PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices (bibtex)
by , , , , , , , , , and
Abstract:
Objective: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we demonstrate a robotic "PatcherBot" system that can perform many patch-clamp recordings sequentially, fully unattended. Approach: comprehensive automation is accomplished by outfitting the robot with machine vision, and cleaning pipettes instead of manually exchanging them. Main results: the PatcherBot can obtain data at a rate exceeding human capability (up to 16 cells per hour) and work with no human intervention for up to 3 hours. We demonstrate the broad applicability and scalability of this system by performing hundreds of recordings in tissue culture cells and mouse brain slices with no human supervision. Using the PatcherBot, we also discovered that pipette cleaning can be improved by a factor of three. Significance: The system is potentially transformative for applications that depend on many high-quality measurements of single cells, such as drug screening, protein functional characterization, and multimodal cell type investigations.
Reference:
PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slicesI. Kolb, C. Landry, M. Yip, C. Lewallen, W. Stoy, J. Lee, A. Felouzis, B. Yang, E.S. Boyden, C.J. Rozell and C.R. Forest. Journal of Neural Engineering, 16(4), pp. 046003, May 2019.
Bibtex Entry:
@Article{kolb.18,
  author = {Kolb, I. and Landry, C. and  Yip, M. and  Lewallen, C. and Stoy, W. and Lee, J. and Felouzis, A. and Yang, B. and  Boyden, E.S. and Rozell, C.J. and Forest, C.R.},
  title = {{PatcherBot}: a single-cell electrophysiology robot for adherent cells and brain slices},
  year = 2019,
  journal={Journal of Neural Engineering},
  abstract = {Objective: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we demonstrate a robotic "PatcherBot" system that can perform many patch-clamp recordings sequentially, fully unattended. Approach: comprehensive automation is accomplished by outfitting the robot with machine vision, and cleaning pipettes instead of manually exchanging them. Main results: the PatcherBot can obtain data at a rate exceeding human capability (up to 16 cells per hour) and work with no human intervention for up to 3 hours. We demonstrate the broad applicability and scalability of this system by performing hundreds of recordings in tissue culture cells and mouse brain slices with no human supervision. Using the PatcherBot, we also discovered that pipette cleaning can be improved by a factor of three. Significance: The system is potentially transformative for applications that depend on many high-quality measurements of single cells, such as drug screening, protein functional characterization, and multimodal cell type investigations.},
volume = {16},
number ={4},
month = may,
pages = {046003},
  url = {https://doi.org/10.1088/1741-2552/ab1834}
}
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