An omics-based framework for assessing the health risk of antimicrobial resistance genes
By A. Zhang, Jeffry M. Gaston, Chengzhen L. Dai, Shijie Zhao, M. Poyet, M. Groussin, Xiaole Yin, Li-Guan Li, Mark C. M. van Loosdrecht, E. Topp and 6 more. Nature Communications, 2021
775 citations recorded by the source corpus.
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. Antibiotic resistance genes are common but not all are of high risk to human health. Here, the authors develop an omics-based framework for ranking genes by risk that incorporates level of enrichment in human associated environments, gene mobility, and host pathogenicity.
Subfields: Infectious Diseases, Molecular Biology, Molecular Medicine
View Paper: https://www.semanticscholar.org/paper/30b0c9b741fe5a6034fc9b6c96980f0ab480c6f3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
In Molecular Medicine
Citations in the corpus
- CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database (2022, background): “However, the complexity and global burden of the AMR crisis (6) continues to expand with the continuous discovery of novel antibiotic resistance genes (ARGs), including those using novel mechanisms such as MCR-mediated colistin resistance via change in the charge of the cell membrane (7) or ejection”