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

• Type of Material: Article
• Authors: Denis Tsygankov, Emory University; Colleen G. Bilancia, University of North Carolina; Eric A. Vitriol, Emory University; Klaus M. Hahn, University of North Carolina; Mark Peifer, University of North Carolina; Timothy C. Elston, University of North Carolina
• Language: English
• Date: 2014-02-03
• Publisher: Rockefeller University Press
• Publication Version: Final Published Version
• Copyright Statement: © 2014 Tsygankov et al.
• License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
• Final Published Version (URL): http://dx.doi.org/10.1083/jcb.201306067
• Title of Journal or Parent Work: Journal of Cell Biology
• Volume: 204
• Issue: 3
• Start Page: 443
• End Page: 460
• Grant/Funding Information: 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: Cell Biology; FILOPODIAL DYNAMICS; Science & Technology; ENA/VASP PROTEINS; Life Sciences & Biomedicine; ACTIN; NEURITE; BARBED END; RHO-GTPASES; DROSOPHILA; CAPPING PROTEIN; KINASE; MYOSIN-II
• Research Categories: Biology, Cell

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.