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直接重编程非成纤维细胞来源为神经干细胞和神经元过程中调控和蛋白亚网络的转录因子。

Transcription Factors in Regulatory and Protein Subnetworks during Generation of Neural Stem Cells and Neurons from Direct Reprogramming of Non-fibroblastic Cell Sources.

机构信息

National Institute of Genetics Engineering and Biotechnology (NIGEB), Tehran, Iran.

Department of Psychiatry, Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada.

出版信息

Neuroscience. 2018 Jun 1;380:63-77. doi: 10.1016/j.neuroscience.2018.03.033. Epub 2018 Apr 11.

Abstract

Direct reprogramming of non-fibroblastic cells to the neuronal cell types including induced neurons (iNs) and induced neural stem cells (iNSCs) has provided an alternative approach for the direct reprogramming of fibroblasts to those cells. However, to increase the efficiency of the reprogramming process the underlying mechanisms should be clarified. In the current study, we analyzed the gene expression profiles of five different cellular conversions to understand the most significant molecular mechanisms and transcription factors (TFs) underlying each conversion. For each conversion, we found the list of differentially expressed genes (DEGs) and the list of differentially expressed TFs (DE-TFs) which regulate expression of DEGs. Moreover, we constructed gene regulatory networks based on the TF-binding sites' data and found the most central regulators and the most active part of the networks. Furthermore, protein complexes were identified from constructed protein-protein interaction networks for DE-TFs. Finally, we proposed a list of main regulators for each conversion; for example, in the direct conversion of epithelial-like cells (ECs) to iNSCs, combination of centrality with active modules or protein complex analyses highlighted the role of POU3F2, BACH1, AR, PBX1, SOX2 and NANOG genes in this conversion. To the best of our knowledge, this study is the first one that analyzed the direct conversion of non-fibroblastic cells toward iNs and iNSCs and we believe that the expression manipulation of identified genes may increase efficiency of these processes.

摘要

直接将非成纤维细胞重编程为神经元细胞类型,包括诱导神经元(iNs)和诱导神经干细胞(iNSCs),为将成纤维细胞直接重编程为这些细胞提供了一种替代方法。然而,为了提高重编程过程的效率,应该阐明其潜在机制。在本研究中,我们分析了五种不同细胞转化的基因表达谱,以了解每种转化背后最重要的分子机制和转录因子(TFs)。对于每种转化,我们找到了差异表达基因(DEGs)和差异表达 TF(DE-TFs)的列表,这些 TF 调节 DEGs 的表达。此外,我们基于 TF 结合位点的数据构建了基因调控网络,找到了最核心的调控因子和网络中最活跃的部分。此外,从构建的 DE-TFs 蛋白质-蛋白质相互作用网络中鉴定了蛋白质复合物。最后,我们为每种转化提出了一个主要调控因子的列表;例如,在将上皮样细胞(ECs)直接转化为 iNSCs 的过程中,中心性与活性模块或蛋白质复合物分析相结合,突出了 POU3F2、BACH1、AR、PBX1、SOX2 和 NANOG 基因在这一转化中的作用。据我们所知,这是第一项分析非成纤维细胞向 iNs 和 iNSCs 的直接转化的研究,我们相信鉴定基因的表达操纵可能会提高这些过程的效率。

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