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A Novel Stretching Platform for Applications in Cell and Tissue Mechanobiology
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Modelling Cell Orientation Under Stretch: The Effect of Substrate Elasticity.

Annachiara Colombi1, Luigi Preziosi2, Marco Scianna1

  • 1Department of Mathematical Sciences "G.L. Lagrange", Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy.

Bulletin of Mathematical Biology
|July 17, 2023
PubMed
Summary

Cells respond to mechanical forces in their environment by changing their shape and orientation. When placed on a stiff surface and stretched, cells often align at an angle to the stretching direction. On softer surfaces, they tend to align either with or perpendicular to the stretching. To understand this behavior, researchers created a simplified model of a cell using elastic elements and a torsional spring. The model shows that the stiffness of the surface determines the orientation pattern. At higher stiffness, cells adopt an oblique orientation. At lower stiffness, they switch to perpendicular or parallel. The model also suggests that elongated cells, like fibroblasts, are more likely to maintain an oblique orientation. Rounder cells, like epithelial cells, tend to align differently. These findings help explain how cells sense and respond to mechanical cues, which is important for tissue engineering and regenerative medicine.

Keywords:
Cell orientationCell–substrate interactionMechanosensingCell mechanicsSubstrate stiffnessMechanotransductionTissue engineering

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Area of Science:

  • Cell mechanics and biophysics
  • Tissue engineering and biomaterials
  • Computational biology

Background:

Cells respond to mechanical cues from their environment, including substrate stiffness and cyclic stretching. These responses influence cell shape, orientation, and function. Previous studies have shown that cells align in specific directions when exposed to cyclic stretching, but the mechanisms behind these patterns remain unclear. The role of substrate elasticity in determining orientation has not been fully explained. Some research suggests that stress fibers and focal adhesions play a role in cell reorientation. However, the transition between different orientation modes is not well understood. This gap motivated the development of a simplified mechanical model to explain how substrate stiffness affects cell orientation. The model aims to clarify the switch between oblique and perpendicular/parallel alignment. Understanding this behavior is important for tissue engineering and regenerative medicine. This work builds on existing knowledge of cell mechanics and substrate interactions.

Purpose Of The Study:

This study aimed to investigate how substrate elasticity influences the orientation of cells under cyclic stretching. The researchers sought to explain the observed switch in cell orientation from oblique to perpendicular or parallel. They focused on the mechanical interactions between cells and their environment. The study examined the role of stress fibers and focal adhesions in this process. The goal was to develop a predictive model of cell behavior under different substrate conditions. The model needed to account for the effects of stiffness and cell shape. The researchers also wanted to determine how cell elongation affects orientation. This work contributes to the understanding of mechanotransduction in cells.

Main Methods:

The researchers developed a simplified mechanical model of a cell under cyclic stretching. The model included two elastic elements representing stress fibers in the main and transverse directions. A torsional spring connected these elements to simulate crosslinking molecules. The model accounted for shear forces between stress fibers. The researchers used this framework to simulate cell orientation on substrates of varying stiffness. They analyzed the asymptotic behavior of the model under different conditions. The model predicted a switch in orientation based on substrate stiffness. The study also considered the effect of cell elongation on orientation patterns.

Main Results:

The model predicted a switch in cell orientation depending on substrate stiffness. At higher stiffness, cells adopted an oblique orientation. At lower stiffness, the orientation shifted to perpendicular or parallel. The model showed a transition between supercritical and subcritical bifurcation scenarios. The oblique orientation was stable only at higher stiffness values. The researchers found that cell elongation reduced the region of oblique orientation. Elongated cells, such as fibroblasts, were more likely to maintain an oblique orientation. Rounder cells, like epithelial cells, tended to align perpendicularly or parallelly. The model's predictions aligned with experimental observations of cell behavior.

Conclusions:

The model provides a framework for understanding how substrate stiffness affects cell orientation. The switch between oblique and perpendicular/parallel alignment is linked to changes in bifurcation scenarios. The model suggests that cell shape influences orientation patterns on soft substrates. Elongated cells are more likely to maintain an oblique orientation. Rounder cells tend to align perpendicularly or parallelly on soft substrates. The findings support the idea that mechanical interactions between cells and substrates are critical. The model can help predict cell behavior in engineered environments. These results may inform the design of biomaterials for tissue engineering.

The orientation depends on substrate stiffness. Oblique orientation occurs at higher stiffness, while perpendicular or parallel orientation occurs at lower stiffness.

The model uses two elastic elements for stress fibers and a torsional spring to simulate crosslinking molecules.

Elongated cells maintain an oblique orientation more often. Rounder cells switch to perpendicular or parallel orientation on soft substrates.

The torsional spring mimics crosslinking molecules that resist shear forces between stress fibers.

The model predicts a transition between supercritical and subcritical bifurcation scenarios as stiffness decreases.

The model helps predict how cells respond to mechanical cues, which can guide the design of biomaterials for tissue engineering.