Year: 2026
Type: article
Abstract: Coexisting strains of the same species within metagenomic data pose a substantial challenge to inferring transmission of pathogenic and commensal microbes. Here we present TRAnsmission Clustering of Strains (TRACS), a highly accurate algorithm for estimating genetic distances between strains at the level of individual single nucleotide polymorphisms, which is robust to intra-species diversity within the host. Analysis of faecal microbiota transplantation datasets and extensive simulations demonstrates that TRACS outperforms existing methods. We use TRACS to infer transmission networks in patients colonized with multiple strains, including severe acute respiratory syndrome coronavirus 2 amplicon sequencing data, deep population sequencing data of Streptococcus pneumoniae and single-cell genome sequencing data from patients infected with Plasmodium falciparum. Applying TRACS to gut metagenomic samples from a mother-infant cohort revealed species-specific transmission rates and identified increased the persistence of Bifidobacterium breve in infants, a finding previously missed owing to the presence of multiple strains. Our study shows that TRACS can be used across microbial kingdoms to uncover strain dynamics.
Source: Nature Microbiology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $12,690
Awards: Population genomic methods for modelling bacterial pathogen evolution, Wellcome Sanger Institute Quinquennial Review 2021-2026, G371461440, Epidemiology, evolution and prevention of streptococcal pandemics, Scalable inference algorithms for Bayesian evolutionary epidemiology, Evolution of Streptococcal pathovars, Wellcome Trust Sanger Institute - generic account for deposition of all core- funded research papers., Scalable genotype to phenotype prediction for pathogen tracking and diagnostics
OpenAlex ID: W7155567441