Veterinary Science

Machine learning and metagenomics reveal shared antimicrobial resistance profiles across multiple chicken farms and abattoirs in China

M. Baker, X. Zhang, et al.

This study, conducted by a team of researchers including Michelle Baker and Xibin Zhang, investigates antimicrobial resistance in large-scale chicken farms and abattoirs in China. Utilizing machine learning and metagenomics, they unveil crucial connections between mobile antibiotic resistance genes and environmental factors, paving the way for significant improvements in livestock health.

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Abstract

This study investigated antimicrobial resistance (AMR) in ten large-scale chicken farms and four connected abattoirs in China over 2.5 years. Using machine learning and metagenomics, researchers analyzed 461 microbiomes, identifying 145 mobile antibiotic resistance genes (ARGs) shared between chickens and environments. A core set of 233 ARGs and 186 microbial species in chicken guts correlated with *E. coli* AMR profiles. Temperature and humidity were also correlated with ARG presence, suggesting multiple routes for AMR improvement in livestock.

Publisher

Nature Food

Published On

Aug 10, 2023

Authors

Michelle Baker, Xibin Zhang, Alexandre Maciel-Guerra, Yinping Dong, Wei Wang, Yujie Hu, David Renney, Yue Hu, Longhai Liu, Hui Li, Zhiqin Tong, Meimei Zhang, Yingzhi Geng, Li Zhao, Zhihui Hao, Nicola Senin, Junshi Chen, Zixin Peng, Fengqin Li, Tania Dottorini

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