A computational framework for modeling cell-matrix interactions in soft biological tissues.

Area of Science:

• Biomedical Engineering
• Mechanobiology
• Computational Biology

Background:

• Living soft tissues exhibit mechanical homeostasis, maintaining a stable mechanical state.
• The micromechanical mechanisms underlying tissue-level mechanical homeostasis are not well understood.
• Understanding these microscale mechanisms is crucial for explaining physiological and pathological processes.

Purpose of the Study:

• To develop a novel computational framework for investigating the micromechanical basis of mechanical homeostasis.
• To model key cellular mechanobiological processes contributing to tissue mechanical stability.
• To bridge the gap between cellular-level mechanics and macroscopic tissue homeostasis.

Main Methods:

• A bottom-up computational framework using the finite element method.
• Modeling of individual cell behaviors, including actin cytoskeleton contraction and molecular clutch dynamics.
• Simulation of cell interactions within a reconstructed three-dimensional extracellular fiber matrix.

Main Results:

• The computational framework successfully reproduces experimental observations of mechanical homeostasis on short timescales.
• The model demonstrates how cellular-level mechanobiology can lead to macroscopic tissue stability.
• The framework neglects extracellular matrix deposition and degradation, focusing on rapid homeostatic mechanisms.

Conclusions:

• The developed computational framework provides a systematic tool for in silico studies of mechanical homeostasis.
• This model offers insights into the poorly understood micromechanical origins of tissue mechanical stability.
• Further research using this framework can elucidate unexplained experimental observations in mechanobiology.