Stochastic Single-Molecule Dynamics of Synaptic Receptor Domains

Abstract

Neurotransmitter receptor molecules, concentrated in postsynaptic membrane domains along with scaffold and other kinds of molecules, are crucial for signal transmission across chemical synapses. Using superresolution light microscopy it has been found that individual receptor molecules have very quick turnover rates of the order of seconds, while synaptic receptor domains are globally stable over months or even longer periods of time. Through an interplay between experiments on a minimal model system and theoretical modeling it has been demonstrated that the diffusion and reaction properties of receptors and scaffolds at the membrane are necessary and sufficient for the formation of stable receptor-scaffold domains of the characteristic size observed in nerve cells. However, existing theoretical models of synaptic receptor domains are limited to the mean-field level, and thus cannot account for the stochastic trajectories of individual synaptic molecules observed in experiments on nerve cells. Here we formulate and study a stochastic lattice gas model of synaptic receptor domains which allows us to overcome this challenge. Using kinetic Monte Carlo simulations we show that our stochastic lattice gas model reproduces the experimentally observed patterns of receptor-scaffold domains of a stable characteristic size, while also allowing for a coupling of reaction and diffusion noise to the nonlinear reaction and diffusion dynamics of receptors and scaffolds in the highly crowded membrane environments provided by synaptic domains. Our stochastic lattice gas model allows us to make detailed comparisons with experimental data on the stochastic properties of synaptic domains, and provides a bridge connecting the rapid and highly stochastic dynamics that rule the molecular realm of cell membranes to the global stability of synaptic receptor domains essential for the biological function of synapses.