Literature DB >> 29911830

[The molecular identification of Bupleurum medicinal species and the quality investigation of Bupleuri Radix].

Bo-chuan Yuan, Wen-dong Li, Yong-sheng Ma, Shan Zhou, Lin-feng Zhu, Rui-chao Lin, Ying Liu.   

Abstract

Bupleuri Radix is one of the most frequently used herbal medicines in China with a 2 000-year medicinal history. However, the use of Bupleuri Radix is very confused. Twenty-five species and eight varieties of Bupleurum have been used as Bupleuri Radix in different regions of China. It is very difficult to identify these Bupleurum species using traditional morphological method. In order to establish a fast and effective method to identify these Bupleurum species, we collected 168 Bupleurum medicinal plants from 14 populations of 9 provinces, and amplified their ITS sequences. 168 ITS sequences with a full length of 600-606 bp were obtained. DNAMAN analyzing results showed that 86 variable sites were present in these sequences and 19 haplotypes (TH1-TH19) were determined. After calculating K2P distance and analyzing an NJ tree, we established a molecular identification method based on ITS sequence. Using this method, 52 samples of Bupleuri Radix were identified successfully. Furthermore, we tested saikosaponin a, c, d content in these Bupleuri Radix by HPLC and analyzed the results by ANOVA and LSD T test to evaluate the quality of Bupleuri Radix. This method is significant for effective identification of Bupleurum medicinal plants, and quality control of Bupleuri Radix in the market.

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Year:  2017        PMID: 29911830

Source DB:  PubMed          Journal:  Yao Xue Xue Bao        ISSN: 0513-4870


  2 in total

1.  Identification of Bupleurum (Apiaceae) seeds by allele-specific PCR based on ITS sequences.

Authors:  Wentao Qi; Julaiti Tuerxun; Jianchao Li; Chen Wang; Rong Luo; Changli Liu
Journal:  3 Biotech       Date:  2020-05-08       Impact factor: 2.406

2.  Identification of the original plants of cultivated Bupleuri Radix based on DNA barcoding and chloroplast genome analysis.

Authors:  Gaixia Zhang; Hui Wang; Linchun Shi; Yang Liu; Ruyu Yao; Chun Sui; Chengmin Yang; Hongliang Ji; Qiuling Wang; Jianhe Wei
Journal:  PeerJ       Date:  2022-04-12       Impact factor: 3.061

  2 in total

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