatogenesis (0,

7, 14,21, 28 and 60 days) [19]. The authors then

applied clustering analysis of their data, and found six

distinct expression patterns that were each enriched for

Fig. 1. The testis is a complex and dynamic tissue. A cross-sectional view is shown of a single mouse testis visualized by light microscopy

with periodic acid–Schiff and hematoxylin staining. Left: a cross-sectional view showing several seminiferous tubules, each with different

complements of developing spermatogenic cells. Spermatogenesis progresses in a wave-like pattern along the length of the seminiferous

tubule, meaning that different segments of the tubules (cross-section) show different stages of spermatogenic cells. Right: a closer look at

a single seminiferous tubule, showing spermatogenic cells at various stages in development. The complex architecture and mixture of cell

types at various stages of development makes the testis a challenging tissue to analyze.

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5637

G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

cellular processes specific for particular stages of sper-

matogenesis (stem cell properties, mitosis, meiosis,

spermiogenesis, and fertilization). This analysis

allowed the authors to link a number of proteins with

unknown functions to specific stages of spermatogene-

sis, such as heat shock protein (HSP)27 (meiosis) and

peroxiredoxin-4 (spermiogenesis), which would not

have been possible if they had been looking at sperm

alone. The results of these studies show how the nat-

ure of the first wave of mammalian spermatogenesis

can be used to gain information regarding a protein’s

possible function, and allow us to infer potential cell

type-specific/enriched expression patterns. However, to

truly characterize specific spermatogenic cell types, it is

necessary to analyze them in isolation.

To date, there have been a number of studies that

have sought to characterize the proteomes of isolated

germ cell populations. This is done by separating cell

suspensions on the basis of size or DNA content with

a number of methods – fluorescence-activated cell

sorting (DNA content) [20], gravity sedimentation in a

StaPut apparatus [21], or centrifugal elutriation [22].

All of the major types of spermatogenic cells –spermatogonia, spermatocytes, spermatids, and

sperm – have been isolated and subjected to analysis

in order to characterize their proteomes. Some experi-

ments have examined even narrower classes of sper-

matogenic cells, such as those described by Delbes

et al., who performed a proteomic analysis of elon-

gated spermatids [23]. Many of these datasets are pub-

licly available, and provide a valuable resource for

other research groups. The first spermatogenic cells to

appear in the mammalian testis, the spermatogonia,

have, in fact, the least characterized proteome, proba-

bly because of technical difficulties in the isolation of

purified cell populations. Two early studies from the

Pineau laboratory identified 53 and 102 nonredundant

proteins from Staput-isolated rat spermatogonia, with

19 proteins in common between the two datasets

[24,25], and another study performed a proteomic

analysis on isolated spermatogonial stem cells from

adult mice that had been cultured in conditions

designed to maintain stem cell-like behavior; although

the number of proteins identified was limited, the

authors observed minimal differences in the proteomes

of the two cell types, which they hypothesized reflects

their similar developmental competence [26]. In sper-

matocytes, the largest proteomic dataset currently

available was produced by Guo et al. [27], who identi-

fied 3625 unique proteins (3427 unique Entrez genes)

in fluorescence-activated cell sorting-isolated primary

spermatocytes, including almost 400 testis-specific pro-

teins and 172 proteins associated with meiosis. These

included 28 different proteins that had previously been

identified as being essential for completion of male

meiosis, including the prominent synaptonemal com-

plex proteins synaptonemal complex protein (SYCP)1,

SYCP2, and SYCP3. Further analysis revealed a large

number of proteins known to be involved in DNA

repair and transcription, corresponding to the peak in

transcriptional activity that is known to occur in

pachytene spermatocytes. The same group used a simi-

lar approach to identify 2116 spermatid proteins map-

ping to 1924 unique genes, with ~ 300 testis-specific

proteins represented [28]. The spermatid proteome was

found to contain a large number of vesicle-related pro-

teins, reflective of the development of the acrosome in

these cells, and the authors identified a novel protein,

vesicle-associated mmebrane protein 4, that they

linked to this process. As mentioned above, one group

isolated a more specific spermatid population – elon-

gated spermatids – and were able to confidently iden-

tify 632 proteins with two or more unique peptides

[23]. Recently, one highly informative study featured a

quantitative proteomic comparison of isolated mouse

spermatogonia, pachytene spermatocytes, round sper-

matids, and elongating spermatids [6], which identified

2008 different proteins, over half of which belonged to

one of four expression pattern clusters reflecting

important aspects of spermatogenesis, such as mitotic

proliferation, meiosis, and spermiogenesis. Found in

the cluster of proteins with higher expression in hap-

loid spermatogenic cells were protein phosphatases

and kinases, including the testis-specific phosphatase

phosphoprotein phosphatase 1 (PPP1)CC2, which

plays key roles in spermatogenesis. The authors’ com-

parison of proteomic changes and transcriptomic data

further classified genes into five different regulatory

mechanisms, including prominent post-transcriptional

regulation of gene expression in the testis, illustrating

the benefit of considering these types of data side-by-

side. This study provides a wealth of information

regarding mechanisms for regulation of gene expres-

sion during spermatogenesis in general, as well as the

ability to see how many individual genes are regulated.

In addition, this study represents the largest spermato-

gonia proteomic dataset published to date [6]. Consid-

ering all of these studies together, we can see that

different spermatogenic cell types contain different

proteomic complements, reflecting the different biolog-

ical processes involved at different times in germ cell

maturation.

In contrast to immature spermatogenic cells, mature

sperm do not require any specialized isolation proce-

dures, and thus can easily be collected even from

human subjects. As a consequence, there have been

5638 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

significantly more studies of the proteome of mature

sperm than of the proteomes of other spermatogenic

cell types. The largest number of human sperm pro-

teins identified in a single dataset was 1760, published

by Johnson et al. in 2005 [29]; however, the authors

did not make their dataset publicly available. The larg-

est publicly available human sperm proteome datasets

consist of 1056 proteins comprising Triton-X-soluble

and insoluble fractions [30], and 1429 proteins in dis-

sociated head and tail fractions [31]. Similarly, the

same group has published high-quality mature sperm

proteomic datasets for mouse [32] and rat [33] that

represent excellent resources for those researching

spermatogenesis. Subsequent bioinformatic analysis of

these three sperm proteomes revealed considerable

overlap, despite the fact that the sperm proteome has

yet to be fully covered [11]. In other species, one very

large dataset has identified thousands of proteins in

mature bull sperm [34]. However, when high-fertility

and low-fertility groups were compared, only 20%

overlap was observed, a strikingly low number for

such a large dataset. A second examination of this

dataset by Baker and Aitken has shown that a large

number of the identified proteins are represented by

only a single unique peptide, which can lead to a high

incidence of false positives, bringing the total number

of identified proteins into question [11]. Nonetheless,

the dataset can still be a useful resource, provided that

certain caveats are considered during analysis. The

issue of single-peptide identifications is key when

examining proteomic data, and one should always

look deeper into the data before interpreting any pro-

tein identification as absolute.

The utility of proteomic analysis of whole testes or

isolated germ cell populations goes beyond simply cat-

aloging the proteome of the cell types. Proteomic

approaches have also been used to ask specific biologi-

cal questions by an increasing number of groups. For

example, the elongating spermatid proteome investiga-

tion by Delbes et al. described above compared the

proteomic profiles of wild-type and Paip2a/Paip2b

double-knockout mice, and identified 29 differentially

expressed proteins, several of which were subsequently

verified by western blot analysis [23]. As the PAIP2

proteins are important translational repressors in sper-

matogenesis, differential expression of proteins in this

knockout background revealed genes that are regu-

lated post-transcriptionally by this pathway. To exam-

ine the effects of Sertoli cell conditional Dicer1

deletion on protein expression throughout the early

postnatal testis, Papaioannou et al. performed a quan-

titative analysis of 130 testis proteins, and found that

a large proportion (~ 38%) were upregulated [35],

although this study would have been more informative

had the authors compared conditional Sertoli-specific

Dicer null testes, which completely lack germ cells,

owing to Sertoli cell dysfunction, with wild-type testes

from mice treated with busulfan, a germ cell toxin that

eliminates all germ cells except the stem cells; both are

Sertoli cell-only testes, but the former lack Dicer-medi-

ated transcriptional and translational regulation.

Another group used a proteomic analysis of enriched

mouse spermatocytes to test the effect of androgen

deprivation and replacement, and identified 88 differ-

entially regulated proteins, including several with

known roles in meiosis, such as HSPA2 [36]. Compar-

ative proteomics has been used to identify proteins

that are differentially regulated throughout spermato-

genesis by comparing the proteomes of isolated sper-

matogonia, pachytene spermatocytes and early

spermatids via 2D difference in gel electrophoresis.

Subsequently, 123 proteins that were differentially

expressed between the three stages of rat spermatogen-

esis were identified [37], including the protein phospha-

tase PPP1CC2, which is known to be essential for

completion of spermatogenesis in mice [8]. These four

studies are representative examples of how proteomic

analysis of spermatogenic cells has the potential to go

far beyond the generation of ‘protein lists’, to answer

biological questions regarding male fertility.

Subcellular proteomics inspermatogenesis

Despite significant advances in the resolution of prote-

omic technologies, to date no one protein extraction/

identification method can identify all proteins in the

cell, owing to technological limitations, and differences

in dynamic range and solubility. Furthermore, the

presence of a protein in a cell type does not necessarily

tell us much about its function. By breaking the cell

down into its constituent parts (be they fractions,

structural elements, or organelles), better coverage of

the proteome and the subcellular localization of pro-

teins within the spermatogenic cell types can be

obtained, which helps to provide functional insights.

In fact, the sperm are uniquely suited to this form of

analysis. Being arguably the most differentiated cell

type in the body, they contain a number of different

component parts that can be readily isolated and sub-

jected to proteomic analysis.

Several reproductive biology research groups have

taken a subcellular proteomic approach to the study

of spermatogenesis. The bulk of this research has

focused on sperm, because of their relative ease of iso-

lation and unique morphology (see Table 1 for a list

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5639

G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

of studies that have examined subcellular sperm frac-

tions). The sperm surface has been one subcellular

locale of great interest for proteomic analysis, because

of its dynamic nature during epididymal maturation

and capacitation, and its importance to fertilization

[38–43]. Recently, two groups have published studies

that have used different biochemical approaches to iso-

late sperm membrane fractions containing lipid

rafts – dynamic, sterol-enriched and sphingolipid-

enriched microdomains that are believed to play key

roles in regulating sperm function at the membrane.

Asano et al. used a detergent-free approach to isolate

three distinct types of mouse sperm membrane raft, as

well as a ‘nonraft’ membrane fraction [38]. Following

gel-based separation, in-gel trypsin digestion, and

LC-MS/MS analysis, they were able to identify 190

proteins between the three sperm raft subtypes, as well

as a number of additional ‘nonraft’ proteins on the

sperm surface. Nixon et al., conversely, used a mild

detergent-based protocol to isolate proteins from the

detergent-resistant membrane fraction from capaci-

tated human [42] and mouse [41] sperm, which were

then subjected to 2DE and LC-MS/MS analysis. From

this analysis, 124 and 100 proteins, respectively, were

identified. Interestingly, there were more proteins in

common between the two mouse datasets with differ-

ent methodologies (35) than between the human and

mouse datasets (14) that were obtained with the same

mild detergent-based method for detergent-resistant

membrane isolation. This discrepancy is interesting,

but perhaps not surprising, as interspecies proteomic

studies have shown that sperm surface proteins are

subject to more rapid evolutionary change than other

sperm proteins [44]. These studies all identified known

zona pellucida-binding proteins, as well as novel cell

adhesion and signaling molecules that may play impor-

tant roles in sperm function and fertilization. Also, the

comparison of these datasets illustrates that different

strategies for preparation of subcellular fractions pro-

duce different pools of proteins – each with their own

contaminants and losses. Although they may have con-

siderable overlap, these differences must be taken into

account when proteomic data from different sources

are analyzed. Furthermore, datasets such as these do

not account for quantitative differences between

subcellular fractions, or differences in PTMs between

fractions.

In addition to the sperm surface, a number of other

subcellular fractions of sperm have been examined

with proteomic methodologies, such as the acrosomal

matrix, a critical subcellular compartment during fer-

tilization in which > 1000 proteins were identified [45].

This number is surprisingly large, which could indicateTable

1.Recentexamplesofsubcellularproteomic

studiesofsperm

.AKAP4,A-kinaseanchorprotein

4;IZUMO1,Izumosperm

–eggfusion1;MFGE8,milk

fatglobule

epiderm

algrowth

factor8;ODF1,outerdensefiber1;PRM2,protamine2;SPACA1,sperm

acrosome-associated1;TSSK6,testis-specificserinekinase6;ZPBP1,zonapellucida-bindingprotein

1.

Sperm

subcellular

fraction

Species

Protein

separation

method

MS/M

Smethod

Numberof

proteins

identified

Example

protein

andbiological

function

Reference

Membrane

Mouse

1D

SDS/PAGE

LC-M

S/M

S190

MFGE8,fertilization

Asanoetal.[38]

Membrane

Human

2D

SDS/PAGE

LC-M

S/M

S124

ZPBP1,bindingofsperm

tozona

pellucida

Nixonetal.[42]

Membrane

Mouse

2D

SDS/PAGE

MALDI-TOF+

nanoLC-M

S/M

S

100

IZUMO1,fusionofsperm

toegg

plasmamembrane

Nixonetal.[41]

Tail

Human

1D

SDS/PAGE

LC-M

S/M

S1049

ODF1,sperm

atogenesis

Amaraletal.[46]

Tail

Human

1D

SDS/PAGE

LC-M

S/M

S901

AKAP4,sperm

motility

Bakeretal.[31]

Head

Human

1D

SDS/PAGE

LC-M

S/M

S704

TSSK6,sperm

chromatin

condensation

Bakeretal.[31]

Nucleus

Human

1D

SDS/PAGE,

2D

SDS/PAGE

LC-M

S/M

S403

PRM2,DNA

packaging

deMateoetal.[49]

Acrosomal

matrix

Mouse

1D

SDS/PAGE

LC-M

S/M

S1026

SPACA1,acrosomeassembly

Guyonnetetal.[45]

5640 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

a much more complicated subcellular compartment

than initially thought, or conversely, a high degree of

false-positive identification/contamination during frac-

tionation. The sperm tail proteome has been investi-

gated intensively in two recent studies. Amaral et al.

produced the largest dataset, with a total of 1049 pro-

teins identified in the human sperm tail [46], including

a surprisingly high number of peroxisomal proteins,

given that the peroxisome is an organelle that is

thought to be largely absent in mature sperm. Concur-

rently, Baker et al. published a study wherein the head

and tail portions of human sperm were separated, and

each fraction was subjected to proteomic analysis [31].

The resultant dataset identified 900 proteins in the

sperm tail and 700 proteins in the sperm head, with

just 159 proteins being found in both subcellular frac-

tions. This relatively low degree of overlap points to

the specialized nature of the sperm subcellular struc-

tures, each with a specific role in the transmission of

the paternal genome. Almost half (46%) of the sperm

tail proteins identified in the Baker et al. dataset were

also identified by Amaral et al. Although this is clearly

a significant amount of overlap, it is lower than one

might expect, given the size of these datasets in rela-

tion to the hypothesized size of the entire sperm prote-

ome, signifying that a substantial portion of the

proteome has been missed in all of the experiments

conducted to date.

The sperm nucleus is another subcellular structure

of great interest in reproductive biology research [47].

During spermiogenesis, the spermatid nucleus under-

goes dramatic chromatin condensation. This process is

regulated by proteins in and around the nucleus, and

is commonly found to be disrupted by gene deletions,

resulting in male infertility [48]. It is not surprising

that several groups have turned to proteomics to ana-

lyze the nuclear content of sperm. One recent study

isolated human sperm nuclei to 99.9% purity, and, fol-

lowing gel fractionation of the protein content, identi-

fied 403 proteins by LC-MS/MS analysis [49].

Strikingly, more than 50% of the identified proteins

had never been reported in human sperm, despite the

availability of a number of such datasets (see above).

This illustrates one of the benefits of subcellular frac-

tionation prior to proteomic analysis – simplification

of the sample leads to an increased depth of coverage

and, thus, a greater amount of useful data. To look

even closer at the proteins involved in DNA packaging

during spermatogenesis, Govin et al. [50] devised a

strategy to extract proteins with either the potential to

bind DNA (basic proteins) or capable of binding basic

proteins (acidic proteins) from isolated mouse

stage 12–16 spermatid nuclei. This analysis identified

70 proteins, which were putative DNA-packaging pro-

teins and their chaperones in spermatogenesis. Fur-

thermore, this study highlighted a clear link between

proteomics and epigenomics, as the proteins identified

provide a clear link to epigenetic regulation of the

postmeiotic nucleus. A comparison of five different

subcellular human sperm proteomic datasets reveals

that a large number of proteins appear to be unique to

each individual dataset (Fig. 2). This demonstrates the

increased proteome coverage that can be achieved

when individual fractions are analyzed, as well as the

specialized nature of sperm components. However, as

a caveat, some of this interstudy variation could result

from differences in analytical strategies, especially with

regard to LC-MS/MS analysis and peptide database

searching. The amount of this variation that arises

from true proteomic differences in subcellular com-

partments and experimental error remains an open

question that future studies should strive to address.

On the basis of our analysis, only five proteins were

common to all human sperm subcellular fractions

(Table 2; see Tables S1 and S2 for full data on overlap

between datasets, and a list of proteins common to

three or more human sperm datasets). The fact that

these proteins are found in all five subcellular prote-

ome datasets does not necessarily imply that they have

a role in spermatogenesis or sperm function, and they

could simply represent prominent housekeeping genes.

In fact, if a protein is restricted to only one highly

Fig. 2. Overlap in protein identification between subcellular

fractions of human sperm. A Venn diagram is shown, depicting the

number of proteins that are unique and shared between the

datasets from human sperm listed in Table 1. The diagram shows

that a considerable number of proteins appear to be unique to

each fraction, whereas a few proteins are identified in all five

datasets. The Venn diagram was generated with the VIB/UGent

Bioinformatics & Evolutionary Genomics web-based tool available

at http://bioinformatics.psb.ugent.be/webtools/Venn/.

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G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

specialized structure, it may have a specific and essen-

tial role in the structure or function of that structure.

Collectively, these studies account for > 2200 proteins,

approaching the estimated size of the sperm proteome.

It is clear from the examples presented above that

there is a wealth of information to be obtained when

subcellular fractionation is combined with proteomic

analysis. Not only can localization information be

gained, but increased depth of coverage can also be

achieved by simplifying the sample and decreasing the

dynamic range. Despite the progress to date, there are

still other structures and cell types to be analyzed, and

even among those for which datasets exist, much of

the subcellular proteome remains undiscovered. For

example, many male infertility mutations show similar

phenotypes, despite their range of gene ontology func-

tions, often starting at the round spermatid stage,

which is characterized by the evolving development of

the acrosome. These mouse mutations often mimic the

testicular failure phenotypes observed in infertile men.

Proteomic analysis of the developing acrosome would

be a useful addition to the repertoire.

PTMs in spermatogenic cells

Another area of proteomics that has garnered

increased interest over the past several years is the

study of PTMs. Once translated in the cell, proteins

can be covalently modified in a number of different

ways, which can govern the activity of proteins and

signaling networks. Identifying PTMs of testis proteins

provides a more detailed picture of how those proteins

exist in the tissue, and can offer clues regarding their

functions. Also, by characterizing changes in PTM sta-

tus in response to different stimuli or at different time

points in spermatogenesis, we can gain even more

insights into the regulation of a protein’s activity. The

analysis of PTMs is especially relevant in mature

sperm, as they are both transcriptionally and transla-

tionally silent [51], meaning that the bulk of cellular

functions must be governed by post-translational mod-

ulation of protein function.

Regulated by the opposing activity of kinases and

phosphatases, phosphorylation is by far the most stud-

ied PTM in spermatogenesis. Following recent techno-

logical advances in the isolation of phosphorylated

peptides, such as those by Larsen et al. [52], the field

of phosphoproteomics has experienced significant

growth over the past several years. The study of sper-

matogenesis has been no exception to this, as an

increasing number of groups have performed phospho-

proteome analysis in sperm and spermatogenic cells.

However, the largest existing testis phosphoproteomic

datasets were not produced from laboratories focusing

directly on spermatogenesis, but from large-scale stud-

ies aiming to map phosphorylation sites across multi-

ple tissues. One large-scale analysis of nine tissues

from 3-week-old mice identified > 2500 phosphopro-

teins in the testis corresponding to > 10 000 phosphor-

ylation sites, following immobilized metal ion affinity

chromatography (IMAC) phosphopeptide enrichment

[53]. Another phosphoproteomic study utilized tita-

nium dioxide (TiO2) phosphopeptide enrichment on 14

different tissues and organs in the rat, and also identi-

fied > 10 000 phosphorylation sites in the testis,

including over 200 testis-specific phosphorylation sites,

and provided quantitative data by the use of extracted

ion chromatograms [54]. These studies, although not

directly focused on spermatogenesis, have provided a

wealth of data to the research community, and insights

into the post-translational regulation of spermatogene-

sis. As an example, both studies found that the testis

was second only to the brain in the number of tissue-

specific phosphorylation sites (17% of all identified

sites in one experiment [53]), which suggests the possi-

bility that protein phosphorylation may be particularly

important in spermatogenesis and the regulation of

sperm function.

Aside from these large-scale analyses of the mamma-

lian testis, most groups have chosen to focus on sperm

Table 2. Proteins common to five human sperm subcellular proteome datasets. Testis/sperm specificity data were compiled from

www.uniprot.org, and information regarding the existence of infertile mouse models was compiled from http://www.informatics.jax.org.

Official gene

symbol

Uniprot

accession Name

Testis/sperm-

specific?

Infertile

mouse

model?

RAB2A B2R5W8 RAB2A, a member of the RAS

oncogene family

No No

HSPA2 Q9UE78 Heat shock 70-kDa protein 2 No Yes

VCP Q969G7 Valosin-containing protein No No

SPANXB1 Q5JYZ7 SPANX family, member B1 Yes No

LTF Q8IU92 Lactotransferrin No No

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Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

for phosphoproteomic analyses, owing to their ease of

retrieval and transcriptional/translational silent status.

Baker et al. have published two separate examinations

of changes in protein phosphorylation during rat epi-

didymal maturation, using TiO2 phosphopeptide

enrichment, and have identified 53and 22 differentially

phosphorylated proteins [55,56]. Perhaps the most

extensively studied aspect of sperm maturation via

phosphoproteomic analysis is capacitation, which has

been examined in the mouse [57], rat [58], and human

[59]. Interestingly, no common phosphorylation event

was found between species, which points to key meth-

odological differences, as well as the probability that a

large portion of the phosphoproteome remains unex-

amined. This may also reflect evolutionary divergence;

analysis of phosphosites, both predicted and known,

across a range of species may yield insights into those

sites that are biologically relevant (see, for example,

www.phosphonet.ca). Another investigation even per-

formed phosphoproteomic analysis of clinical samples,

comparing sperm from fertile individuals with those

suffering from asthenozoospermia (reduced sperm

motility), and identified 66 differentially phosphory-

lated peptides [60]. In contrast to those groups examin-

ing sperm, our group has focused on the response of

developing spermatogenic cells in the testis to the loss

of the protein phosphatase PPP1CC, and identified 10

proteins that are hyperphosphorylated in response to

this deletion [61]. Presently, we are undertaking a larger

phosphoproteomic analysis of the developing mouse

testis, which has identified > 700 phosphorylated pro-

teins, with the ultimate aim of identifying candidate

substrates of PPP1CC2, the testis-specific isoform

(G. MacLeod, P. Taylor, L. Mastropaolo, S. Varmuza,

in preparation). However, a key challenge in such

experiments is differentiating between changes resulting

from perturbation of direct phosphorylation/dephos-

phorylation events, and indirect effects such as com-

pensatory changes, and or downstream signaling

events.

In addition to the growing number of phosphopro-

teomic studies relating to spermatogenesis and sperm

function, a series of other types of PTM have also

been catalogued (Table 3). Similarly to the aforemen-

tioned phosphoproteomic study, Lundby et al.

recently quantified > 15 000 lysine acetylation sites on

> 4500 proteins across a number of rat tissues,

including almost 2000 proteins in the testis [62].

Lysine acetylation is of particular interest in sper-

matogenesis, owing to its well-characterized involve-

ment in the modification of histones, which have a

central role in spermatogenesis. Protein glycosylation

in the mouse testis has been examined in at least two

large-scale studies, which identified 239 and 634

unique glycoproteins [63,64]. One of these studies

identified four glycoproteins that were dominantly

expressed in the testis over any other tissue – dipepti-

dase 3, zona pellucida 3 receptor, TEX101, and Dick-

kopf-like 1 [63]. Other PTMs that have been studied

in human sperm include S-nitrosylation, by Lefi�evre

et al. (240 modified proteins) [65] and, most recently,

SUMOylation by Vigodner et al. (55 modified pro-

teins) [66]. Another PTM of interest is ubiquitination;

however, to our knowledge, no large-scale analysis of

the ubiquitin-modified proteome has been conducted

in the mouse testis or sperm, and a recently published

survey of several mouse tissues analyzed only liver,

kidney, heart, muscle, and brain [67]. However, the

spermatogenesis defects in mice lacking functional

ubiquitin-conjugating enzyme E2B, a ubiquitin ligase,

is a clear sign that this PTM is critical to germline

development [68].

Table 3. Recent examples of large-scale studies characterizing PTMs in mammalian testes or sperm. Studies listed are only those that

published a complete list of mapped PTMs (i.e. not only those showing significant change). AAL, Aleuria aurantia lectin; ConA,

concanavalin A; RCA120, Ricinis communis agglutinin-120; SPEG, solid-phase extraction of N-linked glycopeptides.

PTM Cell/tissue Species Enrichment method

No. of modified

testis proteins Reference

Phosphorylation Testis Mouse IMAC 2714 Huttlin et al. [53]

Phosphorylation Testis Rat TiO2 3430 Lundby et al. [54]

Phosphorylation Testis Mouse IMAC + TiO2 755 MacLeod, Taylor, Mastropaolo and

Varmuza (unpublished results)

Phosphorylation Sperm Human TiO2 120 Baker et al. [58]

Lysine acetylation Testis Rat Anti-acetyl-lysine immunoprecipitation 1941 Lundby et al. [62]

N-Glycosylation Testis Mouse SPEG 239 Tian et al. [63]

N-Glycosylation Testis Mouse Lectin columns (ConA, RCA120, AAL) 634 Kaji et al. [64]

S-Nitrosylation Sperm Human Biotin-switch assay 240 Lefi�evre et al. [65]

SUMOylation Sperm Human Anti-SUMO immunoprecipitation 55 Vigodner et al. [66]

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G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

It is clear from these studies that the nature of a

protein is not fully determined when it is trans-

lated – PTMs confer an extremely high diversity of

protein forms within a given cell type, a complexity

that must be better understood for deciphering of a

protein’s function. Fortunately, technological improve-

ments in MS instrumentation and protein enrichment

are moving us closer to this goal.

Protein–protein interaction networks(interactomes) in spermatogenesis

Proteins rarely, if ever, function in isolation – it is the

interaction between numerous protein species that

results in functions being performed. Thus, to fully

understand a process as complex as spermatogenesis,

we must look not only at what proteins are present in a

given space and how they are modified, but at which

proteins they interact with – the interactome. By char-

acterizing interactomes, i.e. the full complement of pro-

tein–protein interactions for a given protein, we have a

much better chance of understanding a protein’s func-

tion than if we look at each in isolation. In the past,

the most common approach to studying interactomes

was the yeast two-hybrid assay. Although this

approach has been quite successful in identifying pro-

tein–protein interactions, even with regard to genes

that are important to spermatogenesis (e.g. [69–71]), ithas several prominent limitations, owing to the artifi-

cial nature of the system (e.g. the absence of species/tis-

sue-specific PTMs) and the fact that it looks only at

binary interactions. Currently, the yeast two-hybrid

system has been largely replaced by affinity purifica-

tion/MS (AP-MS)-based approaches, featuring either

single or tandem affinity purification (TAP) tags. Other

commonly employed techniques for uncovering

protein–protein interactions, such as coimmunoprecipi-

tation, size-exclusion chromatography, and immunohis-

tochemistry, have been successfully used in the testis;

however, they are less amenable to large-scale and

high-throughput analysis than AP-MS. These

approaches are typically applied to mammalian tissue

culture systems, and can simultaneously identify a large

number of protein–protein interactions, including mul-

tiprotein complexes. AP-MS, when applied with the

appropriate controls, also results in the identification

of fewer false-positive interactions. Additionally, the

use of a mammalian system is, for obvious reasons,

preferable to the use of a yeast-based system (see [72]

for an overview of such systems). Although tissue cul-

ture-based AP-MS systems have been used with some

success to examine the interactomes of proteins

involved in spermatogenesis [73], they still suffer limita-

tions, owing to their artificial nature. This limitation is

particularly important in the study of spermatogenesis.

As outlined in the preceding sections, the testis is

particularly abundant in tissue-specific protein expres-

sion as well as PTMs, and the complex architecture of

the testis cannot be modeled in culture. Thus, if the in-

teractome of a protein involved in spermatogenesis is

defined by the use tissue culture, it is likely that a large

amount of information will be missed. For this reason,

it is important to conduct interactome studies directly

in the testis when possible. This prospect is signifi-

cantly more demanding than tissue culture-based

approaches, because of the need to have either highly

specific antibodies or the ability to generate a trans-

genic line with an affinity-tagged version of the gene

of interest. Despite these technological demands, a

number of groups have successfully performed interac-

tome studies in the testis. In 2009, Chen et al. used

immunoprecipitation followed by gel-free LC-MS/MS

to characterize the interactomes of MIWI and MILI in

the mouse testis [74]. The authors then went on to per-

form a reciprocal experiment using one of their identi-

fied interaction partners, TDRKH, and characterized a

multiprotein interaction network in the testis. Simi-

larly, another experiment used a modified immunopre-

cipitation and MS approach to identify an additional

member of the CATSPER complex in the mouse testis

[75]. The authors of this study had undertaken this

approach because of their inability to successfully

express the CATSPER complex in any other system,

which underscores the importance of examining pro-

tein interactions in their natural environment. Other

groups have generated transgenic mouse lines in order

to perform TAP directly in the testis. To identify novel

interactors involved in Bardet–Biedl syndrome, a com-

mon feature of which is male infertility, Seo et al. gen-

erated a mouse line expressing a green fluorescent

protein-coupled and S-tag-coupled Bardet–Biedl syn-

drome 4 construct, and performed TAP in transgenic

testes, successfully identifying a novel protein complex

member [76]. Another TAP experiment in the testis

using a mouse expressing TAP-tagged 14-3-3f identi-

fied a large number of novel protein–protein interac-

tions, although the lack of appropriate control

experiments leaves the total number of true interactors

in question [77].

The generation of transgenic mouse lines expressing

affinity-tagged genes is not a trivial process, and

requires a significant amount of time for design and

production. For this reason, systems have been devel-

oped to aid in the production of affinity-tagged trans-

genic lines in a more efficient manner. For example,

the Floxin vector system can be used to derive knock-

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Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

in embryonic stem cell lines from gene-trap lines in

just a few relatively basic steps [78]. This system has

the added benefit of allowing for the introduction of

the transgene into the endogenous locus to minimize

any overexpression/mis-expression-related artefacts.

Our laboratory has used the Floxin vector backbone

to generate a streptavidin-binding peptide–3 9 FLAG

tandem affinity tagged knock-in vector that can be

used to produce N-terminally tagged knock-ins of any

gene [73]. This system was used to create an embryonic

stem cell line expressing streptavidin-binding peptide–3 9 FLAG–PPP1CC2, which was used to identify a

novel interacting protein, dolichyl-diphosphooligosac-

charide–protein glycosyltransferase, with a proposed

role in spermatogenesis. However, this system has not

yet been used to successfully generate a transgenic

mouse for interactome studies. Although culture-based

AP-MS strategies remain a powerful tool for interac-

tome discovery, the full power of such approaches can

only be harnessed when they are used in a more bio-

logically relevant context. With technological advances

in the generation of transgenic animals and AP-MS

methodologies, such approaches will probably become

more common in the coming years.

The utilization of proteomics inclinical studies of male infertility

The ultimate aim in furthering our understanding of

spermatogenesis is to improve the ability to diagnose

and treat male infertility. In recent years, a number of

investigators have applied proteomic analysis to clini-

cal samples in an effort to go beyond basic research.

By analyzing the genital tract proteomes of infertile

men, it may be possible to detect aberrations that

explain impairments and evaluate the feasibility and

course of future treatment. Although it is difficult to

obtain a sufficient amount of starting material from

spermatogenic cells in the testes of infertile men, ejacu-

lated sperm and seminal fluid are much easier to

obtain, and have thus been the subject of the bulk of

the studies to date.

The proteome of sperm from infertile donors has

been examined by a number of groups, to date primar-

ily by 2DE followed by identification of differentially

expressed protein spots via MS. Experiments have

identified proteins that are differentially expressed in

patients showing generalized infertility [49,79], low

sperm count and motility [80], asthenozoospermia [81–83], Sertoli cell-only syndrome [84], in vitro fertilization

failure [85], diabetes, and obesity [86]. Collectively,

these studies have been able to identify a large number

of candidate biomarkers for sperm defects that could

be clinically relevant in the coming years. However,

these types of study have had limited impact at the

clinical level, in part because of the heterogeneity of

the disease paradigms, and because of the difficulty in

parsing datasets from tissues that are catastrophically

different from controls.

The seminal plasma provides a protective and facili-

tative environment for sperm transit that is critical in

a number of ways for proper sperm function. There-

fore, a number of clinical studies have applied proteo-

mic analysis in the hopes of finding useful biomarkers

for defects of the male reproductive system. According

to Batruch et al. [87], the seminal plasma is an excel-

lent fluid for clinical research, given its ease of collec-

tion and the fact that it contains secreted and shed

proteins originating from several different tissues,

which can offer clues to the origin of clinical defects.

Many mouse mutations resulting in testicular failure

are characterized by the exfoliation of immature germ

cells into the seminiferous lumen, which would then

contribute breakdown products to the seminal fluid as

they transit the epididymis. The same feature can be

seen in infertile men whose ejaculate contains imma-

ture germ cells, which are sometimes used for intracy-

toplasmic sperm injection in the treatment of male

factor infertility. Although examinations of seminal

plasma proteins have been performed for decades, in

recent years the characterization of the fluid has

reached new heights, owing to the increased use of

LC-MS/MS technologies, leading to the identification

of ~ 3000 seminal plasma proteins. In 2006, Pilch and

Mann, using Fourier transform MS, identified > 900

proteins in seminal plasma from a single individual,

representing, at the time, the largest catalog of pro-

teins in that fluid [88]. Since then, a number of groups

have used proteomic approaches to identify novel bio-

markers for male infertility [87,89–93]. One investiga-

tion, by Wang et al., utilized one-dimensional SDS/

PAGE followed by LC-MS/MS to identify 741 seminal

plasma proteins from normal fertile donors and those

suffering from asthenozoospermia, including 101 that

were differentially expressed between the two groups

[93]. The most comprehensive proteomic analyses of

the seminal plasma published to date are represented

by a series of papers from Jarvi and colleagues, which

include label-free quantitative analysis [87,89,91,94].

Collectively, among five published accounts, > 2500

seminal plasma proteins have been identified in sam-

ples from fertile donors, postvasectomy patients, and

those suffering from nonobstructive azoospermia and

prostatitis. From these studies, a large number of

potential biomarkers have been identified, including

those useful in discrimination between obstructive and

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G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

nonobstructive azoospermia, which provide a noninva-

sive diagnostic alternative to the current practices of

testis biopsy and histology. Another study incorpo-

rated gene expression data from publicly available

databases alongside seminal plasma proteomic data to

identify biomarkers for pathologies of the male genetic

tract [95]. Similar proteomic approaches are being con-

templated for the diagnosis of other male reproductive

tract disorders and diseases, such as prostate cancer.

The flip side to these clinical needs is the development

of a nonsteroidogenic male contraceptive; one promis-

ing compound interferes reversibly with the action of

the testis-specific chromatin regulator BRDT to

temporarily interrupt spermatogenesis [47].

One factor that requires further investigation in clin-

ical studies such as those mentioned above is the

extent of interindividual variability in the proteomic

content of sperm and/or seminal plasma. One study by

Milardi et al., which examined the seminal plasma

proteomes of five different fertile men, found only 83

proteins in common between all individuals in a study

that identified between 919 and 1487 proteins per sam-

ple [92]. This number seems surprisingly low, and per-

haps points to interexperiment variability as much as

interindividual variability. The fact remains, however,

that until we better understand what ‘normal’ varia-

tion in proteomic content constitutes, it will be difficult

to identify a full complement of phenotype-related

abnormalities. Despite this limitation, the routine use

of proteomic analysis in a clinical setting may be prac-

tical in the near future. Alternatively, experiments such

as those listed above can be used as discovery tools to

produce smaller biomarker panels that are simpler to

use and interpret, less expensive, and thus easier

to institute in a clinical setting [94].

Emerging proteomic applications andthe study of spermatogenesis

In the preceding sections, future applications of sper-

matogenesis research have been highlighted for differ-

ent proteomic subdisciplines. If information from all

of these types of studies are considered together, a

great deal can be learned about a protein’s function in

spermatogenesis. As currently existing technologies

improve and new ones emerge, their application to the

study of spermatogenesis will follow. Other methods,

such as antibody microarrays, have the potential to

generate useful information when applied to the study

of spermatogenesis, although this approach has yet to

gain purchase in the field (see, for example, [96]).

One emerging proteomic technology that will probably

be beneficial to the study of spermatogenesis consti-

tutes the interface between imaging and proteo-

mics – MALDI imaging MS. This technique allows

for the identification and detection of proteins directly

in tissue slices which offers a wealth of spatiotemporal

information. This technique has been applied to both

the rat testis [97] and the mouse epididymis [98], in

both cases allowing the mapping of a number of dif-

ferent proteins throughout those tissues. Despite a

high amount of promise, this technique has been held

back by a series of technological hurdles; once these

have been resolved, this technique could become an

extremely powerful new tool.

Technological advances in label-free quantitative

proteomics, such as selective reaction monitoring,

multiple reaction monitoring, and MS1 filtering, could

possibly constitute the most important development

in the proteomic study of spermatogenesis in the near

future. These technologies give researchers the ability

not only to determine which proteins are present, but

also to accurately quantitate them in a variety of bio-

logical contexts at a resolution far exceeding that

obtained with spectral counting-based approaches.

Furthermore, label-free quantitative approaches are

more amenable for use on tissue samples than label-

ing strategies such as stable isotope labeling with

amino acids in cell culture, and thus may find more

widespread use in reproductive biology research. The

development of cross-platform, open-source software

packages such as SKYLINE for label-free quantitative

analysis should allow more researchers to have access

to these quantitative proteomic methods, as well as

allow for increased comparison of results across mul-

tiple laboratories [99]. In fact, our laboratory has

recently used this software in a quantitative phospho-

proteomic study of the mouse testis (G. MacLeod,

P. Taylor, L. Mastropaolo, S. Varmuza, in prepara-

tion). Quantitative proteomics should allow for more

accurate assessment of sperm and seminal plasma sam-

ples in cases of male infertility as well; either in global

proteomic analysis of these samples to identify quanti-

tative changes, or, perhaps more likely, to validate

potential biomarkers identified in larger studies. For

example, Drabovich et al. [94] used selective reaction

monitoring with labeled internal standards to reanalyze

20 candidate biomarkers that discriminate between

fertile, postvasectomy and nonobstructive azoospermia

patients. These approaches could facilitate pilot studies

to identify more specific subsets of proteins that could

then be quantitated on larger samples with less

expensive technologies such as ELISA.

As the technologies discussed in this article continue

to improve, data are being generated at an increasing

rate. Thus, a pressing issue in the future of proteomics

5646 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

is how to integrate the data from a variety of sources,

including genetic studies. A need exists for improved

methods for turning ‘protein lists’ into testable hypoth-

eses. Also, questions of the accuracy of much of the

data in existing proteomic databases have been raised;

a particularly contentious issue is the field of PTM site

assignment. However, despite these questions, it is

clear that the use of proteomic technologies to study

biological processes such as spermatogenesis and

sperm function is becoming more and more prevalent

and powerful. The field of reproductive biology as a

whole will benefit from this, and, as our understanding

of these processes improves, our ability to diagnose

and treat male infertility will be greatly enhanced.

References

1 Matzuk MM & Lamb DJ (2008) The biology of

infertility: research advances and clinical challenges.

Nat Med 14, 1197–1213.

2 Schultz N, Hamra FK & Garbers DL (2003) A

multitude of genes expressed solely in meiotic or

postmeiotic spermatogenic cells offers a myriad of

contraceptive targets. Proc Natl Acad Sci USA 100,

12201–12206.

3 Massart A, Lissens W, Tournaye H & Stouffs K (2012)

Genetic causes of spermatogenic failure. Asian J Androl

14, 40–48.

4 Carrell DT & Aston KI (2011) The search for SNPs,

CNVs, and epigenetic variants associated with the

complex disease of male infertility. Syst Biol Reprod

Med 57, 17–26.

5 Cagney G, Park S, Chung C, Tong B, O’Dushlaine C,

Shields DC & Emili A (2005) Human tissue profiling

with multidimensional protein identification technology.

J Proteome Res 4, 1757–1767.

6 Gan H, Cai T, Lin X, Wu Y, Wang X, Yang F & Han

C (2013) Integrative proteomic and transcriptomic

analyses reveal multiple post-transcriptional regulatory

mechanisms of mouse spermatogenesis. Mol Cell

Proteomics. 12, 1144–1157.

7 Yeo G, Holste D, Kreiman G & Burge C (2004)

Variation in alternative splicing across human tissues.

Genome Biol 5, R74.

8 Varmuza S, Jurisicova A, Okano K, Hudson J,

Boekelheide K & Shipp EB (1999) Spermiogenesis is

impaired in mice bearing a targeted mutation in the

protein phosphatase 1cc gene. Dev Biol 205, 98–110.

9 Bonilla E & Xu EY (2008) Identification and

characterization of novel mammalian spermatogenic

genes conserved from fly to human. Mol Hum Reprod

14, 137–142.

10 Dean MD, Clark NL, Findlay GD, Karn RC, Yi X,

Swanson WJ, MacCoss MJ & Nachman MW (2009)

Proteomics and comparative genomic investigations

reveal heterogeneity in evolutionary rate of male

reproductive proteins in mice (Mus domesticus). Mol

Biol Evol 26, 1733–1743.

11 Baker MA & Aitken RJ (2009) Proteomic insights into

spermatozoa: critiques, comments and concerns. Expert

Rev Proteomics 6, 691–705.

12 Wilhelm D, Huang E, Svingen T, Stanfield S, Dinnis D

& Koopman P (2006) Comparative proteomic analysis

to study molecular events during gonad development in

mice. Genesis 44, 168–176.

13 Zhu Y, Cui Y, Guo X, Wang L, Bi Y, Hu Y, Zhao X,

Liu Q, Huo R, Lin M et al. (2006) Proteomic analysis

of the effect of hyperthermia on spermatogenesis in

adult male mice. J Proteome Res 5, 2217–2225.

14 Guo X, Zhang P, Huo R, Zhou Z & Sha J (2008)

Analysis of the human testis proteome by mass

spectrometry and bioinformatics. Proteomics Clin Appl

2, 1651–1657.

15 Guo X, Zhao C, Wang F, Zhu Y, Cui Y, Zhou Z, Huo

R & Sha J (2010) Investigation of human testis protein

heterogeneity using 2-dimensional electrophoresis. J

Androl 31, 419–429.

16 Li J, Liu F, Liu X, Liu J, Zhu P, Wan F, Jin S, Wang

W, Li N, Liu J et al. (2011) Mapping of the human

testicular proteome and its relationship with that of the

epididymis and spermatozoa. Mol Cell Proteomics 10,

M110.004630.

17 Geiger T, Wehner A, Schaab C, Cox J & Mann M

(2012) Comparative proteomic analysis of eleven

common cell lines reveals ubiquitous but varying

expression of most proteins. Mol Cell Proteomics 11,

M111.014050.

18 Huang S, Lin J, Teng S, Sun HS, Chen Y, Chen H,

Liao J, Chung M, Chen M, Chuang C et al. (2011)

Differential expression of porcine testis proteins during

postnatal development. Anim Reprod Sci 123, 221–233.

19 Huang X, Guo X, Shen J, Wang Y, Chen L, Xie J,

Wang N, Wang F, Zhao C, Huo R et al. (2008)

Construction of a proteome profile and functional

analysis of the proteins involved in the initiation of

mouse spermatogenesis. J Proteome Res 7, 3435–3446.

20 Clausen OPF, Purvis K & Hansson V (1977)

Application of micro-flow fluorometry to studies of

meiosis in the male rat. Biol Reprod 17, 555–560.

21 Lam DMK, Furrer R & Bruce WR (1970) The

separation, physical characterization and differentiation

kinetics of spermatogonial cells of the mouse. Proc Natl

Acad Sci USA 65, 192–199.

22 Grabske RJ, Lake S, Gledhill BL & Meistrich ML

(1975) Centrifugal elutriation: separation of

spermatogenic cells on the basis of sedimentation

velocity. J Cell Physiol 86, 177–189.

23 Delbes G, Yanagiya A, Sonenberg N & Robaire B

(2011) PABP interacting protein 2A (PAIP2A) regulates

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5647

G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

specific key proteins during spermiogenesis in the

mouse. Biol Reprod 86,95: 1–8.

24 Guillaume E, Dupaix A, Moertz E, Courtens J, J�egou

B & Pineau C (2000) Proteome analysis of

spermatogonia: identification of a first set of 53

proteins. Proteome 1, 1–20.

25 Com E, Evrard B, Roepstorff P, Aubry F & Pineau C

(2003) New insights into the rat spermatogonial

proteome. Mol Cell Proteomics 2, 248–261.

26 Dihazi H, Dihazi GH, Nolte J, Meyer S, Jahn O,

M€uller GA & Engel W (2009) Multipotent adult

germline stem cells and embryonic stem cells:

comparative proteomic approach. J Proteome Res 8,

5497–5510.

27 Guo X, Zhang P, Qi Y, Chen W, Chen X, Zhou Z &

Sha J (2011) Proteomic analysis of male 4C germ cell

proteins involved in mouse meiosis. Proteomics 11,

298–308.

28 Guo X, Shen J, Xia Z, Zhang R, Zhang P, Zhao C,

Xing J, Chen L, Chen W, Lin M et al. (2010)

Proteomic analysis of proteins involved in

spermiogenesis in mouse. J Proteome Res 9, 1246–1256.

29 Johnston DS, Wooters J, Kopf GS, Qiu Y & Roberts

KP (2005) Analysis of the human sperm proteome.

Ann N Y Acad Sci 1061, 190–202.

30 Baker MA, Reeves G, Hetherington L, M€uller J, Baur I

& Aitken RJ (2007) Identification of gene products

present in Triton X-100 soluble and insoluble fractions

of human spermatozoa lysates using LC-MS/MS

analysis. Proteomics Clin Appl 1, 524–532.

31 Baker MA, Naumovski N, Hetherington L, Weinberg

A, Velkov T & Aitken RJ (2013) Head and flagella

sub-compartmental proteomic analysis of human

spermatozoa. Proteomics 13, 61–74.

32 Baker MA, Hetherington L, Reeves GM & Aitken RJ

(2008) The mouse sperm proteome characterized via

IPG strip prefractionation and LC-MS/MS

identification. Proteomics 8, 1720–1730.

33 Baker MA, Hetherington L, Reeves G, M€uller J &

Aitken RJ (2008) The rat sperm proteome characterized

via IPG strip prefractionation and LC-MS/MS

identification. Proteomics 8, 2312–2321.

34 Peddinti D, Nanduri B, Kaya A, Feugang J, Burgess S

& Memili E (2008) Comprehensive proteomic analysis

of bovine spermatozoa of varying fertility rates and

identification of biomarkers associated with fertility.

BMC Syst Biol 2, 19.

35 Papaioannou MD, Lagarrigue M, Vejnar CE, Rolland

AD, K€uhne F, Aubry F, Schaad O, Fort A, Descombes

P, Neerman-Arbez M et al. (2011) Loss of dicer in

Sertoli cells has a major impact on the testicular

proteome of mice. Mol Cell Proteomics 10, M900587–

MCP200.

36 Stanton PG, Sluka P, Foo CFH, Stephens AN, Smith

AI, McLachlan RI & O’Donnell L (2012) Proteomic

changes in rat spermatogenesis in response to in vivo

androgen manipulation; impact on meiotic cells. PLoS

One 7, e41718.

37 Rolland AD, Evrard B, Guitton N, Lavigne R, Calvel

P, Couvet M, J�egou B & Pineau C (2007) Two-

dimensional fluorescence difference gel electrophoresis

analysis of spermatogenesis in the rat. J Proteome Res

6, 683–697.

38 Asano A, Nelson JL, Zhang S & Travis AJ (2010)

Characterization of the proteomes associating with

three distinct membrane raft sub-types in murine sperm.

Proteomics 10, 3494–3505.

39 Belleannee C, Belghazi M, Labas V, Teixeira-Gomes A,

Gatti JL, Dacheux J & Dacheux F (2011) Purification

and identification of sperm surface proteins and

changes during epididymal maturation. Proteomics 11,

1952–1964.

40 Byrne K, Leahy T, McCulloch R, Colgrave ML &

Holland MK (2012) Comprehensive mapping of the

bull sperm surface proteome. Proteomics 12, 3559–3579.

41 Nixon B, Bielanowicz A, Mclaughlin EA, Tanphaichitr

N, Ensslin MA & Aitken RJ (2009) Composition and

significance of detergent resistant membranes in mouse

spermatozoa. J Cell Physiol 218, 122–134.

42 Nixon B, Mitchell LA, Anderson AL, Mclaughlin EA,

O’Bryan MK & Aitken RJ (2011) Proteomic and

functional analysis of human sperm detergent resistant

membranes. J Cell Physiol 226, 2651–2665.

43 Gu B, Zhang J, Wu Y, Zhang X, Tan Z, Lin Y,

Huang X, Chen L, Yao K & Zhang M (2011)

Proteomic analyses reveal common promiscuous

patterns of cell surface proteins on human embryonic

stem cells and sperms. PLoS One 6, e19386.

44 Dorus S, Wasbrough ER, Basby J, Wilkin EC & Karr

TL (2010) Sperm proteomics reveals intensified

selection on mouse sperm membrane and acrosome

genes. Mol Biol Evol 27, 1235–1246.

45 Guyonnet B, Zabet-Moghaddam M, SanFrancisco S &

Cornwall GA (2012) Isolation and proteomic

characterization of the mouse sperm acrosomal matrix.

Mol Cell Proteomics 11, 758–774.

46 Amaral A, Castillo J, Estanyol JM, Ballesca JL,

Ramalho-Santos J & Oliva R (2012) Human sperm tail

proteome suggests new endogenous metabolic

pathways. Mol Cell Proteomics 12, 330–342.

47 Matzuk MM, McKeown MR, Filippakopoulos P, Li Q,

Agno JE, Lemieux ME, Picaud S, Yu RN, Qi J, Knapp

S et al. (2012) Small-molecule inhibition of BRDT for

male contraception. Cell 150, 673–684.

48 Yan W (2009) Male infertility caused by spermiogenic

defects: lessons from gene knockouts. Mol Cell

Endocrinol 306, 24–32.

49 de Mateo S, Castillo J, Estanyol JM, Ballesc�a JL &

Oliva R (2011) Proteomic characterization of the

human sperm nucleus. Proteomics 11, 2714–2726.

5648 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

50 Govin J, Gaucher J, Ferro M, Debernardi A, Garin J,

Khochbin S & Rousseaux S (2012) Proteomic strategy

for the identification of critical actors in reorganization

of the post-meiotic male genome. Mol Hum Reprod 18,

1–13.

51 Boerke A, Dieleman SJ & Gadella BM (2007) A

possible role for sperm RNA in early embryo

development. Theriogenology 68 (Suppl 1), S147–S155.

52 Larsen MR, Thingholm TE, Jensen ON, Roepstorff P

& Jørgensen TJD (2005) Highly selective enrichment of

phosphorylated peptides from peptide mixtures using

titanium dioxide microcolumns. Mol Cell Proteomics 4,

873–886.

53 Huttlin EL, Jedrychowski MP, Elias JE, Goswami T,

Rad R, Beausoleil SA, Vill�en J, Haas W, Sowa ME &

Gygi SP (2010) A tissue-specific atlas of mouse protein

phosphorylation and expression. Cell 143, 1174–1189.

54 Lundby A, Secher A, Lage K, Nordsborg NB,

Dmytriyev A, Lundby C & Olsen JV (2012) Quantitative

maps of protein phosphorylation sites across 14 different

rat organs and tissues. Nat Commun 3, 876.

55 Baker MA, Smith ND, Hetherington L, Pelzing M,

Condina MR & Aitken RJ (2011) Use of titanium

dioxide to find phosphopeptide and total protein

changes during epididymal sperm maturation.

J Proteome Res 10, 1004–1017.

56 Baker MA, Hetherington L, Weinburg A, Naumovski

N, Velkov T, Pelzing M, Dolman S, Condina MR &

Aitken RJ (2012) Analysis of phosphopeptide changes

as spermatozoa acquire functional competence in the

epididymis demonstrates changes in the post-

translational modification of Izumo1. J Proteome Res

11, 5252–5264.

57 Platt MD, Salicioni AM, Hunt DF & Visconti PE

(2009) Use of differential isotopic labeling and mass

spectrometry to analyze capacitation-associated changes

in the phosphorylation status of mouse sperm proteins.

J Proteome Res 8, 1431–1440.

58 Baker MA, Smith ND, Hetherington L, Taubman K,

Graham ME, Robinson PJ & Aitken RJ (2010) Label-

free quantitation of phosphopeptide changes during rat

sperm capacitation. J Proteome Res 9, 718–729.

59 Ficarro S, Chertihin O, Westbrook VA, White F, Jayes

F, Kalab P, Marto JA, Shabanowitz J, Herr JC, Hunt

DF et al. (2003) Phosphoproteome analysis of

capacitated human sperm. J Biol Chem 278,

11579–11589.

60 Parte PP, Rao P, Redij S, Lobo V, D’Souza SJ,

Gajbhiye R & Kulkarni V (2012) Sperm

phosphoproteome profiling by ultra performance liquid

chromatography followed by data independent analysis

(LC–MSE) reveals altered proteomic signatures in

asthenozoospermia. J Proteomics 75, 5861–5871.

61 Henderson H, MacLeod G, Hrabchak C & Varmuza S

(2011) New candidate targets of protein phosphatase-

1c-gamma-2 in mouse testis revealed by a differential

phosphoproteome analysis. Int J Androl 34, 339–351.

62 Lundby A, Lage K, Weinert B, Bekker-Jensen D,

Secher A, Skovgaard T, Kelstrup C, Dmytriyev A,

Choudhary C, Lundby C et al. (2012) Proteomic

analysis of lysine acetylation sites in rat tissues reveals

organ specificity and subcellular patterns. Cell Rep 2,

419–431.

63 Tian Y, Kelly-Spratt KS, Kemp CJ & Zhang H (2010)

Mapping tissue-specific expression of extracellular

proteins using systematic glycoproteomic analysis of

different mouse tissues. J Proteome Res 9, 5837–5847.

64 Kaji H, Shikanai T, Sasaki-Sawa A, Wen H, Fujita M,

Suzuki Y, Sugahara D, Sawaki H, Yamauchi Y,

Shinkawa T et al. (2012) Large-scale identification of

N-glycosylated proteins of mouse tissues and

construction of a glycoprotein database, GlycoProtDB.

J Proteome Res 11, 4553–4566.

65 Lefi�evre LL, Chen Y, Conner SJ, Scott JL, Publicover

SJ, Ford WCL & Barratt CLR (2007) Human

spermatozoa contain multiple targets for protein

S-nitrosylation: an alternative mechanism of the

modulation of sperm function by nitric oxide?

Proteomics 7, 3066–3084.

66 Vigodner M, Shrivastava V, Gutstein LE, Schneider J,

Nieves E, Goldstein M, Feliciano M & CallawayM (2013)

Localization and identification of sumoylated proteins in

human sperm: excessive sumoylation is a marker of

defective spermatozoa.Hum Reprod 28, 210–223.

67 Wagner SA, Beli P, Weiner BT, Sch€olz C, Kelstrup

CD, Young C, Nielsen ML, Olsen JV & Choudhary C

(2012) Proteomic analyses reveal divergent

ubiquitylation site patterns in murine tissues. Mol Cell

Proteomics 11, 1578–1585.

68 Baarends WM, Wassenaar E, Hoogerbrugge JW,

van Cappellen G, Roest HP, Vreeburg J, Ooms M,

Hoeijmakers JH & Grootegoed JA (2003) Loss of

HR6B ubiquitin-conjugating activity results in damaged

synaptonemal complex structure and increased

crossing-over frequency during the male meiotic

prophase. Mol Cell Biol 23, 1151–1162.

69 Fardilha M, Esteves SLC, Korrodi-Greg�orio L, Vint�em

AP, Domingues SC, Rebelo S, Morrice N, Cohen

PTW, da Cruz e Silva OA & da Cruz e Silva EF (2011)

Identification of the human testis protein phosphatase 1

interactome. Biochem Pharmacol 82, 1403–1415.

70 Hrabchak C & Varmuza S (2004) Identification of the

spermatogenic zip protein Spz1 as a putative protein

phosphatase-1 (PP1) regulatory protein that specifically

binds the PP1cgamma2 splice variant in the mouse

testis. J Biol Chem 279, 37079–37086.

71 Hrabchak C, Henderson H & Varmuza S (2007) A

testis specific isoform of endophilin B1, endophilin B1t,

interacts specifically with protein phosphatase-

1cgamma2 in mouse testis and is abnormally expressed

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5649

G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis

in PP1cgamma null mice. Biochemistry (NY) 46,

4635–4644.

72 Dunham WH, Mullin M & Gingras AC (2012) Affinity-

purification coupled to mass spectrometry: basic

principles and strategies. Proteomics 12, 1576–1590.

73 MacLeod G & Varmuza S (2012) Tandem affinity

purification in transgenic mouse embryonic stem cells

identifies DDOST as a novel PPP1CC2 interacting

protein. Biochemistry 51, 9678–9688.

74 Chen C, Jin J, James DA, Adams-Cioaba MA, Park

JG, Guo Y, Tenaglia E, Xu C, Gish G, Min J et al.

(2009) Mouse Piwi interactome identifies binding

mechanism of Tdrkh Tudor domain to arginine

methylated Miwi. Proc Natl Acad Sci USA 106,

20336–20341.

75 Chung J, Navarro B, Krapivinsky G, Krapivinsky L &

Clapham DE (2011) A novel gene required for male

fertility and functional CATSPER channel formation in

spermatozoa. Nat Commun 2, 153.

76 Seo S, Zhang Q, Bugge K, Breslow DK, Searby CC,

Nachury MV & Sheffield VC (2011) A novel protein

LZTFL1 regulates ciliary trafficking of the BBSome

and Smoothened. PLoS Genet 7, e1002358.

77 Puri P, Acker-Palmer A, Stahler R, Chen Y, Kline D &

Vijayaraghavan S (2011) Identification of testis 14-3-3

binding proteins by tandem affinity purification.

Spermatogenesis 1, 354–365.

78 Singla V, Hunkapiller J, Santos N, Seol AD, Norman

AR, Wakenight P, Skarnes WC & Reiter JF (2010)

Floxin, a resource for genetically engineering mouse

ESCs. Nat Methods 7, 50–52.

79 Xu W, Hu H, Wang Z, Chen X, Yang F, Zhu Z,

Fang P, Dai J, Wang L, Shi H et al. (2012)

Proteomic characteristics of spermatozoa in

normozoospermic patients with infertility.

J Proteomics 75, 5426–5436.

80 Thacker S, Yadav SP, Sharma RK, Kashou A, Willard

B, Zhang D & Agarwal A (2011) Evaluation of sperm

proteins in infertile men: a proteomic approach. Fertil

Steril 95, 2745–2748.

81 Zhao C, Huo R, Wang F, Lin M, Zhou Z & Sha J

(2007) Identification of several proteins involved in

regulation of sperm motility by proteomic analysis.

Fertil Steril 87, 436–438.

82 Siva AB, Kameshwari DB, Singh V, Pavani K,

Sundaram CS, Rangaraj N, Deenadayal M & Shivaji S

(2010) Proteomics-based study on asthenozoospermia:

differential expression of proteasome alpha complex.

Mol Hum Reprod 16, 452–462.

83 Mart�ınez-Heredia J, de Mateo S, Vidal-Taboada JM,

Ballesc�a JL & Oliva R (2008) Identification of

proteomic differences in asthenozoospermic sperm

samples. Hum Reprod 23, 783–791.

84 Li J, Guo W, Li F, He J, Yu Q, Wu X, Li J & Mao X

(2012) HnRNPL as a key factor in spermatogenesis:

lesson from functional proteomic studies of

azoospermia patients with sertoli cell only syndrome.

J Proteomics 75, 2879–2891.

85 Pixton KL, Deeks ED, Flesch FM, Moseley FLC,

Bj€orndahl L, Ashton PR, Barratt CLR & Brewis IA

(2004) Sperm proteome mapping of a patient who

experienced failed fertilization at IVF reveals altered

expression of at least 20 proteins compared with fertile

donors: case report. Hum Reprod 19, 1438–1447.

86 Kriegel TM, Heidenreich F, Kettner K, Pursche T,

Hoflack B, Grunewald S, Poenicke K, Glander H &

Paasch U (2009) Identification of diabetes- and obesity-

associated proteomic changes in human spermatozoa by

difference gel electrophoresis. Reprod Biomed Online 19,

660–670.

87 Batruch I, Lecker I, Kagedan D, Smith CR, Mullen BJ,

Grober E, Lo KC, Diamandis EP & Jarvi KA (2011)

Proteomic analysis of seminal plasma from normal

volunteers and post-vasectomy patients identifies over

2000 proteins and candidate biomarkers of the

urogenital system. J Proteome Res 10, 941–953.

88 Pilch B & Mann M (2006) Large-scale and high-

confidence proteomic analysis of human seminal

plasma. Genome Biol 7, R40.

89 Batruch I, Smith CR, Mullen BJ, Grober E, Lo KC,

Diamandis EP & Jarvi KA (2012) Analysis of seminal

plasma from patients with non-obstructive azoospermia

and identification of candidate biomarkers of male

infertility. J Proteome Res 11, 1503–1511.

90 Davalieva K, Kiprijanovska S, Noveski P, Plaseski T,

Kocevska B, Broussard C & Plaseska-Karanfilska D

(2012) Proteomic analysis of seminal plasma in men

with different spermatogenic impairment. Andrologia

44, 256–264.

91 Kagedan D, Lecker I, Batruch I, Smith C, Kaploun I,

Lo K, Grober E, Diamandis E & Jarvi K (2012)

Characterization of the seminal plasma proteome in

men with prostatitis by mass spectrometry. Clin

Proteomics 9, 2.

92 Milardi D, Grande G, Vincenzoni F, Messana I,

Pontecorvi A, De Marinis L, Castagnola M & Marana

R (2012) Proteomic approach in the identification of

fertility pattern in seminal plasma of fertile men. Fertil

Steril 97, 67–73.

93 Wang J, Wang J, Zhang H, Shi H, Ma D, Zhao H, Lin

B & Li R (2009) Proteomic analysis of seminal plasma

from asthenozoospermia patients reveals proteins that

affect oxidative stress responses and semen quality.

Asian J Androl 11, 484–491.

94 Drabovich AP, Jarvi K & Diamandis EP (2011)

Verification of male infertility biomarkers in seminal

plasma by multiplex selected reaction monitoring assay.

Mol Cell Proteomics 10, M110.004127.

95 Rolland AD, Lavigne R, Dauly C, Calvel P, Kervarrec

C, Freour T, Evrard B, Rioux-Leclercq N, Auger J &

5650 FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS

Proteomic research in mammalian spermatogenesis G. MacLeod and S. Varmuza

Pineau C (2013) Identification of genital tract markers

in the human seminal plasma using an integrative

genomics approach. Hum Reprod 28, 199–209.

96 Yamamoto T, Nakayama K, Hirano H, Tomonaga T,

Ishihama Y, Yamada T, Kondo T, Kodera Y, Sato Y,

Araki N et al. (2013) Integrated view of the human

chromosome X-centric proteome project. J Proteome

Res 12, 58–61.

97 Lagarrigue M, Becker M, Lavigne R, Deininger S,

Walch A, Aubry F, Suckau D & Pineau C (2011)

Revisiting rat spermatogenesis with MALDI imaging at

20-lm resolution. Mol Cell Proteomics 10,

M110.005991.

98 Chaurand P, Fouch�ecourt S, DaGue BB, Xu BJ,

Reyzer ML, Orgebin-Crist M & Caprioli RM (2003)

Profiling and imaging proteins in the mouse epididymis

by imaging mass spectrometry. Proteomics 3,

2221–2239.

99 Schilling B, Rardin MJ, MacLean BX, Zawadzka AM,

Frewen BE, Cusack MP, Sorensen DJ, Bereman MS,

Jing E, Wu CC et al. (2012) Platform-independent and

label-free quantitation of proteomic data using MS1

extracted ion chromatograms in skyline: application to

protein acetylation and phosphorylation. Mol Cell

Proteomics 11, 202–214.

Supporting information

Additional supporting information may be found in

the online version of this article at the publisher’s web

site:Table S1. Full data from the Venn diagram in Fig. 2.

Table S2. A list of proteins found in three or more

human sperm subcellular proteomic datasets.

FEBS Journal 280 (2013) 5635–5651 ª 2013 FEBS 5651

G. MacLeod and S. Varmuza Proteomic research in mammalian spermatogenesis