Mapping spatial organization of in vitro neuronal networks using high-content imaging

利用高内涵成像技术绘制体外神经元网络的空间组织结构图

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Abstract

Neuronal network formation is an intricate process by which individual neurons connect into a functional circuitry. At the subcellular level, neuronal connectivity is characterized by the number, size and strength of synapses. At the cellular level, in vitro network characterization remains a challenge due to the large number of neurons involved, spreading widely across a culture dish. Here, we demonstrate a pipeline using high-content confocal microscopy and automated image analysis to study spatial organization of individual neurons in an in vitro cellular network. With this approach, we enable analysis of thousands of neurons in one well, and of multiple wells simultaneously. Using this workflow, we compared the spatial organization of primary mouse neuronal networks derived from the hippocampus, cortex and cerebellum. We also demonstrate how to extract morphological details, such as size of the nucleus and axon initial segment number, orientation and length from our data. This workflow can be applied to study underlying molecular mechanisms of circuitry formation, to assess network formation of neurons derived from mouse or human iPSC models for neurological diseases, and serve as a future platform for drug development.

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