DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand

Abstract Traditional medicines are widely traded across the globe and have received considerable attention in the recent past, with expectations of heightened demand in the future. However, there are increasing global concerns over admixture, which can affect the quality, safety, and efficacy of her...

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Autores principales:	Santhosh Kumar J. Urumarudappa, Chayapol Tungphatthong, Pinidphon Prombutara, Suchada Sukrong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/451a8881a4c144b3bdc66b36a995af5e
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spelling	oai:doaj.org-article:451a8881a4c144b3bdc66b36a995af5e2021-12-02T15:09:41ZDNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand10.1038/s41598-020-75305-02045-2322https://doaj.org/article/451a8881a4c144b3bdc66b36a995af5e2020-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-75305-0https://doaj.org/toc/2045-2322Abstract Traditional medicines are widely traded across the globe and have received considerable attention in the recent past, with expectations of heightened demand in the future. However, there are increasing global concerns over admixture, which can affect the quality, safety, and efficacy of herbal medicinal products. In this study, we aimed to use DNA metabarcoding to identify 39 Thai herbal products on the Thai National List of Essential Medicines (NLEM) and assess species composition and admixture. Among the products, 24 samples were in-house-prepared formulations, and 15 samples were registered formulations. In our study, DNA metabarcoding analysis using ITS2 and rbcL barcode regions were employed to identify herbal ingredients mentioned in the products. The nuclear region, ITS2, was able to identify herbal ingredients in the products at the genus- and family-levels in 55% and 63% of cases, respectively. The chloroplast gene, rbcL, enabled genus- and family-level identifications in 58% and 73% of cases, respectively. In addition, plant species were detected in larger numbers (Family identified, absolute %) in registered herbal products than in in-house-prepared formulations. The level of fidelity increases concerns about the reliability of the products. This study highlights that DNA metabarcoding is a useful analytical tool when combined with advanced chemical techniques for the identification of plant species in highly processed, multi-ingredient herbal products.Santhosh Kumar J. UrumarudappaChayapol TungphatthongPinidphon PrombutaraSuchada SukrongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Santhosh Kumar J. Urumarudappa Chayapol Tungphatthong Pinidphon Prombutara Suchada Sukrong DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
description	Abstract Traditional medicines are widely traded across the globe and have received considerable attention in the recent past, with expectations of heightened demand in the future. However, there are increasing global concerns over admixture, which can affect the quality, safety, and efficacy of herbal medicinal products. In this study, we aimed to use DNA metabarcoding to identify 39 Thai herbal products on the Thai National List of Essential Medicines (NLEM) and assess species composition and admixture. Among the products, 24 samples were in-house-prepared formulations, and 15 samples were registered formulations. In our study, DNA metabarcoding analysis using ITS2 and rbcL barcode regions were employed to identify herbal ingredients mentioned in the products. The nuclear region, ITS2, was able to identify herbal ingredients in the products at the genus- and family-levels in 55% and 63% of cases, respectively. The chloroplast gene, rbcL, enabled genus- and family-level identifications in 58% and 73% of cases, respectively. In addition, plant species were detected in larger numbers (Family identified, absolute %) in registered herbal products than in in-house-prepared formulations. The level of fidelity increases concerns about the reliability of the products. This study highlights that DNA metabarcoding is a useful analytical tool when combined with advanced chemical techniques for the identification of plant species in highly processed, multi-ingredient herbal products.
format	article
author	Santhosh Kumar J. Urumarudappa Chayapol Tungphatthong Pinidphon Prombutara Suchada Sukrong
author_facet	Santhosh Kumar J. Urumarudappa Chayapol Tungphatthong Pinidphon Prombutara Suchada Sukrong
author_sort	Santhosh Kumar J. Urumarudappa
title	DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
title_short	DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
title_full	DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
title_fullStr	DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
title_full_unstemmed	DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand
title_sort	dna metabarcoding to unravel plant species composition in selected herbal medicines on the national list of essential medicines (nlem) of thailand
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/451a8881a4c144b3bdc66b36a995af5e
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DNA metabarcoding to unravel plant species composition in selected herbal medicines on the National List of Essential Medicines (NLEM) of Thailand

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