Localization Error and Fitting Model Evaluation in Single Particle Tracking

Abstract

Single Particle Tracking (SPT) is a powerful technique for uncovering molecular dynamics in lipid membrane biophysics, as well as in many other fields. Thus far, it has been successfully used to discover non-Brownian motion phenomena such as transient confined (also known as hop) diffusion of lipids and membrane proteins in the plasma membrane by accessing high framerates (103-104 fps) and claimed localization accuracies in the nanometre range. However, most of literature reporting high-speed SPT data relies on analysis protocols that are very susceptible to underestimations of the effects of localization errors; whose consequences are particularly pronounced at high framerates. Therefore, we propose a different approach to estimate such errors, and a statistically-driven procedure for determining the appropriate mode of motion fitting model. Using Interferometric Scattering (iSCAT) microscopy, we were able to collect high sampling frequency data of immobile and moving particles in different situations, to use for our analysis. First, we compare the effect of Signal-to-Noise Ratio on the localization precision of different immobile particles (gold nanoparticles, single proteins). Next, we show the effect of camera blur and localization error on the same particles diffusing on quasi-homogeneous Supported Lipid Bilayers (SLB), to develop an error correction method and a fitting goodness discrimination method of fitting SPT data. These last results are compared to Fluorescence Correlation Spectroscopy (FCS) measurements as a control for the values of diffusion rate. Finally, we acquired data of gold nanoparticle-tagged lipids diffusing on epithelial cell membranes, and apply the newly developed method to these data, to determine which model is the best statistical fit for cell membrane dynamics. In conclusion, the analysis workflow we propose, based on statistical methods rather than previous knowledge, could increase reliability and accuracy of future SPT measurements at high spatiotemporal resolution.