Metabolic response of Geobacter sulfurreducens towards electron donor/acceptor variation
© Yang et al; licensee BioMed Central Ltd. 2010
Received: 6 August 2010
Accepted: 22 November 2010
Published: 22 November 2010
Geobacter sulfurreducens is capable of coupling the complete oxidation of organic compounds to iron reduction. The metabolic response of G. sulfurreducens towards variations in electron donors (acetate, hydrogen) and acceptors (Fe(III), fumarate) was investigated via 13C-based metabolic flux analysis. We examined the 13C-labeling patterns of proteinogenic amino acids obtained from G. sulfurreducens cultured with 13C-acetate.
Using 13C-based metabolic flux analysis, we observed that donor and acceptor variations gave rise to differences in gluconeogenetic initiation, tricarboxylic acid cycle activity, and amino acid biosynthesis pathways. Culturing G. sulfurreducens cells with Fe(III) as the electron acceptor and acetate as the electron donor resulted in pyruvate as the primary carbon source for gluconeogenesis. When fumarate was provided as the electron acceptor and acetate as the electron donor, the flux analysis suggested that fumarate served as both an electron acceptor and, in conjunction with acetate, a carbon source. Growth on fumarate and acetate resulted in the initiation of gluconeogenesis by phosphoenolpyruvate carboxykinase and a slightly elevated flux through the oxidative tricarboxylic acid cycle as compared to growth with Fe(III) as the electron acceptor. In addition, the direction of net flux between acetyl-CoA and pyruvate was reversed during growth on fumarate relative to Fe(III), while growth in the presence of Fe(III) and acetate which provided hydrogen as an electron donor, resulted in decreased flux through the tricarboxylic acid cycle.
We gained detailed insight into the metabolism of G. sulfurreducens cells under various electron donor/acceptor conditions using 13C-based metabolic flux analysis. Our results can be used for the development of G. sulfurreducens as a chassis for a variety of applications including bioremediation and renewable biofuel production.
Geobacter species conserve energy for growth by coupling the complete oxidation of organic compounds to the reduction of Fe(III) and a variety of toxic and radioactive metals [1–4]. Geobacter sulfurreducens produce electrically conductive pili that function as nano-wires to promote electron transfer to insoluble electron acceptors such as Fe(III) oxide and electrodes [5, 6]. As a result of these properties, Geobacter species are utilized to harvest electricity from waste organic matter [7, 8] and have served as biocatalysts in microbial fuel cell applications [9, 10]. Geobacter species have great biotechnological potential for contaminant removal from groundwater and understanding their physiology is crucial for optimizing such applications.
G. sulfurreducens has served as a model organism for Geobacter species as it is amenable to genetic manipulation and was the first Geobacter species to have its genome fully sequenced [11, 12]. Constraint-based in silico modeling studies have been applied to understand metabolic characteristics of Geobacter species [2, 4, 13]. The in silico study of G. sulfurreducens metabolism has enabled prediction of the metabolic response of Geobacter species to a variety of genetic and culture perturbations in terms of a genome-scale metabolic flux balance analysis. In general, constraint-based in silico modeling approaches necessitate a biological objective function such as specific growth rate that can be minimized or maximized in order to predict steady-state metabolic flux distributions. Based upon the overall stoichiometry of the metabolic model, which is typically an underdetermined system, optimal solutions of steady-state fluxes are computed by minimizing/maximizing the selected objective. However, such optimal solutions are objective-dependent, and a proper choice of an objective is non-trivial and can be condition-specific . Therefore, the information predicted by a constraint-based in silico approach needs to be interpreted carefully in the context of the actual in vivo functional objective of the system.
Metabolic flux analysis using isotopic labeling techniques provide a means to study metabolic pathway activities in vivo without the bias of the selection of a particular biological objective function. Amongst available techniques, 13C-based metabolic flux analysis (13CMFA) has proven to be the most advanced tool for quantifying in vivo intracellular pathway activities [15–18]. Modeling and experimental/analytical techniques for 13CMFA are well-established, and the method has been utilized to gain a quantitative understanding of a variety of biological systems [15–30]. Recently, 13CMFA has also been applied to Geobacter to unveil central pathway fluxes in G. metallireducens and to elucidate an alternative isoleucine biosynthetic pathway in G. sulfurreducens.
G. sulfurreducens can utilize acetate and hydrogen as electron donors, Fe(III) and fumarate as electron acceptors [32–34] and has a single bifunctional enzyme that catalyzes both fumarate reduction and succinate oxidation . Results from previous results suggest that G. sulfurreducens does not utilize fumarate as a carbon source [13, 33, 35]. However, the intracellular fate of fumarate carbons has not been investigated. The goal of this study was to use 13CMFA to quantitatively characterize the in vivo intracellular metabolic flux response of G. sulfurreducens cultured with different electron donors (acetate and hydrogen) and acceptors (Fe(III) and fumarate). Results from the present work are important for the understanding of the central metabolism of G. sulfurreducens and the optimization of bioremediation processes mediated by Geobacter species.
Results and Discussion
Overview of Experimental Design
Cultivation conditions for Geobacter sulfurreducens to study intracellular metabolism with different electron donor/acceptor conditions.
(D = 0.04 h-1)
(D = 0.05 h-1)
(D = 0.05 h-1)
5 mM acetate
1 mM acetate
& 10 mL H2*
5 mM acetate
10 mM acetate
55 mM Fe(III)citrate
55 mM Fe(III)citrate
28 mM fumarate
20 mM fumarate
Steady-State Effluxes in Chemostat Cultures
Extracellular yield coefficients for the three sets of chemostat cultures (E1, E3, E4) were determined from steady-state rate measurements. The complete oxidation of acetate to CO2 releases of 8 electrons, which is sufficient to convert 8 moles of Fe(III) to Fe(II) or 4 moles of fumarate to succinate. For E1 (5 mM acetate + 55 mM Fe(III)citrate), the molar yield of Fe(II) per mole of acetate consumed was 7.1 ± 0.5, suggesting that only 11.3% of the acetate in the growth medium was utilized for biomass synthesis. When fumarate was used as the electron acceptor, the molar yield of succinate per mole of acetate consumed was 2.9 ± 0.2 for E3 (5 mM acetate + 28 mM fumarate) and 2.5 ± 0.2 for E4 (10 mM acetate + 20 mM fumarate), indicating that a higher percentage of acetate, 27.5% to 37.5%, was utilized for biomass synthesis. The molar yield of fumarate uptake on acetate was 2.8 ± 0.1 and 2.5 ± 0.1 in E3 and E4, respectively. The biomass yield coefficient on acetate (YX/DON = gram dry cell weight produced per mmol acetate uptake) of the Fe(III)citrate culture (E1) was 2.8 × 10-3 ± 2 × 10-4 g/mmol, about 4-fold lower than those of the fumarate cultures, 0.013 ± 2 × 10-3 and 0.012 ± 2 × 10-3 for E3 and E4, respectively. Extracellular concentration measurements can be associated with larger uncertainties than mass spectrometric carbon labeling measurements. Thus, the effluxes were set as free parameters to be estimated from 13C labeling measurements during 13CMFA or calculated later from in vivo flux estimates.
Metabolic Fate of Citrate & Fumarate Carbons
In order to assess metabolic flux distributions in G. sulfurreducens grown with Fe(III)citrate as the electron acceptor, we needed to determine whether G. sulfurreducens is able to metabolize citrate in addition to acetate. We also investigated whether G. sulfurreducens can utilize fumarate as a carbon source since previous studies have suggested that fumarate is not utilized as a carbon source [13, 33, 35, 37]. To this end, cells were grown in a batch culture containing 10 mM non-labeled acetate with 55 mM Fe(III)citrate (4.2% [U-13C6]Fe(III)citrate) and 10 mM non-labeled acetate with 27.5 mM fumarate (30% [2,3-13C2]fumarate), respectively. The carbon mass isotopomer distributions (MIDAA) of alanine, glycine, valine, leucine, isoleucine, phenylalanine, serine, aspartate, and glutamate were compared to those obtained from an identical culture containing only non-labeled compounds.
Linear regression of the two sets of MIDAA measured in the acetate/Fe(III)citrate culture gave a slope of 1.003 with R2 of 1.000 and an intercept of 0.000. In addition, the root mean square (RMS)  of the difference between the two MIDAA sets was 0.0006, which was significantly less than the average MIDAA determined measurement error (ca. 0.003) . This result indicates that the citrate carbons were not utilized by G. sulfurreducens cells, Fe(III)citrate served exclusively as an electron acceptor, and that acetate was the sole carbon source in experiments E1 and E2.
In contrast, the acetate/fumarate culture gave a distinct difference from the natural abundance (slope = 1.151, intercept = 0.030, R2 = 0.9326) with an RMS of 0.011. For instance, MIDAA of aspartate gave the largest discrepancy from the natural abundance (RMS = 0.08), followed by glycine (RMS = 0.054), glutamate (RMS = 0.049), serine (RMS = 0.044), phenylalanine (RMS = 0.032), isoleucine (RMS = 0.012), alanine, leucine, and valine (RMS = 0.004). Our results demonstrate that fumarate carbons can be metabolized into different amino acid biosynthesis precursors in the central metabolic pathways. Cellular fumarate utilization was investigated more quantitatively in terms of 13CMFA.
Assessment of Biological Reproducibility
The consistency between biological replicates was evaluated by comparing the MIDAA of replicates. The squared correlation coefficients (R2) between the MIDAA values of the biological replicates (n = 3) were higher than 0.9990 in all the chemostat experiments (E1, E3, E4), suggesting a high consistency between the replicates. Thus, the experimental data were considered to be unbiased by biological variations, and the intracellular metabolic fluxes were computed using the mean values of replicate MIDAA and measured effluxes.
Comparison of Amino Acid Labeling Patterns
Overview of in vivo Fluxes
Abbreviations and EC numbers of the enzymes considered in the central metabolic network of G. sulfurreducens for 13C metabolic flux analysis.
glyceraldehyde-3-phosphate dehydrogenase (NAD)
pyruvate phosphate dikinase
pyruvate synthase (pyruvate ferredoxin oxidoreductase)
isocitrate dehydrogenase (NADP)
succinyl-CoA synthetase (ADP-forming)
succinate dehydrogenase (menaquinone 7)
malic enzyme (NAD)
malic enzyme (NADP)
phosphoenolpyruvate carboxykinase (GTP)
Under the examined four conditions, the majority of consumed acetate was oxidized through the TCA cycle (Figure 2). When comparing fluxes in E1 and E2, the flux through the initial reaction of the TCA cycle (CS/ACONT) in the H2/Fe(III) culture with 1 mM acetate (E2) was significantly less than that obtained from the acetate/Fe(III) culture (E1). The addition of hydrogen increased the flux from acetyl-CoA to pyruvate (POR: pyruvate synthase) as well as other gluconeogenetic fluxes and resulted in a 2-fold higher biomass yield on acetate (cf. YXS values in Figure 2). The coupling of Fe(III) reduction to H2 oxidation, an energy generating process resulted in decreased demand for energy generation by the oxidation of acetyl-CoA via the TCA cycle and therefore increased the fluxes of acetate carbons for gluconeogenesis, biomass synthesis, and other anabolic activities.
Surprisingly, when fumarate was provided as the electron acceptor in both E3 and E4, flux through the initial reactions of the TCA cycle (CS/ACONT) was slightly higher than 1, suggesting that acetate was not the sole source of carbon for the TCA cycle. In addition to acetate, fumarate served as carbon source in these cultures and likely introduced the additional carbons into the TCA cycle. The in vivo flux distribution suggests that when fumarate was provided as the electron acceptor, fumarate was not only reduced to succinate but also converted to malate by fumarase (FUM) and further to oxaloacetate via malate dehydrogenase (MDH). During cell growth with fumarate as the electron acceptor, synthesis of oxaloacetate from fumarate contributed significantly to gluconeogenesis via its conversion to phosphoenolpyruvate by phosphoenolpyruvate carboxykinase (PEPCK/PEPCKG in Figure 2). In addition, there was a significant net conversion of phosphoenolpyruvate into acetyl-CoA (via the combined actions of PDH and/or POR) in the fumarate cultures. This flux accounted for the elevation in the TCA cycle relative to the acetate uptake flux. The fumarate uptake was slightly higher than the succinate secretion, indicating the consumption of fumarate. Our 13CFMA results suggest that fumarate serves not only as an electron acceptor, but also as a carbon source and to a lesser extent, as an electron donor. This finding contrasts with those of previous cultivation and genetic studies [13, 33, 35, 37] which suggested that fumarate was not utilized as a carbon source or an electron donor.
In contrast to the gluconeogenesis during growth with fumarate, no significant gluconeogenetic flux through PEPCK/PEPCKG was observed during growth with Fe(III) citrate, where the conversion of acetyl-CoA into pyruvate by PDH/POR was the main gluconeogenetic flux (Figure 2). In all cases, a small flux through PC was observed that seemed to be necessary for anaplerosis towards oxaloacetate to initiate the TCA cycle. As stated above, PEPCK/PEPCKG also showed anaplerotic function including ATP production and carboxylation in both Fe(III) cultures (E1 and E2), although its contribution to the anaplerosis in the culture with hydrogen (E2) was insignificant.
The flux distributions in acetate/fumarate chemostats E3 and E4 revealed that growing G. sulfurreducens under donor-limiting conditions (E3) versus acceptor-limiting conditions (E4) resulted in differences in fumarate uptake and succinate secretion effluxes, as well as in the utilization of the fumarate carbon source. In both cases, the net fumarate uptake flux was higher than the sum of succinate secretion, further suggesting that fumarate was utilized as an additional carbon source. The reductive flux of SUCOAS/ATO/FRD5 was higher in the donor-limited chemostat than that in the acceptor-limited conditions. Fumarate uptake and succinate secretion effluxes were also larger in E3 than in E4. In addition, the oxidative TCA fluxes (CS/ACONT, AKGD/OOR, FUM, MDH) in E3 were slightly higher than those in E4. Our results suggest that excessive fumarate in E3 resulted in elevation of the reductive flux of succinate dehydrogenase in conjunction with increased oxidative TCA fluxes. Furthermore, excessive fumarate present in E3 elevated the initial flux of gluconeogenesis carried out by PEPCK/PEPCKG. A more detailed investigation of the fumarate cultures is provided in a later section entitled 'Fumarate Utilization'.
Branch Point Flux Distributions
The synthesis of phosphoenolpyruvate is one key branch point of gluconeogenesis. As shown in Figure 3-A, the major pathway for phosphoenolpyruvate synthesis for gluconeogenesis varied with electron acceptors. When Fe(III) was the electron acceptor (E1 & E2), phosphoenolpyruvate for gluconeogenesis was generated almost exclusively (89 - 99%) from pyruvate by PYK/PPDK/PPS, and phosphoenolpyruvate synthesis via the decarboxylation of oxaloacetate (PEPCK/PEPCKG) did not contribute significantly to gluconeogenesis. In contrast, when fumarate was provided as the electron acceptor (E3 & E4), the decarboxylation of oxaloacetate (PEPCK/PEPCKG) was the main route for phosphoenolpyruvate biosynthesis for gluconeogenesis. In the acceptor-limited culture (E4), phosphoenolpyruvate for gluconeogenesis was synthesized almost exclusively from oxaloacetate (ca. 93%), whereas in the donor-limited culture ca. 60% of phosphoenolpyruvate for gluconeogenesis was generated from oxaloacetate by PEPCK/PEPCKG by consuming ATP/GTP.
Conversion of pyruvate to oxaloacetate by pyruvate carboxylase (PC) plays a key role in anaplerosis. As shown in Figure 3-B this branch point of anaplerosis was less sensitive towards electron acceptor variation than gluconeogenesis. In the both Fe(III) cultures, ca. 9% of pyruvate was converted into oxaloacetate for anaplerosis, whereas the amount of pyruvate that was diverted to anaplerosis varied from 4 to 15% during growth with fumarate. This variation appeared to reflect the degree to which oxaloacetate was diverted to gluconeogenesis. In the acceptor-limited culture (E4), where 90-95% of the oxaloacetate synthesized from fumarate was used for gluconeogenesis, about 15% of pyruvate was utilized for anaplerosis. In contrast, in the donor-limited culture (E3), 57-61% of oxaloacetate was consumed for gluconeogenesis and 4% of pyruvate was diverted to anaplerosis.
The condensation of acetyl-CoA and oxaloacetate (CS/ACONT) is the initiation step of the TCA cycle. As shown in Figure 3-C.1, the relative amount of acetyl-CoA (between 92% and 97%) entering the TCA cycle was comparable for all cultivation conditions. The relative amount of acetyl-CoA entering the TCA cycle was nearly identical for the two fumarate cultures (E3 and E4). In the Fe(III) cultures, the percentage of acetyl-CoA entering the TCA cycle in the culture with acetate as the sole electron donor (97%) was higher than that in the presence of both hydrogen and acetate as the electron donors (92%). Examination of oxaloacetate utilization (Figure 3-C.2) revealed that nearly all of the oxaloacetate produced during growth via Fe(III) reduction (96 - 99%) was utilized to initiate the TCA cycle, whereas only 82% to 85% of oxaloacetate utilized to initiate the TCA cycle in the two fumarate cases. This difference can be attributed to the utilization of fumarate as an additional carbon source for gluconeogenesis and amino acid biosynthesis.
A recent study  indicated that G. sulfurreducens has two pathways for isoleucine biosynthesis: the precursor 2-oxobutanoate can be generated (i) by the deamination of threonine and (ii) from pyruvate and acetyl-CoA through the citramalate pathway. Risso et al. (2008)  observed that the citramalate pathway accounted for the majority of isoleucine biosynthesis during growth with fumarate. This was also the case in the present study where 88 to 93% of 2-oxobutanoate was synthesized from pyruvate and acetyl-CoA in the two fumarate cultures (Figure 3-D.1). A smaller fraction of 2-oxobutanoate, ca. 70%, was produced via the citramalate pathway in the acetate Fe(III) culture (E1). In contrast, the 2-oxobutanoate was synthesized almost exclusively from threonine (98 - 99%) in E2 culture containing hydrogen, Fe(III), and 1 mM acetate. During growth in the presence of hydrogen, decreased demand for energy production by the TCA cycle may result in TCA cycle intermediates such as oxaloacetate (main precursor for aspartate and threonine), more available for other uses such as amino acid biosynthesis. In fact, a complete TCA cycle is not required during growth on hydrogen .
G. sulfurreducens also has two pathways for the biosynthesis of glycine: through the conversion of threonine to glycine and acetaldehyde by threonine aldolase (THRLAD) and from the conversion of serine to glycine by glycine hydroxymethyltransferase (GHMT). 13CMFA indicated that the percentages of threonine converted into glycine and acetaldehyde varied under different conditions (Figure 3-D.2). In E1, 99% of threonine was converted to glycine and acetaldehyde. The acetaldehyde was further converted to acetyl-CoA (generating NADH) and the acetyl-CoA was then recycled into the central metabolic pathways.
Another interesting observation which has not been previously described in the literature was that a large portion of 3-phosphoglycerate (75 - 89%) was converted to serine (Figure 3-D.3). At this metabolic branch point, the flux into glyceraldehyde 3-phosphate for gluconeogenesis was kept at a relatively low level corresponding to anabolic demands. Serine was subsequently converted to pyruvate by serine deaminase. As shown in Figure 2, there were significant fluxes through serine. During growth with Fe(III) as the electron acceptor (E1, E2), there was a ATP-consuming futile cycle consisting of phosphoenolpyruvate, phosphoglycerate, serine, and pyruvate, where phosphoenolpyruvate synthase (PPS) and/or pyruvate phosphate dikinase (PPDK) consume ATP when converting pyruvate to phosphoenolpyruvate.
In spite of its small contribution to 2-oxobutanoate biosynthesis, a high level of threonine deaminase activity (25-higher than that of citramalate synthase) has been previously detected in soluble extracts of G. sulfurreducens growing on fumarate . The threonine deaminase of G. sulfurreducens is also capable of deaminating serine to pyruvate , and is likely the enzyme deaminating serine in G. sulfurreducens, as this species does not contain the Fe(II)-dependent and oxygen sensitive serine deaminases gene found in Clostridia and plants. Moreover, knocking out the threonine deaminase eliminated all detectable serine deaminase activity in soluble extracts prepared under aerobic conditions . Given the presence of relatively high levels of serine deaminase activity in G. sulfurreducens extracts, the relatively high flux through serine deaminase that observed by 13CMFA is plausible.
It has been hypothesized that futile cycles in cellular metabolism are involved in the regulation of biochemical pathways. Quian and Beard (2006)  suggested that futile cycles actively shift the effective equilibrium by expending energy where the magnitude of changes in effective equilibria and sensitivities is a function of the amount of energy used by a futile cycle. Also, it has been suggested that cellular regulation of the ATP/ADP ratio depends on both the specific growth rate and the environmental conditions . Tang et al. (2007)  has found futile cycle activity in Geobacter metallireducens, however metabolic function of futile cycles is yet fully understood. The observed futile cycle might be related to an important metabolic function, e.g., in regulating substrate utilization for gluconeogenesis and the oxidative TCA cycle.
Specific Metabolic Fluxes
Specific fluxes (fluxes normalized by the biomass yield estimate: (mmolmetablite/h)(gbiomass/h)-1) in the central metabolic pathways of the experiments listed in Table 1.
specific metabolic fluxes
PFK, FBP, FBA, TPI
PYK, PPDK, PPS
pyruvate ↔ acetyl-CoA
pentose phosphate pathway
decarboxylic acid transporter
Precursor demand of G. sulfurreducens from the intermediary metabolites involved in the central metabolic pathways in Figure 2.
Precursor demand of G. sulfurreducens
As indicated in Figure 2, the initial step in gluconeogenesis was the generation of pyruvate from acetyl-CoA (POR) in the Fe(III) cultures and phosphoenolpyruvate formation from oxaloacetate by PEPCK/PEPCKG in the fumarate cultures. As shown in Table 3, the specific fluxes of POR were identical in the two Fe(III) cultures, and the specific fluxes of PEPCK/PEPCKG in the fumarate cultures were similar. Thus, the initial gluconeogenetic flux per unit biomass synthesis remained constant when the same electron acceptor was utilized.
Also shown in Table 3, the specific flux through the TCA cycle during growth with Fe(III) was approximately 2.4-fold larger in E1 (5 mM acetate) than E2 (H2 + 1 mM acetate). This is due to the direct energy production via hydrogen oxidation which decreased the energy production demand for the TCA cycle. However, energy generation via hydrogen oxidation did not appear to completely replace energy generation via acetate oxidation by the TCA cycle. During growth in the presence of hydrogen and 1 mM acetate, flux through the TCA cycle was higher than what was required for the anabolic demand for α-ketoglutarate and oxaloacetate, and a significant amount of acetate was oxidized via the TCA cycle. One reason of the energy production via acetate oxidation in the presence of hydrogen might be the relatively poor solubility of H2 in water. The Henry's constant of H2 in water is only 7.8 × 10-4 molL-1atm-1 at 298°K and therefore the dissolved H2 concentration at 0.60 atm H2 is approximately 0.5 mM. This can also be due to other metabolic factors such as hydrogenase activity [41, 42] or cell preference for generating reducing power through the oxidative TCA cycle.
In the fumarate cultures, the specific acetate uptake and TCA cycle activity was dramatically lower than that in the Fe(III) cultures (Table 3). The specific acetate uptake in the two fumarate cultures was 65 to 66 mmol acetyl-CoA per gram biomass synthesis as compared to 166 to 369 mmol of acetyl-CoA per gram biomass synthesis for the Fe(III) cultures (Table 3). The standard redox potential of the half reaction Fe3+ + e- → Fe2+ (E° = 771 mV) is higher than that of fumarate2- + 2e- + 2H+ → succinate2- (E° = 31 mV). Thus, it is expected that a higher electromotive force (ΔE°) would be generated by the acetate/Fe(III) pair than the acetate/fumarate pair. However, the fumarate cultures consumed less acetate per unit biomass formation than the Fe(III) cultures, suggesting that the cells in the fumarate cultures utilize acetate more efficiently than in the Fe(III) cultures. Higher biomass yields on acetate in the fumarate cultures relative to Fe(III) have been previously reported [2, 32, 36] and is likely due to the fact that Fe(III) is reduced on the outside of the cells which results in an additional energetic cost for exporting electrons.
The 13CMFA results suggest that G. sulfurreducens utilizes fumarate not only as the electron acceptor for acetate oxidation but also as an additional carbon source. Based on efflux measurements by HPLC, fumarate uptake and succinate secretion were found to be very close in both fumarate cultures (cf. 'Steady-State Effluxes in Chemostat Cultures' section). However, the optimal solutions found by the stochastic 13CMFA runs resulted in larger fumarate uptake than succinate secretion (Figure 2) and the efflux estimates were within the statistical range given by the means and standard deviations determined experimentally (95% confidence interval). As a result, the small percentage (< 10%) of fumarate consumed as a carbon source in the fumarate cultures, which could not be determined by HPLC efflux measurements was discovered by 13CMFA with more accurate GC/MS labeling measurements.
As shown in Table 3, the uptake of fumarate increased the specific oxidative TCA fluxes of fumarase (FUM) and malate dehydrogenase (MDH) compared to that of α-ketoglutarate dehydrogenase (AKGD/OOR). Consequently, phosphoenolpyruvate carboxykinase (PEPCK/PEPCKG) was the enzyme responsible for initiating gluconeogenesis in the fumarate cultures, while pyruvate synthase (POR) initiated gluconeogenesis in the Fe(III) cultures. In the fumarate cultures, acetyl-CoA was replenished from pyruvate (PDH/POR) which was produced by phosphoenolpyruvate through 3-phosphoglycerate and serine. Between the two fumarate cultures, cells in the donor-limited condition E3 had higher net fumarate reduction, succinate secretion, oxidative TCA activities, and gluconeogenesis activities than those in the acceptor-limited condition E4 (Table 3).
We further calculated the net production of redox equivalents (NAD(P)H and menaquinol) and carbon dioxide from the in vivo flux estimates. Because G. sulfurreducens can utilize both NADH and NADPH for Fe(III) and fumarate reduction [43, 44]; NADH and NADPH are pooled for redox balance. NAD(P)H is produced in the central metabolic network by the reactions ICDHy (isocitrate → α-ketoglutarate), AKGD/OOR (α-ketoglutarate → succinyl-CoA), MDH (malate → oxaloacetate), ME1/ME2 (malate → pyruvate), PDH/POR (pyruvate → acetyl-CoA), GAPD (glyceraldehyde 3-phosphate → 1,3-bisphosphoglycerate), and ADA (acetaldehyde → acetyl-CoA). In addition, cells consume 14.2 mmol NADPH and produce 2.32 mmol NADH per gram biomass synthesis based on the genome-scale model . 3-phosphoglycerate dehydrogenase involved in serine biosynthesis produces NADH, yet the next reaction carried out by 3-phosphoserine aminotransferase involves conversion of glutamate to 2-oxoglutrate for transamination. Without 2-oxoglutamate secretion, glutamate has to be regenerated from 2-oxoglutarate which consumes one redox equivalent. Hence, there is no net production of redox equivalent in this case. In G. sulfurreducens, FRD5 reduces menaquinone to menaquinol when succinate is oxidized to fumarate and vice versa for the fumarate reduction. The fluxes related to decarboxylation/carboxylation are ICDHy, AKGD/OOR, PC, ME1/ME2, PEPCK/PECKG, PDH/POR, and other biosynthetic pathways. In addition, cells produce about 1.36 mmol CO2 per gram biomass synthesis. Details of anabolic NADPH net consumption, NADH net production, and net decarboxylation are listed in additional file 1.
In the acetate/Fe(III) culture (E1), the molar yields of redox equivalents and CO2 net production on acetate were 3.97 ± 0.08 and 1.97 ± 0.05, respectively. These corresponded to a molar yield of Fe(III) reduction on acetate of 7.94 ± 0.16 and a ratio of Fe(II) to CO2 production of 4.03 ± 0.13. Comparing the stoichiometry of complete acetate oxidation with Fe(III), i.e., CH3COOH + 8Fe3+ + 10H2O → 2CO2 + 8Fe2+ + 8H3O+, the Fe(III) reduction and CO2 production drawn from the in vivo flux estimates for E1 are consistent with the theoretical stoichiometry.
The direct oxidation of hydrogen coupled with Fe(III) reduction is H2 + 2Fe3+ + 2H2O → 2Fe2+ + 2H3O+[33, 45]. Despite hydrogen utilization, cells in the hydrogen/Fe(III) culture (E2) still produced 3.56 ± 0.05 moles of redox equivalents with 1.80 ± 0.04 moles of CO2 per mole of acetate taken up. These results corresponded to a molar yield of Fe(III) reduction on acetate of 7.12 ± 0.10 and a ratio of Fe(II) to CO2 production of 3.96 ± 0.10. Thus, Fe(III) reduction together with CO2 production coincides with the theoretical stoichiometry of Fe(III) reduction on acetate. In contrast to E1, cells oxidized less acetate via the TCA cycle (smaller yield of Fe(III) reduction and reduced TCA fluxes) and consequently doubled biomass yield on acetate (Figure 2 & Table 3).
The complete acetate oxidation with fumarate follows CH3COOH + 4C4H4O4 + 2H2O → 2CO2 + 4C4H6O4. The net conversion of fumarate to succinate per acetate was 2.9 ± 0.1 in the donor-limited culture (E3) and 2.5 ± 0.2 in the acceptor-limited (E4). The molar yield of CO2 production on acetate was comparable with the theoretical stoichiometry: it was 2.0 ± 0.5 and 1.8 ± 0.3 in E3 and E4, respectively. These results may be due to additional decarboxylation of fumarate carbons, e.g., gluconeogenesis initiated from oxaloacetate by PEPCK/PEPCKG and acetyl-CoA replenishment from pyruvate by PDH. In addition, two fumarate carbons can potentially be released through these reactions.
In the present work, we characterized the intracellular metabolic response of G. sulfurreducens towards different electron donor/acceptor conditions in vivo using 13C-based metabolic flux analysis. The metabolic characteristics were examined from different aspects of acetate and fumarate utilization, biomass formation, and flux distributions of key metabolic branch points. Expanding on this, we compared redox balances drawn from flux estimates of the different cultures. From 13C labeling measurements and subsequent flux analysis, the greater metabolic discrepancies in the central metabolism, such as different initial step in gluconeogenesis, were observed to be induced by the electron acceptor variation of Fe(III) versus fumarate. As shown by the specific fluxes, metabolic activities in the TCA cycle were perturbed not only by electron acceptor variation (Fe(III) vs. fumarate) but also by electron donor variation (acetate vs. hydrogen). Furthermore, we were able to obtain detailed understanding of cellular fumarate utilization and demonstrated that fumarate acts simultaneously as the electron acceptor and an additional carbon source, as previously hypothesized elsewhere . This seems to be the reason why cells in the fumarate cultures initiated gluconeogenesis via phosphoenolpyruvate decarboxykinase and resulting in the higher biomass yield on acetate than in the Fe(III) cultures.
In the hydrogen/Fe(III) culture, we found that cells still maintained the oxidative TCA cycle, with reduced activities as compared to the acetate/Fe(III) culture. From redox balance calculations, we observed that cells gained redox equivalents from both hydrogen and acetate; i.e., acetate supplemented in the hydrogen culture was not only utilized for anabolic demand but also oxidized along with hydrogen by Fe(III).
The two fumarate cultures with different ratios of acetate and fumarate gave discrepancies in metabolic fluxes per unit acetate uptake or per unit biomass synthesis including fumarate uptake and succinate secretion. Nevertheless, the two cultures appeared to have some physiological similarities. In particular, examination of TCA fluxes scaled by fumarate uptake elucidated metabolic similarities between the fumarate cultures in terms of fumarate utilization. The notable discrepancy between the two cultures was reversibility of fumarate reductase.
G. sulfurreducens has great potential for use in applications such as harvesting bioelectricity and environmental remediation. In these applications, understanding the metabolism of G. sulfurreducens with different electron donors and acceptors will allow for improved strategies or designs. Along with in silico studies using material and energy balances , the in vivo information gained from the 13C metabolic flux analysis in the present work can aid improvements of bioprocesses using this interesting microorganism. For example, the flux distributions in donor limiting or acceptor limiting conditions coupled with microbial community models may help improve bioremediation strategies. The flux results of acetate and H2 as donors can provide insights into certain co-cultures or microbial communities containing G. sulfurreducens that produce bioelectricity in microbial fuel cells, and can be used to improve designs for higher electricity production. Also, other fascinating metabolic capabilities of Geobacter species such as degrading variety of organic materials, including aromatic compounds [1, 47] and reducing toxic and radioactive metals [45, 48, 49], can be investigated using 13C metabolic flux analysis in the future.
Experimental Design & Cultivation Conditions
Geobacter sulfurreducens (ATCC51573)  was cultured at 30°C under strict anaerobic conditions with an N2:CO2 atmosphere (8:20) in a defined freshwater medium  either in pressure tubes or in chemostats as previously described .
To investigate the metabolic response of G. sulfurreducens to variations in electron donors and acceptors, three chemostat experiments (E1, E3, E4), in which acetate was provided as the electron donor and carbon source and either Fe(III)citrate or fumarate served as the electron acceptor, were conducted. Three biological replicates were performed for each of the three experiments and chemostats were run at a dilution rate of either 0.04 h-1 (E1) or 0.05 h-1 (E3 and E4). Cells were harvested at steady state, after five volume refills to achieve isotopic steady-state and to make the fraction of inoculum negligible. To confirm steady-state, substrate (s) and biomass (x) concentrations were measured to verify no accumulation of substrate (d[s]/dt = 0) as well as biomass (d[x]/dt = 0).
In addition, one batch experiment (E2) was performed in which both acetate and hydrogen were provided as electron donors and Fe(III)citrate served as the electron acceptor. This experiment consisted of four replicate cultures, which were harvested and pooled when the concentration of Fe(II) approached 50 mM. All the batch cultures were transferred (1 vol/vol-%) into 13C-tracer containing minimal medium at least once prior to the initiation of an experiment to extremely minimize the fraction of non-labeled cells. The main cultures with the identical medium were inoculated with the mid-exponential phase 13C-precultures.
All cultures contained a mixture of 70% non-labeled and 30% uniformly labeled acetate (Sigma-Aldrich, St. Louis, MO) as a 13C-tracer carbon source for 13CMFA. A summary of the cultivation conditions is provided in Table 1.
Cell growth was monitored by determining total protein by the bicinchoninic acid method with bovine serum albumin as a standard  and assuming a protein content of 46% of cell dry weight . Organic acids were monitored by high-performance liquid chromatography (HPLC) as previously described .
The amino acids obtained by cell protein hydrolysis were silylated using N-methyl-N-tert-butyldimethylsilyl trifluoroacetamide as previously described [3, 27]. Gas chromatography/mass spectrometry (GC/MS) analysis was carried out using a Hewlett-Packard HP G1723A GC-quadrupole mass selective detector (electron impact), equipped with a DB-5 column (Agilent Technologies). From the mass spectra of t-butyldimethylsilyl (TBDMS)-amino acid derivatives (triplicate measurements), carbon mass isotopomer distributions (MID) were computed using the method described earlier .
The metabolic fluxes were computed from the carbon mass isotopomer distributions obtained from the mass spectrometric labeling analysis of different fragment ions of TBDMS-derivatives of proteinogenic amino acid hydrolysates comprising alanine, glycine, leucine, isoleucine, serine, phenylalanine, aspartate, and glutamate (see additional file 2). The GC/MS fragment ions for those TBDMS-amino acid derivatives are listed elsewhere .
13C Metabolic Flux Analysis
In the objective function (Eq. 1), the covariance-weighted (Σ) sum of squared of the difference between the measurements η (only efflux and 13C-labeling measurements) and the corresponding model prediction F (Θ) are minimized with respect to [0,1)-scaled independent flux variables Θ (12). As the covariance, experimentally determined uncertainties associated with efflux and labeling measurements were applied. The model F (Θ) describes the mathematical relationship between unknown fluxes (ν) and the measurements in terms of two connected equation systems, i.e., the stoichiometry and the carbon isotopomer reactions in the metabolic network. The fluxes ν, which are the dependent variables of Θ in the stoichiometry system, consist of immeasurable intracellular fluxes νu and measurable effluxes νm, i.e., ν = (νu, νm) T . Typically, realistic models are underdetermined, that is, the rank of the stoichiometric matrix S is smaller than the number of entries in νu. This difference between rank(S) and the number of entries of νu equals the number of fluxes that have to be chosen as the design parameters, Θ. Those independent fluxes are estimated from isotopic labeling measurements in 13CMFA.
Here, νS and νP denote the effluxes of substrates and products, respectively, and cS and cP the number of carbons in the corresponding compounds. From precursor relation, cells are expected to produce 1.36 mmol CO2 per gram dry cell weight. In practice, the constraint on carbon balance can be defined as an inequality to consider measurement uncertainties, e.g., between ± 0.05.
The framework of 13CMFA is to draw up an appropriate metabolic network for the biological system of interest. Based on the genome-scale metabolic network of G. sulfurreducens reconstructed by Mahadevan et al. (2006) , the central metabolic network of G. sulfurreducens designed for 13CMFA comprises 26 intracellular fluxes containing 15 bidirectional flux pairs in the tricarboxylic acid (TCA) cycle, gluconeogenesis, pentose phosphate (PP) pathway, amino acid metabolism, and anabolic demands for biomass synthesis. The details enzyme reactions are listed in Table 2. In terms of the null space investigation of the stoichiometric matrix , the metabolic network was found to have 20 independent flux variables that need to be determined from 13C-labeling measurements.
In this metabolic network, the conversion from phosphoenolpyruvate to pyruvate is catalyzed by pyruvate kinase, whereas the reverse reaction from pyruvate to phosphoenolpyruvate by phosphoenolpyruvate synthase and/or pyruvate phosphate dikinase. Also, the conversion of pyruvate to acetyl-CoA is catalyzed by the irreversible pyruvate dehydrogenase, and the bidirectional pyruvate synthase. Enzyme reactions catalyzing the identical substrate/product pairs in the same direction cannot be discriminated by the 13C-based MFA.
The precursor demand of G. sulfurreducens applied to the present study is listed in Table 4. The anabolic fluxes from the listed precursors into biomass synthesis can be calculated by multiplying the biomass yield coefficients with the precursor demand.
In the present work, we utilized two different flux quantities. The relative fluxes utilized in sections 'Overview of in vivo Fluxes' and 'Fumarate Utilization' are the rates normalized to acetate uptake and fumarate uptake, respectively. They can be understood as molar yield coefficients on a particular substrate or the rates of enzyme reactions associated with the uptake of a unit substrate in unit time.
The specific flux can be understood as the rate of a metabolic enzyme reaction associated with the synthesis of a unit biomass in unit time.
Software Implementation & Statistical Data Analysis
All computations involved in carbon mass isotopomer analysis and 13CMFA were implemented using MATLAB (Version 7.8, The Mathworks Inc., Natick, MA). Numerical optimization was carried out using the Optimization Toolbox (Version 4.2) of MATLAB.
The in vivo metabolic fluxes were computed stochastically by starting the numerical optimization runs from arbitrary points and by using normal random numbers of measurement data. Hereby, 13C labeling patterns of amino acids were computed directly if specified in the stoichiometric network model (Figure 2). Otherwise, 13C labeling patterns were computed from the corresponding precursors. The procedure was repeated for 500 times from different starting points to get sample distributions of the in vivo flux estimates resulting from the numerical optimization. The symbolic operations required for metabolic flux modeling such as parametrization and computing partial derivatives required for EMU modeling were implemented using the Symbolic Math Toolbox (Version 3.2.3) of MATLAB.
Statistical data analysis such as random number generation, confidence interval, analysis of variance (ANOVA) and multiple comparison procedure were conducted using the Statistics Toolbox (Version 7.1) of MATLAB. One-way ANOVA was implemented to test the hypothesis that the means of the flux estimates given for the different culture conditions were identical, against the general alternative that they were not. In addition to this, multiple comparisons were performed to obtain information about which pairs of flux mean estimates are significantly different or not.
[U-13C2] acetate was applied to 13CMFA in all the four experiments (Table 1). To verify whether cells are capable of using citrate as a carbon source, [U-13C6] citrate was utilized.
The research was supported by the Office of Science (BER), U. S. Department of Energy, Cooperative Agreement No. DE-FC02-02ER63446. We would also like to thank Steven Petsch and Mark Woodworth for their assistance with the GC/MS analysis of G. sulfurreducens (University of Massachusetts) and John D. Trawick, Robin Osterhout, and Stephanie J. Culler for their scientific advice and proof-reading (Genomatica, Inc.).
- Lovley DR, Giovannoni SJ, White DC, Champine JE, Phillips EJ, Gorby YA, Goodwin S: Geobacter metallireducens gen. nov. sp. nov., a microorganism capable of coupling the complete oxidation of organic compounds to the reduction of iron and other metals. ArchMicrobiol. 1993, 159: 336-344.Google Scholar
- Mahadevan R, Bond DR, Butler JE, Esteve-Nunez A, Coppi MV, Palsson BO, Schilling CH, Lovley DR: Characterization of metabolism in the Fe(III)-reducing organism Geobacter sulfurreducens by constraint-based modeling. Appl Environ Microbiol. 2006, 72: 1558-1568. 10.1128/AEM.72.2.1558-1568.2006.View ArticleGoogle Scholar
- Risso C, Van Dien SJ, Orloff A, Lovley DR, Coppi MV: Elucidation of an alternate isoleucine biosynthesis pathway in Geobacter sulfurreducens. JBacteriol. 2008, 190: 2266-2274. 10.1128/JB.01841-07.View ArticleGoogle Scholar
- Sun J, Sayyar B, Butler JE, Pharkya P, Fahland TR, Famili I, Schilling CH, Lovley DR, Mahadevan R: Genome-scale constraint-based modeling of Geobacter metallireducens. BMC Syst Biol. 2009, 3: 15- 10.1186/1752-0509-3-15.View ArticleGoogle Scholar
- Reguera G, McCarthy KD, Mehta T, Nicoll JS, Tuominen MT, Lovley DR: Extracellular electron transfer via microbial nanowires. Nature. 2005, 435: 1098-1101. 10.1038/nature03661.View ArticleGoogle Scholar
- Reguera G, Nevin KP, Nicoll JS, Covalla SF, Woodard TL, Lovley DR: Biofilm and nanowire production leads to increased current in Geobacter sulfurreducens fuel cells. Appl Environ Microbiol. 2006, 72: 7345-7348. 10.1128/AEM.01444-06.View ArticleGoogle Scholar
- Bond DR, Holmes DE, Tender LM, Lovley DR: Electrode-reducing microorganisms that harvest energy from marine sediments. Science. 2002, 295: 483-485. 10.1126/science.1066771.View ArticleGoogle Scholar
- Holmes DE, Bond DR, O'Neil RA, Reimers CE, Tender LR, Lovley DR: Microbial communities associated with electrodes harvesting electricity from a variety of aquatic sediments. Microb Ecol. 2004, 48: 178-190. 10.1007/s00248-003-0004-4.View ArticleGoogle Scholar
- Lovley DR: Bug juice: harvesting electricity with microorganisms. Nat Rev Microbiol. 2006, 4: 497-508. 10.1038/nrmicro1442.View ArticleGoogle Scholar
- Lovley DR: Microbial fuel cells: novel microbial physiologies and engineering approaches. Curr Opin Biotechnol. 2006, 17: 327-332. 10.1016/j.copbio.2006.04.006.View ArticleGoogle Scholar
- Lovley DR: Cleaning up with genomics: applying molecular biology to bioremediation. NatRevMicrobiol. 2003, 1: 35-44.Google Scholar
- Methe BA, Nelson KE, Eisen JA, Paulsen IT, Nelson W, Heidelberg JF, Wu D, Wu M, Ward N, Beanan MJ, et al.: Genome of Geobacter sulfurreducens: metal reduction in subsurface environments. Science. 2003, 302: 1967-1969. 10.1126/science.1088727.View ArticleGoogle Scholar
- Segura D, Mahadevan R, Juarez K, Lovley DR: Computational and experimental analysis of redundancy in the central metabolism of Geobacter sulfurreducens. PLoS Comput Biol. 2008, 4: e36- 10.1371/journal.pcbi.0040036.View ArticleGoogle Scholar
- Schuetz R, Kuepfer L, Sauer U: Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. MolSystBiol. 2007, 3: 119-Google Scholar
- Antoniewicz MR, Kelleher JK, Stephanopoulos G: Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions. Metab Eng. 2007, 9: 68-86. 10.1016/j.ymben.2006.09.001.View ArticleGoogle Scholar
- Wiechert W: 13C metabolic flux analysis. MetabEng. 2001, 195-206.Google Scholar
- Wittmann C, Heinzle E: Mass spectrometry for metabolic flux analysis. Biotechnol Bioeng. 1999, 62: 739-750. 10.1002/(SICI)1097-0290(19990320)62:6<739::AID-BIT13>3.0.CO;2-E.View ArticleGoogle Scholar
- Yang TH, Frick O, Heinzle E: Hybrid optimization for 13C metabolic flux analysis using systems parametrized by compactification. BMC Syst Biol. 2008, 2: 29- 10.1186/1752-0509-2-29.View ArticleGoogle Scholar
- Antoniewicz MR, Kelleher JK, Stephanopoulos G: Accurate assessment of amino acid mass isotopomer distributions for metabolic flux analysis. AnalChem. 2007, 79: 7554-7559.Google Scholar
- Blank LM, Kuepfer L, Sauer U: Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol. 2005, 6: R49- 10.1186/gb-2005-6-6-r49.View ArticleGoogle Scholar
- Dauner M, Sauer U: GC-MS analysis of amino acids rapidly provides rich information for isotopomer balancing. Biotechnol Prog. 2000, 16: 642-649. 10.1021/bp000058h.View ArticleGoogle Scholar
- Krömer JO, Sorgenfrei O, Klopprogge K, Heinzle E, Wittmann C: In-depth profiling of lysine-producing Corynebacterium glutamicum by combined analysis of the transcriptome, metabolome, and fluxome. J Bacteriol. 2004, 186: 1769-1784. 10.1128/JB.186.6.1769-1784.2004.View ArticleGoogle Scholar
- Sauer U: High-throughput phenomics: experimental methods for mapping fluxomes. Curr Opin Biotechnol. 2004, 15: 58-63. 10.1016/j.copbio.2003.11.001.View ArticleGoogle Scholar
- Sauer U: Metabolic networks in motion: 13C-based flux analysis. MolSystBiol. 2006, 2: 62-Google Scholar
- Wahl SA, Dauner M, Wiechert W: New tools for mass isotopomer data evaluation in 13C flux analysis: mass isotope correction, data consistency checking, and precursor relationships. Biotechnol Bioeng. 2004, 85: 259-268. 10.1002/bit.10909.View ArticleGoogle Scholar
- Wiechert W, Mollney M, Petersen S, de Graaf AA: A universal framework for 13C metabolic flux analysis. Metab Eng. 2001, 3: 265-283. 10.1006/mben.2001.0188.View ArticleGoogle Scholar
- Yang TH, Bolten CJ, Coppi MV, Sun J, Heinzle E: Numerical bias estimation for mass spectrometric mass isotopomer analysis. Anal Biochem. 2009, 388: 192-203. 10.1016/j.ab.2009.03.005.View ArticleGoogle Scholar
- Yang TH, Heinzle E, Wittmann C: Theoretical aspects of 13C metabolic flux analysis with sole quantification of carbon dioxide labeling. Comput Biol Chem. 2005, 29: 121-133. 10.1016/j.compbiolchem.2005.02.005.View ArticleGoogle Scholar
- Zamboni N, Fischer E, Sauer U: FiatFlux--a software for metabolic flux analysis from 13C-glucose experiments. BMC Bioinformatics. 2005, 6: 209- 10.1186/1471-2105-6-209.View ArticleGoogle Scholar
- Quek LE, Wittmann C, Nielsen LK, Kromer JO: OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis. Microb Cell Fact. 2009, 8: 25- 10.1186/1475-2859-8-25.View ArticleGoogle Scholar
- Tang YJ, Chakraborty R, Martin HG, Chu J, Hazen TC, Keasling JD: Flux analysis of central metabolic pathways in Geobacter metallireducens during reduction of soluble Fe(III)-nitrilotriacetic acid. Appl Environ Microbiol. 2007, 73: 3859-3864. 10.1128/AEM.02986-06.View ArticleGoogle Scholar
- Butler JE, Glaven RH, Esteve-Nunez A, Nunez C, Shelobolina ES, Bond DR, Lovley DR: Genetic characterization of a single bifunctional enzyme for fumarate reduction and succinate oxidation in Geobacter sulfurreducens and engineering of fumarate reduction in Geobacter metallireducens. J Bacteriol. 2006, 188: 450-455. 10.1128/JB.188.2.450-455.2006.View ArticleGoogle Scholar
- Caccavo F, Lonergan DJ, Lovley DR, Davis M, Stolz JF, McInerney MJ: Geobacter sulfurreducens sp. nov., a hydrogen- and acetate-oxidizing dissimilatory metal-reducing microorganism. Appl Environ Microbiol. 1994, 60: 3752-3759.Google Scholar
- Coppi MV, O'Neil RA, Lovley DR: Identification of an uptake hydrogenase required for hydrogen-dependent reduction of Fe(III) and other electron acceptors by Geobacter sulfurreducens. J Bacteriol. 2004, 186: 3022-3028. 10.1128/JB.186.10.3022-3028.2004.View ArticleGoogle Scholar
- Galushko AS, Schink B: Oxidation of acetate through reactions of the citric acid cycle by Geobacter sulfurreducens in pure culture and in syntrophic coculture. ArchMicrobiol. 2000, 174: 314-321.Google Scholar
- Esteve-Nunez A, Rothermich A, Sharma M, Lovley DR: Growth of Geobacter sulfurreducens under nutrient-limiting conditions in continuous culture. Environmental Microbiology. 2005, 7: 641-648. 10.1111/j.1462-2920.2005.00731.x.View ArticleGoogle Scholar
- Coppi MV, Leang C, Kaufmann F, O'Neil RA, Bond DR, Lovley DR: Genetic analysis of a putative soluble Fe(III) reductase from Geobacter sulfurreducens. J Bacteriol. 2005, In PreparationGoogle Scholar
- Massart DL: Handbook of chemometrics and qualimetrics. 1997, Amsterdam; New York: ElsevierGoogle Scholar
- Qian H, Beard DA: Metabolic futile cycles and their functions: a systems analysis of energy and control. Syst Biol (Stevenage). 2006, 153: 192-200.View ArticleGoogle Scholar
- Dauner M, Storni T, Sauer U: Bacillus subtilis metabolism and energetics in carbon-limited and excess-carbon chemostat culture. J Bacteriol. 2001, 183: 7308-7317. 10.1128/JB.183.24.7308-7317.2001.View ArticleGoogle Scholar
- Coppi MV: The hydrogenases of Geobacter sulfurreducens: a comparative genomic perspective. Microbiology. 2005, 151: 1239-1254. 10.1099/mic.0.27535-0.View ArticleGoogle Scholar
- Coppi MV, O'Neil RA, Lovley DR: Identification of an uptake hydrogenase required for hydrogen-dependent reduction of Fe(III) and other electron acceptors by Geobacter sulfurreducens. J Bacteriol. 2004, 186: 3022-3028. 10.1128/JB.186.10.3022-3028.2004.View ArticleGoogle Scholar
- Coppi MV, O'Neil RA, Leang C, Kaufmann F, Methe BA, Nevin KP, Woodard TL, Liu A, Lovley DR: Involvement of Geobacter sulfurreducens SfrAB in acetate metabolism rather than intracellular, respiration-linked Fe(III) citrate reduction. Microbiology. 2007, 153: 3572-3585. 10.1099/mic.0.2007/006478-0.View ArticleGoogle Scholar
- Galushko AS, Schink B: Oxidation of acetate through reactions of the citric acid cycle by Geobacter sulfurreducens in pure culture and in syntrophic coculture. Arch Microbiol. 2000, 174: 314-321. 10.1007/s002030000208.View ArticleGoogle Scholar
- Lovley DR, Phillips EJP, Gorby YA, Landa ER: Microbial reduction of uranium. Nature. 1991, 350: 413-416. 10.1038/350413a0.View ArticleGoogle Scholar
- Esteve-Nunez A, Nunez C, Lovley DR: Preferential reduction of Fe(III) over fumarate by Geobacter sulfurreducens. J Bacteriol. 2004, 186: 2897-2899. 10.1128/JB.186.9.2897-2899.2004.View ArticleGoogle Scholar
- Lovley DR, Lonergan DJ: Anaerobic oxidation of toluene, phenol, and p-cresol by the dissimilatory Iron-reducing organism, GS-15. Appl Environ Microbiol. 1990, 56: 1858-1864.Google Scholar
- Lovley DR, Coates JD: Bioremediation of metal contamination. CurrOpinBiotechnol. 1997, 8: 285-289.Google Scholar
- Lovley DR, Dworkin SFERKHS, Stackebrandt E: Fe(III)- and Mn(IV)-reducing prokaryotes. The Prokaryotes. 2000, New York: Springer-Verlag, Inc, http://www.prokaryotes.comGoogle Scholar
- Lovley DR, Phillips EJ: Novel mode of microbial energy metabolism: organic carbon oxidation coupled to dissimilatory reduction of iron or manganese. Appl Environ Microbiol. 1988, 54: 1472-1480.Google Scholar
- Smith PK, Krohn RI, Hermanson GT, Mallia AK, Gartner FH, Provenzano MD, Fujimoto EK, Goeke NM, Olson BJ, Klenk DC: Measurement of protein using bicinchoninic acid. AnalBiochem. 1985, 150: 76-85.Google Scholar
- Antoniewicz MR, Kelleher JK, Stephanopoulos G: Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements. Metab Eng. 2006, 8: 324-337. 10.1016/j.ymben.2006.01.004.View ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.