A computational approach to understand phenotypic structure and constitutive mechanics relationships of single cells

Cell and Tissue Nanomechanics: From Early Development to Carcinogenesis

Cell and tissue nanomechanics, being inspired by progress in high-resolution physical mapping, has recently burst into biomedical research, discovering not only new characteristics of normal and diseased tissues, but also unveiling previously unknown mechanisms of pathological processes. Some parallels can be drawn between early development and carcinogenesis. Early embryogenesis, up to the blastocyst stage, requires a soft microenvironment and internal mechanical signals induced by the contractility of the cortical actomyosin cytoskeleton, stimulating quick cell divisions. During further development from the blastocyst implantation to placenta formation, decidua stiffness is increased ten-fold when compared to non-pregnant endometrium. Organogenesis is mediated by mechanosignaling inspired by intercellular junction formation with the involvement of mechanotransduction from the extracellular matrix (ECM). Carcinogenesis dramatically changes the mechanical properties of cells and their microenvironment, generally reproducing the structural properties and molecular organization of embryonic tissues, but with a higher stiffness of the ECM and higher cellular softness and fluidity. These changes are associated with the complete rearrangement of the entire tissue skeleton involving the ECM, cytoskeleton, and the nuclear scaffold, all integrated with each other in a joint network. The important changes occur in the cancer stem-cell niche responsible for tumor promotion and metastatic growth. We expect that the promising concept based on the natural selection of cancer cells fixing the most invasive phenotypes and genotypes by reciprocal regulation through ECM-mediated nanomechanical feedback loop can be exploited to create new therapeutic strategies for cancer treatment.

Articular Chondrocyte Phenotype Regulation through the Cytoskeleton and the Signaling Processes That Originate from or Converge on the Cytoskeleton: Towards a Novel Understanding of the Intersection between Actin Dynamics and Chondrogenic Function

Numerous studies have assembled a complex picture, in which extracellular stimuli and intracellular signaling pathways modulate the chondrocyte phenotype. Because many diseases are mechanobiology-related, this review asked to what extent phenotype regulators control chondrocyte function through the cytoskeleton and cytoskeleton-regulating signaling processes. Such information would generate leverage for advanced articular cartilage repair. Serial passaging, pro-inflammatory cytokine signaling (TNF-α, IL-1α, IL-1β, IL-6, and IL-8), growth factors (TGF-α), and osteoarthritis not only induce dedifferentiation but also converge on RhoA/ROCK/Rac1/mDia1/mDia2/Cdc42 to promote actin polymerization/crosslinking for stress fiber (SF) formation. SF formation takes center stage in phenotype control, as both SF formation and SOX9 phosphorylation for COL2 expression are ROCK activity-dependent. Explaining how it is molecularly possible that dedifferentiation induces low COL2 expression but high SF formation, this review theorized that, in chondrocyte SOX9, phosphorylation by ROCK might effectively be sidelined in favor of other SF-promoting ROCK substrates, based on a differential ROCK affinity. In turn, actin depolymerization for redifferentiation would “free-up” ROCK to increase COL2 expression. Moreover, the actin cytoskeleton regulates COL1 expression, modulates COL2/aggrecan fragment generation, and mediates a fibrogenic/catabolic expression profile, highlighting that actin dynamics-regulating processes decisively control the chondrocyte phenotype. This suggests modulating the balance between actin polymerization/depolymerization for therapeutically controlling the chondrocyte phenotype.

Automated generation of tissue-specific three-dimensional finite element meshes containing ellipsoidal cellular inclusions

Finite element analysis provides a means of describing cellular mechanics in tissue, which can be useful in understanding and predicting physiological and pathological changes. Many prior studies have been limited to simulations of models containing single cells, which may not accurately describe the influence of mechanical interactions between cells. It is desirable to generate models that more accurately reflect the cellular organisation in tissue in order to evaluate the mechanical function of cells. However, as the model geometry becomes more complicated, manual model generation can become laborious. This can be prohibitive if a large number of distinct cell-scale models are required, for example, in multiscale modelling or probabilistic analysis. Therefore, a method was developed to automatically generate tissue-specific cellular models of arbitrary complexity, with minimal user intervention. This was achieved through a set of scripts, which are capable of generating both sample-specific models, with explicitly defined geometry, and tissue-specific models, with geometry derived implicitly from normal statistical distributions. Models are meshed with tetrahedral (TET) elements of variable size to sufficiently discretise model geometries at different spatial scales while reducing model complexity. The ability of TET meshes to appropriately simulate the biphasic mechanical response of a single-cell model is established against that of a corresponding hexahedral mesh for an illustrative use case. To further demonstrate the flexibility of this tool, an explicit model was developed from three-dimensional confocal laser scanning image data, and a set of models were generated from a statistical cellular distribution of the articular femoral cartilage. The tools presented herein are free and openly accessible to the community at large.

Structural finite element analysis to explain cell mechanics variability

The ability to model the mechanical responses of different cell types presents many opportunities to tissue engineering research to further identify changes from physiological conditions to disease. Using a previously validated finite element cell model we aim to show how variation of the material properties of the intracellular components affects cell response after compression and shearing. A parametric study was performed to understand the key mechanical features from different cell types, focussing on specific cytoskeleton components and prestress. Results show that actin cortex does not have a mechanical role in resisting shearing loading conditions. The sensitivity analysis predicted that cell force to compression and shearing is highly affected by changes in cortex thickness, cortex Young's modulus and rigidity of the remaining cytoplasm. Variation of prestress affects mainly the response of cells under shear loads and the model defines a relationship between cell force and prestress depending on the specific loading conditions, which is in good agreement with in vitro experiments. The results are used to make predictions that can relate mechanical properties with cell phenotype to be used as guidelines for individual cytoskeletal structures for future modelling efforts of the structure-function relationships of living cells.

A computational approach to understand phenotypic structure and constitutive mechanics relationships of single cells

The goal of this study is to construct a representative 3D finite element model (FEM) of individual cells based on their sub-cellular structures that predicts cell mechanical behavior. The FEM simulations replicate atomic force microscopy (AFM) nanoindentation experiments on live vascular smooth muscle cells. Individual cells are characterized mechanically with AFM and then imaged in 3D using a spinning disc confocal microscope. Using these images, geometries for the FEM are automatically generated via image segmentation and linear programming algorithms. The geometries consist of independent structures representing the nucleus, actin stress fiber network, and cytoplasm. These are imported into commercial software for mesh refinement and analysis. The FEM presented here is capable of predicting AFM results well for 500 nm indentations. The FEM results are relatively insensitive to both the exact number and diameter of fibers used. Despite the localized nature of AFM nanoindentation, the model predicts that stresses are distributed in an anisotropic manner throughout the cell body via the actin stress fibers. This pattern of stress distribution is likely a result of the geometric arrangement of the actin network.