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A Protocol to Quantify Cellular Morphodynamics: From Cell Labelling to Automatic Image Analysis

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Abstract

Cellular morphodynamics can be used as markers for many physiological and pathological processes. This protocol provides a step-by-step guide to identify variations in motility and morphology within (or across) cell populations using non-invasive live imaging and reproducible image analysis techniques such as segmentation and tracking. Detailed instructions cover all the way from cell culturing and labelling to automatic image and statistical analyses, including the definition of multiple descriptors that characterise the shape and movement of cells in a quantitative manner. All methods are available as free open-source software and illustrated by video tutorials.

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Acknowledgements

We acknowledge Marion Louveaux for advice on image analysis reproducibility and data online availability. We are grateful to the technical unit of BioImagerie Photonique of Institut Pasteur for their help with microscopy experiments. A.B.P. is part of the Pasteur-Paris University (PPU) International Ph.D. Program.

Funding

This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 665807, the Institut Carnot Pasteur Microbes & Sante (ANR 16 CARN0023-01), the Labex IBEID (ANR-10-LABX-62-IBEID), France-BioImaging infrastructure (ANR-10-INBS-04) and the program PIA INCEPTION (ANR-16-CONV-0005).

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Correspondence to Jean-Christophe Olivo-Marin .

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Movie 1: Fluorescent cells moving freely.

Movie 2: Segmented cells with Active Contours.

Movie 3: Segmented cells with Active Contours and centroid tracks.

Tutorial 1: Using Time Stamp Overlay plugin.

Tutorial 2: HK-Mean segmentation on frame 0 and color ROIs affectation.

Tutorial 3: Approximative ROIs manual design and automatic segmentation with Active Contours.

Tutorial 4: Automatic ROIs detection with HKM and segmentation with Active Contours.

Tutorial 5: Segmentation with Active Contours and cell tracks analysis with Track Manager and Track Processors.

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Manich, M., Boquet-Pujadas, A., Dallongeville, S., Guillen, N., Olivo-Marin, JC. (2020). A Protocol to Quantify Cellular Morphodynamics: From Cell Labelling to Automatic Image Analysis. In: Guillen, N. (eds) Eukaryome Impact on Human Intestine Homeostasis and Mucosal Immunology. Springer, Cham. https://doi.org/10.1007/978-3-030-44826-4_25

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