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Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform
Public health authorities whole-genome sequence thousands of isolates each month for microbial diagnostics and surveillance of pathogenic bacteria. The computational methods have not kept up with the deluge of data and the need for real-time results. We have therefore created a bioinformatics pipeli...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083913/ https://www.ncbi.nlm.nih.gov/pubmed/32198478 http://dx.doi.org/10.1038/s42003-020-0869-5 |
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author | Szarvas, Judit Ahrenfeldt, Johanne Cisneros, Jose Luis Bellod Thomsen, Martin Christen Frølund Aarestrup, Frank M. Lund, Ole |
author_facet | Szarvas, Judit Ahrenfeldt, Johanne Cisneros, Jose Luis Bellod Thomsen, Martin Christen Frølund Aarestrup, Frank M. Lund, Ole |
author_sort | Szarvas, Judit |
collection | PubMed |
description | Public health authorities whole-genome sequence thousands of isolates each month for microbial diagnostics and surveillance of pathogenic bacteria. The computational methods have not kept up with the deluge of data and the need for real-time results. We have therefore created a bioinformatics pipeline for rapid subtyping and continuous phylogenomic analysis of bacterial samples, suited for large-scale surveillance. The data is divided into sets by mapping to reference genomes, then consensus sequences are generated. Nucleotide based genetic distance is calculated between the sequences in each set, and isolates are clustered together at 10 single-nucleotide polymorphisms. Phylogenetic trees are inferred from the non-redundant sequences and the clustered isolates are added back. The method is accurate at grouping outbreak strains together, while discriminating them from non-outbreak strains. The pipeline is applied in Evergreen Online, which processes publicly available sequencing data from foodborne bacterial pathogens on a daily basis, updating phylogenetic trees as needed. |
format | Online Article Text |
id | pubmed-7083913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70839132020-03-26 Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform Szarvas, Judit Ahrenfeldt, Johanne Cisneros, Jose Luis Bellod Thomsen, Martin Christen Frølund Aarestrup, Frank M. Lund, Ole Commun Biol Article Public health authorities whole-genome sequence thousands of isolates each month for microbial diagnostics and surveillance of pathogenic bacteria. The computational methods have not kept up with the deluge of data and the need for real-time results. We have therefore created a bioinformatics pipeline for rapid subtyping and continuous phylogenomic analysis of bacterial samples, suited for large-scale surveillance. The data is divided into sets by mapping to reference genomes, then consensus sequences are generated. Nucleotide based genetic distance is calculated between the sequences in each set, and isolates are clustered together at 10 single-nucleotide polymorphisms. Phylogenetic trees are inferred from the non-redundant sequences and the clustered isolates are added back. The method is accurate at grouping outbreak strains together, while discriminating them from non-outbreak strains. The pipeline is applied in Evergreen Online, which processes publicly available sequencing data from foodborne bacterial pathogens on a daily basis, updating phylogenetic trees as needed. Nature Publishing Group UK 2020-03-20 /pmc/articles/PMC7083913/ /pubmed/32198478 http://dx.doi.org/10.1038/s42003-020-0869-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Szarvas, Judit Ahrenfeldt, Johanne Cisneros, Jose Luis Bellod Thomsen, Martin Christen Frølund Aarestrup, Frank M. Lund, Ole Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title | Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title_full | Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title_fullStr | Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title_full_unstemmed | Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title_short | Large scale automated phylogenomic analysis of bacterial isolates and the Evergreen Online platform |
title_sort | large scale automated phylogenomic analysis of bacterial isolates and the evergreen online platform |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083913/ https://www.ncbi.nlm.nih.gov/pubmed/32198478 http://dx.doi.org/10.1038/s42003-020-0869-5 |
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