杨果, 李超, 姚武, 夏佳蕊, 祁远梦, 郝长付. A549细胞上皮-间质转分化中差异表达基因的生物信息学分析[J]. 环境与职业医学, 2021, 38(3): 245-253. DOI: 10.13213/j.cnki.jeom.2021.20467
引用本文: 杨果, 李超, 姚武, 夏佳蕊, 祁远梦, 郝长付. A549细胞上皮-间质转分化中差异表达基因的生物信息学分析[J]. 环境与职业医学, 2021, 38(3): 245-253. DOI: 10.13213/j.cnki.jeom.2021.20467
YANG Guo, LI Chao, YAO Wu, XIA Jiarui, QI Yuanmeng, HAO Changfu. Bioinformatics analysis on differentially expressed genes in epithelial-mesenchymal transition of A549 cells[J]. Journal of Environmental and Occupational Medicine, 2021, 38(3): 245-253. DOI: 10.13213/j.cnki.jeom.2021.20467
Citation: YANG Guo, LI Chao, YAO Wu, XIA Jiarui, QI Yuanmeng, HAO Changfu. Bioinformatics analysis on differentially expressed genes in epithelial-mesenchymal transition of A549 cells[J]. Journal of Environmental and Occupational Medicine, 2021, 38(3): 245-253. DOI: 10.13213/j.cnki.jeom.2021.20467

A549细胞上皮-间质转分化中差异表达基因的生物信息学分析

Bioinformatics analysis on differentially expressed genes in epithelial-mesenchymal transition of A549 cells

  • 摘要: 背景

    在肺纤维化中,上皮-间质转分化(EMT)具有重要的作用。肺泡上皮细胞的EMT是肌成纤维细胞的一个重要来源。而随着高通量测序技术的发展,利用生物信息学的分析筛选EMT过程中的关键基因(Hub基因)引起了学者们的关注。

    目的

    分析人肺泡Ⅱ型上皮细胞(A549细胞)相关EMT过程中的差异表达基因,以此筛选肺纤维化相关EMT过程中的Hub基因以及相关的关键信号通路,以期为肺纤维化相关的EMT研究提供新的思路。

    方法

    从美国国立信息中心的基因表达综合数据库下载芯片数据集GSE17708,运用R语言中的limma包进行差异表达基因的分析。采用DAVID 6.8对差异表达基因进行基因本体(GO)富集分析和京都基因与基因组百科全书(KEGG)信号通路分析,并运用相互作用基因库检索工具数据库和Cytoscape软件绘制蛋白质-蛋白质相互作用网络。利用Cytoscape软件中的CytoHubba插件筛选Hub基因,最后通过实时荧光定量聚合酶链式反应(qRT-PCR)技术对A549细胞相关EMT过程中的Hub基因进行验证。

    结果

    基于高通量测序芯片的筛选,55个差异表达的基因主要参与的生物学途径包括胶原蛋白分解代谢的过程、细胞迁移正调控、生长负调节、内皮细胞凋亡过程的负调控以及细胞外基质组织;细胞组分的富集结果显示55个差异表达基因集中在胞外区和细胞外间隙;分子功能的富集显示差异表达基因主要具有细胞外基质结构组成、肝素结合、磷脂酰丝氨酸绑定、酶抑制剂的活动、纤连蛋白结合等功能。KEGG结果表明,差异表达基因可能参与细胞外基质受体相互作用、阿米巴类感染、黏着斑的形成、PI3K-Akt信号通路、矿物质吸收、血小板激活、补体及凝血级联反应、小细胞肺癌等信号通路。随后,通过最大团性中心方法筛选出得分最高的前8个基因(THBS1COL4A1COL5A1COL4A2FGGSERPINE1LAMC2IGFBP5)作为EMT相关的Hub基因,qRT-PCR结果显示IGFBP5在A549细胞中的表达丰度较低,并且与对照组相比,TGF-β刺激A549细胞24 h和72 h的差异并不明显。除FGG在TGF-β刺激A549细胞24 h的时候表达情况与筛选结果不一致外,其他6个Hub基因表达情况与筛选结果一致。

    结论

    筛选出了7个与肺泡上皮细胞间质转分化相关的Hub基因,其中FGG表达下调,其他基因表达上调。

     

    Abstract: Background

    Epithelial mesenchymal transition (EMT) plays an important role in pulmonary fibrosis. EMT of alveolar epithelial cells is a major source of myofibroblasts. Bioinformatic analysis used to screen hub genes in EMT process has attracted the attention of scholars as the highthroughput sequencing technology evolves.

    Objective

    This study is conducted to screen potential hub genes and related key signaling pathways in the EMT process related to pulmonary fibrosis by analyzing the genes differentially expressed during the EMT of human alveolar type Ⅱ epithelial cells (A549 cells), aiming to provide new ideas for the study of EMT related to pulmonary fibrosis.

    Methods

    An GSE17708 dataset was downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information, and used to identify differentially expressed genes by limma package in R language. DAVID 6.8 was used to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis. An interaction gene database and Cytoscape software were used to draw protein-protein interaction (PPI) network. The hub genes were identified by the CytoHubba plugin of Cytoscape software. Finally, the hub genes in the process of EMT of A549 cells were verified by real-time fluorescence quantitative polymerase chain reaction (qRT-PCR).

    Results

    A total of 55 differentially expressed genes were screened out based on high-throughput chip screening. The GO enrichment results showed that 5 enriched GO terms fell in the biological process category, namely collagen catabolic process, positive regulation of cell migration, negative regulation of growth, negative regulation of endothelial cell apoptotic process, and extracellular matrix organization; 2 enriched terms in the cellular component category, mainly in extracellular region and extracellular space; and 5 enriched terms in the molecular function category, containing extracellular matrix structural constituent, heparin binding, phosphatidylserine binding, enzyme inhibitor activity, and fibronectin binding. The results of KEGG showed that differentially expressed genes were mainly involved in extracellular matrix-receptor interaction, amoebiasis, focal adhesion, PI3K-Akt signaling pathway, mineral absorption, platelet activation, complement and coagulation cascades, and small lung cell cancer. Subsequently, the top eight genes with the highest scores were determined as hub genes related to EMT through the maximal clique centrality (MCC) method: THBS1, COL4A1, COL5A1, COL4A2, FGG, SERPINE1, LAMC2, and IGFBP5. The qRT-PCR results showed that the abundance of IGFBP5 was lower and not significantly different in A549 cells after TGF-β stimulation for 24 h and 72 h compared with the control group. Except the expression of FGG, the expressions of the remaining 6 hub genes were consistent with the screening results of A549 cells after TGF-β stimulation for 24 h.

    Conclusion

    Seven hub genes related to EMT are identified. The expression of FGG is down-regulated, and the expressions of THBS1, COL4A1, COL5A1, COL4A2, LAMC2 and SERPINE1 are up-regulated.

     

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