Effect of Variations in Gap Junctional Coupling on the Frequency of Oscillatory Action Potentials in a Smooth Muscle Syncytium

Gap junctions provide pathways for intercellular communication between adjacent cells, allowing exchange of ions and small molecules. Based on the constituent protein subunits, gap junctions are classified into different subtypes varying in their properties such as unitary conductances, sensitivity to transjunctional voltage, and gating kinetics. Gap junctions couple cells electrically, and therefore the electrical activity originating in one cell can affect and modulate the electrical activity in adjacent cells. Action potentials can propagate through networks of such electrically coupled cells, and this spread is influenced by the nature of gap junctional coupling. Our study aims to computationally explore the effect of differences in gap junctional properties on oscillating action potentials in electrically coupled tissues. Further, we also explore variations in the biophysical environment by altering the size of the syncytium, the location of the pacemaking cell, as well as the occurrence of multiple pacemaking cells within the same syncytium. Our simulation results suggest that the frequency of oscillations is governed by the extent of coupling between cells and the gating kinetics of different gap junction subtypes. The location of pacemaking cells is found to alter the syncytial behavior, and when multiple oscillators are present, there exists an interplay between the oscillator frequency and their relative location within the syncytium. Such variations in the frequency of oscillations can have important implications for the physiological functioning of syncytial tissues.

Molecular Insights Into the Gating Kinetics of the Cardiac hERG Channel, Illuminated by Structure and Molecular Dynamics

The rapidly activating delayed rectifier K+ current generated by the cardiac hERG potassium channel encoded by KCNH2 is the most important reserve current for cardiac repolarization. The unique inward rectification characteristics of the hERG channel depend on the gating regulation, which involves crucial structural domains and key single amino acid residues in the full-length hERG channel. Identifying critical molecules involved in the regulation of gating kinetics for the hERG channel requires high-resolution structures and molecular dynamics simulation models. Based on the latest progress in hERG structure and molecular dynamics simulation research, summarizing the molecules involved in the changes in the channel state helps to elucidate the unique gating characteristics of the channel and the reason for its high affinity to cardiotoxic drugs. In this review, we aim to summarize the significant advances in understanding the voltage gating regulation of the hERG channel based on its structure obtained from cryo-electron microscopy and computer simulations, which reveal the critical roles of several specific structural domains and amino acid residues.

Refining the Identity and Role of Kv4 Channels in Mouse Substantia Nigra Dopaminergic Neurons

ABSTRACTSubstantia nigra pars compacta (SNc) dopaminergic (DA) neurons display a peculiar electrical phenotype characterized in vitro by a spontaneous tonic regular activity (pacemaking activity), a broad action potential and a biphasic post-inhibitory response. Several studies in rodents have underlined the central role played by the transient A-type current (IA) in the control of pacemaking activity and post-inhibitory rebound properties, thereby influencing both DA release and the physiological response of SNc neurons to incoming inhibitory inputs. Kv4.3 potassium channels were considered to be fully responsible for IA in these neurons, their density being tightly related to pacemaking frequency. In spite of this crucial electrophysiological role, we show that Kv4.3-/- transgenic mice exhibit minor alterations in locomotion and motor learning, although no compensation by functionally overlapping ion channels is observed in Kv4.3-/- SNc DA neurons. Using antigen retrieval immunohistochemistry, we further demonstrate that Kv4.2 potassium channels are also expressed in SNc DA neurons, even though their contribution to IA appears significant only in a minority of neurons (~5-10%). Using correlative analysis on recorded electrophysiological parameters and multi-compartment modeling, we then demonstrate that, rather than its conductance level, IA gating kinetics (inactivation time constant) appear as the main biophysical property defining post-inhibitory rebound delay and pacemaking frequency. Moreover, we show that the hyperpolarization-activated current (IH) has an opposing and complementary influence on the same firing features, and that the biophysical properties of IA and IH are likely coregulated in mouse SNc DA neurons.SIGNIFICANCE STATEMENTSubstantia nigra pars compacta (SNc) dopaminergic (DA) neurons are characterized by pacemaking activity, a broad action potential and biphasic post-inhibitory response. The A-type transient potassium current (IA) plays a central role in both pacemaking activity and post-inhibitory response. While it was thought so far that Kv4.3 ion channels were fully responsible for IA, using a Kv4.3-/- transgenic mouse and antigen retrieval immunohistochemistry we demonstrate that Kv4.2 channels are also expressed in SNc DA neurons, although their contribution is significant in a minority of neurons only. Using electrophysiological recordings and computational modeling, we then demonstrate that IA gating kinetics and its functional complementarity with the hyperpolarization-activated current are major determinants of both pacemaking activity and post-inhibitory response in SNc DA neurons.

Reducing complexity and unidentifiability when modelling human atrial cells

Mathematical models of a cellular action potential (AP) in cardiac modelling have become increasingly complex, particularly in gating kinetics, which control the opening and closing of individual ion channel currents. As cardiac models advance towards use in personalized medicine to inform clinical decision-making, it is critical to understand the uncertainty hidden in parameter estimates from their calibration to experimental data. This study applies approximate Bayesian computation to re-calibrate the gating kinetics of four ion channels in two existing human atrial cell models to their original datasets, providing a measure of uncertainty and indication of potential issues with selecting a single unique value given the available experimental data. Two approaches are investigated to reduce the uncertainty present: re-calibrating the models to a more complete dataset and using a less complex formulation with fewer parameters to constrain. The re-calibrated models are inserted back into the full cell model to study the overall effect on the AP. The use of more complete datasets does not eliminate uncertainty present in parameter estimates. The less complex model, particularly for the fast sodium current, gave a better fit to experimental data alongside lower parameter uncertainty and improved computational speed. This article is part of the theme issue ‘Uncertainty quantification in cardiac and cardiovascular modelling and simulation’.