基于UHPLC-QTOF-MS探讨高原鼠兔棕色脂肪低氧环境代谢分子机制

薛华, 何雨昕, 郭子旭, 林凯歌, 白振忠, 曹学锋

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重庆医科大学学报 ›› 2025, Vol. 50 ›› Issue (02) : 267-274. DOI: 10.13406/j.cnki.cyxb.003731
基础研究

基于UHPLC-QTOF-MS探讨高原鼠兔棕色脂肪低氧环境代谢分子机制

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Molecular mechanism of brown adipose tissue metabolism in the hypoxic environment in plateau pikas: a study based on ultra-performance liquid chromatography-quadruple time-of-flight mass spectrometry

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摘要

目的 基于超高效液相色谱—四极杆飞行时间质谱联用(ultra high performance liquid chromatography quadrupole time-of-flight mass spectrometry,UHPLC-QTOF-MS)研究不同海拔下高原鼠兔棕色脂肪组织(brown adipose tissue,BAT)中的内源性差异代谢物及代谢通路,探讨BAT适应高原极端环境的代谢分子机制。 方法 分别捕捉青海省果洛地区(4 360 m)(MD组)和海北州门源地区(2 900 m)(MY组)高原鼠兔各8只,利用UHPLC-QTOF-MS检测2组高原鼠兔BAT样本代谢产物,采用Simca软件对BAT代谢轮廓特征进行主成分分析(principal component analysis,PCA)和正交偏最小二乘判别分析(orthogonal projections to latent structures- discriminant analysis,OPLS-DA),结合t检验、火山图分析差异代谢物,并对差异代谢物进行KEGG代谢通路分析,构建气泡图。 结果 PCA和OPLS-DA模式结果显示,2组BAT代谢组均表现出明显聚类型分布,这些代谢物参与体内糖代谢、脂代谢、氨基酸代谢、核苷酸代谢、胆汁酸代谢等多种生命活动。其中,葡萄糖-6-磷酸、胆酸、ADP-核糖、腺苷、脱氧胞苷、L-苯丙氨酸等代谢物水平在MD组高原鼠兔BAT中明显上调(P<0.05);去甲肾上腺素、硬脂酸、尿素、鸟氨酸、丙硫氧嘧啶等代谢物水平明显下调(P<0.05)。富集通路分析发现BAT代谢与苯丙氨酸、磷酸戊糖途径、酪氨酸、色氨酸等代谢通路相关。 结论 高原极端环境影响机体的能量相关代谢通路有效激活BAT非颤抖产热,促进机体脂肪组织分化与白色脂肪褐变,增加BAT比重,以此适应高原极端环境。

Abstract

Objective To investigate the differentially expressed endogenous metabolites and metabolic pathways in the brown adipose tissue(BAT) of plateau pikas at different altitudes based on ultra-performance liquid chromatography-quadruple time-of-flight mass spectrometry(UHPLC-QTOF-MS),as well as the metabolic molecular mechanism for BAT to adapt to extreme high-altitude environments. Methods Eight pikas captured from Guoluo area(4 360 m) of Qinghai Province in China were established as MD group,and eight pikas captured from Menyuan area(2 900 m) of Haibei Prefecture were established as MY group. UHPLC-QTOF-MS was used to analyze the metabolites in BAT samples of the two groups,and Simca software was used to perform the principal component analysis (PCA) and the orthogonal partial least squares-discriminant analysis(OPLS-DA) of the metabolic profile features of BAT. The t-test,volcanic map analysis,and KEGG metabolic pathway analysis were performed for differentially expressed metabolites,and a bubble map was constructed. Results PCA and OPLS-DA showed that the BAT metabolomics in both groups showed significant clustering distribution,and these metabolites were involved in various life activities such as glucose metabolism,lipid metabolism,amino acid metabolism,nucleotide metabolism,and bile acid metabolism in the body. Among these metabolites,glucose 6-phosphate,cholic acid,ADP ribose,adenosine,deoxycytidine,and L-phenylalanine were significantly upregulated in the BAT of the MD group(P<0.05),while norepinephrine,stearic acid,urea,ornithine,and propylthiouracil were significantly downregulated(P<0.05). The pathway enrichment analysis showed that BAT metabolism was associated with the metabolic pathways of phenylalanine,phosphopentose,tyrosine,and tryptophan. Conclusion Extreme high-altitude environment effectively activates non-shivering heat production in BAT by affecting the energy-related metabolic pathways in the body,promotes adipose tissue differentiation and white adipose browning,and increases the proportion of BAT,thereby helping to adapt to the extreme high-altitude environment.

关键词

超高效液相色谱—四极杆飞行时间质谱联用技术 / 高原低氧 / 高原鼠兔 / 棕色脂肪组织 / 代谢组学

Key words

ultra-performance liquid chromatography-quadruple time-of-flight mass spectrometry / high altitude hypoxia / plateau pikas / brown adipose tissue / metabolomics

中图分类号

R339.5

引用本文

导出引用
薛华 , 何雨昕 , 郭子旭 , . 基于UHPLC-QTOF-MS探讨高原鼠兔棕色脂肪低氧环境代谢分子机制. 重庆医科大学学报. 2025, 50(02): 267-274 https://doi.org/10.13406/j.cnki.cyxb.003731
Xue Hua, He Yuxin, Guo Zixu, et al. Molecular mechanism of brown adipose tissue metabolism in the hypoxic environment in plateau pikas: a study based on ultra-performance liquid chromatography-quadruple time-of-flight mass spectrometry[J]. Journal of Chongqing Medical University. 2025, 50(02): 267-274 https://doi.org/10.13406/j.cnki.cyxb.003731

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基金

青海省“昆仑英才”行动计划资助项目(K9924072)
青海省科技厅基础研究计划资助项目(2023-ZJ-773)

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