Single Quantum Dot Trajectory Analysis: Beyond the Single Diffusion Mode Model

Abstract

Single quantum dots are increasingly used for single-molecule imaging, thanks to their brightness, functionalization versatility and relatively small size. So far, however, experimentalists have limited themselves to standard analysis methods developed for single-dye imaging, which are notoriously short-lived, and require statistical analysis of many trajectories. We show that there is much more information to be extracted from long single quantum dot trajectories than afforded by these standard methods. In particular, we show by simulations and using real data obtained in live cells that it is possible to identify the presence of several diffusion modes within a single trajectory and characterize these different diffusion modes quantitatively. Our approach is based on the probability distribution of square displacements measured for different time lags. We use both simulated data and live cell single quantum dot tracking data to illustrate the capability of our method and compare it to other commonly used techniques. This method was recently used to demonstrate the existence of two diffusion regimes for GPI-anchored proteins in the membrane of HeLa cells, identified respectively with diffusion in and out of raft domains (1).Reference:1. Pinaud et al., Traffic 10 (2009) 691.