吉林大学学报(医学版) ›› 2022, Vol. 48 ›› Issue (5): 1290-1297.doi: 10.13481/j.1671-587X.20220524

• 临床研究 • 上一篇    

基于囊性纤维化疾病分子特征及其作用机制的生物信息学分析

王小燕1,张秋月2,胡雨洁2,莫之婧2()   

  1. 1.桂林医学院生物技术学院实验教学中心,广西 桂林 541199
    2.桂林医学院生物技术学院生物化学与分子生物学教研室,广西 桂林 541199
  • 收稿日期:2021-12-01 出版日期:2022-09-28 发布日期:2022-11-15
  • 通讯作者: 莫之婧 E-mail:mozhijing@glmc.edu.cn
  • 作者简介:王小燕(1983-),女,江西省上饶市人,实验师,理学硕士,主要从事疾病分子机制方面的研究。
  • 基金资助:
    国家自然科学基金项目(32060159);广西壮族自治区科技厅自然科学基金项目(2019JJA140462);广西壮 族自治区教育厅大学生创新创业训练计划项目(202110601033)

Bioinformatics analysis based on molecular characteristics and mechanism of cystic fibrosis

Xiaoyan WANG1,Qiuyue ZHANG2,Yujie HU2,Zhijing MO2()   

  1. 1.Department of Experimental Teaching Center,College of Biotechnology,Guilin Medical University,Guilin 541199,China
    2.Department of Biochemistry and Molecular Biology,College of Biotechnology,Guilin Medical University,Guilin 541199,China
  • Received:2021-12-01 Online:2022-09-28 Published:2022-11-15
  • Contact: Zhijing MO E-mail:mozhijing@glmc.edu.cn

摘要:

目的 筛选囊性纤维化(CF)特异性相关基因,预测其靶基因,并探讨其作用机制。 方法 从基因表达汇编(GEO)数据库获取CF样本和正常对照样本的高通量芯片数据集GSE71799、GSE24206、GSE98925和GSE69764,并分为CF组和对照组。采用R软件limma包筛选CF组和对照组差异表达基因(DEGs),使用基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)对DEGs进行功能和通路富集分析,使用基因集富集分析(GSEA)获取DEGs显著富集的基因集,采用STRING数据库建立蛋白-蛋白互作(PPI)网络,采用Cytoscape软件可视化并筛选hub基因。 结果 GEO数据库获取并筛选共429个DEGs(|log2(FC)|>1,P<0.05),CF组中显著高表达DEGs 105个,对照组中显著高表达DEGs 324个。GO富集分析,DEGs主要富集于中性粒细胞介导的免疫、趋化因子活动和细胞黏附分子结合等方面;KEGG通路分析,DEGs主要富集于白细胞介素17(IL-17)信号通路(P<0.05)。GSEA分析,DEGs主要富集于信号通路翻译、核糖体RNA(rRNA)处理和线粒体翻译等相关基因集。STRING数据库和Cytoscape软件分析共筛选出基质金属蛋白酶9(MMP9)、C-X-C基序趋化因子配体2(CXCL2)、C-X-C基序趋化因子配体3(CXCL3)等35个hub基因,其中CXCL2和CXCL3 hub基因与DNA甲基化有关联。 结论 hub基因可能是CF中调节中性粒细胞免疫的关键基因,通过中性粒细胞介导的免疫和与免疫密切相关的IL-17信号通路相关基因失调可促进CF发生发展,CXCL2和CXCL3基因可能成为CF的DNA甲基化治疗的生物标志物。

关键词: 囊性纤维化, 生物信息学, 差异表达基因, hub基因, 分子机制

Abstract:

Objective To screen the specific genes of cystic fibrosis (CF) and predict the target genes, and to study its mechanism. Methods The datasets(GSE71799,GSE24206,GSE98925 and GSE69764) including CF samples and normal samples were downloaded from the Gene Expression Omnibus(GEO)database and divided into CF group and control group. The R software limma package was used to screen the differentially expressed genes(DEGs) in CF group and control group. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG)were used to analyze the function and pathway enrichment of DEGs, Gene Set Enrichment Analysis(GSEA)was used to obtain the significantly enriched gene sets of DEGs, and STRING database was used to establish the protein-protein interaction(PPI)network. The PPI network was analyzed and visualized by Cytoscape software, and the hub genes were screened. Results A total of 429 DEGs were obtained and screened, including 105 DEGs that were overexpressed in CF group and 324 DEGs that were overexpressed in control group(|log2(FC)|>1,P<0.05). The GO enrichment analysis results showed that DEGs were mainly enriched in the neutrophil mediated immunity, chemokine activity and cell adhesion molecule binding and so on(P<0.05). The results of KEGG pathway analysis demonstrated that DEGs were mainly enriched in interleukin-17(IL-17) signaling pathway(P<0.05). The results of GSEA demonstrated that DEGs were mainly enriched in signaling pathway translation, ribosomal RNA(rRNA) processing and mitochondrial translation and so on. Through STRING database and Cytoscape software, 35 hub genes in the PPI network were screened out, including matrix metallopeptidase 9(MMP9), C-X-C motif chemokine ligand 2(CXCL2) and C-X-C motif chemokine ligand 3(CXCL3). In addition, CXCL2 and CXCL3 were associated with DNA methylation. Conclusion The disorder of neutrophil-mediated immunity-related genes and IL-17 signaling pathway-related genes may play an important role in the occurrence and development of CF. CXCL2 and CXCL3 genes may become the biomarkers for DNA methylation therapy of CF.

Key words: Cystic fibrosis, Bioinformatics, Differentially expressed genes, Hub gene, Molecular mechanism

中图分类号: 

  • R34