Development of microbial‐enzyme‐mediated decomposition model parameters through steady‐state and dynamic analyses

Abstract

We developed a microbial-enzyme-mediated decomposition (MEND) model, based on the Michaelis-Menten kinetics, that describes the dynamics of physically defined pools of soil organic matter (SOC). These include particulate, mineral-associated, dissolved organic matter (POC, MOC, and DOC, respectively), microbial biomass, and associated exoenzymes. The ranges and/or distributions of parameters were determined by both analytical steady-state and dynamic analyses with SOC data from the literature. We used an improved multi-objective parameter sensitivity analysis (MOPSA) to identify the most important parameters for the full model: maintenance of microbial biomass, turnover and synthesis of enzymes, and carbon use efficiency (CUE). The model predicted that an increase of 2 degrees C (baseline temperature 12 degrees C) caused the pools of POC-cellulose, MOC, and total SOC to increase with dynamic CUE and decrease with constant CUE, as indicated by the 50% confidence intervals. Regardless of dynamic or constant CUE, the changes in pool size of POC, MOC, and total SOC varied from -8% to 8% under +2 degrees C. The scenario analysis using a single parameter set indicates that higher temperature with dynamic CUE might result in greater net increases in both POC-cellulose and MOC pools. Different dynamics of various SOC pools reflected the catalytic functions of specific enzymes targeting specific substrates and the interactions between microbes, enzymes, and SOC. With the feasible parameter values estimated in this study, models incorporating fundamental principles of microbial-enzyme dynamics can lead to simulation results qualitatively different from traditional models with fast/slow/passive pools.

On the relationships between the Michaelis–Menten kinetics, reverse Michaelis–Menten kinetics, equilibrium chemistry approximation kinetics, and quadratic kinetics

“…They further concluded that the MM kinetics is applicable when the substrate concentration far exceeds the enzyme concentration, and the RMM kinetics is applicable when either the enzyme concentration far exceeds the substrate concentration or vice versa. The condition for the MM kinetics to be applicable as provided by Wang and Post (2013) was however much narrower than that was proposed in some earlier studies. For instance, Borghans et al (1996) showed that the MM kinetics is a good approximation to the quadratic kinetics when enzyme concentration is far smaller than the sum of the substrate concentration and the Michaelis-Menten constant (Palsson, 1987;Segel, 1988;Segel and Slemrod, 1989).…”

“…[S] T proposed in Wang and Post (2013). I also note that the derivation of the RMM kinetics does not take into account the mass balance constraint for enzymes (Eq.…”

“…This has been manifested in a long list of microbial models that were published in the last few years (e.g., Schimel and Weintrub, 2003;Moorhead and Sinsabaugh, 2006;Allison et al, 2010;German et al, 2012;Wang et al, 2013;Wieder et al, 2013;Li et al, 2014;He et al, 2014;Riley et al, 2014;Xenakis and Williams, 2014;Tang and Riley, 2015;Sulman et al, 2014;Wieder et al, 2015). To build a microbial model, the substrate kinetics is fundamental as it describes the rate at which microbes would take up a substrate and represents the first step towards describing how microbes would decompose the soil organic matter.…”

“…The success by Schimel and Weintraub has led to a number of studies using the RMM kinetics as the backbone of their microbial models, including the Moorhead and Sinsabaugh (2006) model of litter decomposition, the Drake et al (2013) model for root priming, the Waring et al (2013) model for change in microbial community structure in soil carbon and nitrogen cycling, and the Averill (2014) model for change in microbial allocation in soil carbon decomposition. Wang and Post (2013) pointed out that both the MM kinetics and RMM kinetics (although the latter is empirical) are special approximations to the quadratic kinetics that exactly solves for the enzyme-substrate complex under the quasi-steady-state approximation (QSSA), which states that the enzyme-substrate complexes are in instantaneous equilibrium with enzyme and substrate concentrations (Borghans et al, 1996). They further concluded that the MM kinetics is applicable when the substrate concentration far exceeds the enzyme concentration, and the RMM kinetics is applicable when either the enzyme concentration far exceeds the substrate concentration or vice versa.…”

Dispersal-Based Microbial Community Assembly Decreases Biogeochemical Function

“…Microbially-explicit models (e.g., MIMICS, MEND) are rapidly becoming more sophisticated and are readily amenable to modules that represent ecological assembly processes [70,71]. As models begin to consider microbial ecology, there is a need to decipher linkages among spatiotemporal microbial processes and ecosystem-level biogeochemical function.…”