Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli
Abstract
Since antibiotic development lags, we search for potential drug targets through directed evolution experiments. A challenge is that many resistance genes hide in a noisy mutational background as mutator clones emerge in the adaptive population. Here, to overcome this noise, we quantify the impact of mutations through evolutionary action (EA). After sequencing ciprofloxacin or colistin resistance strains grown under different mutational regimes, we find that an elevated sum of the evolutionary action of mutations in a gene identifies known resistance drivers. This EA integration approach also suggests new antibiotic resistance genes which are then shown to provide a fitness advantage in competition experiments. Moreover, EA integration analysis of clinical and environmental isolates of antibiotic resistant of E. coli identifies gene drivers of resistance where a standard approach fails. Together these results inform the genetic basis of de novo colistin resistance and support the robust discovery of phenotype-driving genes via the evolutionary action of genetic perturbations in fitness landscapes.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 09, 2022
- Source ID
- 10.1038/s41467-022-30889-1
Entities
People
- Benu Atri
- Chen Wang
- Christophe Herman
- David C Marciano
- Elizabeth A. Bowling
- Nicholas S. Abel
- Olivier Lichtarge
- Pamela D. Lurie
- Panagiotis Katsonis
- Ralf B. Nehring
- Susan M Rosenberg
- Taylor J. Chen
- Teng-kuei Hsu
- Thomas Bourquard
Organizations
- Intelligence Advanced Research Projects Activity
- National Institutes of Health
- National Science Foundation
- United States Department of Health and Human Services