论文标题

纤维网络中的非线性机械密度

Nonlinear mechanosensation in fiber networks

论文作者

Berthier, Estelle, Yang, Haiqian, Guo, Ming, Ronceray, Pierre, Broedersz, Chase P.

论文摘要

在各种生理环境中,真核细胞粘附在具有复杂非线性力学的无序网络上的细胞外基质(ECM)。这样的细胞可以执行机械敏:使用局部力探测它们可以测量并响应其底物的机械性能。然而,尚不清楚ECM在细胞尺度下的机械复杂性如何影响机械敏化。在这里,我们研究了ECM的固有结构障碍和非线性弹性反应所施加的机械敏化的物理限制。使用无序纤维网络的理论框架,我们发现细胞可以通过较小的探测力在局部感知的极端机械异质性会随着力增加而大大降低。具体而言,我们预测,遵循对本构细节的通用能力定律不敏感,机械敏化的准确性会大大提高,我们使用胶原蛋白和纤维蛋白凝胶中的微流变实验进行定量确认。我们通过引入非线性机械敏化的通用模型,基于与纤维屈曲相关的新线性长度尺度的想法,通过引入非线性机械敏化的通用模型来提供对这种行为的概念见解。这种依赖力的长度尺度增强了进行局部机械测量的范围,从而平均无序网络在扩大区域上的响应。我们展示了一个示例,一个细胞如何使用局部测量值使用这种非线性机械敏化来推断无序ECM的宏观机械性能。总之,我们的结果表明,细胞可以利用纤维网络的固有非线性来牢固地感知,控制和响应其机械环境。

In a diversity of physiological contexts, eukaryotic cells adhere to an extracellular matrix (ECM), a disordered network with complex nonlinear mechanics. Such cells can perform mechanosensation: using local force probing they can measure and respond to their substrate's mechanical properties. It remains unclear, however, how the mechanical complexity of the ECM at the cellular scale impacts mechanosensation. Here, we investigate the physical limits of mechanosensation imposed by the inherent structural disorder and nonlinear elastic response of the ECM. Using a theoretical framework for disordered fiber networks, we find that the extreme mechanical heterogeneity that cells can locally sense with small probing forces is strongly reduced with increasing force. Specifically, we predict that the accuracy of mechanosensation dramatically improves with force, following a universal power law insensitive to constitutive details, which we quantitatively confirm using microrheology experiments in collagen and fibrin gels. We provide conceptual insights into this behavior by introducing a general model for nonlinear mechanosensation, based on the idea of an emergent nonlinear length-scale associated with fiber buckling. This force-dependent length-scale enhances the range over which local mechanical measurements are performed, thereby averaging the response of a disordered network over an enlarged region. We show with an example how a cell can use this nonlinear mechanosensation to infer the macroscopic mechanical properties of a disordered ECM using local measurements. Together, our results demonstrate that cells can take advantage of the inherent nonlinearity of fibrous networks to robustly sense, control, and respond to their mechanical environment.

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