Verification of emerging genomic mutations in Mycobacterium tuberculosis allows transmission chains to be distinguished in an epidemiological typing cluster extending over thirty years
de Zwaan, Rina de Vries, Gerard Ubbelohde, Ella Mulder, Arnout Kamst-van Agterveld, Miranda Rebel, Karin Kautz, Saskia Kremer, Kristin Anthony, Richard M van Soolingen, Dick
de Zwaan, Rina
de Vries, Gerard
Ubbelohde, Ella
Mulder, Arnout
Kamst-van Agterveld, Miranda
Rebel, Karin
Kautz, Saskia
Kremer, Kristin
Anthony, Richard M
van Soolingen, Dick
Series / Report no.
Open Access
Type
Journal Article
Article
Article
Language
en
Date
2025-06-18
Research Projects
Organizational Units
Journal Issue
Title
Verification of emerging genomic mutations in Mycobacterium tuberculosis allows transmission chains to be distinguished in an epidemiological typing cluster extending over thirty years
Translated Title
Published in
PLoS One 2025; 20(6):e0319630
Abstract
Whole genome sequencing (WGS) is able to identify epidemiological links between Mycobacterium tuberculosis isolates. Recent clustering can be ruled out using a pre-defined single nucleotide polymorphism (SNP) threshold. If WGS clusters grow significantly over time limited genetic variability hampers epidemiological investigations. Newly emerging (informative) SNPs in isolates of an extended cluster growing for more than 30 years to >150 cases in the Netherlands were analysed. WGS data was analyzed from 61 sequencing files from 54 patients. Genomic positions that varied within the cluster isolates were carefully screened for minority populations in other isolates from the cluster. A transmission scheme was generated on the basis of WGS data alone then compared to the epidemiological information available. Fifty-two informative SNPs were identified, eight of which were also detected as mixed variants. One emerging SNP in dnaA (1199G > A R400H) has been observed in other transmitted strains and may be under selection. There was high concordance between the transmission chains suggested on basis of the newly emerging SNPs and scenarios identified using classical epidemiological cluster investigations. Analysis of filtered SNPs accumulating in the genome of M. tuberculosis in large clusters contains information on transmission dynamics and can be used to support epidemiological investigations.