中华皮肤科杂志 ›› 2024, Vol. 57 ›› Issue (7): 601-609.doi: 10.35541/cjd.20230452

• 论著 • 上一篇    下一篇

基于非靶向代谢组学分析婴幼儿血管瘤内皮细胞代谢特征

杨开颖    田博闻    蓝超婷   

  1. 广州医科大学附属妇女儿童医疗中心  国家儿童区域医疗中心（中南）小儿外科，广州  510623
  • 收稿日期:2023-08-07 修回日期:2024-04-29 发布日期:2024-07-02
  • 通讯作者: 杨开颖 E-mail:yangkaiying1123@126.com
  • 基金资助:
    广东省基础与应用基础研究基金（2023A1515012751）；广州市基础与应用基础研究基金（2024A04J3857）；中国博士后科学基金（2023M730791、2023M730793）；广州市妇女儿童医疗中心博士启动科研基金（2023BS014、2023BS015）

Untargeted metabolomics analysis-based metabolic characterization of hemangioma-derived endothelial cells

Yang Kaiying, Tian Bowen, Lan Chaoting   

  1. Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, National Children's Medical Center for South Central Region, Guangzhou Medical University, Guangzhou 510623, China
  • Received:2023-08-07 Revised:2024-04-29 Published:2024-07-02
  • Contact: Yang Kaiying E-mail:yangkaiying1123@126.com
  • Supported by:
    The Guangdong Basic and Applied Basic Research Foundation （2023A1515012751）; the Guangzhou Basic and Applied Basic Research Foundation （2024A04J3857）; the China Postdoctoral Science Foundation （2023M730793, 2023M730793）; the Research Foundation of Guangzhou Women and Children′s Medical Center for Clinical Doctor （2023BS014, 2023BS015）

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摘要： 【摘要】 目的 基于非靶向代谢组学探究血管瘤内皮细胞（HemEC）的代谢特征。方法 以原代人脐静脉内皮细胞（HUVEC）为对照组，以HemEC为实验组，提取细胞代谢物，采用超高效液相色谱-质谱法（UPLC-MS）对HUVEC与HemEC进行非靶向代谢组学检测，采用生物信息学分析筛选差异代谢物并进行京都基因与基因组百科全书（KEGG）富集分析和代谢通路分析。单变量分析包括t检验和倍数变化分析，多变量分析包括无监督主成分分析（PCA）和正交偏最小二乘判别分析（OPLS-DA）。结果 在UPLC-MS的正离子模式和负离子模式下，HUVEC与HemEC两组间分别鉴定出542种和241种差异代谢物。正离子模式中差异代谢物主要为脂质和类脂质分子（35.142%）与有机酸和衍生物（24.537%），负离子模式中则为有机酸及其衍生物（31.466%）与脂质和类脂分子（28.879%）。对差异代谢物进行注释分析，在两种离子模式下差异代谢物均主要聚类富集在氨基酸代谢途径中。KEGG代谢通路分析显示，正离子模式下筛选出3条显著差异代谢通路（P < 0.05），包括“精氨酸和脯氨酸代谢”“谷氨酸与谷氨酰胺代谢”及“鞘脂代谢”；负离子模式下共筛选出12条显著性差异代谢通路（P < 0.05），如“精氨酸和脯氨酸代谢”“三羧酸循环”及“甘氨酸、丝氨酸和苏氨酸代谢”。结论 HemEC与HUVEC之间存在显著的代谢差异，氨基酸代谢尤其是精氨酸和脯氨酸代谢是参与调控HemEC代谢的重要通路。

关键词: 血管瘤, 儿童, 血管瘤内皮细胞, 人脐静脉内皮细胞, 非靶向代谢组学, 氨基酸代谢

Abstract: 【Abstract】 Objective To investigate the metabolic profiles of hemangioma-derived endothelial cells （HemECs） based on untargeted metabolomics analysis. Methods Primary human umbilical vein endothelial cells （HUVECs） served as the control group, and HemECs as the experimental group. Cellular metabolites were extracted and analyzed using ultra-performance liquid chromatography-mass spectrometry （UPLC‐MS） for untargeted metabolomics analysis of HUVECs and HemECs. Bioinformatics analysis was employed to screen differentially expressed metabolites, followed by Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis and metabolic pathway analysis. Univariate analysis including t test and fold change analysis, as well as multivariate analysis including unsupervised principal component analysis （PCA） and orthogonal partial least squares discriminant analysis （OPLS-DA） were carried out. Results A total of 542 and 241 differential metabolites were identified between HemECs and HUVECs by using the positive and negative ion modes of UPLC-MS, respectively. In the positive ion mode, the differential metabolites were mainly lipids and lipid-like molecules （35.142%） as well as organic acids and derivatives （24.537%）, while in the negative ion mode the differential metabolites were organic acids and derivatives （31.466%） as well as lipids and lipid-like molecules （28.879%） . Annotation analysis of differential metabolites indicated that differential metabolites were mainly clustered and enriched in amino acid metabolic pathways in both positive and negative ion modes. KEGG metabolic pathway analysis revealed that 3 significantly differential metabolic pathways were screened out in the positive ion mode （P < 0.05）, including "arginine and proline metabolism","glutamic acid and glutamine metabolism" and "sphingolipid metabolism"; in the negative ion mode, 12 significantly differential metabolic pathways were screened out （P < 0.05）, including "arginine and proline metabolism", "tricarboxylic acid cycle", "glycine, serine and threonine metabolism", etc. Conclusion There were significant differences in metabolic profiles between HemECs and HUVECs, and amino acid metabolism, especially arginine and proline metabolism, was an important metabolic pathway involved in the regulation of HemEC metabolism.

Key words: Hemangioma, Child, Hemangioma-derived endothelial cell, Human umbilical vein endothelial cells, Untargeted metabolomics, Amino acid metabolism

引用本文

杨开颖 田博闻 蓝超婷. 基于非靶向代谢组学分析婴幼儿血管瘤内皮细胞代谢特征[J]. 中华皮肤科杂志, 2024,57(7):601-609. doi:10.35541/cjd.20230452

Yang Kaiying, Tian Bowen, Lan Chaoting. Untargeted metabolomics analysis-based metabolic characterization of hemangioma-derived endothelial cells[J]. Chinese Journal of Dermatology, 2024, 57(7): 601-609.doi:10.35541/cjd.20230452