天津医药 ›› 2021, Vol. 49 ›› Issue (6): 583-587.doi: 10.11958/20200326

• 实验研究 • 上一篇    下一篇

基于GC-TOF/MS技术分析肾性高血压大鼠血清代谢组学变化

陈慧霞,闫宇涵,于慧,王占黎,胡海   

  1. 1包头医学院研究生学院(邮编014040),2基础医学与法医学院;3内蒙古自治区疾病相关生物标志物重点实验室
  • 收稿日期:2020-11-02 修回日期:2021-03-11 出版日期:2021-06-15 发布日期:2021-06-15
  • 通讯作者: 陈慧霞 E-mail:1207841643@qq.com
  • 基金资助:
    基于肠道菌群探讨吴茱萸碱对肾性高血压大鼠VECs功能的影响及机制

Analysis of serum metabonomics in renovascular hypertensive rats based on GC-TOF/MS

CHEN Hui-xia, YAN Yu-han, YU Hui, WANG Zhan-li, HU Hai#br#   

  1. 1 Graduate School, 2 School of Basic Medical Sciences & Forensic Medicine, Baotou Medical College, Baotou 014040, China;
    3 the Inner Mongolia Autonomous Region Key Laboratory of Disease-Related Biomarkers

  • Received:2020-11-02 Revised:2021-03-11 Published:2021-06-15 Online:2021-06-15

摘要: 目的 基于气相色谱-质谱(GC-TOF/MS)技术分析两肾一夹(2K1C)肾性高血压大鼠血清代谢物的变化 情况。方法 20只健康雄性SD大鼠按照随机数字表法分为假手术(Sham)组和2K1C组,每组10只。比较建模前及 建模4周后2组大鼠体质量及尾动脉收缩压变化。采用GC-TOF/MS检测血清代谢产物的表达水平,正交偏最小二乘 法-判别分析(OPLS-DA)筛选出差异表达代谢物,并对筛选出的差异表达代谢物进行聚类分析及KEGG通路分析。 结果 4周后2K1C组共7只大鼠建模成功。与Sham组相比,2K1C组共筛选到14种差异表达代谢物,其中,花生四 烯酸(arachidonic acid)、马尿酸(hippuric acid)、七烷酸(heptadecanoic acid)、吲哚乳酸酯(indolelactate)、木糖(xylose)、 顺-巨头鲸鱼酸(cis-gondoic acid)、富马酸(fumaric acid)、胞苷-磷酸(cytidine-monophosphate)、乳酰胺(lactamide)、2- 羟基-3-异丙基丁二酸(2-hydroxy-3-isopropylbutanedioic acid)、双缩脲(biuret)这 11 种代谢物表达上调,酪氨酸 (tyrosine)、胆酸(cholic acid)、豆甾醇(stigmasterol)表达下调。以上差异表达代谢物与能量代谢、氨基酸代谢、脂质代 谢、初级胆汁酸生物合成等生物过程密切相关。结论 2K1C肾性高血压大鼠血清代谢物发生变化,并涉及能量代谢 等多种通路,进而影响肾性高血压的病理生理过程。

关键词: 高血压, 肾性, 代谢组学, 气相色谱-质谱法, 聚类分析, 大鼠, Sprague-Dawley, 两肾一夹

Abstract: Objective To analyze changes of serum metabolites in two-kidney-one-clip (2K1C) renal hypertension rats and sham-operated rats based on the gas chromatography-time-of-flight mass spectrometry (GC-TOF/MS) technology. Methods Twenty healthy male SD rats were randomly divided into sham operation group and 2K1C model group with 10 rats in each group. The changes of body mass and tail artery systolic pressure before modeling and four weeks after modeling were compared between the two groups of rats. GC-TOF/MS was used to detect the expression level of serum metabolites, and orthogonal partial least squares discriminant analysis (OPLS-DA) was used to screen out the differential metabolites. The screened differential metabolites were analyzed by Cluster analysis and KEGG pathway analysis. Results A total of 7 rats were successfully modeled after 4 weeks in the 2K1C model group. Compared with the Sham group, a total of 14 differentially expressed metabolites were screened in the 2K1C model group, including up-regulated arachidonic acid, hippuric acid, heptadecanoic acid, indolelactate, xylose, cis-gondoic acid, fumaric acid, cytidine-monophosphate, lactamide, 2-hydroxy-3-isopropylbutanedioic acid and biuret, and down-regulated tyrosine, cholic acid and stigmasterol. These differential metabolites were closely related to energy metabolism, amino acid metabolism, lipid metabolism and primary bile acid biosynthesis. Conclusion The changes of serum metabolites in 2K1C hypertensive rats are involved in various pathways such as energy metabolism, which in turn affects the pathophysiological process of renal hypertension.

Key words: hypertension, renal, metabolomics, gas chromatography-mass spectrometry, cluster analysis, rats, Sprague-Dawley, two-kidney-one-clip