The Cardiac Electrophysiology Web Lab

Cooper, Jonathan; Scharm, Martin; Mirams, Gary R.

doi:10.1016/j.bpj.2015.12.012

Cited by 58 publications

(53 citation statements)

References 44 publications

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“…However, at present and unlike when addressing the forward problem where MECSim and other software packages are available, web applications that are specifically designed for addressing the inverse problem in electrochemistry at a sophisticated and automated level are not yet available. In the future we plan to develop such a web application for voltammetry, based on one available for cardiac electrophysiology …”

Section: Discussionmentioning

confidence: 99%

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

et al. 2018

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The thermodynamic and electrode kinetic parameters that describe each of the three unresolved proton‐coupled two‐electron transfer processes of surface‐confined Keggin‐type phosphomolybdate, [PMo12O40]3− adsorbed onto glassy carbon electrode in 1.0 M H2SO4 have been elucidated by comparison of experimental and simulated AC voltammmetric data. Modelling of this problem requires the introduction of over 30 parameters, although this may be reduced to about half this number when intelligent forms of data analysis are introduced. Heuristic (i. e., an experimenter based trial and error method) and automated data optimization approaches are integrated in this very extensive parameter estimation exercise. However, obtaining a unique solution remains challenging for reasons that are outlined. In the final analysis and using the automated strategy, estimates of six reversible potentials, lower limits of the six electron transfer rate constants, the double layer capacitance, uncompensated resistance and surface coverage are reported, with others (such as the charge transfer co‐efficient) present in the model being unobtainable for reasons that are provided. The fit to experimental data using parameters obtained by automated data optimisation is excellent and slightly superior to that obtained by heuristic analysis. The parameters obtained by either method account for differences in shapes and current magnitudes of each of the overall two electron processes.

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Section: Discussionmentioning

confidence: 99%

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

et al. 2018

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“…Pr6 was formed by combining a series of different simulated action potentials from the Cardiac Electrophysiology Web Lab (Cooper et al . ). The range of models we used for the simulations encompassed different cell types, species and pacing rates.…”

Section: Methodsmentioning

confidence: 97%

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics

Beattie

Hill

Bardenet

et al. 2018

The Journal of Physiology

180

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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. 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 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.

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“…Pr6 was formed by combining a series of different simulated action potentials from the Cardiac Electrophysiology Web Lab (Cooper et al 2016). The range of models we used for the simulations encompassed different cell types, species and pacing rates.…”

Section: Experimental Methodsmentioning

confidence: 99%

Sinusoidal Voltage Protocols for Rapid Characterisation of Ion Channel Kinetics

Beattie¹,

Hill

Bardenet

et al. 2018

Biophysical Journal

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Key pointsr 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.r 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.r 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. r 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.r 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 Kylie Beattie is an applied mathematician now working within the Systems Modelling and Translational Biology group at GlaxoSmithKline. She obtained her PhD from the University of Oxford; it focused on the characterisation of ion channel kinetics and drug interactions with cardiac ion channels. The work presented in this article was initiated during her PhD work and continued during subsequent postdoctoral work. After completing this study she spent a year at the US Food and Drug Administration working on ion channel modelling as part of the in silico modelling efforts for the Comprehensive in vitro Proarrhythmia Assay initiative.This article was first published as a preprint on bioRχiv: Beattie et al. 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...

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The Cardiac Electrophysiology Web Lab

Cited by 58 publications

References 44 publications

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Integration of Heuristic and Automated Parametrization of Three Unresolved Two‐Electron Surface‐Confined Polyoxometalate Reduction Processes by AC Voltammetry

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics

Sinusoidal Voltage Protocols for Rapid Characterisation of Ion Channel Kinetics

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