Integrated population clustering and genomic epidemiology with PopPIPE
File(s)
Published version
Author(s)
McHugh, Martin P
Horsfield, Samuel T
von Wachsmann, Johanna
Toussaint, Jacqueline
Pettigrew, Kerry A
Type
Journal Article
Abstract
Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here, we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high-quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin-resistant Enterococcus faecium samples, PopPIPE finds transmission clusters that are more epidemiologically plausible than core genome or multilocus sequence typing (MLST) approaches. Our pipeline is rapid and reproducible, creates interactive visualizations and can easily be reconfigured and re-run on new datasets. Therefore, PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations.
Date Issued
2025-04-28
Date Acceptance
2025-03-22
Citation
Microbial Genomics, 2025, 11 (4)
ISSN
2057-5858
Publisher
Microbiology Society
Journal / Book Title
Microbial Genomics
Volume
11
Issue
4
Copyright Statement
© 2025 The Authors This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40294103
Subjects
clustering
genomic epidemiology
pipelines
transmission
Humans
Streptococcus pneumoniae
Genome, Bacterial
Genomics
Multilocus Sequence Typing
Cluster Analysis
Molecular Epidemiology
Enterococcus faecium
Computational Biology
Phylogeny
Cross Infection
Publication Status
Published
Coverage Spatial
England
Article Number
001404
Date Publish Online
2025-04-28