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Related Experiment Video

Updated: Jul 10, 2026

Genotyping of Staphylococcus aureus by Ribosomal Spacer PCR (RS-PCR)
08:51

Genotyping of Staphylococcus aureus by Ribosomal Spacer PCR (RS-PCR)

Published on: November 4, 2016

Based Upon Repeat Pattern (BURP): an algorithm to characterize the long-term evolution of Staphylococcus aureus

Alexander Mellmann1, Thomas Weniger, Christoph Berssenbrügge

  • 1Institute for Hygiene, University Hospital Münster, Münster, Germany. mellmann@uni-muenster.de

BMC Microbiology
|October 31, 2007
PubMed
Summary

The Based Upon Repeat Pattern (BURP) algorithm objectively clusters Staphylococcus aureus spa types, reflecting clonal relatedness. This tool aligns well with established methods like MLST and microarray data for epidemiological studies.

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Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Published on: December 7, 2021

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Last Updated: Jul 10, 2026

Genotyping of Staphylococcus aureus by Ribosomal Spacer PCR (RS-PCR)
08:51

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Published on: November 4, 2016

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

  • Microbiology
  • Genetics
  • Bioinformatics

Background:

  • Staphylococcus aureus typing using protein A (spa) gene sequencing is crucial for outbreak investigations.
  • The spa gene's repeat region may also indicate long-term epidemiology.
  • An automated, objective algorithm was needed to cluster diverse spa types.

Purpose of the Study:

  • To evaluate the Based Upon Repeat Pattern (BURP) algorithm for inferring clonal relatedness from spa repeat regions.
  • To optimize BURP parameters by comparing its clustering with Multilocus Sequence Typing (MLST) and eBURST as a gold standard.
  • To assess BURP's performance on a diverse collection of S. aureus strains.

Main Methods:

  • Utilized 400 representative S. aureus strains with known spa types and MLST data for BURP parameter calibration.
  • Employed eBURST to define clonal complexes (CCs) as the reference phylogeny.
  • Systematically analyzed BURP clustering concordance with eBURST CCs across all parameter combinations, optimizing for maximum agreement and minimal data exclusion.

Main Results:

  • The optimal BURP parameters (exclude spa types <5 repeats, cluster if cost distance <4) achieved 95.3% concordance with eBURST CCs, excluding only 7.8% of spa types.
  • Compared to MLST/eBURST, BURP identified 24 spa-CCs and 40 singletons.
  • BURP showed 87.1% concordance with whole-genome microarray data and 95.7% with manually grouped spa types in a natural population.

Conclusions:

  • BURP is the first automated and objective tool for inferring clonal relatedness from spa repeat regions.
  • The BURP algorithm effectively captures an evolutionary signal comparable to MLST and microarray analyses.
  • BURP provides a reliable method for analyzing the long-term epidemiology of Staphylococcus aureus.