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A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome

The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have been transmitted around the world. The large pool of sequencing data available in public repositories provides...

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Autores principales: Martiny, Hannah-Marie, Munk, Patrick, Brinch, Christian, Aarestrup, Frank M., Petersen, Thomas N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9447899/
https://www.ncbi.nlm.nih.gov/pubmed/36067158
http://dx.doi.org/10.1371/journal.pbio.3001792
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author Martiny, Hannah-Marie
Munk, Patrick
Brinch, Christian
Aarestrup, Frank M.
Petersen, Thomas N.
author_facet Martiny, Hannah-Marie
Munk, Patrick
Brinch, Christian
Aarestrup, Frank M.
Petersen, Thomas N.
author_sort Martiny, Hannah-Marie
collection PubMed
description The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have been transmitted around the world. The large pool of sequencing data available in public repositories provides an excellent resource for monitoring the temporal and spatial dissemination of AMR in different ecological settings. However, only a limited number of research groups globally have the computational resources to analyze such data. We retrieved 442 Tbp of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive (ENA) and aligned them using a uniform approach against ARGs and 16S/18S rRNA genes. Here, we present the results of this extensive computational analysis and share the counts of reads aligned. Over 6.76∙10(8) read fragments were assigned to ARGs and 3.21∙10(9) to rRNA genes, where we observed distinct differences in both the abundance of ARGs and the link between microbiome and resistome compositions across various sampling types. This collection is another step towards establishing global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs.
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spelling pubmed-94478992022-09-07 A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome Martiny, Hannah-Marie Munk, Patrick Brinch, Christian Aarestrup, Frank M. Petersen, Thomas N. PLoS Biol Methods and Resources The growing threat of antimicrobial resistance (AMR) calls for new epidemiological surveillance methods, as well as a deeper understanding of how antimicrobial resistance genes (ARGs) have been transmitted around the world. The large pool of sequencing data available in public repositories provides an excellent resource for monitoring the temporal and spatial dissemination of AMR in different ecological settings. However, only a limited number of research groups globally have the computational resources to analyze such data. We retrieved 442 Tbp of sequencing reads from 214,095 metagenomic samples from the European Nucleotide Archive (ENA) and aligned them using a uniform approach against ARGs and 16S/18S rRNA genes. Here, we present the results of this extensive computational analysis and share the counts of reads aligned. Over 6.76∙10(8) read fragments were assigned to ARGs and 3.21∙10(9) to rRNA genes, where we observed distinct differences in both the abundance of ARGs and the link between microbiome and resistome compositions across various sampling types. This collection is another step towards establishing global surveillance of AMR and can serve as a resource for further research into the environmental spread and dynamic changes of ARGs. Public Library of Science 2022-09-06 /pmc/articles/PMC9447899/ /pubmed/36067158 http://dx.doi.org/10.1371/journal.pbio.3001792 Text en © 2022 Martiny et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Methods and Resources
Martiny, Hannah-Marie
Munk, Patrick
Brinch, Christian
Aarestrup, Frank M.
Petersen, Thomas N.
A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title_full A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title_fullStr A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title_full_unstemmed A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title_short A curated data resource of 214K metagenomes for characterization of the global antimicrobial resistome
title_sort curated data resource of 214k metagenomes for characterization of the global antimicrobial resistome
topic Methods and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9447899/
https://www.ncbi.nlm.nih.gov/pubmed/36067158
http://dx.doi.org/10.1371/journal.pbio.3001792
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