Rapid Characterization of hERG Channel Kinetics I: Using an Automated High-Throughput System

Lei, Chon Lok; Clerx, Michael; Gavaghan, David J.; Polonchuk, Liudmila; Mirams, Gary R.; Wang, Ken

Abstract

Predicting how pharmaceuticals may affect heart rhythm is a crucial step in drug-development, and requires a deep understanding of a compound’s action on ion channels. In vitro hERG-channel current recordings are an important step in evaluating the pro-arrhythmic potential of small molecules, and are now routinely performed using automated high-throughput patch clamp platforms. These machines can execute traditional voltage clamp protocols aimed at specific gating processes, but the array of protocols needed to fully characterise a current is typically too long to be applied in a single cell. Shorter high-information protocols have recently been introduced which have this capability, but they are not typically compatible with high-throughput platforms. We present a new 15 second protocol to characterise hERG (Kv11.1) kinetics, suitable for both manual and high-throughput systems. We demonstrate its use on the Nanion SyncroPatch 384PE, a 384 well automated patch clamp platform, by applying it to CHO cells stably expressing hERG1a. From these recordings we construct 124 cell-specific variants/parameterisations of a hERG model at 25C. A further 8 independent protocols are run in each cell, and are used to validate the model predictions. We then combine the experimental recordings using a hierarchical Bayesian model, which we use to quantify the uncertainty in the model parameters, and their variability from cell to cell, which we use to suggest reasons for the variability. This study demonstrates a robust method to measure and quantify uncertainty, and shows that it is possible and practical to use high-throughput systems to capture full hERG channel kinetics quantitatively and rapidly.

Citation

Lei, C. L., Clerx, M., Gavaghan, D. J., Polonchuk, L., Mirams, G. R., & Wang, K. (2019). Rapid Characterization of hERG Channel Kinetics I: Using an Automated High-Throughput System. Biophysical Journal, 117(12), 2438-2454. https://doi.org/10.1016/j.bpj.2019.07.029

• Journal Article Type: Article
• Acceptance Date: Jul 17, 2019
• Online Publication Date: Jul 25, 2019
• Publication Date: Dec 17, 2019
• Deposit Date: Jul 19, 2019
• Publicly Available Date: Jul 26, 2020
• Print ISSN: 0006-3495
• Electronic ISSN: 1542-0086
• Publisher: Biophysical Society
• Peer Reviewed: Peer Reviewed
• Volume: 117
• Issue: 12
• Pages: 2438-2454
• DOI: https://doi.org/10.1016/j.bpj.2019.07.029
• Public URL: https://nottingham-repository.worktribe.com/output/1881713
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0006349519305971