Analysis of Microtubule Dynamic Instability Using a Plus End Growth Marker

Regulation of microtubule dynamics is essential for many cell biological processes, and is likely to be variable between different subcellular regions. We describe a computational approach to analyze microtubule dynamics by detecting growing microtubule plus ends. Our algorithm tracks all EB1-EGFP comets visible in an image time-lapse sequence allowing the detection of spatial patterns of microtubule dynamics. We use spatiotemporal clustering of EB1-EGFP growth tracks to infer microtubule behaviors during phases of pause and shortening. The algorithm was validated by comparison to manually tracked, homogeneously labeled microtubules, and by analysis of the effects of well-characterized inhibitors of microtubule polymerization dynamics. We used our method to analyze spatial variations of intracellular microtubule dynamics in migrating epithelial cells.