qPCR-HRM Authentication of Single-Component Dominant Functional Foods

Accurate identification of biological components is of fundamental importance for food quality. Currently, DNA-based methods are considered the most accurate and receive significant attention. Among them, High-Resolution Melting analysis of qPCR-amplified fragments (qPCR-HRM) allows for sequencing-free amplicon differentiation at single-base resolution. The initial research showed that statistical clustering of yeast strains, based on profiles of three rDNA sub-regions from qPCR-HRM analysis of pure cultures, closely corresponded to species identification by MALDI-TOF mass spectrometry and Sanger sequencing. Consistent with existing validation methods, the primary limitations of the procedure were the completeness and accessibility of the reference database. Further work proved that qPCR-HRM analysis with the plastidial DNA rbcL fragment identified the botanical variety of honey with a prevalent plant pollen within a complex honey mixture and enabled the detection of the honey product “mis-labelling”. The results demonstrated good correspondence between the more time-consuming melissopalynology analysis and the more rapid qPCR-HRM. The subsequent study evaluated a previously designed primer set targeting heterogeneous regions of yeast rDNA and genes associated with the physiological divergence of S. cerevisiae var. boulardii, the only yeast with confirmed probiotic properties. This qPCR profiling approach successfully distinguished the boulardii variety in pure cultures and verified the probiotic composition of dietary supplements. The identification of S. cerevisiae var. boulardii within the complex microbial mixtures of kefir was successful when intraspecific sequences were utilised. The dominance of S. cerevisiae var. boulardii at levels typical for probiotic-fortified food was crucial for its identification via qPCR–HRM. Effective HRM analysis heavily relies on both the purity and quantity of the DNA template, which must be comparable to the reference. Consequently, while challenges may arise in detecting and identifying biological constituents within complex food matrices, our research demonstrated that the qPCR-HRM method can be successfully applied to the authentication of dominant-component functional foods.