Wu Qiuyu, Chubykin Alexander A
Department of Biological Sciences, Purdue University; Purdue Institute for Integrative Neuroscience, Purdue University.
Department of Biological Sciences, Purdue University; Purdue Institute for Integrative Neuroscience, Purdue University;
J Vis Exp. 2017 Jul 31(125):56010. doi: 10.3791/56010.
Whole-cell patch clamp is the gold-standard method to measure the electrical properties of single cells. However, the in vitro patch clamp remains a challenging and low-throughput technique due to its complexity and high reliance on user operation and control. This manuscript demonstrates an image-guided automatic patch clamp system for in vitro whole-cell patch clamp experiments in acute brain slices. Our system implements a computer vision-based algorithm to detect fluorescently labeled cells and to target them for fully automatic patching using a micromanipulator and internal pipette pressure control. The entire process is highly automated, with minimal requirements for human intervention. Real-time experimental information, including electrical resistance and internal pipette pressure, are documented electronically for future analysis and for optimization to different cell types. Although our system is described in the context of acute brain slice recordings, it can also be applied to the automated image-guided patch clamp of dissociated neurons, organotypic slice cultures, and other non-neuronal cell types.
全细胞膜片钳是测量单细胞电学特性的金标准方法。然而,体外膜片钳技术由于其复杂性以及对用户操作和控制的高度依赖性,仍然是一项具有挑战性且通量较低的技术。本论文展示了一种用于急性脑片体外全细胞膜片钳实验的图像引导自动膜片钳系统。我们的系统实现了一种基于计算机视觉的算法,用于检测荧光标记的细胞,并使用微操纵器和内部移液器压力控制对其进行全自动封接。整个过程高度自动化,对人工干预的需求极小。包括电阻和内部移液器压力在内的实时实验信息以电子方式记录下来,以供未来分析以及针对不同细胞类型进行优化。尽管我们的系统是在急性脑片记录的背景下进行描述的,但它也可应用于解离神经元、器官型切片培养物以及其他非神经元细胞类型的自动图像引导膜片钳实验。