Automated Tracking of Cell Migration with Rapid Data Analysis

Brian J. DuChez1

1 Cell Biology Section, National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, Maryland
Publication Name:  Current Protocols in Cell Biology
Unit Number:  Unit 12.12
DOI:  10.1002/cpcb.28
Online Posting Date:  September, 2017
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Abstract

Cell migration is essential for many biological processes including development, wound healing, and metastasis. However, studying cell migration often requires the time‐consuming and labor‐intensive task of manually tracking cells. To accelerate the task of obtaining coordinate positions of migrating cells, we have developed a graphical user interface (GUI) capable of automating the tracking of fluorescently labeled nuclei. This GUI provides an intuitive user interface that makes automated tracking accessible to researchers with no image‐processing experience or familiarity with particle‐tracking approaches. Using this GUI, users can interactively determine a minimum of four parameters to identify fluorescently labeled cells and automate acquisition of cell trajectories. Additional features allow for batch processing of numerous time‐lapse images, curation of unwanted tracks, and subsequent statistical analysis of tracked cells. Statistical outputs allow users to evaluate migratory phenotypes, including cell speed, distance, displacement, and persistence, as well as measures of directional movement, such as forward migration index (FMI) and angular displacement. © 2017 by John Wiley & Sons, Inc.

Keywords: automated tracking; cell tracking; cell migration; time‐lapse imaging

     
 
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Table of Contents

  • Introduction
  • Basic Protocol 1: Obtaining Cell Tracks
  • Support Protocol 1: Obtaining FastTracks Program Files
  • Support Protocol 2: Delete Cell Trajectories From the Tracks Data Set
  • Support Protocol 3: Batch Processing
  • Support Protocol 4: Masking a Region of Interest (ROI)
  • Basic Protocol 2: Cell Migration Statistics
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

Basic Protocol 1: Obtaining Cell Tracks

  Materials
  • Windows, 64‐bit
  • Downloaded FastTracks program (see protocol 2 for instructions to install the automated tracking and rapid data analysis software, FastTracks)

Support Protocol 1: Obtaining FastTracks Program Files

  Materials
  • Windows, 64‐bit

Support Protocol 2: Delete Cell Trajectories From the Tracks Data Set

  Materials
  • Windows, 64‐bit
  • Downloaded FastTracks program (see protocol 2 for instructions to install the automated tracking and rapid data analysis software, FastTracks)

Support Protocol 3: Batch Processing

  Materials
  • Windows, 64‐bit
  • Downloaded FastTracks program (see protocol 2 for instructions to install the automated tracking and rapid data analysis software, FastTracks)

Support Protocol 4: Masking a Region of Interest (ROI)

  Materials
  • Windows, 64‐bit
  • Downloaded FastTracks program (see protocol 2 for instructions to install the automated tracking and rapid data analysis software, FastTracks)

Basic Protocol 2: Cell Migration Statistics

  Materials
  • Windows, 64‐bit
  • Downloaded FastTracks program (see protocol 2 for instructions to install the automated tracking and rapid data analysis software, FastTracks)
  • Tracks data set ( protocol 1)
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Figures

Videos

Literature Cited

  Cordelieres, F. P., Petit, V., Kumasaka, M., Debeir, O., Letort, V., Gallagher, S. J., & Larue, L. (2013). Automated cell tracking and analysis in phase‐contrast videos (iTrack4U): Development of Java software based on combined mean‐shift processes. PLoS One, 8, e81266. doi: 10.1371/journal.pone.0081266.
  Crocker, J. C., & Grier, D. G. (1996). Methods of digital video microscopy for colloidal studies. Journal of Colloid and Interface Science, 179, 298–310. doi: 10.1006/jcis.1996.0217.
  Friedl, P., & Alexander, S. (2011). Cancer invasion and the microenvironment: Plasticity and reciprocity. Cell, 147, 992–1009. doi: 10.1016/j.cell.2011.11.016.
  Hand, A. J., Sun, T., Barber, D. C., Hose, D. R., & MacNeil, S. (2009). Automated tracking of migrating cells in phase‐contrast video microscopy sequences using image registration. Journal of Microscopy, 234, 62–79. doi: 10.1111/j.1365‐2818.2009.03144.x.
  Manzo, C., & Garcia‐Parajo, M. F. (2015). A review of progress in single particle tracking: From methods to biophysical insights. Reports on Progress in Physics, 78(12)124601. doi: 10.1088/0034‐4885/78/12/124601
  Masuzzo, P., Van Troys, M., Ampe, C., & Martens, L. (2016). Taking Aim at Moving Targets in Computational Cell Migration. Trends in Cell Biology, 26, 88–110. doi: 10.1016/j.tcb.2015.09.003.
  Mayor, R., & Theveneau, E. (2013). The neural crest. Development (Cambridge, England), 140, 2247–2251. doi: 10.1242/dev.091751.
  Meijering, E., Dzyubachyk, O., Smal, I., & van Cappellen, W. A. (2009). Tracking in cell and developmental biology. Seminars in Cell & Developmental Biology, 20, 894–902. doi: 10.1016/j.semcdb.2009.07.004.
  Piccinini, F., Kiss, A., & Horvath, P. (2016). CellTracker (not only) for dummies. Bioinformatics, 32, 955–957. doi: 10.1093/bioinformatics/btv686.
  Rajan, S. S., Liu, H. Y., & Vu, T. Q. (2008). Ligand‐bound quantum dot probes for studying the molecular scale dynamics of receptor endocytic trafficking in live cells. ACS Nano, 2, 1153–1166. doi: 10.1021/nn700399e.
  Sako, Y., Minoghchi, S., & Yanagida, T. (2000). Single‐molecule imaging of EGFR signalling on the surface of living cells. Nature Cell Biology, 2, 168–172. doi: 10.1038/35004044.
  Schutz, G. J., Kada, G., Pastushenko, V. P., & Schindler, H. (2000). Properties of lipid microdomains in a muscle cell membrane visualized by single molecule microscopy. EMBO Journal, 19, 892–901. doi: 10.1093/emboj/19.5.892.
  Singer, A. J., & Clark, R. A. (1999). Cutaneous wound healing. New England Journal of Medicine, 341, 738–746. doi: 10.1056/NEJM199909023411006.
Internet Resources
  http://site.physics.georgetown.edu/matlab/
  The Matlab Particle Tracking Code Repository contains MATLAB files adapted from IDL particle tracking software. Several of these files are used by FastTracks.
  http://www.physics.emory.edu/faculty/weeks//idl/index.html
  Tutorial of IDL particle tracking software and links to alternate particle tracking methods.
  http://www.celltracker.website/index.html
  Description and downloads for the automated cell tracking software CellTracker.
  https://sites.google.com/site/itrack4usoftware/home
  iTrack4U downloads for automated tracking of phase‐contrast videos.
  https://tinevez.github.io/msdanalyzer/
  Tutorial and program files for understanding and evaluating mean square displacement of tracked particles.
  http://imagej.net/TrackMate
  Documentation and tutorials for using the ImageJ plug‐in: TrackMate.
  http://icy.bioimageanalysis.org/plugin/Spot_Tracking
  Documentation and tutorials for using the Icy plugin: Spot Tracking.
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