食品科学 ›› 2024, Vol. 45 ›› Issue (8): 114-121.doi: 10.7506/spkx1002-6630-20230531-289

• 营养卫生 • 上一篇    下一篇

山茶油干预的阿尔茨海默病小鼠尿液代谢组学分析

王瑞锋,周宁,陈龙,刘通,郭彭莉,张冰贤,张振凯,曾梦楠,熊维政,郑晓珂,冯卫生   

  1. (1.河南中医药大学药学院,河南 郑州 450046;2.河南绿达山茶油股份有限公司,河南 信阳 465550;3.河南省中药开发工程技术研究中心,河南 郑州 450046)
  • 出版日期:2024-04-25 发布日期:2024-05-01
  • 基金资助:
    国家重点研发计划中医药现代化研究重点专项(2019YFC1708802); 河南省高等学校青年骨干教师培养计划(2021GGJS082)

Urine Metabolomics Analysis of the Intervention Effect of Camellia Oil in Mice with Alzheimer’s Disease

WANG Ruifeng, ZHOU Ning, CHEN Long, LIU Tong, GUO Pengli, ZHANG Bingxian, ZHANG Zhenkai, ZENG Mengnan, XIONG Weizheng, ZHENG Xiaoke, FENG Weisheng   

  1. (1. College of Pharmacy, Henan University of Chinese Medicine, Zhengzhou 450046, China; 2. Henan Luda Camellia Oil Limited Company, Xinyang 465550, China; 3. The Engineering and Technology Center for Chinese Medicine Development of Henan Province, Zhengzhou 450046, China)
  • Online:2024-04-25 Published:2024-05-01

摘要: 目的:基于超高效液相色谱-四极杆飞行时间质谱(ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry,UPLC-Q/TOF-MS)技术,利用代谢组学方法探讨山茶油干预的阿尔茨海默病(Alzheimer’s disease,AD)小鼠尿液的代谢组学变化。方法:将小鼠随机分为正常对照组、模型组、阳性药组、山茶油组,除对照组外其余各组小鼠均由β-淀粉样蛋白25-35肽诱导AD,并取尿液样本。尿液沉淀蛋白后进行UPLC-Q/TOF-MS分析,获得小鼠尿液代谢物数据,使用SIMCA-P14.1软件进行主成分分析(principal component analysis,PCA)和正交偏最小二乘判别分析,使用HMBD、MassBank、MetaboAnalyst、京都基因与基因组百科全书在线数据库对生物标志物进行鉴定、通路富集分析和代谢网络的构建。结果:在PCA得分图中,山茶油组样本点远离模型组样本点区域,更接近正常对照组样本点区域。鉴定得到48 个生物标志物,主要涉及的通路有牛磺酸和次牛磺酸代谢,精氨酸和脯氨酸代谢,半胱氨酸和蛋氨酸代谢,丙氨酸、天冬氨酸和谷氨酸代谢等。结论:山茶油通过调节能量代谢、氨基酸代谢等改善了AD小鼠体内代谢,为山茶油干预AD的进一步研究提供参考。

关键词: 代谢组学;山茶油;小鼠;尿液;阿尔茨海默病

Abstract: Objective: Metabolomics based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was applied to explore the metabolic changes in the urine of mice with Alzheimer’s disease (AD) after intervention with camellia oil. Methods: Mice were randomly divided into four groups: normal control, AD model, positive drug and camellia oil treatment. In all mice except for those in the control group, AD was induced by amyloid β-protein (Aβ) 25-35 peptide, and urine samples were collected from each group for UPLC-Q/TOF-MS analysis after protein precipitation. The obtain urine metabolite data were analyzed by the SIMCA-P14.1 software with principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Using the online databases of HMBD, MassBank, MetaboAnalyst and Kyoto Encyclopedia of Genes and Genomes (KEGG), biomarker identification, pathway enrichment analysis, and metabolic network construction were conducted. Results: In the PCA score plots, the camellia oil group was clearly separated from the model group and closer to the normal group. Totally 48 biomarkers were identified and the major pathways involved were taurine and hypotaurine metabolism, arginine and proline metabolism, cysteine and methionine metabolism, alanine, aspartate and glutamate metabolism. Conclusion: Camellia oil can improve the metabolism of AD mice by regulating energy metabolism, amino acid metabolism and other pathways, which provides a reference for further study of camellia oil intervention against AD.

Key words: metabolomics; camellia oil; mice; urine; Alzheimer’s disease

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