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Author Notes:

Correspondence to Timothy C. Elston: timothy_elston@med.unc.edu

Acknowledgments We thank Vinal Lakhani, Ben Ritchie, and Steph Nowotarski for initial help in establishing this collaboration.

We thank Preeti Arunapuram for her help at early stages in developing the CellGeo module MovThresh, Steve Rogers and the Rogers laboratory for D16C3 cells and reagents, and S. Wasserman and the Developmental Studies Hybridoma Bank for Dia and Ena antibodies, respectively.

We thank Andrei Karginov and Kerry Bloom for valuable discussions.

The authors declare no competing financial interests.

Subject:

Research Funding:

This work was supported by grants from National Institutes of Health R01 GM47857 (M. Peifer), R01 GM057464 (K.M. Hahn), National Institutes of Health grants GM079271, GM68820, and NCI 200079604, a grant from the Army Research Office (T.C. Elston and D. Tsygankov), and National Institutes of Health F31 fellowship 5F31NS062487 (E.A. Vitriol).

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Cell Biology
  • RHO-GTPASES
  • BARBED END
  • FILOPODIAL DYNAMICS
  • ENA/VASP PROTEINS
  • CAPPING PROTEIN
  • MYOSIN-II
  • ACTIN
  • NEURITE
  • DROSOPHILA
  • KINASE

CellGeo: A computational platform for the analysis of shape changes in cells with complex geometries

Tools:

Journal Title:

Journal of Cell Biology

Volume:

Volume 204, Number 3

Publisher:

, Pages 443-460

Type of Work:

Article | Final Publisher PDF

Abstract:

Cell biologists increasingly rely on computer-aided image analysis, allowing them to collect precise, unbiased quantitative results. However, despite great progress in image processing and computer vision, current computational approaches fail to address many key aspects of cell behavior, including the cell protrusions that guide cell migration and drive morphogenesis. We developed the open source MATLAB application CellGeo, a user-friendly computational platform to allow simultaneous, automated tracking and analysis of dynamic changes in cell shape, including protrusions ranging from filopodia to lamellipodia. Our method maps an arbitrary cell shape onto a tree graph that, unlike traditional skeletonization algorithms, preserves complex boundary features. CellGeo allows rigorous but flexible definition and accurate automated detection and tracking of geometric features of interest. We demonstrate CellGeo's utility by deriving new insights into (a) the roles of Diaphanous, Enabled, and Capping protein in regulating filopodia and lamellipodia dynamics in Drosophila melanogaster cells and (b) the dynamic properties of growth cones in catecholaminergic a- differentiated neuroblastoma cells.

Copyright information:

© 2014 Tsygankov et al.

This is an Open Access work distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License (https://creativecommons.org/licenses/by-nc-sa/3.0/).
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