VirHostNet: a knowledge base for the management and the analysis of proteome-wide virus–host interaction networks

Navratil, Vincent; de Chassey, Benoît; Meyniel, Laurène; Delmotte, Stéphane; Gautier, Christian; André, Patrice; Lotteau, Vincent; Rabourdin-Combe, Chantal

Eukaryotic cells express a large panel of proteins that coordinately participate to the cellular machinery through a highly connected and regulated network of protein-protein interactions (1) . Physical architecture of model organisms and human cellular protein networks exhibits a strong robustness against random failures, and strikingly a high sensitivity to targeted attacks on highly connected and central proteins, also called 'hubs' (2, 3) . Cellular protein network is not static and its robustness may change dynamically according to various factors like tissue and cell-line origins, signals received by cellular environment or more specifically during viral infections (4) . Replication and pathogenesis of viruses depend on a complex interplay between viral and host cellular proteins both acting through a complex network of protein-protein interactions. In order to evade the cell innate immune response and/or to favour their own replication and transmission, viruses have developed strategies to hijack central functions of the cell (5) (6) (7) . Viruses also use intra-viral, i.e. virus-virus, protein-protein interactions for virion assembly or viral egress from the cell. Accumulation of functional perturbations associated with such virus-virus and virus-host protein-protein interactions may lead to severe and complex diseases, like the development of cancers (8, 9) . From a systems biology perspective, a deeper understanding of infectious diseases may rely on an exhaustive characterization of all potential interactions occurring between proteins encoded by viruses and those expressed in infected cells (10) . Thus, integration of all protein-protein interactions into an infected cellular network, or 'infectome', is a great challenge that may provide a powerful framework for virtual modelling and analysis of viral infection.