scholarly journals Rapid Characterisation of R56Q Mutant hERG Channel Kinetics using Sinusoidal Voltage Protocols

2020 ◽  
Vol 118 (3) ◽  
pp. 112a
Author(s):  
Dominic G. Whittaker ◽  
Jake M. Kemp ◽  
Gary R. Mirams ◽  
Tom W. Claydon
2017 ◽  
Vol 88 ◽  
pp. 195-196 ◽  
Author(s):  
Kylie A. Beattie ◽  
Remi Bardenet ◽  
James B. Louttit ◽  
Jamie I. Vandenberg ◽  
Adam P. Hill ◽  
...  

2017 ◽  
Author(s):  
Kylie A. Beattie ◽  
Adam P. Hill ◽  
Rémi Bardenet ◽  
Yi Cui ◽  
Jamie I. Vandenberg ◽  
...  

AbstractUnderstanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics — the voltage-dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fit a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells over-expressing hERG1a. The model is then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprised of a collection of physiologically-relevant action potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches.Table of Contents CategoryTechniques for Physiology1Key PointsIon current kinetics are commonly represented by current-voltage relationships, time-constant voltage relationships, and subsequently mathematical models fitted to these. These experiments take substantial time which means they are rarely performed in the same cell.Rather than traditional square-wave voltage clamps, we fit a model to the current evoked by a novel sum-of-sinusoids voltage clamp that is only 8 seconds long.Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions.The new model predicts the current under traditional square-wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically-relevant series of action potential clamps is predicted extremely well.The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell-cell variability in current kinetics for the first time.


2019 ◽  
Vol 117 (12) ◽  
pp. 2438-2454 ◽  
Author(s):  
Chon Lok Lei ◽  
Michael Clerx ◽  
David J. Gavaghan ◽  
Liudmila Polonchuk ◽  
Gary R. Mirams ◽  
...  

2018 ◽  
Vol 596 (10) ◽  
pp. 1813-1828 ◽  
Author(s):  
Kylie A. Beattie ◽  
Adam P. Hill ◽  
Rémi Bardenet ◽  
Yi Cui ◽  
Jamie I. Vandenberg ◽  
...  

2019 ◽  
Author(s):  
Chon Lok Lei ◽  
Michael Clerx ◽  
Kylie A. Beattie ◽  
Dario Melgari ◽  
Jules C. Hancox ◽  
...  

ABSTRACTIon channel behaviour can depend strongly on temperature, with faster kinetics at physiological temperatures leading to considerable changes in currents relative to room temperature. These temperature-dependent changes in voltage-dependent ion channel kinetics (rates of opening, closing and inactivating) are commonly represented with Q10coefficients or an Eyring relationship. In this paper we assess the validity of these representations by characterising channel kinetics at multiple temperatures. We focus on the hERG channel, which is important in drug safety assessment and commonly screened at room temperature, so that results require extrapolation to physiological temperature. In Part I of this study we established a reliable method for high-throughput characterisation of hERG1a (Kv11.1) kinetics, using a 15 second information-rich optimised protocol. In this Part II, we use this protocol to study the temperature dependence of hERG kinetics using CHO cells over-expressing hERG1a on the Nanion SyncroPatch 384PE, a 384-well automated patch clamp platform, with temperature control. We characterise the temperature dependence of hERG gating by fitting the parameters of a mathematical model of hERG kinetics to data obtained at five distinct temperatures between 25 and 37 °C, and validate the models using different protocols. Our models reveal that activation is far more temperature sensitive than inactivation, and we observe that the temperature dependency of the kinetic parameters is not represented well by Q10coefficients: it broadly follows a generalised, but not the standardly-used, Eyring relationship. We also demonstrate that experimental estimations of Q10coefficients are protocol-dependent. Our results show that a direct fit using our 15 second protocol best represents hERG kinetics at any given temperature, and suggests that predictions from the Generalised Eyring theory may be preferentially used if no experimentally-derived data are available.Statement of SignificanceIon channel currents are highly sensitive to temperature changes. Yet because many experiments are performed more easily at room temperature, it is common to extrapolate findings to physiological temperatures through the use of Q10coefficients or Eyring rate theory. By applying short, information-rich protocols that we developed in Part I of this study we identify how kinetic parameters change over temperature. We find that the commonly-used Q10and Eyring formulations are incapable of describing the parameters’ temperature dependence, a more Generalised Eyring relationship works well, but remeasuring kinetics and refitting a model is optimal. The findings have implications for the accuracy of the many applications of Q10coefficients in electrophysiology, and suggest that care is needed to avoid misleading extrapolations in their many scientific and industrial pharmaceutical applications.


2019 ◽  
Author(s):  
Chon Lok Lei ◽  
Michael Clerx ◽  
David J. Gavaghan ◽  
Liudmila Polonchuk ◽  
Gary R. Mirams ◽  
...  

ABSTRACTPredicting 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 vitrohERG-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 high-information 15 s 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 25 °C. 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.Statement of SignificanceWe present a method for high-throughput characterisation of hERG potassium channel kinetics, via fitting a mathematical model to results of over one hundred single cell patch clamp measurements collected simultaneously on an automated voltage clamp platform. The automated patch clamp data are used to parameterise a mathematical ion channel model fully, opening a new era of automated and rapid development of mathematical models from quick and cheap experiments. The method also allows ample data for independent validation of the models and enables us to study experimental variability and propose its origins. In future the method can be applied to characterise changes to hERG currents in different conditions, for instance at different temperatures (see Part II of the study) or under mutations or the action of pharmaceuticals; and should be easily adapted to study many other currents.


2002 ◽  
Vol 80 (8) ◽  
pp. 524-532 ◽  
Author(s):  
Dirk Isbrandt ◽  
Patrick Friederich ◽  
Anna Solth ◽  
Wilhelm Haverkamp ◽  
Andreas Ebneth ◽  
...  

Author(s):  
Kylie Beattie ◽  
Teun de Boer ◽  
David Gavaghan ◽  
James Louttit ◽  
Gary Mirams

2019 ◽  
Vol 117 (12) ◽  
pp. 2455-2470 ◽  
Author(s):  
Chon Lok Lei ◽  
Michael Clerx ◽  
Kylie A. Beattie ◽  
Dario Melgari ◽  
Jules C. Hancox ◽  
...  

2015 ◽  
Vol 108 (2) ◽  
pp. 121a ◽  
Author(s):  
Gary R. Mirams ◽  
Kylie Beattie ◽  
James B. Louttit ◽  
Teun de Boer ◽  
David J. Gavaghan

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