Assessment of global health risk of antibiotic resistance genes

Zhenyan Zhang, Qi Zhang, Tingzhang Wang, Nuohan Xu, Tao Lu, Wenjie Hong, Josep Penuelas, Michael Gillings, Meixia Wang, Wenwen Gao and Haifeng Qian ()
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Zhenyan Zhang: Zhejiang University of Technology
Qi Zhang: Zhejiang University of Technology
Tingzhang Wang: Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province
Nuohan Xu: Zhejiang University of Technology
Tao Lu: Zhejiang University of Technology
Wenjie Hong: Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province
Josep Penuelas: Global Ecology Unit CREAF-CSIC-UAB, Bellaterra
Michael Gillings: Macquarie University
Meixia Wang: Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province
Wenwen Gao: Key Laboratory of Microbial Technology and Bioinformatics of Zhejiang Province
Haifeng Qian: Zhejiang University of Technology

Nature Communications, 2022, vol. 13, issue 1, 1-11

Abstract: Abstract Antibiotic resistance genes (ARGs) have accelerated microbial threats to human health in the last decade. Many genes can confer resistance, but evaluating the relative health risks of ARGs is complex. Factors such as the abundance, propensity for lateral transmission and ability of ARGs to be expressed in pathogens are all important. Here, an analysis at the metagenomic level from various habitats (6 types of habitats, 4572 samples) detects 2561 ARGs that collectively conferred resistance to 24 classes of antibiotics. We quantitatively evaluate the health risk to humans, defined as the risk that ARGs will confound the clinical treatment for pathogens, of these 2561 ARGs by integrating human accessibility, mobility, pathogenicity and clinical availability. Our results demonstrate that 23.78% of the ARGs pose a health risk, especially those which confer multidrug resistance. We also calculate the antibiotic resistance risks of all samples in four main habitats, and with machine learning, successfully map the antibiotic resistance threats in global marine habitats with over 75% accuracy. Our novel method for quantitatively surveilling the health risk of ARGs will help to manage one of the most important threats to human and animal health.

Date: 2022
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DOI: 10.1038/s41467-022-29283-8

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