Jaqaman, K. et al. Robust single-particle tracking in live-cell time-lapse sequences. Nat. Methods 5, 695-702

Department of Cell Biology, The Scripps Research Institute, 10550 N. Torrey Pines Rd, La Jolla, California 92037, USA.
Nature Methods (Impact Factor: 32.07). 08/2008; 5(8):695-702. DOI: 10.1038/nmeth.1237
Source: PubMed

ABSTRACT

Single-particle tracking (SPT) is often the rate-limiting step in live-cell imaging studies of subcellular 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 a 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.

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    • "cells) from the irrelevant ones, such as those that belong to the image background or other parts of the signal that are of no interest for the analysis. In studies that involve following the evolution of objects over time (e.g. in cell lineage reconstruction ), objects are linked throughout the complete series by tracking (Jaqaman et al., 2008). Global movements or deformations of the sample might require an alignment (or registration) step before individual features can be tracked (Wang et al., 2014). "

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