Nicola Bernabo, Mauro Mattioli and Barbara Barboni
Mammalian spermatozoa gain their fertilizing ability only after they reside within the female genital tract, where important physical-chemical modifications, the “capacitation”, occur: the cytoskeleton reorganizes, the membranes become more instable and tend to fuse each other, the protein phosphorylation pattern changes, a new motility pattern, the hyperactivated motility, appears. These events are regulated by several signal transduction pathways, whose failure could have negative implication for fertility. Unfortunately, frequently it is impossible to issue a diagnosis, as in the case of “idiopathic infertility”. In our opinion, this inability could be not due to the scarcity of molecular data, but to the difficulty to manage them. Indeed, spermatozoa (like other cells) are constituted by heterogeneous components that interact collectively and nonlinearly, giving rise to a complex behavior in which the whole system is more than the sum of its single components. To overcome this problem, we adopted a holistic approach based on computational modeling. We represented the events occurring during human spermatozoa capacitation as a biological network of nodes (the molecules) and links (the interactions). Topological analyses of network showed that it has a scale free topology and that it is characterized by a high signaling efficiency and robustness against random failure. Interestingly, we found that the same topology is shared with other organisms, sea urchin and Caenorhabditis elegans, belonging to different Phyla and characterized by very different reproductive ecology. Further, we modelized boar sperm capacitation, separating the molecules depending on their subcellular compartment: model analysis suggested that actin cytoskeleton is not only a mechanical support, but it could participate to the coordination of the capacitation-related events. This hypothesis was, then, successfully validated in an in vitro experiment. In conclusion, from computational models it is possible to infer important information not otherwise obtainable, then improving the understanding of the spermatozoa biology complexity.
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