bioRxiv2025
Lethal mutagenesis is a strategy to achieve viral extinction by drugging viral mutation rates beyond an extinction threshold. Accurate estimation of the extinction threshold is critical, as elevating viral mutation rates near, but not past this threshold increases the likelihood of mutations that could result in drug resistance, vaccine escape, or increased pathogenesis. Traditional models of lethal mutagenesis rely on the Poisson distribution, which assumes a uniform mutation rate across individuals. Yet, RNA viruses like influenza A virus (IAV) can have varied mutation rates due to mutations in the polymerase complex. This variability suggests that lethal mutagenesis models incorporating mutation rate diversity, such as ones using the gamma-Poisson distribution, may be more accurate for RNA viruses. Poisson models assume count data have equal mean and variance, while gamma-Poisson counts are overdispersed (variance greater than mean). Here we provide experimental data showing that IAV mutations are overdispersed, indicating that the gamma-Poisson distribution is more appropriate for modeling IAV mutations. Modeling of lethal mutagenesis using the gamma-Poisson distribution reveals that the degree of overdispersion is critical in determining survival or extinction. Increased overdispersion shifts the extinction threshold higher, indicating that Poisson-based models have underestimated the mutation rate required to achieve viral extinction and avoid viral escape or accelerated evolution. Furthermore, time to extinction in simulated populations is significantly longer with gamma-Poisson-based models than Poisson-based. This investigation of how mutation rate variability affects lethal mutagenesis will directly impact antiviral drug design and strategy, thus advancing efforts to combat virus outbreaks and future pandemics. Significance StatementRNA viruses mutate at high rates. Some antiviral drugs work by further increasing these rates to unsustainable levels, a process called lethal mutagenesis. In this work, we discover that mutation rates vary significantly throughout viral populations. This discovery changes our understanding of how mutations and mutation rates should be modeled. By considering variability in mutation rates, our new model reveals that lethal mutagenesis is less effective as an antiviral drug strategy than previously thought.