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Pakorn Aiewsakun

Publications and source records attributed to Pakorn Aiewsakun.

2 recordsLinked to original sources

Phylogenetic inconsistency of pairwise SNP clustering for inferring tuberculosis transmission in a high-burden, endemic setting: a case study from Thailand.

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 &#x2265;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 &#x2265;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.IMPORTANCEFixed-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.

Mycobacterium tuberculosis

Discovery of diverse anellovirus sequences in Thai human sequencing data.

UNLABELLED: Anelloviruses are part of the normal human viral flora. Although their diversity in humans has been investigated in many countries, and despite their initial detection in Thailand in 1999, knowledge of Thai anelloviruses remains very limited. This study analyzed 1,175 whole-genome sequencing data sets from Thai individuals to mine for potential anellovirus sequences. Our analyses detected anellovirus sequences in 149 data sets (12.68%), uncovering 434 partial anellovirus sequences and 77 complete genome sequences, characterized by the presence of terminal redundancy, complete orf1, and the conserved untranslated region upstream of the orf1 gene. Sequence analyses indicated that these viruses belong to seven genera, including Alphatorquevirus, Betatorquevirus, Gammatorquevirus, Hetorquevirus, Lamedtorquevirus, Samektorquevirus, and Yodtorquevirus. Notably, Hetorquevirus, Lamedtorquevirus, Samektorquevirus, and Yodtorquevirus had not previously been reported in Thailand. Phylogenetic analysis of ORF1 protein sequences showed that Thai anelloviruses form multiple phylogenetic clusters with non-Thai anelloviruses, indicating frequent cross-country transmission and multiple origins of the virus in Thailand. Furthermore, sequence similarity network analysis identified 33 potentially novel anellovirus species in our data set. Our findings greatly expand the knowledge of anellovirus diversity in Thailand and demonstrate the potential of human whole-genome sequencing data as a valuable resource for viral discovery. Lastly, we highlight and discuss some challenges with the use of the current pairwise sequence similarity-based classification scheme, in particular, how gaps can influence similarity calculation and potentially lead to inconsistencies with a phylogenetic-based classification scheme. IMPORTANCE: Anelloviruses are widespread in humans, yet their diversity remains poorly characterized in many regions, including Thailand. Here, we demonstrate that human sequencing data sets, originally generated without the intention for virome research, can be effectively mined for anellovirus sequences, including complete genomes. Our findings reveal a substantial number of previously unreported anelloviruses in Thailand, significantly expanding the known diversity of the virus. We also highlight potential limitations of the current anellovirus species classification scheme, which is based on pairwise orf1 sequence similarity analysis with a hard threshold cutoff at 69%. Our results reveal that the current scheme can sometimes yield taxonomic groupings that are inconsistent with phylogenetic relationships, particularly when significant alignment gaps are present. Overall, our results show that existing human sequencing data can be effectively repurposed for virus discovery research and suggest the need for more robust and phylogenetically informed classification frameworks as viral sequence databases continue to expand.

Humans