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Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings
The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now be...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755710/ https://www.ncbi.nlm.nih.gov/pubmed/36532424 http://dx.doi.org/10.3389/fmicb.2022.1066995 |
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author | Pillay, Stephanie Calderón-Franco, David Urhan, Aysun Abeel, Thomas |
author_facet | Pillay, Stephanie Calderón-Franco, David Urhan, Aysun Abeel, Thomas |
author_sort | Pillay, Stephanie |
collection | PubMed |
description | The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment – including animals, plants, soil, and water – are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance. |
format | Online Article Text |
id | pubmed-9755710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97557102022-12-17 Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings Pillay, Stephanie Calderón-Franco, David Urhan, Aysun Abeel, Thomas Front Microbiol Microbiology The success of antibiotics as a therapeutic agent has led to their ineffectiveness. The continuous use and misuse in clinical and non-clinical areas have led to the emergence and spread of antibiotic-resistant bacteria and its genetic determinants. This is a multi-dimensional problem that has now become a global health crisis. Antibiotic resistance research has primarily focused on the clinical healthcare sectors while overlooking the non-clinical sectors. The increasing antibiotic usage in the environment – including animals, plants, soil, and water – are drivers of antibiotic resistance and function as a transmission route for antibiotic resistant pathogens and is a source for resistance genes. These natural compartments are interconnected with each other and humans, allowing the spread of antibiotic resistance via horizontal gene transfer between commensal and pathogenic bacteria. Identifying and understanding genetic exchange within and between natural compartments can provide insight into the transmission, dissemination, and emergence mechanisms. The development of high-throughput DNA sequencing technologies has made antibiotic resistance research more accessible and feasible. In particular, the combination of metagenomics and powerful bioinformatic tools and platforms have facilitated the identification of microbial communities and has allowed access to genomic data by bypassing the need for isolating and culturing microorganisms. This review aimed to reflect on the different sequencing techniques, metagenomic approaches, and bioinformatics tools and pipelines with their respective advantages and limitations for antibiotic resistance research. These approaches can provide insight into resistance mechanisms, the microbial population, emerging pathogens, resistance genes, and their dissemination. This information can influence policies, develop preventative measures and alleviate the burden caused by antibiotic resistance. Frontiers Media S.A. 2022-12-02 /pmc/articles/PMC9755710/ /pubmed/36532424 http://dx.doi.org/10.3389/fmicb.2022.1066995 Text en Copyright © 2022 Pillay, Calderón-Franco, Urhan and Abeel. 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 Pillay, Stephanie Calderón-Franco, David Urhan, Aysun Abeel, Thomas Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title | Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title_full | Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title_fullStr | Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title_full_unstemmed | Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title_short | Metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
title_sort | metagenomic-based surveillance systems for antibiotic resistance in non-clinical settings |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755710/ https://www.ncbi.nlm.nih.gov/pubmed/36532424 http://dx.doi.org/10.3389/fmicb.2022.1066995 |
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