Nonuniform filament turnover, contractility, and bundle formation in disordered actomyosin networks

Area of Science:

• Cellular mechanics
• Biophysics
• Computational biology

Background:

• Actomyosin networks are crucial for cellular functions like contraction and structure.
• Filament turnover and mechanics significantly impact network behavior.
• Understanding these dynamics is key to cellular processes.

Purpose of the Study:

• To investigate how filament turnover and mechanics influence contractility and bundle formation in disordered actomyosin networks.
• To compare the effects of four distinct filament turnover models: uniform, biased, branching, and treadmilling.
• To explore the relationship between filament flexibility, crosslinking friction, and network properties.

Main Methods:

• Utilized a two-dimensional agent-based model for actomyosin networks.
• Simulated four simplified models of filament turnover.
• Analyzed contractility, bundle formation, and network patterns under different turnover conditions.
• Investigated the impact of filament bendability and crosslinking friction.

Main Results:

• Networks without turnover lose contractility and form static bundles.
• Introducing filament turnover enhances and prolongs contractility.
• Uniform turnover disrupts bundles but maintains contractility.
• Non-uniform turnover models (biased, branching, treadmilling) promote bundle formation while allowing sustained contractility.
• Branching at 70° favors contractility; treadmilling affects the trade-off.
• Biased turnover enhances bundles but reduces contractility persistence.
• More flexible filaments increase bundle formation; higher crosslinking friction boosts contractility.

Conclusions:

• Filament turnover is essential for persistent contractility in actomyosin networks.
• Cells can regulate contractility and bundle formation by modulating actin turnover pathways.
• Specific turnover mechanisms offer distinct trade-offs between bundle formation and contractility, providing tunable control over network mechanics.