An omics-based framework for assessing the health risk of antimicrobial resistance genes
<jats:title>Abstract</jats:title><jats:p>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...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2022
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| Online Access: | https://hdl.handle.net/1721.1/133506.2 |
| _version_ | 1810994540585156608 |
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| author | Zhang, An-Ni Gaston, Jeffry M. Dai, Chengzhen L. Zhao, Shijie Poyet, Mathilde Groussin, Mathieu Yin, Xiaole Li, Li-Guan van Loosdrecht, Mark C. M. Topp, Edward Gillings, Michael R. Hanage, William P. Tiedje, James M. Moniz, Katya Alm, Eric J. Zhang, Tong |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Zhang, An-Ni Gaston, Jeffry M. Dai, Chengzhen L. Zhao, Shijie Poyet, Mathilde Groussin, Mathieu Yin, Xiaole Li, Li-Guan van Loosdrecht, Mark C. M. Topp, Edward Gillings, Michael R. Hanage, William P. Tiedje, James M. Moniz, Katya Alm, Eric J. Zhang, Tong |
| author_sort | Zhang, An-Ni |
| collection | MIT |
| description | <jats:title>Abstract</jats:title><jats:p>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.</jats:p> |
| first_indexed | 2024-09-23T13:43:00Z |
| format | Article |
| id | mit-1721.1/133506.2 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:43:00Z |
| publishDate | 2022 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/133506.22024-03-15T16:10:20Z An omics-based framework for assessing the health risk of antimicrobial resistance genes Zhang, An-Ni Gaston, Jeffry M. Dai, Chengzhen L. Zhao, Shijie Poyet, Mathilde Groussin, Mathieu Yin, Xiaole Li, Li-Guan van Loosdrecht, Mark C. M. Topp, Edward Gillings, Michael R. Hanage, William P. Tiedje, James M. Moniz, Katya Alm, Eric J. Zhang, Tong Massachusetts Institute of Technology. Department of Biological Engineering Massachusetts Institute of Technology. Center for Microbiome Informatics and Therapeutics <jats:title>Abstract</jats:title><jats:p>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.</jats:p> 2022-05-18T15:30:42Z 2021-10-27T19:53:13Z 2022-05-18T15:30:42Z 2021-08 2021-04 2021-08-24T17:57:26Z Article http://purl.org/eprint/type/JournalArticle 2041-1723 https://hdl.handle.net/1721.1/133506.2 en http://dx.doi.org/10.1038/s41467-021-25096-3 Nature Communications Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/octet-stream Springer Science and Business Media LLC Nature |
| spellingShingle | Zhang, An-Ni Gaston, Jeffry M. Dai, Chengzhen L. Zhao, Shijie Poyet, Mathilde Groussin, Mathieu Yin, Xiaole Li, Li-Guan van Loosdrecht, Mark C. M. Topp, Edward Gillings, Michael R. Hanage, William P. Tiedje, James M. Moniz, Katya Alm, Eric J. Zhang, Tong An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title | An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title_full | An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title_fullStr | An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title_full_unstemmed | An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title_short | An omics-based framework for assessing the health risk of antimicrobial resistance genes |
| title_sort | omics based framework for assessing the health risk of antimicrobial resistance genes |
| url | https://hdl.handle.net/1721.1/133506.2 |
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