Metabolic Properties of Mouse Spermatogenesis Defined through Constraint-Based Modeling

Genome-scale metabolic models provide the means to interrogate computationally biological connectivity between genes, reactions, and the associated metabolites. Exploring the process of spermatogenesis through constraint-based metabolic modeling has not been carried out to date, leaving a gap in our understanding of metabolic properties and vulnerabilities that may exist in this process. In this study, we generated stage-specific metabolic models of spermatogenesis by integrating mouse transcriptomic data corresponding to different developmental stages into a murine genome-scale model, iSS1393. The generated models correspond to whole testis tissues at ages ranging from day 6 (post-partum) to adult (day 38). At day 6, the network model accounted for 932 genes, 2,834 reactions, and 1,443 metabolites. Although the numbers of genes and reactions decreased during the course of puberty by ~10%, a hub of 43 highly connected reactions, involving Na⁺/Cl^--dependent system B amino acid transports (ATB⁰⁺), selenoamino acids, and hyaluronan metabolism, appeared with the onset of the first meiotic division at day 12. We validated our models by comparing the results of in silico single-gene deletion with publically available experimental data, then carried out in silico double gene deletions to predict gene interactions that uniquely affect spermatogenesis. Out of ~970,000 gene pair deletions tested, 25 pairs predicted synthetic lethality to testis biomass production, and 248 gene pairs synthetically reduced testis biomass output by more than 50% without affecting other tissues significantly. Of these, we identified drugs targeting 14 synthetic pairs, some of which enriched in Glutathione metabolism. Our results provide a systems level characterization of mammalian spermatogenesis, identifying unique vulnerabilities of testis metabolism with respect to gene deletions as well as providing information that can aid identifying genetic causes of infertility. Furthermore, our findings can set forth strategies for combinatorial use of known drugs for contraception.