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Microbial Genomics logo Microbial Genomics

Volume 11, Issue 4

Integrated population clustering and genomic epidemiology with PopPIPE Open Access

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 ulation analysis line (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 . When applied to nosocomial vancomycin-resistant 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.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): clustering , genomic epidemiology , pipelines and transmission
Funding
This study was supported by the:
  • Biotechnology and Biological Sciences Research Council (Award BB/S019669/1)
    • Principal Award Recipient: MartinP. McHugh
  • Chief Scientist Office (Award SIRN/10)
    • Principal Award Recipient: MartinP. McHugh
  • Medical Research Council (Award MR/X020258/1)
    • Principal Award Recipient: NicholasJ. Croucher
  • Medical Research Council (Award MR/T016434/1)
    • Principal Award Recipient: NicholasJ. Croucher
  • Medical Research Council (Award MR/R015600/1)
    • Principal Award Recipient: NicholasJ. Croucher
  • Biotechnology and Biological Sciences Research Council (Award BB/Y513805/1)
    • Principal Award Recipient: JohnA Lees
  • European Molecular Biology Laboratory
    • Principal Award Recipient: JohnA Lees
© 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.
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2026-04-21

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Integrated population clustering and genomic epidemiology with PopPIPE
M Gen 11, 001404 (2025); https://doi.org/10.1099/mgen.0.001404
/content/journal/mgen/10.1099/mgen.0.001404
/content/journal/mgen/10.1099/mgen.0.001404
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