Robust single particle tracking in live cell time-lapse sequences

Abstract

Single particle tracking (SPT) is often the rate-limiting step in live cell imaging studies of sub-cellular dynamics. Here we present a tracking algorithm that addresses the principal challenges of SPT, namely high particle density, particle motion heterogeneity, temporary particle disappearance, and particle merging and splitting. The algorithm first links particles between consecutive frames and then links the resulting track segments into complete trajectories. Both steps are formulated as global combinatorial optimization problems whose solution identifies the overall most likely set of particle trajectories throughout the movie. Using this approach, we show that the GTPase dynamin differentially affects the kinetics of long and short-lived endocytic structures, and that the motion of CD36 receptors along cytoskeleton-mediated linear tracks increases their aggregation probability. Both applications indicate the requirement for robust and complete tracking of dense particle fields to dissect the mechanisms of receptor organization at the level of the plasma membrane.