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

Beside table representation of protein-protein interactions, a more dynamic and interactive network visualization tool was specifically developed for graph representation of infection networks. This new network visualisator was fully implemented in Jung 2.0 (http://jung.sourceforge.net) as a Java Web applet. It efficiently takes into account viruses and host nodes dichotomy for both graph rendering (colour of nodes) and navigation (host and viral neighbours). The visualisator provides also sliders to dynamically filter graphs based on the number of PMIDs and experimental procedures used to identify interactions. Additional features are also provided to draw protein node size according to the number of viral or host interacting partners (i.e. their degree into the virus-virus, virushost, host-host networks) or to highlight targeted proteins. As a case study, we built a protein sub-network view of the mTOR KEGG signalling pathway that has been found significatively enriched in targeted proteins (Supplementary Table 4 ). Indeed, the modulation of PI3K-Akt-mTOR signal transduction pathway by viruses has been shown to play a crucial role in inhibition of apoptosis, cell survival, cell transformation, viral replication and viral assembly (40, 41) . To identify and compare how viruses interplay with this network, virus-host protein interactions annotated by VirHostNet were added. This mTOR-infection network is composed of 42 cellular interacting proteins (blue nodes), 10 viral proteins (coloured nodes according to viral taxonomy), 84 host-host (blue edges) and 14 virus-host (red edges) physical proteinprotein interactions ( Figure 5 ). Protein network visualization showed that cellular proteins of this pathway are highly inter-connected in contrast to the classical representation given by the KEGG pathway, underlying the extreme complexity and regulation of this pathway. Moreover, graph visualization allows identifying viral proteins targeting multiple cellular proteins (e.g. NS5A protein interacting with AKT1, PDPK1 and PIK3CB) and reciprocally cellular proteins interacting with multiple viral proteins (e.g. HIF1A interacting with LANA of Human Herpes Virus 8 type P and X protein of Hepatitis B Virus). Hence, the VirHostNet interface allows users to visualize protein interaction networks associated to any kind of GO term, KEGG pathway, list of proteins or keywords and to analyse how they interplay with viruses.