Proper Orthogonal Decomposition Analysis Reveals Cell Migration Directionality During Wound Healing

Area of Science:

• Biophysics
• Computational Biology
• Cell Biology

Background:

• Cell migration is crucial for wound healing, development, and disease.
• Understanding cell migration dynamics under fluid flow is complex.
• Order reduction methods can simplify high-dimensional dynamical systems.

Purpose of the Study:

• To apply proper orthogonal decomposition (POD) for reducing a wound healing cell migration model.
• To identify and characterize prevalent cell trajectories under varying fluid flow conditions.
• To establish a foundation for AI-driven cell migration modeling.

Main Methods:

• Implemented proper orthogonal decomposition (POD) to reduce a high-dimensional dynamical system.
• Analyzed POD modes representing prevalent cell trajectories.
• Investigated the influence of disturbed (DF) and undisturbed (UF) fluid flow on cell migration patterns.

Main Results:

• POD modes effectively represented prevalent cell trajectories, influenced by cell location and fluid flow (DF/UF).
• Downstream cells showed upstream migration against flow; upstream cells exhibited sideways migration.
• Absence of flow resulted in similar POD modes on both sides of the wound.
• Cell migration was accurately reconstructed using as few as three POD modes, with accuracy increasing with more modes.

Conclusions:

• POD successfully identified predominant cell migratory trajectories under static and pulsatile flow.
• The method provides a low-dimensional approximation of complex cell migration dynamics.
• This work is a foundational step towards developing AI models for cell migration in biological contexts.