ArticleFrontiers in microbiology2017
Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process.
Article in Frontiers in microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching.Scientific reports · 2025Article
- Exploring the competitive dynamic enzyme allocation scheme through enzyme cost minimization.ISME communications · 2023Article
- Ecological modelling approaches for predicting emergent properties in microbial communities.Nature ecology & evolution · 2022Review
- Enzyme promiscuity in natural environments: alkaline phosphatase in the ocean.The ISME journal · 2021Article
- Does It Pay Off to Explicitly Link Functional Gene Expression to Denitrification Rates in Reaction Models?Frontiers in microbiology · 2021Article
- Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling.Frontiers in microbiology · 2020Article
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Authors and funding
10 authors.
Funding
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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.
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