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Advancing digital PCR-HRM assays for better pathogen identification

The accurate identification of pathogenic bacteria is paramount in advancing microbiology research for global health. While traditional methods are tedious, time consuming and can lead to inaccurate results, a groundbreaking approach combines digital PCR and high resolution melt (HRM®) techniques to achieve single-cell resolution using species-specific digital melt curves. By meticulously selecting PCR primers targeting hypervariable gene regions and using bulk-based PCR-HRM® with Biotium’s EvaGreen® Dye to examine species-specific melt curve variability, this method has unlocked a new foundation in better identifying pathogenic bacteria. 

In an October 2023 publication in Analytical Chemistry, Pei-Wei Lee et al. developed a procedure that efficiently integrates digital PCR and HRM® techniques to more effectively achieve single-cell resolution than traditional techniques. Bulk-based PCR-HRM® can lead to composite melt curves, while digital PCR-HRM® unmasks specific and nonspecific amplicons, causing high intraspecies variability. Such intraspecies variability arises from DNA sequence variations within bacterial genomes and nonspecific amplification caused by degenerate primers. The study confirmed such through three sets of PCR primers and five bacterial species. To combat these issues, computational in silico HRM® is introduced before digital PCR-HRM® to ensure appropriate variability in digital melt curves (high interspecies variability and low intraspecies variability). The PCR-HRM® assays themselves combine Biotium’s EvaGreen® Dye with purified genomic DNA of each bacterial species, PCR primers, and PCR Master mix. Identification accuracy was improved, paving the way for greater exploration of PCR primers to target other gene regions and enhanced future digital PCR-HRM® assays for a wide range of infectious diseases beyond bacteria.


Full Citation

Lee, P.W., Chen, L., Hseih, K. et al (2023) Harnessing Variabilities in Digital Melt Curves for Accurate Identification of Bacteria (2023). Analytical Chemistry 2023 95 (42), 15522-15530. DOI: 10.1021/acs.analchem.3c01654

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