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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

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Alexandre Maciel-Guerra

Yue Hu

Wei Wang

Xibin Zhang

Jia Rong

Yimin Zhang

Jing Zhang

Professor of Epidemiology & Precision Livestock Informatics

David Renney

Professor of Developmental and Computational Biology

Richard D. Emes

Longhai Liu

Junshi Chen

Zixin Peng

Fengqin Li


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.


Maciel-Guerra, A., Baker, M., Hu, Y., Wang, W., Zhang, X., Rong, J., …Dottorini, T. (2023). Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock. ISME Journal, 17, 21-35.

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 ISME Journal
Print ISSN 1751-7362
Electronic ISSN 1751-7370
Publisher Springer Science and Business Media LLC
Peer Reviewed Peer Reviewed
Volume 17
Pages 21-35
Keywords Ecology, Evolution, Behavior and Systematics; Microbiology
Public URL
Publisher URL


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