高等学校化学学报 ›› 2012, Vol. 33 ›› Issue (09): 1932.doi: 10.3969/j.issn.0251-0790.2012.09.010

• 分析化学 • 上一篇    下一篇

阿卡波糖对Ⅱ型糖尿病大鼠尿液代谢轮廓的影响

刘跃芹1,2, 皮子凤2, 宋凤瑞2, 刘志强2, 刘忠英1   

  1. 1. 吉林大学药学院, 长春 130021;
    2. 中国科学院长春应用化学研究所, 长春质谱中心, 长春 130022
  • 收稿日期:2012-01-16 出版日期:2012-09-10 发布日期:2012-08-14
  • 通讯作者: 皮子凤,女,副研究员,主要从事中药活性成分筛选及代谢方面研究.E-mail:mslab21@ciac.jl.cn E-mail:mslab21@ciac.jl.cn; liuzy@jlu.edu.cn
  • 基金资助:

    吉林省科技发展计划项目(批准号: 20090739)和国家自然科学基金(批准号: 21005075)资助.

Effect of Acarbose on Urine Metabolic Profiling of Type Ⅱ Diabete Rats

LIU Yue-Qin1,2, PI Zi-Feng2, SONG Feng-Rui2, LIU Zhi-Qiang2, LIU Zhong-Ying1   

  1. 1. School of Pharmacetical Sciences, Jilin University, Changchun 130021, China;
    2. Changchun Center of Mass Spectrometry, Changchun Insititute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China
  • Received:2012-01-16 Online:2012-09-10 Published:2012-08-14

摘要:

采用超高效液相色谱-质谱联用(UPLC-MS/MS)方法研究了阿卡波糖对Ⅱ型糖尿病大鼠代谢轮廓的影响, 分析了健康组、 糖尿病模型组和糖尿病给予阿卡波糖组的大鼠尿样, 采用主成分分析法(PCA)和偏最小二乘法-判别分析(PLS-DA)对数据进行分析. PCA得分图表明, 健康组、 糖尿病组和阿卡波糖组的代谢轮廓有显著差别, 根据PLS-DA载荷图筛选, 将对各组分离贡献大的化合物的串联质谱分析数据经Human Metabolome Database(HMDB)和Mass Bank.jp等数据库检索, 进行质谱信息匹配, 鉴定出苯乙酰甘氨酸、 肌酐及葡萄糖酸等8种内源性代谢物为潜在生物标记物.

关键词: Ⅱ型糖尿病大鼠, 尿液, 代谢组学, 超高效液相色谱-质谱联用, 主成分分析

Abstract:

An ultra performance liquid chromatography-mass spectrometry(UPLC-MS) method was developed for the metabonomics study of effect of acarbose on type Ⅱ diabete rats. Urine from three groups of rats including control group, model group and diabete rats treated with acarbose group were analyzed, and the data were analyzed by the method of principal component analysis(PCA) and partial least squares-discriminant analysis(PLS-DA). The PCA score plots showed that the three groups were significantly different between the metabolic profile. According to the results of PLS-DA, the MS/MS data of each compound which provide greater contribution to separation of each group was searched from the Human Metabolome Database(HMDB) and Mass Bank. jp databases. Eight kinds of endogenous metabolites were identified as potential biomarkers such as gluconic acid, phenylacetylglycine, creatinine, etc.

Key words: Type Ⅱ diabete rat, Urine, Metabonomics, UPLC-MS/MS, Principal component analysis(PCA)

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