Kalman-filter force inference: an estimation framework for cellular forces from temporal evolution of epithelial...

Area of Science:

• Cell Biology
• Biophysics
• Developmental Biology

Background:

• Epithelial morphogenesis relies on cellular forces like tension and pressure.
• Existing force inference methods often assume static force balance, limiting their use in dynamic tissues.

Purpose of the Study:

• To develop a novel method for inferring cellular forces that accounts for tissue dynamics.
• To enable accurate measurement of spatio-temporal force dynamics during epithelial morphogenesis.

Main Methods:

• Developed a Kalman-filter force inference approach based on dynamic force balance and smooth force evolution assumptions.
• Utilized Bayesian formalization to integrate these assumptions into the inference method.
• Validated the method using synthetic data from cell vertex model simulations.

Main Results:

• The Kalman-filter method accurately estimated cellular force dynamics across various mechanical parameters.
• The approach demonstrated robustness against observation noise in simulations.
• Successfully inferred dynamic cellular forces in epithelial tissues undergoing deformation.

Conclusions:

• The novel Kalman-filter force inference method accurately captures dynamic cellular forces.
• This approach expands the applicability of force inference to dynamic biological systems.
• Provides new insights into the mechanical principles governing epithelial morphogenesis.