CellSpecks: A Software for Automated Detection and Analysis of Calcium Channels in Live Cells

Syed Islamuddin Shah, Martin Smith, Divya Swaminathan, Ian Parker, G. Ullah, A. Demuro
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引用次数: 5

Abstract

To couple the fidelity of patch-clamp recording with a more high-throughput screening capability, we pioneered a novel approach to single channel recording that we named “optical patch clamp”. By using highly-sensitive fluorescent Ca2+ indicator dyes in conjunction with total internal fluorescence microscopy techniques, we monitor Ca2+ flux through individual Ca2+-permeable channels. This approach provides information about channel gating analogous to patch-clamp recording at time resolution of ~ 2 ms, with the additional advantage of being massively parallel, providing simultaneous and independent recording from thousands of channels in native environment. However, manual analysis of the data generated by this technique presents severe challenges as a video recording can include many thousands of frames. To overcome this bottleneck, we developed an image processing and analysis framework called CellSpecks, capable of detecting and fully analyzing the kinetics of ion channels within a video sequence. By using a randomly generated synthetic data, we tested the ability of CellSpecks to rapidly and efficiently detect and analyze the activity of thousands of ion channels, including openings for a few milliseconds. Here, we report the use of CellSpecks for the analysis of experimental data acquired by imaging muscle nicotinic acetylcholine receptors and the Alzheimer’s disease-associated amyloid beta pores with multiconductance levels in the plasma membrane of Xenopus laevis oocytes. We show that CellSpecks can accurately and efficiently generate location maps, create raw and processed fluorescence time-traces, histograms of mean open times, mean close times, open probabilities, durations, and maximum amplitudes, and a ‘channel chip’ showing the activity of all channels as a function of time. Although we specifically illustrate the application of CellSpecks for analyzing data from Ca2+ channels, it can be easily customized to analyze other spatially and temporally localized signals.
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CellSpecks:活细胞中钙通道的自动检测和分析软件
为了将膜片钳记录的保真度与更高通量的筛选能力相结合,我们开创了一种新的单通道记录方法,我们将其命名为“光学膜片钳”。通过使用高灵敏度的荧光Ca2+指示染料与总内部荧光显微镜技术相结合,我们监测Ca2+通量通过单个Ca2+可渗透通道。这种方法提供了类似于膜片钳记录的通道门控信息,时间分辨率约为2ms,具有大规模并行的额外优势,可以在本地环境中同时提供数千个通道的独立记录。然而,手工分析由这种技术产生的数据提出了严峻的挑战,因为视频记录可以包括数千帧。为了克服这一瓶颈,我们开发了一种称为CellSpecks的图像处理和分析框架,能够检测和全面分析视频序列中离子通道的动力学。通过使用随机生成的合成数据,我们测试了CellSpecks快速有效地检测和分析数千个离子通道活动的能力,包括几毫秒的开口。在这里,我们报告了使用CellSpecks来分析通过成像肌肉尼古丁乙酰胆碱受体和非洲爪蟾卵母细胞质膜中具有多导水平的阿尔茨海默病相关淀粉样蛋白β孔获得的实验数据。我们表明,CellSpecks可以准确有效地生成位置地图,创建原始和处理过的荧光时间轨迹,平均打开时间,平均关闭时间,打开概率,持续时间和最大幅度的直方图,以及显示所有通道活动作为时间函数的“通道芯片”。虽然我们特别说明了CellSpecks用于分析Ca2+通道数据的应用,但它可以很容易地定制来分析其他空间和时间上的局部信号。
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