Coupling a Genome-Scale Metabolic Model with a Reactive Transport Model to Describe In Situ Uranium Bioremediation
Journal Article
·
· Microbial Biotechnology, 2(2):274-286
Quantitative numerical simulation codes known as reactive transport models are widely used for simulating the hydrologic transport and geochemical speciation of dissolved constituents in the subsurface (Steefel et al., 2005). Because the activity of microorganisms strongly influences the fate of many constituents, both organic and inorganic, such models often include microbially-mediated reactions in their reaction networks (Hunter et al., 1998; Burgos et al., 2002; Fang et al., 2006; Scheibe et al., 2006; Yabusaki et al., 2007). However, the canonical form and stoichiometry of microbial reactions, reaction rate formulations and parameters, and biomass growth yield coefficients are prescribed a priori and applied over the entire range of simulated conditions. This approach does not account for the fact that fundamental microbial functions vary in response to local variations in environmental conditions(Stewart and Franklin, 2008). Multiple alternative reaction pathways are encoded in microbial genomes; specific pathways become active or inactive in response to, for example, nutrient limitation. Recent advances in genomic analysis allow us to define cellular metabolic networks, and accurate predictions of active pathways and reaction fluxes have been made using constraint-based metabolic models (Mahadevan et al., 2002; Price et al., 2003; Reed and Palsson, 2003; Mahadevan et al., 2006). Here, we demonstrate for the first time a methodology of coupling constraint-based metabolic models with reactive transport models. Our approach integrates advanced microbiological characterization, hydrology, and geochemistry in a powerful manner that will significantly improve subsurface reactive transport models.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 965999
- Report Number(s):
- PNNL-SA-61861; KP1504010
- Journal Information:
- Microbial Biotechnology, 2(2):274-286, Journal Name: Microbial Biotechnology, 2(2):274-286 Journal Issue: 2 Vol. 2
- Country of Publication:
- United States
- Language:
- English
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