Upscaling decomposition kinetics from enzyme to ecosystem: Developing a kinetic parameter database for metagenomics-informed soil biogeochemical models

A series of diverse enzymes catalyze the decomposition of soil organic matter (SOM) from raw litter to bioavailable monomers along a continuum of structural complexity of organic matters. The Michaelis-Menten equation has been applied in ecosystem and Earth system models to explicitly represent microbial enzyme-mediated decomposition processes. This application requires a number of kinetic parameters, including maximum specific reaction rate, half-saturation constant, optimal temperature, activation energy, optimal pH, and pH sensitivity. These parameters are fundamental for modeling SOM decomposition and its response to environmental change. However, integrating the kinetics of soil enzymes into the Michaelis-Menten equation is still a challenge due to a serious lack of availability of relevant enzyme kinetic parameters.

This study aims to build a kinetic parameter database of all metagenomics-informed enzymes relevant to the continuum decomposition of SOM. This database will enable the scaling of enzyme kinetics up to the level of enzyme functional groups (EFG) to represent the decomposition dynamics of SOM. Using soil metagenomics data collected from a Panama tropical forest, we identified 118 enzymes participating in the continuum decomposition of SOM. These enzymes were further grouped into 22 EFGs according to substrate chemical composition and enzymatically-cleaved bond location within the organic substrate. Six kinetic parameters of each enzyme and their variations with origins (e.g. archaea, bacteria and fungi) were statistically analyzed by investigating around 4,900 observational data from the BRaunscheig Enzyme DAtabase (BRENDA). These kinetic parameters were upscaled to the EFG level by estimating the gene abundance weighted mean of the corresponding enzyme kinetic parameters of all EC numbers in each EFG.

This EFG-based kinetic parameters database provides a tool to parameterize multiple enzyme-mediated SOM decomposition processes in biogeochemical models, e.g., the first metagenomics-informed Continuum Microbial Enzyme Decomposition model (CoMEND). This database enables us to link enzyme functional kinetics with ecosystem dynamics to identify key rate-limiting steps in SOM decomposition and nutrient acquisition in response to environmental change.