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Modeling Polygenic Antibiotic Resistance Evolution in Biofilms
The recalcitrance of biofilms to antimicrobials is a multi-factorial phenomenon, including genetic, physical, and physiological changes. Individually, they often cannot account for biofilm recalcitrance. However, their combination can increase the minimal inhibitory concentration of antibiotics need...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301000/ https://www.ncbi.nlm.nih.gov/pubmed/35875522 http://dx.doi.org/10.3389/fmicb.2022.916035 |
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author | Trubenová, Barbora Roizman, Dan Rolff, Jens Regoes, Roland R. |
author_facet | Trubenová, Barbora Roizman, Dan Rolff, Jens Regoes, Roland R. |
author_sort | Trubenová, Barbora |
collection | PubMed |
description | The recalcitrance of biofilms to antimicrobials is a multi-factorial phenomenon, including genetic, physical, and physiological changes. Individually, they often cannot account for biofilm recalcitrance. However, their combination can increase the minimal inhibitory concentration of antibiotics needed to kill bacterial cells by three orders of magnitude, explaining bacterial survival under otherwise lethal drug treatment. The relative contributions of these factors depend on the specific antibiotics, bacterial strain, as well as environmental and growth conditions. An emerging population genetic property—increased biofilm genetic diversity—further enhances biofilm recalcitrance. Here, we develop a polygenic model of biofilm recalcitrance accounting for multiple phenotypic mechanisms proposed to explain biofilm recalcitrance. The model can be used to generate predictions about the emergence of resistance—its timing and population genetic consequences. We use the model to simulate various treatments and experimental setups. Our simulations predict that the evolution of resistance is impaired in biofilms at low antimicrobial concentrations while it is facilitated at higher concentrations. In scenarios that allow bacteria exchange between planktonic and biofilm compartments, the evolution of resistance is further facilitated compared to scenarios without exchange. We compare these predictions to published experimental observations. |
format | Online Article Text |
id | pubmed-9301000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93010002022-07-22 Modeling Polygenic Antibiotic Resistance Evolution in Biofilms Trubenová, Barbora Roizman, Dan Rolff, Jens Regoes, Roland R. Front Microbiol Microbiology The recalcitrance of biofilms to antimicrobials is a multi-factorial phenomenon, including genetic, physical, and physiological changes. Individually, they often cannot account for biofilm recalcitrance. However, their combination can increase the minimal inhibitory concentration of antibiotics needed to kill bacterial cells by three orders of magnitude, explaining bacterial survival under otherwise lethal drug treatment. The relative contributions of these factors depend on the specific antibiotics, bacterial strain, as well as environmental and growth conditions. An emerging population genetic property—increased biofilm genetic diversity—further enhances biofilm recalcitrance. Here, we develop a polygenic model of biofilm recalcitrance accounting for multiple phenotypic mechanisms proposed to explain biofilm recalcitrance. The model can be used to generate predictions about the emergence of resistance—its timing and population genetic consequences. We use the model to simulate various treatments and experimental setups. Our simulations predict that the evolution of resistance is impaired in biofilms at low antimicrobial concentrations while it is facilitated at higher concentrations. In scenarios that allow bacteria exchange between planktonic and biofilm compartments, the evolution of resistance is further facilitated compared to scenarios without exchange. We compare these predictions to published experimental observations. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9301000/ /pubmed/35875522 http://dx.doi.org/10.3389/fmicb.2022.916035 Text en Copyright © 2022 Trubenová, Roizman, Rolff and Regoes. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Trubenová, Barbora Roizman, Dan Rolff, Jens Regoes, Roland R. Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title | Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title_full | Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title_fullStr | Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title_full_unstemmed | Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title_short | Modeling Polygenic Antibiotic Resistance Evolution in Biofilms |
title_sort | modeling polygenic antibiotic resistance evolution in biofilms |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9301000/ https://www.ncbi.nlm.nih.gov/pubmed/35875522 http://dx.doi.org/10.3389/fmicb.2022.916035 |
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