Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission

The global tuberculosis (TB) epidemic is driven by primary transmission. Pathogen genome sequencing is increasingly used in molecular epidemiology and outbreak investigations. Based on contact tracing and epidemiological links, Single Nucleotide Polymorphism (SNP) cut-offs, ranging from 3 to 12 SNPs, identify probable transmission clusters or exclude direct transmission. However, contact tracing can be limited by recall bias and inconsistent methodologies across TB settings. We propose phylodynamic models, i.e. methods to infer transmission processes from pathogen genomes and associated epidemiological data, as an alternative reference to infer transmission events. We analyzed 2,008 whole-genome sequences from Dutch TB patients collected from 2015 to 2019. Genetic clusters were defined within a 20-SNP range, and the phylodynamic model phybreak was employed to infer transmission. Probable transmission SNP cut-offs were assessed by the proportion of inferred transmission events with a SNP distance below these cut-offs. A total of 79 clusters were identified, with a median size of 4 isolates (IQR = 3-8). A SNP cut-off of 4 captured 98% of inferred transmission events while reducing pairs without transmission links. A cut-off beyond 12 SNPs effectively excluded transmission. Phylodynamic approaches provide a valuable alternative to contact tracing for defining SNP cut-offs, allowing for a more precise assessment of transmission events.

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Publication Details

Journal
Scientific Reports
Published
2025-03-28
DOI
https://doi.org/10.1038/s41598-025-94646-2
Citations
7
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
9.48
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article

Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission

Matthias I. Gröschel, Don Klinkenberg, Rina de Zwaan, Richard Anthony et al.
7 citations
Scientific Reports
Mycobacterium research and diagnosis
9.48
article

Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission

Matthias I. Gröschel, Don Klinkenberg, Rina de Zwaan, Richard Anthony, Mirjam Kretzschmar, Bastiaan R. Van der Roest, Martin Bootsma, Egil A.J. Fischer
article en
7 citations

Abstract

The global tuberculosis (TB) epidemic is driven by primary transmission. Pathogen genome sequencing is increasingly used in molecular epidemiology and outbreak investigations. Based on contact tracing and epidemiological links, Single Nucleotide Polymorphism (SNP) cut-offs, ranging from 3 to 12 SNPs, identify probable transmission clusters or exclude direct transmission. However, contact tracing can be limited by recall bias and inconsistent methodologies across TB settings. We propose phylodynamic models, i.e. methods to infer transmission processes from pathogen genomes and associated epidemiological data, as an alternative reference to infer transmission events. We analyzed 2,008 whole-genome sequences from Dutch TB patients collected from 2015 to 2019. Genetic clusters were defined within a 20-SNP range, and the phylodynamic model phybreak was employed to infer transmission. Probable transmission SNP cut-offs were assessed by the proportion of inferred transmission events with a SNP distance below these cut-offs. A total of 79 clusters were identified, with a median size of 4 isolates (IQR = 3-8). A SNP cut-off of 4 captured 98% of inferred transmission events while reducing pairs without transmission links. A cut-off beyond 12 SNPs effectively excluded transmission. Phylodynamic approaches provide a valuable alternative to contact tracing for defining SNP cut-offs, allowing for a more precise assessment of transmission events.

Scientific ReportsVol. 15(1)
University of Applied Sciences Utrecht (NL), Utrecht University (NL), University of Münster (DE), University Medical Center Utrecht (NL), National Institute for Public Health and the Environment (NL), Charité - Universitätsmedizin Berlin (DE)
Zero hunger
Openalex Percentile: Top 2%
Mycobacterium research and diagnosis
9.48
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