Abstract:
:Product mislabeling and/or species fraud in Traditional Chinese Medicine (TCM) not only decrease TCM quality, but also pose a potential health issue to the end user. Up to now, methods to control TCM quality have been developed to detect specific metabolites or identify the original species. However, species quantification in complex herbal formulas is rarely concerned. Here, we reported a simple Vector Control Quantitative Analysis (VCQA) method for flexible and accurate multiplex species quantification in traditional Chinese herbal formulas. We developed PCR-based strategy to quickly generate the integrated DNA fragments from multiple targeted species, which can be assembled into the quantitative vector in one round of cloning by Golden Gate ligation and Gateway recombination technique. With this method, we recruited the nuclear ribosomal DNA Internal Transcribed Spacer (ITS) region for the quantification of Ligusticum sinense "Chuanxiong," Angelica dahurica (Hoffm.) Benth. & Hook.f. ex Franch. & Sav., Notopterygium incisum K. C. Ting ex H. T. Chang, Asarum sieboldii Miq., Saposhnikovia divaricata (Turcz.) Schischk., Nepeta cataria L., Mentha canadensis L., and Glycyrrhiza uralensis Fisch. ex DC. in ChuanXiong ChaTiao Wan, a classic Chinese herbal formula with very long historical background. We found that, firstly, VCQA method could eliminate the factors affecting such as the variations in DNA extracts when in combination with the use of universal and species-specific primers. Secondly, this method detected the limit of quantification of A. sieboldii Miq. in formula products down to 1%. Thirdly, the stability of quality of ChuanXiong ChaTiao Wan formula varies significantly among different manufacturers. In conclusion, VCQA method has the potential power and can be used as an alternative method for species quantification of complex TCM formulas.
journal_name
Front Pharmacoljournal_title
Frontiers in pharmacologyauthors
Zhao B,Xiong C,Li J,Zhang D,Shi Y,Sun W,Duan Xdoi
10.3389/fphar.2020.488193subject
Has Abstractpub_date
2020-11-26 00:00:00pages
488193issn
1663-9812pii
488193journal_volume
11pub_type
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