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

Alexandre Maciel-Guerra, Michelle Baker, Yue Hu, Wei Wang, Xibin Zhang, Jia Rong, Yimin Zhang, Jing Zhang, Jasmeet Kaler, David Renney, Matthew Loose, Richard D. Emes, Longhai Liu, Junshi Chen, Zixin Peng, Fengqin Li, Tania Dottorini

Research output: Journal PublicationArticlepeer-review

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.

Original languageEnglish
JournalISME Journal
DOIs
Publication statusAccepted/In press - 2022
Externally publishedYes

ASJC Scopus subject areas

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics

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