@article {426,
	title = {Development of a biomarker for Geobacter activity and strain composition; proteogenomic analysis of the citrate synthase protein during bioremediation of U(VI).},
	journal = {Microb Biotechnol},
	volume = {4},
	year = {2011},
	month = {2011 Jan},
	pages = {55-63},
	abstract = {Monitoring the activity of target microorganisms during stimulated bioremediation is a key problem for the development of effective remediation strategies. At the US Department of Energy{\textquoteright}s Integrated Field Research Challenge (IFRC) site in Rifle, CO, the stimulation of Geobacter growth and activity via subsurface acetate addition leads to precipitation of U(VI) from groundwater as U(IV). Citrate synthase (gltA) is a key enzyme in Geobacter central metabolism that controls flux into the TCA cycle. Here, we utilize shotgun proteomic methods to demonstrate that the measurement of gltA peptides can be used to track Geobacter activity and strain evolution during in situ biostimulation. Abundances of conserved gltA peptides tracked Fe(III) reduction and changes in U(VI) concentrations during biostimulation, whereas changing patterns of unique peptide abundances between samples suggested sample-specific strain shifts within the Geobacter population. Abundances of unique peptides indicated potential differences at the strain level between Fe(III)-reducing populations stimulated during in situ biostimulation experiments conducted a year apart at the Rifle IFRC. These results offer a novel technique for the rapid screening of large numbers of proteomic samples for Geobacter species and will aid monitoring of subsurface bioremediation efforts that rely on metal reduction for desired outcomes.},
	keywords = {Amino Acid Sequence, Bacterial Proteins, Biodegradation, Environmental, Biological Markers, Citrate (si)-Synthase, Geobacter, Groundwater, Molecular Sequence Data, Phylogeny, Proteomics, Sequence Alignment, Uranium},
	issn = {1751-7915},
	doi = {10.1111/j.1751-7915.2010.00194.x},
	author = {Wilkins, Michael J and Callister, Stephen J and Miletto, Marzia and Williams, Kenneth H and Nicora, Carrie D and Lovley, Derek R and Long, Philip E and Lipton, Mary S}
}
@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}
}
