plusTipTracker: Quantitative image analysis software for the measurement of microtubule dynamics
Introduction
Microtubules (MTs) are highly dynamic cytoskeletal polymers that stochastically switch between phases of growth, shrinkage, and pause, a behavior known as dynamic instability (Mitchison and Kirschner, 1984). While MTs are best known for their role in segregating chromosomes during cell division (Alberts et al., 2002), they also function in cell polarization and migration (Watanabe et al., 2005, Wittman and Waterman-Storer, 2001), intracellular trafficking (Caviston and Holzbaur, 2006), morphogenesis (Kirschner and Mitchison, 1986), and signaling to adhesions (Kaverina et al., 1998) and other organelles. In addition, MTs are a key drug target for the treatment of cancer (Giannakakou et al., 2000, Risinger et al., 2009) and other pathologies. Thus, quantitative characterization of MT dynamics in different cellular contexts is essential for our understanding of cell physiology and disease.
Researchers have measured MT dynamics in time-lapse images of fluorescently-labeled tubulin injected or expressed in living cells (Goodson and Wadsworth, 2004, Semenova and Rodionov, 2007). Because of the density of MTs in the cell body, this approach allows analysis of MT behavior only at the cell periphery. In recent years, imaging labeled +TIP proteins such as EB1 or EB3, which appear as comets streaking throughout the cell (Fig. 1A), has replaced these experiments as a convenient technique for visualizing MT growth across all phases of the cell cycle (Gatlin et al., 2009, Perez et al., 1999, Piehl et al., 2004, Salaycik et al., 2005, Stepanova et al., 2003, Tirnauer et al., 2002a, Tirnauer et al., 2002b). +TIPs are a subset of MT-associated proteins (MAPs) that bind directly or indirectly at the tips of growing but not shrinking or paused MT plus ends, presumably by recognizing structural or chemical differences between the plus end and the lattice (Fig. 1B) (Akhmanova and Hoogenraad, 2005, Dragestein et al., 2008, Galjart, 2010, Jiang and Akhmanova, 2011, Schuyler and Pellman, 2001). While early studies of +TIPs focused on qualitative observations, kymograph analysis and recently-developed automated particle tracking methods have enabled the estimation of nucleation rates (Piehl et al., 2004, Salaycik et al., 2005, Srayko et al., 2005) and the systematic measurement of growth speeds (Gatlin et al., 2009, Houghtaling et al., 2009, Kelly et al., 2010, Sironi et al., 2011, Smal et al., 2008).
The disadvantage of tracking MT dynamics by +TIP imaging is that comets reveal directly only the phases of MT growth. However, many of the MT-associated functions are determined by the dynamic switching between phases of growth, pause, and shrinkage. In principle, these transitions can be recovered from the growth trajectories: where two MT growth events are collinear and separated by a short time lag, it is likely that they belong to the same MT. By linking them together, parameters like shrinkage velocity or pause duration can be inferred (Fig. 1C). Matov et al. showed proof of concept for this approach (Matov et al., 2010), but a globally optimal solution, integrated into a software package, is necessary for application of the method by the broader cytoskeleton community.
Here we describe plusTipTracker, a Matlab-based open source software package enabling +TIP comet detection, track reconstruction, track visualization, sub-cellular regional analysis, and MT subpopulation analysis. The package is available from http://lccb.hms.harvard.edu and runs on either Windows or Linux operating systems. Graphical user interfaces and several stand-alone support functions allow novice Matlab users to track and visualize thousands of MTs in minutes—a vast improvement for cytoskeleton biologists who have for many years painstakingly tracked MTs by hand. In addition, batch processing and bioinformatics tools make possible the development of cell-based screens from time-lapse images, enabling diverse applications from drug discovery to mechanistic cell biology.
Section snippets
Imaging and software
plusTipTracker has been tested on a wide range of +TIP live-cell data and performs optimally on image series filmed at 60× or 100× magnification with a frame rate ranging from 0.5 to 2.0 s. The software was developed and tested using Matlab R2008a. It can be assumed that the package runs on newer Matlab versions and the website http://lccb.hms.harvard.edu will feature regular updates.
Project setup, particle detection, tracking, and track post-processing are controlled by the plusTipGetTracks
Results and discussion
The software has been applied to a wide range of data from diverse cell types and +TIP markers, and imaged with different acquisition settings (although all in 2D). Of note, the software has been applied to cells in 3D environments where light scattering produces relatively high background signals and thus reduces the achievable SNR (Myers et al., 2011). Moreover, the software is also being employed in high-content screens, where large movie data sets are processed without user intervention
Conclusions
We have introduced plusTipTracker, a user-friendly software package for the automated tracking, visualization, and analysis of MT dynamics in live cells using only +TIP markers of MT growth. Extensive validation of the general tracking algorithm used by the software package has been previously published (Jaqaman et al., 2008). Application of the sub-track linking concept to inferring MT pause and shrinkage events based on +TIP growth tracks has also been validated, using continuously labeled
Acknowledgments
We thank Ken Myers (NIH/NHLBI) for providing EB3 movies, Alexis Lomakin for the EB3 movie in Fig. 4, and Torsten Wittmann (UCSF) for providing the two-color EB1/MT movie used for validation. This work was funded by NIH Grant U01 GM67230.
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