Functional evaluation of microrna-networks of neuronal differentiation in cell models of limited and full differentiation capability

microrna作为重要的转录后调控因子，本质上参与了许多生物过程的调控。它们在控制神经元分化的复杂分子网络中发挥着关键作用，这些分子网络涉及时间过程和表达水平的精确协调。对于他们的实验性审讯，干细胞已经成为一种有价值和有前途的工具。来自人类脐带血的非限制性体细胞干细胞（USSC）可以被生长和分化因子的混合物诱导为有限的神经元分化（XXL-USSC）。此外，它们可以通过异位逆转录病毒表达OCT4、SOX2、KLF4和C-MYC，被重编程为具有完全分化潜力的诱导多能干细胞（ipUSSC）。本研究旨在比较和功能评价microrna调控的USSC和ipUSSC神经元分化的分子网络。我们假设USSC神经元分化的限制是由于不受管制的检查点，这是一个不完全功能的分子参与者网络，可以通过与ipUSSC观察到的完整神经元分化进行比较来揭示。在确定相互作用的分子参与者后，有针对性的实验干预应该揭示与神经元分化相关的检查点的一般特征。在我们提出的方法的第一步，我们将生成USSC和ipUSSC部分和完全神经元分化的mRNA， microRNA和蛋白质的全面图像，以获得神经元分化过程中协调基因表达，转录后调控和翻译后过程的概述。最近，我们发现了在XXL-USSC中下调的18个microrna，主要是miR-17-92家族的成员，并通过实验验证了许多生物信息学预测的在神经元分化和相关生化途径中重要的靶基因。基于这些表达图，我们研究的核心部分旨在通过大量的生物信息学分析和候选microRNA的功能验证来确定USSC中不受管制的检查点。后者将通过对候选microRNA靶基因进行实验验证，然后使用microRNA模拟物、-抑制剂和sirna的混合物进行扰动分析，然后诱导分化来实现。而不是仅仅关注单一因素，小rna的混合允许更密切地模仿几种候选的真实表达变化模式。在蛋白质组分析的支持下，形态学和分子神经特异性读出将使我们能够测试候选基因的功能输入。这些分析将为分子网络和神经元分化检查点中的microrna提供新的功能见解，并为优先计划中的进一步研究确定起点。

MicroRNAs as important posttranscriptional regulators are essentially involved in the regulation of many biological processes. They play pivotal roles in the complex but yet poorly understood networks of molecular players controlling neuronal differentiation which involve precise coordination in the time course and level of expression. For their experimental interrogation stem cells have emerged as a valuable and promising tool.Unrestricted somatic stem cells from human cord blood (USSC) can be induced to limited neuronal differentiation by a cocktail of growth- and differentiation factors (XXL-USSC). In addition, they can be reprogrammed to induced pluripotent stem cells (ipUSSC) of full differentiation potential by ectopic retroviral expression of OCT4, SOX2, KLF4, and C-MYC. Here we aim to compare and functionally evaluate the microRNA-regulated molecular networks controlling neuronal differentiation of USSC and ipUSSC.We hypothesize that the limitations in neuronal differentiation of USSC are due to deregulated checkpoints, a not fully functional network of molecular players which can be revealed by comparison with the full neuronal differentiation observed with ipUSSC. Upon identification of interacting molecular players, a targeted experimental intervention should reveal a general signature of checkpoints relevant for neuronal differentiation.In the first step of our proposed approach, we will generate a comprehensive picture of mRNA, microRNA and protein in partial and complete neuronal differentiation of USSC and ipUSSC, in order to obtain an overview of coordinated gene expression, posttranscriptional regulation and posttranslational processes during neuronal differentiation. Recently, we identified 18 microRNAs, mainly members of the miR-17-92 family, that are downregulated in XXL-USSC and experimentally validated numerous bioinformatically predicted target genes important in neuronal differentiation and related biochemical pathways. Based on the expression pictures, the central part of our study aims to identify deregulated checkpoints in USSC by substantial bioinformatic analysis followed by functional validation of microRNA candidates. The latter will be achieved by experimental validation of candidate microRNA target genes followed by perturbation analysis using mixtures of microRNA-mimics, -inhibitors and siRNAs followed by induction to differentiation. Rather than solely focusing on single factors, mixes of small RNAs allow to more closely mimic patterns of real expression changes of several candidates. Morphological and molecular neuro-specific read-outs, supported by proteome analysis will allow us to test the functional input of candidates. These analyses will provide new functional insights into microRNAs in molecular networks and checkpoints of neuronal differentiation and define starting points for further investigations within the priority programme.