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Protein mobility is conventionally analyzed in terms of an effective diffusion. Yet, this description often fails to properly distinguish and evaluate the physical parameters (such as the membrane friction) and the biochemical interactions governing the motion. Here, we present a method combining high-density single-molecule imaging and statistical inference to separately map the diffusion and energy landscapes of membrane proteins across the cell surface at ~100 nm resolution (with acquisition of a few minutes). When applying these analytical tools to glycine neurotransmitter receptors (GlyRs) at inhibitory synapses, we find that gephyrin scaffolds act as shallow energy traps (~3 kBT) for GlyRs, with a depth modulated by the biochemical properties of the receptor-gephyrin interaction loop. In turn, the inferred maps can be used to simulate the dynamics of proteins in the membrane, from the level of individual receptors to that of the population, and thereby, to model the stochastic fluctuations of physiological parameters (such as the number of receptors at synapses). Overall, our approach provides a powerful and comprehensive framework with which to analyze biochemical interactions in living cells and to decipher the multi-scale dynamics of biomolecules in complex cellular environments., 23 pages, 4 figures

Single-molecule tracking (SMT) experiments have shown that post-synaptic receptors (e.g. AMPA, NMDA, Glycine or GABA receptors) can be described as being in a dynamic equilibrium between free extrasynaptic diffusion and confined motion at synapses where they are transiently stabilized by molecular scaffolds. Although these experiments have been useful in characterizing receptor motion, they only provide a partial description of the biochemical environment encountered by the receptors. Indeed, standard analysis of SMT measurements fails to properly distinguish the contributions of viscosity and specific binding processes in molecular movements. Here, we use high-density single-molecule imaging coupled to statistical inference methods to separately map the diffusion and energy landscapes of proteins in cell membranes with a resolution of ∼70 nm. With this novel approach, we analyze the properties of a transmembrane protein susceptible or not to interact with the synaptic scaffold protein gephyrin, thus mimicking the behavior of glycine receptors at inhibitory synapses. The energy maps reveal that gephyrin clusters act as shallow energy traps with a depth ∼3 kT, offering a trade-off between receptor stability and plasticity at synapses. This depth is independent of the trap extension, consistent with the organization of gephyrin clusters as two-dimensional scaffolds. Next, we used the phenomenological diffusion and energy maps as inputs for simulating the lateral dynamics of individual transmembrane proteins. Thereby we evaluated the distributions of key parameters of the dynamic equilibrium: the residence time at synapses and the first passage time of an extrasynaptic receptor at a synapse (namely, the association and dissociation rate). Finally, we show that the diffusivity and energy landscapes lead to anomalous membrane diffusion, likely due to broadly-distributed trapping times. Overall, our approach is applicable in many contexts and constitutes an important step towards the in situ analysis of biochemical processes.

The movement of proteins in the cell membrane is governed by the local friction and their interactions with molecular partners. Yet, most experimental descriptions fail to unequivocally distinguish these effects; instead, they combine the diffusive and energetic contributions into an effective diffusion coefficient or anomalous exponent. Here, we show how the diffusion and energy landscapes of membrane proteins can be mapped separately over the entire cell surface using high-density single-molecule imaging and statistical inference [1]. In the case of glycine neuroreceptors, we demonstrate that scaffolds at inhibitory synapses act as energy traps with a depth modulated by the properties of the intracellular loop that mediates the receptor-scaffold interactions. Furthermore, we bridge the gap between local properties of the membrane environment and characteristics of the mobility at the cellular scale by simulating random walks in the inferred maps and computing estimators such as the propagator, mean square displacement, and first-passage time. Results are used to investigate the relation between numbers of receptors and synaptic plasticity. Overall, our approach provides a versatile framework with which to analyze biochemical interactions in situ.[1] J.-B Masson et al, Nat. Chem. (submitted)View Large Image | View Hi-Res Image | Download PowerPoint Slide

Synapses are the fundamental structures involved in signal transmission in neurons. Due to its sub-micron size, spatial resolution has been a major limiting factor in investigating the structure and dynamics of the synapses using light microscopy. We have developed a novel approach, based on light microscopy, combining three-dimensional single particle tracking with super-resolution imaging (PALM) to overcome this limitation. The technique has been successfully applied on live neurons to visualize the diffusion behavior of AMPA receptors near synapses, with sub-diffraction-limit resolution. We first used commercially available quantum dots with 20-30 nm in size to label the AMPA receptors as markers for single particle tracking and a photoactivable protein attached to post-synaptic protein Homer1 as a marker for PALM. As a result, we are able to simultaneously localize the post-synaptic density in three dimensions and observe the dynamic changes of AMPA receptors that move into, and out of, the synaptic area. We then changed our probe to a much smaller quantum dot, only 6 nm in diameter. With this smaller probe, different diffusion behavior of AMPA receptors is observed, which indicates the bigger quantum dots may have hindered the AMPA receptors' accessibility to the synaptic cleft.