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Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence
Background. Accurate tracking of Clostridium difficile transmission within healthcare settings is key to its containment but is hindered by the lack of discriminatory power of standard genotyping methods. We describe a whole-genome phylogenetic-based method to track the transmission of individual cl...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772841/ https://www.ncbi.nlm.nih.gov/pubmed/26683317 http://dx.doi.org/10.1093/cid/civ1031 |
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author | Kumar, Nitin Miyajima, Fabio He, Miao Roberts, Paul Swale, Andrew Ellison, Louise Pickard, Derek Smith, Godfrey Molyneux, Rebecca Dougan, Gordon Parkhill, Julian Wren, Brendan W. Parry, Christopher M. Pirmohamed, Munir Lawley, Trevor D. |
author_facet | Kumar, Nitin Miyajima, Fabio He, Miao Roberts, Paul Swale, Andrew Ellison, Louise Pickard, Derek Smith, Godfrey Molyneux, Rebecca Dougan, Gordon Parkhill, Julian Wren, Brendan W. Parry, Christopher M. Pirmohamed, Munir Lawley, Trevor D. |
author_sort | Kumar, Nitin |
collection | PubMed |
description | Background. Accurate tracking of Clostridium difficile transmission within healthcare settings is key to its containment but is hindered by the lack of discriminatory power of standard genotyping methods. We describe a whole-genome phylogenetic-based method to track the transmission of individual clones in infected hospital patients from the epidemic C. difficile 027/ST1 lineage, and to distinguish between the 2 causes of recurrent disease, relapse (same strain), or reinfection (different strain). Methods. We monitored patients with C. difficile infection in a UK hospital over a 2-year period. We performed whole-genome sequencing and phylogenetic analysis of 108 strains isolated from symptomatic patients. High-resolution phylogeny was integrated with in-hospital transfers and contact data to create an infection network linking individual patients and specific hospital wards. Results. Epidemic C. difficile 027/ST1 caused the majority of infections during our sampling period. Integration of whole-genome single nucleotide polymorphism (SNP) phylogenetic analysis, which accurately discriminated between 27 distinct SNP genotypes, with patient movement and contact data identified 32 plausible transmission events, including ward-based contamination (66%) or direct donor–recipient contact (34%). Highly contagious donors were identified who contributed to the persistence of clones within distinct hospital wards and the spread of clones between wards, especially in areas of intense turnover. Recurrent cases were identified between 4 and 26 weeks, highlighting the limitation of the standard <8-week cutoff used for patient diagnosis and management. Conclusions. Genome-based infection tracking to monitor the persistence and spread of C. difficile within healthcare facilities could inform infection control and patient management. |
format | Online Article Text |
id | pubmed-4772841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47728412016-03-01 Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence Kumar, Nitin Miyajima, Fabio He, Miao Roberts, Paul Swale, Andrew Ellison, Louise Pickard, Derek Smith, Godfrey Molyneux, Rebecca Dougan, Gordon Parkhill, Julian Wren, Brendan W. Parry, Christopher M. Pirmohamed, Munir Lawley, Trevor D. Clin Infect Dis Articles and Commentaries Background. Accurate tracking of Clostridium difficile transmission within healthcare settings is key to its containment but is hindered by the lack of discriminatory power of standard genotyping methods. We describe a whole-genome phylogenetic-based method to track the transmission of individual clones in infected hospital patients from the epidemic C. difficile 027/ST1 lineage, and to distinguish between the 2 causes of recurrent disease, relapse (same strain), or reinfection (different strain). Methods. We monitored patients with C. difficile infection in a UK hospital over a 2-year period. We performed whole-genome sequencing and phylogenetic analysis of 108 strains isolated from symptomatic patients. High-resolution phylogeny was integrated with in-hospital transfers and contact data to create an infection network linking individual patients and specific hospital wards. Results. Epidemic C. difficile 027/ST1 caused the majority of infections during our sampling period. Integration of whole-genome single nucleotide polymorphism (SNP) phylogenetic analysis, which accurately discriminated between 27 distinct SNP genotypes, with patient movement and contact data identified 32 plausible transmission events, including ward-based contamination (66%) or direct donor–recipient contact (34%). Highly contagious donors were identified who contributed to the persistence of clones within distinct hospital wards and the spread of clones between wards, especially in areas of intense turnover. Recurrent cases were identified between 4 and 26 weeks, highlighting the limitation of the standard <8-week cutoff used for patient diagnosis and management. Conclusions. Genome-based infection tracking to monitor the persistence and spread of C. difficile within healthcare facilities could inform infection control and patient management. Oxford University Press 2016-03-15 2015-12-18 /pmc/articles/PMC4772841/ /pubmed/26683317 http://dx.doi.org/10.1093/cid/civ1031 Text en © The Author 2015. Published by Oxford University Press for the Infectious Diseases Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles and Commentaries Kumar, Nitin Miyajima, Fabio He, Miao Roberts, Paul Swale, Andrew Ellison, Louise Pickard, Derek Smith, Godfrey Molyneux, Rebecca Dougan, Gordon Parkhill, Julian Wren, Brendan W. Parry, Christopher M. Pirmohamed, Munir Lawley, Trevor D. Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title | Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title_full | Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title_fullStr | Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title_full_unstemmed | Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title_short | Genome-Based Infection Tracking Reveals Dynamics of Clostridium difficile Transmission and Disease Recurrence |
title_sort | genome-based infection tracking reveals dynamics of clostridium difficile transmission and disease recurrence |
topic | Articles and Commentaries |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4772841/ https://www.ncbi.nlm.nih.gov/pubmed/26683317 http://dx.doi.org/10.1093/cid/civ1031 |
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