Investigation of Male Infertility Using Quantitative Comparative

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Investigation of Male Infertility Using Quantitative Comparative Proteomics Christine Légaré,† Arnaud Droit,‡ Frédéric Fournier,‡ Sylvie Bourassa,‡ André Force,§ Francine Cloutier,∥ Roland Tremblay,∥ and Robert Sullivan*,† †

Département Obstétrique, Gynécologie et Reproduction and ‡Département Médecine Moléculaire, Centre de Recherche, Centre Hospitalier Universitaire de Québec, Quebec City, Quebec, Canada G1V 4G2 § Laboratoire Bionnis, 69130 Ecully, France ∥ Department-Médecine, Faculté de Médecine, Université Laval, Quebec City, Quebec G1V 0A6, Canada ABSTRACT: Male factors account for 40% of infertility cases. The identification of differentially expressed proteins on spermatozoa from fertile and infertile men can help in the elucidation of the molecular basis of male infertility. The aim of this study was to compare sperm proteomes from 3 different groups: fertile men, normozoospermic men consulting for infertility, and normozoospermic men with an impaired capacity for fertilization (IVF-failure). We used differential proteomics with isobaric tags for relative and absolute quantitation (iTRAQ) labeling, and LC−MS analysis to identify proteins that are differentially expressed. A total of 348 unique proteins were identified and quantified. The analysis identified 33 proteins that were differentially expressed in the IVF-failure group vs the fertile group. Comparison of the infertile and fertile groups revealed that 18 proteins appeared to be differentially expressed. Four proteins were similarly altered in the IVF-failure and infertile groups: semenogelin 1 (SEMG1), prolactin-induced protein (PIP), glyceraldehyde-3-phosphate dehydrogenase (GAPDHS), and phosphoglycerate kinase 2 (PGK2). These protein markers were selected for validation using multiple reactions monitoring mass spectrometry (MRM-MS) and further confirmed by Western blot analysis. Overall, these results suggest that a panel of proteins may be used as biomarkers for future studies of infertility. KEYWORDS: infertility, spermatozoa, proteomics, ITRAQ, MRM-based



INTRODUCTION Infertility is a major reproductive health problem affecting 10% to 15% of couples, with approximately equal contributions from both partners. The causes of spermatogenic defects in infertile men are multifactorial; many environmental, nutritional, behavioral, and genetic factors affect male fertility. Traditionally, the diagnosis of male infertility depends on a descriptive evaluation, with an emphasis on sperm concentration, motility, and morphology. More than 80% of samples from infertile men show low sperm motility,1 and as such are defined as asthenozoospermia. However, these clinical parameters are not always relevant to understand the etiology of male infertility. It is generally accepted that 25% of male infertility cases have no identifiable cause.2 Clinical and laboratory evidence also indicates that sperm dysfunction is not always apparent with conventional semen analysis, and that these dysfunctions can lead to infertility.3−6 As the male gamete is transcriptionally and transitionally quiescent, the identification and characterization of differentially expressed proteins on spermatozoa from fertile and infertile men can help in the elucidation of the etiology of male infertility and its diagnosis. Proteomics is emerging as a tool for defining specific protein profiles in male reproductive biology. Recent advances in proteomic technology, particularly mass spectrometry, have © XXXX American Chemical Society

produced valuable tools for studying the protein compositions of sperm cells and seminal plasma.7−13 An in-depth understanding of the sperm proteome would be beneficial to the elucidation of the roles of sperm proteins in the regulation of motility, capacitation, acrosome reaction, and fertilization, in addition to establishing biomarkers for male infertility. A combined approach of vectorial labeling, differential extraction, and 2-dimensional electrophoresis of human sperm surface proteins has led to the identification of novel sperm molecules that could be potential candidates for immuno-contraception.14 In this study, proteomic analysis was used to investigate sperm protein profiles, and to identify potential markers for male infertility from samples obtained from 3 different groups of men: fertile men (pool of 2 different groups), normozoospermic men consulting for infertility at a health institution providing secondary care to infertile couples, and normozoospermic men with a history of unsuccessful in vitro fertilization (IVF) treatment provided by a tertiary care fertility clinic. Proteomic analyses of sperm proteins have previously been performed in order to understand the etiology of male infertility; however, in this study, we performed the first Received: March 18, 2014

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dx.doi.org/10.1021/pr501031x | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

Article

Figure 1. Experimental design and schematic diagram of the workflow used in this study. Equal amounts of sperm protein (40 μg) from 2 groups of fertile donors (n = 3 each), normozoospermic men consulting for infertility (infertile) (n = 6), and normozoospermic men with an impaired capacity for fertilization (IVF-failure) (n = 4) were pooled separately. The two pools of fertile donors were labeled with 114 and 115 iTRAQ labels, and infertile and IVF donors were labeled with 116 and 117 iTRAQ labels. The labeled samples were pooled and were subjected to a strong cation exchange chromatography to remove the excess label. Liquid chromatography−MS/MS was subsequently performed for protein identification and quantification. Targeted proteins were selected for multiple reaction monitoring analysis (MRM). According to time of elution and the m/z of the precursor ion (selected in Q1), the precursor is fragmented (in Q2) and selected fragment ions are monitored (detector after Q3) and quantified, by translating the signals into “area under curve” values (Multiquant software).

Biological Material

quantitative proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) labeling, and LC−MS/MS to identify proteins that were deregulated in fertile vs. infertile groups. Further validation of the observations was obtained by multiple reaction monitoring-(MRM) based and Western blot analysis. Taken together, our results show that changes in sperm protein profiles characterize both couples consulting for infertility at the secondary care level in addition to couples with documented in vitro fertilization failure.



Proteomic analyses were performed on semen obtained from three categories of donors: fertile men, men consulting an infertility clinic (infertile), and men who failed to fertilize eggs during IVF procedures (IVF failure). Men who had fathered a child within the last two years were considered fertile. Semen samples from men who had not fathered a child after at least 12 months of unprotected intercourse were obtained from the clinical andrology laboratory of our institution (Québec, Qc, Canada). Men with a history of IVF failure were selected from couples with at least one collected mature oocyte selected on the basis of usual morphological criteria. Only couples undergoing conventional IVF procedures were included in this study; ICSI cases were excluded. In vitro fertilization-failure was defined by the absence of pronuclei in all oocytes 12−18 h postinsemination in vitro. Aliquots of semen samples processed for IVF procedures were used in this study. All donors recruited to this study were normozoospermic in accordance with World Health Organization (WHO) guidelines (WHO Laboratory Manual for the Examination and Processing of Human Semen, 5th ed; World Health Organization: Geneva, 2010). Spermatozoa

MATERIALS AND METHODS

Ethics Statement

Human semen samples were obtained with informed written consent from a panel of healthy normozoospermic donors and patients suffering from idiopathic infertility associated or with an impaired capacity for fertilization. All experiments were conducted with the approval of the Laval University Ethics Committee for Research on Human Subjects. B

dx.doi.org/10.1021/pr501031x | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

Article

peptide was prepared from the stock solutions and used to reconstitute the samples after tryptic digestion for relative quantification. LC−MRM Analysis (QTRAP). Two hundred nanograms of peptides (in 2 μL) was analyzed on an AB Sciex 5500 QTRAP hybrid triple quadrupole/linear ion trap mass spectrometer with a nanospray ionization source equipped with a Nano LC Ultra system supported by Analyst 1.6. The analytical method was developed by using Skyline v1.3. LC−MRM/MS analyses were performed using three transitions on two peptides for each of the target proteins, and quantification was based on the relative areas of the SIS and endogenous peptides by using Multiquant software v2.1. The MRM transition that gave the highest area counts was used for the quantitation, with the other two transitions acting as qualifier transitions to confirm peptide retention times and the fragment ion ratios. A blank solvent injection was run between biological samples to prevent sample carryover on the HPLC column. The samples were injected in random order and analyzed in duplicate.

were pelleted by centrifugation at 800g and washed twice in Dulbecco’s phosphate buffer (D-PBS; Gibco-BRL). Spermatozoa pellets were frozen at −80 °C until use. To avoid interindividual variations when comparing the proteomes of the three categories of donors, pools of semen from men from each group under study were analyzed by iTRAQ. Two different pools of 3 fertile donors were analyzed in parallel. The iTRAQ results were compared between these two pools as well as with pools of semen donated by 4 men consulting for infertility, and with samples from 6 men with an impaired capacity for fertilization. The protocol followed is illustrated in Figure 1. For subsequent validation of individual proteins, the above individual samples and additional fertile control samples (total n = 13), the above individual samples and additional sperm samples from IVF failure patients (total n = 14), and the above individual samples and additional infertile sample (total n = 8) were analyzed. Protein Preparation

Proteins were extracted in 50 mM ammonium bicarbonate buffer containing 0.5% sodium deoxycholate, 50 mM dithiothreitol (DTT), and protease inhibitor. Samples were sonicated for 1 s (20 times) then centrifuged at 10 000g for 15 min. The supernatant was precipitated overnight with 5 vol of acetone and resuspended in triethylammonium bicarbonate 0.5 M containing 0.5% sodium deoxycholate. Protein concentrations were determined using the Bradford method.

Western Blot analysis

Ten micrograms of protein from each individual sample of fertile (n =13), IVF failure (n = 14) and infertile8 sperms was used for Western blot analysis. Proteins were immunoblotted with primary antibodies: GAPDHS goat polyclonal antibody (AF6276, Cedarlane Laboratories LTD, ON, Canada) at 1 mg/ mL dilution, PGK2 rabbit polyclonal antibody (ARP53820, Cedarlane) at 1 mg/mL dilution, PIP rabbit monoclonal antibody (EP1582Y, Abcam, ON, Canada), and α-tubulin mouse monoclonal antibody (T6074, Sigma, St. Louis, MO). Goat anti-mouse IgG (1:5000) (v/v), rabbit anti-goat IgG (1:5000) (v/v), or goat anti-rabbit IgG (1:5000) (v/v) were used as secondary antibodies (Cedarlane). Bands were revealed using a chemiluminescence reagent (ECL kit, PerkinElmer, Boston, MA). Results were expressed as a ratio of α-tubulin.

ITRAQ Analysis

Forty micrograms of each cohort was reduced and alkylated, digested with trypsin then labeled with iTRAQ (4 plex) according to the AB SCIEX protocol. Peptides were fractionated by isoelectric focusing into 72 fractions prior to LC−MS/MS analyses. Chromatography. Peptide separation was performed on an Agilent 1200 Nano LC system. Approximately 200 ng from each fraction was desalted on a Zorbax C18 5 μm, 5 mm 300SB trap column and eluted on an analytical 75 μm × 120 mm column filled with Jupiter (Phenomenex) C18 5 mμ 300 Å. Peptides were separated by a linear gradient of 5−35% acetonitrile over 90 min at 300 nL/min. Mass Spectrometry. The MS analysis was performed on a QSTAR XL or a TripleTOF 5600 system (AB SCIEX, Foster City, CA) in an information-dependent acquisition (IDA) mode. Mass spectra were acquired across 400−1600 m/z for 1 s followed by 3 MS/MS of 3 s per cycle. A dynamic exclusion window of 15 s was used. Rolling collision energy was on with CE adjustment for iTRAQ reagent analysis. Data Analysis. Protein/peptide identification and quantification were performed using Protein Pilot Software version 4.5 searching a Uniprot database containing human proteins and common contaminants. Only proteins identified by at least two peptides and with a p-value less than 0.05 were used for quantitation.

Ingenuity Pathway Analysis (IPA)

The differentially regulated proteins (p < 0.01) were overlaid onto a global molecular network developed from information contained in the Ingenuity Knowledge Base (Ingenuity Systems, http://www.ingenuity.com, content version 12402621, release date: 2012-03-09). Networks of these proteins were then algorithmically generated based on their connectivity. Biological functions associated with proteins within the newly formed networks were displayed using the functional analysis feature in the order of their significance to the network. If the significance of the association between the network and the biological function had a p-value 1.2 correspond to overexpression in the IVF-failure group. Values 1.2 correspond to overexpression in the infertile group. Values