Phase-field modeling of constrained interactive fungal networks

Area of Science:

• Computational Biology
• Mycology
• Biophysics

Background:

• Fungi exhibit adaptive evolution under geometrical constraints, solving complex problems.
• The pathogenic fungus Ophiocordyceps is a model for studying constrained interactive networks.
• Modeling fungal networks is difficult due to coupled physics and moving boundaries.

Purpose of the Study:

• To develop a computational phase-field model for fungal networks.
• To elucidate the mechanics of emergent properties in fungal networks.
• To simulate fungal growth in confined geometries and resource depletion.

Main Methods:

• Developed a computational phase-field model.
• Used a variational approach to derive equations for mycelium biomass and nutrient evolution.
• Extensively tested the model against growing and decaying phenomena.

Main Results:

• The model captures spatial and temporal scales of fungal growth.
• Identified mechanisms of variable interplay leading to diverse colony morphologies.
• Explained abrupt pattern changes observed in laboratory experiments.
• Successfully simulated Ophiocordyceps-like growth in confined, resource-limited environments.

Conclusions:

• The computational phase-field model effectively elucidates emergent properties in fungal networks.
• The model is suitable for studying biological networks, including Ophiocordyceps evolution.
• Demonstrated the model's ability to reproduce complex fungal growth dynamics and adaptations.