Understanding the body's response to infection is an important part of disease research. The responses to viral infection in individual tissues is commonly studied using gene expression microarrays, and the blood has proven to be a particularly useful tissue in the study of a number of infections. In this dissertation, we use computational analysis of a number of microarray datasets to understand the global effects of chronic Hepatitis C virus (HCV) infection on the blood of infected patients, and we discuss new computational techniques which have been developed to analyze this data. We find that, during chronic infection with HCV, pathways associated with the innate immune response were significantly up-regulated in peripheral blood mononuclear cells (PBMCs), and that upon stimulation with a double-stranded RNA analog, PBMCs from HCV patients displayed a much more pronounced induction of the Interferon (IFN) pathway. In order to understand the underlying mechanisms of this IFN signature, we used direct analysis of IFN signaling by in vitro stimulation to identify key members of the IFN pathway. We showed that both the type I and type III IFN families stimulate a large set of antiviral genes, and that many of these genes were also found to be stimulated during chronic HCV infection. Finally, we propose two new computational methods for the analysis of gene expression data, which we use to characterize the activation of biological pathways during infection, and to identify the cell-specific effects of infection with HCV. These results further our understanding of the effects of chronic HCV infection, and help to define the role of IFN signaling in the body's response to chronic infection.
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