Single-particle tracking: the distribution of diffusion coefficients

Abstract

In single-particle tracking experiments, the diffusion coefficient D may be measured from the trajectory of an individual particle in the cell membrane. The statistical distribution of single-trajectory diffusion coefficients is examined by Monte Carlo calculations. The width of this distribution may be useful as a measure of the heterogeneity of the membrane and as a test of models of hindered diffusion in the membrane. For some models, the distribution of the short-range diffusion coefficient is much narrower than the observed distribution for proteins diffusing in cell membranes. To aid in the analysis of single-particle tracking measurements, the distribution of D is examined for various definitions of D and for various trajectory lengths.

Nonergodic subdiffusion from transient interactions with heterogeneous partners

“…The broad diffusivity distribution of our model is in agreement with several experimental reports [17]. In addition, it accounts for the presence of heterogeneity in interaction products (i.e., formation of clusters with a varying number of molecules and thus different diffusivities) as well as in interacting partners (i.e., interactions with a pool of chemically different species with different diffusivity) that can be found in the cellular environment.…”

Single-Molecule Imaging on Living Bacterial Cell Surface by High-Speed AFM

“…Wade et al reported that the diffusion constants of molecules in the cell membrane follow a lognormal distribution. 22,23 In our study, the distribution of diffusion constants was fitted with a lognormal distribution and the mean diffusion constant was 3.2 ± 0.4 nm 2 /s. This is the first report of the observation of molecular dynamics on a living cell surface using HS-AFM.…”

Activity-Dependent Movements of Postsynaptic Scaffolds at Inhibitory Synapses

“…The VeGe fluorescence mass center was tracked with MIA using a shape recognition algorithm. Values of the mean square displacement (MSD) were calculated from the resulting trajectories with Matlab (The Mathworks S.A.S., Sèvres, France) applying the relation MSD (ndt) (Saxton, 1997), where x i and y i are the coordinates of an object on frame i, N is the total number of steps in the trajectory, dt is the time interval between two successive frames, and ndt is the time interval over which displacement is averaged. The diffusion coefficients were calculated by computing the MSD curves.…”

“…The trajectories were typically composed of 100 points. The MSD was considered over the first 30 time intervals to avoid large statistical fluctuations (Saxton, 1997). To compare gephyrin cluster dynamics on short and longer time scales in different conditions, two apparent diffusion coefficients D ini and D 20 -30 were derived by fitting the MSD curve with the linear function MSD(t) ϭ 4 D a-b ϫ t ϩ C a-b , between a ϭ 1 and b ϭ 4, a ϭ 20 and b ϭ 30, respectively.…”