Literature DB >> 19949291

Quimp3, an automated pseudopod-tracking algorithm.

Leonard Bosgraaf1, Peter J M Van Haastert.   

Abstract

To understand movement of amoeboid cells we have developed an information tool that automatically detects protrusions of moving cells. The algorithm uses digitized cell recordings at a speed of approximately 1 image per second that are analyzed in three steps. In the first part, the outline of a cell is defined as a polygon of approximately 150 nodes, using the previously published Quimp2 program. By comparing the position of the nodes in place and time, each node contains information on position, local curvature and speed of movement. The second part uses rules for curvature and movement to define the position and time of start and end of a growing pseudopod. This part of the algorithm produces quantitative data on size, surface area, lifetime, frequency and direction of pseudopod extension. The third part of the algorithm assigns qualitative properties to each pseudopod. It decides on the origin of a pseudopod as splitting of an existing pseudopod or as extension de novo. It also decides on the fate of each pseudopod as merged with the cell body or retracted. Here we describe the pseudopod tool and present the first data based on the analysis of approximately 1,000 pseudopodia extended by Dictyostelium cells in the absence of external cues.

Mesh:

Year:  2010        PMID: 19949291      PMCID: PMC2852557          DOI: 10.4161/cam.4.1.9953

Source DB:  PubMed          Journal:  Cell Adh Migr        ISSN: 1933-6918            Impact factor:   3.405


  13 in total

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Authors:  Dirk Dormann; Thorsten Libotte; Cornelis J Weijer; Till Bretschneider
Journal:  Cell Motil Cytoskeleton       Date:  2002-08

Review 2.  Chemotaxis: signalling the way forward.

Authors:  Peter J M Van Haastert; Peter N Devreotes
Journal:  Nat Rev Mol Cell Biol       Date:  2004-08       Impact factor: 94.444

3.  A local coupling model and compass parameter for eukaryotic chemotaxis.

Authors:  Cécile Arrieumerlou; Tobias Meyer
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4.  Morphodynamic profiling of protrusion phenotypes.

Authors:  M Machacek; G Danuser
Journal:  Biophys J       Date:  2005-12-02       Impact factor: 4.033

Review 5.  Regulation of actin filament assembly by Arp2/3 complex and formins.

Authors:  Thomas D Pollard
Journal:  Annu Rev Biophys Biomol Struct       Date:  2007

Review 6.  Regulation of actin assembly associated with protrusion and adhesion in cell migration.

Authors:  Christophe Le Clainche; Marie-France Carlier
Journal:  Physiol Rev       Date:  2008-04       Impact factor: 37.312

7.  Semi-automated quantification of filopodial dynamics.

Authors:  Santiago Costantino; Christopher B Kent; Antoine G Godin; Timothy E Kennedy; Paul W Wiseman; Alyson E Fournier
Journal:  J Neurosci Methods       Date:  2008-02-26       Impact factor: 2.390

8.  A computer-assisted system for reconstructing and interpreting the dynamic three-dimensional relationships of the outer surface, nucleus and pseudopods of crawling cells.

Authors:  D Wessels; E Voss; N Von Bergen; R Burns; J Stites; D R Soll
Journal:  Cell Motil Cytoskeleton       Date:  1998

9.  The ordered extension of pseudopodia by amoeboid cells in the absence of external cues.

Authors:  Leonard Bosgraaf; Peter J M Van Haastert
Journal:  PLoS One       Date:  2009-04-22       Impact factor: 3.240

10.  Preaggregative cell motion in Dictyostelium.

Authors:  M J Potel; S A Mackay
Journal:  J Cell Sci       Date:  1979-04       Impact factor: 5.285

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  23 in total

1.  A stochastic model for chemotaxis based on the ordered extension of pseudopods.

Authors:  Peter J M Van Haastert
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

2.  Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

Authors:  Simon Gordonov; Mun Kyung Hwang; Alan Wells; Frank B Gertler; Douglas A Lauffenburger; Mark Bathe
Journal:  Integr Biol (Camb)       Date:  2015-12-11       Impact factor: 2.192

3.  Purinergic P2X4 receptors and mitochondrial ATP production regulate T cell migration.

Authors:  Carola Ledderose; Kaifeng Liu; Yutaka Kondo; Christian J Slubowski; Thomas Dertnig; Sara Denicoló; Mona Arbab; Johannes Hubner; Kirstin Konrad; Mahtab Fakhari; James A Lederer; Simon C Robson; Gary A Visner; Wolfgang G Junger
Journal:  J Clin Invest       Date:  2018-07-23       Impact factor: 14.808

4.  Allorecognition, via TgrB1 and TgrC1, mediates the transition from unicellularity to multicellularity in the social amoeba Dictyostelium discoideum.

Authors:  Shigenori Hirose; Balaji Santhanam; Mariko Katoh-Kurosawa; Gad Shaulsky; Adam Kuspa
Journal:  Development       Date:  2015-09-22       Impact factor: 6.868

Review 5.  Tools for analyzing cell shape changes during chemotaxis.

Authors:  Yuan Xiong; Pablo A Iglesias
Journal:  Integr Biol (Camb)       Date:  2010-10-01       Impact factor: 2.192

6.  Combinative in vitro studies and computational model to predict 3D cell migration response to drug insult.

Authors:  Joseph S Maffei; Jaya Srivastava; Brian Fallica; Muhammad H Zaman
Journal:  Integr Biol (Camb)       Date:  2014-10       Impact factor: 2.192

Review 7.  Excitable behavior in amoeboid chemotaxis.

Authors:  Changji Shi; Pablo A Iglesias
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-06-11

8.  A model for a correlated random walk based on the ordered extension of pseudopodia.

Authors:  Peter J M Van Haastert
Journal:  PLoS Comput Biol       Date:  2010-08-12       Impact factor: 4.475

9.  The ordered extension of pseudopodia by amoeboid cells in the absence of external cues.

Authors:  Leonard Bosgraaf; Peter J M Van Haastert
Journal:  PLoS One       Date:  2009-04-22       Impact factor: 3.240

10.  Navigation of chemotactic cells by parallel signaling to pseudopod persistence and orientation.

Authors:  Leonard Bosgraaf; Peter J M Van Haastert
Journal:  PLoS One       Date:  2009-08-31       Impact factor: 3.240

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