A FIRST STEP TOWARD THE IDENTIFICATION OF MAMMALIAN SPERMATOZOA ITERACTOME.

The study of unexplained infertility of male origin is one of the most important challenges in the reproductive medicine of post genomic era. Unfortunately, despite the continuously growing effort of researchers, it remains unresolved 1. This causes the worsening of living conditions and of physical and psychological wellness of a large number of couples and determines the rising of healthcare costs for National Health Services. Recently, the availability of high throughput technologies, the so called –omics, has opened new perspective in clarifying this issue and posed new problems, related to the management of big data. On this basis, the adoption of a computational modelling-based strategy could offer a reliable tool to manage the continuously growing data on male gametes physiology 2,3. Here, we realized a computational model representing the whole ensemble of molecules present in spermatozoa, linked by their interaction. As first, we collected the data from papers indicized in PubMed referred to proteomic studies of sperm biology. Then, staring from the list of identified proteins, we carried out a pathways reconstruction analysis (Reactome FI). All the obtained pathways were used to realize a network-based computational model by using Cytoscape 3.3, called Mammalian Sperm Interactome (MSI), constituted by nodes, representing the molecules, linked by their interactions. Whole MSI is constituted by 7052 nodes, 15587 links, and 104 connected components. In particular, we identified a Main Connected Component (MCC_MSI) that accounts for 6525 nodes and 14944 links. The analysis of MCC_MSI showed that it is characterized by a scale free topology that follows the Barabasi-Albert (BA) model. The number of links per node (the node degree) follows a power law, with a negative exponent (y = a x-1.639, R2 = 0.826), and the clustering coefficient (cc), which is a measure of the network tendency to form clusters, is low (cc = 0.152) and unrelated with the node degree (R2 = 0.259). In addition, MCC_MSI displays a small world architecture: the averaged no. neighbours, which represents the mean number of connection of each node, is 3.337 and the characteristic path length, which gives the expected distance between two connected nodes, is 7.227. The analysis of MSI network topology has led us to infer important characteristics of the biological system: • the network is robust against random failure: indeed a random damage has the higher probability to affect the most frequent nodes, i.e. the less linked ones, with negligible consequences on network topology; • the messages will spread within the networks quickly and efficiently thus allowing to male gametes to adapt efficiently to the intra and extracellular stimuli. In addition, it will be possible to identify the nodes that shows a higher level of control within the networks, thus potentially offering new perspectives in the study of molecular target for diagnostics and therapeutics of male infertility of unknown origin