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CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes
Due to recent developments in NGS technologies, genome sequencing is generating large volumes of new data containing a wealth of biological information. Understanding sequenced genomes in a biologically meaningful way and delineating their functional and metabolic landscapes is a first-level challen...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9196194/ https://www.ncbi.nlm.nih.gov/pubmed/35711759 http://dx.doi.org/10.3389/fmicb.2022.893474 |
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author | Duré, Felicita Mabel Silveira, Melise Chaves Rocha-de-Souza, Cláudio Marcos Leão, Robson Souza de Oliveira Santos, Ivson Cassiano Albano, Rodolpho Mattos Marques, Elizabeth Andrade D’Alincourt Carvalho-Assef, Ana Paula da Silva, Fabricio Alves Barbosa |
author_facet | Duré, Felicita Mabel Silveira, Melise Chaves Rocha-de-Souza, Cláudio Marcos Leão, Robson Souza de Oliveira Santos, Ivson Cassiano Albano, Rodolpho Mattos Marques, Elizabeth Andrade D’Alincourt Carvalho-Assef, Ana Paula da Silva, Fabricio Alves Barbosa |
author_sort | Duré, Felicita Mabel |
collection | PubMed |
description | Due to recent developments in NGS technologies, genome sequencing is generating large volumes of new data containing a wealth of biological information. Understanding sequenced genomes in a biologically meaningful way and delineating their functional and metabolic landscapes is a first-level challenge. Considering the global antimicrobial resistance (AMR) problem, investments to expand surveillance and improve existing genome analysis technologies are pressing. In addition, the speed at which new genomic data is generated surpasses our capacity to analyze it with available bioinformatics methods, thus creating a need to develop new, user-friendly and comprehensive analytical tools. To this end, we propose a new web application, CABGen, developed with open-source software. CABGen allows storing, organizing, analyzing, and interpreting bioinformatics data in a friendly, scalable, easy-to-use environment and can process data from bacterial isolates of different species and origins. CABGen has three modules: Upload Sequences, Analyze Sequences, and Verify Results. Functionalities include coverage estimation, species identification, de novo genome assembly, and assembly quality, genome annotation, MLST mapping, searches for genes related to AMR, virulence, and plasmids, and detection of point mutations in specific AMR genes. Visualization tools are also available, greatly facilitating the handling of biological data. The reports include those results that are clinically relevant. To illustrate the use of CABGen, whole-genome shotgun data from 181 bacterial isolates of different species collected in 5 Brazilian regions between 2018 and 2020 were uploaded and submitted to the platform’s modules. |
format | Online Article Text |
id | pubmed-9196194 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91961942022-06-15 CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes Duré, Felicita Mabel Silveira, Melise Chaves Rocha-de-Souza, Cláudio Marcos Leão, Robson Souza de Oliveira Santos, Ivson Cassiano Albano, Rodolpho Mattos Marques, Elizabeth Andrade D’Alincourt Carvalho-Assef, Ana Paula da Silva, Fabricio Alves Barbosa Front Microbiol Microbiology Due to recent developments in NGS technologies, genome sequencing is generating large volumes of new data containing a wealth of biological information. Understanding sequenced genomes in a biologically meaningful way and delineating their functional and metabolic landscapes is a first-level challenge. Considering the global antimicrobial resistance (AMR) problem, investments to expand surveillance and improve existing genome analysis technologies are pressing. In addition, the speed at which new genomic data is generated surpasses our capacity to analyze it with available bioinformatics methods, thus creating a need to develop new, user-friendly and comprehensive analytical tools. To this end, we propose a new web application, CABGen, developed with open-source software. CABGen allows storing, organizing, analyzing, and interpreting bioinformatics data in a friendly, scalable, easy-to-use environment and can process data from bacterial isolates of different species and origins. CABGen has three modules: Upload Sequences, Analyze Sequences, and Verify Results. Functionalities include coverage estimation, species identification, de novo genome assembly, and assembly quality, genome annotation, MLST mapping, searches for genes related to AMR, virulence, and plasmids, and detection of point mutations in specific AMR genes. Visualization tools are also available, greatly facilitating the handling of biological data. The reports include those results that are clinically relevant. To illustrate the use of CABGen, whole-genome shotgun data from 181 bacterial isolates of different species collected in 5 Brazilian regions between 2018 and 2020 were uploaded and submitted to the platform’s modules. Frontiers Media S.A. 2022-05-27 /pmc/articles/PMC9196194/ /pubmed/35711759 http://dx.doi.org/10.3389/fmicb.2022.893474 Text en Copyright © 2022 Duré, Silveira, Rocha-de-Souza, Leão, de Oliveira Santos, Albano, Marques, Carvalho-Assef and Silva. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Duré, Felicita Mabel Silveira, Melise Chaves Rocha-de-Souza, Cláudio Marcos Leão, Robson Souza de Oliveira Santos, Ivson Cassiano Albano, Rodolpho Mattos Marques, Elizabeth Andrade D’Alincourt Carvalho-Assef, Ana Paula da Silva, Fabricio Alves Barbosa CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title | CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title_full | CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title_fullStr | CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title_full_unstemmed | CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title_short | CABGen: A Web Application for the Bioinformatic Analysis of Bacterial Genomes |
title_sort | cabgen: a web application for the bioinformatic analysis of bacterial genomes |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9196194/ https://www.ncbi.nlm.nih.gov/pubmed/35711759 http://dx.doi.org/10.3389/fmicb.2022.893474 |
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