Both animal and plant tissue exhibit a nonlinear rheological phenomenon known as compression stiffening, or an increase in moduli with increasing uniaxial compressive strain. Does such a phenomenon exist in single cells, which are the building blocks of tissues? One expects an individual cell to compression soften since the semiflexible biopolymer-based cytoskeletal network maintains the mechanical integrity of the cell and in vitro semiflexible biopolymer networks typically compression soften. To the contrary, we find that mouse embryonic fibroblasts (mEFs) compression stiffen under uniaxial compression via atomic force microscopy studies. To understand this finding, we uncover several potential mechanisms for compression stiffening. First, we study a single semiflexible polymer loop modeling the actomyosin cortex enclosing a viscous medium modeled as an incompressible fluid. Second, we study a two-dimensional semiflexible polymer/fiber network interspersed with area-conserving loops, which are a proxy for vesicles and fluid-based organelles. Third, we study two-dimensional fiber networks with angular-constraining crosslinks, i.e. semiflexible loops on the mesh scale. In the latter two cases, the loops act as geometric constraints on the fiber network to help stiffen it via increased angular interactions. We find that the single semiflexible polymer loop model agrees well with the experimental cell compression stiffening finding until approximately 35% compressive strain after which bulk fiber network effects may contribute. We also find for the fiber network with area-conserving loops model that the stress–strain curves are sensitive to the packing fraction and size distribution of the area-conserving loops, thereby creating a mechanical fingerprint across different cell types. Finally, we make comparisons between this model and experiments on fibrin networks interlaced with beads as well as discuss implications for single cell compression stiffening at the tissue scale.
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Bioinspired Fiber Networks With Tunable Mechanical Properties by Additive Manufacturing
Abstract Soft bioinspired fiber networks offer great potential in biomedical engineering and material design due to their adjustable mechanical behaviors. However, existing strategies to integrate modeling and manufacturing of bioinspired networks do not consider the intrinsic microstructural disorder of biopolymer networks, which limits the ability to tune their mechanical properties. To fill in this gap, we developed a method to generate computer models of aperiodic fiber networks mimicking type I collagen ready to be submitted for additive manufacturing. The models of fiber networks were created in a scripting language wherein key geometric features like connectivity, fiber length, and fiber cross section could be easily tuned to achieve desired mechanical behavior, namely, pretension-induced shear stiffening. The stiffening was first predicted using finite element software, and then a representative network was fabricated using a commercial 3D printer based on digital light processing technology using a soft resin. The stiffening response of the fabricated network was verified experimentally on a novel test device capable of testing the shear stiffness of the specimen under varying levels of uniaxial pretension. The resulting data demonstrated clear pretension-induced stiffening in shear in the fabricated network, with uniaxial pretension of 40% resulting in a factor of 2.65 increase in the small strain shear stiffness. The strategy described in this article addresses current challenges in modeling bioinspired fiber networks and can be readily integrated with advances in fabrication technology to fabricate materials truly replicating the mechanical response of biopolymer networks.
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- Award ID(s):
- 1749400
- PAR ID:
- 10422331
- Date Published:
- Journal Name:
- Journal of Applied Mechanics
- Volume:
- 90
- Issue:
- 8
- ISSN:
- 0021-8936
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1115/1.4062451
