TY - JOUR
T1 - Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock
AU - Maciel-Guerra, Alexandre
AU - Baker, Michelle
AU - Hu, Yue
AU - Wang, Wei
AU - Zhang, Xibin
AU - Rong, Jia
AU - Zhang, Yimin
AU - Zhang, Jing
AU - Kaler, Jasmeet
AU - Renney, David
AU - Loose, Matthew
AU - Emes, Richard D.
AU - Liu, Longhai
AU - Chen, Junshi
AU - Peng, Zixin
AU - Li, Fengqin
AU - Dottorini, Tania
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85138728493&partnerID=8YFLogxK
U2 - 10.1038/s41396-022-01315-7
DO - 10.1038/s41396-022-01315-7
M3 - Article
C2 - 36151458
AN - SCOPUS:85138728493
SN - 1751-7362
VL - 17
SP - 21
EP - 35
JO - ISME Journal
JF - ISME Journal
IS - 1
ER -