Characterization of Metabolism in the Fe(III)-Reducing Organism Geobacter sulfurreducens by Constraint-Based Modeling

Abstract

Geobacter sulfurreducens is a well-studied representative of the Geobacteraceae, which play a critical role in organic matter oxidation coupled to Fe(III) reduction, bioremediation of groundwater contaminated with organics or metals, and electricity production from waste organic matter. In order to investigate G. sulfurreducens central metabolism and electron transport, a metabolic model which integrated genome-based predictions with available genetic and physiological data was developed via the constraint-based modeling approach. Evaluation of the rates of proton production and consumption in the extracellular and cytoplasmic compartments revealed that energy conservation with extracellular electron acceptors, such as Fe(III), was limited relative to that associated with intracellular acceptors. This limitation was attributed to lack of cytoplasmic proton consumption during reduction of extracellular electron acceptors. Model-based analysis of the metabolic cost of producing an extracellular electron shuttle to promote electron transfer to insoluble Fe(III) oxides demonstrated why Geobacter species, which do not produce shuttles, have an energetic advantage over shuttleproducing Fe(III) reducers in subsurface environments. In silico analysis also revealed that the metabolic network of G. sulfurreducens could synthesize amino acids more efficiently than that of Escherichia coli due to the presence of a pyruvate-ferredoxin oxidoreductase, which catalyzes synthesis of pyruvate from acetate and carbon dioxide in a single step. In silico phenotypic analysis of deletion mutants demonstrated the capability of the model to explore the flexibility of G. sulfurreducens central metabolism and correctly predict mutant phenotypes. These results demonstrate that iterative modeling coupled with experimentation can accelerate the understanding of the physiology of poorly studied but environmentally relevant organisms and may help optimize their practical applications.

Flux Analysis of Central Metabolic Pathways in Geobacter metallireducens during Reduction of Soluble Fe(III)-Nitrilotriacetic Acid

“…On the other hand, the NADP ϩ -dependent malic enzyme, which is inhibited by the presence of acetyl-CoA (13) and whose corresponding gene was annotated in the genome, had no flux. These results are consistent with the predictions from the genome-scale, constraints-based model (22). With respect to energy production, zero flux through the glyoxylate shunt and malic enzyme maximizes the total carbon flow through the oxidative TCA cycle and thus produces the most reducing power (NADH).…”

“…2). In general, the isotopomer model gave results consistent with the previous predictions from a constraints-based model for a closely related species, G. sulfurreducens (22). However, the presence of PEP carboxykinase was not predicted by the constraints-based model but was found using the isotopomer model.…”

“…Under standard conditions (1 atm and 25°C, indicated by ), Fe 3ϩ (⌬G ϭ Ϫ24.38 kcal/eq) has a similar electron potential as oxygen (⌬G ϭ Ϫ25.28 kcal/eq) (23). However, the Geobacter Fe(III) reduction site is extracellular (not in the cytoplasm); under Fe 3ϩ -NTA reduction, the electrons have to be transported outside the cell or into the periplasmic cytochrome pool, but the protons remain in the cytoplasm (22). This could result in dissipation of the membrane potential and acidifying the cytoplasm, which in turn could reduce the biomass yield that results from acetate via Fe 3ϩ reduction compared to that obtained during oxygen or fumarate reduction (9,22).…”

“…To quantitatively analyze central metabolism in Geobacter sulfurreducens, a constraint-based model was developed using the annotated genome sequence and a series of physicochemical constraints (thermodynamic directionality, enzymatic capacity, and reaction stoichiometry) (22). While the model provided important insight into energy conservation, biosynthesis of building blocks (such as amino acids), and the relationship of the genotype to its phenotype, underdetermined models require one to assume an objective function (i.e., maximizing the specific growth rate) that may or may not be accurate and underdetermined models may have difficulty predicting fluxes through reversible reactions or reactions that may form futile cycles (7,32,39).…”

The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli

“…This growth expectation is in part based on the on-going reconstruction of additional cellular processes, such as transcriptional regulation and protein production. Computations based on genome-scale models are also beginning to influence other areas of industrial microbiology such as generation of renewable energy [88][89][90] and bioremediation 89 .…”