Buzy-pop: Multi-objective budget optimisation for constitutive and adaptive enzymatic activities of microbe populations

Enzyme production is a key concept of the metabolism of microbe populations. Extracellular enzymes are notably responsible for the decomposition of the Particular Organic Matter (POM) in order to feed the Dissolved Available Matter (DAM) from where microbe populations and plants assimilate carbon (C), nitrogen (N) and phosphorus (P) based nutrients required for respiration and growth. The resource allocation theory tend to show that the production of enzymes by microbes dynamically adapts to the current needs of the population and to the composition of the POM and the DAM. @ However, it would be unrealistic to simulate all possible enzymes species, and the exact chemical composition of a real world POM and DAM is assumed unknown. In order to evaluate the decomposition of the substrate by a microbe population in this context, we propose the definition of generic enzymatic actions in a model called Buzy-pop. The notion of an enzymatic budget that can be allocated to each action allows to represent both constitutive and adaptive enzymatic activities according to the resource allocation theory. A multi-objective optimisation algorithm allocates the budget to available actions according to microscopic environmental conditions and life strategies of microbes, efficiently representing the decisions of microbe populations as the result of a compromise between sometimes contradictory objectives. The Buzy-pop model finally allows to dynamically compute quantitative decomposition rates of labile and recalcitrant C, N and P over time in any POM and DAM composition, and is configurable thanks to a carefully chosen set of meaningful parameters that could be calibrated to fit results to real world cases. Because of its low input parameters requirements and its extensibility, Buzy-pop could be used in many contexts. Calibration is provided for a set of life strategies (Opportunists, Foragers and Minimalists) as an use case example. Experimental results prove its consistency with theoretical expectations about the behaviour of microbe populations according to the proposed life strategies.