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The first part will be on the application of Next-Generation Sequencing (NGS) as a deep sequencing approach to study viral evolution. NGS has redefined the modus operandi in both human and microbial genetics research, allowing the unprecedented generation of very large sequencing datasets on a short time scale and at affordable costs. We have used this technology to study evolution of viral diversity from the founder virus, and also to inform evolution of immune escape in subjects followed longitudinally. A key challenge in NGS technology is the bioinformatics and statistical analysis of the information generated to ensure high quality in the analyses and interpretation of large, error-prone datasets. The increasing size of the NGS datasets being generated, short read lengths, and significant technical error rates carried with each of the emerging technologies will continue to demand sophisticated and efficient support systems. Here I will discuss current bioinformatics and computational modeling approaches for the analysis of NGS data, with particular focus on hepatitis C (HCV) and B viruses.
In the second part, I will present recent studies on founder virus analysis in HCV. New HCV infections are on average initiated by only 1-3 unique ‘founder’ variants. This reduction in genetic diversity may be a potential vulnerable period in HCV infection and offer a new vaccine strategy for targeting founder variants. However, as yet there has been very little understanding of how rapidly or by what amount these founder viruses evolve. I will present data on the evolution of the HCV founder in response to CD8+ T cell driven pressure in both resolving and persistent infections. These data suggest that the HCV founder virus has a rapid turnover and that in HCV, rapid adaptation to cellular immune response is a major driving force in early founder virus evolution.
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