Comparative Sperm Proteomics in Mouse Species with Divergent Mating Systems

Abstract

Sexual selection is the pervasive force underlying the dramatic divergence of sperm form and function. Although it has been demonstrated that testis gene expression evolves rapidly, exploration of the proteomic basis of sperm diversity is in its infancy. We have employed a whole-cell proteomics approach to characterize sperm divergence among closely related Mus species that experience different sperm competition regimes and exhibit pronounced variation in sperm energetics, motility and fertilization capacity. Interspecific comparisons revealed significant abundance differences amongst proteins involved in fertilization capacity, including those that govern sperm-zona pellucida interactions, axoneme components and metabolic proteins. Ancestral reconstruction of relative testis size suggests that the reduction of zona pellucida binding proteins and heavy-chain dyneins was associated with a relaxation in sperm competition in the M. musculus lineage. Additionally, the decreased reliance on ATP derived from glycolysis in high sperm competition species was reflected in abundance decreases in glycolytic proteins of the principle piece in M. spretus and M. spicilegus. Comparison of protein abundance and stage-specific testis expression revealed a significant correlation during spermatid development when dynamic morphological changes occur. Proteins underlying sperm diversification were also more likely to be subject to translational repression, suggesting that sperm composition is influenced by the evolution of translation control mechanisms. The identification of functionally coherent classes of proteins relating to sperm competition highlights the utility of evolutionary proteomic analyses and reveals that both intensified and relaxed sperm competition can have a pronounced impact on the molecular composition of the male gamete.

Keywords: acrosome; fertilization; oocyte; sperm competition; translation regulation; zona pellucida.

Fig. 1.

Interspecific mouse sperm proteome comparisons. (A) Venn diagram displaying the overlap of sperm protein identification between species. Greater than 99% of proteins were identified by multiple unique peptides in each species and 78.3% of proteins were identified in at least two species. (B) Frequency distribution of normalized protein abundance estimates in each mouse species. (C) Ranked protein abundance estimates in Mus musculus and corresponding estimates in M. spretus and M. spicilegus. (D) Hierarchical clustering analysis conducted using protein abundance estimates in each species. Dendogram ordering, based on Euclidean distances, recapitulates the phylogenetic relationship of Sarver et al. (2017). Bootstrap probability is indicated and branch uncertainty was assessed with nonparametric resampling (10,000 iterations; bootstrap samples sizes ranged from 0.5 to 1.4). Heatmap ranges from low (yellow) to high (red) abundance.

Fig. 2.

Relative testis size ancestral state reconstruction. Body and testis ancestral states were reconstructed independently to calculate ancestral relative testis size estimates. Lineages associated with the species analyzed in the current study are highlighted in red. Phylogenetic relationships and branch lengths (scaled to nucleotide substitutions) were based on Sarver et al. (2017).

Fig 3.

Protein abundance variation in relation to sperm competition. (A) Soft-clustering analyses were conducted to identify global patterns of protein abundance differences that are associated with interspecific variation in sperm competition. Protein abundance patterns relative to the cluster average are depicted for each protein (purple: high identity; green: lower identity). Deviation in cluster size relative to uniform membership across clusters is indicated; 60 proteins per cluster were expected based on a uniform distribution. (B) Fold enrichment of proteins belonging to significant Gene Ontology Categories relating to sperm head and acrosome, metabolism and flagellum. Significant enrichments are indicated by an asterisk for Clusters 1–4. Enrichment calculations were based on the expected frequency of proteins belonging to a given Gene Ontology category within the sperm proteome as a whole.

Fig 4.

Spermatogenic gene expression and sperm proteome composition. (A) Linear regression analyses of spermatozoa protein abundance estimates in Mus musculus with gene expression levels across successive stages of spermatogenesis. Stage-specific expression values were obtained from Soumillon et al. (2013). All proteins are included which have corresponding gene expression data. (B) Percentage of genes subject to translational repression at the spermatogonia–spermatocyte and spermatocyte–spermatid transition based on Gan et al. (2013). Proteins exhibiting significant abundance differences between low (M. musculus) and high (either M. spretus or M. spicilegus) sperm competition species (orange), proteins exhibiting comparable abundance between low and high sperm competition species (grey) and testis expressed genes identified by Gan et al. (2013) that were not identified by MS/MS analysis in mature sperm (black) are displayed. (C) Stage-specific relative protein abundance relative to spermatogonia, based on Gan et al. (2013), for proteins exhibiting significant abundance differences between low (M. musculus) and high (either M. spretus or M. spicilegus) sperm competition species (orange), the remainder of the sperm proteome (grey) and other testis expressed genes not encoding protein products in mature sperm (black).