Computational modeling in male reproduction

In recent years we are seeing an increase in male infertility, with important negative consequences on our present and future life, such as population ageing, increase in expenses for National Health Services, worsening of sexual, personal, and social strains. Unfortunately, in about 50% of cases, it is impossible to perform an adequate diagnosis. This is likely due to the specific biology of male gametes. In fact spermatozoa gain their fertilizing ability only after they reside within the female genital tract, where important physical-chemical modifications, the "capacitation", occur. At present many aspects of this process are still unsatisfactory known. In our opinion this could be the reductionist approach adopted until now in the study of this topic. Then, in consideration that spermatozoa are constituted by a network of heterogeneous components that interact collectively and nonlinearly, characterized by a complex behaviour in which the whole system is more than the sum of its single components, for the first time we adopted a computational modeling-based approach to study sperm capacitation. We realized the biological network of molecular event occurring during this process in Human sperm. As a result, we have found that spermatozoa are an ideal candidate to this approach because their molecular composition is stable, it is possible to manage them outside the organism, and it is possible to in vitro test the achievement of capacitation. Topological analyses of network demonstrated that capacitation is characterized by a high signaling efficiency and robustness against random failure. In a further experiment we modelized boar sperm capacitation, separating the molecules depending on their subcellular compartment. The analysis of model suggested that actin cytoskeleton is not only a mechanical support but it could exert a key role in coordinating the capacitation-related biochemical events. This hypothesis was, then, successfully validated by a traditional in vitro approach. More recently, we compared the models representing sperm activation in sea urchin, Caenorhabditis elegans and Human. It was found that these organisms share a similar signalling and metabolism architecture, reasonably because of the maintenance of ancestral mechanisms, characterized by important biological features such as robustness against random failure and signalling fastness, rapidity and efficiency. In conclusion, from computational models it is possible to infer some important information not otherwise obtainable, and leading to achieve important goals, such as the understanding of complex interactions that characterize spermatozoa biology, potentially opening new perspective in drug discovery and diagnosis and therapy of male infertility