Dataset Information

Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence.

ABSTRACT: Ion channel behavior 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, inactivating, and recovery) are commonly represented with Q10 coefficients or an Eyring relationship. In this article, we assess the validity of these representations by characterizing channel kinetics at multiple temperatures. We focus on the human Ether-à-go-go-Related Gene (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 characterization of hERG1a (Kv11.1) kinetics, using a 15-second information-rich optimized protocol. In this Part II, we use this protocol to study the temperature dependence of hERG kinetics using Chinese hamster ovary cells overexpressing hERG1a on the Nanion SyncroPatch 384PE, a 384-well automated patch-clamp platform, with temperature control. We characterize 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 Q10 coefficients; it broadly follows a generalized, but not the standardly-used, Eyring relationship. We also demonstrate that experimental estimations of Q10 coefficients are protocol dependent. Our results show that a direct fit using our 15-s protocol best represents hERG kinetics at any given temperature and suggests that using the Generalized Eyring theory is preferable if no experimental data are available to derive model parameters at a given temperature.

SUBMITTER: Lei CL

PROVIDER: S-EPMC6990152 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence.

Lei Chon Lok CL Clerx Michael M Beattie Kylie A KA Melgari Dario D Hancox Jules C JC Gavaghan David J DJ Polonchuk Liudmila L Wang Ken K Mirams Gary R GR

Biophysical journal 20190725 12

Ion channel behavior 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, inactivating, and recovery) are commonly represented with Q<sub>10</sub> coefficients or an Eyring relationship. In this article, we assess the validity of these representations by characterizing channel kinetics ...[more]

PMID: 31451180

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Project description:Human ether-à-go-go related gene (hERG) voltage-activated potassium channels are critical for cardiac excitability. Characteristic slow closing (deactivation) in hERG is regulated by direct interaction between the N-terminal Per-Arnt-Sim (PAS) domain and the C-terminal cyclic nucleotide binding homology domain (CNBHD). We aim to understand how the PAS domain that is distal to the pore rearranges during gating to allosterically regulate the channel pore (and ion flux). To achieve this, we utilized the non-canonical amino acid 4-Benzoyl-L-phenylalanine (BZF) which is a photo-activatable cross-linkable probe, that when irradiated with ultraviolet (U.V.) light forms a double radical capable of forming covalent cross-links with C-H bond-containing groups, enabling selective and potent U.V.-driven photoinactivation of ion channel dynamics. Here we incorporate BZF directly into the hERG potassium channel PAS domain at three locations (G47, F48, and E50) using TAG codon suppression technology. hERG channels with BZF incorporated into the PAS domain (hERG-BZF) showed a significant change in the biophysical properties of the channel. hERG-G47BZF activated slowly when irradiated in the closed state (-100mV) but deactivated quickly when irradiated in both the open (0mV) and closed state. hERG-F48BZF channels showed a state independent and U.V. dose-dependent change in channel activation (slowing down) and channel deactivation (speeding up), as well as a marked change (right-shift) in the voltage-dependence of conductance. When irradiated at -100 mV hERG-E50BZF showed a state dependent and U.V. dose-dependent change in a channel activation (slowing down) and deactivation (speeding up) of channel deactivation, as well as a marked change (right-shift) in the voltage-dependence of conductance that occurred only when the channel was irradiated in the closed state (-100mV). This approach demonstrated that direct photo-crosslinking of the PAS domain in hERG channels causes a measurable change in biophysical parameters and more broadly stabilized the closed state of the channel. We propose that altered channel gating is as a direct result of reduced dynamic motions in the PAS domain of hERG due to photo-chemical crosslinking.

Project description:KEY POINTS:Ion 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 fitted a model to the current evoked by a novel sum-of-sinusoids voltage clamp that was only 8 s 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. ABSTRACT:Understanding 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 fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was 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 comprising 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.

Project description:Current regulatory guidelines for assessing the risk of QT prolongation include in vitro assays assessing drug effects on the human ether-à-go-go-related (hERG; also known as Kv11.1) channel expressed in cell lines. These assays are typically conducted at room temperature to promote the ease and stability of recording hERG currents. However, the new Comprehensive in vitro Proarrhythmia Assay (CiPA) paradigm proposes to use an in silico model of the human ventricular myocyte to assess risk, requiring as input hERG channel pharmacology data obtained at physiological temperatures. To accommodate current industry safety pharmacology practices for measuring hERG channel activity, an in silico model of hERG channel that allows for the extrapolation of hERG assay data across different temperatures is desired. Because temperature may have an effect on both channel gating and drug binding rate, such models may need to have two components: a base model dealing with temperature-dependent gating changes without drug, and a pharmacodynamic component simulating temperature-dependent drug binding kinetics. As a first step, a base mode that can capture temperature effects on hERG channel gating without drug is needed.To meet this need for a temperature-dependent base model, a Markov model of the hERG channel with state transition rates explicitly dependent on temperature was developed and calibrated using data from a variety of published experiments conducted over a range of temperatures. The model was able to reproduce observed temperature-dependent changes in key channel gating properties and also to predict the results obtained in independent sets of new experiments.This new temperature-sensitive model of hERG gating represents an attempt to improve the predictivity of safety pharmacology testing by enabling the translation of room temperature hERG assay data to more physiological conditions. With further development, this model can be incorporated into the CiPA paradigm and also be used as a tool for developing insights into the thermodynamics of hERG channel gating mechanisms and the temperature-dependence of hERG channel block by drugs.

Dataset Information

Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence.

Publications

Rapid Characterization of hERG Channel Kinetics II: Temperature Dependence.

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