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Using Neisseria meningitidis genomic diversity to inform outbreak strain identification
Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177650/ https://www.ncbi.nlm.nih.gov/pubmed/34003852 http://dx.doi.org/10.1371/journal.ppat.1009586 |
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author | Retchless, Adam C. Chen, Alex Chang, How-Yi Blain, Amy E. McNamara, Lucy A. Mustapha, Mustapha M. Harrison, Lee H. Wang, Xin |
author_facet | Retchless, Adam C. Chen, Alex Chang, How-Yi Blain, Amy E. McNamara, Lucy A. Mustapha, Mustapha M. Harrison, Lee H. Wang, Xin |
author_sort | Retchless, Adam C. |
collection | PubMed |
description | Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010–2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions. |
format | Online Article Text |
id | pubmed-8177650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81776502021-06-07 Using Neisseria meningitidis genomic diversity to inform outbreak strain identification Retchless, Adam C. Chen, Alex Chang, How-Yi Blain, Amy E. McNamara, Lucy A. Mustapha, Mustapha M. Harrison, Lee H. Wang, Xin PLoS Pathog Research Article Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010–2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions. Public Library of Science 2021-05-18 /pmc/articles/PMC8177650/ /pubmed/34003852 http://dx.doi.org/10.1371/journal.ppat.1009586 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Retchless, Adam C. Chen, Alex Chang, How-Yi Blain, Amy E. McNamara, Lucy A. Mustapha, Mustapha M. Harrison, Lee H. Wang, Xin Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title | Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title_full | Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title_fullStr | Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title_full_unstemmed | Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title_short | Using Neisseria meningitidis genomic diversity to inform outbreak strain identification |
title_sort | using neisseria meningitidis genomic diversity to inform outbreak strain identification |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177650/ https://www.ncbi.nlm.nih.gov/pubmed/34003852 http://dx.doi.org/10.1371/journal.ppat.1009586 |
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