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PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks
BACKGROUND: Whole-genome sequencing (WGS) is increasingly used to map the spread of bacterial and viral pathogens in nosocomial settings. A limiting factor for more widespread adoption of WGS for hospital infection prevention practices is the availability of standardized tools for genomic epidemiolo...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670629/ https://www.ncbi.nlm.nih.gov/pubmed/33198787 http://dx.doi.org/10.1186/s13073-020-00798-3 |
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author | Berbel Caban, Ana Pak, Theodore R. Obla, Ajay Dupper, Amy C. Chacko, Kieran I. Fox, Lindsey Mills, Alexandra Ciferri, Brianne Oussenko, Irina Beckford, Colleen Chung, Marilyn Sebra, Robert Smith, Melissa Conolly, Sarah Patel, Gopi Kasarskis, Andrew Sullivan, Mitchell J. Altman, Deena R. van Bakel, Harm |
author_facet | Berbel Caban, Ana Pak, Theodore R. Obla, Ajay Dupper, Amy C. Chacko, Kieran I. Fox, Lindsey Mills, Alexandra Ciferri, Brianne Oussenko, Irina Beckford, Colleen Chung, Marilyn Sebra, Robert Smith, Melissa Conolly, Sarah Patel, Gopi Kasarskis, Andrew Sullivan, Mitchell J. Altman, Deena R. van Bakel, Harm |
author_sort | Berbel Caban, Ana |
collection | PubMed |
description | BACKGROUND: Whole-genome sequencing (WGS) is increasingly used to map the spread of bacterial and viral pathogens in nosocomial settings. A limiting factor for more widespread adoption of WGS for hospital infection prevention practices is the availability of standardized tools for genomic epidemiology. METHODS: We developed the Pathogen Sequencing Phylogenomic Outbreak Toolkit (PathoSPOT) to automate integration of genomic and medical record data for rapid detection and tracing of nosocomial outbreaks. To demonstrate its capabilities, we applied PathoSPOT to complete genome surveillance data of 197 MRSA bacteremia cases from two hospitals during a 2-year period. RESULTS: PathoSPOT identified 8 clonal clusters encompassing 33 patients (16.8% of cases), none of which had been recognized by standard practices. The largest cluster corresponded to a prolonged outbreak of a hospital-associated MRSA clone among 16 adults, spanning 9 wards over a period of 21 months. Analysis of precise timeline and location data with our toolkit suggested that an initial exposure event in a single ward led to infection and long-term colonization of multiple patients, followed by transmissions to other patients during recurrent hospitalizations. CONCLUSIONS: We demonstrate that PathoSPOT genomic surveillance enables the detection of complex transmission chains that are not readily apparent from epidemiological data and that contribute significantly to morbidity and mortality, enabling more effective intervention strategies. |
format | Online Article Text |
id | pubmed-7670629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76706292020-11-18 PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks Berbel Caban, Ana Pak, Theodore R. Obla, Ajay Dupper, Amy C. Chacko, Kieran I. Fox, Lindsey Mills, Alexandra Ciferri, Brianne Oussenko, Irina Beckford, Colleen Chung, Marilyn Sebra, Robert Smith, Melissa Conolly, Sarah Patel, Gopi Kasarskis, Andrew Sullivan, Mitchell J. Altman, Deena R. van Bakel, Harm Genome Med Research BACKGROUND: Whole-genome sequencing (WGS) is increasingly used to map the spread of bacterial and viral pathogens in nosocomial settings. A limiting factor for more widespread adoption of WGS for hospital infection prevention practices is the availability of standardized tools for genomic epidemiology. METHODS: We developed the Pathogen Sequencing Phylogenomic Outbreak Toolkit (PathoSPOT) to automate integration of genomic and medical record data for rapid detection and tracing of nosocomial outbreaks. To demonstrate its capabilities, we applied PathoSPOT to complete genome surveillance data of 197 MRSA bacteremia cases from two hospitals during a 2-year period. RESULTS: PathoSPOT identified 8 clonal clusters encompassing 33 patients (16.8% of cases), none of which had been recognized by standard practices. The largest cluster corresponded to a prolonged outbreak of a hospital-associated MRSA clone among 16 adults, spanning 9 wards over a period of 21 months. Analysis of precise timeline and location data with our toolkit suggested that an initial exposure event in a single ward led to infection and long-term colonization of multiple patients, followed by transmissions to other patients during recurrent hospitalizations. CONCLUSIONS: We demonstrate that PathoSPOT genomic surveillance enables the detection of complex transmission chains that are not readily apparent from epidemiological data and that contribute significantly to morbidity and mortality, enabling more effective intervention strategies. BioMed Central 2020-11-16 /pmc/articles/PMC7670629/ /pubmed/33198787 http://dx.doi.org/10.1186/s13073-020-00798-3 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Berbel Caban, Ana Pak, Theodore R. Obla, Ajay Dupper, Amy C. Chacko, Kieran I. Fox, Lindsey Mills, Alexandra Ciferri, Brianne Oussenko, Irina Beckford, Colleen Chung, Marilyn Sebra, Robert Smith, Melissa Conolly, Sarah Patel, Gopi Kasarskis, Andrew Sullivan, Mitchell J. Altman, Deena R. van Bakel, Harm PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title | PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title_full | PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title_fullStr | PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title_full_unstemmed | PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title_short | PathoSPOT genomic epidemiology reveals under-the-radar nosocomial outbreaks |
title_sort | pathospot genomic epidemiology reveals under-the-radar nosocomial outbreaks |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670629/ https://www.ncbi.nlm.nih.gov/pubmed/33198787 http://dx.doi.org/10.1186/s13073-020-00798-3 |
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