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Curation of the AMRFinderPlus databases: applications, functionality and impact

Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed...

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Autores principales: Feldgarden, Michael, Brover, Vyacheslav, Fedorov, Boris, Haft, Daniel H., Prasad, Arjun B., Klimke, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Microbiology Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455714/
https://www.ncbi.nlm.nih.gov/pubmed/35675101
http://dx.doi.org/10.1099/mgen.0.000832
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author Feldgarden, Michael
Brover, Vyacheslav
Fedorov, Boris
Haft, Daniel H.
Prasad, Arjun B.
Klimke, William
author_facet Feldgarden, Michael
Brover, Vyacheslav
Fedorov, Boris
Haft, Daniel H.
Prasad, Arjun B.
Klimke, William
author_sort Feldgarden, Michael
collection PubMed
description Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed to identify these genomic elements. Most of those tools rely on reference databases of nucleotide or protein sequences and collections of models and rules for analysis. While the tools are critical for the identification of AMR genes, the databases themselves also provide significant utility for researchers, for applications ranging from sequence analysis to information about AMR phenotypes. Additionally, these databases can be evaluated by domain experts and others to ensure their accuracy. Here we describe how we curate the genes, point mutations and blast rules, and hidden Markov models used in NCBI’s AMRFinderPlus, along with the quality-control steps we take to ensure database quality. We also describe the web interfaces that display the full structure of the database and their newly developed cross-browser relationships. Then, using the Reference Gene Catalog as an example, we detail how the databases, rules and models are made publicly available, as well as how to access the software. In addition, as part of the Pathogen Detection system, we have analysed over 1 million publicly available genomes using AMRFinderPlus and its databases. We discuss how the computed analyses generated by those tools can be accessed through a web interface. Finally, we conclude with NCBI’s plans to make these databases accessible over the long-term.
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spelling pubmed-94557142022-09-09 Curation of the AMRFinderPlus databases: applications, functionality and impact Feldgarden, Michael Brover, Vyacheslav Fedorov, Boris Haft, Daniel H. Prasad, Arjun B. Klimke, William Microb Genom Bioresources Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed to identify these genomic elements. Most of those tools rely on reference databases of nucleotide or protein sequences and collections of models and rules for analysis. While the tools are critical for the identification of AMR genes, the databases themselves also provide significant utility for researchers, for applications ranging from sequence analysis to information about AMR phenotypes. Additionally, these databases can be evaluated by domain experts and others to ensure their accuracy. Here we describe how we curate the genes, point mutations and blast rules, and hidden Markov models used in NCBI’s AMRFinderPlus, along with the quality-control steps we take to ensure database quality. We also describe the web interfaces that display the full structure of the database and their newly developed cross-browser relationships. Then, using the Reference Gene Catalog as an example, we detail how the databases, rules and models are made publicly available, as well as how to access the software. In addition, as part of the Pathogen Detection system, we have analysed over 1 million publicly available genomes using AMRFinderPlus and its databases. We discuss how the computed analyses generated by those tools can be accessed through a web interface. Finally, we conclude with NCBI’s plans to make these databases accessible over the long-term. Microbiology Society 2022-06-08 /pmc/articles/PMC9455714/ /pubmed/35675101 http://dx.doi.org/10.1099/mgen.0.000832 Text en https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License.
spellingShingle Bioresources
Feldgarden, Michael
Brover, Vyacheslav
Fedorov, Boris
Haft, Daniel H.
Prasad, Arjun B.
Klimke, William
Curation of the AMRFinderPlus databases: applications, functionality and impact
title Curation of the AMRFinderPlus databases: applications, functionality and impact
title_full Curation of the AMRFinderPlus databases: applications, functionality and impact
title_fullStr Curation of the AMRFinderPlus databases: applications, functionality and impact
title_full_unstemmed Curation of the AMRFinderPlus databases: applications, functionality and impact
title_short Curation of the AMRFinderPlus databases: applications, functionality and impact
title_sort curation of the amrfinderplus databases: applications, functionality and impact
topic Bioresources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9455714/
https://www.ncbi.nlm.nih.gov/pubmed/35675101
http://dx.doi.org/10.1099/mgen.0.000832
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