An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy.
Abstract
The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.
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BibTeX
@article{bank2026experimental,
title = {{An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy.}},
author = {Claudia Bank and Nicholas Renzette and Ping Liu and Sebastian Matuszewski and Hyunjin Shim and Matthieu Foll and Daniel N A Bolon and Konstantin B Zeldovich and Timothy F Kowalik and Robert W Finberg and Jennifer P Wang and Jeffrey D Jensen},
journal = {Evolution; international journal of organic evolution},
year = {2026},
month = oct,
doi = {10.1111/evo.13041},
url = {https://hal.science/hal-05842792v1},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy.
AU - Claudia Bank
AU - Nicholas Renzette
AU - Ping Liu
AU - Sebastian Matuszewski
AU - Hyunjin Shim
AU - Matthieu Foll
AU - Daniel N A Bolon
AU - Konstantin B Zeldovich
AU - Timothy F Kowalik
AU - Robert W Finberg
AU - Jennifer P Wang
AU - Jeffrey D Jensen
PY - 2026
DA - 2026/10/28
JO - Evolution; international journal of organic evolution
DO - 10.1111/evo.13041
UR - https://hal.science/hal-05842792v1
AB - The rapid evolution of drug resistance remains a critical public health concern. The treatment of influenza A virus (IAV) has proven particularly challenging, due to the ability of the virus to develop resistance against current antivirals and vaccines. Here, we evaluate a novel antiviral drug therapy, favipiravir, for which the mechanism of action in IAV involves an interaction with the viral RNA-dependent RNA polymerase resulting in an effective increase in the viral mutation rate. We used an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across 15 time points under multiple drug concentrations and in controls, we present the first evidence for the ability of IAV populations to effectively adapt to low concentrations of favipiravir. In contrast, under high concentrations, we observe population extinction, indicative of mutational meltdown. We discuss the observed dynamics with respect to the evolutionary forces at play and emphasize the utility of evolutionary theory to inform drug development.
ER -