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Updated: Jul 18, 2026

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Microfluidic Tools for Probing Fungal-Microbial Interactions at the Cellular Level
Published on: June 23, 2022
Fungi use efficient algorithms for the exploration of microfluidic networks
Kristi L Hanson1, Dan V Nicolau, Luisa Filipponi
1BioNanoEngineering Labs, Faculty of Engineering and Industrial Science, Swinburne University of Technology, John Street, Hawthorn, Victoria 3122, Australia.
Small (Weinheim an Der Bergstrasse, Germany)
|December 29, 2006
Summary
Fungi exhibit remarkable space-searching strategies in confined environments. Their complex growth algorithms, involving directional memory and branching, optimize survival and biomass distribution in microconfined networks.
Area of Science:
- Mycology
- Biophysics
- Computational Biology
Background:
- Basidiomycetous fungi efficiently colonize diverse microconfined environments like soil and tissues.
- This suggests fungi may possess inherent capabilities for solving geometrical problems.
Purpose of the Study:
- To evaluate the growth behavior and optimality of fungal space-searching algorithms.
- To understand how microconfinement geometry influences fungal growth strategies.
Main Methods:
- Experiments using microfluidic mazes and networks to observe fungal growth.
- Analysis of fungal growth strategies, including directional memory and branching.
- Stochastic simulations using experimentally measured parameters.
Main Results:
- Fungal growth is significantly modulated by microconfinement geometry.
- Fungi employ a dual strategy: long-range directional hyphal memory and branching induced by physical obstruction.
- Simulations confirm this strategy maximizes survival and biomass homogeneity in confined networks.
Conclusions:
- Fungal space-searching strategies are complex and adaptive to geometrical challenges.
- The synergistic use of directional memory and obstruction-induced branching leads to optimal network colonization.
- Even simple microorganisms like fungi demonstrate sophisticated problem-solving capabilities for navigating complex environments.

