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Development and Application of a Core Genome Multilocus Sequence Typing Scheme for the Health Care-Associated

Richard A Stanton1, Gillian McAllister2, Jonathan B Daniels2

  • 1Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, USA njr5@cdc.gov.

Journal of Clinical Microbiology
|June 5, 2020
PubMed

Insights

A new core genome multilocus sequence typing (cgMLST) scheme offers rapid, stable analysis for Pseudomonas aeruginosa, improving the tracking of health care-associated infections (HAIs) and outbreak investigations.

Area of Science:

  • Microbiology
  • Genomics
  • Infectious Diseases

Background:

  • Pseudomonas aeruginosa is a major cause of health care-associated infections (HAIs).
  • Its metabolic versatility and biofilm formation enable environmental persistence and prolonged outbreaks.
  • Accurate and rapid typing methods are crucial for controlling P. aeruginosa spread.

Purpose of the Study:

  • To develop and validate a core genome multilocus sequence typing (cgMLST) scheme for P. aeruginosa.
  • To establish a stable platform for whole-genome sequencing (WGS) data analysis.
  • To enhance the speed and resolution of bacterial isolate comparison for surveillance and outbreak investigations.

Main Methods:

  • Curated a set of 4,440 core genes from 58 complete P. aeruginosa genomes.
  • Expanded gene alleles using 1,991 additional contig-level genome sequences.
  • Applied the cgMLST scheme to analyze genomes from four historical HAI outbreaks.

Main Results:

  • The cgMLST scheme demonstrated high resolution for analyzing individual outbreaks.
  • Phylogenetic comparisons using cgMLST were consistent with traditional methods (MLST, PFGE, SNV analysis).
  • The scheme provides stability for comparing diverse P. aeruginosa isolates in surveillance.

Conclusions:

  • The developed cgMLST scheme is a valuable tool for rapid P. aeruginosa genome analysis.
  • It offers a stable and high-resolution platform for outbreak investigations and epidemiological surveillance.
  • cgMLST facilitates timely identification and control of P. aeruginosa-associated HAIs.
Keywords:
HAIPseudomonas aeruginosaantibiotic resistancecgMLST

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