A multiscale cytoskeletal network model for shear rheological property and its evolutionary mechanism
The cytoskeleton is a dynamic biopolymer network whose shear rheological properties are crucial for cellular physiology and pathology. However, its mechanical behavior spans multiple spatiotemporal scales, and the coupling of dynamic remodeling and viscoelastic dissipation mechanisms poses a challenge for traditional models to comprehensively capture complex cellular responses. This study aims to establish a multiscale cytoskeletal network model that integrates the bio-chemo-mechanical properties of local linked proteins, the viscoelasticity of actin filaments, and their deformation states. Developing a boundary-modified finite element method with an incremental iterative algorithm, we demonstrated the dynamic remodeling of network and the resultant rheological properties of cytoskeleton by extending the predictive time scale to one thousand seconds. The results not only reproduced the short- and intermediate-term power-law creep behavior and long-term strain plateau response of the cytoskeletal network observed in shear rheological experiments, but also indicate that the synergy among the chemo-mechanical coupling of cross-linked proteins and the bending-to-tension transition of actin filaments govern both the network remodeling and its power-law response evolutionary, whereas the steady-state properties of actin filaments determine the long-term network behavior. Simulations of cancerous and drug effects show that cancer-induced softening and reduced filament viscosity lead to accelerated cytoskeletal responses and decreased apparent shear modulus, respectively; and drug-enhanced filament prestress, along with promoting association or inhibiting dissociation of cross-linked proteins, can effectively increase the steady-state shear modulus. These findings advance the understanding of the spatiotemporal evolution and pathological mechanisms of cellular mechanical responses and provide insights for regulating polymer network performance.