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

Hyun-Seob Song,Jim K Fredrickson,Minjing Li,James C Stegen,Chongxuan Liu,Timothy D Scheibe,Xingyuan Chen,Dennis G Thomas,Xuehang Song,John M Zachara

doi:10.3389/fmicb.2017.01866

Hyun-Seob Song, Jim K Fredrickson + Show 8 more

Open Access

https://doi.org/10.3389/fmicb.2017.01866

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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.

Highlights

Microbes in terrestrial and aquatic ecosystems are primary drivers of biogeochemical processes, including carbon and nitrogen cycling (Gougoulias et al, 2014)
We structured and parameterized the denitrification model based on the experimental data collected by the Pacific Northwest National Laboratory (PNNL)’s subsurface biogeochemistry research group
The RegulationStructured Cybernetic Model (RSCM) describes the dynamic microbial regulation based on the cybernetic approach

Summary

Introduction

Microbes in terrestrial and aquatic ecosystems are primary drivers of biogeochemical processes, including carbon and nitrogen cycling (Gougoulias et al, 2014). Existing models account for metabolic lags by using temporal convolution integrals (Nilsen et al, 2012) or by introducing exposure time as an additional dimension (or coordinate; Wood et al, 1995) These models, do not address the fundamental mechanisms that lead to such delayed metabolic responses; limiting their use for prediction. The trait-based modeling often considers grouping organisms that share certain metabolic functional similarities (i.e., traits) into a fewer number of species guilds or functional guilds (Taffs et al, 2009; Jin and Roden, 2011; Bouskill et al, 2012) This guild-based grouping can be less effective, in the case where microorganisms can perform multiple functions (functional versatility) that are partially overlapping with one another (functional degeneracy) in a dynamically changing environment (Whitacre and Bender, 2010; Song et al, 2015). This enzyme-based approach views a microbial community as a collective assembly of metabolic capabilities as opposed to a complex network of individual organisms or their groups (e.g., functional guilds), requiring no a priori knowledge of the functional roles of individual organisms

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