High-throughput metabolomics reveals the perturbed metabolic pathways and biomarkers of Yang Huang syndrome as potential targets for evaluating the therapeutic effects and mechanism of geniposide
1. National Chinmedomics Research Center, Sino-America Chinmedomics Technology Collaboration Center, National TCM Key Laboratory of Serum Pharmacochemistry, Laboratory of Metabolomics, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin 150040, China 2. State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau 519020, China
High-throughput metabolomics can clarify the underlying molecular mechanism of diseases via the qualitative and quantitative analysis of metabolites. This study used the established Yang Huang syndrome (YHS) mouse model to evaluate the efficacy of geniposide (GEN). Urine metabolic data were quantified by ultra-performance liquid chromatography–tandem mass spectrometry. The non-target screening of the massive biological information dataset was performed, and a total of 33 metabolites, including tyramine glucuronide, aurine, and L-cysteine, were identified relating to YHS. These differential metabolites directly participated in the disturbance of phase I reaction and hydrophilic transformation of bilirubin. Interestingly, they were completely reversed by GEN. While, as the auxiliary technical means, we also focused on the molecular prediction and docking results in network pharmacological and integrated analysis part. We used integrated analysis to communicate the multiple results of metabolomics and network pharmacology. This study is the first to report that GEN indirectly regulates the metabolite “tyramine glucuronide” through its direct effect on the target heme oxygenase 1 in vivo. Meanwhile, heme oxygenase-1, a prediction of network pharmacology, was the confirmed metabolic enzyme of phase I reaction in hepatocytes. Our study indicated that the combination of high-throughput metabolomics and network pharmacology is a robust combination for deciphering the pathogenesis of the traditional Chinese medicine (TCM) syndrome.
. [J]. Frontiers of Medicine, 2020, 14(5): 651-663.
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