RT Journal Article SR Electronic T1 Automatic detection of spatio-temporal signalling patterns in cell collectives JF bioRxiv FD Cold Spring Harbor Laboratory SP 2022.07.12.499734 DO 10.1101/2022.07.12.499734 A1 Paolo Armando Gagliardi A1 Benjamin Grädel A1 Marc-Antoine Jacques A1 Lucien Hinderling A1 Pascal Ender A1 Andrew R. Cohen A1 Gerald Kastberger A1 Olivier Pertz A1 Maciej Dobrzyński YR 2022 UL http://biorxiv.org/content/early/2022/07/12/2022.07.12.499734.abstract AB An increasing experimental evidence points to physiological importance of space-time correlations in signalling of cell collectives. From wound healing to epithelial homeostasis to morphogenesis, coordinated activation of bio-molecules between cells allows the collectives to perform more complex tasks and better tackle environmental challenges. To understand this information exchange and to advance new theories of emergent phenomena, we created ARCOS, a computational method to detect and quantify collective signalling. We demonstrate ARCOS on cell and organism collectives with space-time correlations on different scales in 2D and 3D. We make a new observation that oncogenic mutations in the MAPK/ERK and PIK3CA/Akt pathways of MCF10A epithelial cells induce ERK activity waves with different size, duration, and frequency. The open-source implementations of ARCOS are available as R and Python packages, and as a plugin for napari image viewer to interactively quantify collective phenomena without prior programming experience.Competing Interest StatementThe authors have declared no competing interest.