Computational modeling of extracellular mechanotransduction

Area of Science:

• Biophysics
• Cell Biology
• Computational Biology

Background:

• Mechanotransduction is crucial for cellular responses to mechanical stimuli.
• Autocrine signaling in the extracellular space is a proposed mechanotransduction pathway.
• The epithelial lateral intercellular space (LIS) is a dynamic microenvironment potentially involved in mechanotransduction.

Purpose of the Study:

• To computationally analyze how epithelial lateral intercellular space (LIS) geometry alterations impact ligand concentrations.
• To investigate the relationship between LIS geometric changes, ligand diffusion-convection, and cellular signaling.
• To explore the role of extracellular ligand dynamics in mechanotransduction.

Main Methods:

• Developed a computational model using the finite element method.
• Solved ligand diffusion-convection equations within and outside idealized parallel plate LIS geometry.
• Simulated effects of varying ligand diffusivity, shedding rate, and deformation rate.

Main Results:

• Demonstrated that the kinetics of mechanical deformation correlate with ligand accumulation rates.
• Showed that rapid LIS geometry changes can transiently elevate ligand concentrations below the LIS.
• Identified a potential mechanism for epithelial cells to discriminate varying mechanical rates.

Conclusions:

• Extracellular ligand dynamics offer a plausible mechanism for mechanotransduction.
• Changes in LIS geometry can mediate communication of mechanical states between epithelial and subepithelial cells.
• Computational modeling provides insights into the complexity of extracellular mechanotransduction.