Ambele Melvin Anyasi, Pepper Michael Sean
Department of Immunology and Institute for Cellular and Molecular MedicineSAMRC Extramural Unit for Stem Cell Research and TherapyFaculty of Health SciencesUniversity of PretoriaPretoriaSouth Africa.
Mol Genet Genomic Med. 2017 Mar 3;5(3):210-222. doi: 10.1002/mgg3.269. eCollection 2017 May.
Increased adiposity in humans leads to obesity, which is a major risk factor for cardiovascular disease, type 2 diabetes, and cancer. We previously conducted an extensive unbiased in vitro transcriptomic analysis of adipogenesis, using human adipose-derived stromal cells (ASCs). Here, we have applied computational methods to these data to identify transcription factors (TFs) that constitute the upstream gene regulatory networks potentially, driving adipocyte formation in human ASCs.
We used Affymetrix Transcription Analysis Console™ v3.0 for calculating differentially expressed genes. MATCH™ and F-MATCH™ algorithms for TF identification. STRING v10 to predict protein-protein interactions between TFs.
A number of TFs that were reported to have a significant role in adipogenesis, as well as novel TFs that have not previously been described in this context, were identified. Thus, 32 upstream TFs were identified, with most belonging to the C2H2-type zinc finger and HOX families, which are potentially involved in regulating most of the differentially expressed genes observed during adipocyte differentiation. Furthermore, 17 important upstream TFs were found to have increased regulatory effects on their downstream target genes and were consistently up-regulated during the differentiation process. A strong hypothetical functional interaction was observed among these TFs, which supports their common role in the downstream regulation of gene expression during adipogenesis.
Our results support several previous findings on TFs involved in adipogenesis and thereby validate the comprehensive and systematic in silico approach described in this study. In silico analysis also allowed for the identification of novel regulators of adipocyte differentiation.
人类肥胖程度增加会导致肥胖症，而肥胖症是心血管疾病、2型糖尿病和癌症的主要危险因素。我们之前使用人脂肪来源的基质细胞（ASCs）对脂肪生成进行了广泛的无偏倚体外转录组分析。在此，我们应用计算方法对这些数据进行分析，以识别可能构成上游基因调控网络、驱动人ASCs中脂肪细胞形成的转录因子（TFs）。
我们使用Affymetrix转录分析控制台™ v3.0计算差异表达基因，使用MATCH™和F-MATCH™算法识别TFs，使用STRING v10预测TFs之间的蛋白质-蛋白质相互作用。
我们识别出了一些据报道在脂肪生成中起重要作用的TFs，以及此前在此背景下未被描述过的新型TFs。因此，共识别出32个上游TFs，其中大多数属于C2H2型锌指和HOX家族，它们可能参与调控脂肪细胞分化过程中观察到的大多数差异表达基因。此外，发现17个重要的上游TFs对其下游靶基因具有增强的调控作用，且在分化过程中持续上调。在这些TFs之间观察到强烈的假设性功能相互作用，这支持了它们在脂肪生成过程中对基因表达的下游调控中的共同作用。
我们的结果支持了之前关于参与脂肪生成的TFs的多项发现，从而验证了本研究中描述的全面且系统的计算机模拟方法。计算机模拟分析还使得能够识别脂肪细胞分化的新型调节因子。
