Spatial distribution and dynamics of plasma-membrane proteins are thought to be modulated by lipid composition and by the underlying cytoskeleton, which forms transient barriers to diffusion. So far this idea was probed by single-particle tracking of membrane components in which gold particles or antibodies were used to individually monitor the molecules of interest. Unfortunately, the relatively large particles needed for single-particle tracking can in principle alter the very dynamics under study. Here, we use a method that makes it possible to investigate plasmamembrane proteins by means of small molecular labels, specifically single GFP constructs. First, fast imaging of the region of interest on the membrane is performed. For each time delay in the resulting stack of images the average spatial correlation function is calculated. We show that by fitting the series of correlation functions, the actual protein "diffusion law" can be obtained directly from imaging, in the form of a mean-square displacement vs. time-delay plot, with no need for interpretative models. This approach is tested with several simulated 2D diffusion conditions and in live Chinese hamster ovary cells with a GFP-tagged transmembrane transferrin receptor, a well-known benchmark of membrane-skeleton-dependent transiently confined diffusion. This approach does not require extraction of the individual trajectories and can be used also with dim and dense molecules. We argue that it represents a powerful tool for the determination of kinetic and thermodynamic parameters over very wide spatial and temporal scales.fluorescence | protein dynamics | membrane heterogeneity | transient confinement | single molecule T he plasma-membrane "fluid mosaic" model was proposed in a seminal work by Singer and Nicholson in 1972 (1). Since then, an intense research effort has led to significant advancements; current models include the notion that membranes are crowded environments (2) with a complex topology and that they interact with the cytoskeleton and contain microdomains of different size and lipid/protein composition (3-5). Using electron tomography, the structure of the membrane skeleton on the cytoplasmic face of the plasma membrane was clarified (6). It was found that virtually all of the cytoplasmic surface is covered by the meshwork of the actin-based membrane skeleton, and that the latter is closely associated with the membrane (within 0.83 nm). Because transmembrane proteins protrude into the cytoplasm, their intracellular domains may collide with these actin filaments that can act as "fences," inducing temporary confinement of the protein within mesh domains. Transmembrane proteins are assumed to hop between these domains whenever there is space between the membrane and the actin filament owing to membrane structural fluctuations and/or when the actin filament temporarily dissociates (for further details see ref. 7). Overall, these phenomena are master regulators of specific molecular interactions involved, for instance, in cellular signaling (...

The translational motion of molecules in cells deviates from what is observed in dilute solutions. Theoretical models provide explanations for this effect but with predictions that drastically depend on the nanoscale organization assumed for macromolecular crowding agents. A conclusive test of the nature of the translational motion in cells is missing owing to the lack of techniques capable of probing crowding with the required temporal and spatial resolution. Here we show that fluorescence-fluctuation analysis of raster scans at variable timescales can provide this information. By using green fluorescent proteins in cells, we measure protein motion at the unprecedented timescale of 1 μs, unveiling unobstructed Brownian motion from 25 to 100 nm, and partially suppressed diffusion above 100 nm. Furthermore, experiments on model systems attribute this effect to the presence of relatively immobile structures rather than to diffusing crowding agents. We discuss the implications of these results for intracellular processes.