Single molecule tracking and analysis framework including theory-predicted parameter settings

Imaging, tracking and analyzing individual biomolecules in living systems is a powerful technology to obtain quantitative kinetic and spatial information such as reaction rates, diffusion coefficients and localization maps. Common tracking tools often operate on single movies and require additional manual steps to analyze whole data sets or to compare different experimental conditions. We report a fast and comprehensive single molecule tracking and analysis framework (TrackIt) to simultaneously process several multi-movie data sets. A user-friendly GUI offers convenient tracking visualization, multiple state-of-the-art analysis procedures, display of results, and data im- and export at different levels to utilize external software tools. We applied our framework to quantify dissociation rates of a transcription factor in the nucleus and found that tracking errors, similar to fluorophore photobleaching, have to be considered for reliable analysis. Accordingly, we developed an algorithm, which accounts for both tracking losses and suggests optimized tracking parameters when evaluating reaction rates. Our versatile and extensible framework facilitates quantitative analysis of single molecule experiments at different experimental conditions.

Automated summary

The study introduces a fast and comprehensive single molecule tracking and analysis framework called TrackIt, which can simultaneously process multiple video data sets and provide users with convenient tracking visualization, various analysis procedures, result display, and data import/export functions. It was found that tracking errors and fluorophore photobleaching can affect reliable analysis, and an algorithm was developed to address this issue and optimize tracking parameters for evaluating reaction rates.