Evidence map›Paper›PMID 27454470›Full record

ArticleBMC complementary and alternative medicine2016

Creation of reference DNA barcode library and authentication of medicinal plant raw drugs used in Ayurvedic medicine.

Sophie Lorraine Vassou, Stalin Nithaniyal, Balaji Raju, Madasamy Parani

Abstract read
In one paragraph

Article in BMC complementary and alternative medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

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14citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Review
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  5. Deoxyribonucleic Acid Barcoding for the Identification of Botanicals.Progress in the chemistry of organic natural products · 2023
    Article
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sophie Lorraine VassouDepartment of Genetic Engineering, Center for DNA Barcoding, SRM University, Kattankulathur, 603203, India.
Stalin NithaniyalDepartment of Genetic Engineering, Center for DNA Barcoding, SRM University, Kattankulathur, 603203, India.
Balaji RajuDepartment of Genetic Engineering, Center for DNA Barcoding, SRM University, Kattankulathur, 603203, India.
Madasamy ParaniDepartment of Genetic Engineering, Center for DNA Barcoding, SRM University, Kattankulathur, 603203, India. parani.m@ktr.srmuniv.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAyurveda is a system of traditional medicine that originated in ancient India, and it is still in practice. Medicinal plants are the backbone of Ayurveda, which heavily relies on the plant-derived therapeutics. While Ayurveda is becoming more popular in several countries throughout the World, lack of authenticated medicinal plant raw drugs is a growing concern. Our aim was to DNA barcode the medicinal plants that are listed in the Ayurvedic Pharmacopoeia of India (API) to create a reference DNA barcode library, and to use the same to authenticate the raw drugs that are sold in markets.

methodsWe have DNA barcoded 347 medicinal plants using rbcL marker, and curated rbcL DNA barcodes for 27 medicinal plants from public databases. These sequences were used to create Ayurvedic Pharmacopoeia of India - Reference DNA Barcode Library (API-RDBL). This library was used to authenticate 100 medicinal plant raw drugs, which were in the form of powders (82) and seeds (18).

resultsAyurvedic Pharmacopoeia of India - Reference DNA Barcode Library (API-RDBL) was created with high quality and authentic rbcL barcodes for 374 out of the 395 medicinal plants that are included in the API. The rbcL DNA barcode differentiated 319 species (85 %) with the pairwise divergence ranging between 0.2 and 29.9 %. PCR amplification and DNA sequencing success rate of rbcL marker was 100 % even for the poorly preserved medicinal plant raw drugs that were collected from local markets. DNA barcoding revealed that only 79 % raw drugs were authentic, and the remaining 21 % samples were adulterated. Further, adulteration was found to be much higher with powders (ca. 25 %) when compared to seeds (ca. 5 %).

conclusionsThe present study demonstrated the utility of DNA barcoding in authenticating medicinal plant raw drugs, and found that approximately one fifth of the market samples were adulterated. Powdered raw drugs, which are very difficult to be identified by taxonomists as well as common people, seem to be the easy target for adulteration. Developing a quality control protocol for medicinal plant raw drugs by incorporating DNA barcoding as a component is essential to ensure safety to the consumers.

Indexed as

Medicine, AyurvedicDNA Barcoding, TaxonomicDNA, PlantPhylogenyPlant ExtractsPlants, MedicinalDNA, PlantPlant Extracts

Identifiers

PMID27454470
PMCPMC4959393

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.