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Computational Modeling Reveals Key Contributions of KCNQ and hERG Currents to the Malleability of Uterine Action Potentials Underpinning Labor

Lookup NU author(s): Dr Winnie Tong, Professor Michael Taggart

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

The electrical excitability of uterine smooth muscle cells is a key determinant of the contraction of the organ during labor and is manifested by spontaneous, periodic action potentials (APs). Near the end of term, APs vary in shape and size reflecting an ability to change the frequency, duration and amplitude of uterine contractions. A recent mathematical model quantified several ionic features of the electrical excitability in uterine smooth muscle cells. It replicated many of the experimentally recorded uterine AP configurations but its limitations were evident when trying to simulate the long-duration bursting APs characteristic of labor. A computational parameter search suggested that delayed rectifying K+ currents could be a key model component requiring improvement to produce the longer-lasting bursting APs. Of the delayed rectifying K+ currents family it is of interest that KCNQ and hERG channels have been reported to be gestationally regulated in the uterus. These currents exhibit features similar to the broadly defined uterine IK1 of the original mathematical model. We thus formulated new quantitative descriptions for several IKCNQ and IhERG. Incorporation of these currents into the uterine cell model enabled simulations of the long-lasting bursting APs. Moreover, we used this modified model to simulate the effects of different contributions of IKCNQ and IhERG on AP form. Our findings suggest that the alterations in expression of hERG and KCNQ channels can potentially provide a mechanism for fine tuning of AP forms that lends a malleability for changing between plateau-like and long-lasting bursting-type APs as uterine cells prepare for parturition.


Publication metadata

Author(s): Tong WC, Tribe RM, Smith R, Taggart MJ

Publication type: Article

Publication status: Published

Journal: PLoS One

Year: 2014

Volume: 9

Issue: 12

Pages: e114034

Online publication date: 04/12/2014

Acceptance date: 03/11/2014

Date deposited: 28/01/2015

ISSN (electronic): 1932-6203

Publisher: Public Library of Science

URL: http://dx.doi.org/10.1371/journal.pone.0114034

DOI: 10.1371/journal.pone.0114034

PubMed id: 25474527


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Funding

Funder referenceFunder name
G0902091Bioinformatics Training Fellowship
G1100243UK Medical Research Council
G0900525UK Medical Research Council

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