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A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks

Whole-genome sequencing is increasingly adopted in clinical settings to identify pathogen transmissions, though largely as a retrospective tool. Prospective monitoring, in which samples are continuously added and compared to previous samples, can generate more actionable information. To enable prosp...

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Autores principales: Aggelen, Helen van, Kolde, Raivo, Chamarthi, Hareesh, Loving, Joshua, Fan, Yu, Fallon, John T., Huang, Weihua, Wang, Guiqing, Fortunato-Habib, Mary M., Carmona, Juan J., Gross, Brian D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534532/
https://www.ncbi.nlm.nih.gov/pubmed/31127153
http://dx.doi.org/10.1038/s41598-019-44189-0
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author Aggelen, Helen van
Kolde, Raivo
Chamarthi, Hareesh
Loving, Joshua
Fan, Yu
Fallon, John T.
Huang, Weihua
Wang, Guiqing
Fortunato-Habib, Mary M.
Carmona, Juan J.
Gross, Brian D.
author_facet Aggelen, Helen van
Kolde, Raivo
Chamarthi, Hareesh
Loving, Joshua
Fan, Yu
Fallon, John T.
Huang, Weihua
Wang, Guiqing
Fortunato-Habib, Mary M.
Carmona, Juan J.
Gross, Brian D.
author_sort Aggelen, Helen van
collection PubMed
description Whole-genome sequencing is increasingly adopted in clinical settings to identify pathogen transmissions, though largely as a retrospective tool. Prospective monitoring, in which samples are continuously added and compared to previous samples, can generate more actionable information. To enable prospective pathogen comparison, genomic relatedness metrics based on single-nucleotide differences must be consistent across time, efficient to compute and reliable for a large variety of samples. The choice of genomic regions to compare, i.e., the core genome, is critical to obtain a good metric. We propose a novel core genome method that selects conserved sequences in the reference genome by comparing its k-mer content to that of publicly available genome assemblies. The conserved-sequence genome is sample set-independent, which enables prospective pathogen monitoring. Based on clinical data sets of 3436 S. aureus, 1362 K. pneumoniae and 348 E. faecium samples, ROC curves demonstrate that the conserved-sequence genome disambiguates same-patient samples better than a core genome consisting of conserved genes. The conserved-sequence genome confirms outbreak samples with high sensitivity: in a set of 2335 S. aureus samples, it correctly identifies 44 out of 44 known outbreak samples, whereas the conserved-gene method confirms 38 known outbreak samples.
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spelling pubmed-65345322019-06-03 A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks Aggelen, Helen van Kolde, Raivo Chamarthi, Hareesh Loving, Joshua Fan, Yu Fallon, John T. Huang, Weihua Wang, Guiqing Fortunato-Habib, Mary M. Carmona, Juan J. Gross, Brian D. Sci Rep Article Whole-genome sequencing is increasingly adopted in clinical settings to identify pathogen transmissions, though largely as a retrospective tool. Prospective monitoring, in which samples are continuously added and compared to previous samples, can generate more actionable information. To enable prospective pathogen comparison, genomic relatedness metrics based on single-nucleotide differences must be consistent across time, efficient to compute and reliable for a large variety of samples. The choice of genomic regions to compare, i.e., the core genome, is critical to obtain a good metric. We propose a novel core genome method that selects conserved sequences in the reference genome by comparing its k-mer content to that of publicly available genome assemblies. The conserved-sequence genome is sample set-independent, which enables prospective pathogen monitoring. Based on clinical data sets of 3436 S. aureus, 1362 K. pneumoniae and 348 E. faecium samples, ROC curves demonstrate that the conserved-sequence genome disambiguates same-patient samples better than a core genome consisting of conserved genes. The conserved-sequence genome confirms outbreak samples with high sensitivity: in a set of 2335 S. aureus samples, it correctly identifies 44 out of 44 known outbreak samples, whereas the conserved-gene method confirms 38 known outbreak samples. Nature Publishing Group UK 2019-05-24 /pmc/articles/PMC6534532/ /pubmed/31127153 http://dx.doi.org/10.1038/s41598-019-44189-0 Text en © The Author(s) 2019 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
Aggelen, Helen van
Kolde, Raivo
Chamarthi, Hareesh
Loving, Joshua
Fan, Yu
Fallon, John T.
Huang, Weihua
Wang, Guiqing
Fortunato-Habib, Mary M.
Carmona, Juan J.
Gross, Brian D.
A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title_full A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title_fullStr A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title_full_unstemmed A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title_short A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
title_sort core genome approach that enables prospective and dynamic monitoring of infectious outbreaks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6534532/
https://www.ncbi.nlm.nih.gov/pubmed/31127153
http://dx.doi.org/10.1038/s41598-019-44189-0
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