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

Area of Science:

• Biophysics
• Cell Biology
• Soft Matter Physics

Background:

• Tracking semi-flexible biopolymer networks in live tissues is key to understanding their mechanical and dynamic properties.
• Challenges in tracking arise from stochastic events like merges and splits, causing rapid local rearrangements.
• Biopolymer network dynamics are crucial for tissue organization and function.

Purpose of the Study:

• To develop a novel algorithm for tracking complex biopolymer network dynamics.
• To analyze the dynamics of actin-enriched microridges on epithelial surfaces.
• To uncover the rhythmic mechanisms underlying pattern maintenance in these networks.

Main Methods:

• Introduction of the Spatio Temporal Information on Pixel Subsets (STIPS) algorithm.
• STIPS links trajectories across frames by creating pixel subsets to handle stochastic transitions.
• Application of STIPS to analyze time-lapse microscopy images of epithelial microridges.

Main Results:

• The STIPS algorithm successfully tracks challenging biopolymer network dynamics.
• Two distinct actomyosin-based rhythmic dynamics were identified in neighboring cells.
• A 2-6.25 min pulsatile mechanism governs network fusion/fission, while cell area pulses show a ~10 min period.

Conclusions:

• The STIPS algorithm provides a robust method for analyzing dynamic biopolymer networks.
• Rhythmic cellular dynamics play a critical role in maintaining active Turing-pattern-like structures.
• Understanding these dynamics offers insights into tissue organization and mechanical properties.