Name: application of automated image-guided patch clamp for the study of neurons in brain slices
Uploaded: 2017-07-31T14:00:00
Description: Watch this Scientific Journal Video about Application of Automated Image-guided Patch Clamp for the Study of Neurons in Brain Slices Video at JoVE.com

We are grateful for the financial support from the Whitehall Foundation. We would like to thank Samuel T. Kissinger for the valuable comments.

1. System Setup
<ol>
	<li>Construct the pressure control unit.
	<ol>
		<li>Assemble the pressure control unit according to the circuit map (Figure 1). Solder the necessary parts onto the Printed Circuit Board (PCB) manufactured according to the electrical circuit schematics (Figure 1b). Use standard resistors, LEDs, Metal-Oxide Semiconductor Field-Eeffect Transistors (MOSFETs), capacitors, and connectors (see the Table of Materials). Solder so...

<ol>
	<li>Sakmann, B., Neher, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patch+clamp+techniques+for+studying+ionic+channels+in+excitable+membranes.">Patch clamp techniques for studying ionic channels in excitable membranes.</a> Annu Rev Physiol. 46, 455-472 (1984).</li><li>Collins, M. D., Gordon, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Giant+liposome+preparation+for+imaging+and+patch-clamp+electrophysiology.">Giant liposome preparation for imaging and patch-clamp electrophysiology.</a> J Vis Exp. (76), (2013).</li><li>Kodandaramaiah, S. B., Franzesi, G. T., Chow, B. Y., Boyden, E. S., Forest, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+whole-cell+patch-clamp+electrophysiology+of+neurons+in+vivo.">Automated whole-cell patch-clamp electrophysiology of neurons in vivo.</a> Nat Methods. 9 (6), 585-587 (2012).</li><li>Desai, N. S., Siegel, J. J., Taylor, W., Chitwood, R. A., Johnston, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MATLAB-based+automated+patch-clamp+system+for+awake+behaving+mice.">MATLAB-based automated patch-clamp system for awake behaving mice.</a> J Neurophysiol. 114 (2), 1331-1345 (2015).</li><li>Kodandaramaiah, S. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Assembly+and+operation+of+the+autopatcher+for+automated+intracellular+neural+recording+in+vivo.">Assembly and operation of the autopatcher for automated intracellular neural recording in vivo.</a> Nat Protocols. 11 (4), 634-654 (2016).</li><li>Wu, Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integration+of+autopatching+with+automated+pipette+and+cell+detection+in+vitro.">Integration of autopatching with automated pipette and cell detection in vitro.</a> J Neurophysiol. 116 (4), 1564-1578 (2016).</li><li>Perin, R., Markram, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+computer-assisted+multi-electrode+patch-clamp+system.">A computer-assisted multi-electrode patch-clamp system.</a> J Vis Exp. (80), e50630 (2013).</li><li>Fertig, N., Blick, R. H., Behrends, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole+cell+patch+clamp+recording+performed+on+a+planar+glass+chip.">Whole cell patch clamp recording performed on a planar glass chip.</a> Biophys J. 82 (6), 3056-3062 (2002).</li><li>Brown, A. L., Johnson, B. E., Goodman, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Making+patch-pipettes+and+sharp+electrodes+with+a+programmable+puller.">Making patch-pipettes and sharp electrodes with a programmable puller.</a> J Vis Exp. (20), (2008).</li><li>Segev, A., Garcia-Oscos, F., Kourrich, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-cell+Patch-clamp+Recordings+in+Brain+Slices.">Whole-cell Patch-clamp Recordings in Brain Slices.</a> J Vis Exp. (112), (2016).</li><li>Campagnola, L., Kratz, M. B., Manis, P. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ACQ4:+an+open-source+software+platform+for+data+acquisition+and+analysis+in+neurophysiology+research.">ACQ4: an open-source software platform for data acquisition and analysis in neurophysiology research.</a> Front Neuroinform. 8 (3), (2014).</li><li>Kolb, I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cleaning+patch-clamp+pipettes+for+immediate+reuse.">Cleaning patch-clamp pipettes for immediate reuse.</a> Sci Rep. 6, (2016).</li></ol>

Here, we describe a method for automatic image-guided patch clamp recordings in vitro. The key steps in this process are summarized as follows. First, computer vision is used to automatically recognize the pipette tip using a series of images acquired via a microscope. This information is then used to calculate the coordinate transformation function between the microscope and the manipulator coordinate systems. Computer vision is used to automatically detect fluorescently labeled cells and to identify their coor...

The patch clamp technique was first developed by Neher and Sakmann in the 1970s to study the ionic channels of excitable membranes1. Since then, patch clamping has been applied to the study of many different subjects at the cellular, synaptic, and circuit level&#8212;both in vitro and in vivo&#8212;in many different cell types, including neurons, cardiomyocytes, Xenopus oocytes, and artificial liposomes2. This process involves the correct identification and targeting of a cell of interest, intricate micromanipulator control to move the patch pipette in close proximity to the cell, the application of positive and negative pressure to the pipette at the proper time to establish a tight gigaseal patch, and a break-in to establish a whole-cell patch configuration. Patch clamping is typically conducted manually and requires extensive training to master. Even for a researcher experienced with the patch clamp, the success rate is relatively low. More recently, several attempts have been made to automate patch-clamp experiments. Two main strategies have evolved to accomplish automation: augmenting standard patch clamp equipment to provide automatic control of the patching process and the design of new equipment and techniques from the ground up. The former strategy is adaptable to existing hardware and can be used in a variety of patch clamp applications, including in vivo blind patch clamp3,4,5, in vitro patch clamp of acute brain slices, organotypic slice cultures, and cultured dissociated neurons6. It enables the interrogation of complex local circuits by using multiple micromanipulators simultaneously7. The planar patch method is an example of the new development strategy, which can achieve the high-throughput simultaneous patch clamp of cells in suspension for drug screening purposes8. However, the planar patch method is not applicable to all cell types, particularly neurons with long processes or intact circuits containing extensive connections. This limits its application to mapping the intricate circuitry of the nervous system, which is a key advantage of traditional patch clamp technology.
We have developed a system that automates the manual patch clamp process in vitro by augmenting standard patch clamp hardware. Our system, Autopatcher IG, provides automatic pipette calibration, fluorescent cell target identification, automatic control of pipette movement, automatic whole-cell patching, and data logging. The system can automatically acquire multiple images of brain slices at different depths; analyze them using computer vision; and extract information, including the coordinates of fluorescently labeled cells. This information can then be used to target and automatically patch cells of interest. The software is written in Python&#8212;a free, open-source programming language&#8212;using several open-source libraries. This ensures its accessibility to other researchers and improves the reproducibility and rigor of electrophysiology experiments. The system has a modular design, such that additional hardware can easily be interfaced with the current system demonstrated here.

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			<td style="width:256px;">Include microscope and manipulators. The manufacturer provided manipulator control software demonstrated in this manuscript is &#8220;Linlab2&#8221;.</td>
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			<td style="width:147px;">version 2.7 (32-bit for windows)</td>
			<td style="width:256px;">https://www.continuum.io/downloads</td>
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application of automated image-guided patch clamp for the study of neurons in brain slices

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.

Our system has been tested on its ability to patch cells in acute brain slices, mouse induced Pluripotent Stem Cells (iPSCs) differentiated into neurons, and HEK 293 cells artificially expressing channels of interest. Figure 3 shows an experiment using Thy1-ChR2-YFP transgenic mice (B6.Cg-Tg(Thy1-COP4/EYFP)18Gfng/J) targeting fluorescently labeled layer 5 pyramidal neurons in the visual cortex. The target cell was one of the automatically identified green flu...

Watch this Scientific Journal Video about Application of Automated Image-guided Patch Clamp for the Study of Neurons in Brain Slices Video at JoVE.com

Application of Automated Image-guided Patch Clamp for the Study of Neurons in Brain Slices Video (Video) | JoVE

This protocol describes how to conduct automatic image-guided patch-clamp experiments using a system recently developed for standard in vitro electrophysiology equipment.

Application of Automated Image-guided Patch Clamp for the Study of Neurons in Brain Slices

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 ...

Research

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