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

Mitchell, C. J., Caroff, L., Solis-Lemus, J. A., Reyes-Aldasoro, C. C. ORCID: 0000-0002-9466-2018, Vigilante, A., Warburton, F., de Chaumont, F., Dufour, A., Dallongeville, S., Olivo-Marin, J-C. and Knight, R. (2020). Cell Tracking Profiler: a user-driven analysis framework for evaluating 4D live cell imaging data. Journal of Cell Science (JCS), doi: 10.1242/jcs.241422

Abstract

Accurate measurements of cell morphology and behaviour are fundamentally important for understanding how disease, molecules and drugs affect cell function in vivo Using muscle stem cell (muSC) responses to injury in zebrafish as our biological paradigm we established a ground truth for muSC behaviour. This revealed 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-lapsed 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.

Publication Type: Article
Additional Information: © 2020. Published by The Company of Biologists Ltd
Publisher Keywords: muscle, zebrafish, cell tracking, segmentation, in vivo imaging, Phagosight, Icy, Imaris
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QH Natural history > QH301 Biology
T Technology
Departments: School of Mathematics, Computer Science & Engineering > Computer Science
Date Deposited: 27 Oct 2020 15:28
URI: https://openaccess.city.ac.uk/id/eprint/25147
[img] Text - Accepted Version
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