Evidence map›Paper›PMID 39763003›Full record

ArticleMicrobiome2025

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

Yuqing Feng, Xin Lu, Jiayong Zhao, Hongmin Li, Jialiang Xu, Zhenpeng Li, Mengyu Wang, Yao Peng, Tian Tian, Gailing Yuan and 12 more

Abstract read
In one paragraph

Article in Microbiome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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  11. Review
  12. Clinical Significance ofMicroorganisms · 2026
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Review
  18. Celebrating three years ofScience in One Health · 2025
    Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Yuqing Feng *State Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Xin Lu *National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. luxin@icdc.cn.
Jiayong Zhao *Institute of Infectious Disease Prevention and Control, Henan Center for Disease Control and Prevention, Zhengzhou, 450016, China.
Hongmin Li *Dengfeng Center for Disease Control and Prevention, Dengfeng, Zhengzhou, 452470, China.
Jialiang Xu *School of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China.
Zhenpeng LiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Mengyu WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yao PengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Tian TianDengfeng Center for Disease Control and Prevention, Dengfeng, Zhengzhou, 452470, China.
Gailing YuanDengfeng Center for Disease Control and Prevention, Dengfeng, Zhengzhou, 452470, China.
Yuan ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Jiaqi LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Meihong ZhangState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
A La Teng Zhu LaState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Geruo QuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
Yujiao MuInstitute of Infectious Disease Prevention and Control, Henan Center for Disease Control and Prevention, Zhengzhou, 450016, China.
Wanshen GuoInstitute of Infectious Disease Prevention and Control, Henan Center for Disease Control and Prevention, Zhengzhou, 450016, China.
Yongning WuNHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, 100022, China.
Yuyu ZhangSchool of Light Industry Science and Engineering, Beijing Technology and Business University, Beijing, 100048, China. zhangyuyu@btbu.edu.cn.
Dexiang WangDengfeng Center for Disease Control and Prevention, Dengfeng, Zhengzhou, 452470, China. 17513332866@163.com.
Yongfei HuState Key Laboratory of Animal Nutrition and Feeding, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China. huyongfei@cau.edu.cn.
Biao KanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. kanbiao@icdc.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntimicrobial 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.

resultsIn 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.

conclusionsOur 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.

Indexed as

Anti-Bacterial AgentsBacteriaGene FlowGene Transfer, HorizontalOne HealthChinaDrug Resistance, BacterialFecesFood MicrobiologyGenes, BacterialHumansMetagenomicsAnti-Bacterial AgentsAntimicrobial resistance geneCarbapenemaseMobile genetic elementOne HealthTransmission pathway

Identifiers

PMID39763003
PMCPMC11705761

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.