Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics

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 ele...

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Main Authors: Beattie, Kylie, Hill, Adam P., Bardenet, Rémi, Cui, Yi, Vandenberg, Jamie I., Gavaghan, David J., de Boer, Teun P., Mirams, Gary R.
Format: Article
Published: Wiley 2018
Subjects:
Online Access:https://eprints.nottingham.ac.uk/49871/
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author Beattie, Kylie
Hill, Adam P.
Bardenet, Rémi
Cui, Yi
Vandenberg, Jamie I.
Gavaghan, David J.
de Boer, Teun P.
Mirams, Gary R.
author_facet Beattie, Kylie
Hill, Adam P.
Bardenet, Rémi
Cui, Yi
Vandenberg, Jamie I.
Gavaghan, David J.
de Boer, Teun P.
Mirams, Gary R.
author_sort Beattie, Kylie
building Nottingham Research Data Repository
collection Online Access
description 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 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.
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spelling nottingham-498712020-05-04T19:36:35Z https://eprints.nottingham.ac.uk/49871/ Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics Beattie, Kylie Hill, Adam P. Bardenet, Rémi Cui, Yi Vandenberg, Jamie I. Gavaghan, David J. de Boer, Teun P. Mirams, Gary R. 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 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. Wiley 2018-05-15 Article PeerReviewed Beattie, Kylie, Hill, Adam P., Bardenet, Rémi, Cui, Yi, Vandenberg, Jamie I., Gavaghan, David J., de Boer, Teun P. and Mirams, Gary R. (2018) Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics. Journal of Physiology, 596 (10). pp. 1813-1828. ISSN 1469-7793 hERG IKr mathematical model electrophysiology patch clamp voltage protocol https://physoc.onlinelibrary.wiley.com/doi/10.1113/JP275733 doi:10.1113/JP275733 doi:10.1113/JP275733
spellingShingle hERG
IKr
mathematical model
electrophysiology
patch clamp
voltage protocol
Beattie, Kylie
Hill, Adam P.
Bardenet, Rémi
Cui, Yi
Vandenberg, Jamie I.
Gavaghan, David J.
de Boer, Teun P.
Mirams, Gary R.
Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title_full Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title_fullStr Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title_full_unstemmed Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title_short Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
title_sort sinusoidal voltage protocols for rapid characterisation of ion channel kinetics
topic hERG
IKr
mathematical model
electrophysiology
patch clamp
voltage protocol
url https://eprints.nottingham.ac.uk/49871/
https://eprints.nottingham.ac.uk/49871/
https://eprints.nottingham.ac.uk/49871/