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Genome-based infection tracking reveals dynamics of Clostridium difficile transmission and disease recurrence
Kumar, Nitin Miyajima, Fabio He, Miao Swale, Andrew Ellison, Louise Pickard, Derek Smith, Godfrey Molyneux, Rebecca Dougan, Gordon
Kumar, Nitin
Miyajima, Fabio
He, Miao
Swale, Andrew
Ellison, Louise
Pickard, Derek
Smith, Godfrey
Molyneux, Rebecca
Dougan, Gordon
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2015-12-18
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Abstract
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.
Citation
Kumar, N., Miyajima, F., He, M., Roberts, P. et al. (2016) Genome-based infection tracking reveals dynamics of Clostridium difficile transmission and disease recurrence, Clinical Infectious Diseases, 62(6), pp. 746–752, https://doi.org/10.1093/cid/civ1031
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Journal article
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en
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© 2015 The Authors. Published by Oxford University Press. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1093/cid/civ1031
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1058-4838
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1537-6591
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This work was supported by the Wellcome Trust (grant number 098051) and Medical Research Council UK (grant number PF451).