Final Report Summary - VIRMUT (Variability in the mutation rate of RNA viruses)
RNA viruses are known to exhibit extremely high rates of spontaneous mutation, but these rates vary amply and the causes of such variability have remained poorly understood. In this project, we have addressed whether spontaneous mutations tend to occur preferentially at some viral genome sites or regions, to what extent host factors determine viral mutation rates, and whether RNA viruses with different genome properties mutate differently. Using selection-free in vitro and cell culture systems, we have shown that HIV-1 and hepatitis C virus exhibit highly variable mutation rates across their genomes and that this variation is mainly determined by template-based factors such as sequence context and, in the case of HIV-1, RNA structure and host-mediated genome editing. We have also unveiled other, non-polymerase determinants of viral mutation rates. For instance, we have found that changes in lysis time modulate the rate of mutation accumulation in experimental populations of bacteriophage φX174, and we have found that the mutation rate of vesicular stomatitis virus varies according to cell type. We also assessed how vesicular stomatitis virus mutates in single cells, allowing us to establish links between per-cell replication kinetics and diversity production. Such host dependencies show the importance of quantifying mutation rates in vivo. We have taken advantage of population genetic principles to achieve this goal and infer the mutation rate of HIV-1 within patents, using next generation sequencing. This has revealed an extremely high mutation rate, which is mainly driven by host-mediating genome editing. Interestingly, the HIV-1 mutation rate in vivo is negatively correlated with clinical predictors of disease progression. We have applied similar methods to hepatitis B virus, which has revealed that the standard base analog therapy has a mutagenic effect on the virus, and can thus increase its genetic diversity. Our work also included a human adenovirus, for which we have provided the first genome-wide mutation rate estimation using a recently developed high-fidelity deep sequencing method. Finally, we have also demonstrated that mutation rates correlate negatively with genome size across RNA viruses. Viral mutation rates are of utmost importance for understanding the ability of viruses to evade the immune system, evolve drug resistance, or generate epidemic outbreaks. Unveiling key determinants of viral mutation rates should help us better understand viral evolution and pathogenesis.