The success of antimicrobial treatment is threatened by the evolution of drug resistance. Population genetic models are an important tool in mitigating that threat. However, most such models consider resistance emergence via a single mutational step. Here, we assembled experimental evidence that drug resistance evolution follows two patterns: i) a single mutation, which provides a large resistance benefit, or ii) multiple mutations, each conferring a small benefit, which combine to yield high-level resistance. Using stochastic modeling we then investigated the consequences of these two patterns for treatment failure and population diversity under various treatments. We find that resistance evolution is substantially limited if more than two mutations are required and that the extent of this limitation depends on the combination of drug type and pharmacokinetic profile. Further, if multiple mutations are necessary, adaptive treatment, which only suppresses the bacterial population, delays treatment failure due to resistance for a longer time than aggressive treatment, which aims at eradication.
All data and code generated or analysed during this study are included in the manuscript and supporting files. Source code has been provided for Figures 2-4, as well as S2-S17 in the form of an R package. Source data has been provided for Table 1, Figure 1B and S1.
The fitness costs of antibiotic resistance mutationsDryad Digital Repository: http://doi.org/10.5061/dryad.5rc47.
- Claudia Igler
- Jens Rolff
- Roland Regoes
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Ben S Cooper, Mahidol University, Thailand
© 2021, Igler et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.