Branching activity switches actin network between connected and fragmented states in a myosin-dependent manner

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M-A-0-1.tar.bz2 (1.17 GB)
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Date

2021

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Abstract

Actin networks rely on nucleation mechanisms to generate new filaments because de-novo nucleation is kinetically disfavored. Branching nucleation of actin filaments by Arp2/3, in particular, is critical for actin self-organization. In this study, we use the simulation platform for active matter, MEDYAN, to generate 2000s long stochastic trajectories of actin networks, under varying Arp2/3 concentrations, in reaction volumes of biologically meaningful size (> 20m3). We find that mechanosensitive dynamics of Arp2/3 increases the abundance of short filaments and increases network treadmilling rate. By analyzing the density-fields of F-actin, we find that at low Arp2/3 concentration, F-actin is organized into a single, connected and contractile domain, while at elevated Arp2/3 levels (10nM and above), such contractile actin domains fragment into smaller domains spanning a wide range of volumes. These fragmented domains are extremely dynamic, continuously merging and splitting, owing to the high treadmilling rate of the underlying actin network. Treating the domain dynamics as a drift-diffusion process, we find that the fragmented state is stochastically favored, and the network state slowly drifts towards the fragmented state with considerable diffusion (variability) in the number of domains. We suggest that tuning the Arp2/3 concentration enables cells to transition from a globally coherent cytoskeleton, whose response involves the entire cytoplasmic network, to a fragmented cytoskeleton where domains can respond independently to local varying signals.

Notes

This repository contains the inputfiles for MEDYAN and the processed MATLAB files for three trials corresponding to M:A=0.1, 0.05 and 0.01 values. MEDYAN trajectories were converted into MATLAB files using the following code: https://github.com/achansek/readMEDYANtraj.git. Processed MATLAB files were analyzed to generate graphs for the manuscript. The codes for analyses can be found here: https://github.com/achansek/MEDYANArp23_2021.git

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