STIPS algorithm enables tracking labyrinthine patterns and reveals distinct rhythmic dynamics of actin microridges

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Abstract

Tracking and motion analyses of semi-flexible biopolymer networks from time-lapse microscopy images are important tools that enable quantitative measurements to unravel dynamical and mechanical properties of biopolymers in living tissues important for understanding their organization and function. Biopolymer networks pose tracking challenges as they exhibit continuous stochastic transitions in the form of merges/splits resulting in local neighborhood rearrangements over short time/length scales. We propose the STIPS algorithm ( S patio T emporal I nformation on P ixel S ubsets) that tracks merging/splitting events in self-organizing patterning systems, by creating pixel subsets to link trajectories across consecutive frames. We demonstrate our method on actin-enriched protrusions, the ‘microridges’ that form dynamic labyrinthine patterns on outer surfaces of squamous cell epithelia, mimicking ‘active Turing-patterns’. We uncovered two distinct actomyosin based rhythmic dynamics within neighboring cells; common pulsatile mechanism between 2-5.9 mins period governing both fusion and fission contributing to pattern maintenance and cell area pulses predominantly exhibiting ∼10 mins period.

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