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Investigation of mechanisms of mesenchymal stem cells for treatment of diabetic nephropathy via construction of a miRNA-TF-mRNA network

机译:通过构建miRNA-TF-mRNA网络研究间充质干细胞治疗糖尿病肾病的机制

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Abstract Background: Recent studies have reported that mesenchymal stem cells (MSCs) exert therapeutic effects on the treatment of diabetic nephropathy (DN), but the underlying mechanisms remain unclear. Methods: A dataset GSE65561 was obtained from Gene Expression Omnibus (GEO) database, which contained four healthy control samples (group 1), four healthy controls samples co-cultured with MSCs (group 2), five DN samples (group 3) and five DN samples co-cultured with MSCs (group 4). The differentially expressed genes (DEGs) between group 3 vs. group 1 and group 4 vs. group 2 were constructed using Linear Models for Microarray (LIMMA) package package. Then, DAVID was used to analyze the functional enrichment of DEGs. Based on STRING database the protein-protein interaction (PPI) network was visualized by the Cytoscape plug-in CytoNCA. Besides, the hub miRNAs and transcription factors (TFs) regulating DEGs were predicted using Webgestalt. Results: Totally, 303 up-regulated and 88 down-regulated DEGs were shared in group 3 vs. group 1 and group 4 vs. group 2. Besides, the up-regulated DEGs were mainly enriched in ‘translation’ and ‘translational elongation’, while the down-regulated genes were only enriched in ‘protein kinase activity’. RPS27A and RPLP0 had a higher degree in the PPI network and they were regulated by EIF3M. In addition, ETF1 was predicted to be an important gene, which was regulated by miR-150, miR-134 and EIF2S1. Conclusions: RPS27A, RPLP0 and ETF1 may be potential targets for MSCs on the treatment of DN. Highlights RPS27A and RPLP0 may be important genes in the treatment of MSCs for DN. TF EIF3M may play a key role in the treatment of MSCs for DN. MiR-150 and miR-134 may be essential microRNAs in the treatment of MSCs for DN.
机译:摘要背景:最近的研究报道,间充质干细胞(MSCs)对糖尿病性肾病(DN)具有治疗作用,但其潜在机制尚不清楚。方法:从Gene Expression Omnibus(GEO)数据库获得数据集GSE65561,其中包含四个健康对照样品(第1组),四个与MSC共培养的健康对照样品(第2组),五个DN样品(第3组)和五个与MSC共培养的DN样品(第4组)。使用微阵列线性模型(LIMMA)包装套件构建了第3组与第1组之间的差异表达基因(DEG)和第4组与第2组之间的差异表达基因(DEG)。然后,使用DAVID分析DEG的功能。基于STRING数据库,可以通过Cytoscape插件CytoNCA可视化蛋白质-蛋白质相互作用(PPI)网络。此外,使用Webgestalt预测了调节DEG的中枢miRNA和转录因子(TF)。结果:第3组与第1组,第4组与第2组共有303个上调的DEG和88个下调的DEG。此外,上调的DEG主要富含“翻译”和“翻译延伸” ,而下调的基因仅富含“蛋白激酶活性”。 RPS27A和RPLP0在PPI网络中具有较高的程度,并且受EIF3M调节。此外,预计ETF1是重要的基因,受miR-150,miR-134和EIF2S1调控。结论:RPS27A,RPLP0和ETF1可能是MSC治疗DN的潜在靶标。重点说明RPS27A和RPLP0可能是MSC治疗DN的重要基因。 TF EIF3M可能在MSC治疗DN中起关键作用。 MiR-150和miR-134可能是DN MSC治疗中必不可少的microRNA。

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