PT - JOURNAL ARTICLE AU - Paolo Armando Gagliardi AU - Benjamin Grädel AU - Marc-Antoine Jacques AU - Lucien Hinderling AU - Pascal Ender AU - Andrew R. Cohen AU - Gerald Kastberger AU - Olivier Pertz AU - Maciej Dobrzyński TI - Automatic detection of spatio-temporal signalling patterns in cell collectives AID - 10.1101/2022.07.12.499734 DP - 2022 Jan 01 TA - bioRxiv PG - 2022.07.12.499734 4099 - http://biorxiv.org/content/early/2022/07/12/2022.07.12.499734.short 4100 - http://biorxiv.org/content/early/2022/07/12/2022.07.12.499734.full 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.