Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology

Summary Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed “blind,” meaning that throughput for sampling some genetically or morphologically defined cell types is unacceptably low. One solution to this problem is to use two-photon microscopy to target fluorescently labeled neurons. Combining this with robotic automation is difficult, however, as micropipette penetration induces tissue deformation, moving target cells from their initial location. Here we describe a platform for automated two-photon targeted patch-clamp recording, which solves this problem by making use of a closed loop visual servo algorithm. Our system keeps the target cell in focus while iteratively adjusting the pipette approach trajectory to compensate for tissue motion. We demonstrate platform validation with patch-clamp recordings from a variety of cells in the mouse neocortex and cerebellum.

[1]  F. A. Edwards,et al.  A thin slice preparation for patch clamp recordings from neurones of the mammalian central nervous system , 1989, Pflügers Archiv.

[2]  T. Kaneko,et al.  Green fluorescent protein expression and colocalization with calretinin, parvalbumin, and somatostatin in the GAD67‐GFP knock‐in mouse , 2003, The Journal of comparative neurology.

[3]  B. Sakmann,et al.  In vivo, low-resistance, whole-cell recordings from neurons in the anaesthetized and awake mammalian brain , 2002, Pflügers Archiv.

[4]  Andreas T Schaefer,et al.  Transfection via whole-cell recording in vivo: bridging single-cell physiology, genetics and connectomics , 2011, Nature Neuroscience.

[5]  W. Denk,et al.  Targeted patch-clamp recordings and single-cell electroporation of unlabeled neurons in vivo , 2008, Nature Methods.

[6]  Carlos Portera-Cailliau,et al.  In vivo 2-photon calcium imaging in layer 2/3 of mice. , 2008, Journal of visualized experiments : JoVE.

[7]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[8]  Craig R. Forest,et al.  An Instrument for Controlled, Automated Production of Micrometer Scale Fused Silica Pipettes , 2011 .

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

[10]  Arnold R. Kriegstein,et al.  Whole cell recording from neurons in slices of reptilian and mammalian cerebral cortex , 1989, Journal of Neuroscience Methods.

[11]  W. Denk,et al.  Lentivirus-based genetic manipulations of cortical neurons and their optical and electrophysiological monitoring in vivo , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[12]  Lynne E Bilston,et al.  Rheological properties of the tissues of the central nervous system: a review. , 2008, Medical engineering & physics.

[13]  Igor L. Medintz,et al.  Quantum dot-based multiphoton fluorescent pipettes for targeted neuronal electrophysiology , 2014, Nature Methods.

[14]  D. Ferster,et al.  EPSP-IPSP interactions in cat visual cortex studied with in vivo whole- cell patch recording , 1992, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[15]  F. Helmchen,et al.  Sulforhodamine 101 as a specific marker of astroglia in the neocortex in vivo , 2004, Nature Methods.

[16]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

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

[18]  Winfried Denk,et al.  Targeted Whole-Cell Recordings in the Mammalian Brain In Vivo , 2003, Neuron.

[19]  Robert H Blick,et al.  Whole cell patch clamp recording performed on a planar glass chip. , 2002, Biophysical journal.

[20]  M. Häusser,et al.  Spatial Pattern Coding of Sensory Information by Climbing Fiber-Evoked Calcium Signals in Networks of Neighboring Cerebellar Purkinje Cells , 2009, The Journal of Neuroscience.

[21]  B. Sakmann,et al.  Improved patch-clamp techniques for high-resolution current recording from cells and cell-free membrane patches , 1981, Pflügers Archiv.

[22]  J. Kauer,et al.  Whole-Cell Patch-Clamp Recording Reveals Subthreshold Sound-Evoked Postsynaptic Currents in the Inferior Colliculus of Awake Bats , 1996, The Journal of Neuroscience.

[23]  C. Stosiek,et al.  In vivo two-photon calcium imaging of neuronal networks , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[24]  O D Creutzfeldt,et al.  Whole cell recording and conductance measurements in cat visual cortex in-vivo. , 1991, Neuroreport.

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

[26]  Andrew Blake,et al.  Articulated body motion capture by annealed particle filtering , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[27]  Yuan Li,et al.  Tracking in Low Frame Rate Video: A Cascade Particle Filter with Discriminative Observers of Different Lifespans , 2007, CVPR.

[28]  M B Jackson,et al.  Single‐Channel Recording , 1998, Current protocols in neuroscience.

[29]  Michael R DeWeese,et al.  Whole-cell recording in vivo. , 2007, Current protocols in neuroscience.

[30]  B. Sakmann,et al.  Patch-clamp recordings from the soma and dendrites of neurons in brain slices using infrared video microscopy , 1993, Pflügers Archiv.

[31]  W. Denk,et al.  Two-photon laser scanning fluorescence microscopy. , 1990, Science.

[32]  M. Garcia-Parajo,et al.  A review of progress in single particle tracking: from methods to biophysical insights , 2015, Reports on progress in physics. Physical Society.

[33]  N. Otsu A threshold selection method from gray level histograms , 1979 .