Tensegrity structures and data-driven analysis for 3d cell mechanics
Ziran Zhou, Jacinto Ulloa, Guruswami Ravichandran, Jose E. Andrade
TL;DR
The paper develops a 3D finite-element tensegrity framework to model cell mechanics across scales, from single cells to multicellular spheroids, explicitly linking cytoskeletal prestress to nonlinear mechanical responses. To tackle the computational burden of large assemblies, it introduces a multiscale data-driven (DD) computing approach that uses material data to drive continuum-like solutions without explicit constitutive models. Key findings include successful replication of the nonlinear indentation response of a single cell, the nonlinear-to-linear transition observed in monolayer stretch, and spatially varying stress distributions within a multicellular spheroid that qualitatively align with experimental proliferation maps. This work offers a pathway to mechanobiology analyses of large cellular assemblies and organ-scale tissue mechanics, while recognizing limitations in material nonlinearities and boundary-state representations that warrant future extensions to generalized continua and nonlinear material laws.
Abstract
The cytoskeleton (CSK) plays an important role in many cell functions. Given the similarities between the mechanical behavior of tensegrity structures and the CSK, many studies have proposed different tensegrity-based models for simulating cell mechanics. However, the low symmetry of most tensegrity units has hindered the analysis of realistic 3D structures. As a result, tensegrity-based modeling in cell mechanics has been mainly focused on single cells or monolayers. In this paper, we propose a 3D tensegrity model based on the finite element method for simulating 3D cell mechanics. We show that the proposed model not only captures the nonlinearity of a single cell in an indentation test and a monolayer in stretch test but also the non-uniform stress distribution in multicellular spheroids upon non-uniform prestress design. Furthermore, we introduce a multiscale data-driven framework for cellular mechanics to optimize the computation, thus paving the way for modeling the mechanobiology of large cellular assemblies such as organs.
