用于中枢神经系统疾病建模和高通量筛选的高度可扩展的人类iPS细胞衍生神经祖细胞(NPC)和神经元

Chialin Cheng, Daniel M. Fass, Kat Folz-Donahue, Marcy E. MacDonald, Stephen J. Haggarty
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引用次数: 34

摘要

人类体细胞重编程为诱导多能干细胞(iPS)极大地扩展了一套可用的研究工具,用于研究中枢神经系统(CNS)疾病的分子和细胞机制。实现iPS细胞技术在识别新的治疗靶点和高通量药物筛选方面的前景,需要实施大规模生产特定中枢神经系统细胞类型的方法。在这里,我们描述了一种生成稳定的,高度可扩展的,iPS细胞衍生的中枢神经系统神经祖细胞(NPC)的方案,使用多维荧光激活细胞分选(FACS)纯化由细胞表面标记物定义的NPC。此外,我们描述了一种快速、高效、可重复的方法,通过诱导表达前神经转录因子Neurogenin 2 (iNgn2-NPC),从这些NPC中产生兴奋性皮质样神经元。最后,我们描述了使用iNgn2-NPC探测人类神经可塑性的方法,以及使用高含量、单细胞水平的自动显微镜检测中枢神经系统疾病的机制。©2017 by John Wiley &儿子,Inc。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Highly Expandable Human iPS Cell–Derived Neural Progenitor Cells (NPC) and Neurons for Central Nervous System Disease Modeling and High-Throughput Screening

Reprogramming of human somatic cells into induced pluripotent stem (iPS) cells has greatly expanded the set of research tools available to investigate the molecular and cellular mechanisms underlying central nervous system (CNS) disorders. Realizing the promise of iPS cell technology for the identification of novel therapeutic targets and for high-throughput drug screening requires implementation of methods for the large-scale production of defined CNS cell types. Here we describe a protocol for generating stable, highly expandable, iPS cell–derived CNS neural progenitor cells (NPC) using multi-dimensional fluorescence activated cell sorting (FACS) to purify NPC defined by cell surface markers. In addition, we describe a rapid, efficient, and reproducible method for generating excitatory cortical-like neurons from these NPC through inducible expression of the pro-neural transcription factor Neurogenin 2 (iNgn2-NPC). Finally, we describe methodology for the use of iNgn2-NPC for probing human neuroplasticity and mechanisms underlying CNS disorders using high-content, single-cell-level automated microscopy assays. © 2017 by John Wiley & Sons, Inc.

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Current Protocols in Human Genetics
Current Protocols in Human Genetics Biochemistry, Genetics and Molecular Biology-Genetics
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期刊介绍: Current Protocols in Human Genetics is the resource for designing and running successful research projects in all branches of human genetics.
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