High-Resolution Melting PCR as a Fast and Simple Molecular Biology-Based Method for the Identification of

Tomasz Bogiel1,2,3, Robert Górniak2,4, Weronika Ambroziak3

  • 1Microbiology Department Ludwik Rydygier, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 9 Maria Skłodowska-Curie Street, 85-094 Bydgoszcz, Poland.

Microorganisms
|November 27, 2024
PubMed

Insights

A new real-time HRM-PCR method quickly identifies hypervirulent Clostridioides difficile strains in patient stool samples. This technique aids in diagnosing C. difficile infections, particularly those caused by toxin-producing strains.

Area of Science:

  • Medical Microbiology
  • Infectious Diseases
  • Molecular Diagnostics

Background:

  • Clostridioides difficile is a leading cause of hospital-acquired infections globally.
  • Hypervirulent strains producing binary toxin (CDT) increase infection severity.
  • Rapid diagnostics are crucial for managing C. difficile infections.

Purpose of the Study:

  • To develop and evaluate a real-time HRM-PCR assay for detecting hypervirulent C. difficile.
  • To assess the diagnostic accuracy of the assay in identifying CDT-producing strains.
  • To compare the assay's performance against a standard LAMP-based diagnostic test.

Main Methods:

  • Real-time high-resolution melting-PCR (HRM-PCR) targeting cdtA, cdtB, and gluD genes.
  • Direct detection in patient diarrheal stool samples.
  • Comparison with eazyplex® C. difficile complete test (LAMP method).

Main Results:

  • The HRM-PCR method successfully detected target genes in C. difficile strains.
  • Diagnostic parameters (sensitivity, specificity, PPV, NPV) varied by gene, with NPV for cdtB reaching 98.85%.
  • The method demonstrated fast and simple detection of hypervirulent C. difficile genes.

Conclusions:

  • Real-time HRM-PCR offers a rapid and straightforward approach for identifying hypervirulent C. difficile.
  • The assay shows potential for integration into routine microbiological diagnostics.
  • Further optimization may enhance its utility in clinical settings.