Abstract
Since its development in the late 70s and early 80s by Nobel laureates Erwin Neher and Bert Sakmann [1], patch clamping has been the gold standard single-cell electrophysiology technique. With the highest temporal and spatial resolution achievable by any recording technology, patch clamping has expanded from its inception of studying frog muscle fibers to studying intracellular synaptic computations within single neurons. Beyond single-cell electrophysiology, intracellular access via whole-cell patch clamping allows the harvesting of cell cytosol for transcriptomic profiling [2] and the infusion of dyes for visualizing morphology of the cells being recorded. Thus, electrophysiological information ofthe cell can be integrated with genetic and morphological characteristics, providing a comprehensive characterization of the cell. Patch clamping is, however, a delicate process, requiring considerable practice, experience and skill to manipulate a glass micropipette, carefully place it in physical contact with a cell, andmodulate the internal pressure to achieve a gigaohm seal. Consequently, despite its many advantages, patch clamping is a relatively low throughput and laborious process as compared with other electrophysiology techniques. Until recently, this has precluded the application of patch clamping for high-throughput analysis.
Original language | English (US) |
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Pages (from-to) | 3-6 |
Number of pages | 3 |
Journal | Bioelectronics in Medicine |
DOIs | |
State | Published - Sep 17 2020 |
Keywords
- Automation
- computer vision
- Electrophysiology
- Patch-clamping
- Robotics
- Single cells