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Automatic detection of spatio-temporal signaling patterns in cell collectives
Journal article   Open access   Peer reviewed

Automatic detection of spatio-temporal signaling patterns in cell collectives

Paolo Armando Gagliardi, Benjamin Grädel, Marc-Antoine Jacques, Lucien Hinderling, Pascal Ender, Andrew R Cohen, Gerald Kastberger, Olivier Pertz and Maciej Dobrzyński
The Journal of cell biology, v 222(10), e202207048
02 Oct 2023
url
https://boris.unibe.ch/185140/View
Published, Version of Record (VoR)CC BY-NC-SA V4.0 Open
url
https://doi.org/10.1083/jcb.202207048View
Published, Version of Record (VoR) Open

Abstract

Increasing experimental evidence points to the physiological importance of space–time correlations in signaling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of biomolecules between cells allows the collectives to perform more complex tasks and to better tackle environmental challenges. To capture this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signaling. We demonstrate ARCOS on cell and organism collectives with space–time correlations on different scales in 2D and 3D. We made a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells hyperstimulate intercellular ERK activity waves that are largely dependent on matrix metalloproteinase intercellular signaling. ARCOS is open-source and available as R and Python packages. It also includes a plugin for the napari image viewer to interactively quantify collective phenomena without prior programming experience.

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Cell Biology
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