MTrack: Automated Detection, Tracking, and Analysis of Dynamic Microtubules
Date
2019
Authors
Kapoor, Varun
Hirst, William
Hentschel, Christoph
Preibisch, Stephan
Reber, Simone
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Volume Title
Publisher
Nature Publishing Group
Abstract
Microtubules are polar, dynamic filaments fundamental to many cellular processes. In vitro reconstitution approaches with purified tubulin are essential to elucidate different aspects of microtubule behavior. To date, deriving data from fluorescence 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 identifies 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.
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Source
Scientific Reports
Type
Journal article
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Access Statement
Open Access
License Rights
Creative Commons Attribution 4.0 International License