@article {429,
	title = {Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.},
	journal = {J Contam Hydrol},
	volume = {122},
	year = {2011},
	month = {2011 Mar 25},
	pages = {96-103},
	abstract = {The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The modeling system is designed in such a way that constraint-based models targeting different microorganisms or competing organism communities can be easily plugged into the system. Constraint-based modeling is very costly given the size of a genome-scale reaction network. To save computation time, a binary tree is traversed to examine the concentration and solution pool generated during the simulation in order to decide whether the constraint-based model should be called. We also show preliminary results from the integrated model including a comparison of the direct and indirect coupling approaches and evaluated the ability of the approach to simulate field experiment.},
	keywords = {Biodegradation, Environmental, Biological Transport, Colorado, Computer Simulation, Genome, Bacterial, Geobacter, Models, Biological, Uranium},
	issn = {1873-6009},
	doi = {10.1016/j.jconhyd.2010.11.007},
	author = {Fang, Yilin and Scheibe, Timothy D and Mahadevan, Radhakrishnan and Garg, Srinath and Long, Philip E and Lovley, Derek R}
}
@article {438,
	title = {Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.},
	journal = {ISME J},
	volume = {5},
	year = {2011},
	month = {2011 Feb},
	pages = {305-16},
	abstract = {The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.},
	keywords = {Acetates, Anaerobiosis, Biodegradation, Environmental, Biomass, Comamonadaceae, Genome, Genome, Bacterial, Geobacter, Models, Biological, Nitrogen Fixation, Quaternary Ammonium Compounds, RNA, Ribosomal, 16S, Uranium, Water Microbiology, Water Pollutants, Radioactive},
	issn = {1751-7370},
	doi = {10.1038/ismej.2010.117},
	author = {Zhuang, Kai and Izallalen, Mounir and Mouser, Paula and Richter, Hanno and Risso, Carla and Mahadevan, Radhakrishnan and Lovley, Derek R}
}
@article {430,
	title = {In situ to in silico and back: elucidating the physiology and ecology of Geobacter spp. using genome-scale modelling.},
	journal = {Nat Rev Microbiol},
	volume = {9},
	year = {2011},
	month = {2011 Jan},
	pages = {39-50},
	abstract = {There is a wide diversity of unexplored metabolism encoded in the genomes of microorganisms that have an important environmental role. Genome-scale metabolic modelling enables the individual reactions that are encoded in annotated genomes to be organized into a coherent whole, which can then be used to predict metabolic fluxes that will optimize cell function under a range of conditions. In this Review, we summarize a series of studies in which genome-scale metabolic modelling of Geobacter spp. has resulted in an in-depth understanding of their central metabolism and ecology. A similar iterative modelling and experimental approach could accelerate elucidation of the physiology and ecology of other microorganisms inhabiting a diversity of environments, and could guide optimization of the practical applications of these species.},
	keywords = {Computer Simulation, Environment, Gene Expression Regulation, Bacterial, Genome, Bacterial, Geobacter, Models, Biological},
	issn = {1740-1534},
	doi = {10.1038/nrmicro2456},
	author = {Mahadevan, Radhakrishnan and Palsson, Bernhard {\O} and Lovley, Derek R}
}
@article {464,
	title = {Coupling a genome-scale metabolic model with a reactive transport model to describe in situ uranium bioremediation.},
	journal = {Microb Biotechnol},
	volume = {2},
	year = {2009},
	month = {2009 Mar},
	pages = {274-86},
	abstract = {The increasing availability of the genome sequences of microorganisms involved in important bioremediation processes makes it feasible to consider developing genome-scale models that can aid in predicting the likely outcome of potential subsurface bioremediation strategies. Previous studies of the in situ bioremediation of uranium-contaminated groundwater have demonstrated that Geobacter species are often the dominant members of the groundwater community during active bioremediation and the primary organisms catalysing U(VI) reduction. Therefore, a genome-scale, constraint-based model of the metabolism of Geobacter sulfurreducens was coupled with the reactive transport model HYDROGEOCHEM in an attempt to model in situ uranium bioremediation. In order to simplify the modelling, the influence of only three growth factors was considered: acetate, the electron donor added to stimulate U(VI) reduction; Fe(III), the electron acceptor primarily supporting growth of Geobacter; and ammonium, a key nutrient. The constraint-based model predicted that growth yields of Geobacter varied significantly based on the availability of these three growth factors and that there are minimum thresholds of acetate and Fe(III) below which growth and activity are not possible. This contrasts with typical, empirical microbial models that assume fixed growth yields and the possibility for complete metabolism of the substrates. The coupled genome-scale and reactive transport model predicted acetate concentrations and U(VI) reduction rates in a field trial of in situ uranium bioremediation that were comparable to the predictions of a calibrated conventional model, but without the need for empirical calibration, other than specifying the initial biomass of Geobacter. These results suggest that coupling genome-scale metabolic models with reactive transport models may be a good approach to developing models that can be truly predictive, without empirical calibration, for evaluating the probable response of subsurface microorganisms to possible bioremediation approaches prior to implementation.},
	keywords = {Acetates, Biodegradation, Environmental, Biological Transport, Genome, Bacterial, Geobacter, Iron, Models, Biological, Uranium},
	issn = {1751-7915},
	doi = {10.1111/j.1751-7915.2009.00087.x},
	author = {Scheibe, Timothy D and Mahadevan, Radhakrishnan and Fang, Yilin and Garg, Srinath and Long, Philip E and Lovley, Derek R}
}
@article {456,
	title = {Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III)-reducer Rhodoferax ferrireducens.},
	journal = {BMC Genomics},
	volume = {10},
	year = {2009},
	month = {2009},
	pages = {447},
	abstract = {BACKGROUND: Rhodoferax ferrireducens is a metabolically versatile, Fe(III)-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies.

RESULTS: The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress.

CONCLUSION: This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.},
	keywords = {Comamonadaceae, Comparative Genomic Hybridization, DNA, Bacterial, Ferric Compounds, Genome, Bacterial, Genomics, Models, Biological, Oxidation-Reduction, Sequence Analysis, DNA},
	issn = {1471-2164},
	doi = {10.1186/1471-2164-10-447},
	author = {Risso, Carla and Sun, Jun and Zhuang, Kai and Mahadevan, Radhakrishnan and DeBoy, Robert and Ismail, Wael and Shrivastava, Susmita and Huot, Heather and Kothari, Sagar and Daugherty, Sean and Bui, Olivia and Schilling, Christophe H and Lovley, Derek R and Meth{\'e}, Barbara A}
}
@article {466,
	title = {Genome-scale constraint-based modeling of Geobacter metallireducens.},
	journal = {BMC Syst Biol},
	volume = {3},
	year = {2009},
	month = {2009},
	pages = {15},
	abstract = {BACKGROUND: Geobacter metallireducens was the first organism that can be grown in pure culture to completely oxidize organic compounds with Fe(III) oxide serving as electron acceptor. Geobacter species, including G. sulfurreducens and G. metallireducens, are used for bioremediation and electricity generation from waste organic matter and renewable biomass. The constraint-based modeling approach enables the development of genome-scale in silico models that can predict the behavior of complex biological systems and their responses to the environments. Such a modeling approach was applied to provide physiological and ecological insights on the metabolism of G. metallireducens.

RESULTS: The genome-scale metabolic model of G. metallireducens was constructed to include 747 genes and 697 reactions. Compared to the G. sulfurreducens model, the G. metallireducens metabolic model contains 118 unique reactions that reflect many of G. metallireducens{\textquoteright} specific metabolic capabilities. Detailed examination of the G. metallireducens model suggests that its central metabolism contains several energy-inefficient reactions that are not present in the G. sulfurreducens model. Experimental biomass yield of G. metallireducens growing on pyruvate was lower than the predicted optimal biomass yield. Microarray data of G. metallireducens growing with benzoate and acetate indicated that genes encoding these energy-inefficient reactions were up-regulated by benzoate. These results suggested that the energy-inefficient reactions were likely turned off during G. metallireducens growth with acetate for optimal biomass yield, but were up-regulated during growth with complex electron donors such as benzoate for rapid energy generation. Furthermore, several computational modeling approaches were applied to accelerate G. metallireducens research. For example, growth of G. metallireducens with different electron donors and electron acceptors were studied using the genome-scale metabolic model, which provided a fast and cost-effective way to understand the metabolism of G. metallireducens.

CONCLUSION: We have developed a genome-scale metabolic model for G. metallireducens that features both metabolic similarities and differences to the published model for its close relative, G. sulfurreducens. Together these metabolic models provide an important resource for improving strategies on bioremediation and bioenergy generation.},
	keywords = {Biodegradation, Environmental, Biomass, Computer Simulation, Ecosystem, Electron Transport, Energy Metabolism, Genome, Bacterial, Geobacter, Iron, Metabolic Networks and Pathways, Models, Biological, Models, Genetic, Mutation, Phenotype, Species Specificity, Systems Biology},
	issn = {1752-0509},
	doi = {10.1186/1752-0509-3-15},
	author = {Sun, Jun and Sayyar, Bahareh and Butler, Jessica E and Pharkya, Priti and Fahland, Tom R and Famili, Iman and Schilling, Christophe H and Lovley, Derek R and Mahadevan, Radhakrishnan}
}
@article {700,
	title = {Characterizing regulation of metabolism in Geobacter sulfurreducens through genome-wide expression data and sequence analysis.},
	journal = {OMICS},
	volume = {12},
	year = {2008},
	month = {2008 Mar},
	pages = {33-59},
	abstract = {Geobacteraceae are a family of metal reducing bacteria with important applications in bioremediation and electricity generation. G. sulfurreducens is a representative of Geobacteraceae that has been extensively studied with the goal of extending the understanding of this family of organisms for optimizing their practical applications. Here, we have analyzed gene expression data from 10 experiments involving environmental and genetic perturbations and have identified putative transcription factor binding sites (TFBS) involved in regulating key aspects of metabolism. Specifically, we considered data from both a subset of 10 microarray experiments (7 of 10) and all 10 experiments. The expression data from these two sets were independently clustered, and the upstream regions of genes and operons from the clusters in both sets were used to identify TFBS using the AlignACE program. This analysis resulted in the identification of motifs upstream of several genes involved in central metabolism, sulfate assimilation, and energy metabolism, as well as genes potentially encoding acetate permease. Further, similar TFBS were identified from the analysis of both sets, suggesting that these TFBS are significant in the regulation of metabolism in G. sulfurreducens. In addition, we have utilized microarray data to derive condition specific constraints on the capacity of key enzymes in central metabolism. We have incorporated these constraints into the metabolic model of G. sulfurreducens and simulated Fe(II)-limited growth. The resulting prediction was consistent with data, suggesting that regulatory constraints are important for simulating growth phenotypes in nonoptimal environments.},
	keywords = {Gene Expression Regulation, Bacterial, Genome, Bacterial, Geobacter, Models, Genetic, Oligonucleotide Array Sequence Analysis, Sequence Analysis, DNA, Transcription, Genetic},
	issn = {1536-2310},
	doi = {10.1089/omi.2007.0043},
	author = {Mahadevan, Radhakrishnan and Yan, Bin and Postier, Brad and Nevin, Kelly P and Woodard, Trevor L and O{\textquoteright}Neil, Regina and Coppi, Maddalena V and Meth{\'e}, Barbara A and Krushkal, Julia}
}
