Robotic Inside-Out Patch Clamp System for Adherent Cells Based on Vesicle Rupture Control
Yuzhu Liu, Ruimin Li, Jinyu Qiu, Biting Ma, Zuqi Wang, Minghui Li, Xin Zhao, Qili Zhao
Abstract
The inside-out patch clamp technique has been widely applied in brain science and neuroscience research due to its ability to detect extremely weak currents flowing through a single ion channel. The current manual inside-out patch clamp operations are highly expertise-requisite and low efficient. Meanwhile, the existing robotic systems are only applicable for suspended cells due to their new system setups. For the first time, this letter proposed a robotic inside-out patch clamp system for adherent cells based on vesicle rupture control. Firstly, impedance models were established to detect the vesicle rupture state. Then, a force analysis that combines the defocusing imaging model was developed to precisely control the exposure time of the vesicle in the air, which is a key factor in the rupture process of the vesicle. Based on the above works, a robotic inside-out patch clamp process for adherent cells was established. Experimental results demonstrate that the proposed robotic system can detect vesicle rupture state with a 100% success rate, control exposure time with an average error of 0.02<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\,\text{s}$</tex-math></inline-formula> and operate adherent HEK-293 cells with a success rate of 70% at an average operation speed of 61.3<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\,$</tex-math></inline-formula>seconds/cell. The success rate of our system is more than three times that of manual operation results, laying a solid foundation for subsequent single ion channel functionality research.
BibTeX
@inproceedings{ral2025_roboticinsideout,
title = {Robotic Inside-Out Patch Clamp System for Adherent Cells Based on Vesicle Rupture Control},
author = {Yuzhu Liu and Ruimin Li and Jinyu Qiu and Biting Ma and Zuqi Wang and Minghui Li and Xin Zhao and Qili Zhao},
booktitle = {RA-L 2025},
year = {2025}
}