Co-evolving mutations in hepatitis C virus in the context of immune escape against neutralising antibody responses - A bioinformatic workflow for the analysis of co-evolving mutations in viral genomes

Abstract

Rapidly evolving pathogens, such as RNA viruses exploit the high mutation rate to avoid or escape host immune response. Despite a random mutation process, the relatively small size of their genomes imposes evolutionary constraints. Viral evolution hence is characterized by highly connected mutations that arise within the same genome through a random sequential process. In this abstract we present a bioinformatics pipeline that aims at predicting co-evolving mutations within ongoing hepatitis C viral infection which result in a significant advantage for the virus in terms of survival from the adaptive response exerted by neutralizing antibodies. This workflow utilizes the idea of Mutual information to identify pairs of potentially related genomic sites that confer a selective advantage.