摘要
目的应用生物信息学方法,对肺结核miRNA表达谱详细分析,筛选出具有差异性的miRNA并对其靶基因进行预测,同时对相应靶基因的生物学功能进行分析。方法下载GEO数据库肺结核miRNA表达谱芯片数据GSE34608,应用R软件对数据进行处理分析,筛选差异表达miRNA;应用TargetScanHuman网站预测其靶基因;采用FunRich软件进行生物功能富集分析;String、Cytoscape软件则用来构建靶基因的蛋白-蛋白互作网络以及筛选Hub基因,使miRNA-Hub gene网络进一步构建完善。结果GSE34608芯片数据共筛选出253个差异表达的miRNAs,在肺结核患者外周血中表达上调的201个,下调的52个。预测上调幅度和下调幅度最显著的两个miRNA的靶基因1450个,它们参与了内皮素信号通路,VEGF信号通路,磷脂酰肌醇聚糖1等信号通路等。在PPI网络中,靶基因连通度最高的前十位的Hub基因,如STAT6等。构建的miRNA-Hub gene网络表明大部分hub基因都可能被has-miR-144和hsa-miR-768-3p调控。结论通过生物信息学方法分析肺结核患者和健康人群外周血的差异表达miRNAs,最终筛选出2个差异显著的miRNA和10个关键的Hub基因,为进一步研究肺结核的分子标志物和机制提供了新的方向和依据。
Objective To analyze the biological functions of miRNAs expressed in the pulmonary tuberculosis and to screen their differentially expressed miRNAs(DE-miRNAs)and potential target gene by using various bioinformatics analysis tools.Methods All the expression profiles of GSE34608 were downloaded from the Gene Expression Omnibus(GEO)database;apply the software R to analyze the data and to screen DE-miRNAs;Target Scan Human was employed to predict their target gene while performing functional annotation and pathway enrichment analysis was distributed to FunRich;String and Cytoscape were introduced to construct protein-protein interaction(PPI)network and identify the key Hub genes,and further to construct miRNA-Hub gene network.Results A total of 253 DE-miRNAs were screened out by the data chip GES34608,containing 201 upregulated miRNAs and 52 downregulated miRNAs in peripheral blood of patients with pulmonary tuberculosis.We predict 1450 target genes range from the top two upregulated and downregulated miRNAs,and they were involved in several signaling pathways,such as endothelin,VEGF and phosphatidylinositol glycan1.In the PPI network,we identified the top 10 hub nodes with higher degrees.STAT6 is the top hub genes.Through constructing the miRNA-hub gene network,it is discovered that has-miR-144 and hsa-miR-768-3p could potentially modulate most of hub genes.Conclusion Two DE-miRNAs and ten key hub genes were finally screened out in peripheral blood between tuberculosis patients and healthy population by bioinformatics analysis of the differentially expressed miRNAs.These are to provide theoretical guidance for further research on molecular marker mechanisms of pulmonary tuberculosis.
作者
黄继康
刘斌
HUANG Ji-kang;LIU Bin(Infectious Disease Department,the Affiliated ShunDe Hospital of Ji Nan University,Foshan,Guangdong 528000)
出处
《智慧健康》
2020年第34期1-5,18,共6页
Smart Healthcare
作者简介
黄继康(1984-),主治医师,研究方向:肺结核;通信作者:刘斌(1966-),副主任医师,研究方向:肺结核。
