29 April 2025, 14:30
Metagenomics-enabled transmission inference
AbstractThe use of genomics in the surveillance of infectious disease has been hindered by the reliance on single genome assemblies which only provide a partial view of the microbial population within a sample and usually requires enrichment steps such as isolating individual bacterial colonies or amplicon sequencing Metagenomics offers an attractive alternative enabling the simultaneous... AbstractThe use of genomics in the surveillance of infectious disease has been hindered by the reliance on single genome assemblies, which only provide a partial view of the microbial population within a sample and usually requires enrichment steps such as isolating individual bacterial colonies or amplicon sequencing. Metagenomics offers an attractive alternative, enabling the simultaneous consideration of multiple strains and species in a single analysis. Despite its benefits, the computational tools available for tracking transmission using metagenomic data are challenging to use or lack the necessary resolution to accurately differentiate between recently transmitted and distantly related strains. To address this issue, we developed TRACS, an accurate and easy-to-use algorithm for establishing if two samples are plausibly related by a recent transmission event. We...
Speaker(s): Gerry Tonkin-Hill, Peter MacCallum Cancer Centre
Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Australia
Host: Michael Kuhn
Place: Small Operon
External Faculty Speaker
EMBL Heidelberg, Virtual
Additional information
Abstract
The use of genomics in the surveillance of infectious disease has been hindered by the reliance on single genome assemblies, which only provide a partial view of the microbial population within a sample and usually requires enrichment steps such as isolating individual bacterial colonies or amplicon sequencing.
Metagenomics offers an attractive alternative, enabling the simultaneous consideration of multiple strains and species in a single analysis. Despite its benefits, the computational tools available for tracking transmission using metagenomic data are challenging to use or lack the necessary resolution to accurately differentiate between recently transmitted and distantly related strains.
To address this issue, we developed TRACS, an accurate and easy-to-use algorithm for establishing if two samples are plausibly related by a recent transmission event. We illustrate the utility of TRACS by inferring transmission networks in patients colonised with multiple strains of the same species, utilising diverse datasets such as deep population sequencing data of Streptococcus pneumoniae, and single-cell whole genome sequencing data from patients infected with the malaria parasite Plasmodium falciparum.
Analysis of gut metagenomic samples from a large cohort of 176 mothers and 1,288 infants born in UK hospitals revealed species-specific transmission rates between mothers and their infants. Notably, we identified an increased persistence of Bifidobacterium breve in infants, a finding missed by previous analyses due to the presence of multiple strains.
Our findings highlight the limitations of using representative genomes to track microbial transmission and persistence in public health, and advocate for the use of metagenomics as a more robust and sensitive alternative.
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