Evolutionary Action of Mutations Reveals Antimicrobial Resistance Genes in Escherichia coli

Authors

David C Marciano
Chen Wang
Teng-Kuei Hsu
Thomas Bourquard
Benu Atri
Ralf B Nehring
Nicholas S Abel
Elizabeth A Bowling
Taylor J Chen
Pamela D Lurie
Panagiotis Katsonis
Susan M Rosenberg
Christophe Herman
Olivier Lichtarge

Publication Date

6-9-2022

Journal

Nature Communications

DOI

10.1038/s41467-022-30889-1

PMID

PMC9184624

PMCID

35680894

PubMedCentral® Posted Date

6-9-2022

PubMedCentral® Full Text Version

Post-print

Published Open-Access

yes

Keywords

Anti-Bacterial Agents, Ciprofloxacin, Colistin, Drug Resistance, Bacterial, Escherichia coli, Escherichia coli Proteins, Microbial Sensitivity Tests, Mutation, Computational models, Antimicrobial resistance

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.

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