Model-based Evaluation of Biophysical Properties of Gap Junction Channels from Electrophysiological Data recorded at Macroscopic and Single-Channel Levels

Abstract

Electrophysiological recording via the patch clamp technique allows for the assessment of the biophysical properties of various types of ion channels. However, electrophysiological recordings of gap junction (GJ) channels poses challenges due to their unique intercellular configuration and natural clustering into plaques, making it difficult to obtain reliable data at a single-channel level. Additionally, until recently, no mathematical models adequately explained both the steady-state and kinetic properties of GJ channel gating, which is crucial for model-based evaluation of single-channel level characteristics. Consequently, the methods for accurately correlating data recorded at macroscopic and single-channel levels have been lacking in studies of gap junctional electrophysiology. To address these issues, we combined our previously published four-state model (4SM) of GJ channel gating with probabilistic methods, such as maximum likelihood estimation (MLE)-based analysis of single-channel level currents and stationary noise analysis of macroscopic level electrophysiological recordings. First, we address evaluation of biophysical single-channel-level properties of GJ channels, such as open-state probability and unitary conductance, using data from macroscopic-level recordings. Second, we consider MLE-based methodologies to extract information about gating parameters of GJ channels from electrophysiological recordings with observable unitary events. The validity of the proposed methodologies is first illustrated through stochastic simulations and further extended to real electrophysiological data. Overall, our findings show that these techniques can provide valuable insights into biophysical properties of GJ channels.