Discovery and identification of antithrombotic chemical markers in Gardenia Fructus by herbal metabolomics and zebrafish model

抗血栓 代谢组学 传统医学 弗洛斯 偏最小二乘回归 化学 色谱法 药理学 医学 生物化学 数学 统计 心脏病学 芦丁 抗氧化剂
作者
Yongping Shi,Yougang Zhang,Haonan Li,Haotian Kong,Shanshan Zhang,Xuanming Zhang,Xiaobin Li,Ke‐chun Liu,Liwen Han,Qingping Tian
出处
期刊:Journal of Ethnopharmacology [Elsevier BV]
卷期号:253: 112679-112679 被引量:19
标识
DOI:10.1016/j.jep.2020.112679
摘要

Gardenia Fructus (GF), a traditional Chinese medicine for clearing heat and purging fire, has been reported to use to treat thrombotic related diseases, but the antithrombotic components are not clear. To develop efficient research methods for discovering some representative antithrombotic compounds of GF. AB line zebrafish induced by arachidonic acid (AA) was used as a fast and trace-sample-required valuation model for antithrombptic effect of GF samples. Among nine samples of GF from different production areas, two samples with the largest difference in bioactivity were selected for downstream analysis. High-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-Q-TOF/MS) was applied to detect compounds in the GF samples. And herbal metabolomics and grey correlation analysis (GCA) were used to identify crucial compounds with potential antithrombotic activity. Then the bioactivity of those important compounds was verified on the zebrafish model. Network pharmacology was used to explore the protein targets and signaling pathways of these compounds. Among the GF samples, S1 (Huoshan City, Anhui Province), and S6 (Jichun City, Hubei Province), significantly differed in thrombus inhibiting bioactivity. HPLC-Q-TOF/MS identified a total of 614 compounds in each GF sample. 19 compounds were selected as important potential variables from metabolomics data by orthogonal partial least squares discriminant analysis (OPLS-DA). And 10 compounds among them were further found to be positively correlated with the antithrombotic bioactivity of GF by GCA. Finally, 3 compounds in them, geniposide, citric acid, and quinic acid, were confirmed as representative antithrombotic chemical markers of GF. Using network pharmacology analysis, some key protein targets, such as proto-oncogene tyrosine-protein kinase Src (SRC) and cyclin-dependent kinase 2 (CDK2), and some signaling pathways were found to supply powerful evidence about antithrombotic mechanisms of three compounds and GF. This research have succeeded to discover and identify three representative antithrombotic compounds of GF using an efficient integrated research strategy we established, an Omics Discriminant-Grey Correlation-Biological Activity strategy. The antithrombotic chemical makers we found could also contribute to provided more accurate index components for comprehensive quality control of GF.

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