Determining the rules for self-organised adaptive biological networks
Mark Fricker writes for the Trinity Term 2021 Alumni Newsletter about his research into adaptive biological networks
Fungi account for the second largest fraction of biomass in terrestrial ecosystems after plants, and they are critically involved in soil formation, wood decomposition and nutrient cycling. However, in comparison to plants and animals, we know remarkably little about how they operate, not least because most of the action is hidden below ground. Saprotrophic fungi form extensive interconnected mycelial networks that scavenge efficiently for scarce and ephemeral resources in this patchy and unpredictable environment. They also face of aggressive competition from other fungi, predation by soil micro-fauna, and accidental disturbance by larger animals. Exploration, repair, and combat all require resources, that in turn require internal transport of nutrients from spatially disparate sources to these rapidly altering sinks through the ever-changing network. As these organisms do not have any centralized control system, we infer their relatively sophisticated behaviour must emerge from parallel implementation of many local decisions that collectively manage to solve this dynamic combinatorial optimization problem.
To begin to tease apart this control system, we use graph-theoretic analysis of digitised networks, as illustrated above, to investigate how these indeterminate, de-centralized systems can yield adaptive networks with both high transport capacity and robustness to damage, but at a relatively low cost. One element is a 'Darwinian' process of selective reinforcement of key transport pathways, combined with recycling of redundant routes. In addition, fungal networks can remodel link strengths and local connectivity when subject to experimental attack to readjust the balance between transport capacity and robustness to damage. This results in increased resilience as the environment becomes more challenging.
The underlying mechanisms leading to the emergence of adaptive behaviour in macroscopic mycelial networks are unknown. However, we have developed a set of mathematical models that treat the network as a single hydraulically coupled system to predict nutrient flows. These models turn out to be surprisingly powerful, even though they are based solely on measurable biophysical features such as hyphal width, length, growth, and connectivity. We are now extending this approach across widely divergent network-forming organisms, such as slime molds, to identify universal biological algorithms that yield optimized network design.
These types of models also provide an explanation as to why fungi evolved in the first place. Development of multicellularity was one of the major transitions in evolution and occurred independently multiple times in algae, plants, animals, and fungi. Recent comparative genome analyses suggest that fungi followed a different route to other eukaryotic lineages. To understand the driving forces leading to a hyphal growth form, we added resource acquisition to the model. This predicts that whenever the local resource is immobile, hard-to-digest, and nutrient poor, hyphal organisms outcompete motile or autolytic unicellular organisms. The ‘hyphal advantage’ arises because transporting nutrients via a contiguous cytoplasm enables continued exploitation of remaining resources, even after essential nutrients are depleted. The model provides a mechanistic explanation for the origins of multicellular hyphal organisms, and explains why fungi, rather than unicellular bacteria, evolved to dominate decay of recalcitrant, nutrient poor substrates such as leaf litter or wood.