Recent evidence has shown that， in addition to rigidity， the viscous response of the extracellular matrix (ECM) significantly affects the behavior and function of cells. However， the mechanism behind such mechanosensitivity toward viscoelasticity remains unclear. In this study， we systematically examined the dynamics of motor clutches (i.e.， focal adhesions) formed between the cell and a viscoelastic substrate using analytical methods and direct Monte Carlo simulation. Interestingly， we observe that， for low ECM rigidity， maximum cell spreading is achieved at an optimal level of viscosity in which the substrate relaxation time falls between the timescale for clutch binding and its characteristic... More
Recent evidence has shown that， in addition to rigidity， the viscous response of the extracellular matrix (ECM) significantly affects the behavior and function of cells. However， the mechanism behind such mechanosensitivity toward viscoelasticity remains unclear. In this study， we systematically examined the dynamics of motor clutches (i.e.， focal adhesions) formed between the cell and a viscoelastic substrate using analytical methods and direct Monte Carlo simulation. Interestingly， we observe that， for low ECM rigidity， maximum cell spreading is achieved at an optimal level of viscosity in which the substrate relaxation time falls between the timescale for clutch binding and its characteristic binding lifetime. That is， viscosity serves to stiffen soft substrates on a timescale faster than the clutch off-rate， which enhances cell-ECM adhesion and cell spreading. On the other hand， for substrates that are stiff， our model predicts that viscosity will not influence cell spreading， since the bound clutches are saturated by the elevated stiffness. The model was tested and validated using experimental measurements on three different material systems and explained the different observed effects of viscosity on each substrate. By capturing the mechanism by which substrate viscoelasticity affects cell spreading across a wide range of material parameters， our analytical model provides a useful tool for designing biomaterials that optimize cellular adhesion and mechanosensing.
