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Whole-genome sequencing to identify transmission of Mycobacterium abscessus between patients with cystic fibrosis: a retrospective cohort study

Open access
Bryant, Josephine M, Grogono, Dorothy M, Greaves, Daniel, Foweraker, Juliet, Roddick, Iain, Inns, Thomas, Reacher, Mark, Haworth, Charles S, Curran, Martin D, Harris, Simon R, Peacock, Sharon J, Parkhill, Julian, Floto, R Andres·2013·The Lancet

Abstract

Summary Background Increasing numbers of individuals with cystic fibrosis are becoming infected with the multidrug-resistant non-tuberculous mycobacterium (NTM) Mycobacterium abscessus, which causes progressive lung damage and is extremely challenging to treat. How this organism is acquired is not currently known, but there is growing concern that person-to-person transmission could occur. We aimed to define the mechanisms of acquisition of M abscessus in individuals with cystic fibrosis. Method Whole genome sequencing and antimicrobial susceptibility testing were done on 168 consecutive isolates of M abscessus from 31 patients attending an adult cystic fibrosis centre in the UK between 2007 and 2011. In parallel, we undertook detailed environmental testing for NTM and defined potential opportunities for transmission between patients both in and out of hospital using epidemiological data and social network analysis. Findings Phylogenetic analysis revealed two clustered outbreaks of near-identical isolates of the M abscessus subspecies massiliense (from 11 patients), differing by less than ten base pairs. This variation represents less diversity than that seen within isolates from a single individual, strongly indicating between-patient transmission. All patients within these clusters had numerous opportunities for within-hospital transmission from other individuals, while comprehensive environmental sampling, initiated during the outbreak, failed to detect any potential point source of NTM infection. The clusters of M abscessus subspecies massiliense showed evidence of transmission of mutations acquired during infection of an individual to other patients. Thus, isolates with constitutive resistance to amikacin and clarithromycin were isolated from several individuals never previously exposed to long-term macrolides or aminoglycosides, further indicating cross-infection. Interpretation Whole genome sequencing has revealed frequent transmission of multidrug resistant NTM between patients with cystic fibrosis despite conventional cross-infection measures. Although the exact transmission route is yet to be established, our epidemiological analysis suggests that it could be indirect. Funding The Wellcome Trust, Papworth Hospital, NIHR Cambridge Biomedical Research Centre, UK Health Protection Agency, Medical Research Council, and the UKCRC Translational Infection Research Initiative.

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Metadata

Authors
Bryant, J. M., Grogono, D. M., Greaves, D., Foweraker, J., Roddick, I., Inns, T., Reacher, M., Haworth, C. S., Curran, M. D., Harris, S. R., Peacock, S. J., Parkhill, J., & Floto, R. A.
Venue
The Lancet
Publisher
Elsevier BV
Published
2013-05
Volume
381
Issue
9877
Pages
1551-1560
ISSN
  • 0099-5355 (ISSN-L)
  • 0140-6736
OpenAlex
W2021463425
Cited by
694
References
3
FWCI
49.72
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Whole-genome sequencing to identify transmission of Mycobacterium abscessus between patients with cystic fibrosis: a retrospective cohort study. https://app.cochat.ai/papers/10.1016/s0140-6736(13)60632-7
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Bryant, J. M., Grogono, D. M., Greaves, D., Foweraker, J., Roddick, I., Inns, T., Reacher, M., Haworth, C. S., Curran, M. D., Harris, S. R., Peacock, S. J., Parkhill, J., & Floto, R. A. (2013). Whole-genome sequencing to identify transmission of Mycobacterium abscessus between patients with cystic fibrosis: a retrospective cohort study. The Lancet. https://doi.org/10.1016/s0140-6736(13)60632-7

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.