Evolutionary action of mutations reveals antimicrobial resistance genes in Escherichia coli
Year: 2022
Type: article
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.
Source: Nature Communications
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $5,890
Funders: National Science Foundation, U.S. Department of Health and Human Services, Office of the Director of National Intelligence, National Institutes of Health, Intelligence Advanced Research Projects Activity, National Institute on Aging, NIH Office of the Director, National Cancer Institute, National Institute of General Medical Sciences, National Institute of Allergy and Infectious Diseases
Awards: RAPID - COVID-19 target epitopes and human genetic factors of virulence, G1601287694, G3158353285, G3664515446, A knowledge map to find Alzheimer's disease drugs, G4797008958, ABI Innovation: Towards Recovery of Biological Information, MOLECULAR MECHANISMS OF STRESS-INDUCED MUTATION, G5014598028, G5250970604, G5427725083, G5697108406, Cognitive Computing of Alzheimer's Disease Genes and Risk, G7263789177, G7438095202, G782485094, G7979422089, G8222056937, Mechanisms of Endogenous DNA Damage Promotion, G8742054587, G9000003056, G9000014469, G9000043437, G9000060084, G9000062933, G9000107134, G9000127332, G9000154030, G9000217251
OpenAlex ID: W4281774081