Hepatitis C virus (HCV) infection is characterized by a high rate of chronicity and concerns 170 millions of individuals worldwide. Chronically infected patients present liver injury essentially mediated by immune mechanisms and metabolic disorders associated with hepatic steatosis, fibrogenesis and insulin resistance to various extent (Negro, 2006; Moradpour et al, 2007). Long-term-infected patients have a high risk of developing cirrhosis and hepatocarcinoma, but despite considerable efforts, molecular basis of HCV pathology remains poorly understood. HCV genome is a positive-strand RNA of 9.6 kb encoding a polyprotein that is post-translationally processed into structural (CORE, E1, E2 and p7) and non-structural (NS2, NS3, NS4A, NS4B, NS5A and NS5B) proteins (Appel et al, 2006). HCV variants have been classified into six genotypes with biological and antigenic differences. Whereas infection by all genotypes is associated with insulin resistance and fibrosis, a correlation between hepatic steatosis severity and viral replication is preferentially observed for genotype 3. Genotypic differences also correlate with interferon sensitivity, with genotypes 2 and 3 responding better to combined interferon and ribavirine therapy. We focused here on HCV genotype 1b, which is associated with insulin resistance, fibrosis, mild steatosis and poor sensitivity to treatment (Lonardo et al, 2004; Strader et al, 2004).
The rapidly growing knowledge of protein–protein interaction (PPI) networks (interactome) for human, model organisms and host–pathogen begins to provide network-based models for diseases. In a network approach, viral pathogenesis can be viewed as the expression of new constraints on the protein network imposed by the virus when connecting to the cellular interactome. Identification of topological and functional properties that are lost or deregulated, or that emerged in the ‘infection network’, becomes a major challenge for a systems understanding of viral infection (Tan et al, 2007).
High-throughput yeast two-hybrid (Y2H) screens of human cDNA library (Calderwood et al, 2007) and computation-based analysis (Uetz et al, 2006) have been used previously to study Epstein–Barr virus (EBV), Kaposi sarcoma herpes virus and varicella zoster virus interactions with host cell factors. Analysis of virus–human protein inter-interactome network revealed that host interactors tend to be enriched in proteins that are highly connected in the cellular network (Calderwood et al, 2007; Dyer et al, 2008). These hub proteins are thought to be essential for the normal cell functioning and during pathogenesis.
Several laboratories have joined their efforts to develop infection mapping project (I-MAP). The goal of I-MAP is to provide a comprehensive view of viral infections at the protein level by mapping the interactions of a large number of viral proteins with host proteins. Screening and mapping have been designed to address specific questions, such as virulence/attenuation, species barrier, identification of therapeutic targets, chronicity and the risk of cancer development.
Here, a proteome-wide mapping approach of interactions between HCV and cellular proteins was performed to provide a comprehensive view of viral infection (Figure 1A). A viral ORFeome was first generated that included ORFs encoding all full-length mature proteins and several protein domains of genotype 1b strain (Supplementary Figure S1). These viral baits were screened against human cDNA libraries using a highly stringent Y2H assay (IMAP Y2H data set). Together with interactions extensively mined and curated from the literature (IMAP LCI data set), this comprehensive host–virus infection network was integrated into a reconstructed human protein–protein interactome. Analysis of the ‘infection network’ (V-HHCV; Figure 1A) revealed topological features of cellular interactors and identified functional pathways related to viral biology and pathogenesis.