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

Authors :
Feng, Yuqing
Lu, Xin
Zhao, Jiayong
Li, Hongmin
Xu, Jialiang
Li, Zhenpeng
Wang, Mengyu
Peng, Yao
Tian, Tian
Yuan, Gailing
Zhang, Yuan
Liu, Jiaqi
Zhang, Meihong
Zhu La, A La Teng
Qu, Geruo
Mu, Yujiao
Guo, Wanshen
Wu, Yongning
Zhang, Yuyu
Wang, Dexiang
Source :
Microbiome; 1/7/2025, Vol. 13, p1-18, 18p
Publication Year :
2025

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. EovijMVq4EnQBaYQdN7uV2 Video Abstract [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20492618
Volume :
13
Database :
Complementary Index
Journal :
Microbiome
Publication Type :
Academic Journal
Accession number :
182324134
Full Text :
https://doi.org/10.1186/s40168-024-01983-x