4.8 Article

Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-30889-1

Keywords

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Funding

  1. Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA) [BAA-17-01, 2019-19071900001]
  2. National Institutes of Health [R35-GM122598, DP1-AG072751, R01CA250905, DP1-AI152073, R01-GM066099, R01-AG074009, U01AG068214, R01-AG061105]
  3. National Science Foundation [DBI2032904]

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By quantifying the impact of mutations through evolutionary action, known resistance drivers can be identified and new antibiotic resistance genes can be discovered. This method provides a more robust approach for finding antibiotic resistance genes compared to traditional methods.
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. coil 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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