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Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients

Identifying plant, fungal, and animal ingredients in a specific mixture remains challenging during the limitation of PCR amplification and low specificity of traditional methods. Genomic DNA was extracted from mock and pharmaceutical samples. Four type of DNA barcodes were generated from shotgun seq...

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Autores principales: Zhang, Zhaolei, Mu, Weishan, Kong, Weijun, Liu, Jiali, Zhao, Jingyi, Zhao, Qing, Shi, Mengmeng, Zhao, Hongye, Liu, Jinxin, Shi, Linchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317219/
https://www.ncbi.nlm.nih.gov/pubmed/37399206
http://dx.doi.org/10.1371/journal.pone.0286069
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author Zhang, Zhaolei
Mu, Weishan
Kong, Weijun
Liu, Jiali
Zhao, Jingyi
Zhao, Qing
Shi, Mengmeng
Zhao, Hongye
Liu, Jinxin
Shi, Linchun
author_facet Zhang, Zhaolei
Mu, Weishan
Kong, Weijun
Liu, Jiali
Zhao, Jingyi
Zhao, Qing
Shi, Mengmeng
Zhao, Hongye
Liu, Jinxin
Shi, Linchun
author_sort Zhang, Zhaolei
collection PubMed
description Identifying plant, fungal, and animal ingredients in a specific mixture remains challenging during the limitation of PCR amplification and low specificity of traditional methods. Genomic DNA was extracted from mock and pharmaceutical samples. Four type of DNA barcodes were generated from shotgun sequencing dataset with the help of a local bioinformatic pipeline. Taxa of each barcode was assigned by blast to TCM-BOL, BOLD, and GenBank. Traditional methods including microscopy, thin layer chromatography (TLC), and high-performance liquid chromatography (HPLC) were carried out according to Chinese pharmacopoeia. On average, 6.8 Gb shotgun reads were sequenced from genomic DNA of each sample. Then, 97, 11, 10, 14, and one operational taxonomic unit (OTU) were generated for ITS2, psbA-trnH, rbcL, matK, and COI, respectively. All the labeled ingredients including eight plant, one fungal, and one animal species were successfully detected in both the mock and pharmaceutical samples, in which Chebulae Fructus, Poria, and Fritilariae Thunbergia Bulbus were identified via mapping reads to organelle genomes. In addition, four unlabeled plant species were detected from pharmaceutical samples, while 30 genera of fungi, such as Schwanniomyces, Diaporthe, Fusarium were detected from mock and pharmaceutical samples. Furthermore, the microscopic, TLC, and HPLC analysis were all in accordance with the standards stipulated by Chinese Pharmacopoeia. This study indicated that shotgun metabarcoding could simultaneously identified plant, fungal, and animal ingredients in herbal products, which has the ability to serve as a valuable complement to traditional methods.
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spelling pubmed-103172192023-07-04 Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients Zhang, Zhaolei Mu, Weishan Kong, Weijun Liu, Jiali Zhao, Jingyi Zhao, Qing Shi, Mengmeng Zhao, Hongye Liu, Jinxin Shi, Linchun PLoS One Research Article Identifying plant, fungal, and animal ingredients in a specific mixture remains challenging during the limitation of PCR amplification and low specificity of traditional methods. Genomic DNA was extracted from mock and pharmaceutical samples. Four type of DNA barcodes were generated from shotgun sequencing dataset with the help of a local bioinformatic pipeline. Taxa of each barcode was assigned by blast to TCM-BOL, BOLD, and GenBank. Traditional methods including microscopy, thin layer chromatography (TLC), and high-performance liquid chromatography (HPLC) were carried out according to Chinese pharmacopoeia. On average, 6.8 Gb shotgun reads were sequenced from genomic DNA of each sample. Then, 97, 11, 10, 14, and one operational taxonomic unit (OTU) were generated for ITS2, psbA-trnH, rbcL, matK, and COI, respectively. All the labeled ingredients including eight plant, one fungal, and one animal species were successfully detected in both the mock and pharmaceutical samples, in which Chebulae Fructus, Poria, and Fritilariae Thunbergia Bulbus were identified via mapping reads to organelle genomes. In addition, four unlabeled plant species were detected from pharmaceutical samples, while 30 genera of fungi, such as Schwanniomyces, Diaporthe, Fusarium were detected from mock and pharmaceutical samples. Furthermore, the microscopic, TLC, and HPLC analysis were all in accordance with the standards stipulated by Chinese Pharmacopoeia. This study indicated that shotgun metabarcoding could simultaneously identified plant, fungal, and animal ingredients in herbal products, which has the ability to serve as a valuable complement to traditional methods. Public Library of Science 2023-07-03 /pmc/articles/PMC10317219/ /pubmed/37399206 http://dx.doi.org/10.1371/journal.pone.0286069 Text en © 2023 Zhang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Zhang, Zhaolei
Mu, Weishan
Kong, Weijun
Liu, Jiali
Zhao, Jingyi
Zhao, Qing
Shi, Mengmeng
Zhao, Hongye
Liu, Jinxin
Shi, Linchun
Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title_full Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title_fullStr Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title_full_unstemmed Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title_short Validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
title_sort validation of the shotgun metabarcoding approach for comprehensively identifying herbal products containing plant, fungal, and animal ingredients
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10317219/
https://www.ncbi.nlm.nih.gov/pubmed/37399206
http://dx.doi.org/10.1371/journal.pone.0286069
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