Dynamics of Glycine Receptors and their Interactions with Gephyrin Scaffolds Revealed with High-Density Single Particle Tracking and Bayesian Inference

Abstract

The scaffold protein gephyrin plays a critical regulatory role in the transmission of nerve signals in inhibitory synapses.. Its interactions with receptors of inhibitory neurotransmitters, such as glycine or GABA, are postulated to be a key molecular mechanism of synaptic formation and plasticity. Previous studies have shown that glycine receptors transiently bind to gephyrin scaffolds inside the synapse, however there is limited knowledge of the strength of this interaction. This is due, in part, to the consensus view that the synapse is a complex and dynamic assembly that is sensitive to a host of stimuli including neuronal activity, hormones, and pathological states. Therefore, a beneficial approach to improve our understanding is to reconstitute gephyrin scaffolds and their interactions with receptors in non-neuronal cells. To this end, in a greatly simplified system we use a transmembrane construction that consists of the large intracellular s-Loop that directly interacts with the gephyrin scaffold, mimicking the actions of the endogenous glycine receptor.Based on high-density single-particle tracking, we use a robust Bayesian inference approach to spatially map the dynamics inside receptor-scaffold sites in non-neuronal cells. Through adaptive spatial meshing techniques, we are able to conform our maps to highly heterogeneous trajectory and diffusion distributions and, notably, generate whole-cell landscapes of interaction energies. Importantly, we treat the inherently multi-scale nature of receptor motion in a faithful and reproducible manner.We show that our method allows us to distinguish interactions between different s-Loop mutants, effectively correlating protein-level modifications to quantifiable metrics of receptor dynamics. This is an important advance that reinforces the treatment of complex biological systems with statistical methods.