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Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks
BACKGROUND: While overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005–2006 and in 2010–2013. The outbreaks were centered within drug use and sexual ne...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261407/ https://www.ncbi.nlm.nih.gov/pubmed/30485280 http://dx.doi.org/10.1371/journal.pone.0202615 |
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author | Ezeoke, Ifeoma Galac, Madeline R. Lin, Ying Liem, Alvin T. Roth, Pierce A. Kilianski, Andrew Gibbons, Henry S. Bloch, Danielle Kornblum, John Del Rosso, Paula Janies, Daniel A. Weiss, Don |
author_facet | Ezeoke, Ifeoma Galac, Madeline R. Lin, Ying Liem, Alvin T. Roth, Pierce A. Kilianski, Andrew Gibbons, Henry S. Bloch, Danielle Kornblum, John Del Rosso, Paula Janies, Daniel A. Weiss, Don |
author_sort | Ezeoke, Ifeoma |
collection | PubMed |
description | BACKGROUND: While overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005–2006 and in 2010–2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns. METHODS: Whole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks. RESULTS: Neisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the outbreak strains, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no polymorphism was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations. CONCLUSIONS: Neisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission. |
format | Online Article Text |
id | pubmed-6261407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-62614072018-12-20 Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks Ezeoke, Ifeoma Galac, Madeline R. Lin, Ying Liem, Alvin T. Roth, Pierce A. Kilianski, Andrew Gibbons, Henry S. Bloch, Danielle Kornblum, John Del Rosso, Paula Janies, Daniel A. Weiss, Don PLoS One Research Article BACKGROUND: While overall rates of meningococcal disease have been declining in the United States for the past several decades, New York City (NYC) has experienced two serogroup C meningococcal disease outbreaks in 2005–2006 and in 2010–2013. The outbreaks were centered within drug use and sexual networks, were difficult to control, and required vaccine campaigns. METHODS: Whole Genome Sequencing (WGS) was used to analyze preserved meningococcal isolates collected before and during the two outbreaks. We integrated and analyzed epidemiologic, geographic, and genomic data to better understand transmission networks among patients. Betweenness centrality was used as a metric to understand the most important geographic nodes in the transmission networks. Comparative genomics was used to identify genes associated with the outbreaks. RESULTS: Neisseria meningitidis serogroup C (ST11/ET-37) was responsible for both outbreaks with each outbreak having distinct phylogenetic clusters. WGS did identify some misclassifications of isolates that were more distant from the outbreak strains, as well as those that should have been included based on high genomic similarity. Genomes for the second outbreak were more similar than the first and no polymorphism was found to either be unique or specific to either outbreak lineage. Betweenness centrality as applied to transmission networks based on phylogenetic analysis demonstrated that the outbreaks were transmitted within focal communities in NYC with few transmission events to other locations. CONCLUSIONS: Neisseria meningitidis is an ever changing pathogen and comparative genomic analyses can help elucidate how it spreads geographically to facilitate targeted interventions to interrupt transmission. Public Library of Science 2018-11-28 /pmc/articles/PMC6261407/ /pubmed/30485280 http://dx.doi.org/10.1371/journal.pone.0202615 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 Ezeoke, Ifeoma Galac, Madeline R. Lin, Ying Liem, Alvin T. Roth, Pierce A. Kilianski, Andrew Gibbons, Henry S. Bloch, Danielle Kornblum, John Del Rosso, Paula Janies, Daniel A. Weiss, Don Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title | Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title_full | Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title_fullStr | Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title_full_unstemmed | Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title_short | Tracking a serial killer: Integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
title_sort | tracking a serial killer: integrating phylogenetic relationships, epidemiology, and geography for two invasive meningococcal disease outbreaks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6261407/ https://www.ncbi.nlm.nih.gov/pubmed/30485280 http://dx.doi.org/10.1371/journal.pone.0202615 |
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