代谢组学
化学
中医药
线性判别分析
层次聚类
主成分分析
偏最小二乘回归
质谱法
计算生物学
色谱法
人工智能
聚类分析
计算机科学
生物
机器学习
医学
病理
替代医学
作者
Wei Zhang,Wenbo Li,Hui Zou,Kang Xu,Hongping Long,Jing Li,Qi Huang,Zhen‐Xing Zou,Yikun Wang,Gui‐Shan Tan
标识
DOI:10.1016/j.arabjc.2022.104281
摘要
Quality control of traditional Chinese medicine (TCM) should be linked with the authentication and efficacy of TCM. Selaginella tamariscina is a frequently used traditional Chinese herbal medicine. However, its quality control is still difficult due to its multiple adulterants. We established quality markers (Q-markers) of S. tamariscina by using metabolomics, molecular networking and network pharmacology to improve the authenticity study and quality control of S. tamariscina. In this study, ultra high performance liquid chromatography-mass spectrum (UHPLC-MS) coupled with multivariate statistical analyses was applied to distinguish between S. tamariscina samples and their confusing adulterants. Principal component analysis, hierarchical clustering analysis (PCA), hierarchical clustering analysis (HCA) and partial least squares discriminant analysis (PLS-DA) were employed to screen the distinguishing markers from S. tamariscina samples and their adulterants. The top-2 distinguishing markers were isolated from S. tamariscina and identified by molecular networking together with nuclear magnetic resonance spectroscopy (NMR). Network pharmacology predicted the bioactivity and cytotoxicity of the top-2 distinguishing markers. The top-2 distinguishing markers were adopted as Q-markers of S. tamariscina for content determination. Based on the results of ultra performance liquid chromatography-quardrupole-time of flight mass spectrometry (UHPLC-QTOF-MS) metabolomics, we revealed that selaginellins could only be detected in S. tamariscina samples and contributed greatly to discriminating S. tamariscina samples from their confused species. The top-2 distinguishing markers were isolated and purified from S. tamariscina extract. Then, they were further identified as selaginellin and selaginellin A by molecular networking and NMR. Network pharmacology predicted the antitumor activity of selaginellin and selaginellin A, while the cytotoxicity assay verified their bioactivity. In conclusion, selaginellin and selaginellin A were selected as Q-markers for the determination and quality evaluation of S. tamariscina based on ultra performance liquid chromatography-triple quadrupole tandem mass spectrometry (UHPLC-QQQ-MS). The ranges of the concentrations of selaginellin and selaginellin A were 41.57–44.89 μg/g and 15.09–16.75 μg/g, respectively. This study provides a novel strategy combining Ultra performance liquid chromatography mass spectrometry based (UHPLC-MS-based) metabolomics with molecular networking for rapid species identification of S. tamariscina and discovery of the Q-markers of TCM.
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