A genomic approach of the hepatitis C virus generates a protein interaction map.

The hepatitis C virus (HCV) causes severe liver disease, including liver cancer. A vaccine preventing HCV infection has not yet been developed, and, given the increasing number of infected people, this virus is now considered a major public-health problem. The HCV genome is a plus-stranded RNA that encodes a single polyprotein processed into at least 10 mature polypeptides. So far, only the interaction between the protease NS3 and its cofactor, NS4A, which is involved in the processing of the non-structural region, has been extensively studied. Our work was aimed at constructing a protein interaction map of HCV. A classical two-hybrid system failed to detect any interactions between mature HCV polypeptides, suggesting incorrect folding, expression or targetting of these proteins. We therefore developed a two-hybrid strategy, based on exhaustive screens of a random genomic HCV library. Using this method, we found known interactions, such as the capsid homodimer and the protease dimer, NS3-NS4A, as well as several novel interactions such as NS4A-NS2. Thus, our results are consistent with the idea that the use of a random genomic HCV library allows the selection of correctly folded viral protein fragments. Interacting domains of the viral polyprotein are identified, opening the possibility of developing specific anti-viral agents, based on their ability to modulate these interactions.