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Cell Tracking Profiler - a user-driven analysis framework for evaluating 4D live-cell imaging data

delete2020-11-23
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OA
AI
C
C. A. Mitchell
L
Lauryanne Caroff
J
José Alonso Solís-Lemus
C
Constantino Carlos Reyes‐Aldasoro
A
Alessandra Vigilante
F
Fiona Warburton
F
Fabrice de Chaumont
A
Alexandre Dufour
S
Stéphane Dallongeville
J
Jean‐Christophe Olivo‐Marín
R
Robert Knight *
DOI:10.1242/jcs.241422delete
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Abstract

Abstract

En 中文
Accurate measurements of cell morphology and behaviour are fundamentally important for understanding how disease, molecules and drugs affect cell function in vivo. Here, by using muscle stem cell (muSC) responses to injury in zebrafish as our biological paradigm, we established a 'ground truth' for muSC behaviour. This revealed that segmentation and tracking algorithms from commonly used programs are error-prone, leading us to develop a fast semi-automated image analysis pipeline that allows user-defined parameters for segmentation and correction of cell tracking. Cell Tracking Profiler (CTP) is a package that runs two existing programs, HK Means and Phagosight within the Icy image analysis suite, to enable user-managed cell tracking from 3D time-lapse datasets to provide measures of cell shape and movement. We demonstrate how CTP can be used to reveal changes to cell behaviour of muSCs in response to manipulation of the cell cytoskeleton by small-molecule inhibitors. CTP and the associated tools we have developed for analysis of outputs thus provide a powerful framework for analysing complex cell behaviour in vivo from 4D datasets that are not amenable to straightforward analysis.
Keywords:
Muscle
Zebrafish
Cell tracking
Segmentation
In vivo imaging
Phagosight
Icy
Imaris
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Journal

Journal of Cell Science cover
Journal of Cell Science
IF:
3.6
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1.1W
Citations:
3.7W

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C
City, University of London
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U
university of london
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city st georges, university of london
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