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WANG Tao, SUN Hong-Guo, HUA Yong-Li, LI Peng-Ling, WEI Yan-Ming. Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model[J]. 中国天然药物, 2016, 14(3): 210-219.
引用本文: WANG Tao, SUN Hong-Guo, HUA Yong-Li, LI Peng-Ling, WEI Yan-Ming. Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model[J]. 中国天然药物, 2016, 14(3): 210-219.
WANG Tao, SUN Hong-Guo, HUA Yong-Li, LI Peng-Ling, WEI Yan-Ming. Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model[J]. Chinese Journal of Natural Medicines, 2016, 14(3): 210-219.
Citation: WANG Tao, SUN Hong-Guo, HUA Yong-Li, LI Peng-Ling, WEI Yan-Ming. Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model[J]. Chinese Journal of Natural Medicines, 2016, 14(3): 210-219.

Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model

Urine metabonomic study for blood-replenishing mechanism of Angelica sinensis in a blood-deficient mouse model

  • 摘要: This study aimed at determining the effects of Angelica sinensis (AS) on urinary metabolites in blood deficiency mice and exploring its replenishing blood mechanism. Gas chromatography-mass spectrometry (GC-MS) was applied to detect metabolites in the urine samples in different collection periods. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the differences in metabolic profiles among control group (CG), blood deficiency model group (MG), AS groups, and Colla Corii Asini group (CCAG). The potential biomarkers were identified based on the variable importance in the projection (VIP), T-test, and National Institute of Standards and Technology (NIST) and mass spectra library. The metabolites were analyzed using metabolomics pathway analysis (MetPA) to build the metabolic pathways. Our results indicated that, on the seventh day, the levels of glucose, lactic acid, pyruvic acid, alanine, acetoacetic acid, and citric acid changed significantly in blood deficiency mice. However, these metabolic deviations came to closer to normal levels after AS intervention. The reversing blood-deficiency mechanism of AS might involve regulating synthesis and degradation of ketone bodies, Pyruvate metabolism, TCA cycle, and Glycolysis/Gluconeogenesis. In conclusion, metabonomics is a robust and promising means for the identification of biomarkers and elucidation of the mechanisms of a disease, thereby highlighting its importance in drug discovery.

     

    Abstract: This study aimed at determining the effects of Angelica sinensis (AS) on urinary metabolites in blood deficiency mice and exploring its replenishing blood mechanism. Gas chromatography-mass spectrometry (GC-MS) was applied to detect metabolites in the urine samples in different collection periods. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the differences in metabolic profiles among control group (CG), blood deficiency model group (MG), AS groups, and Colla Corii Asini group (CCAG). The potential biomarkers were identified based on the variable importance in the projection (VIP), T-test, and National Institute of Standards and Technology (NIST) and mass spectra library. The metabolites were analyzed using metabolomics pathway analysis (MetPA) to build the metabolic pathways. Our results indicated that, on the seventh day, the levels of glucose, lactic acid, pyruvic acid, alanine, acetoacetic acid, and citric acid changed significantly in blood deficiency mice. However, these metabolic deviations came to closer to normal levels after AS intervention. The reversing blood-deficiency mechanism of AS might involve regulating synthesis and degradation of ketone bodies, Pyruvate metabolism, TCA cycle, and Glycolysis/Gluconeogenesis. In conclusion, metabonomics is a robust and promising means for the identification of biomarkers and elucidation of the mechanisms of a disease, thereby highlighting its importance in drug discovery.

     

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