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Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations
Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6984361/ https://www.ncbi.nlm.nih.gov/pubmed/31504754 http://dx.doi.org/10.1093/molbev/msz199 |
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author | Sun, Lei Ashcroft, Peter Ackermann, Martin Bonhoeffer, Sebastian |
author_facet | Sun, Lei Ashcroft, Peter Ackermann, Martin Bonhoeffer, Sebastian |
author_sort | Sun, Lei |
collection | PubMed |
description | Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell and we observe the growth and survival dynamics of the cell population. Resistance-enhancing mutations are introduced by varying parameters that control the enzyme expression or efficacy. We find that stochastic gene expression can cause complex dynamics in terms of survival and extinction for these mutants. Regulatory mutations, which augment the frequency and duration of resistance gene transcription, can provide limited resistance by increasing mean expression. Structural mutations, which modify the enzyme or efflux efficacy, provide most resistance by improving the binding affinity of the resistance protein to the antibiotic; increasing the enzyme’s catalytic rate alone may contribute to resistance if drug binding is not rate limiting. Overall, we identify conditions where regulatory mutations are selected over structural mutations, and vice versa. Our findings show that stochastic gene expression is a key factor underlying efflux and enzymatic resistances and should be taken into consideration in future antibiotic research. |
format | Online Article Text |
id | pubmed-6984361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-69843612020-01-30 Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations Sun, Lei Ashcroft, Peter Ackermann, Martin Bonhoeffer, Sebastian Mol Biol Evol Discoveries Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell and we observe the growth and survival dynamics of the cell population. Resistance-enhancing mutations are introduced by varying parameters that control the enzyme expression or efficacy. We find that stochastic gene expression can cause complex dynamics in terms of survival and extinction for these mutants. Regulatory mutations, which augment the frequency and duration of resistance gene transcription, can provide limited resistance by increasing mean expression. Structural mutations, which modify the enzyme or efflux efficacy, provide most resistance by improving the binding affinity of the resistance protein to the antibiotic; increasing the enzyme’s catalytic rate alone may contribute to resistance if drug binding is not rate limiting. Overall, we identify conditions where regulatory mutations are selected over structural mutations, and vice versa. Our findings show that stochastic gene expression is a key factor underlying efflux and enzymatic resistances and should be taken into consideration in future antibiotic research. Oxford University Press 2020-01 2019-09-04 /pmc/articles/PMC6984361/ /pubmed/31504754 http://dx.doi.org/10.1093/molbev/msz199 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Discoveries Sun, Lei Ashcroft, Peter Ackermann, Martin Bonhoeffer, Sebastian Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title | Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title_full | Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title_fullStr | Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title_full_unstemmed | Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title_short | Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations |
title_sort | stochastic gene expression influences the selection of antibiotic resistance mutations |
topic | Discoveries |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6984361/ https://www.ncbi.nlm.nih.gov/pubmed/31504754 http://dx.doi.org/10.1093/molbev/msz199 |
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