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Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities
Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that neighbouring species enforce the re‐distribution of carbon and antimicrobial molecules, predictably changing drug efficacy with respect to standard laboratory assays. A simple math...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723709/ https://www.ncbi.nlm.nih.gov/pubmed/37938684 http://dx.doi.org/10.1038/s43705-022-00186-5 |
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author | Reding, Carlos |
author_facet | Reding, Carlos |
author_sort | Reding, Carlos |
collection | PubMed |
description | Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that neighbouring species enforce the re‐distribution of carbon and antimicrobial molecules, predictably changing drug efficacy with respect to standard laboratory assays. A simple mathematical model, validated experimentally using pairwise competition assays, suggests that differences in drug sensitivity between the competing species causes the re‐distribution of drug molecules without affecting carbon uptake. The re‐distribution of drug is even when species have similar drug sensitivity, reducing drug efficacy. But when their sensitivities differ the re‐distribution is uneven: The most sensitive species accumulates more drug molecules, increasing efficacy against it. Drug efficacy tests relying on samples with multiple species are considered unreliable and unpredictable, but study demonstrates that efficacy in these cases can be qualitatively predicted. It also suggests that living in communities can be beneficial even when all species compete for a single carbon source, as the relationship between cell density and drug required to inhibit their growth may be more complex than previously thought. |
format | Online Article Text |
id | pubmed-9723709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97237092023-01-04 Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities Reding, Carlos ISME Commun Article Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that neighbouring species enforce the re‐distribution of carbon and antimicrobial molecules, predictably changing drug efficacy with respect to standard laboratory assays. A simple mathematical model, validated experimentally using pairwise competition assays, suggests that differences in drug sensitivity between the competing species causes the re‐distribution of drug molecules without affecting carbon uptake. The re‐distribution of drug is even when species have similar drug sensitivity, reducing drug efficacy. But when their sensitivities differ the re‐distribution is uneven: The most sensitive species accumulates more drug molecules, increasing efficacy against it. Drug efficacy tests relying on samples with multiple species are considered unreliable and unpredictable, but study demonstrates that efficacy in these cases can be qualitatively predicted. It also suggests that living in communities can be beneficial even when all species compete for a single carbon source, as the relationship between cell density and drug required to inhibit their growth may be more complex than previously thought. Nature Publishing Group UK 2022-11-05 /pmc/articles/PMC9723709/ /pubmed/37938684 http://dx.doi.org/10.1038/s43705-022-00186-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Reding, Carlos Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title | Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title_full | Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title_fullStr | Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title_full_unstemmed | Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title_short | Predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
title_sort | predicting the re‐distribution of antibiotic molecules caused by inter‐species interactions in microbial communities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9723709/ https://www.ncbi.nlm.nih.gov/pubmed/37938684 http://dx.doi.org/10.1038/s43705-022-00186-5 |
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