Protein profiling of testicular tissue from boars with different levels of hyperactive sperm motility

Abstract

Hyperactive sperm motility is important for successful fertilization. In the present study, a proteome profiling approach was performed to identify the differences between Landrace boars with different levels of hyperactive sperm motility in liquid extended semen. Two contrasts were studied: (i) high versus low levels of sperm hyperactivity at semen collection day and (ii) high versus low change in levels of sperm hyperactivity after 96 h semen storage. Testicular samples were analyzed on a Q Exactive mass spectrometer and more than 6000 proteins were identified in the 13 samples. The most significant differentially expressed proteins were mediator complex subunit 28 (MED28), cell division cycle 37 like 1 (CDC37L1), ubiquitin specific peptidase 10 (USP10), zinc finger FYVE-type containing 26 (ZFYVE26), protein kinase C delta (PRKCD), actinin alpha 4 (ACTN4), N(alpha)-acetyltransferase 30 (NAA30), C1q domain-containing (LOC110258309) and uncharacterized LOC100512926. Of the differentially expressed proteins, 11 have previously been identified as differentially expressed at the corresponding mRNA transcript level using the same samples and contrasts. These include sphingosine kinase 1 isoform 2 (SPHK1), serine and arginine rich splicing factor 1 (SRSF1), and tubulin gamma-1 (TUBG1) which are involved in the acrosome reaction and sperm motility. A mass spectrometry approach was applied to investigate the protein profiles of boars with different levels of hyperactive sperm motility. This study identified several proteins previously shown to be involved in sperm motility and quality, but also proteins with no known function for sperm motility. Candidates that are differentially expressed on both mRNA and protein levels are especially relevant as biological markers of semen quality.

Findings

The quality of semen in terms of fertilization rate is critical for efficient use of artificial insemination, and parameters that can predict the fertilization rate of semen samples are valuable. One important parameter is the level of hyperactive sperm motility, which is a movement pattern of spermatozoa after capacitation, normally taking place in the oviduct. The increased vigor in swimming movement makes the sperm more efficient in ascending the oviduct and penetrating the zona pellucida [1]. Computer-Assisted Semen Analysis (CASA) is an objective examination of semen characteristics [2] and we have previously shown that several CASA parameters defining hyperactive sperm motility was correlated to total number of piglets born [3]. Moreover, the Landrace pig breed developed a more hyperactive swimming pattern during storage compared to the Duroc breed, which is relevant as semen is usually stored before insemination. However, if hyperactive sperm motility is acquired too early, sperm cells may deplete their energy and die before reaching oocytes.

Genetic factors related to fertility are interesting as they can be used to ensure good semen quality. We have previously identified differentially expressed (DE) genes in testis related to levels of hyperactive sperm motility [4]. The aim of the current study was to gain further insights into the molecular background causing sperm hyperactivity by performing protein profiling of the same testicular samples as previously used in mRNA expression. This allowed us to establish differentially expressed proteins related to hyperactive sperm motility as well as investigate the correlation of the proteome to the transcriptome.

The animals, ejaculate samples, testicular tissue samples and CASA analysis used in this study have been described [4]. Data are also available in Additional file 1. From the CASA analysis, hyperactive motility for each single sperm cell track were defined as VCL > 97 µm/s, ALH > 3.5 µm, LIN < 32% and WOB < 71%. Testicular tissue was collected after slaughter and immediately frozen in liquid nitrogen and stored at -80 °C until protein extraction. Protein extraction was done using the Qproteome Mammalian Protein Prep kit [Qiagen, Germany] and the protocol “Purification of protein from animal tissues using the Qproteome Mammalian Protein Prep kit and the TissueRuptor”. Methods used for in-gel digestion, peptide clean-up and liquid chromatography-mass spectrometry are also described in detail in Additional file 1. Peak lists were generated from raw data files by the MaxQuant software and proteins were identified from the Uniprot porcine reference protein database. We performed protein DE analyses using the Bioconductor Differential Enrichment analysis of Proteomics data (DEP) package [5] and the Perseus software [6]. The DEP workflow started from MaxLFQ values obtained from MaxQuant, which are intensity values for each protein in each sample. Filtering removed proteins that were potential contaminants or originated from reverse sequences. Only proteins that were missing in maximum one sample were kept and normalization was done using the Variance Stabilizing Normalization approach [7]. Missing values were present in some samples due to low intensities, and these were imputed using random draws from a Gaussian distribution centered around a minimal value (option “MinProb”). Correction for multiple testing was done by the R package fdrtool [8] and DE was considered significant with an FDR of 0.05 and a log2 fold change of 0.6 (corresponding to a fold change of 1.5 on a linear scale). A workflow in Perseus v.1.6.7 was created starting from the same MaxLFQ values. Proteins that were only identified by a modification site, potential contaminants, or reverse sequences were removed. The dataset was log2 transformed and filtered so that each protein was present in at least 70% of the samples. Two-sample t-tests were performed for both contrasts. A p-value of 0.05 with log2 fold change of 0.6 was applied to indicate significance.

Two different contrasts were examined in this study: (i) high versus low sperm hyperactivity at collection and (ii) high versus low change in levels of hyperactivity after 96 h storage (Table 1). Samples L2 and L11 are from the same boar and have extreme values in both contrasts, the same is the case for samples L7 and L14. Sample L2/L11 clustered as an outlier in both contrasts by hierarchical clustering and was excluded from DE analyses. The mean (± SD) hyperactivity values for the subsequent high and low groups were 14.5% (± 1.7) (n = 4) and 1.7% (± 0.2) (n = 3) for contrast (i) and 15.1% (± 3.0) (n = 3) and 2.8% (± 0.6) (n = 4) for contrast (ii). The data analysis obtained 66,366 unique peptides, which were assembled into 6,362 proteins (see Additional file 2).

Table 1 Sperm hyperactivity measurements for the different boars included in this study

Using the DEP analysis, 32 and 16 proteins were found DE for contrasts (i) (see Additional file 3: Table X1) and (ii) (see Additional file 4: Table X1), respectively. The most significant DE proteins for contrast (i) were mediator complex (MED28), cell division cycle 37 like (CDC37L1), zinc finger FYVE-type containing 26 (ZFYVE26), ubiquitin carboxyl-terminal hydrolase (USP10) and uncharacterized LOC100512926 (all with q-value 1.76e−13). For contrast (ii), the most significant DE proteins were N(alpha)-acetyltransferase 30 (NAA30) and C1q domain-containing (LOC110258309) (both with q-value of 9.46e−13).

Using the Perseus analysis procedure, 44 proteins were DE in contrast (i) (see Additional file 3: Table X2) and 87 proteins in contrast (ii) (see Additional file 4: Table X2). The most significant DE protein of contrast (i) was protein kinase C (PRKCB) (P-value = 0.0004), whereas for contrast (ii), the most significant protein was actinin alpha 4 (ACTN4; P-value = 0.0003).

Results obtained by both DEP and Perseus workflows showed that nine and five proteins were significantly DE for contrast (i) and (ii), respectively, using both analysis methods (Table 2). Comparing results for the two different contrasts indicated that 10 proteins are relevant for sperm hyperactivity both at collection and after 96 h storage (Table 3). Of these, PRKCB, parvalbumin alpha (PVALB), sphingosine kinase 1 (SPHK1) (Table 2), ACTN4 and tubulin alpha chain (TUBA8) (Tables 2 and 3), have previously been associated with sperm quality. PRKCB is a protein kinase involved in sperm motility and acrosome reaction [9]. The ACTN4 gene was previously found up-regulated in Landrace boars with high sperm DNA fragmentation index [10], where the boars were from the same population as the current study. PVALB has previously been associated with sperm motility in carp [11] whereas TUBA8 levels were associated with reduced sperm motility in human [12]. SPHK1 was implicated to be involved in the acrosome reaction in mice [13].

Table 2 Differentially expressed proteins found in both analysis methods

Table 3 Differentially expressed proteins found for both contrast (i) and (ii)

By comparing results of the proteome profiling to those previously obtained in transcriptome profiling of the same samples [4], 10 were in common for contrast (i) and one for contrast (ii) (Table 4). Some of these candidates have previously been shown to have a role in spermatogenesis and sperm motility, supporting a role also in hyperactive motility. Knock-out of the serine/arginine-rich splicing factor 1 (SRSF1) in mice showed that this protein is essential for sperm motility [14]. Tubulin gamma 1 (TUBG1) is suggested to have an important role in sperm motility in human samples [15]. Solute carrier family 12A7 (SLC12A7) is a NaCl cotransporter [16], making it an interesting candidate for sperm hyperactivity as Na ions are necessary for sperm motility, whereas WD repeat domain 13 (WDR13) is regulated by genes essential to normal spermatogenesis [17]. SPHK1 is already described above as it is one of the proteins identified by both analysis methods. The exact function of the other proteins listed in Table 4 needs to be further investigated, however based on their differential expression both on mRNA and protein level, we suggest an important role in hyperactive sperm motility.

Table 4 Complementary protein and transcriptome results for high versus low hyperactivity at collection (i) and after 96 h storage (ii)

In conclusion, we identified DE proteins in testicular samples from pigs related to levels of hyperactive sperm motility. Eleven candidates were significant both on protein and mRNA level and are highly relevant as potential biomarkers for pig fertility.