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基于神经元的基因编码钙指示剂优化筛选平台。

A neuron-based screening platform for optimizing genetically-encoded calcium indicators.

机构信息

Genetically-Encoded Neuronal Indicator and Effector Project, Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, United States of America.

出版信息

PLoS One. 2013 Oct 14;8(10):e77728. doi: 10.1371/journal.pone.0077728. eCollection 2013.

Abstract

Fluorescent protein-based sensors for detecting neuronal activity have been developed largely based on non-neuronal screening systems. However, the dynamics of neuronal state variables (e.g., voltage, calcium, etc.) are typically very rapid compared to those of non-excitable cells. We developed an electrical stimulation and fluorescence imaging platform based on dissociated rat primary neuronal cultures. We describe its use in testing genetically-encoded calcium indicators (GECIs). Efficient neuronal GECI expression was achieved using lentiviruses containing a neuronal-selective gene promoter. Action potentials (APs) and thus neuronal calcium levels were quantitatively controlled by electrical field stimulation, and fluorescence images were recorded. Images were segmented to extract fluorescence signals corresponding to individual GECI-expressing neurons, which improved sensitivity over full-field measurements. We demonstrate the superiority of screening GECIs in neurons compared with solution measurements. Neuronal screening was useful for efficient identification of variants with both improved response kinetics and high signal amplitudes. This platform can be used to screen many types of sensors with cellular resolution under realistic conditions where neuronal state variables are in relevant ranges with respect to timing and amplitude.

摘要

基于荧光蛋白的神经元活动检测传感器主要是基于非神经元筛选系统开发的。然而,与非兴奋细胞相比,神经元状态变量(如电压、钙等)的动力学通常非常迅速。我们开发了一种基于分离的大鼠原代神经元培养物的电刺激和荧光成像平台。我们描述了其在测试基因编码钙指示剂(GECIs)中的应用。使用含有神经元选择性基因启动子的慢病毒可以有效地表达神经元 GECI。通过电场刺激定量控制动作电位(APs),从而控制神经元钙水平,并记录荧光图像。对图像进行分割,以提取对应于单个 GECI 表达神经元的荧光信号,这比全场测量提高了灵敏度。我们证明了在神经元中筛选 GECIs 比在溶液中测量具有优越性。神经元筛选对于有效识别具有改善的响应动力学和高信号幅度的变体非常有用。该平台可用于在与神经元状态变量在时间和幅度上相关的实际条件下,以细胞分辨率筛选多种类型的传感器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1051/3796516/a762f0fa3783/pone.0077728.g001.jpg

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