REVIEW

Sperm proteomics: potential impact on male infertility treatmentAshok Agarwala, Ricardo Pimenta Bertollab and Luna Samanta c

aAmerican Center for Reproductive Medicine, Department of Urology, Cleveland Clinic, Cleveland, OH, USA; bDepartment of Surgery, Division ofUrology, Human Reproduction Section, Federal University of São Paulo, São Paulo, Brazil; cDepartment of Zoology, School of Life Sciences,Ravenshaw University, Cuttack, India

ABSTRACTSpermatozoa are unique cells that have highly compact DNA, motility (and hypermotility) patterns, a specificmorphology, localized mitochondria and an apical acrosome. They are the end product of a dynamic processtermed spermatogenesis. Sperm are therefore produced with specific proteins in order to effect differenttraits, such as the presence of cysteine-rich protamines in DNA, which effectively compacts DNA. Moreover,specific proteins are transferred during epididymal maturation and after ejaculation in order to render spermcapable of undergoing post-ejaculatory alterations, generally termed capacitation, which confers capacity tofertilize a mature oocyte. In addition, sperm exhibit several post-translational modifications, which arefundamental to their function, such as SUMOylation and ubiquitination. Discussed in this review is the currentknowledge of the spermproteome in terms of its composition and the function that these proteins determine,as well as their post-translational modifications and how these alter sperm functional integrity. Studies areemphasized that focus on shotgun proteomics – untargeted determination of the protein constituent of a cellin a given biological condition – and technologies currently applied toward that end are reviewed.

ARTICLE HISTORYReceived 4 November 2015Accepted 3 February 2016

KEYWORDSSperm; proteome; maleinfertility; human; post-translational modifications;LC-MS/MS

Introduction

Infertility affects 15% of couples of reproductive age, and in50% of these cases, there is a male component [1]. Variouscellular mechanisms are related to? Cause? Male infertility,such as sperm functional alterations (i.e. DNA fragmentation,acrosome integrity, among others) related to failed fertilization[2], poor embryo development [3,4], and assisted reproductionoutcome [3,5,6]. Recently, focus has been placed on investi-gating the molecular machineries that affect these mechan-isms, with a special focus on the protein composition ofejaculated sperm [7–9].

Spermatozoa are the product of spermatogenesis – a com-plex process in which diploid spermatogonia undergo meiosisand extensive morphological remodeling within the seminifer-ous tubules in the testes [10]. In humans, the process of sperma-togenesis is responsible for generating between 20 and 240million sperm per day and depends on tight regulation of cellularmetabolism [10]. Moreover, a number of selective mechanismswithin the testes and epididymides help ensure that high qualitysperm are available for ejaculation [10].

Many studies have hinted at a specific proteome signaturethat allow for the differentiation of high quality from lowquality sperm [9], as well as specific proteins that activatefollowing ejaculation in order to orchestrate acquisition ofspecific motility patterns [11], exocytosis of the acrosomalcontent, [11,12] and fusion of the sperm membrane to theoolemma [13,14]. However, many proteins in sperm may beadded after spermatogenesis via microvesicles within the epi-didymal lumen (epididymosomes) [15–18] or even after ejacu-lation through prostatic microvesicles (prostasomes) [19–21].

Moreover, different subsets of sperm seem to coexist within anejaculate. D’amours et al., for example, demonstrated that deadbovine sperm (but not live sperm) are tagged, via transfer byepididymosomes, with a protein containing multiple fibronectinII domains, which are known to bind to collagen – EpididymalSperm Binding Protein 1 (ELSPBP1) [15]. This protein has also beenassociated with increased sperm DNA fragmentation in humans[9]. Other bovine studies have localized Fas – a membrane recep-tor of the tumor necrosis factor family that initiates apoptosis – toat least three different sperm regions, indicating that these areindeed subsets with different activities [22].

This division of sperm into subsets poses important con-siderations in regards to study design because the wholeproteome of an ejaculate may not reflect its true fertilitypotential. It has been demonstrated, for example, that spermmarked for specific processes, such as apoptosis, are indeed oflower reproductive potential than those unmarked [23].Conversely, specific proteins, which may offer sperm resis-tance within the female reproductive tract may also mark apopulation of viable sperm [24].

The field of proteomics has greatly benefited from thedevelopment of mass spectrometry (MS)-based systems[25,26]. While initial studies relied on gel separation of pro-teins by their isoelectric point and their mass (two-dimen-sional (2D) gel electrophoresis) [27,28], the exponential rateat which mass spectrometric resolution and sensitivity, alliedto the development of protein- and peptide-specific chroma-tographic separation techniques, have led to systems that candetect and quantify a greater number of proteins at a higherdynamic range [26,29–31]. The latter is usually achieved viadigestion of proteins into their constitutive peptides (this may

CONTACT Ashok Agarwal agarwaa@ccf.org

EXPERT REVIEW OF PROTEOMICS, 2016VOL. 13, NO. 3, 285–296http://dx.doi.org/10.1586/14789450.2016.1151357

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be preceded by protein fractionation) and identification andquantification of these peptides by liquid chromatography–tandem mass spectrometry (LC–MS/MS) in an approach‘termed shotgun proteomics’ [25,26,29].

In the first part of this review, we will discuss the technol-ogies that are currently used for sperm proteomic studies aswell as the challenges in data analysis. In the second part, wewill extensively review the data that have been generatedregarding the human sperm proteome.

Review criteria

A literature search was performed using PubMed and GoogleScholar electronic databases, using the following keywords:‘human’, ‘spermatozoa’, ‘proteome’, ‘protein–protein interac-tion network’, ‘shotgun proteomics’, ‘proteomics’, ‘spermato-genesis’, ‘epididymal maturation’, ‘post-translationalmodifications’, ‘infertility’, and ‘sperm function’. Only articlespublished in peer-reviewed journals were selected. The searchtargeted studies that were published in English-based journalswithin the past 10 years.

Methods for determining the sperm proteome

Proteomics is the identification and quantification of all theproteins in a given fluid or cell under a specific biologicalcondition [32]. Initial untargeted studies used 2D-gel electro-phoresis (2D-GE) in which proteins are separated initially bythe isoelectric points – the pH at which their net charge is zero– followed by separation by mass in conventional laemmli gelsand staining. Each protein thus forms a spot on a gel, and spotintensities are compared across gels in order to observe differ-ential expression levels. Spots of interest may then be identi-fied by MS (in the same principle that will be discussedfurther), and the relative quantification information isextracted from the gel (spot intensities) (for a review, see [27]).

Due to the variable nature of gel polymerization, thesestudies usually have high intra- and inter-assay variation[33,34]. To decrease this variability, difference gel electrophor-esis (DIGE) can be used. With DIGE, proteins of one sample aretagged with a fluorescent stain whereas proteins of anothersample are tagged with a different fluorescent stain. Thesesamples are then pooled and run through all the stepstogether. Fluorescent gel analysis then quantifies the fluores-cent signals from each sample to provide a more accuratedifferential analysis [27,35].

More recently, MS-based proteomics pipelines have beendeveloped, increasing dynamic range, quantification, and sen-sitivity with direct integration to chromatographic separation[26,29,31,36]. In these studies, proteins are digested into theirconstituent peptides, which are extensively analyzed andquantified. Proteins are therefore identified and quantifiedbased on in silico construction of their identified peptides(i.e. a bottom-up approach). This is achieved using MS equip-ment in an approach termed ‘shotgun proteomics’ [26,29,37].

Mass spectrometers analyze the masses of ionized mole-cules in a gas phase. The spectrometers contain an ionizationsource and one or more mass analyzers [31]. Ionization isachieved through the use of ‘soft’ ionization – usually matrix-

assisted laser desorption/ionization [38,39] and electrosprayionization (ESI) [40]. Because ESI ionizes molecules that are ina liquid phase, they are utilized for direct integration withliquid chromatography equipment in a setup (LC–MS) thatallows quantitative information to be derived from the con-structed chromatograms [36].

Following ionization, the mass analyzers select or analyzethe mass of the ionized molecules, utilizing different princi-ples. In general, quadrupole (Q) and ion trap mass analyzersfilter and accumulate the ions of interest, whereas time-of-flight and orbitrap mass analyzers detect mass values withhigh resolution [31]. Current shotgun proteomic platformsusually couple an ultraperformance liquid chromatographer(UPLC) to a hybrid mass spectrometer (MS/MS) in a setuptermed LC–MS/MS [7,9,41–43].

In most MS-based shotgun proteomics studies, an initialscan is generated in the high-resolution mass analyzer, andthe most important parent scan ions are determined. In sub-sequent scans, each parent ion selected in the first massanalyzer is fragmented in a collision chamber, and the frag-ment ions are identified in the high-resolution mass analyzer[31]. This approach is considered a data-dependent approachbecause an initial scan is necessary.

More recently, data-independent acquisition techniques havebeen generated, such as MSe [42,44] and sequential windowacquisition of all theoretical fragment ion spectra-MS [45–47].In data-independent acquisition, there is no precursor ion selec-tion: all ions are analyzed in their unfragmented and fragmentedforms. These techniques improve quantitative analysis of theidentified proteins as well as reproducibility of the data analyses[48].

Another important point is that coverage of the proteomedepends on the resolution of the chromatographic separation,because coelution of peptides decreases the odds that LC–MS/MS will be able to identify them, and this effect is moreimportant than low peptide quantity [49]. This ultimatelymeans that decreasing the sample complexity will allow for agreater number of peptides (and thus of proteins) to bedetermined. Fractionation of proteins before the LC–MS/MSexperiment has increasingly been used toward that end.Fractionation may be performed using a number of methods:running 1D gels to preseparate proteins based on their massand then slicing the generated protein lanes into mass frac-tions; in-solution isoelectric focusing, and prefractionation uti-lizing affinity columns [50–52].

Finally, in order to decrease inter-assay variability, many stu-dies have utilized differential mass tags. These mass tags, such asiTRAQ, iCAT, tandem mass tags [53], and dimethyl labels [54]allow for the differential marking of samples. These samples arethen pooled prior to the LC–MS/MS experiment. Software pro-cessing allows for relative quantification between different sam-ples in a same run, thus increasing reproducibility.

In studies focusing on sperm proteins, some other impor-tant points should be considered. If sperm are collected byejaculation, it is important to remove any contaminatinground cells [9]. Moreover, some authors have suggested thatdifferent subpopulations of sperm coexist in the human eja-culate [22,55,56]. For example, if this is the case, researchersmay want to select only viable sperm using density gradient or

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swim-up techniques. Sperm selection based on functionaltraits could also generate important information on spermphysiology (such as selecting sperm with fragmented DNA orsperm bound to the zona pellucida of mature oocytes). Thisinformation is probably diluted in whole ejaculates, whichenhances the importance of planning sperm prefractionationeven before protein extraction.

Because sperm interaction with the surrounding media isfundamental in sperm physiology, approaches targeting spe-cific sperm regions are also important. Isolating membraneproteins, for example, may be useful in determining sperm–egg interacting proteins [57] or proteins transferred duringepididymal maturation [15,58]. Similarly, isolating mitochon-drial proteins could generate information regarding oxidativephosphorylation energy-producing pathways in mature spermunder diverse conditions [59].

There are many methods for determining the constituentsperm proteome as well as differential proteomes under dif-ferent biological conditions. It is important, however, to con-sider isolating specific subsets of sperm, or specific regionswithin these subsets, in order to focus on the intended organ-isms. Furthermore, technological considerations should bemade such as whether a data-independent approach is feasi-ble and if a label-free approach will suffice or if poolingsamples with different labels for comparison within a samerun will generate better information. Finally, studies may focuson differential proteome networks, as these will overexpressspecific functions when acting conjointly. Or, a functionalcomponent may be added to these studies by verifying reg-ulatory post-translational modifications in specific proteins orin a similar shotgun approach.

Differences in form and function: differentialproteome signatures and post-translationalmodifications

Technological advances in MS-based proteomics and inpeptide separation technologies have greatly increased cov-erage of the proteome [29,31]. As a result, studies haveidentified and quantified thousands of peptides and

proteins within biological samples [60,61]. This has led tothe understanding that proteins interact with one anotherto enrich specific functions and thus to produce a givenphenotype [62].

Proteins thus form protein–protein interaction (PPI) net-works and participate in specific pathways to produce spe-cific functions, such as fertilization (Figure 1). These PPInetworks are scale-free in that few proteins may lead tomultiple interactions (hub proteins) while many proteinsmay lead to few interactions (Figure 2) [63]. This is impor-tant to understand because proteins of more centrality (orwith more interactions), when altered or absent, will affectthe function of many different proteins and pathways.These are usually lethal gene products. More often thannot, however, mild phenotypic differences will be observeddue to altered expression of proteins with few interac-tions [64].

Another important point is that proteins, even when pre-sent, may have altered function due to post-translationalmodifications (PTMs) [65,66]. There are many different typesof PTMs, such as SUMOylation, phosphorylation, glycosylation,and ubiquitination [67]. In many cases, the proteome mapitself may not be altered but differences in PTMs may causea deviation in function. Sperm capacitation, for example,depends on an orchestrated cascade of protein phosphoryla-tion which, when finely regulated, leads to alteration in moti-lity patterns and eventually in acrosome exocytosis [68]. Inaddition, ubiquitination of sperm mitochondria prevents thepaternal mitochondrial DNA from being transmitted to theoffspring [69]. Finally, SUMOylation of specific proteins insperm such as topoisomerase-IIα has been associated withDNA damage, thus demonstrating an effect of PTM onsperm function [55].

In order to convincingly establish protein function, as afunction of their interaction networks, there is a necessity todesign studies that provides as complete a picture of theproteome as possible. Moreover, enriching PTMs for theircharacterization in shotgun studies may lend a functionalcomponent to the understanding of the sperm proteome.Downstream data analysis therefore must be able to deal

Figure 1. Protein-protein interaction (PPI) network (left) and the ‘Fertilization’ Reactome Pathway [75] effected by this PPI network.

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with a large number of inter-correlated variables to filter outunimportant data.

Data analysis in proteomics

Shotgun proteomic studies can identify and quantify hun-dreds to thousands of proteins at a time [7,9,41–43]. Resultsmatrices are therefore quite complex, containing thousandsof variables – many of which are intercorrelated. In addition,the variables are scaled differently from those used in con-ventional sperm analysis studies such as sperm concentra-tion, motility, morphology, DNA integrity, and acrosomeintegrity as other information (age, hormonal profile, etc.).Therefore, the statistical analysis must consider the intercor-relation observed between the quantified proteins as wellas filter unimportant variables to remove them from con-structed models [41]. Furthermore, because proteins interactwith one another, the data analysis must also include func-tional enrichment analysis [70,71].

In regards to statistical analysis, a univariate approach isoften used. However, in these cases, the analysis mustinclude adjustments for multiple comparisons, such as per-mutation-based false discovery rate determination forp-value adjustment [72]. A multivariate statistical designmay deal with these data more appropriately. Principalcomponent analysis, an unsupervised data multivariate ana-lysis, extracts components (highly correlated variables thatexplain patterns in the data) of independent variables. Thisis useful if general patterns are observed and if eventualsample outliers are present as confounding individuals inthe data [72]. Partial least squares discriminant analysis, asupervised multivariate analysis test, extracts componentsfrom both the independent and the dependent variablesin order to generate a model that best explains why twogroups of patients or samples differ from one another[41].Logistic regression models may also be constructed in orderto predict group participation based on protein quantifica-tion. These models will produce odds ratios for individualprotein quantities – variations of these quantities willincrease the odds of that individual being of one group(e.g. infertile) or another [41].

Proteins can be annotated in different ways usingonline databases. Gene ontology terms, for example, areannotated into three general categories: biological process,molecular function, and cellular component [73]. However,proteins may also be annotated with pathway terms (Kyotoencyclopedia of genes and genomes – KEGG [74],Reactome [75], PantherDB [70]), domains (InterPro [76]),interactions (IntAct [77], BioGRID [78], HPRD [79], STRING[80], among others. Because a single protein is usuallyannotated with many terms from each database, statisticaltests have been designed to observe if the frequency ofthese terms in the PPI network or in one of its clusters ishigher than the frequency of these terms in the wholedatabase or in reference samples [81]. This approach,termed functional enrichment analysis, will offer a func-tional inference as to what role that protein (and its coun-terparts in the PPI network) plays in determining aphenotype [71,81–83].

In this workflow, a PPI network is generated by searchingfor interaction information from the databases cited above.Thenceforth, functional enrichment analysis of the differen-tially expressed proteins generates information regarding thefunctions enriched by these clusters and possible mechanismsthat explain the biological state [9,41–43].

The proteomic study of spermatozoa has taken a big leapever since the historical discovery of protamines in salmonsperm by Miescher [84]. Interest in using proteomic studies toidentify potential diagnostic markers has grown in recentyears. In one study, 2045 proteins were identified from agroup of patients with idiopathic infertility – 21 proteinswere differentially expressed (>1.2-fold) in men whose spermresulted in a clinical pregnancy via ART versus those who didnot [85]. With the absence of physiologically active transcrip-tion and translation, spermatozoa could be regarded as out-standing candidates for proteomic study. This is furthersupported by the fact that they can be purified at high con-centrations and can be pharmacologically manipulated intovarious functional states such as capacitated, non-capacitated,and acrosome reacted [86,87]. Moreover, understanding thedifferences in the proteomic profile of developing spermpopulations – caput verses cauda epididymis and ejaculatedverses capacitated, for example–will help unravel the post-

Figure 2. Scale-free protein-protein interaction sub-network of reviewed human sperm proteins (Uniprot [83]) highlighting hub proteins (proteins with manyinteractions) in red.

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translational modifications relevant to sperm maturation[88,89]. In addition, comparative proteomic analysis will notonly pave the way for understanding any ‘hidden’ spermfactors responsible for infertility but also provide a molecularbiomarker for diagnosis and prognosis of male factor infertility– thus helping to develop an appropriate therapeuticapproach to treat male infertility [90].

Origin and characterization of sperm proteins –spermatogenesis, epididymal maturation,and post-ejaculation

Spermatogenesis is a highly coordinated process that marksthe differentiation of diploid spermatogonia through haploidround spermatid cells into the highly specialized, elongated,terminally differentiated spermatozoon that is packaged todeliver the paternal genome to an oocyte. Spermatozoa areleft with a limited amount of cytosolic organelles and a com-plete loss of transcriptional ability during post-testicularmaturation, while during epididymal transit, spermatozoaundergo a series of post translational modifications andacquire new proteins, making it competent to fuse with theoocyte [91]. Most of our knowledge regarding human sperm isbased on proteomic analysis of ejaculated human spermato-zoa. However, data on the characterization of proteins respon-sible for spermatogenesis and epididymal maturation are as ofyet still unavailable.

According to a systematic compilation by Amaral et al.,approximately 6198 different sperm proteins have been iden-tified – about 30% are known to be expressed in the testis[92]. Gene ontology (GO) analysis revealed that these proteinswere involved in various functional pathways, such as meta-bolism, apoptosis, cell cycle, meiosis, and membrane traffick-ing, among others. Apart from the expected abundance ofcytoskeletal, mitochondrial, flagellar, and membrane proteins,GO analysis has also provided reports on the presence of alarge proportion of proteins involved in transcription, proteinsynthesis, and turnover [93,94].

Human sperm proteins of testicular and epididymal originwere characterized by Li et al. and his group [95,96]. In theirreport, 112 of 319 identified human sperm-located proteins(35%) were exclusively of testicular-origin, 152 (48%) wereexclusively of epididymal origin and 55 (17%) were commonto both organs [96]. The report suggested that 47% of theidentified proteins were intrinsic sperm proteins expressed atthe spermatid stage while 23% were extrinsic sperm proteinsthat were acquired during epididymal transit and had anepididymal origin [95].

It was further validated that these proteins had a specificpattern of localization in sperm based on their origin.The epididymal proteins were more specifically concentratedat the principal piece while less so in the acrosomal areain comparison to testicular proteins [96]. HSPA2, a novel,testis-specific member of the HSP70 family, is expressedin the sperm plasma membrane along with another memberHSPA5 [97]. Underexpression of HSPA2 in oligoteratozoosper-mic men [98] suggests that human HSPA2 may act as a marker

for sperm maturity [99]. It is postulated to play a secondaryrole in the remodeling of the sperm plasma membrane duringspermatogenesis [100] to facilitate the formation of the ZP-binding sites. Another study also found this major spermcomponent to be underexpressed in oxidatively stressedspermatozoa [101]. Recent evidence states that HSPs, includ-ing 60, 70, and 90, migrate to the sperm surface and undergophosphorylation during capacitation [102] since tyrosine-phosphorylated sperm heads were able to bind to the zonapellucida [103]. Wang et al identified about 4675 proteins inhuman spermatozoa of which only 227 proteins had a testi-cular origin [104].

Sperm proteomics and male infertility

In the field of male infertility, where conventional semenanalysis sometimes fails to report the underlying cause ofmale factor infertility, recent advances in proteomic researchhave provided important biomarkers for diagnosis and prog-nosis of male infertility. One of the initial reports in the studyof sperm defects through the use of 2D proteomics reportedthe proteomic mapping of a patient who experienced a failurein in vitro fertilization, where 20 different proteins were iden-tified as compared to controls [105]. Subsequently, a differen-tial expression profile of 17 proteins was observed inasthenozoospermia [106], and further reports demonstratedthat clusterin and semenogelin were increased in thesepatients [101,107]. In an independent study, oligoastheno-zoospermic (OAT) patients exhibited significantly higher inci-dence of heterozygosity for cytosine-adenine-guanine repeatsand a higher mtDNA content with a lower percentage ofsperm expressing polymerase ᵞ and transcription factor A,mitochondrial in the spermatozoa of OAT group [108].

In globozoospermic patients, 35 proteins were differentiallyexpressed, of which 9 proteins were upregulated and 26proteins were downregulated in round-headed spermatozoacompared with normal spermatozoa [109]. These differentiallyexpressed proteins were suggested to be involved in a varietyof cellular processes and structures, including spermatogen-esis, cell skeleton, metabolism, and motility of spermatozoa.

A focused study on proteomic signatures in infertilepatients whose semen parameters were normal but with failedin vitro fertilization revealed 24 proteins with altered expres-sion in the normozoospermic infertile group. These proteinswere reported to be involved in energy production, structureand movement, and cell signaling and regulation [90]. Inanother study on patients with idiopathic infertility, a compar-ison of sperm proteome in men whose sperm resulted in aclinical pregnancy via assisted reproductive technology (ART)from those who did not, revealed 21 proteins to be differen-tially expressed (>1.2-fold) [85].

Abnormal DNA fragmentation and/or motility is asso-ciated with four main protein groups, viz. (i) sperm nuclearproteins such as the sperm protein associated with nucleusin the X chromosome (SPANX) isoforms and several types ofhistones [110]; (ii) mitochondria-related functions and oxi-dative stress proteins including mitochondrial ferritin,

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mitochondrial single-stranded DNA binding protein, andseveral isoforms of Peroxiredoxins; (iii) proteins related tosperm motility such as microtubule-based flagellum andspindle microtubule, and (iv) proteins related to the ubiqui-tin–proteasome pathway.

In an attempt to detect the differential protein profile inmen with and without varicocele using 2D gel electrophoresis;15 consistent differences in protein expression were identifiedin patients with varicocele when compared with controls[111]. Heat shock proteins, mitochondrial proteins, and cytos-keleton proteins are the major proteins affected by varicocele.Particularly, a significant upregulation of heat shock proteins(HSP70 and HSP90) was observed in subjects with varicocelewhich was further validated by Western blot and immunocy-tochemistry [112].

In a recent study, 369 differentially expressed proteins(DEP) were detected in infertile patients with unilateral vari-cocele in comparison to fertile donors [111]. Of the totalreported DEPs, 120 proteins were unique to the fertilegroup, and 38 were unique to the unilateral varicocele group114 overexpressed and 97 underexpressed in the unilateralvaricocele group. The major functional pathways of the 359DEP involve metabolism, disease, immune system, geneexpression, signal transduction, and apoptosis.

In another study comparing sperm of men with bilateralvaricocele with fertile controls, 73 DEP were reported, themajority of which associated with metabolic processes, stressresponse, oxidoreductase activity, enzyme regulation, andimmune system processes [112]. Comparison of the spermproteomes of men with unilateral versus bilateral varicoceledemonstrated 64 proteins in the bilateral group and 31 pro-teins in the unilateral group [7]. Core functions of the topprotein interaction networks were post-translational modifica-tion, protein folding, free-radical scavenging, cell death, andsurvival.

In another study, the sperm proteome from groups ofmen with high levels of reactive oxygen species (ROS+) werecompared with that of men with low or physiological levelsof ROS (ROS–) [101,113]. In the first case [113], a 2D-DIGEwith differential fluorescence tagging and in gel digestion ofthe proteins followed by LC–MS detection. A total of 31spots were differentially expressed with 6 significantlydecreased and 25 increased in the ROS– sample comparedwith the ROS+ sample. The result showed overabundance offour antioxidant proteins in ROS– sperm that may exertessential cytoprotective effects against the build-up of ROSlevels: lactotransferrin isoform 2, lactotransferrin isoform 1precursor, peroxiredoxin-1, and Mn-SOD mitochondrial iso-form A precursor [113]. In the second study, the sampleswere subjected to LC–MS/MS analysis through in-solutiondigestion of proteins for peptide characterization [101]. Thefindings revealed a total of 74 proteins in spermatozoa, outof which 15 proteins with more than twofold differencewere overexpressed (ROS+ group) when compared to theROS– group. The overexpressed proteins comprised the his-tone cluster 1 H2ba (HIST1H2BA); mitochondrial malate

dehydrogenase precursor (MDH2); heat shock protein 90kDa beta, member 1 (HSP90B1); heat shock 70 kDa protein5(HSPA5); glutamine synthetase (GLUL); transglutaminase4(prostate) (TGM4); glutathione peroxidase 4 isoform A pre-cursor (GPX4); sperm acrosomal membrane protein4(SPACA4); olfactomedin 4 precursor (OLFM4); and chromo-some 20 open reading frame 3 (C20orf3), whereas theunderexpressed proteins included semenogelin II precursor(SEMG2); peroxiredoxin 6 (PRDX6); clathrin heavy chain 1(CLTC); eukaryotic translation elongation factor 2 (EEF2);and enolase 1 (ENO1). Furthermore, there was significantchange in localization profile of the differentially expressedproteins. While the overexpressed proteins were predomi-nantly found in the cellular compartments of intracellular,organelle, macromolecular complex region and mitochon-dria; the underexpressed proteins were dominated in thecytoplasm extracellular, plasma membrane, protein complex(e.g. enolase) and the vesicular region (e.g. clathrin heavychain). Remarkably, the endosome, lipid particle, membrane-bound organelles and the microtubules showed an exclusiveabundance of overexpressed proteins in ROS+ group; whilethe proteinaceous extracellular matrix was restricted only tothe underexpressed proteins. In a recent study, comparisonswere made between protein profiles of spermatozoa fromfertile donors and infertile men with varying levels of ROS.Identification of six DEPs (Calmegin, Tripeptidyl peptidase II,Dynein intermediate chain 2, axonemal, heat shock 70 kDaprotein 4 L, early endosome antigen 1, and plasma serineprotease inhibitor) that were present in all the three ROSgroups with varying expression levels suggests that theymay serve as potential candidates of oxidative stress mar-kers [114].

Many of the proteins in its precursor or preprotein formhave been identified in studies relating to male fertilityanomalies, and it may be speculated that the accumulationof these protein is an indication of generalized defects at thepost translational level. Assumptions are also made regardingthe down regulation of some of the downstream functionsrelated to these proteins [101,106,115]. Such differential altera-tion pattern may be due to PTM which could be used as aneffective diagnostic strategy valuable for understanding malefactor infertility.

Ubiquitination and acetylation were reported to be theprincipal PTM found in non-obstructive azoospermia (NOA).Impairment in production of different enzymes belonging toUPS, namely UBE2B protein (an ubiquitin-conjugatingenzyme) may cause defects in spermatozoa maturation andresult in NOA [116,117]. Besides, mutations in genes encod-ing for testis-specific ubiquitin proteases, namely USP26 [118]and USP9Y [119], as observed in azoospermic patients, eluci-dates the role of protein ubiquitination in azoospermia. Onthe other hand, hyperacetylation of histone H4 is reported inobstructive azoospermic spermatids [120]. USP might playsome regulatory role in oligozoospermic patients [121],Differential expression of ubiquitin-conjugating enzymeUBE2B [117,122], and protease USP26 [123] was noticed in

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oligozoospermic semen samples suggesting its possibleinvolvement.

Potential involvement of altered protein phosphorylationevents, such as phosphorylation of the gamma–tubulincomplex associated protein 2 (GCP2) in the pathogenesisof asthenozoospermia (AZS) [124] suggests the role of thisPTM in sperm motility. Parte et al. [125] further establishedthis by identifying 66 differentially expressed phosphopro-teins in AZS sperm, which comprised predominantly of theHSPs, cytoskeletal proteins, proteins associated with thefibrous sheath, and those associated with energy.Furthermore, a correlation between deficiency of tyrosinephosphorylation of tail proteins, especially those related tohyperactivated motility and AZS was also reported [126].Nevertheless, decreased membrane fluidity is hypothesizedto be the cause of hypophosphorylation of proteins duringcapacitation in these groups [127]. In two separate proteo-mic studies, several proteins having S-nitrosylation siteswere identified to be differentially expressed in AZS sperm[106,128]. Similarly, testis-specific α-tubulin isoformsTUBA3 C and TUBA8, in their acetylated state, wasdecreased, and TUBA4A was increased in AZS as comparedwith normal spermatozoa [129]. A variation of ubiquitinprotease USP26 was also reported to be directly associatedwith human sperm motility [123]. Moreover, in some AZSpatients, a severe form of structural anomaly is found in thesperm known as dysplasia of the fibrous sheath (DFS). Astudy demonstrated that sperm with DFS were accompa-nied by increased ubiquitination of the sperm surface aswell as the sperm mitochondrial proteins [130]. In AZSpatients only, percentage of SUMO1-positive spermatozoawas found to be inversely correlated with total and progres-sive motility [56]. In addition, an association of AZS withanomalies in seminal glycome has also been documented[131,132].

Teratozoospermia patients (TZS) are documented to pre-sent differential tyrosine phosphorylation of six sperm pro-teins in comparison to normozoospermic men [133].Furthermore, spermatozoa from TZS males exhibited a com-promised ability to undergo tyrosine phosphorylation fol-lowing capacitation [134]. Significant negative correlationwith the phosphorylated levels of protein Stat3 was alsoobserved in TZS [134]. Similarly, ejaculated sperm of theTZS group demonstrated increased binding of anti-ubiquitinantibodies to the sperm surface, reflecting the occurrence ofenhanced sperm surface ubiquitination in nonsystematiccases of TZS [135].

A comparative study on assessment of tyrosine phos-phorylation status in spermatozoa of varicocele patientsrevealed a reduced level of phosphorylation [136], which isattributed to an alteration in plasma membrane dynamicsresulting in sperm dysfunction in these patients.Furthermore, enzymes linked to protein glycosylationnamely acid β-glucuronidase, α-mannosidase, α-glucosidase,α-galactosidase, β-galactosidase, and β-N-acetylglucosamini-dase showed overexpression and hyperactivity in seminalplasma of infertile men with varicocele [137]. As theseextracellular glycosidases are implicated to cause the mod-ification of sperm plasma membrane glycoproteins during

sperm maturation process, it could be postulated that suchoverexpression of acid glycosidase in the seminal plasmawould mask the carbohydrate-containing molecules presentin ejaculated spermatozoa of varicocele group, altering theirfertilization potential. One of the major pathways of PTMand protein folding found to be severely compromised invaricocele individuals is the UPS [7]. In addition, assessmentof the ubiquitination median, a marker for functionality ofthe UPS was also lower in varicocele group, where it wasreported to show a negative correlation with sperm mor-phology [138].

Expert commentary

In the post-genomic era, studies have mainly focused onthe identification of novel protein biomarkers in complexbiological systems. A biomarker is a distinctive biological orbiologically derived indicator of a process, event, or condi-tion, and is considered ideal if it serves the purpose ofscreening, diagnosis, and monitoring disease activity. Inaddition, they may hold responsible for targeted therapyor would assess therapeutic response [139]. With regard tomale factor infertility, the main objective of a biomarker isto evaluate in an accurate and minimally invasive manner,the male potential to father a child. Furthermore, use ofsemen for proteomic analysis is complicated because itcontains sperm as well as seminal plasma and the mostimportant challenge in sperm proteomics is the fact thatspermatozoa undergoes distinct physiological changes afterejaculation. The advantages of using proteomic over routinesemen analysis is that it confirms the qualitative and quan-titative measure of a protein within the spermatozoa.Nevertheless, identification of the ideal biomarker for clin-ical diagnosis in such a complex scenario to distinguish thepathophysiological state is one of the main challenges.Furthermore, in a clinical proteomics study one sample perindividual is used with the assumption that this sample, isrepresentative of a disease. However, it is more likely repre-sentative of the time of day it was drawn, the nutritionalstatus and life style of the patient, and their genetic back-ground rather than the pathology under investigation.Therefore, longitudinal sampling where samples are col-lected over time to determine how the proteome changesover time within an individual is necessary for discovery ofputative biomarker. Personalized reference ranges are wheremedicine will have a tremendous impact; discovery-basedproteomics using longitudinal sampling will be critical toelucidate predictive biomarkers.

As vide supra in the past two decades, studies on pro-teomic profiling of spermatozoa result in the generation ofan increasing amount of data. The information generatedmainly comprises of complex protein compositions and alarge number of isolated proteins whose implications inthe biological state is yet to be discovered. This limits theuse of proteomic approaches to elucidate the role of biolo-gical markers [140]. Furthermore, an additional confoundingfactor is the inherent complexity of the disease, therefore,the pathogenesis cannot be singled out by a protein, butmight indeed be a result of multiple interacting proteins

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across multiple pathways. Thus, employing a panel of bio-markers for identification of infertility is more likely to besuccessful. With relation to oxidative stress in the spermato-zoa, proteins, such as MDH2, TGM4, GPX4, GLUL, HSP90B1,and HSPA5 are suggested as possible biomarkers due totheir increased expression in samples with high levels ofROS compared with those without oxidative stress [141].Data from a number of independent laboratories suggeststhat an underrepresentation of a key molecular chaperone,HSPA2 is responsible for impaired sperm–egg recognition[142] which is reported to be modulated by oxidative stress(lipid aldehydes) [143]. While considering the use of multipleinteracting-markers to provide specific valid signatures, theproblems inherent to validation increases exponentially[144]. The question is how to test the validity. Is the changein expression of a candidate protein directly associated withthe disease or is it due to the presence of a PTM(s) or mightit only be an artefact resulting from technical variability?This fact is further complicated by the identification of pro-teins possessing PTM within the normal and abnormal sper-matozoa, specific to different pathological states, such asoxidative stress. Nevertheless, the current trends to identifyPTMs are only predictive [145]. Therefore, creation of newpipelines as well as analytical methods [146] that allow foranalysis of specific PTMs on sperm function will impact theunderstanding of protein function in healthy and infertilespermatozoa. A study that attested to the inherent technicalvariability present in proteomic profiling, as published bymembers of the Human Proteome Organization (HUPO)showed that when an equimolar protein sample containing20 human proteins was given to 27 different laboratories,only 7 out of 27 labs were able to correctly identify all the20 proteins in the sample. The discrepancies in the resultswere attributed to the databases used for analysis, as theycontain erroneous confidence levels, thereby missing severalof the 20 proteins present in the sample [147].

Another aspect of understanding the sperm proteome indifferent pathophysiological states is to identify theabnormality in structure and function of the protein so asto target them for development of reversible male contra-ception. This necessitates the identification of sperm pro-teins on different domains, which are acquired by spermmostly as they traverse the epididymis. The sperm pro-teome is dynamic due to the fact that proteins are trans-ported into the spermatozoa from the epididymal, seminal,or prostatic fluid. Epididymal proteins are preferred targets

for contraception development over testicular proteins, asthe blockage of sperm maturational events will not obstructspermatogenesis and testicular endocrine function, as wellas allow for reversibility [148,149]. Both pre- and postfertili-zation events are possibly affected by targeting the spermhead and the flagellar proteins. Evaluation of sperm pro-teins thus allows for a straightforward assessment of testi-cular homeostasis, and is an increasingly important area ofstudy in male infertility.

Five-year view

Among the main challenges that will need to be dealt with instudying the infertile male, sperm proteomics studies will greatlybenefit from increased sensitivity, specificity and reproducibility ofMS-based proteomics. Studying post-translational modificationswill further allow for determination of understanding how thedynamic equilibrium of fertile sperm, co-inhabiting with alteredsperm, may lead to positive or negative effects to fertility.Furthermore, the clinical impact of proteomics to sperm biologyand functional state may (i) allow for determination of the biolo-gical systems leading to the observed cellular integrity and (ii)allow for pathway specific intervention. In a recent report, Intasquiet al. demonstrated a number of proteins associated with spermDNA fragmentation, some of which are transferred specificallyduring epididymal transit through epididymosomes [9]. It is inter-esting that multiplatform studiesmay indeed enhance our currentknowledge of sperm biology, as well as of male fertility.

Acknowledgement

Financial support for this study was provided by the American Center forReproductive Medicine, Cleveland Clinic.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with anyorganization or entity with a financial interest in or financial conflict with thesubject matter or materials discussed in the manuscript. This includesemployment, consultancies, honoraria, stock ownership or options, experttestimony, grants or patents received or pending, or royalties.

ORCID

Luna Samanta http://orcid.org/0000-0002-2969-0071

Key issues

● Seminal improvement in MS and development of bioinformatics tools together with a renaissance in wet-bench aspects, such as 2D-gel electrophoresis,gel-free, and off-gel separation techniques have allowed proteomics to achieve its zenith.

● Proteomics is more promising for the study of sperm biology than other omics as these cells are essentially silent in terms of transcription andtranslation.

● A large number of spermatozoa proteins have been cataloged in various case-control studies.● A set of proteins differentially expressed in spermatozoa of infertile patients point toward use of a set of biomarkers rather than a single protein.● The spermatozoa proteome is a dynamic one and changes during post testicular stages enable sperm to fertilize the egg.● Spermatozoal proteins undergo a series of post-translational changes during post-testicular maturation.● Some proteins in spermatozoa undergo multiple post-translational modifications.● Current trends that involve identifying PTMs are only predictive.● Studying protein interactions and the structures of multi-protein complexes may shed more light on the different proteins involved in sperm function.

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137. Corrales JJ, Burgo RM, Galindo P, et al. Abnormal expression of acidglycosidases in seminal plasma and spermatozoa from infertilemen with varicocele. Reproduction. 2002;123(3):411–417.

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