MTrack: Automated Detection, Tracking, and Analysis of Dynamic Microtubules.

Varun Kapoor, William G. Hirst, Christoph Hentschel, Stephan Preibisch & Simone Reber


In brief


Microtubules are polar, dynamic filaments fundamental to many cellular processes. In vitro reconstitution approaches with purifed tubulin are essential to elucidate diferent aspects of microtubule behavior. To date, deriving data from fuorescence microscopy images by manually creating and analyzing kymographs is still commonplace. Here, we present MTrack, implemented as a plug-in for the open-source platform Fiji, which automatically identifes and tracks dynamic microtubules with sub-pixel resolution using advanced objection recognition. MTrack provides automatic data interpretation yielding relevant parameters of microtubule dynamic instability together with population statistics. The application of our software produces unbiased and comparable quantitative datasets in a fully automated fashion. This helps the experimentalist to achieve higher reproducibility at higher throughput on a user-friendly platform. We use simulated data and real data to benchmark our algorithm and show that it reliably detects, tracks, and analyzes dynamic microtubules and achieves sub-pixel precision even at low signal-to-noise ratios