Effect of heterogeneity on the characterization of cell membrane compartments: I. Uniform size and permeability

Observations of the motion of individual molecules in the membrane of a number of different cell types have led to the suggestion that the outer membrane of many eukaryotic cells may be effectively partitioned into microdomains. A major cause of this suggested partitioning is believed to be due to the direct/indirect association of the cytosolic face of the cell membrane with the cortical cytoskeleton. Such intimate association is thought to introduce effective hydrodynamic barriers into the membrane that are capable of frustrating molecular Brownian motion over distance scales greater than the average size of the compartment. To date, the standard analytical method for deducing compartment characteristics has relied on observing the random walk behavior of a labeled lipid or protein at various temporal frequencies and different total lengths of time. Simple theoretical arguments suggest that the presence of restrictive barriers imparts a characteristic turnover to a plot of mean squared displacement versus sampling period that can be interpreted to yield the average dimensions of the compartment expressed as the respective side lengths of a rectangle. In the following series of articles, we used computer simulation methods to investigate how well the conventional analytical strategy coped with heterogeneity in size, shape, and barrier permeability of the cell membrane compartments. We also explored questions relating to the necessary extent of sampling required (with regard to both the recorded time of a single trajectory and the number of trajectories included in the measurement bin) for faithful representation of the actual distribution of compartment sizes found using the SPT technique. In the current investigation, we turned our attention to the analytical characterization of diffusion through cell membrane compartments having both a uniform size and permeability. For this ideal case, we found that (i) an optimum sampling time interval existed for the analysis and (ii) the total length of time for which a trajectory was recorded was a key factor.