Voltage laws in nanodomains revealed by asymptotics and simulations of electro-diffusion equations

TL;DR

This paper develops an asymptotic and numerical framework to analyze voltage distributions in nanodomains driven by ionic currents, addressing a key challenge in biophysical modeling of cellular activity.

Contribution

The authors introduce a new method combining asymptotic analysis and simulations to solve nonlinear electro-diffusion equations in complex nanodomains with boundary channels.

Findings

Derived ionic profiles and voltage drops in different charge regimes.

Showed how surface curvature and channel size influence voltage dynamics.

Validated theoretical predictions with numerical simulations.

Abstract

Characterizing the local voltage distribution within nanophysiological domains, driven by ionic currents through membrane channels, is crucial for studying cellular activity in modern biophysics, yet it presents significant experimental and theoretical challenges. Theoretically, the complexity arises from the difficulty of solving electro-diffusion equations in three-dimensional domains. Currently, there are no methods available for obtaining asymptotic computations or approximated solutions of nonlinear equations, and numerically, it is challenging to explore solutions across both small and large spatial scales. In this work, we develop a method to solve the Poisson-Nernst-Planck equations with ionic currents entering and exiting through two narrow, circular window channels located on the boundary. The inflow through the first window is composed of a single cation, while the outflow maintains a constant ionic density satisfying local electro-neutrality conditions. Employing regular expansions and Green's function representations, we derive the ionic profiles and voltage drops in both small and large charge regimes. We explore how local surface curvature and window channels size influence voltage dynamics and validate our theoretical predictions through numerical simulations, assessing the accuracy of our asymptotic computations. These novel relationships between current, voltage, concentrations and geometry can enhance the characterization of physiological behaviors of nanodomains.