Generation of DYT1 dystonia-specific iPS cells with isogenic controls

描述（由申请人提供）：理解和治疗肌张力障碍的一个主要挑战是目前研究该疾病的模型的局限性。肌张力障碍通常被认为代表控制运动的脑区域内的神经元中的慢性信号传导功能障碍，尽管在分子水平上表征这些细胞中的微妙的肌张力障碍相关的干扰是困难的。对该病症进行建模的传统方法依赖于（1）外周患者细胞（成纤维细胞或成淋巴细胞）;（2）突变小鼠;和/或（3）携带在疾病过程中涉及的蛋白质中的操纵的培养细胞。虽然这些策略有价值，但它们所能揭示的肌张力障碍相关基因突变对人类神经元的影响是有限的。将患者体细胞重编程为可分化为神经元的诱导多能干细胞（iPSC）已成为建模CNS疾病的越来越常见的方法。然而，随着时间的推移，已经清楚的是，iPSC可以显示出大量的个体间变异性，这可能混淆疾病特异性表型的鉴定。在这里，我们提出了一种策略，开发一种新的DYT 1肌张力障碍的人类神经元培养模型，该模型将iPSC重编程与使用转录激活因子样效应核酸酶（TALEN）的基因靶向相结合。通过使用工程化的TALEN来校正患者iPSC中的DYT 1基因突变，我们将从相同的表观遗传背景产生匹配的同基因对照系。作为该模型的第一个应用，我们将通过通路分析进行转录谱分析，以识别与匹配的对照细胞相比在DYT 1 iPSC衍生的神经元中受到干扰的功能网络。这项工作的结果将是一个强大的新资源，用于探测DYT 1肌张力障碍的神经元特异性缺陷，详细的表达谱分析将为该模型系统的未来研究提供信息。

DESCRIPTION (provided by applicant): A major challenge in understanding and treating dystonia is the limitation of current models for studying the disease. The dystonias are generally believed to represent chronic signaling dysfunctions in neurons within brain regions controlling movement, although characterizing subtle, dystonia-related disturbances in these cells at the molecular level has been difficult. Traditional approaches to model the disorder have relied on (1) peripheral patient cells (fibroblasts or lymphoblasts); (2) mutant mice; and/or (3) cultured cells bearing manipulations in proteins implicated in the disease process. While these strategies have value, there are limits to what they can reveal about effects of dystonia-related gene mutations on human neurons. Reprogramming patient somatic cells to induced pluripotent stem cells (iPSCs) which can be differentiated into neurons has become an increasingly common approach to modeling CNS disorders. Yet over time it has become clear that iPSCs can display substantial inter-individual variability which may confound identification of disease-specific phenotypes. Here we propose a strategy to develop a new human neuronal culture model of DYT1 dystonia that combines iPSCs reprogramming with gene targeting using transcription activator-like effector nucleases (TALENs). By using engineered TALENs to correct the DYT1 gene mutation in patient iPSCs, we will generate matched isogenic control lines from the same epigenetic background. As a first application of this model, we will perform transcriptional profiling with pathway analyses to identify functional networks that are perturbed in DYT1 iPSC-derived neurons compared to matched control cells. The outcome of this work will be a powerful new resource for probing neuron-specific deficits in DYT1 dystonia, with detailed expression profiling that will inform future studies of this model system.