Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

Abstract

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community's traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

Drought Conditions Maximize the Impact of High‐Frequency Flow Variations on Thermal Regimes and Biogeochemical Function in the Hyporheic Zone

“…The effectiveness of the cybernetic modeling was successfully demonstrated in previous case studies of modeling denitrifying organisms (Song & Liu, ) and microbial communities (Song et al, ). In the present work, we used a simplified version of the cybernetic model developed by Song et al () for linking microbial communities with enzyme expression observed in a denitrification experiment (Li et al, ). The supporting information provides more details on the derivation of the simplified cybernetic model (Text S1).…”

Using Bayesian Networks for Sensitivity Analysis of Complex Biogeochemical Models

“…The biogeochemical reaction network and the reaction rates in the model were adopted from the work of Li et al () and H.‐S. Song et al (). The reactions of oxidative respiration and denitrification for the dissolved organic carbon (CH 2 O) and the synthesis of biomass (C 5 H 7 O 2 N) were considered as follows: …”

“…Temperature‐dependent reaction rate, r i , is defined using the Arrhenius equation, that is, where r i is the reaction rate under temperature T (in Kelvin) with subscript i being the generic reaction index, E a is the activation energy (0.65 ev in this study), R is the gas constant (8.314 J·mol −1 ·K −1 ), and r base, i is the base rate derived from laboratory batch experiments (under the room temperature of 26 °C). After incorporating microbial regulation term into the Monod kinetics, the base rate, r base, i , is defined by where the relative enzyme levels, , regulate the rates of oxidative respiration and denitrification reactions (H. Song et al, ), k i (mol·L −1 ·day −1 ) is the maximum specific uptake rate of organic carbon (CH 2 O), a i (mol/L) is the electron acceptor concentration, d i (mol/L) is the electron donor concentration, and K a , i (mol/L) and K d , i (mol/L) are the half‐saturation constants for electron acceptors and electron donors, respectively. More details about the reaction network and rates can be found in X.…”

“…The biogeochemical reaction network and the reaction rates in the model were adopted from the work of Li et al (2017) and H.-S. Song et al (2017). The reactions of oxidative respiration and denitrification for the dissolved organic carbon (CH 2 O) and the synthesis of biomass (C 5 H 7 O 2 N) were considered as follows:…”

“…We used an enzyme-based cybernetic modeling approach to represent biogeochemical reaction regulated by microbial activities (H. Song et al, 2017;X. Song et al, 2018).…”