Integrated Bacterial Identification and Antimicrobial Susceptibility Testing Using PCR and High-Resolution Melt

Area of Science:

• Microbiology
• Molecular Diagnostics
• Bioinformatics

Background:

• Current bacterial infection diagnostics, like culture-based methods, are slow, delaying treatment and contributing to antibiotic resistance.
• Nucleic acid amplification tests (NAATs) like PCR offer speed but often lack broad identification and antimicrobial susceptibility testing (AST) capabilities.

Purpose of the Study:

• To develop and validate an integrated assay for rapid, simultaneous bacterial identification and antimicrobial susceptibility testing (AST).
• To overcome the limitations of existing diagnostic methods for bacterial infections.

Main Methods:

• An integrated assay combining real-time quantitative PCR (qPCR) or digital PCR (dPCR) with high-resolution melt (HRM) analysis.
• Antimicrobial susceptibility was determined by measuring bacterial growth in the presence/absence of antibiotics using qPCR/dPCR.
• Bacterial species identification was achieved through automated analysis of 16S rRNA gene melt-curve profiles using HRM and a machine learning algorithm.

Main Results:

• The assay correctly identified bacterial species and their antimicrobial susceptibility profiles in blinded tests.
• Demonstrated successful application for multiple unknown samples.
• Achieved a total turnaround time of approximately 6.5 hours for diagnosis.

Conclusions:

• The developed integrated PCR-HRM assay provides a rapid and accurate method for diagnosing bacterial infections.
• This approach enables simultaneous bacterial identification and AST, offering a significant advancement over current diagnostic strategies.
• The assay has the potential to improve clinical outcomes and combat the spread of antibiotic resistance.