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Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme

For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predict...

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Autores principales: Schenk, Martijn F., Szendro, Ivan G., Krug, Joachim, de Visser, J. Arjan G. M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386231/
https://www.ncbi.nlm.nih.gov/pubmed/22761587
http://dx.doi.org/10.1371/journal.pgen.1002783
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author Schenk, Martijn F.
Szendro, Ivan G.
Krug, Joachim
de Visser, J. Arjan G. M.
author_facet Schenk, Martijn F.
Szendro, Ivan G.
Krug, Joachim
de Visser, J. Arjan G. M.
author_sort Schenk, Martijn F.
collection PubMed
description For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance.
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spelling pubmed-33862312012-07-03 Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme Schenk, Martijn F. Szendro, Ivan G. Krug, Joachim de Visser, J. Arjan G. M. PLoS Genet Research Article For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance. Public Library of Science 2012-06-28 /pmc/articles/PMC3386231/ /pubmed/22761587 http://dx.doi.org/10.1371/journal.pgen.1002783 Text en Schenk et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Schenk, Martijn F.
Szendro, Ivan G.
Krug, Joachim
de Visser, J. Arjan G. M.
Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title_full Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title_fullStr Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title_full_unstemmed Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title_short Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
title_sort quantifying the adaptive potential of an antibiotic resistance enzyme
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3386231/
https://www.ncbi.nlm.nih.gov/pubmed/22761587
http://dx.doi.org/10.1371/journal.pgen.1002783
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