The population genetics of collateral resistance and sensitivity

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Abstract

Resistance mutations against one drug can elicit collateral sensitivity against other drugs. Multi-drug treatments exploiting such trade-offs can help slow down the evolution of resistance. However, if mutations with diverse collateral effects are available, a treated population may evolve either collateral sensitivity or collateral resistance. How to design treatments robust to such uncertainty is unclear. We show that many resistance mutations in Escherichia coli against various antibiotics indeed have diverse collateral effects. We propose to characterize such diversity with a joint distribution of fitness effects (JDFE) and develop a theory for describing and predicting collateral evolution based on simple statistics of the JDFE. We show how to robustly rank drug pairs to minimize the risk of collateral resistance and how to estimate JDFEs. In addition to practical applications, these results have implications for our understanding of evolution in variable environments.

Data availability

All code is available on GitHub. All data are available as Source Data files, included with the manuscript.

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Sarah M Ardell

Division of Biological Sciences, University of California, San Diego, La Jolla, United States

Competing interests
The authors declare that no competing interests exist.
Sergey Kryazhimskiy

Division of Biological Sciences, University of California, San Diego, La Jolla, United States

For correspondence
skryazhi@ucsd.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-9128-8705

Funding

Burroughs Wellcome Fund (1010719.01)

Sergey Kryazhimskiy

Alfred P. Sloan Foundation (FG-2017-9227)

Sergey Kryazhimskiy

Hellman Foundation

Sergey Kryazhimskiy

National Institutes of Health (1R01GM137112)

Sergey Kryazhimskiy

National Institutes of Health (1T32GM133351-01)

Sarah M Ardell

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

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.