Tracking coordinated cellular dynamics in time-lapse microscopy with ARCOS.px

Living cells contain dynamic structures that constantly change shape, merge together, split apart and travel in coordinated patterns, much like flocks of birds or schools of fish. Quantifying these complex, collective behaviours can be challenging, as most available tools are designed to follow discrete objects rather than distributed, shape-shifting pixel-level activity patterns. We developed ARCOS.px, a freely available software tool with a user-friendly graphical interface, to automatically identify and track these coordinated dynamic cellular events in time-lapse microscopy movies. The software works by taking semantically segmented binary images, in which pixels are classified as 'active' or 'inactive'. It then uses spatial clustering to group pixels into distinct coordinated events, and tracks how these events evolve over time. We tested our method by tracking cellular structures involved in cell movement and signalling in REF52 cells. Our analyses revealed how different drugs affect the behaviour of these structures and uncovered the timing relationships between different cellular components during wave-like spreading events. ARCOS.px fills a gap in current image analysis tools by enabling researchers to quantify coordinated intracellular phenomena, which was previously difficult to achieve.

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Publication Details

Journal
Journal of Cell Science
Published
2025-11-03
DOI
https://doi.org/10.1242/jcs.264022
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
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article

Tracking coordinated cellular dynamics in time-lapse microscopy with ARCOS.px

Benjamin Grädel, Olivier Pertz, Paolo Armando Gagliardi, Lucien Hinderling et al.
Journal of Cell Science
Cell Image Analysis Techniques
article

Tracking coordinated cellular dynamics in time-lapse microscopy with ARCOS.px

Benjamin Grädel, Olivier Pertz, Paolo Armando Gagliardi, Lucien Hinderling, Maciej Dobrzyński, Lea Brönnimann
article en

Abstract

Living cells contain dynamic structures that constantly change shape, merge together, split apart and travel in coordinated patterns, much like flocks of birds or schools of fish. Quantifying these complex, collective behaviours can be challenging, as most available tools are designed to follow discrete objects rather than distributed, shape-shifting pixel-level activity patterns. We developed ARCOS.px, a freely available software tool with a user-friendly graphical interface, to automatically identify and track these coordinated dynamic cellular events in time-lapse microscopy movies. The software works by taking semantically segmented binary images, in which pixels are classified as 'active' or 'inactive'. It then uses spatial clustering to group pixels into distinct coordinated events, and tracks how these events evolve over time. We tested our method by tracking cellular structures involved in cell movement and signalling in REF52 cells. Our analyses revealed how different drugs affect the behaviour of these structures and uncovered the timing relationships between different cellular components during wave-like spreading events. ARCOS.px fills a gap in current image analysis tools by enabling researchers to quantify coordinated intracellular phenomena, which was previously difficult to achieve.

Journal of Cell ScienceVol. 138(23)
University of Bern (CH), Bern University of Applied Sciences (CH), 5T Torino (Italy) (IT), Torino e-district (IT), University of Turin (IT)
Openalex Percentile: Top 77%
Cell Image Analysis Techniques
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Tracking coordinated cellular dynamics in time-lapse microscopy with ARCOS.px — Benjamin Grädel, Olivier Pertz, et al. · Journal of Cell Science (2025) | TGRS Research Map | TGRS