Hepatitis C virus and the innate immune response: from transcriptome to function

Rockefeller University, New York NY

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Abstract

DESCRIPTION (provided by applicant): Current therapy for chronic hepatitis C virus (HCV) infection consists of treatment with a combination of interferon (IFN) and the antiviral prodrug ribaviron. IFNs are a well-characterized component of the innate immune system that inhibits a wide range of viruses through the activities of interferon-stimulated genes (ISGs). Surprisingly, the majority of known ISGs are poorly characterized and their mechanism of antiviral action undefined. A previous antiviral ISG screen with the lab uncovered a role of the cellular protein Mov10 in HCV inhibition. Mov10 will be further defined with respect to their antiviral activity by identifying what stages in the HCV lifecycle are affected through various virological, biochemical and computational approaches. This work will clarify the role of Mov10 in viral infection and add to our current understanding of virus-host interactions. In addition a lack in mechanistic understanding of known ISGs we continue to lack a hierarchal view of the ISG induction network. Stimulation by IFN results in the establishment of a complex network of ISGs that is likely controlled by feedback loops and threshold effects. While many genes are known to respond to IFN, little is known of how the complex network of ISGs is established and controlled. We propose to address this gap in scientific knowledge by performing transcriptome analysis on cells treated with IFN in a dose- and time-dependent manner using the RNA-seq method. In this proposal, primary human hepatocytes, the natural reservoirs for HCV, will be used with an emphasis on low IFN concentrations. PUBLIC HEALTH RELEVANCE: Hepatitis C virus chronically infects nearly 170 million people worldwide. Therapeutic options for chronic hepatitis C are extremely limited, poorly tolerated, and the mechanisms are poorly understood. Here we propose to investigate the cellular interferon response in hopes that understanding the molecular mechanisms by which predictive biomarkers influence hepatitis C treatment outcome may help guide additional antiviral drugs.