Mechanisms of Neural Stem Cell Mechanoregulation

描述(申请人提供)：干细胞自我更新和分化的过程在很大程度上受到特殊的生态位、结构复杂的微环境的调控，这些微环境为其常驻干细胞提供了大量的信号，形式包括来自邻近细胞的可溶性因子、细胞外基质(ECM)和旁分泌因子。例如，在成年哺乳动物的大脑中，海马区的神经干细胞(NSCs)不断分裂，产生新的神经元，这些神经元在学习和记忆中发挥作用，这些细胞受到来自邻近星形胶质细胞的生长因子、形态原、细胞外基质和旁分泌信号的调节。通过更深入地了解这些利基调控干细胞的机制，可以帮助开发体外生物材料培养系统，用于在转化医学应用中扩增和分化干细胞。现在人们普遍认识到，除了其生化特性外，利基的机械特性(例如，硬度)也可以有力地调节干细胞的行为，事实上，我们最近证明了这一点对神经干细胞是正确的。然而，总的来说，该领域缺乏关于干细胞如何在细胞-ECM界面处理这种机械信号以引起细胞命运变化的关键分子和机制信息，这些机械转导信号如何与传统上被认为控制神经发生等过程的转录事件相互作用，以及机械转导信号是否也可以控制体内的神经发生。在这项提案中，我们将解决所有这些悬而未决的问题。目的1研究细胞黏附受体和细胞骨架的机械转导动力学。具体地说，我们将进行生物物理和生化测量，以分析在细胞命运决定时，来自细胞微环境的机械信息是如何通过细胞-包括黏附受体、焦点黏附蛋白和非肌肉肌球蛋白II-传播的。此外，Aim 2将研究底物硬度如何影响神经D的激活，以控制神经元分化。我们将通过量化编码关键的原神经转录因子的基因接收和整合上游机械信号的动力学来实现这一点，因为细胞致力于神经元的命运。在这一目标上的一个创新工具，在这个修订的应用中是新的，i使用合成的ECM，其硬度可以动态和可逆地切换。这一修订后的应用还包括了新的数据，证明了我们通过在大鼠模型中通过遗传操作机械传导信号来控制体内神经发生的能力。因此，在这两个目标中，我们将利用这一能力来确定在体外参与机械敏感命运选择的信号效应器是否也在体内调节这一过程。综上所述，这项建议融合了干细胞生物学、机械生物学和材料合成，以发展对干细胞机械调节的定量、机械性见解，对基础干细胞生物学和再生医学先进生物材料系统的未来发展具有重要意义。

DESCRIPTION (provided by applicant): The processes of stem cell self-renewal and differentiation are regulated in large part by specialized niches, structurally complex microenvironments that present their resident stem cells with numerous cues in the form of soluble factors, extracellular matrix (ECM), and juxtacrine factors from neighboring cells. Within the adult mammalian brain, for example, neural stem cells (NSCs) in the hippocampus continuously divide to give rise to new neurons that play roles in learning and memory, and these cells are regulated by growth factors, morphogens, ECM, and juxtacrine signals from neighboring astrocytes. Gaining deeper insights into the mechanisms through which these niches regulate stem cells can aid in the development of in vitro biomaterials culture systems for expanding and differentiating stem cells in translational medicine applications. It is now widely appreciated that in addition to its biochemical properties, the mechanical properties of the niche (e.g., stiffness) can also powerfully regulate stem cell behavior, and indeed we recently showed that this true of NSCs. However, in general the field lacks key molecular and mechanistic information about how stem cells process such mechanical cues at the cell-ECM interface to give rise to changes in cell fate, how these mechanotransductive signals interface with transcriptional events traditionally understood to control processes such as neurogenesis, and whether mechanotransductive signaling can also control neurogenesis in vivo. In this proposal we will address all of these open questions. Aim 1 will investigate the dynamics of mechanotransduction to cellular adhesion receptors and the cytoskeleton. Specifically, we will conduct biophysical and biochemical measurements to analyze how mechanical information from the cellular microenvironment is propagated through cells - including adhesion receptors, focal adhesion proteins, and nonmuscle myosin II - as cell fate decisions are made. In addition, Aim 2 will investigate how substrate stiffness impacts the activation of NeuroD to control neuronal differentiation. We will do this by quantifying the dynamics by which the gene encoding a key proneural transcription factor receives and integrates upstream mechanical signals as cells commit to a neuronal fate. An innovative tool in this aim, new to this revised application, i the use of synthetic ECMs whose stiffness may be dynamically and reversibly switched. This revised application also includes new data demonstrating our ability to control neurogenesis in vivo by genetically manipulating mechanotransductive signals in a rat model. Thus, in both aims we will apply this capability to determine whether signaling effectors implicated in mechanosensitive fate choice in vitro also regulate this process in vivo. In summary, this proposal blends stem cell biology, mechanobiology, and materials synthesis to develop quantitative, mechanistic insights into stem cell mechanoregulation, with implications for both basic stem cell biology and the future development of advanced biomaterials systems for regenerative medicine.