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Regional antimicrobial resistance gene flow among the One Health sectors in China

Authors :
Yuqing Feng
Xin Lu
Jiayong Zhao
Hongmin Li
Jialiang Xu
Zhenpeng Li
Mengyu Wang
Yao Peng
Tian Tian
Gailing Yuan
Yuan Zhang
Jiaqi Liu
Meihong Zhang
A La Teng Zhu La
Geruo Qu
Yujiao Mu
Wanshen Guo
Yongning Wu
Yuyu Zhang
Dexiang Wang
Yongfei Hu
Biao Kan
Source :
Microbiome, Vol 13, Iss 1, Pp 1-18 (2025)
Publication Year :
2025
Publisher :
BMC, 2025.

Abstract

Abstract Background Antimicrobial resistance poses a significant threat to global health, with its spread intricately linked across human, animal, and environmental sectors. Revealing the antimicrobial resistance gene (ARG) flow among the One Health sectors is essential for better control of antimicrobial resistance. Results In this study, we investigated regional ARG transmission among humans, food, and the environment in Dengfeng, Henan Province, China by combining large-scale metagenomic sequencing with culturing of resistant bacterial isolates in 592 samples. A total of 40 ARG types and 743 ARG subtypes were identified, with a predominance of multidrug resistance genes. Compared with microbes from human fecal samples, those from food and environmental samples showed a significantly higher load of ARGs. We revealed that dietary habits and occupational exposure significantly affect ARG abundance. Pseudomonadota, particularly Enterobacteriaceae, were identified as the main ARG carriers shaping the resistome. The resistome in food samples was found more affected by mobile genetic elements (MGEs), whereas in environmental samples, it was more associated with the microbial composition. We evidenced that horizontal gene transfer (HGT) mediated by plasmids and phages, together with strain transmission, particularly those associated with the Enterobacteriaceae members, drive regional ARG flow. Lifestyle, dietary habits, and occupational exposure are all correlated with ARG dissemination and flies and food are important potential sources of ARGs to humans. The widespread mobile carbapenemase gene, OXA-347, carried by non-Enterobacteriaceae bacteria in the human gut microbiota, requires particular attention. Finally, we showed that machine learning models based on microbiome profiles were effective in predicting the presence of carbapenem-resistant strains, suggesting a valuable approach for AMR surveillance. Conclusions Our study provides a full picture of regional ARG transmission among the One Health sectors in a county-level city in China, which facilitates a better understanding of the complex routes of ARG transmission and highlights new points of focus for AMR surveillance and control. Video Abstract

Details

Language :
English
ISSN :
20492618
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Microbiome
Publication Type :
Academic Journal
Accession number :
edsdoj.89b3eba1ba4fbb9da959ddce0e05b0
Document Type :
article
Full Text :
https://doi.org/10.1186/s40168-024-01983-x