Tracking a tuberculosis outbreak over 21 years: strain-specific single nucleotide polymorphism-typing combined with targeted whole genome sequencing.

Stucki, David; Ballif, Marie; Bodmer, Thomas; Coscolla, Mireia; Maurer, Anne-Marie; Droz, Sara Christine; Butz, Christa; Borrell, Sonia; Längle, Christel; Feldmann, Julia; Furrer, Hansjakob; Mordasini, Carlo; Helbling, Peter; Rieder, Hans L; Egger, Matthias; Gagneux, Sébastien; Fenner, Lukas (2015). Tracking a tuberculosis outbreak over 21 years: strain-specific single nucleotide polymorphism-typing combined with targeted whole genome sequencing. Journal of infectious diseases, 211(8), pp. 1306-1316. Oxford University Press 10.1093/infdis/jiu601

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BACKGROUND  Whole genome sequencing (WGS) is increasingly used in molecular-epidemiological investigations of bacterial pathogens, despite cost- and time-intensive analyses. We combined strain-specific single nucleotide polymorphism (SNP)-typing and targeted WGS to investigate a tuberculosis cluster spanning 21 years in Bern, Switzerland. METHODS  Based on genome sequences of three historical outbreak Mycobacterium tuberculosis isolates, we developed a strain-specific SNP-typing assay to identify further cases. We screened 1,642 patient isolates, and performed WGS on all identified cluster isolates. We extracted SNPs to construct genomic networks. Clinical and social data were retrospectively collected. RESULTS  We identified 68 patients associated with the outbreak strain. Most were diagnosed in 1991-1995, but cases were observed until 2011. Two thirds belonged to the homeless and substance abuser milieu. Targeted WGS revealed 133 variable SNP positions among outbreak isolates. Genomic network analyses suggested a single origin of the outbreak, with subsequent division into three sub-clusters. Isolates from patients with confirmed epidemiological links differed by 0-11 SNPs. CONCLUSIONS  Strain-specific SNP-genotyping allowed rapid and inexpensive identification of M. tuberculosis outbreak isolates in a population-based strain collection. Subsequent targeted WGS provided detailed insights into transmission dynamics. This combined approach could be applied to track bacterial pathogens in real-time and at high resolution.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Social and Preventive Medicine
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Infectiology
04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases
04 Faculty of Medicine > Service Sector > Institute for Infectious Diseases > Mycobacteriology

UniBE Contributor:

Ballif, Marie; Bodmer, Thomas; Droz, Sara Christine; Längle, Christel; Furrer, Hansjakob; Mordasini, Carlo; Egger, Matthias and Fenner, Lukas

Subjects:

600 Technology > 610 Medicine & health
300 Social sciences, sociology & anthropology > 360 Social problems & social services
500 Science > 570 Life sciences; biology

ISSN:

0022-1899

Publisher:

Oxford University Press

Language:

English

Submitter:

Annelies Luginbühl

Date Deposited:

03 Dec 2014 14:39

Last Modified:

28 Apr 2018 02:32

Publisher DOI:

10.1093/infdis/jiu601

PubMed ID:

25362193

Additional Information:

Stucki and Ballif contributed equally to this work.

BORIS DOI:

10.7892/boris.59939

URI:

https://boris.unibe.ch/id/eprint/59939

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