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Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively s...

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Autores principales: Iwasawa, Junichiro, Maeda, Tomoya, Shibai, Atsushi, Kotani, Hazuki, Kawada, Masako, Furusawa, Chikara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746992/
https://www.ncbi.nlm.nih.gov/pubmed/36512529
http://dx.doi.org/10.1371/journal.pbio.3001920
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author Iwasawa, Junichiro
Maeda, Tomoya
Shibai, Atsushi
Kotani, Hazuki
Kawada, Masako
Furusawa, Chikara
author_facet Iwasawa, Junichiro
Maeda, Tomoya
Shibai, Atsushi
Kotani, Hazuki
Kawada, Masako
Furusawa, Chikara
author_sort Iwasawa, Junichiro
collection PubMed
description The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.
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spelling pubmed-97469922022-12-14 Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape Iwasawa, Junichiro Maeda, Tomoya Shibai, Atsushi Kotani, Hazuki Kawada, Masako Furusawa, Chikara PLoS Biol Research Article The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes by comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the phenotype-based fitness landscape for antibiotic resistance evolution by quantifying the multidimensional phenotypic changes, i.e., time-series data of resistance for eight different drugs. We show that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred phenotype-fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution. Public Library of Science 2022-12-13 /pmc/articles/PMC9746992/ /pubmed/36512529 http://dx.doi.org/10.1371/journal.pbio.3001920 Text en © 2022 Iwasawa et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Iwasawa, Junichiro
Maeda, Tomoya
Shibai, Atsushi
Kotani, Hazuki
Kawada, Masako
Furusawa, Chikara
Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title_full Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title_fullStr Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title_full_unstemmed Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title_short Analysis of the evolution of resistance to multiple antibiotics enables prediction of the Escherichia coli phenotype-based fitness landscape
title_sort analysis of the evolution of resistance to multiple antibiotics enables prediction of the escherichia coli phenotype-based fitness landscape
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9746992/
https://www.ncbi.nlm.nih.gov/pubmed/36512529
http://dx.doi.org/10.1371/journal.pbio.3001920
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