Ke Peng, Qian Lin, Zhou Yi, Feng Liu, Zhang Zhentao, Zheng Chengjie, Chen Mengnan, Huang Xinlei, Wu Xiaodan
Department of Anesthesiology, Shengli Clinical Medical College, Fujian Medical University, Fuzhou, Fujian, China.
Institute of Pharmaceutics, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
PeerJ. 2021 Oct 26;9:e12375. doi: 10.7717/peerj.12375. eCollection 2021.
Renal ischemia-reperfusion injury (IRI) is a disease with high incidence rate in kidney related surgery. Micro RNA (miRNA) and transcription factors (TFs) are widely involved in the process of renal IRI through regulation of their target genes. However, the regulatory relationships and functional roles of TFs, miRNAs and mRNAs in the progression of renal IRI are insufficiently understood. The present study aimed to clarify the underlying mechanism of regulatory relationships in renal IRI.
Six gene expression profiles were downloaded from Gene Expression Omnibus (GEO). Differently expressed genes (DEGs) and differently expressed miRNAs (DEMs) were identified through RRA integrated analysis of mRNA datasets (GSE39548, GSE87025, GSE52004, GSE71647, and GSE131288) and miRNA datasets (GSE29495). miRDB and TransmiR v2.0 database were applied to predict target genes of miRNA and TFs, respectively. DEGs were applied for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, followed with construction of protein-protein interaction (PPI) network. Then, the TF-miRNA-mRNA network was constructed. Correlation coefficient and ROC analysis were used to verify regulatory relationship between genes and their diagnostic value in GSE52004. Furthermore, in independent mouse RNA-seq datasets GSE98622, human RNA-seq GSE134386 and , the expression of hub genes and genes from the network were observed and correlation coefficient and ROC analysis were validated.
A total of 21 DEMs and 187 DEGs were identified in renal IRI group compared to control group. The results of PPI analysis showed 15 hub genes. The TF-miRNA-mRNA regulatory network was constructed and several important pathways were identified and further verified, including Junb-miR-223-Ranbp3l, Cebpb-miR-223-Ranbp3l, Cebpb-miR-21-Ranbp3l and Cebpb-miR-181b-Bsnd. Four regulatory loops were identified, including Fosl2-miR-155, Fosl2-miR-146a, Cebpb-miR-155 and Mafk-miR-25. The hub genes and genes in the network showed good diagnostic value in mice and human.
In this study, we found 15 hub genes and several TF-miRNA-mRNA pathways, which are helpful for understanding the molecular and regulatory mechanisms in renal IRI. Junb-miR-223-Ranbp3l, Cebpb-miR-223-Ranbp3l, Cebpb-miR-21-Ranbp3l and Cebpb-miR-181b-Bsnd were the most important pathways, while Spp1, Fos, Timp1, Tnc, Fosl2 and Junb were the most important hub genes. Fosl2-miR-155, Fosl2-miR-146a, Cebpb-miR-155 and Mafk-miR-25 might be the negative feedback loops in renal IRI.
肾缺血再灌注损伤(IRI)是肾脏相关手术中发病率较高的一种疾病。微小RNA(miRNA)和转录因子(TFs)通过调控其靶基因广泛参与肾IRI过程。然而,TFs、miRNAs和mRNAs在肾IRI进展中的调控关系和功能作用尚未得到充分了解。本研究旨在阐明肾IRI调控关系的潜在机制。
从基因表达综合数据库(GEO)下载六个基因表达谱。通过对mRNA数据集(GSE39548、GSE87025、GSE52004、GSE71647和GSE131288)和miRNA数据集(GSE29495)进行RRA综合分析,鉴定差异表达基因(DEGs)和差异表达miRNAs(DEMs)。分别应用miRDB和TransmiR v2.0数据库预测miRNA和TFs的靶基因。对DEGs进行基因本体(GO)和京都基因与基因组百科全书(KEGG)分析,随后构建蛋白质-蛋白质相互作用(PPI)网络。然后,构建TF-miRNA-mRNA网络。使用相关系数和ROC分析验证基因之间的调控关系及其在GSE52004中的诊断价值。此外,在独立的小鼠RNA测序数据集GSE98622、人类RNA测序数据集GSE134386中,观察枢纽基因和网络中基因的表达,并验证相关系数和ROC分析。
与对照组相比,肾IRI组共鉴定出21个DEMs和187个DEGs。PPI分析结果显示15个枢纽基因。构建了TF-miRNA-mRNA调控网络,鉴定并进一步验证了几条重要通路,包括Junb-miR-223-Ranbp3l、Cebpb-miR-223-Ranbp3l、Cebpb-miR-21-Ranbp3l和Cebpb-miR-181b-Bsnd。鉴定出四个调控环,包括Fosl2-miR-155、Fosl2-miR-146a、Cebpb-miR-155和Mafk-miR-25。枢纽基因和网络中的基因在小鼠和人类中显示出良好的诊断价值。
在本研究中,我们发现了15个枢纽基因和几条TF-miRNA-mRNA通路,这有助于理解肾IRI的分子和调控机制。Junb-miR-223-Ranbp3l、Cebpb-miR-223-Ranbp3l、Cebpb-miR-21-Ranbp