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CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database
The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825576/ https://www.ncbi.nlm.nih.gov/pubmed/36263822 http://dx.doi.org/10.1093/nar/gkac920 |
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author | Alcock, Brian P Huynh, William Chalil, Romeo Smith, Keaton W Raphenya, Amogelang R Wlodarski, Mateusz A Edalatmand, Arman Petkau, Aaron Syed, Sohaib A Tsang, Kara K Baker, Sheridan J C Dave, Mugdha McCarthy, Madeline C Mukiri, Karyn M Nasir, Jalees A Golbon, Bahar Imtiaz, Hamna Jiang, Xingjian Kaur, Komal Kwong, Megan Liang, Zi Cheng Niu, Keyu C Shan, Prabakar Yang, Jasmine Y J Gray, Kristen L Hoad, Gemma R Jia, Baofeng Bhando, Timsy Carfrae, Lindsey A Farha, Maya A French, Shawn Gordzevich, Rodion Rachwalski, Kenneth Tu, Megan M Bordeleau, Emily Dooley, Damion Griffiths, Emma Zubyk, Haley L Brown, Eric D Maguire, Finlay Beiko, Robert G Hsiao, William W L Brinkman, Fiona S L Van Domselaar, Gary McArthur, Andrew G |
author_facet | Alcock, Brian P Huynh, William Chalil, Romeo Smith, Keaton W Raphenya, Amogelang R Wlodarski, Mateusz A Edalatmand, Arman Petkau, Aaron Syed, Sohaib A Tsang, Kara K Baker, Sheridan J C Dave, Mugdha McCarthy, Madeline C Mukiri, Karyn M Nasir, Jalees A Golbon, Bahar Imtiaz, Hamna Jiang, Xingjian Kaur, Komal Kwong, Megan Liang, Zi Cheng Niu, Keyu C Shan, Prabakar Yang, Jasmine Y J Gray, Kristen L Hoad, Gemma R Jia, Baofeng Bhando, Timsy Carfrae, Lindsey A Farha, Maya A French, Shawn Gordzevich, Rodion Rachwalski, Kenneth Tu, Megan M Bordeleau, Emily Dooley, Damion Griffiths, Emma Zubyk, Haley L Brown, Eric D Maguire, Finlay Beiko, Robert G Hsiao, William W L Brinkman, Fiona S L Van Domselaar, Gary McArthur, Andrew G |
author_sort | Alcock, Brian P |
collection | PubMed |
description | The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts. |
format | Online Article Text |
id | pubmed-9825576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98255762023-01-10 CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database Alcock, Brian P Huynh, William Chalil, Romeo Smith, Keaton W Raphenya, Amogelang R Wlodarski, Mateusz A Edalatmand, Arman Petkau, Aaron Syed, Sohaib A Tsang, Kara K Baker, Sheridan J C Dave, Mugdha McCarthy, Madeline C Mukiri, Karyn M Nasir, Jalees A Golbon, Bahar Imtiaz, Hamna Jiang, Xingjian Kaur, Komal Kwong, Megan Liang, Zi Cheng Niu, Keyu C Shan, Prabakar Yang, Jasmine Y J Gray, Kristen L Hoad, Gemma R Jia, Baofeng Bhando, Timsy Carfrae, Lindsey A Farha, Maya A French, Shawn Gordzevich, Rodion Rachwalski, Kenneth Tu, Megan M Bordeleau, Emily Dooley, Damion Griffiths, Emma Zubyk, Haley L Brown, Eric D Maguire, Finlay Beiko, Robert G Hsiao, William W L Brinkman, Fiona S L Van Domselaar, Gary McArthur, Andrew G Nucleic Acids Res Database Issue The Comprehensive Antibiotic Resistance Database (CARD; card.mcmaster.ca) combines the Antibiotic Resistance Ontology (ARO) with curated AMR gene (ARG) sequences and resistance-conferring mutations to provide an informatics framework for annotation and interpretation of resistomes. As of version 3.2.4, CARD encompasses 6627 ontology terms, 5010 reference sequences, 1933 mutations, 3004 publications, and 5057 AMR detection models that can be used by the accompanying Resistance Gene Identifier (RGI) software to annotate genomic or metagenomic sequences. Focused curation enhancements since 2020 include expanded β-lactamase curation, incorporation of likelihood-based AMR mutations for Mycobacterium tuberculosis, addition of disinfectants and antiseptics plus their associated ARGs, and systematic curation of resistance-modifying agents. This expanded curation includes 180 new AMR gene families, 15 new drug classes, 1 new resistance mechanism, and two new ontological relationships: evolutionary_variant_of and is_small_molecule_inhibitor. In silico prediction of resistomes and prevalence statistics of ARGs has been expanded to 377 pathogens, 21,079 chromosomes, 2,662 genomic islands, 41,828 plasmids and 155,606 whole-genome shotgun assemblies, resulting in collation of 322,710 unique ARG allele sequences. New features include the CARD:Live collection of community submitted isolate resistome data and the introduction of standardized 15 character CARD Short Names for ARGs to support machine learning efforts. Oxford University Press 2022-10-20 /pmc/articles/PMC9825576/ /pubmed/36263822 http://dx.doi.org/10.1093/nar/gkac920 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Database Issue Alcock, Brian P Huynh, William Chalil, Romeo Smith, Keaton W Raphenya, Amogelang R Wlodarski, Mateusz A Edalatmand, Arman Petkau, Aaron Syed, Sohaib A Tsang, Kara K Baker, Sheridan J C Dave, Mugdha McCarthy, Madeline C Mukiri, Karyn M Nasir, Jalees A Golbon, Bahar Imtiaz, Hamna Jiang, Xingjian Kaur, Komal Kwong, Megan Liang, Zi Cheng Niu, Keyu C Shan, Prabakar Yang, Jasmine Y J Gray, Kristen L Hoad, Gemma R Jia, Baofeng Bhando, Timsy Carfrae, Lindsey A Farha, Maya A French, Shawn Gordzevich, Rodion Rachwalski, Kenneth Tu, Megan M Bordeleau, Emily Dooley, Damion Griffiths, Emma Zubyk, Haley L Brown, Eric D Maguire, Finlay Beiko, Robert G Hsiao, William W L Brinkman, Fiona S L Van Domselaar, Gary McArthur, Andrew G CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title | CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title_full | CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title_fullStr | CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title_full_unstemmed | CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title_short | CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database |
title_sort | card 2023: expanded curation, support for machine learning, and resistome prediction at the comprehensive antibiotic resistance database |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825576/ https://www.ncbi.nlm.nih.gov/pubmed/36263822 http://dx.doi.org/10.1093/nar/gkac920 |
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