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Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures

Metagenomics can unveil the genetic content of the total microbiota in different environments, such as food products and the guts of humans and livestock. It is therefore considered of great potential to investigate the transmission of foodborne hazards as part of source-attribution studies. Source-...

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Autores principales: Duarte, Ana Sofia Ribeiro, Röder, Timo, Van Gompel, Liese, Petersen, Thomas Nordahl, Hansen, Rasmus Borup, Hansen, Inge Marianne, Bossers, Alex, Aarestrup, Frank M., Wagenaar, Jaap A., Hald, Tine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843941/
https://www.ncbi.nlm.nih.gov/pubmed/33519742
http://dx.doi.org/10.3389/fmicb.2020.601407
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author Duarte, Ana Sofia Ribeiro
Röder, Timo
Van Gompel, Liese
Petersen, Thomas Nordahl
Hansen, Rasmus Borup
Hansen, Inge Marianne
Bossers, Alex
Aarestrup, Frank M.
Wagenaar, Jaap A.
Hald, Tine
author_facet Duarte, Ana Sofia Ribeiro
Röder, Timo
Van Gompel, Liese
Petersen, Thomas Nordahl
Hansen, Rasmus Borup
Hansen, Inge Marianne
Bossers, Alex
Aarestrup, Frank M.
Wagenaar, Jaap A.
Hald, Tine
author_sort Duarte, Ana Sofia Ribeiro
collection PubMed
description Metagenomics can unveil the genetic content of the total microbiota in different environments, such as food products and the guts of humans and livestock. It is therefore considered of great potential to investigate the transmission of foodborne hazards as part of source-attribution studies. Source-attribution of antimicrobial resistance (AMR) has traditionally relied on pathogen isolation, while metagenomics allows investigating the full span of AMR determinants. In this study, we hypothesized that the relative abundance of fecal resistome components can be associated with specific reservoirs, and that resistomes can be used for AMR source-attribution. We used shotgun-sequences from fecal samples of pigs, broilers, turkeys- and veal calves collected across Europe, and fecal samples from humans occupationally exposed to livestock in one country (pig slaughterhouse workers, pig and broiler farmers). We applied both hierarchical and flat forms of the supervised classification ensemble algorithm Random Forests to classify resistomes into corresponding reservoir classes. We identified country-specific and -independent AMR determinants, and assessed the impact of country-specific determinants when attributing AMR resistance in humans. Additionally, we performed a similarity percentage analysis with the full spectrum of AMR determinants to identify resistome signatures for the different reservoirs. We showed that the number of AMR determinants necessary to attribute a resistome into the correct reservoir increases with a larger reservoir heterogeneity, and that the impact of country-specific resistome signatures on prediction varies between countries. We predicted a higher occupational exposure to AMR determinants among workers exposed to pigs than among those exposed to broilers. Additionally, results suggested that AMR exposure on pig farms was higher than in pig slaughterhouses. Human resistomes were more similar to pig and veal calves’ resistomes than to those of broilers and turkeys, and the majority of these resistome dissimilarities can be explained by a small set of AMR determinants. We identified resistome signatures for each individual reservoir, which include AMR determinants significantly associated with on-farm antimicrobial use. We attributed human resistomes to different livestock reservoirs using Random Forests, which allowed identifying pigs as a potential source of AMR in humans. This study thus demonstrates that it is possible to apply metagenomics in AMR source-attribution.
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spelling pubmed-78439412021-01-30 Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures Duarte, Ana Sofia Ribeiro Röder, Timo Van Gompel, Liese Petersen, Thomas Nordahl Hansen, Rasmus Borup Hansen, Inge Marianne Bossers, Alex Aarestrup, Frank M. Wagenaar, Jaap A. Hald, Tine Front Microbiol Microbiology Metagenomics can unveil the genetic content of the total microbiota in different environments, such as food products and the guts of humans and livestock. It is therefore considered of great potential to investigate the transmission of foodborne hazards as part of source-attribution studies. Source-attribution of antimicrobial resistance (AMR) has traditionally relied on pathogen isolation, while metagenomics allows investigating the full span of AMR determinants. In this study, we hypothesized that the relative abundance of fecal resistome components can be associated with specific reservoirs, and that resistomes can be used for AMR source-attribution. We used shotgun-sequences from fecal samples of pigs, broilers, turkeys- and veal calves collected across Europe, and fecal samples from humans occupationally exposed to livestock in one country (pig slaughterhouse workers, pig and broiler farmers). We applied both hierarchical and flat forms of the supervised classification ensemble algorithm Random Forests to classify resistomes into corresponding reservoir classes. We identified country-specific and -independent AMR determinants, and assessed the impact of country-specific determinants when attributing AMR resistance in humans. Additionally, we performed a similarity percentage analysis with the full spectrum of AMR determinants to identify resistome signatures for the different reservoirs. We showed that the number of AMR determinants necessary to attribute a resistome into the correct reservoir increases with a larger reservoir heterogeneity, and that the impact of country-specific resistome signatures on prediction varies between countries. We predicted a higher occupational exposure to AMR determinants among workers exposed to pigs than among those exposed to broilers. Additionally, results suggested that AMR exposure on pig farms was higher than in pig slaughterhouses. Human resistomes were more similar to pig and veal calves’ resistomes than to those of broilers and turkeys, and the majority of these resistome dissimilarities can be explained by a small set of AMR determinants. We identified resistome signatures for each individual reservoir, which include AMR determinants significantly associated with on-farm antimicrobial use. We attributed human resistomes to different livestock reservoirs using Random Forests, which allowed identifying pigs as a potential source of AMR in humans. This study thus demonstrates that it is possible to apply metagenomics in AMR source-attribution. Frontiers Media S.A. 2021-01-15 /pmc/articles/PMC7843941/ /pubmed/33519742 http://dx.doi.org/10.3389/fmicb.2020.601407 Text en Copyright © 2021 Duarte, Röder, Van Gompel, Petersen, Hansen, Hansen, Bossers, Aarestrup, Wagenaar and Hald. http://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
Duarte, Ana Sofia Ribeiro
Röder, Timo
Van Gompel, Liese
Petersen, Thomas Nordahl
Hansen, Rasmus Borup
Hansen, Inge Marianne
Bossers, Alex
Aarestrup, Frank M.
Wagenaar, Jaap A.
Hald, Tine
Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title_full Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title_fullStr Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title_full_unstemmed Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title_short Metagenomics-Based Approach to Source-Attribution of Antimicrobial Resistance Determinants – Identification of Reservoir Resistome Signatures
title_sort metagenomics-based approach to source-attribution of antimicrobial resistance determinants – identification of reservoir resistome signatures
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843941/
https://www.ncbi.nlm.nih.gov/pubmed/33519742
http://dx.doi.org/10.3389/fmicb.2020.601407
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