UCLA

Hepatitis C virus (HCV) is a major cause of human liver diseases and the mortality associated with chronic infection has been increasing due to lack of effective treatments. Thus, better understanding the functional domains in the virus genome and their contributions to viral-host interactions will shed light on novel drug development.

In an attempt to systematically map the anti-interferon (IFN) functional domains in HCV genome, we established a genetic profiling platform by combining high-throughput mutagenesis and next-generation sequencing. An IFN-α screen performed with a 15-nucleotide random insertion library identified four regions with increased IFN-sensitivity when mutated. Further analyzing the N-terminus of core in a secondary screen with saturation mutagenesis revealed that phenylalanine 24 is essential for inhibiting STAT1 phosphorylation thereby blocking IFN signaling transduction. The genomic IFN-α screen suggested that p7 is a novel immune evasion protein. To interrogate the mechanism that governs p7 counteracting the IFN response, a cDNA library screen of liver-specific interferon-stimulated genes was conducted, and individual effect of 107 genes on p7 mutant virus replication was determined. The screen showed that virus with p7 knockout is more sensitive to IFI6-16 over-expression. Further analysis demonstrated a physical interaction between p7 and IFI6-16, suggesting p7 may target IFI6-16 to actively suppress innate immune response.

The same concept of systematic profiling approach was applied to determine the residues interacting with Daclatasvir, which was identified as an effective NS5A inhibitor. Quantitatively examining the fitness of a saturation mutant library within domain IA of NS5A upon the drug treatment uncovered potential drug-interaction residues. Epistatic interactions among these residues are correlated with genotype-specific differences in drug-sensitivity. Remarkably, the fitness score of all possible substitutions and their drug-sensitivity allow for systematical mapping of the genetic barriers and prediction of evolutionary paths for potentially emerging resistances.

Taken together, we have profiled the HCV genome to define the essential residues for evading host immune responses or mediating drug interactions. We suggest that the genetic profiling platform described in this thesis can be generally applied in interrogating virus-host interactions and chemical-target interactions, which will provide comprehensive knowledge on new therapeutic strategies to overcome persistent HCV infection.