Alexandre Maciel-Guerra
Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock
Maciel-Guerra, Alexandre; Baker, Michelle; Hu, Yue; Wang, Wei; Zhang, Xibin; Rong, Jia; Zhang, Yimin; Zhang, Jing; Kaler, Jasmeet; Renney, David; Loose, Matthew; Emes, Richard D.; Liu, Longhai; Chen, Junshi; Peng, Zixin; Li, Fengqin; Dottorini, Tania
Authors
MICHELLE BAKER MICHELLE.BAKER@NOTTINGHAM.AC.UK
Research Fellow
Yue Hu
Wei Wang
Xibin Zhang
Jia Rong
Yimin Zhang
JING ZHANG J.ZHANG@NOTTINGHAM.AC.UK
Assistant Professor
JASMEET KALER JASMEET.KALER@NOTTINGHAM.AC.UK
Professor of Epidemiology & Precision Livestock Informatics
David Renney
MATTHEW LOOSE matt.loose@nottingham.ac.uk
Professor of Developmental and Computational Biology
Richard D. Emes
Longhai Liu
Junshi Chen
Zixin Peng
Fengqin Li
TANIA DOTTORINI TANIA.DOTTORINI@NOTTINGHAM.AC.UK
Professor of Bioinformatics
Abstract
A debate is currently ongoing as to whether intensive livestock farms may constitute reservoirs of clinically relevant antimicrobial resistance (AMR), thus posing a threat to surrounding communities. Here, combining shotgun metagenome sequencing, machine learning (ML), and culture-based methods, we focused on a poultry farm and connected slaughterhouse in China, investigating the gut microbiome of livestock, workers and their households, and microbial communities in carcasses and soil. For both the microbiome and resistomes in this study, differences are observed across environments and hosts. However, at a finer scale, several similar clinically relevant antimicrobial resistance genes (ARGs) and similar associated mobile genetic elements were found in both human and broiler chicken samples. Next, we focused on Escherichia coli, an important indicator for the surveillance of AMR on the farm. Strains of E. coli were found intermixed between humans and chickens. We observed that several ARGs present in the chicken faecal resistome showed correlation to resistance/susceptibility profiles of E. coli isolates cultured from the same samples. Finally, by using environmental sensing these ARGs were found to be correlated to variations in environmental temperature and humidity. Our results show the importance of adopting a multi-domain and multi-scale approach when studying microbial communities and AMR in complex, interconnected environments.
Citation
Maciel-Guerra, A., Baker, M., Hu, Y., Wang, W., Zhang, X., Rong, J., Zhang, Y., Zhang, J., Kaler, J., Renney, D., Loose, M., Emes, R. D., Liu, L., Chen, J., Peng, Z., Li, F., & Dottorini, T. (2023). Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock. ISME Journal, 17(1), 21-35. https://doi.org/10.1038/s41396-022-01315-7
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 1, 2022 |
Online Publication Date | Sep 23, 2022 |
Publication Date | 2023-01 |
Deposit Date | Sep 26, 2022 |
Publicly Available Date | Sep 26, 2022 |
Journal | The ISME Journal |
Print ISSN | 1751-7362 |
Electronic ISSN | 1751-7370 |
Publisher | Nature Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 17 |
Issue | 1 |
Pages | 21-35 |
DOI | https://doi.org/10.1038/s41396-022-01315-7 |
Keywords | Ecology, Evolution, Behavior and Systematics; Microbiology |
Public URL | https://nottingham-repository.worktribe.com/output/11743987 |
Publisher URL | https://www.nature.com/articles/s41396-022-01315-7 |
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Dissecting microbial communities
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Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
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