McCready Fraser P, Gordillo-Sampedro Sara, Pradeepan Kartik, Martinez-Trujillo Julio, Ellis James
Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada.
Developmental & Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada.
Biology (Basel). 2022 Feb 16;11(2):316. doi: 10.3390/biology11020316.
In vitro multielectrode array (MEA) systems are increasingly used as higher-throughput platforms for functional phenotyping studies of neurons in induced pluripotent stem cell (iPSC) disease models. While MEA systems generate large amounts of spatiotemporal activity data from networks of iPSC-derived neurons, the downstream analysis and interpretation of such high-dimensional data often pose a significant challenge to researchers. In this review, we examine how MEA technology is currently deployed in iPSC modeling studies of neurodevelopmental disorders. We first highlight the strengths of in vitro MEA technology by reviewing the history of its development and the original scientific questions MEAs were intended to answer. Methods of generating patient iPSC-derived neurons and astrocytes for MEA co-cultures are summarized. We then discuss challenges associated with MEA data analysis in a disease modeling context, and present novel computational methods used to better interpret network phenotyping data. We end by suggesting best practices for presenting MEA data in research publications, and propose that the creation of a public MEA data repository to enable collaborative data sharing would be of great benefit to the iPSC disease modeling community.
体外多电极阵列（MEA）系统越来越多地被用作诱导多能干细胞（iPSC）疾病模型中神经元功能表型研究的高通量平台。虽然MEA系统能从iPSC衍生的神经元网络中生成大量时空活动数据，但对这些高维数据的下游分析和解读往往给研究人员带来重大挑战。在本综述中，我们探讨了MEA技术目前在神经发育障碍的iPSC建模研究中的应用方式。我们首先通过回顾其发展历程以及MEA旨在回答的原始科学问题，突出体外MEA技术的优势。总结了用于MEA共培养的患者iPSC衍生神经元和星形胶质细胞的生成方法。然后，我们讨论了疾病建模背景下与MEA数据分析相关的挑战，并介绍了用于更好地解读网络表型数据的新型计算方法。最后，我们提出在研究出版物中呈现MEA数据的最佳实践建议，并提议创建一个公共MEA数据存储库以实现协作数据共享，这将对iPSC疾病建模领域大有裨益。
