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With the widespread adoption of barcoding and next-generation sequencing, metabarcoding is emerging as a potential tool for detecting labelled and unlabelled plant species in herbal products. In this study, newly designed rbcL and ITS2 metabarcode primers were validated for metabarcoding using in-house mock controls of medicinal plant gDNA pools and biomass pools. The applicability of the multi-barcode sequencing approach was evaluated on 17 single drugs and 15 polyherbal formulations procured from the Indian market. The rbcL metabarcode demonstrated detection efficiencies of 86.7% and 71.7% in gDNA plant pools and biomass mock controls, respectively, while the ITS2 metabarcode demonstrated 82.2% and 69.4%. In the gDNA plant pool and biomass pool mock controls, the cumulative detection efficiency increased by 100% and 90%, respectively. A total of 79% cumulative detection efficiency of both metabarcodes was observed in single drugs, while 76.3% was observed in polyherbal formulations. An average fidelity of 83.6% was observed for targeted plant species present within mock controls as well as in herbal formulations. Our results demonstrated the applicability of multilocus strategies in metabarcoding as a potential tool for detecting labelled and unlabelled plant species in herbal formulations.

BackgroundThe herbal products market is expanding and creating a bottleneck for raw materials. Hence, economically motivated adulteration has a high prevalence. DNA barcoding and species-specific PCR assays are now revolutionising the molecular identification of herbal products and are included in a number of pharmacopoeias for the identification of raw materials. High-throughput sequencing with barcoding advances toward metabarcoding, which enables the identification of unintentionally or intentionally unlabelled plant material present in herbal products. Brahmi is one of the most commercially significant and nootropic botanicals, with great controversy over the terms “Brahmi” being used to describe both Bacopa monneri (BM) and Centella asiatica (CA) species.PurposeThis study evaluates DNA-based methods for Brahmi herbal products with the traditional HPLC-based analytical approach in order to assess their effectiveness.MethodsWe employed a species-specific PCR assay, DNA metabarcoding using rbcL minibarcode, and HPLC to detect the presence of the Brahmi (either BM or CA) in eighteen market samples. All the methods have been validated using in-house blended formulations.ResultsComprehensive analysis of all three methods revealed the presence of 22.2%, 55.6%, and 50.0% of Brahmi by PCR assay, DNA metabarcoding, and HPLC, respectively, in Brahmi market formulations, whereas blended formulations only exhibited targeted plant species with all three methods.ConclusionSpecies-specific PCR can be used as a cost-effective and rapid method to detect the presence of the Brahmi, while in high-throughput methods, DNA metabarcoding can be used to detect the presence of widespread adulterated botanicals, and further, bioactive compounds could be detected by HPLC. These results emphasise the need for quality control of the marketed Brahmi herbal products as well as the implementation of all methodologies in accordance with fit for purpose.

IntroductionEmpirical research has refined traditional herbal medicinal systems. The traditional market is expanding globally, but inadequate regulatory guidelines, taxonomic knowledge, and resources are causing herbal product adulteration. With the widespread adoption of barcoding and next-generation sequencing, metabarcoding is emerging as a potential tool for detecting labeled and unlabeled plant species in herbal products.MethodsThis study validated newly designed rbcL and ITS2 metabarcode primers for metabarcoding using in-house mock controls of medicinal plant gDNA pools and biomass pools. The applicability of the multi-barcode sequencing approach was evaluated on 17 single drugs and 15 polyherbal formulations procured from the Indian market.ResultsThe rbcL metabarcode demonstrated 86.7% and 71.7% detection efficiencies in gDNA plant pools and biomass mock controls, respectively, while the ITS2 metabarcode demonstrated 82.2% and 69.4%. In the gDNA plant pool and biomass pool mock controls, the cumulative detection efficiency increased by 100% and 90%, respectively. A 79% cumulative detection efficiency of both metabarcodes was observed in single drugs, while 76.3% was observed in polyherbal formulations. An average fidelity of 83.6% was observed for targeted plant species present within mock controls and in herbal formulations.DiscussionIn the present study, we achieved increasing cumulative detection efficiency by combining the high universality of the rbcL locus with the high-resolution power of the ITS2 locus in medicinal plants, which shows applicability of multilocus strategies in metabarcoding as a potential tool for the Pharmacovigilance of labeled and unlabeled plant species in herbal formulations.

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