Name: using plustiptracker software to measure microtubule dynamics in xenopus laevis growth cones
Uploaded: 2014-09-07T15:00:00.000+00:00
Duration: 7 min 32 s
Description: Watch this Scientific Journal Video about Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones at JoVE.com

We thank Dr. Gaudenz Danuser and members of his lab for creating the plusTipTracker software and for helpful discussion regarding using the software, in particular Maria Bagonis and Sebastien Besson. We especially thank the Boston College Media Center for their assistance and support in the creation and editing of the video. We also thank members of the Lowery Lab for useful discussions and constructive criticism, and Abigail Antoine for proof-reading the manuscript. This work was funded by an NIH R00 MH095768 award to LAL.

This protocol and video are meant to serve as a companion to the original paper describing the software package in more detail4, as well as the Technical Report that comes with the software download on the Danuser Lab website. Readers are encouraged to review these documents carefully if there are additional questions regarding using the software.
1. Prior to Image Analysis
<ol>
	<li>Convert each time-lapse movie into a sequence of TIFF (Tagged Image File Format) image files. If there are multiple growth cones/cells in a given movie, first crop each growth cone/cell to create its own image sequence. 
	Note: This is not necessary, as individual regions-of-interest (ROI) can be selected within plusTipTracker. However, using smaller image dimensions increases the speed of the computational processing, so this step is recommended if there is significant blank space in the image.</li>
	<li>Save each TIFF series in its own folder called &#8220;images&#8221; within a path that MATLAB&#160;is set to access (note that &#8220;images&#8221; is case-sensitive). To add a new path, navigate to the relevant file directory in the &#8220;Current Folder&#8221; window, right-click on the directory icon, and select &#8220;Add to Path &#8211; Selected Folders and Sub-Folders&#8221;. It is important that the plusTipTracker software folder be added to the Path, as well.</li>
</ol>
2. plusTipGetTracks
Note: The first step in image analysis is to detect the EB1-GFP comets, link the comets into tracks, and determine the parameters of microtubule dynamics. This is obtained with the command &#8220;plusTipGetTracks&#8221;4.
<ol>
	<li>To begin analysis, open MATLAB&#160;application and type &#8220;plusTipGetTracks&#8221; into the command window. This will cause a new dialog box to appear.</li>
	<li>Click on &#8220;Set Up New Projects&#8221; and select one (or more) of the previous TIFF image series by selecting the appropriate &#8220;images&#8221; folder (or directories containing &#8220;images&#8221; folders). Upon completion of this step, a file directory (roi_1) will be created (in the same folder that holds &#8220;images&#8221;) that will contain the future data files. Note: the &#8220;Set Up New Projects&#8221; step can be completed ahead of time, during a separate session.</li>
	<li>A new window will appear: &#8220;Select a polygon, right-click on last point, and click on &#8216;Create Mask&#8217;&#8221;. Click on &#8220;OK&#8221;. The first image of the selected image series will then be displayed. Use the mouse to click and create a polygon that encompasses the entirety of the growth cone. Double click the mouse to close the polygon.</li>
	<li>Once the polygon has been closed, a dialog box will appear: &#8220;Do you want to select another ROI?&#8221; If the image has another growth cone to analyze, select &#8220;Yes&#8221;; otherwise select &#8220;No&#8221;.</li>
	<li>Select the projects that will be immediately analyzed. Click on &#8220;Select Projects&#8221; and select the folder (roi_X) to analyze.</li>
	<li>A listSelectGUI screen will appear. Select the project(s) from the left side of the screen and move them over to the right side of the screen. Click on &#8220;OK&#8221;. Choose a location to save the project list and click on &#8220;Save&#8221;.</li>
	<li>Select &#8220;Detection&#8221;, &#8220;Tracking&#8221;, and &#8220;Post-Processing&#8221;. Once these selections have been made, the right side of the dialog box will become configurable. Configure each option.
	<ol>
		<li>These parameters are used to link detected comets into MT tracks. Details for choosing these control parameters for tracking are included on pages 9-10 of the Technical Report PDF which accompanies the software package download; read this report carefully if problems are encountered. For the purposes of tracking EB1-GFP comets in Xenopus laevis growth cones, use the following Tracking Settings: Search Radius Range (pixels) 5-12, Minimum Sub-Track Length (frames) 3; Max Gap Length (frames) 8; Max Shrinkage Factor 0.8, Max angle Forward 50, Max angle Backward 10, Fluctuation Radius 2.5. These settings are shown in Figure 1.</li>
	</ol>
	 
	Note: Max Shrinkage Factor is set to reduce the number of &#8220;backward gaps&#8221; detected, as &#8220;backward gaps&#8221; are not useful to analyze in the context of growth cones, given the crowded conditions and likely errors in track linkages. Additionally, both Max Forward angle as well as Fluctuation Radius are set relatively high, as growth cone MTs exhibit small frequent translocations in addition to growths and shrinkages, and increasing these control settings allows for this increased movement during the linkage step.
	<ol>
		<li>Fill in the Post-Processing Settings depending upon the desired specific image acquisition settings.</li>
	</ol>
	</li>
	<li>Once the settings have been configured, click on &#8220;Start&#8221;. The software will run whichever settings have been selected. This may take minutes to hours, depending on the number of projects selected and their sizes. The Command Window displays the estimated time remaining for each function. When the plusTipGetTracks step is completed, the Command Window will display &#8220;Finished!&#8221; 
	Note: A long list of specific parameters of MT dynamics have now been calculated by this software (see Reference 4 for details), but for analysis of MT dynamics in growth cones, the most useful parameters to examine are MT growth track velocity (in microns/minute), growth track lifetime (in seconds), and growth track length (in microns).</li>
</ol>
3. plusTipSeeTracks
Note: Now that the microtubule tracks have been defined, the function &#8220;plustipSeeTracks&#8221; is used for track visualization4. This function can provide multiple outputs for visualization, including spatial MT dynamics maps and speed movies, but here, the focus is solely on using &#8220;Track Movies&#8221; to display MT tracks superimposed on the growth cone images. While plusTipGetTracks can analyze multiple movies at a time, plusTipSeeTracks can only analyze one movie at a time.
<ol>
	<li>Type &#8220;plusTipSeeTracks&#8221; into the command window.</li>
	<li>After the dialog box loads, click on &#8220;Select Project&#8221;. Select the parent directory containing the project to visualize and click on &#8220;Select Folder&#8221;. A new window will appear: &#8220;Select the project&#160;you want to visualize&#8221;. Choose the file to visualize and click on &#8220;OK&#8221;.</li>
	<li>Next, click on &#8220;Select Saved ROI&#8221;. Navigate to the same roi_X folder as the one selected in the previous step and select the file named &#8220;roiYX&#8221;.</li>
	<li>Click on &#8220;Select Output Directory&#8221; to designate where MATLAB&#160;will save the track visualization files. Note: We recommend using the same folder that contains the rest of the data.</li>
	<li>Select &#8220;Make Track Movie&#8221; and a screen will appear displaying all of the tracks plusTipGetTracks calculated from the +TIP comets. This step saves the tracked time series in a movie format, in the file &#8220;allTracks_X_X_X&#8221;. There is an option for saving the movie as an AVI, otherwise the default format is as a Quicktime.mov file.</li>
</ol>

4. plusTipGroupAnalysis
Note: This final function is used to create groups of movies for analysis and comparison of their MT track parameters.
<ol>
	<li>Type &#8220;plusTipGroupAnalysis&#8221; into the command window. To manually select the groups to compare, first de-select &#8220;Auto group from hierarchy&#8221;. Then, click on &#8220;Select projects&#8221;. Navigate to the parent directories containing all the roi_X folders to analyze.</li>
	<li>A listSelectGUI screen will appear. Select all of the projects to include in the groups from the left side of the screen and move them over to the right side of the screen. Click on &#8220;OK&#8221;. Choose a location to save the project list and click on &#8220;Save&#8221;.</li>
	<li>A window will appear: &#8220;Please select first group from the list&#8221;. Click on &#8220;OK&#8221;. The listSelectGUI window will display again. This time, select only those files that correspond to the first group that should be pooled together. Click on &#8220;OK&#8221;.</li>
	<li>Then, enter the group name, and click on &#8220;OK&#8221;. A window will appear: &#8220;Select another group?&#8221; Answer accordingly and continue selecting groups. A window will appear: &#8220;Select a location to save your group list&#8221;. Navigate to the location and click on &#8220;Save&#8221;.</li>
	<li>Click on &#8220;Select Output Directory&#8221; to choose where the output folders will be stored.</li>
	<li>Select which type of group analysis to conduct &#8211; whether the MT tracks should be pooled for each group or per cell analysis should be performed. The recommended statistical tests are already designated. To include all of the tracks in the analysis, de-select &#8220;Remove tracks at beginning/end of movie&#8221;. Otherwise, having this box selected removes any MT growth tracks that are in process as the movie begins or ends.</li>
	<li>After the Group Analysis selection is made, select &#8220;Compare groups&#8221;.</li>
</ol>

<ol>
	<li>Stepanova, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualization+of+microtubule+growth+in+cultured+neurons+via+the+use+of+EB3-GFP+(end-binding+protein+3-green+fluorescent+protein).">Visualization of microtubule growth in cultured neurons via the use of EB3-GFP (end-binding protein 3-green fluorescent protein).</a> The Journal of neuroscience : the official journal of the Society for Neuroscience. 23, 2655-2664 (2003).</li><li>Lee, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+microtubule+plus+end+tracking+protein+Orbit/MAST/CLASP+acts+downstream+of+the+tyrosine+kinase+Abl+in+mediating+axon+guidance.">The microtubule plus end tracking protein Orbit/MAST/CLASP acts downstream of the tyrosine kinase Abl in mediating axon guidance.</a> Neuron. , 913-926 (2004).</li><li>Purro, S. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wnt+regulates+axon+behavior+through+changes+in+microtubule+growth+directionality:+a+new+role+for+adenomatous+polyposis+coli.">Wnt regulates axon behavior through changes in microtubule growth directionality: a new role for adenomatous polyposis coli.</a> The Journal of neuroscience : the official journal of the Society for Neuroscience. 28, 8644-8654 (2008).</li><li>Applegate, K. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=plusTipTracker:+Quantitative+image+analysis+software+for+the+measurement+of+microtubule+dynamics.">plusTipTracker: Quantitative image analysis software for the measurement of microtubule dynamics.</a> Journal of structural biology. 176, 168-184 (2011).</li><li>Lowery, L. A., Faris, A. E., Stout, A., Van Vactor, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neural+Explant+Cultures+from+Xenopus+laevis.">Neural Explant Cultures from Xenopus laevis.</a> Journal of visualized experiments : JoVE. (68), e4232 (2012).</li><li>Long, J. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiparametric+analysis+of+CLASP-interacting+protein+functions+during+interphase+microtubule+dynamics.">Multiparametric analysis of CLASP-interacting protein functions during interphase microtubule dynamics.</a> Molecular and cellular biology. 33, 1528-1545 (2013).</li><li>Myers, K. A., Applegate, K. T., Danuser, G., Fischer, R. S., Waterman, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Distinct+ECM+mechanosensing+pathways+regulate+microtubule+dynamics+to+control+endothelial+cell+branching+morphogenesis.">Distinct ECM mechanosensing pathways regulate microtubule dynamics to control endothelial cell branching morphogenesis.</a> The Journal of cell biology. 192, 321-334 (2011).</li><li>Nishimura, Y., Applegate, K., Davidson, M. W., Danuser, G., Waterman, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+screening+of+microtubule+growth+dynamics+identifies+MARK2+as+a+regulator+of+leading+edge+microtubules+downstream+of+Rac1+in+migrating+cells.">Automated screening of microtubule growth dynamics identifies MARK2 as a regulator of leading edge microtubules downstream of Rac1 in migrating cells.</a> PLoS One. 7, e41413 (2012).</li><li>Akhmanova, A., Steinmetz, M. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tracking+the+ends:+a+dynamic+protein+network+controls+the+fate+of+microtubule+tips.">Tracking the ends: a dynamic protein network controls the fate of microtubule tips.</a> Nature reviews. Molecular cell biology. 9, 309-322 (2008).</li><li>Schuyler, S. C., Pellman, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule+'plus-end-tracking+proteins':+The+end+is+just+the+beginning.">Microtubule 'plus-end-tracking proteins': The end is just the beginning.</a> Cell. 105, 421-424 (2001).</li><li>Mitchison, T., Kirschner, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+instability+of+microtubule+growth.">Dynamic instability of microtubule growth.</a> Nature. 312, 237-242 (1984).</li><li>Mimori-Kiyosue, Y., Shiina, N., Tsukita, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+dynamic+behavior+of+the+APC-binding+protein+EB1+on+the+distal+ends+of+microtubules.">The dynamic behavior of the APC-binding protein EB1 on the distal ends of microtubules.</a> Current biology : CB. 10, 865-868 (2000).</li><li>Dixit, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microtubule+plus-end+tracking+by+CLIP-170+requires+EB1.">Microtubule plus-end tracking by CLIP-170 requires EB1.</a> Proceedings of the National Academy of Sciences of the United States of America. 106, 492-497 (2009).</li><li>Li, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EB1+promotes+microtubule+dynamics+by+recruiting+Sentin+in+Drosophila+cells.">EB1 promotes microtubule dynamics by recruiting Sentin in Drosophila cells.</a> The Journal of cell biology. 193, 973-983 (2011).</li><li>Maurer, S. P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EB1+accelerates+two+conformational+transitions+important+for+microtubule+maturation+and+dynamics.">EB1 accelerates two conformational transitions important for microtubule maturation and dynamics.</a> Current biology : CB. 24, 372-384 (2014).</li><li>Zanic, M., Widlund, P. O., Hyman, A. A., Howard, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synergy+between+XMAP215+and+EB1+increases+microtubule+growth+rates+to+physiological+levels.">Synergy between XMAP215 and EB1 increases microtubule growth rates to physiological levels.</a> Nature cell biology. 15, 688-693 (2013).</li><li>Lowery, L. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth+cone-specific+functions+of+XMAP215+in+restricting+microtubule+dynamics+and+promoting+axonal+outgrowth.">Growth cone-specific functions of XMAP215 in restricting microtubule dynamics and promoting axonal outgrowth.</a> Neural development. 8, 22 (2013).</li><li>Marx, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Xenopus+cytoplasmic+linker-associated+protein+1+(XCLASP1)+promotes+axon+elongation+and+advance+of+pioneer+microtubules.">Xenopus cytoplasmic linker-associated protein 1 (XCLASP1) promotes axon elongation and advance of pioneer microtubules.</a> Molecular biology of the cell. 24, 1544-1558 (2013).</li></ol>

The authors declare that they have no competing financial interests.

PlusTipTracker provides a straightforward, graphical user interface to quickly and automatically detect virtually all visible EB1-GFP comets in a cell or growth cone, link the comets into tracks, and calculate MT parameters. Other publications have reported the design of similar types of software (for example, Marx et al. also utilized quantitative analysis of tagged EB1 dynamics in growth cones18). But, this software appears to be unique in its ease of access, as it is freely downloadable from the website of the Danuser Lab, which specializes in designing open-source, turn-key software useful to the cell biological community. While access to MATLAB&#160;is required, one does not need to be fully familiar with this computer application in order to utilize the software. However, there are a few points that need to be addressed for ease of use.
First of all, one of the most common issues that arise when using the software and computer application for the first time is related to the file path. If this error occurs (with the prompt &#8220;Error using cd &#8211; Argument must contain a string. Error in formatPath&#8230;&#8221;), then the easiest solution is to ensure that the plusTipTracker software, as well as the directory with all of the &#8220;images&#8221; subdirectories, are both in the same &#8220;MATLAB&#8221; file path. It is best if these are not in the &#8220;Program Files&#8221; directory, as it has been suggested that the space in the &#8220;Program Files&#8221; name may be an issue. Related to this, it is important to note that plusTipTracker saves the file path that was utilized when first computing the plusTipGetTracks analysis, and as such, this file path must be maintained when this data is accessed and employed by another component of the software. The functions plusTipGetTracks, plusTipSeeTracks, and plusTipGroupAnalysis all use the original saved file path, and thus, trying to call those functions for a given movie, after moving the files to another path, will result in an error.
Another common error to occur during analysis is when Tracking fails during the plusTipGetTracks step. This will occur if a frame in the image series contains no detectable comets. This will completely halt the analysis and no post-processing will occur. An easy fix to circumvent this issue and allow the analysis to proceed, is to create a mock comet on the image in an area where it will not be incorrectly linked to any actual tracks. This will not impact the final track parameters, as any comet that does not exist in a minimum number of consecutive frames will be filtered out of the final analysis.
One other issue that may arise is faulty comet detection. This can usually be fixed by improving the region-of-interest selection in step 2.3. It is important to draw the region of interest closely around the cell and not to draw a wider region than is necessary. The software uses this region to determine the background used during comet detection. If comet detection is still sub-optimal with the default settings, the settings can be adjusted in the plusTipGetTracks window (during step 2.7).
After any analysis, it is critical to validate the automated track linkages by eye, using plusTipSeeTracks. Tracking settings may need to be modified to reduce the numbers of false positive or false negative comet linkages. See the original plusTipTracker documentation4 as well as the Technical Report PDF that accompanies the software download for details on optimizing the settings. The performance of this software compared to hand-tracking has previously been tested in non-neuronal cells4. Growth cones pose a slightly different challenge, however, as growth cone MTs exhibit frequent translocations in all directions17, in addition to MT growth and shrinkage. One issue that was not found to be a major concern is whether the tightly packed MTs in growth cones pose tracking difficulties17. As only a subset of MTs are in the growing phase, with EB1-GFP on the ends, resolving and tracking individual EB1-GFP comets was not problematic. However, it should be noted that these previous studies used Xenopus laevis growth cones, which were specifically chosen because of their relatively large growth cone size (approximately 10 microns), compared to other vertebrate growth cones. Using these larger growth cones allows for more accurate EB1-GFP comet analysis.
To assess the utility and accuracy of this software for analyzing EB1-GFP tracks in Xenopus laevis growth cones, we compared the experience of using plusTipTracker with hand-tracking of an identical data series (data not shown). The time it took to hand-track EB1-GFP comets in an average growth cone of 39 comet tracks (in a 1 minute time-lapse series, with 2 seconds between each frame) was over two hours, compared to two minutes with the software. The parameters obtained with the two methods were similar for MT growth velocity (7.4 microns per minute for automated tracking versus 7.0 microns per minute for hand-tracking). However, for growth lifetime and length, software analysis leads to significantly shorter tracks (by about half the time and distance). This is due to growth tracks being split by the software if a comet goes in and out of focus over time. While the human eye can easily identify that it is the same comet, the software does not. This issue is not problematic though, if one is using the software in order to compare multiple conditions. Since identical tracking parameters are used for all conditions (and assuming that comets go in and out of focus at the same rate in multiple conditions), then the relative lifetimes and lengths are still quite useful measurements for comparison. As for automated analysis error rates, these depend greatly on the quality of the images. In high signal-to-noise movies, the percent of misjoined or incorrect tracks is in the single digits. Even in lower-quality movies (where individual comets are still clearly visible by eye, but the background noise is greater), the error rates are still low enough (5-15%) that the significant time saved by using the software is worth the costs in error. This is especially the case when analyzing hundreds of growth cones (sixty to eight growth cones per condition were analyzed in a previous study17).
It is important to note that this software was designed for detecting +TIP comets that only bind to growing MT ends, such as EB1-GFP. Given that the linkage and tracking algorithms expect that comets only exist on polymerizing MTs, using this software to analyze the dynamics of a fluorescently-tagged +TIP that binds to shrinking MT ends in addition to growing ends will lead to incorrect information regarding calculated MT growth velocities.
One of the unique features of this software compared to other single-particle-tracking software, is that it takes into account known MT behaviors to calculate not only polymerization parameters, but also shrinkage parameters. It does this by linking an EB1-GFP comet that has disappeared with one that has newly formed directly behind it in the same trajectory (this is called a backgap, or bgap track). While this algorithm works well for some cell types, such as HeLa cells4, it is a less effective feature when analyzing MT dynamics in growth cones. This is because MT tracks frequently follow each other along the exact same paths in growth cones (often following along F-actin bundles), and so it is usually impossible to tell if bgap linkages are correct. For this reason, it is not recommended to utilize the bgap data outputs in growth cones.
Despite these minor caveats and issues which must be taken into consideration when using plusTipTracker (and most any automated image processing program), this software can be a very useful tool for analyzing thousands of EB1-GFP comets in a relatively short amount of time.

The goal of this method is to obtain quantitative information regarding microtubule (MT) plus-end-tracking protein (+TIP) dynamics in living growth cones. MT +TIPs are a group of proteins that localize to the plus-ends of MTs9,10. They perform a range of functions to regulate parameters of MT dynamic instability11, including rates of polymerization, catastrophe, and rescue. One well-used method for analyzing MT dynamics is to track the behavior of the +TIP EB1, which binds specifically to growing MT plus-ends1,12. EB1 is known to recruit several other proteins to growing MT plus-ends13,14, and has recently been established as a MT maturation factor15, promoting both MT growth and catastrophe frequency15,16.
Many studies of MT dynamics within growth cones have utilized hand-tracking methods to measure changes in EB1-GFP dynamics over time1-3, as EB1 localization to MT plus-ends can be used as a marker for MT polymerization. A key benefit for examining EB1-GFP comets as a proxy for MT growth is that MT dynamics can be measured even in regions of significant MT overlap. While the method of hand-tracking EB1-GFP comets has provided useful insights into MT behaviors1-3, it is time-consuming and can be biased. Additionally, as aberrant growth cone behaviors are likely the result of minute shifts in cytoskeletal dynamics, analyzing only a small subset of MTs (usually necessary when hand-tracking) may miss significant information.
Thus, we measure global MT dynamics parameters using the software package, plusTipTracker4, after the acquisition of high-resolution, live images of tagged EB1 in cultured embryonic growth cones5. This software, developed in the Danuser Lab, has been used in several studies characterizing MT dynamics in various cell types6-8. It is an open-source, user-friendly, MATLAB-based package that includes automated detection, tracking, visualization, and analysis for movies of fluorescently-labeled +TIPs. A long list of specific parameters of MT dynamics are calculated by this software (see Reference 4 for details), but for analysis of MT dynamics in growth cones, the most useful parameters are MT growth track velocity (in microns/minute), growth track lifetime (in seconds), and growth track length (in microns). The software can be downloaded directly from the Danuser Lab website (under &#8220;Software&#8221;). While the Danuser Lab currently supports a newer interface for +TIP tracking analysis, which is incorporated into a software package called u-track 2.0, the original, stand-alone software will remain available. The underlying algorithms between the two programs are the same (at least as of 2014), with only a difference of interface and analysis outputs. For the novice user with little MATLAB&#160;and/or computational analysis experience, plusTipTracker has more user-friendly features, including automated statistical parameter outputs.
Here, we describe the steps for analyzing images of EB1-GFP dynamics in cultured Xenopus laevis growth cones. This protocol was utilized in a recent paper examining MT dynamics17. See also Lowery et al. 20125 for detailed instructions regarding culturing growth cones expressing EB1-GFP. While this paper primarily focused on examining EB1-GFP dynamics in growth cones, the same protocol can be used for other cell types17. For all cell types, the time interval between frames should be between 0.5-2 sec&#160;for optimal +TIP tracking. A time interval of up to 4 seconds between frames is possible, but this increased interval time results in additional tracking errors.

<table><tbody><tr><td>plusTipTracker software</td><td>Danuser Lab</td><td>&lt;a href=&quot;http://lccb.hms.harvard.edu/software.html&quot;&gt;http://lccb.hms.harvard.edu/software.html&lt;/a&gt;</td><td>This software may be hosted by another website in the future.&amp;nbsp; If the listed site does not exist, search &quot;Danuser Lab Software&quot; on a web search engine to find the site.</td></tr><tr><td>MATLAB software</td><td>Mathworks</td><td>&lt;a href=&quot;http://www.mathworks.com/products/matlab/&quot;&gt;http://www.mathworks.com/products/matlab/&lt;/a&gt;</td><td></td></tr></tbody></table>

using plustiptracker software to measure microtubule dynamics in xenopus laevis growth cones

Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics1,2. One of the most well-known and widely-utilized +TIPs for analyzing MT dynamics is the End-Binding protein, EB1, which binds all growing MT plus-ends, and thus, is a marker for MT polymerization1. Many studies of EB1 behavior within growth cones have used time-consuming and biased computer-assisted, hand-tracking methods to analyze individual MTs1-3. Our approach is to quantify global parameters of MT dynamics using the software package, plusTipTracker4, following the acquisition of high-resolution, live images of tagged EB1 in cultured embryonic growth cones5. This software is a MATLAB-based, open-source, user-friendly package that combines automated detection, tracking, visualization, and analysis for movies of fluorescently-labeled +TIPs. Here, we present the protocol for using plusTipTracker for the analysis of fluorescently-labeled +TIP comets in cultured Xenopus laevis growth cones. However, this software can also be used to characterize MT dynamics in various cell types6-8.

Using this software as described here will provide several files of information that quantify +TIP dynamics in living cells.
The function plusTipGetTracks identifies the tracks (using example settings shown in Figure 1), and then provides parameters regarding the +TIP tracks. To view the information that the software has obtained, go into the roi_X directory that was created in step 2.2. The &#8220;feat&#8221; folder contains &#8220;overlayImages&#8221;, which is a series of images showing the detected comets. Examining these images using image analysis software can demonstrate the accuracy of comet detection. The &#8220;meta&#8221; folder also contains detailed information regarding +TIP comet statistics, including the &#8220;projData&#8221; file, as well as the &#8220;Stats&#8221; file. To view the &#8220;Stats&#8221; file, drag it into an open worksheet of a spreadsheet application. This file contains the calculated microtubule parameters for each movie (Figure 2). As noted above, a long list of specific parameters of MT dynamics are calculated by this software (see Reference 4 for details), including MT growth track velocity (in microns/minute), growth track lifetime (in seconds), and growth track length (in microns).
The function plusTipSeeTracks saves a movie of the tracked comets, which can be reviewed by opening the file &#8220;allTracks_X_X_X&#8221; (Figure 3).
The function plusTipGroupAnalysis combines multiple individual data sets into groups and creates folders (named perCell or pooledData, depending on which analysis is selected) that contain group parameter data, including histograms, plots, and spreadsheets for comparing groups and individual parameters within each group (Figure 4).
<img alt="Figure 1" fo:content-width="6in" src="/files/ftp_upload/52138/52138fig1highres.jpg" width="600" /> 
Figure 1.&#160;PlusTipGetTracks settings used for EB1-GFP comets in Xenopus laevis growth cones. This figure shows the specific settings for &#8220;Detection&#8221;, &#8220;Tracking&#8221;, and &#8220;Post-Processing&#8221; steps that may be used for the analysis of EB1-GFP comets in Xenopus laevis&#160;growth cones. The plusTipParamSweepGUI tool, available within the plusTipTracker package, may be used to optimize tracking settings for other model organisms and/or cell types7.
<img alt="Figure 2" fo:content-width="5in" src="/files/ftp_upload/52138/52138fig2highres.jpg" width="500" /> 
Figure 2.&#160;Screenshot of MT parameters obtained from plusTipGetTracks analysis. The &#8220;meta&#8221; folder, created by running plusTipGetTracks, contains information regarding +TIP comet statistics. By dragging the &#8220;Stats&#8221; file into a spreadsheet application, microtubule dynamics parameters can be examined.
<img alt="Figure 3" fo:content-width="6in" src="/files/ftp_upload/52138/52138fig3highres.jpg" width="600" /> 
Figure 3.&#160;Screenshot of MT track movie obtained from plusTipSeeTracks analysis. PlusTipSeeTracks not only allows for microtubule track visualization, but also serves as a verification tool by allowing the user to view the validity of the data acquired from plusTipGetTracks.
<img alt="Figure 4" fo:content-width="5in" src="/files/ftp_upload/52138/52138fig4highres.jpg" width="500" /> 
Figure 4.&#160;Screenshot of MT parameters obtained from plusTipGroupAnalysis. PlusTipGroupAnalysis offers the user a simple method for comparing groups and individual parameters between within each group by combining multiple individual data sets and generating statistical output, which can be examined in a spreadsheet application.

Watch this Scientific Journal Video about Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones at JoVE.com

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

The MATLAB-based, open source software package, plusTipTracker, can be used to analyze image series of fluorescently-labeled +TIPs to quantify microtubule dynamics.

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics1,2. One of the most well-known and ...

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Nanyang Technological University

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JoVE Journal

Biology

10.3K Views.  Boston College. The MATLAB-based, open source software package, plusTipTracker, can be used to analyze image series of fluorescently-labeled +TIPs to quantify microtubule dynamics.

Video: Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Microtubules are polymers of &#945;&#946;-tubulin heterodimers that organize into distinct structures in cells. Microtubule-based architectures and networks often contain subsets of microtubule arrays that differ in their dynamic properties. For example, in dividing cells, stable bundles of crosslinked microtubules coexist in close proximity to dynamic non-crosslinked microtubules. TIRF-microscopy-based in vitro reconstitution studies enable the simultaneous visualization of the dynamics of these different microtubule arrays. In this assay, an imaging chamber is assembled with surface-immobilized microtubules, which are either present as single filaments or organized into crosslinked&#160;bundles. Introduction of tubulin, nucleotides, and protein regulators allows direct visualization of associated proteins and of dynamic properties of single and crosslinked microtubules. Furthermore, changes that occur as dynamic single microtubules organize into bundles can be monitored in real-time. The method described here allows for a systematic evaluation of the activity and localization of individual proteins, as well as synergistic effects of protein regulators on two different microtubule subsets under identical experimental conditions, thereby providing mechanistic insights that are inaccessible by other methods.

Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Here, a TIRF microscopy-based in vitro reconstitution assay is presented to simultaneously quantify and compare the dynamics of two microtubule populations. A method is described to simultaneously view the collective activity of multiple microtubule-associated proteins on crosslinked microtubule bundles and single microtubules.

Microtubules are polymers of &#945;&#946;-tubulin heterodimers that organize into distinct structures in cells. Microtubule-based architectures and ...

Biochemistry

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

Several techniques have been employed for the direct visualization of cytoskeletal filaments and their associated proteins. Total-internal-reflection-fluorescence (TIRF) microscopy has a high signal-to-background ratio, but it suffers from photobleaching and photodamage of the fluorescent proteins. Label-free techniques such as interference reflection microscopy (IRM) and interferometric scattering microscopy (iSCAT) circumvent the problem of photobleaching but cannot readily visualize single molecules. This paper presents a protocol for combining IRM with a commercial TIRF microscope for the simultaneous imaging of microtubule-associated proteins (MAPs) and dynamic microtubules in vitro. This protocol allows for high-speed observation of MAPs interacting with dynamic microtubules. This improves on existing two-color TIRF setups by eliminating both the need for microtubule labeling and the need for several additional optical components, such as a second excitation laser. Both channels are imaged on the same camera chip to avoid image registration and frame synchronization problems. This setup is demonstrated by visualizing single kinesin molecules walking on dynamic microtubules.

We present a protocol for implementing interference-reflection microscopy and total-internal-reflection-fluorescence microscopy for the simultaneous imaging of dynamic microtubules and fluorescently labeled microtubule-associated proteins.

Several techniques have been employed for the direct visualization of cytoskeletal filaments and their associated proteins. ...

Microtubule Plus-End Dynamics Visualization in Huntington's Disease Model based on Human Primary Skin Fibroblasts

Transfection with a fluorescently labeled marker protein of interest in combination with time-lapse video microscopy is a classic method of studying the dynamic properties of the cytoskeleton. This protocol offers a technique for human primary fibroblast transfection, which can be difficult because of the specifics of primary cell cultivation conditions. Additionally, cytoskeleton dynamic property maintenance requires a low level of transfection to obtain a good signal-to-noise ratio without causing microtubule stabilization. It is important to take measures to protect the cells from light-induced stress and fluorescent dye fading. In the course of our work, we tested different transfection methods and protocols as well as different vectors to select the best combination of conditions suitable for human primary fibroblast studies. We analyzed the resulting time-lapse videos and calculated microtubule dynamics using ImageJ. The dynamics of microtubules' plus-ends in the different cell parts are not similar, so we divided the analysis into subgroups - the centrosome region, the lamella, and the tail of fibroblasts. Notably, this protocol can be used for in vitro analysis of cytoskeleton dynamics in patient samples, enabling the next step towards understanding the dynamics of the various disease development.

This protocol is dedicated to the microtubule plus-end visualization by EB3 protein transfection to study their dynamic properties in primary cell culture. The protocol was implemented on human primary skin fibroblasts obtained from Huntington's disease patients.

Transfection with a fluorescently labeled marker protein of interest in combination with time-lapse video microscopy is a classic method of studying the ...

Bioengineering

3D Particle Tracking for Noninvasive In Vivo Analysis of Synaptic Microtubule Dynamics in Dendrites and Neuromuscular Junctions of Drosophila

Microtubules (MTs) play critical roles in neuronal development, but many questions remain about the molecular mechanisms of their regulation and function. Furthermore, despite progress in understanding postsynaptic MTs, much less is known about the contributions of presynaptic MTs to neuronal morphogenesis. In particular, studies of in vivo MT dynamics in Drosophila sensory dendrites yielded significant insights into polymer-level behavior. However, the technical and analytical challenges associated with live imaging of the fly neuromuscular junction (NMJ) have limited comparable studies of presynaptic MT dynamics. Moreover, while there are many highly effective software strategies for automated analysis of MT dynamics in vitro and ex vivo, in vivo data often necessitate significant operator input or entirely manual analysis due to inherently inferior signal-to-noise ratio in images and complex cellular morphology. &#160;To address this, this study optimized a new software platform for automated and unbiased in vivo particle detection. Multiparametric analysis of live time-lapse confocal images of EB1-GFP labeled MTs was performed in both dendrites and the NMJ of Drosophila larvae and found striking differences in MT behaviors. MT dynamics were furthermore analyzed following knockdown of the MT-associated protein (MAP) dTACC, a key regulator of Drosophila synapse development, and identified statistically significant changes in MT dynamics compared to wild type. These results demonstrate that this novel strategy for the automated multiparametric analysis of both pre- and postsynaptic MT dynamics at the polymer-level significantly reduces human-in-the-loop criteria. The study furthermore shows the utility of this method in detecting distinct MT behaviors upon dTACC-knockdown, indicating a possible future application for functional screens of factors that regulate MT dynamics in vivo. Future applications of this method may also focus on elucidating cell type and/or compartment-specific MT behaviors, and multicolor correlative imaging of EB1-GFP with other cellular and subcellular markers of interest.&#160;

This study presents a noninvasive intravital neuronal imaging strategy combined with a new software strategy to achieve automated, unbiased tracking and analysis of in vivo microtubule (MT) plus-end dynamics in the sensory dendrites and the neuromuscular junctions of Drosophila.

Microtubules (MTs) play critical roles in neuronal development, but many questions remain about the molecular mechanisms of their regulation and function. ...

Neuroscience

Preparation of Segmented Microtubules to Study Motions Driven by the Disassembling Microtubule Ends

Microtubule depolymerization can provide force to transport different protein complexes and protein-coated beads in vitro. The underlying mechanisms are thought to play a vital role in the microtubule-dependent chromosome motions during cell division, but the relevant proteins and their exact roles are ill-defined. Thus, there is a growing need to develop assays with which to study such motility in vitro using purified components and defined biochemical milieu. Microtubules, however, are inherently unstable polymers; their switching between growth and shortening is stochastic and difficult to control. The protocols we describe here take advantage of the segmented microtubules that are made with the photoablatable stabilizing caps. Depolymerization of such segmented microtubules can be triggered with high temporal and spatial resolution, thereby assisting studies of motility at the disassembling microtubule ends. This technique can be used to carry out a quantitative analysis of the number of molecules in the fluorescently-labeled protein complexes, which move processively with dynamic microtubule ends. To optimize a signal-to-noise ratio in this and other quantitative fluorescent assays, coverslips should be treated to reduce nonspecific absorption of soluble fluorescently-labeled proteins. Detailed protocols are provided to take into account the unevenness of fluorescent illumination, and determine the intensity of a single fluorophore using equidistant Gaussian fit. Finally, we describe the use of segmented microtubules to study microtubule-dependent motions of the protein-coated microbeads, providing insights into the ability of different motor and nonmotor proteins to couple microtubule depolymerization to processive cargo motion.

Microtubules are inherently unstable polymers, and their switching between growth and shortening is stochastic and difficult to control. Here we describe protocols using segmented microtubules with photoablatable stabilizing caps. Depolymerization of segmented microtubules can be triggered with high temporal and spatial resolution, thereby assisting analysis of motions with the disassembling microtubule ends.

Microtubule depolymerization can provide force to transport different protein complexes and protein-coated beads in vitro. The underlying mechanisms are ...

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes depend on the advances of growth cones that located at the tips of neurites. Axonal growth cones generate driving forces by sensing their local microenvironment and modulating cytoskeletal dynamics and actin-adhesion coupling (clutch coupling). Decades of research have led to the identification of guidance molecules, their receptors, and downstream signaling cascades for regulating neuronal migration and axonal guidance; however, the molecular machineries required for generating forces to drive growth cone advance and navigation are just beginning to be elucidated. At the leading edge of neuronal growth cones, actin filaments undergo retrograde flow, which is powered by actin polymerization and actomyosin contraction. A clutch coupling between F-actin retrograde flow and adhesive substrate generates traction forces for growth cone advance. The present study describes a detailed protocol for monitoring F-actin retrograde flow by single speckle imaging. Importantly, when combined with an F-actin marker Lifeact, this technique can quantify 1) the F-actin polymerization rate and 2) the clutch coupling efficiency between F-actin retrograde flow and the adhesive substrate. Both are critical variables for generating forces for growth cone advance and navigation. In addition, the present study describes a detailed protocol of traction force microscopy, which can quantify 3) traction force generated by growth cones. Thus, by coupling the analyses of&#160;single speckle imaging and traction force microscopy, investigators can monitor the molecular mechanics underlying growth cone advance and navigation.

To advance, growth cones must exert traction forces against the external environment. The generation of traction forces is dependent on actin dynamics and clutch coupling. The present study describes methods for analyzing actin dynamics, clutch coupling and traction forces for growth cone advance.

To establish functional networks, neurons must migrate to their appropriate destinations and then extend axons toward their target cells. These processes ...

High-resolution Time-lapse Imaging and Automated Analysis of Microtubule Dynamics in Living Human Umbilical Vein Endothelial Cells

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes within individual endothelial cells (ECs). These processes are critical for homeostatic maintenance such as wound healing, and are also crucial in promoting tumor growth and metastasis. EC morphology is defined by the organization of the cytoskeleton, a tightly regulated system of actin and microtubule (MT) dynamics that is known to control EC branching, polarity and directional migration, essential components of angiogenesis. To study MT dynamics, we used high-resolution fluorescence microscopy coupled with computational image analysis of fluorescently-labeled MT plus-ends to investigate MT growth dynamics and the regulation of EC branching morphology and directional migration. Time-lapse imaging of living Human Umbilical Vein Endothelial Cells (HUVECs) was performed following transfection with fluorescently-labeled MT End Binding protein 3 (EB3) and Mitotic Centromere Associated Kinesin (MCAK)-specific cDNA constructs to evaluate effects on MT dynamics. PlusTipTracker software was used to track EB3-labeled MT plus ends in order to measure MT growth speeds and MT growth lifetimes in time-lapse images. This methodology allows for the study of MT dynamics and the identification of how localized regulation of MT dynamics within sub-cellular regions contributes to the angiogenic processes of EC branching and migration.

Protocols for Human Umbilical Vein Endothelial Cell (HUVEC) culture, transient transfection of fluorescently-labeled markers of microtubule growth, live-cell imaging and automated analysis of interphase microtubule growth dynamics are detailed.

The physiological process by which new vasculature forms from existing vasculature requires specific signaling events that trigger morphological changes ...

High-resolution Imaging and Analysis of Individual Astral Microtubule Dynamics in Budding Yeast

Dynamic microtubules are fundamental to many cellular processes, and accurate measurements of microtubule dynamics can provide insight into how cells regulate these processes and how genetic mutations impact regulation. The quantification of microtubule dynamics in metazoan models has a number of associated challenges, including a high microtubule density and limitations on genetic manipulations. In contrast, the budding yeast model offers advantages that overcome these challenges. This protocol describes a method to measure the dynamics of single microtubules in living yeast cells. Cells expressing fluorescently tagged tubulin are adhered to assembled slide chambers, allowing for stable time-lapse image acquisition. A detailed guide for high-speed, four-dimensional image acquisition is also provided, as well as a protocol for quantifying the properties of dynamic microtubules in confocal image stacks. This method, combined with conventional yeast genetics, provides an approach that is uniquely suited for quantitatively assessing the effects of microtubule regulators or mutations that alter the activity of tubulin subunits.

Budding yeast is an advantageous model for studying microtubule dynamics in vivo due to its powerful genetics and the simplicity of its microtubule cytoskeleton. The following protocol describes how to transform and culture yeast cells, acquire confocal microscopy images, and quantitatively analyze microtubule dynamics in living yeast cells.

Dynamic microtubules are fundamental to many cellular processes, and accurate measurements of microtubule dynamics can provide insight into how cells ...

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex signaling mechanisms underlying filopodial initiation, elongation and subsequent stabilization or retraction, it is crucial to determine the spatio-temporal protein activity in these dynamic structures. To analyze protein function in filopodia, we recently developed a semi-automated tracking algorithm that adapts to filopodial shape-changes, thus allowing parallel analysis of protrusion dynamics and relative protein concentration along the whole filopodial length. Here, we present a detailed step-by-step protocol for optimized cell handling, image acquisition and software analysis. We further provide instructions for the use of optional features during image analysis and data representation, as well as troubleshooting guidelines for all critical steps along the way. Finally, we also include a comparison of the described image analysis software with other programs available for filopodia quantification. Together, the presented protocol provides a framework for accurate analysis of protein dynamics in filopodial protrusions using image analysis software.

We present a software solution for semi-automated tracking of relative protein concentration along the length of dynamic cellular protrusions.

Filopodia are dynamic, finger-like cellular protrusions associated with migration and cell-cell communication. In order to better understand the complex ...

Measurement of Microtubule Dynamics by Spinning Disk Microscopy in Monopolar Mitotic Spindles

We describe a modification of an established method to determine microtubule dynamics in living cells. The protocol is based on the expression of a genetically encoded marker for the positive ends of microtubules (EB3 labelled with tdTomato fluorescent protein) and high-speed, high-resolution, live-cell imaging using spinning disk confocal microscopy. Cell cycle synchronization and increased density of microtubules are achieved by inhibiting centrosomal separation in mitotic cells, and analysis of growth is performed using open-source U-Track software. The use of a bright and red-shifted fluorescent protein, in combination with the lower laser power and reduced exposure time required for spinning disk microscopy reduce phototoxicity and the probability of light-induced artifacts. This allows for imaging a larger number of cells in the same preparation while maintaining the cells in a growth medium under standard culture conditions. Because the analysis is performed in a supervised automatic fashion, the results are statistically robust and reproducible.

Here we present a robust and detailed method of microtubule dynamics analysis in cells synchronized in prometaphase using live-cell spinning disk confocal microscopy and MATLAB-based image processing.

We describe a modification of an established method to determine microtubule dynamics in living cells. The protocol is based on the expression of a ...

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

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Simultaneous Visualization of the Dynamics of Crosslinked and Single Microtubules In Vitro by TIRF Microscopy

Simultaneous Interference Reflection and Total Internal Reflection Fluorescence Microscopy for Imaging Dynamic Microtubules and Associated Proteins

Microtubule Plus-End Dynamics Visualization in Huntington's Disease Model based on Human Primary Skin Fibroblasts

3D Particle Tracking for Noninvasive In Vivo Analysis of Synaptic Microtubule Dynamics in Dendrites and Neuromuscular Junctions of Drosophila

Preparation of Segmented Microtubules to Study Motions Driven by the Disassembling Microtubule Ends

Analyses of Actin Dynamics, Clutch Coupling and Traction Force for Growth Cone Advance

High-resolution Time-lapse Imaging and Automated Analysis of Microtubule Dynamics in Living Human Umbilical Vein Endothelial Cells

High-resolution Imaging and Analysis of Individual Astral Microtubule Dynamics in Budding Yeast

A Graphical User Interface for Software-assisted Tracking of Protein Concentration in Dynamic Cellular Protrusions

Measurement of Microtubule Dynamics by Spinning Disk Microscopy in Monopolar Mitotic Spindles