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Transmission dynamics study of tuberculosis isolates with whole genome sequencing in southern Sweden.

Journal article
Authors Nader Alaridah
Erika Tång Hallbäck
Niclas Winqvist
Erik Sturegård
Bodil Jönsson
Erik Tenland
Christina Welinder-Olsson
Patrik Medstrand
Bertil Kaijser
Gabriela Godaly
Published in Scientific reports
Volume 9
Issue 1
ISSN 2045-2322
Publication year 2019
Published at Institute of Biomedicine, Department of Infectious Medicine
Language en
Links dx.doi.org/10.1038/s41598-019-39971...
www.ncbi.nlm.nih.gov/entrez/query.f...
Subject categories Clinical Laboratory Medicine, Infectious Medicine, Respiratory Medicine and Allergy

Abstract

Epidemiological contact tracing complemented with genotyping of clinical Mycobacterium tuberculosis isolates is important for understanding disease transmission. In Sweden, tuberculosis (TB) is mostly reported in migrant and homeless where epidemiologic contact tracing could pose a problem. This study compared epidemiologic linking with genotyping in a low burden country. Mycobacterium tuberculosis isolates (n = 93) collected at Scania University Hospital in Southern Sweden were analysed with the standard genotyping method mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR) and the results were compared with whole genome sequencing (WGS). Using a maximum of twelve single nucleotide polymorphisms (SNPs) as the upper threshold of genomic relatedness noted among hosts, we identified 18 clusters with WGS comprising 52 patients with overall pairwise genetic maximum distances ranging from zero to nine SNPs. MIRU-VNTR and WGS clustered the same isolates, although the distribution differed depending on MIRU-VNTR limitations. Both genotyping techniques identified clusters where epidemiologic linking was insufficient, although WGS had higher correlation with epidemiologic data. To summarize, WGS provided better resolution of transmission than MIRU-VNTR in a setting with low TB incidence. WGS predicted epidemiologic links better which could consolidate and correct the epidemiologically linked cases, avoiding thus false clustering.

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