Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock

Maciel-Guerra, A, Baker, M, Hu, Y, Wang, W, Zhang, X, Rong, J, Zhang, Y, Zhang, J, Kaler, J, Renney, D, Loose, M, Emes, RD ORCID: https://orcid.org/0000-0001-6855-5481, Liu, L, Chen, J, Peng, Z, Li, F and Dottorini, T, 2023. Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock. The ISME Journal, 17 (1), pp. 21-35. ISSN 1751-7362

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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.

Item Type:	Journal article
Publication Title:	The ISME Journal
Creators:	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. and Dottorini, T.
Publisher:	Springer
Date:	January 2023
Volume:	17
Number:	1
ISSN:	1751-7362
Identifiers:	Number Type 10.1038/s41396-022-01315-7 DOI 1727732 Other
Rights:	This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Record created by:	Jonathan Gallacher
Date Added:	09 Feb 2023 08:58
Last Modified:	09 Feb 2023 08:58
URI:	https://irep.ntu.ac.uk/id/eprint/48202

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