Sharing of Antimicrobial Resistance Genes between Humans and Food Animals

Huiluo Cao, Salim Bougouffa, Tae-Jin Park, Andes Lau, Man-Ki Tong, Kin-Hung Chow, Pak-Leung Ho

Research output: Contribution to journalArticlepeer-review

Abstract

The prevalence and propagation of antimicrobial resistance (AMR) are serious global public health concerns. The large and the ever-increasing use of antibiotics in livestock is also considered a great concern. The extent of the similarity of acquired antibiotic resistance genes (ARGs) between humans and food animals and the driving factors underlying AMR transfer between them are not clear, although a link between ARGs in both hosts was proposed. To address this question, with swine and chicken as examples of food animals, we analyzed over 1,000 gut metagenomes of humans and food animals from over the world. A relatively high abundance and diversity of ARGs were observed in swine compared with those in humans as a whole. Commensal bacteria, particularly species from Clostridiales, contribute the most ARGs associated with mobile genetic elements (MGEs) and were found in both humans and food animals. Further studies demonstrate that overrepresented MGEs, namely, Tn4451/Tn4453 and TnAs3, are attributed mainly to the sharing between humans and food animals. A member of large resolvase family site-specific recombinases, TnpX, is found in Tn4451/Tn4453 which facilitates the insertions of the transient circular molecule. Although the variance in the transferability of ARGs in humans is higher than that in swine, a higher average transferability was observed in swine than that in humans. In conclusion, the potential antibiotic resistance hot spots with higher transferability in food animals observed in the present study emphasize the importance of surveillance for emerging resistance threats before they spread.
Original languageEnglish (US)
JournalmSystems
DOIs
StatePublished - Oct 11 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-10-13
Acknowledgements: We thank the Computational Bioscience Research Centre at The King Abdullah University of Science and Technology for support on computational resources.
This work is supported by grants from (i) the Consultancy Service for Enhancing Laboratory Surveillance of Emerging Infectious Disease for the HKSAR Department of Health, (ii) the Health and Medical Research Fund, Health Bureau, HKSAR (reference: CID-HKU-1-13) and (iii) the Seed Fund for Basic Research, University of Hong Kong (reference: 201711159159).

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