高等学校化学学报 ›› 2019, Vol. 40 ›› Issue (2): 246-253.doi: 10.7503/cjcu20180452

• 分析化学 • 上一篇    下一篇

HPLC-MS结合多元统计分析区分人参产地及筛选皂苷类标志物

赵幻希1, 王秋颖1, 孙秀丽1, 李雪1, 苗瑞1, 吴冬雪1, 刘淑莹1,2(), 修洋1()   

  1. 1. 长春中医药大学吉林省人参科学研究院, 长春 130117
    2. 中国科学院长春应用化学研究所, 长春 130022
  • 收稿日期:2018-06-22 出版日期:2019-02-10 发布日期:2018-12-27
  • 作者简介:

    联系人简介: 修 洋, 男, 博士, 助理研究员, 主要从事中药化学方面的研究. E-mail: ys830805@sina.com;刘淑莹, 女, 博士, 教授, 博士生导师, 主要从事有机质谱方面的研究. E-mail: syliu@ciac.ac.cn

  • 基金资助:
    国家自然科学基金(批准号: 21475012)、 吉林省科技发展计划项目(批准号: 20160520123JH, 20160309002YY)和长春中医药大学百青计划项目(批准号: 2017073)资助

Discrimination of Ginseng Origins and Identification of Ginsenoside Markers Based on HPLC-MS Combined with Multivariate Statistical Analysis

ZHAO Huanxi1, WANG Qiuying1, SUN Xiuli1, LI Xue1, MIAO Rui1, WU Dongxue1, LIU Shuying1,2,*(), XIU Yang1,*()   

  1. 1. Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China
    2. Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China
  • Received:2018-06-22 Online:2019-02-10 Published:2018-12-27
  • Contact: LIU Shuying,XIU Yang E-mail:syliu@ciac.ac.cn;ys830805@sina.com
  • Supported by:
    † Supported by the National Natural Science Foundation of China(No.21475012), the Science and Technology Development Plan Project of Jilin Province, China(Nos.20160520123JH, 20160309002YY) and the Training Plan of Hundreds of Outstanding Teachers of Changchun University of Chinese Medicine(No.2017073)

摘要:

利用高效液相色谱-质谱联用(HPLC-MS)技术结合多元统计分析方法, 区分中国人参主产区5个不同产地的45个人参样本, 筛选出差异性皂苷类标志物. 根据人参总皂苷在反相C18色谱柱中的洗脱顺序, 结合串联质谱分析和标准品比对, 在提取的人参总皂苷中鉴定出15种原人参三醇型、 24种原人参二醇型和2种齐墩果酸型共41种皂苷. 对人参总皂苷的HPLC-MS全扫描数据进行了多元统计分析. 正交偏最小二乘-判别分析(OPLS-DA)结果表明, 所建立的分析模型具有良好的数据描述能力和预测能力. 所有人参样本能够根据产地被区分, 并筛选得到同时区分5个产地的差异性皂苷类组分18种; 能够区分任意2个产地人参样本的差异性组分主要为在人参中含量较高的人参皂苷Rb1, Rg1, Re, Rc, Rd, Ro和m-Rb1等. 分层聚类分析(HCA)结果显示, 黑龙江和吉林两省的样本能够独自聚类, 但是绥化市的样本更接近于吉林省. 初步推断原因为绥化市地理位置较接近吉林省, 两地人参生长环境相似并可能存在种质资源交换.

关键词: 高效液相色谱-质谱联用, 多元统计分析, 人参产地区分, 人参皂苷

Abstract:

High performance liquid chromatography-mass spectrometry combined with multi-variate statistical analysis was employed to discriminate 45 ginseng samples harvested from 5 different main cultivation areas in Northeast China and to identify the differential ginsenoside markers. A total of 41 ginsenosides, which included 15 protopanaxatriol type, 24 protopanaxadiol type and 2 oleanolic type ginsenosides, were identified based on the elution order of total ginsenosides in the reverse-phase C18 column coupled with the tandem MS analysis and comparison with authentic standard. Multivariate statistical analysis was further used to extract the information of HPLC-MS data sets. Orthogonal partial least squares-discriminate analysis revealed that the established analysis model had high goodness of fit and predictability. All the 45 ginseng samples were discriminated according to their origins. And 18 ginsenosides were identified as the differential markers, which contri-buted most to the simultaneous discrimination of the 5 ginseng origins. In addition, the differential ginsenoside markers which could distinguish any two origins were mainly those of high content in wild ginseng, such as Rb1, Rg1, Re, Rc, Rd, Ro, and m-Rb1. In the results of hierarchical clustering analysis, the ginseng samples of Heilongjiang and Jilin Province gathered separately except for the samples from Suihua city, which showed similarity to those of Jilin Province. This discrepancy may be attributed to the geographical location. Suihua city is relatively closer to Jilin Province and hence results in the similar growth environment of ginseng and the facility to exchange germplasm resources.

Key words: High performance liquid chromatography-mass spectrometry(HPLC-MS), Multivariate statistical analysis, Discrimination of ginseng origin, Ginsenoside

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