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Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach

Matthew Jennings, Perumal Nithiarasu Orcid Logo, Sanjay Pant Orcid Logo

International Journal for Numerical Methods in Biomedical Engineering, Volume: 40, Issue: 5

Swansea University Authors: Matthew Jennings, Perumal Nithiarasu Orcid Logo, Sanjay Pant Orcid Logo

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DOI (Published version): 10.1002/cnm.3815

Abstract

Voltage-clamp experiments are commonly utilised to characterise cellular ion channel kinetics. In these experiments, cells are stimulated using a known time-varying voltage, referred to as the voltage protocol, and the resulting cellular response, typically in the form of current, is measured. Param...

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Published in: International Journal for Numerical Methods in Biomedical Engineering
ISSN: 2040-7939 2040-7947
Published: Wiley 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65810
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In these experiments, cells are stimulated using a known time-varying voltage, referred to as the voltage protocol, and the resulting cellular response, typically in the form of current, is measured. Parameters of models that describe ion channel kinetics are then estimated by solving an inverse problem which aims to minimise the discrepancy between the predicted response of the model and the actual measured cell response. In this paper, a novel framework to evaluate the information content of voltage-clamp protocols in relation to ion channel model parameters is presented. Additional quantitative information metrics that allow for comparisons among various voltage protocols are proposed. These metrics offer a foundation for future optimal design frameworksto devise novel, information-rich protocols. The efficacy of the proposed framework is evidenced through the analysis of seven voltage protocols from the literature. By comparing known numerical results for inverse problems using these protocols with the information-theoretic metrics, the proposed approach is validated. The essential steps of the framework are: (i) generate random samples of the parameters from chosen prior distributions; (ii) run the model to generate model output (current) for all samples; (iii) construct reduceddimensional representations of the time-varying current output using Proper Orthogonal Decomposition (POD); (iv) estimate information-theoretic metrics such as mutual information, entropy equivalent variance, and conditional mutual information using non-parametric methods; (v) interpret the metrics; for example, a higher mutual information between a parameter and the current output suggests the protocol yields greaterinformation about that parameter, resulting in improved identifiability; and (vi) integrate the informationtheoretic metrics into a single quantitative criterion, encapsulating the protocol’s efficacy in estimating model parameters.</abstract><type>Journal Article</type><journal>International Journal for Numerical Methods in Biomedical Engineering</journal><volume>40</volume><journalNumber>5</journalNumber><paginationStart/><paginationEnd/><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2040-7939</issnPrint><issnElectronic>2040-7947</issnElectronic><keywords>Information theory, Experimental design, Ion channel kinetics, Parameter estimation, Identifiability</keywords><publishedDay>1</publishedDay><publishedMonth>5</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-05-01</publishedDate><doi>10.1002/cnm.3815</doi><url/><notes/><college>COLLEGE NANME</college><CollegeCode>COLLEGE CODE</CollegeCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>MJ acknowledges the support of EPSRC Standard Research Studentship (DTP) for this work.</funders><projectreference/><lastEdited>2024-06-03T11:06:06.6872721</lastEdited><Created>2024-03-11T12:14:45.5622064</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Engineering and Applied Sciences - Biomedical Engineering</level></path><authors><author><firstname>Matthew</firstname><surname>Jennings</surname><order>1</order></author><author><firstname>Perumal</firstname><surname>Nithiarasu</surname><orcid>0000-0002-4901-2980</orcid><order>2</order></author><author><firstname>Sanjay</firstname><surname>Pant</surname><orcid>0000-0002-2081-308X</orcid><order>3</order></author></authors><documents><document><filename>65810__30037__6d48c8ca1ed34d29b21bcfd1e6067b00.pdf</filename><originalFilename>65810.VOR.pdf</originalFilename><uploaded>2024-04-16T13:41:03.8098145</uploaded><type>Output</type><contentLength>2309086</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2024 The Authors. 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spelling v2 65810 2024-03-11 Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach 3b2502b658cc0bc56043340b9d54c065 Matthew Jennings Matthew Jennings true false 3b28bf59358fc2b9bd9a46897dbfc92d 0000-0002-4901-2980 Perumal Nithiarasu Perumal Nithiarasu true false 43b388e955511a9d1b86b863c2018a9f 0000-0002-2081-308X Sanjay Pant Sanjay Pant true false 2024-03-11 Voltage-clamp experiments are commonly utilised to characterise cellular ion channel kinetics. In these experiments, cells are stimulated using a known time-varying voltage, referred to as the voltage protocol, and the resulting cellular response, typically in the form of current, is measured. Parameters of models that describe ion channel kinetics are then estimated by solving an inverse problem which aims to minimise the discrepancy between the predicted response of the model and the actual measured cell response. In this paper, a novel framework to evaluate the information content of voltage-clamp protocols in relation to ion channel model parameters is presented. Additional quantitative information metrics that allow for comparisons among various voltage protocols are proposed. These metrics offer a foundation for future optimal design frameworksto devise novel, information-rich protocols. The efficacy of the proposed framework is evidenced through the analysis of seven voltage protocols from the literature. By comparing known numerical results for inverse problems using these protocols with the information-theoretic metrics, the proposed approach is validated. The essential steps of the framework are: (i) generate random samples of the parameters from chosen prior distributions; (ii) run the model to generate model output (current) for all samples; (iii) construct reduceddimensional representations of the time-varying current output using Proper Orthogonal Decomposition (POD); (iv) estimate information-theoretic metrics such as mutual information, entropy equivalent variance, and conditional mutual information using non-parametric methods; (v) interpret the metrics; for example, a higher mutual information between a parameter and the current output suggests the protocol yields greaterinformation about that parameter, resulting in improved identifiability; and (vi) integrate the informationtheoretic metrics into a single quantitative criterion, encapsulating the protocol’s efficacy in estimating model parameters. Journal Article International Journal for Numerical Methods in Biomedical Engineering 40 5 Wiley 2040-7939 2040-7947 Information theory, Experimental design, Ion channel kinetics, Parameter estimation, Identifiability 1 5 2024 2024-05-01 10.1002/cnm.3815 COLLEGE NANME COLLEGE CODE Swansea University SU Library paid the OA fee (TA Institutional Deal) MJ acknowledges the support of EPSRC Standard Research Studentship (DTP) for this work. 2024-06-03T11:06:06.6872721 2024-03-11T12:14:45.5622064 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Matthew Jennings 1 Perumal Nithiarasu 0000-0002-4901-2980 2 Sanjay Pant 0000-0002-2081-308X 3 65810__30037__6d48c8ca1ed34d29b21bcfd1e6067b00.pdf 65810.VOR.pdf 2024-04-16T13:41:03.8098145 Output 2309086 application/pdf Version of Record true © 2024 The Authors. This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
spellingShingle Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
Matthew Jennings
Perumal Nithiarasu
Sanjay Pant
title_short Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
title_full Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
title_fullStr Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
title_full_unstemmed Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
title_sort Quantifying the efficacy of voltage protocols in characterising ion channel kinetics: A novel information‐theoretic approach
author_id_str_mv 3b2502b658cc0bc56043340b9d54c065
3b28bf59358fc2b9bd9a46897dbfc92d
43b388e955511a9d1b86b863c2018a9f
author_id_fullname_str_mv 3b2502b658cc0bc56043340b9d54c065_***_Matthew Jennings
3b28bf59358fc2b9bd9a46897dbfc92d_***_Perumal Nithiarasu
43b388e955511a9d1b86b863c2018a9f_***_Sanjay Pant
author Matthew Jennings
Perumal Nithiarasu
Sanjay Pant
author2 Matthew Jennings
Perumal Nithiarasu
Sanjay Pant
format Journal article
container_title International Journal for Numerical Methods in Biomedical Engineering
container_volume 40
container_issue 5
publishDate 2024
institution Swansea University
issn 2040-7939
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doi_str_mv 10.1002/cnm.3815
publisher Wiley
college_str Faculty of Science and Engineering
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hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering
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description Voltage-clamp experiments are commonly utilised to characterise cellular ion channel kinetics. In these experiments, cells are stimulated using a known time-varying voltage, referred to as the voltage protocol, and the resulting cellular response, typically in the form of current, is measured. Parameters of models that describe ion channel kinetics are then estimated by solving an inverse problem which aims to minimise the discrepancy between the predicted response of the model and the actual measured cell response. In this paper, a novel framework to evaluate the information content of voltage-clamp protocols in relation to ion channel model parameters is presented. Additional quantitative information metrics that allow for comparisons among various voltage protocols are proposed. These metrics offer a foundation for future optimal design frameworksto devise novel, information-rich protocols. The efficacy of the proposed framework is evidenced through the analysis of seven voltage protocols from the literature. By comparing known numerical results for inverse problems using these protocols with the information-theoretic metrics, the proposed approach is validated. The essential steps of the framework are: (i) generate random samples of the parameters from chosen prior distributions; (ii) run the model to generate model output (current) for all samples; (iii) construct reduceddimensional representations of the time-varying current output using Proper Orthogonal Decomposition (POD); (iv) estimate information-theoretic metrics such as mutual information, entropy equivalent variance, and conditional mutual information using non-parametric methods; (v) interpret the metrics; for example, a higher mutual information between a parameter and the current output suggests the protocol yields greaterinformation about that parameter, resulting in improved identifiability; and (vi) integrate the informationtheoretic metrics into a single quantitative criterion, encapsulating the protocol’s efficacy in estimating model parameters.
published_date 2024-05-01T11:06:06Z
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