Integration of autopatching with automated pipette and cell detection in vitro.

Patch clamp is the main technique for measuring electrical properties of individual cells. Since its discovery in 1976 by Neher and Sakmann, patch clamp has been instrumental in broadening our understanding of the fundamental properties of ion channels and synapses in neurons. The conventional patch-clamp method requires manual, precise positioning of a glass micropipette against the cell membrane of a visually identified target neuron. Subsequently, a tight "gigaseal" connection between the pipette and the cell membrane is established, and suction is applied to establish the whole cell patch configuration to perform electrophysiological recordings. This procedure is repeated manually for each individual cell, making it labor intensive and time consuming. In this article we describe the development of a new automatic patch-clamp system for brain slices, which integrates all steps of the patch-clamp process: image acquisition through a microscope, computer vision-based identification of a patch pipette and fluorescently labeled neurons, micromanipulator control, and automated patching. We validated our system in brain slices from wild-type and transgenic mice expressing channelrhodopsin 2 under the Thy1 promoter (line 18) or injected with a herpes simplex virus-expressing archaerhodopsin, ArchT. Our computer vision-based algorithm makes the fluorescent cell detection and targeting user independent. Compared with manual patching, our system is superior in both success rate and average trial duration. It provides more reliable trial-to-trial control of the patching process and improves reproducibility of experiments.

[1]  E. Kandel,et al.  Neuroscience thinks big (and collaboratively) , 2013, Nature Reviews Neuroscience.

[2]  B Sakmann,et al.  Quantal analysis of inhibitory synaptic transmission in the dentate gyrus of rat hippocampal slices: a patch‐clamp study. , 1990, The Journal of physiology.

[3]  B. Sakmann,et al.  A new cellular mechanism for coupling inputs arriving at different cortical layers , 1999, Nature.

[4]  Hanchuan Peng,et al.  3D Image-Guided Automatic Pipette Positioning for Single Cell Experiments in vivo , 2015, Scientific Reports.

[5]  Henry Markram,et al.  A computer-assisted multi-electrode patch-clamp system. , 2013, Journal of visualized experiments : JoVE.

[6]  Paul S. Weiss,et al.  The Brain Activity Map , 2013, Science.

[7]  R. Nicoll,et al.  Comparison of two forms of long-term potentiation in single hippocampal neurons. , 1990, Science.

[8]  T. Insel,et al.  The NIH BRAIN Initiative , 2013, Science.

[9]  C. Petersen,et al.  The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex , 2009, Neuron.

[10]  Wolfgang Walz,et al.  Patch-clamp applications and protocols , 1995 .

[11]  G. Feng,et al.  Acute brain slice methods for adult and aging animals: application of targeted patch clamp analysis and optogenetics. , 2014, Methods in molecular biology.

[12]  Thomas K. Berger,et al.  A synaptic organizing principle for cortical neuronal groups , 2011, Proceedings of the National Academy of Sciences.

[13]  Y. Kubota,et al.  Correlation of physiological subgroupings of nonpyramidal cells with parvalbumin- and calbindinD28k-immunoreactive neurons in layer V of rat frontal cortex. , 1993, Journal of neurophysiology.

[14]  M. Bear,et al.  Visual Experience and Deprivation Bidirectionally Modify the Composition and Function of NMDA Receptors in Visual Cortex , 2001, Neuron.

[15]  W. Denk,et al.  Two-photon targeted patching (TPTP) in vivo , 2006, Nature Protocols.

[16]  E. Bamberg,et al.  Channelrhodopsin-2 is a leaky proton pump , 2009, Proceedings of the National Academy of Sciences.

[17]  Nico Stuurman,et al.  Computer Control of Microscopes Using µManager , 2010, Current protocols in molecular biology.

[18]  T Hoshi,et al.  Biophysical and molecular mechanisms of Shaker potassium channel inactivation , 1990, Science.

[19]  Suhasa B. Kodandaramaiah,et al.  Automated whole-cell patch clamp electrophysiology of neurons in vivo , 2012, Nature Methods.

[20]  D. Johnston,et al.  Induction of long-term potentiation at hippocampal mossy-fiber synapses follows a Hebbian rule. , 1990, Journal of neurophysiology.

[21]  Benjamin R. Arenkiel,et al.  In Vivo Light-Induced Activation of Neural Circuitry in Transgenic Mice Expressing Channelrhodopsin-2 , 2007, Neuron.

[22]  Daniel Johnston,et al.  MATLAB-based automated patch-clamp system for awake behaving mice. , 2015, Journal of neurophysiology.

[23]  Wolfgang Walz,et al.  Patch-Clamp Analysis , 2002, Neuromethods.

[24]  R. Nicoll,et al.  Comparison of two forms of long-term potentiation in single hippocampus neurons. Correction , 1991, Science.

[25]  E. Greisheimer,et al.  Physiology and Anatomy , 1934, The Indian Medical Gazette.

[26]  K. Deisseroth,et al.  Millisecond-timescale, genetically targeted optical control of neural activity , 2005, Nature Neuroscience.

[27]  N. Seidah,et al.  Regulation by gastric acid of the processing of progastrin‐derived peptides in rat antral mucosa , 1997, The Journal of physiology.

[28]  Xiaolong Jiang,et al.  An optogenetics- and imaging-assisted simultaneous multiple patch-clamp recording system for decoding complex neural circuits , 2015, Nature Protocols.

[29]  Vijay Iyer,et al.  Ephus: Multipurpose Data Acquisition Software for Neuroscience Experiments , 2010, Front. Neural Circuits.

[30]  H. Markram,et al.  Spontaneous and evoked synaptic rewiring in the neonatal neocortex , 2006, Proceedings of the National Academy of Sciences.

[31]  D. Clapham,et al.  Ion channels--basic science and clinical disease. , 1997, The New England journal of medicine.

[32]  R. Yuste,et al.  The Brain Activity Map Project and the Challenge of Functional Connectomics , 2012, Neuron.

[33]  B. Sakmann,et al.  Single-channel currents recorded from membrane of denervated frog muscle fibres , 1976, Nature.

[34]  F Guilak,et al.  A method for quantifying cell size from differential interference contrast images: validation and application to osmotically stressed chondrocytes , 2002, Journal of microscopy.

[35]  Jason Chung,et al.  Long-term channelrhodopsin-2 (ChR2) expression can induce abnormal axonal morphology and targeting in cerebral cortex , 2013, Front. Neural Circuits.

[36]  R. C. Gerkin,et al.  Brain-wide analysis of electrophysiological diversity yields novel categorization of mammalian neuron types. , 2015, Journal of neurophysiology.

[37]  Paul B. Manis,et al.  ACQ4: an open-source software platform for data acquisition and analysis in neurophysiology research , 2014, Front. Neuroinform..

[38]  K. Svoboda,et al.  Channelrhodopsin-2–assisted circuit mapping of long-range callosal projections , 2007, Nature Neuroscience.

[39]  H. Markram,et al.  Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. , 1997, The Journal of physiology.

[40]  John Y. Lin,et al.  A user's guide to channelrhodopsin variants: features, limitations and future developments , 2011, Experimental physiology.

[41]  Alexander S. Ecker,et al.  Principles of connectivity among morphologically defined cell types in adult neocortex , 2015, Science.

[42]  Wolfgang Walz,et al.  Patch-clamp analysis : advanced techniques , 2002 .