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. 2019 Mar 7;9(1):3794.
doi: 10.1038/s41598-018-37767-1.

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

Varun Kapoor  1   2   3 , William G Hirst  2   4 , Christoph Hentschel  2 , Stephan Preibisch  5 , Simone Reber  6   7
Affiliations

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

Varun Kapoor et al. Sci Rep. .

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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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Microtubule Dynamics by TIRF Microscopy. (a) Schematic experimental design: Stabilized microtubule seeds (red) are bound to the coverglass by antibodies and serve as nucleation points for dynamic microtubules (green). One microtubule end usually shows higher growth rates (+) than the other end (−). Total internal reflection fluorescence (TIRF) microscopy selectively excites fluorophores in a restricted volume adjacent to the glass-water interface allowing the visualization of individual microtubules. (b) TIRF microscopy image of dynamic microtubules (green) grown from stabilized seeds (red). Scale bar: 10 µm.
Figure 2
Figure 2
Microtubule Seed Detection. (a) The default algorithm to identify microtubule seeds as objects is Maximally Stable Extremal Regions (MSER). 1. Microtubule seeds detected by MSER are marked by fitted red ellipses. 2. To determine the extact end point of each microtubule seed, a sum of 2D Gaussian model is fit to the major axis of the ellipsoid. FWHM (full width at half maximum) of the PSF (point spread function) is determined experimentally. 3. Detected end points are marked by green circles. (b) Detection accuracy of microtubule seeds with a close to 100% accuracy when the distance between seeds is larger than 5 pixels. Detection error is marked in yellow. (c) Subpixel accuracy of microtubule seed end point detection depends on SNR. Values correspond to detection errors in pixels.
Figure 3
Figure 3
Microtubule Tracking. The MTrack algorithm successfully tracks straight, bending and crossing microtubules over time. (a) First, MSER detects an image region (red ellipse) for each dynamic microtubule (blue). The seed end is used as starting point (green circle) and the end point (x) is estimated by the intersection of the current MSER region boundary with the projected growth direction (dashed line) from the last successfully segmented microtubule. These two points initialize a 2D SoG fit represented by a 3rd order polynomial function. The actual length of the dynamic microtubule is calculated as the contour length (l–c) of the final fit. This approach allows tracking of bending (b) and crossing (c) microtubules. Tracking accuracy for (d) bending microtubules (SNR 10) and (e) straight microtubules (SNR 3, 5 and 10) was determined as the distance between the actual simulated position of the microtubule end (Δactual) and the position given by the tracking algorithm (Δtracked).
Figure 4
Figure 4
Automated Derivation of Parameters of Microtubule Dynamic Instability using Iterative Robust Outlier Removal. (a) Kymograph of a dynamic microtubule. (b) In the length versus time plot obtained from tracking, RANSAC first identifies the largest subset of consecutive time points that follow near-linear growth as a growth event. (c) To identify all growth events, RANSAC iteratively removes time points belonging to an identified growth event from the sampling set and repeats the RANSAC sampling until no further growth events can be identified. (d) The final graph containing detected growth and shrinkage events, as well as catastrophes and rescues.
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References

    1. Mitchison T. Localization of an exchangeable gtp binding site at the plus end of microtubules. Science. 1993;261(5124):1044–1047. doi: 10.1126/science.8102497. - DOI - PubMed
    1. Mitchison T. Dynamic instability of microtubule growth. Nature. 1984;312(5124):237–242. doi: 10.1038/312237a0. - DOI - PubMed
    1. Brouhard, G. J. & Rice, L. M. Microtubule dynamics: an interplay of biochemistry and mechanics, Nature Reviews Molecular Cell Biology, 1 (2018). - PMC - PubMed
    1. Vleugel M, Kok M, Dogterom M. Understanding force-generating microtubule systems through in vitro reconstitution. Cell adhesion & migration. 2016;10(5):475–494. doi: 10.1080/19336918.2016.1241923. - DOI - PMC - PubMed
    1. Bowne-Anderson H, Hibbel A, Howard J. Regulation of microtubule growth and catastrophe: unifying theory and experiment. Trends in cell biology. 2015;25(12):769–779. doi: 10.1016/j.tcb.2015.08.009. - DOI - PMC - PubMed

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