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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...

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Autores principales: Szarvas, Judit, Ahrenfeldt, Johanne, Cisneros, Jose Luis Bellod, Thomsen, Martin Christen Frølund, Aarestrup, Frank M., Lund, Ole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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.
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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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