The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
An omics-based framework for assessing the health risk of antimicrobial resistance genes
Open accessAbstract
Antibiotic resistance genes (ARGs) are widespread among bacteria. However, not all ARGs pose serious threats to public health, highlighting the importance of identifying those that are high-risk. Here, we developed an ‘omics-based’ framework to evaluate ARG risk considering human-associated-enrichment, gene mobility, and host pathogenicity. Our framework classifies human-associated, mobile ARGs (3.6% of all ARGs) as the highest risk, which we further differentiate as ‘current threats’ (Rank I; 3%) - already present among pathogens - and ‘future threats’ (Rank II; 0.6%) - novel resistance emerging from non-pathogens. Our framework identified 73 ‘current threat’ ARG families. Of these, 35 were among the 37 high-risk ARGs proposed by the World Health Organization and other literature; the remaining 38 were significantly enriched in hospital plasmids. By evaluating all pathogen genomes released since framework construction, we confirmed that ARGs that recently transferred into pathogens were significantly enriched in Rank II (‘future threats’). Lastly, we applied the framework to gut microbiome genomes from fecal microbiota transplantation donors. We found that although ARGs were widespread (73% of genomes), only 8.9% of genomes contained high-risk ARGs. Our framework provides an easy-to-implement approach to identify current and future antimicrobial resistance threats, with potential clinical applications including reducing risk of microbiome-based interventions.
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Cites
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Cited by
Alcock, B. P., Huynh, W., Chalil, R., Smith, K. W., Raphenya, A. R., Wlodarski, M. A., Edalatmand, A., Petkau, A., Syed, S. A., Tsang, K. K., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac920 · Cited by 2,441
Emerging contaminants: A One Health perspective
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Self-citationGood microbes, bad genes? The dissemination of antimicrobial resistance in the human microbiome
Crits-Christoph, A., Hallowell, H. A., Koutouvalis, K., & Suez, J. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2055944 · Cited by 156
Microbial hitchhikers harbouring antimicrobial-resistance genes in the riverine plastisphere
Zadjelovic, V., Wright, R. J., Borsetto, C., Quartey, J., Cairns, T. N., Langille, M. G. I., Wellington, E. M. H., & Christie-Oleza, J. A. (2023) · Microbiome · doi:10.1186/s40168-023-01662-3 · Cited by 87
Metadata
- Authors
- Zhang, A.-N., Gaston, J. M., Dai, C. L., Zhao, S., Poyet, M., Groussin, M., Yin, X., Li, L.-G., van Loosdrecht, M. C. M., Topp, E., Gillings, M. R., Hanage, W. P., Tiedje, J. M., Moniz, K., Alm, E. J., & Zhang, T.
- Venue
- Nature Communications
- Published
- 2021-08-06
- Volume
- 12
- Issue
- 1
- Pages
- 4765-4765
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3187959711
- Cited by
- 939
- References
- 80
- FWCI
- 32.17
- Type
- journal article
- Language
- en
- Open access
- gold
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- Zhang, A.-N., Gaston, J. M., Dai, C. L., Zhao, S., Poyet, M., Groussin, M., Yin, X., Li, L.-G., van Loosdrecht, M. C. M., Topp, E., Gillings, M. R., Hanage, W. P., Tiedje, J. M., Moniz, K., Alm, E. J., & Zhang, T. (2021). An omics-based framework for assessing the health risk of antimicrobial resistance genes. Nature Communications. https://doi.org/10.1038/s41467-021-25096-3
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
