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Simulations of dynamically cross-linked actin networks: Morphology, rheology, and hydrodynamic interactions.

Authors :
Maxian, Ondrej
Peláez, Raúl P.
Mogilner, Alex
Donev, Aleksandar
Source :
PLoS Computational Biology. 12/6/2021, Vol. 17 Issue 12, p1-38. 38p. 1 Color Photograph, 5 Charts, 10 Graphs.
Publication Year :
2021

Abstract

Cross-linked actin networks are the primary component of the cell cytoskeleton and have been the subject of numerous experimental and modeling studies. While these studies have demonstrated that the networks are viscoelastic materials, evolving from elastic solids on short timescales to viscous fluids on long ones, questions remain about the duration of each asymptotic regime, the role of the surrounding fluid, and the behavior of the networks on intermediate timescales. Here we perform detailed simulations of passively cross-linked non-Brownian actin networks to quantify the principal timescales involved in the elastoviscous behavior, study the role of nonlocal hydrodynamic interactions, and parameterize continuum models from discrete stochastic simulations. To do this, we extend our recent computational framework for semiflexible filament suspensions, which is based on nonlocal slender body theory, to actin networks with dynamic cross linkers and finite filament lifetime. We introduce a model where the cross linkers are elastic springs with sticky ends stochastically binding to and unbinding from the elastic filaments, which randomly turn over at a characteristic rate. We show that, depending on the parameters, the network evolves to a steady state morphology that is either an isotropic actin mesh or a mesh with embedded actin bundles. For different degrees of bundling, we numerically apply small-amplitude oscillatory shear deformation to extract three timescales from networks of hundreds of filaments and cross linkers. We analyze the dependence of these timescales, which range from the order of hundredths of a second to the actin turnover time of several seconds, on the dynamic nature of the links, solvent viscosity, and filament bending stiffness. We show that the network is mostly elastic on the short time scale, with the elasticity coming mainly from the cross links, and viscous on the long time scale, with the effective viscosity originating primarily from stretching and breaking of the cross links. We show that the influence of nonlocal hydrodynamic interactions depends on the network morphology: for homogeneous meshworks, nonlocal hydrodynamics gives only a small correction to the viscous behavior, but for bundled networks it both hinders the formation of bundles and significantly lowers the resistance to shear once bundles are formed. We use our results to construct three-timescale generalized Maxwell models of the networks. Author summary: The cytoskeleton is composed of semiflexible, inextensible actin filaments, dynamic cross linkers, and molecular motors, and makes the primary contribution to the structural properties of the cell. Despite its being so fundamental to cell biology, the biological complexity of the cytoskeleton hinders our ability to understand its mechanical properties through in vitro experiments. In this paper, we perform microscopic simulations of actin fibers and transient cross linkers to quantify the principle timescales involved in the network, study how these timescales influence the morphology and rheology of the system, and examine the role of hydrodynamic interactions in cytoskeletal networks. We find three principle timescales which we associate with fiber flexibility, cross linker detachment, and network remodeling, respectively. We show that the morphology of the network is more important on longer timescales, where the viscosity of links inside of fiber bundles is enhanced. We also show that hydrodynamic interactions reduce the stress inside of bundles because of entrainment flows. Finally, we propose a continuum model which can be used to coarse-grain our agent-based simulations and enable modeling of larger systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1553734X
Volume :
17
Issue :
12
Database :
Academic Search Index
Journal :
PLoS Computational Biology
Publication Type :
Academic Journal
Accession number :
153984853
Full Text :
https://doi.org/10.1371/journal.pcbi.1009240