An experimental evaluation of drug-induced mutational meltdown as an antiviral treatment strategy [preprint]
Authors
Bank, ClaudiaRenzette, Nicholas
Liu, Ping
Matuszewski, Sebastian
Shim, Hyunjin
Foll, Matthieu
Bolon, Daniel N.
Zeldovich, Konstantin B.
Kowalik, Timothy F.
Finberg, Robert W.
Wang, Jennifer P.
Jensen, Jeffrey D.
UMass Chan Affiliations
Program in Bioinformatics and Integrative BiologyDepartment of Biochemistry and Molecular Pharmacology
Department of Medicine, Division of Infectious Diseases and Immunology
Department of Microbiology and Physiological Systems
Document Type
PreprintPublication Date
2016-06-02Keywords
evolutionary biologyinfluenza A virus. drug resistance
favipiravir
RNA
antiviral drugs
mutational meltdown
Ecology and Evolutionary Biology
Genetic Phenomena
Immunology and Infectious Disease
Pharmaceutical Preparations
Therapeutics
Viruses
Metadata
Show full item recordAbstract
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 utilize an experimental evolution framework, combined with novel population genetic method development for inference from time-sampled data, in order to evaluate the effectiveness of favipiravir against IAV. Evaluating whole genome polymorphism data across fifteen time points under multiple drug concentrations and in controls, we present the first evidence for the ability of viral 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.Source
bioRxiv 048934; doi: https://doi.org/10.1101/048934. Link to preprint on bioRxiv service.
DOI
10.1101/048934Permanent Link to this Item
http://hdl.handle.net/20.500.14038/29313Related Resources
Now published in Evolution doi: 10.1111/evo.13041
Rights
The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.Distribution License
http://creativecommons.org/licenses/by-nc-nd/4.0/ae974a485f413a2113503eed53cd6c53
10.1101/048934
Scopus Count
Except where otherwise noted, this item's license is described as The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.