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The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always
BACKGROUND: Antibiotic resistance is considered one of the most urgent threats to modern healthcare, and the role of the environment in resistance development is increasingly recognized. It is often assumed that the abundance and diversity of known resistance genes are representative also for the no...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035801/ https://www.ncbi.nlm.nih.gov/pubmed/29981578 http://dx.doi.org/10.1186/s40168-018-0508-2 |
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author | Bengtsson-Palme, Johan |
author_facet | Bengtsson-Palme, Johan |
author_sort | Bengtsson-Palme, Johan |
collection | PubMed |
description | BACKGROUND: Antibiotic resistance is considered one of the most urgent threats to modern healthcare, and the role of the environment in resistance development is increasingly recognized. It is often assumed that the abundance and diversity of known resistance genes are representative also for the non-characterized fraction of the resistome in a given environment, but this assumption has not been verified. In this study, this hypothesis is tested, using the resistance gene profiles of 1109 metagenomes from various environments. RESULTS: This study shows that the diversity and abundance of known antibiotic resistance genes can generally predict the diversity and abundance of undescribed resistance genes. However, the extent of this predictability is dependent on the type of environment investigated. Furthermore, it is shown that carefully selected small sets of resistance genes can describe total resistance gene diversity remarkably well. CONCLUSIONS: The results of this study suggest that knowledge gained from large-scale quantifications of known resistance genes can be utilized as a proxy for unknown resistance factors. This is important for current and proposed monitoring efforts for environmental antibiotic resistance and has implications for the design of risk ranking strategies and the choices of measures and methods for describing resistance gene abundance and diversity in the environment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-018-0508-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6035801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-60358012018-07-12 The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always Bengtsson-Palme, Johan Microbiome Research BACKGROUND: Antibiotic resistance is considered one of the most urgent threats to modern healthcare, and the role of the environment in resistance development is increasingly recognized. It is often assumed that the abundance and diversity of known resistance genes are representative also for the non-characterized fraction of the resistome in a given environment, but this assumption has not been verified. In this study, this hypothesis is tested, using the resistance gene profiles of 1109 metagenomes from various environments. RESULTS: This study shows that the diversity and abundance of known antibiotic resistance genes can generally predict the diversity and abundance of undescribed resistance genes. However, the extent of this predictability is dependent on the type of environment investigated. Furthermore, it is shown that carefully selected small sets of resistance genes can describe total resistance gene diversity remarkably well. CONCLUSIONS: The results of this study suggest that knowledge gained from large-scale quantifications of known resistance genes can be utilized as a proxy for unknown resistance factors. This is important for current and proposed monitoring efforts for environmental antibiotic resistance and has implications for the design of risk ranking strategies and the choices of measures and methods for describing resistance gene abundance and diversity in the environment. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-018-0508-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-07 /pmc/articles/PMC6035801/ /pubmed/29981578 http://dx.doi.org/10.1186/s40168-018-0508-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Bengtsson-Palme, Johan The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title | The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title_full | The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title_fullStr | The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title_full_unstemmed | The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title_short | The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
title_sort | diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants—but not always |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6035801/ https://www.ncbi.nlm.nih.gov/pubmed/29981578 http://dx.doi.org/10.1186/s40168-018-0508-2 |
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