Nonlinear Mechanics of Biopolymer Networks

The progress of modern biology demands an interdisciplinary approach to research, bridging the gap between previously disparate fields. This thesis presents a study of the elasticity and microstructure of neurofilaments, which are the primary constituents of neurons, providing the essential mechanical support to resist external stresses. To probe the underlying mechanical properties of neurofilaments, we use a model system composed of reconstituted neurofilaments purfied from bovine spinal cords. We use a combination of bulk rheology, microrheology, and confocal microscopy to determine both mechanical and structural properties of networks of neurofilaments at a variety of length scales. Our focus is to elucidate the origins of elasticity in these networks. A remarkable feature of neurofilament networks is the pronounced nonlinearity in the elastic response; its characterization is essential to understanding the mechanical properties of the network. Such nonlinear response is highly unusual in typical soft materials and thus demands careful measurement techniques to fully characterize. We present a new method, inertio-elastic oscillations, to characterize nonlinear elasticity and dissipation at each stress, and show that this method has advantages over other techniques. This method utilizes the coupling of the sample’s elasticity to the rheometer’s inertia to probe the viscoelasticity of the network. We combine this technique with other measurements of both the linear and nonlinear elasticity to probe the viscoelastic properties of neurofilament networks. These networks are soft solids that exhibit dramatic strain stiffening above critical strains of 30-70%. Their viscoelastic properties are remarkably similar to that of cross-linked networks of filamentous acitn, another major cytoskeletal network. However, there are no known cross-linking proteins for neurofilaments; instead, we find that surprisingly, divalent ions, such as Mg, Ca, and Zn, act as effective cross-linkers for neurofilament networks, controlling their solid-like elastic response. Moreover, similar cross-linking behavior by divalent ions is observed for networks of a second intermediate filament, vimentin, confirming the generality of ionic cross-linking. We show that the elasticity of neurofilament networks is entropic in origin and is consistent with a model for cross-linked semiflexible networks, which we use to quantify the cross-linking by divalent ions.