mSystems· 2026Q1
Phylogenetic inconsistency of pairwise SNP clustering for inferring tuberculosis transmission in a high-burden, endemic setting: a case study from Thailand
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- Q1SCImago
- 2026year
Short summary
Pairwise SNP-distance clustering, a common method for inferring tuberculosis transmission, frequently generates non-monophyletic clusters in high-burden, endemic settings like Thailand, unlike in low-burden settings like the UK.
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Key points
- Pairwise SNP-distance clustering often produces non-monophyletic clusters in tuberculosis transmission inference, violating the principle of a single origin for a true cluster.
- The method showed high consistency with tree-based clustering in a low-burden UK dataset (≥12 SNPs) but frequently failed in a high-burden Thai dataset (≥22 SNPs).
- Persistent transmission, sparse sampling, large cluster sizes, high intra-cluster genetic distances, and broad sample collection time spans exacerbate the issue of non-monophyletic clusters.
- Mixed infections can create spurious SNP linkages, highlighting the need for strict sequence quality control.
AI-generated from the title and abstract; the full text is not read.
Abstract
ABSTRACT Whole-genome sequence analysis is now widely used to delineate tuberculosis transmission clusters. A standard practice is to cluster bacterial isolates based on a fixed maximum genome-wide pairwise single nucleotide polymorphism (pwSNP) distance threshold. In this study, we evaluated the phylogenetic consistency of pwSNP-distance clustering with thresholds ranging between 1 and 25 single nucleotide polymorphisms (SNPs) using two contrasting data sets: (i) a data set from the UK ( N = 390) published by T. M. Walker, C. L. C. Ip, R. H. Harrell, J. T. Evans, et al. (Lancet Infect Dis 13:137–146, 2013, https://doi.org/10.1016/S1473-3099(12)70277-3 ), which was foundational to the establishment of this method, and (ii) a data set from Thailand ( N = 3,341), characterized by persistent transmission and sparse, non-systematic sampling. For the UK data set, the standard pwSNP-distance clustering using thresholds of ≥12 SNPs yielded entirely monophyletic clusters and showed high concordance with a comparative monophyly constrained, tree-based method. In contrast, for the Thai data set, pwSNP-distance clustering often generated non-monophyletic clusters, even by the 25-SNP threshold. The pwSNP-distance and comparative tree-based clustering methods only showed large consistency at thresholds of ≥22 SNPs. This suggests that SNP clusters defined by low distance thresholds (i.e., <12 SNPs for the UK data set, and <22 SNPs for the Thai data set) may lack robustness, and the problem is particularly severe for data sets characterized by persistent transmission, likely due to poorer cluster separation. Moreover, our findings indicate that large cluster sizes, high maximum intra-cluster genetic distances, and broad sample collection time spans may serve as useful indicators of potentially non-monophyletic clusters. We also demonstrate that mixed infections can produce spurious, phylogenetically long-range SNP linkages, underscoring the necessity of strict sequence quality control. IMPORTANCE Fixed-threshold pairwise single nucleotide polymorphism (pwSNP)-distance clustering is commonly used to delineate tuberculosis transmission clusters. From an epidemiological perspective, a genuine transmission cluster must be monophyletic, originating from a single source. However, pwSNP-distance clustering is inherently simplistic and can therefore violate this principle, making the assessment of its phylogenetic consistency critical. Our results demonstrate that while this method effectively delineated complete transmission clusters for the data set from the UK, a low-burden and non-persistent transmission setting, it frequently generated non-monophyletic clusters when applied to the Thai data set, characterized by persistent transmission alongside sparse and non-systematic sampling. Furthermore, we found that clusters derived using low distance thresholds could notably vary between the pwSNP-distance and comparative tree-based clustering methods, suggesting limited reliability and robustness. To accurately delineate tuberculosis transmission clusters, especially for complex data from high-burden, endemic settings, we recommend transitioning from pwSNP-distance clustering toward more robust, phylogenetic clustering that respects evolutionary descent.
The authors' abstract, as published at the source. mSystems, 2026 · DOI ↗
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Field: Infectious Diseases
Infectious DiseasesMedicine