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主要挑战是当前研究该疾病的模型的局限性。肌张力障碍通常被认为是控制运动的大脑区域内神经元的慢性信号功能障碍，尽管在分子水平上表征这些细胞中与肌张力障碍相关的细微紊乱一直很困难。传统的疾病建模方法依赖于(1)患者周围细胞（成纤维细胞或淋巴细胞）；(2)突变小鼠；和/或(3)在与疾病过程有关的蛋白质中进行操纵的培养细胞。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（iPSCs）已成为一种越来越普遍的模拟中枢神经系统疾病的方法。然而，随着时间的推移，已经清楚的是，多能干细胞可以显示出大量的个体间变异性，这可能会混淆疾病特异性表型的鉴定。在这里，我们提出了一种开发新的DYT1肌张力障碍人类神经元培养模型的策略，该模型结合了iPSCs重编程和转录激活因子样效应核酸酶（TALENs）的基因靶向。通过使用工程TALENs来纠正患者iPSCs中的DYT1基因突变，我们将从相同的表观遗传背景中产生匹配的等基因控制系。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，以确定与匹配的对照细胞相比，DYT1 ipsc衍生神经元中受到干扰的功能网络。这项工作的结果将为探索DYT1肌张力障碍中神经元特异性缺陷提供强大的新资源，详细的表达谱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.