Molecular quantification of herbs (Herb-Q): a pyrosequencing-based approach and its application in Pinellia ternata

Changes in the dosage of herbs, owing to the risk of species adulteration and inaccuracies in dosing, can significantly impact their clinical safety and efficacy. However, accurate species quantification is challenging as current approaches typically yield inconsistent results. Herein, we propose a novel pyrosequencing-based approach called herb molecular quantification (Herb-Q) for herbal product quantification and evaluate its effectiveness using Pinellia ternata and its five adulterants. We first evaluated commonly used DNA barcodes using effective sequences from a public database and obtained two candidate regions (matK and ITS2) for screening specific single nucleotide polymorphism loci, allowing for one identification locus per species. These loci were identified and verified by amplifying and sequencing genomic materials extracted from the collected samples. Validation studies demonstrated that the proposed approach yielded optimal linearity, accuracy, repeatability, and limit of detection. A set of quantitative standard curves with high R² values (> 0.99) was established to enable precise quantification of the target species, which were then combined with external standards to provide visualized, accurate quantification results. The average bias value of the quantitation results of the tuber of P. ternata was 2.38%, demonstrating that Herb-Q could identify the species and accurately quantify the constituents of herbal products. In addition, the entire quantification process required less than 4 h. This study offers a novel, rapid method to accurately quantify species in herbal products and advances DNA barcoding from species identification to quantitative detection.