Inhibition of a U (VI)-and Sulfate-Reducing Consortia by U (VI)

Aug 18, 2007 - Hung Duc Nguyen , Bin Cao , Bhoopesh Mishra , Maxim I. Boyanov , Kenneth M. Kemner , Jim K. Fredrickson , Haluk Beyenal. Water Research...
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Environ. Sci. Technol. 2007, 41, 6528-6533

Inhibition of a U(VI)- and Sulfate-Reducing Consortia by U(VI) J E N N I F E R L . N Y M A N , * ,† H S I N - I W U , MARGARET E. GENTILE, PETER K. KITANIDIS, AND CRAIG S. CRIDDLE Department of Civil and Environmental Engineering, 380 Panama Mall, Terman Building, Stanford University, Stanford, California 94305-4020

The stimulation of microbial U(VI) reduction is currently being investigated as a means to reduce uranium’s mobility in groundwater, but little is known about the concentration at which U(VI) might inhibit microbial activity, or the effect of U(VI) on bacterial community structure. We investigated these questions with an ethanol-fed U(VI)and sulfate-reducing enrichment developed from sediment from the site of an ongoing field biostimulation experiment at Area 3 of the Oak Ridge Field Research Center (FRC). Sets of triplicate enrichments were spiked with increasing concentrations of U(VI) (from 49 µm to 9.2 mM). As the U(VI) concentration increased to 224 µM, the culture’s production of acetate from ethanol slowed, and at or above 1.6 mM U(VI) little acetate was produced over the time frame of the experiment. An uncoupling inhibition model was applied to the data, and the inhibition coefficient for U(VI), KU, was found to be ∼100 µM U(VI), or 24 mg/L, indicating the inhibitory effect is relevant at highly contaminated sites. Microbial community structure at the conclusion of the experiment was analyzed with terminal restriction fragment length polymorphism (T-RFLP) analysis. T-RFs associated with Desulfovibrio-like organisms decreased in relative abundance with increasing U(VI) concentration, whereas Clostridia-like T-RFs increased.

Introduction A multitude of subsurface environments are contaminated with uranium as a result of mining activities and nuclear weapons manufacturing (1). Though hexavalent uranium, U(VI), sorbs readily to solids, sorption of U(VI) is not an effective strategy to prevent the migration of uranium with groundwater because the soluble concentration of U(VI) in equilibrium with sorbed U(VI) usually exceeds drinking water standards. Bacterial reduction of U(VI) to U(IV) and precipitation of U(IV) is potentially effective as a remediation strategy, however, as U(IV) precipitates have low solubility and soluble uranium concentrations below drinking water standards can be achieved (2). Stimulating the activity of bacteria with subsurface nutrient or electron donor amendment is therefore being investigated as a means of removing uranium from groundwater and preventing its release to surface waters. This strategy is currently being evaluated at * Corresponding author phone: 510-735-3012; fax: 510-596-8855; e-mail: [email protected]. † Current affiliation and contact information: Jennifer Nyman, Malcolm Pirnie, Inc., 2000 Powell Street, Suite 1180, Emeryville, CA 94608. 6528

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a field site at Area 3 of the Environmental Remediation Sciences Program (ERSP) Field Research Center (FRC) in Oak Ridge, Tennessee, and work to date has demonstrated successful biostimulation of in situ U(VI) reduction with intermittent ethanol addition (3). Area 3 of the FRC is adjacent to the source of the subsurface contamination, so groundwater concentrations of U(VI) are high (84-210 µM). Previous studies have noted toxic effects of U(VI) on several genera, including Pseudomonas, Thermoterrabacterium and Zoogloea (4-6). Another study reported inhibition of the growth of a U(VI)-reducing Clostridium sp. upon exposure to increasing concentrations of U(VI) (7), and Tucker et al. (8) observed a decrease in yield of U(VI)reducing Desulfovibrio desulfuricans when grown in the presence of 1 mM U(VI). There has been no investigation, however, into the effects of increasing concentrations of U(VI) on the growth of U(VI)-reducing consortia. Understanding how U(VI) differentially impacts microbial community members is an important factor in predicting the effectiveness of biostimulation for uranium immobilization. Because different types of bacteria vary in their growth rates, ability to reduce U(VI) and ability to gain energy from U(VI) reduction, the composition of a subsurface stimulated community could significantly impact the transformation and transport of uranium. Though the structure of U(VI)reducing communities has been characterized in samples from field experiments (9, 10), model laboratory communities allow for more precise control of variables in a confined system. Accordingly, we used terminal restriction fragment length polymorphism (T-RFLP) analysis, a community fingerprinting technique, in this work to assess the effect of increasing concentrations of U(VI) on the community structure of a model sulfate-reducing culture enriched from FRC Area 3 sediment. Microbial growth models are necessary to interpret results from field-scale biostimulation experiments, to design future remediation scenarios and to optimize removal of uranium from groundwater. To date, however, no model has accounted for the potential inhibition of microbial growth by U(VI). Part of the reason for this may be that previous studies of U(VI) reduction rates have been conducted under nongrowth conditions (11-13). In the field, however, U(VI) reduction will likely occur during growth stimulated by electron donor addition, so models should include reduction rates for growth conditions and any effect of U(VI) on growth rates. We therefore examined and modeled the growth of an ethanol-fed, sulfate-reducing enrichment upon exposure to increasing concentrations of U(VI). The effects of U(VI) on members of the bacterial community were assessed using T-RFLP, and a model incorporating U(VI) reduction during growth and uncoupling inhibition by U(VI) was developed to describe the observed inhibition.

Materials and Methods Development and Maintenance of the Enrichment. Sediment from a core from the FRC Area 3 field site was used in a flow-through column experiment in which ethanol amendment stimulated the reduction of U(VI) (14). After the conclusion of the experiment, subsamples were taken from the column, preserved anaerobically, and used as an inoculum for a sulfate-reducing enrichment. Ethanol served as an electron donor, and enrichments were transferred approximately every 14 days and maintained at 30 °C. Prior to the transfer for the uranium inhibition experiment, the enrichments had not been exposed to U(VI). A complete 10.1021/es062985b CCC: $37.00

 2007 American Chemical Society Published on Web 08/18/2007

description of the development and maintenance of the enrichment is provided elsewhere (15). U(VI) Inhibition Experiment. To assess the effect of uranium on growth of the enrichment and on community structure, fifteen replicate enrichments were established in bicarbonate media supplemented with ∼10 mM ethanol, an average of 6.4 mM sulfate and other amendments as described previously (15). Four mL culture from the same source was inoculated into each of the fifteen enrichments concurrently. These enrichments were divided into five sets of triplicate enrichments: four sets received U(VI) as uranyl chloride and one set of controls received no uranium. The uranium-spiked enrichments received different levels of U(VI), resulting in sets of triplicate enrichments with final average U(VI) concentrations of 49 ( 1.9 µM, 224 ( 1.1 µM, 1.6 ( 0.023 mM, and 9.2 ( 0.039 mM (referred to as Levels 1, 2, 3, and 4, respectively). Samples of the enrichments were periodically removed and analyzed for U(VI) concentration. At the same time, additional samples were removed and centrifuged at 14 000 rpm for 10 min. Supernatant from centrifuged samples was frozen at -20 °C for subsequent analysis of ethanol, acetate, and sulfate. During growth on ethanol, acetate accumulated. When acetate production stabilized, samples were removed for protein and DNA analysis. For control and Level 1 enrichments, acetate accumulation stopped after 14 days. For Levels 2-4 enrichments, acetate accumulation stopped after 18 days. To harvest cells, 7.6 mL culture was collected and centrifuged at 14 000 rpm for 15 min, the supernatant decanted, and the pellets frozen at -20 °C. Separate pellets were preserved for both protein and DNA analyses, and cell pellets from the inoculum were also preserved for protein analysis. DNA Extraction and Amplification. Before DNA extraction, cell pellets were washed to remove sulfides. Pellets were suspended in 1 mL 10 mM Tris-HCl (pH 8.0), centrifuged for 20 min at 14 000 rpm, and decanted. This procedure was then repeated. DNA was extracted from pelleted cells with the UltraClean microbial DNA isolation kit (MoBio Laboratories, Solana Beach, CA) according to the manufacturer’s instructions. The product was quantified with a NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies, Wilmington, DE). 16S rRNA genes were amplified from DNA extracted from pellets preserved at the end of the experiment as described by Nyman et al. (15). The primer combination of 5-hexachlorofluorescein (HEX)-labeled 27f (5′-AGA-GTT-TGA-TCMTGG-CTC-AG-3′) (Operon Biotechnologies, Germantown, MD) and unlabeled 1492r (5′-GGT-TAC-CTT-GTT-ACG-ACTT-3′) (Operon Biotechnologies) was used (16). Terminal Restriction Fragment Length Polymorphism (T-RFLP). We digested16S rDNA with the restriction enzyme Sau96I as described by Nyman et al. (15). Comparisons were made between profiles based on peak height. Profiles with a total peak height of greater than 7500 fluorescent units were considered in the analysis. Total peak height was normalized as described previously (15), with the peak detection threshold set at 50 fluorescent units. None of the peaks discussed in this study were discarded from any profiles through the normalization procedure. Analytical Techniques. U(VI) was measured using a spectrofluorometer (Jobin Yvon Inc., Edison, NJ). Samples were diluted 1:30 in 10% phosphoric acid. The fluorescence of uranyl-phosphate complexes was measured at 515.4 nm in emission acquisition mode. All measurements were referenced to the fluorescence of the background matrix. Sulfate was measured on an ion chromatograph (Dionex, Sunnyvale, CA) fitted with an AS11-HC column. Acetate was measured in 0.03 mM oxalic acid by direct liquid injection to a Hewlett-Packard 5890A gas chromatograph (GC)

(Hewlett-Packard, Palo Alto, CA) with a packed column (80/ 120 Carbopack B-DA/4% CARBOWAX 20M column) and a flame ionization detector (FID). The detection limit for acetate was 0.022 mM. Protein concentration was measured using the Bradford assay (17). Kinetic Model and Error Analysis. A Monod-based saturation model was used to model ethanol consumption, biomass growth, and U(VI) reduction over time. Because sulfate was present throughout the experiment, the electron donor (ethanol) limited the growth of cells. Under electron donor-limiting conditions, equations for substrate utilization and biomass accumulation are given by

qmaxXS dS )dt S + Ks

(1)

dX YeffqmaxXS ) dt S + Ks

(2)

in which S is substrate concentration (here, ethanol, mM), t is time (days), qmax is the maximum specific rate of substrate utilization (mmol ethanol/mg VSS/d), X is biomass concentration (mg VSS/L), Ks is the half-saturation coefficient for ethanol (mM ethanol) and Yeff is effective yield (a measured value, mg VSS/mmol ethanol). In previous work, no metabolic activity (i.e., production of hydrogen or acetate or reduction of sulfate) was observed in controls lacking ethanol in the first 20 days (15), indicating that ethanol is a requirement for growth. Decay of biomass was assumed negligible for the time scale investigated, and a decay term was not included in the model. U(VI) reduction over time was modeled with a second-order rate equation:

dU ) -kUUX dt

(3)

in which kU is the second-order rate coefficient (L/mg VSS/d) and U is U(VI) concentration (µM). Inhibition by U(VI) was modeled using an uncoupling inhibition model (18) according to

Yeff )

Y 1 + U/KU

(4)

where Y is yield (mg VSS/mmol ethanol) and KU is the uranium inhibition coefficient (µM). Uncoupling inhibition models have been applied previously for aromatic hydrocarbons (18-20). These models describe a decrease in Y or increase in decay rate resulting from inhibitors that disrupt the cell membrane or interfere with electron transfer within the membrane (21-22). A noncompetitive inhibition model was also tested for applicability but gave a poor fit to the data. Effective yield (Yeff) of each enrichment was determined as the difference between the final concentration of protein and the protein concentration of the inoculum. Protein concentration was converted to volatile suspended solids (VSS) concentration using a conversion factor determined previously (15). For each U(VI) level, yield values for replicates were averaged. Because U(VI) interfered with the measurement of ethanol, for modeling purposes ethanol concentration was calculated from acetate concentration data by assuming a 1:1 stoichiometric ratio between ethanol consumption and acetate production. In all previous and subsequent work with the culture (for example, see ref 15), the difference between the moles of acetate produced and moles of ethanol consumed was less than 11% of the initial ethanol concentration, which is within the combined error of the analytical methods for ethanol and acetate. Furthermore, Nagpal et al. (23) studied a mixed sulfate-reducing VOL. 41, NO. 18, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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culture (containing Desulfovibrio desulfuricans) in multiple experiments and found the ratio between ethanol consumed and acetate produced was, on average, 1:1. Equations 1-4 were integrated using MATLAB’s ordinary differential equation (ODE) suite (The MathWorks, Inc.). The value of Yeff measured for the control enrichments was used as the value of Y. The set of parameters qmax, Ks, KU, and kU were fit for data from all replicates simultaneously using nonlinear least-squares analysis. Sensitivity coefficients and error were determined based on the linearized approach, a method commonly used in practice and previously used for similar problems (24). Approximate first derivatives of model predictions with respect to each parameter were calculated and compiled into the Jacobian matrix, J. The covariance matrix, C, of the errors of the parameters is given by

C ) σ2(JT × J)-1

(5)

in which JT is the transpose of J, the superscript -1 indicates the inverse of the matrix and σ2 is the mean square fitting error, which is estimated as follows:

σ2 )

1

n

∑ (y

n k)1

model

- yactual)2

(6)

in which n is the number of observations, ymodel represents the predicted value of the kth observation and yactual represents the measured value of the kth observation (25). The standard error of the ith parameter is given by Cii, and the 95% singleparameter confidence region for parameter i is given by ( 2xCii. A matrix of correlation coefficients for the parameter estimates was calculated from elements of the covariance matrix. The absolute values of the correlation coefficients were less than 0.65, indicating unique parameter estimates (25). Sulfate concentrations over time were modeled to check the fit of the model to the measured sulfate data. The fraction of electrons from ethanol converted to biomass, fs0, was calculated from Yeff for the controls as 0.08. An overall equation for metabolism was written according to Rittmann and McCarty (18), and the predicted stoichiometric ratio of sulfate to ethanol was calculated to be 0.46. Modeled ethanol concentration over time was converted to modeled sulfate concentration by multiplying by this factor for sets of controls and enrichments spiked with U(VI). Statistics. Clustering of T-RFLP profiles was performed using the statistical package R Version 2.2.1 for Windows (The R Foundation for Statistical Computing). The percentage of each terminal restriction fragment’s (T-RF’s) contribution to peak height was calculated. Hellinger distances between these relative abundance data were calculated by taking their square root. The Ward’s method of hierarchical cluster analysis was applied.

FIGURE 1. Acetate concentrations and fits of the Monod-based uncoupling inhibition model for a representative replicate without U(VI) (control) (A), with 49 µM U(VI) (Level 1) (B) or with 224 µM U(VI) (Level 2) (C). Two additional replicates for each condition showed similar progress curves of measured acetate concentration over time and model fits. (0), observed data; solid lines, model fit.

Results Effect of U(VI) on Metabolism. Replicate cultures of a sulfatereducing enrichment were exposed to increasing concentrations of U(VI). In control enrichments with no U(VI), metabolism was similar to that observed previously (15): ethanol was used concomitantly with sulfate, and acetate was produced. Since U(VI) interfered with measurements of ethanol, acetate production was used as a measure of metabolic activity, as discussed in the Materials and Methods section. Exposure to increasing concentrations of U(VI) slowed acetate production and sulfate reduction (Figures 1 and 2). No change in sulfate or acetate was observed in Level 3 and 4 enrichments over the time frame of the experiment (data 6530

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FIGURE 2. Sulfate concentrations and fits of the Monod-based uncoupling inhibition model for a representative replicate without U(VI) (control) (A), with 49 µM U(VI) (Level 1) (B) or with 224 µM U(VI) (Level 2) (C). Two additional replicates for each condition showed similar progress curves of measured sulfate concentration over time and model fits. (0), observed data; solid lines, model fit. not shown), indicating that metabolism was completely inhibited at U(VI) concentrations at or above 1.6 mM over these time scales. Though acetate production was slower in Level 1 enrichments relative to the controls (Figure 1), the difference was not statistically significant at a 95% confidence level. U(VI) was reduced in Level 1 and 2 enrichments

FIGURE 3. U(VI) concentrations and fits of the Monod-based uncoupling inhibition model for a representative replicate with 49 µM U(VI) (Level 1) (A) or with 224 µM U(VI) (Level 2) (B). Two additional replicates for each condition showed similar progress curves of measured U(VI) concentration over time and model fits. (0), observed data; solid lines, model fit.

TABLE 1. Yield Measurements at Varying Uranium Concentrations average initial U(VI) concentration (µM)

Yeff (mg VSS/mmol ethanol)

0 49 224

1.8 ( 0.05 1.2 ( 0.10 0.97 ( 0.07

concurrent with sulfate reduction and acetate production (Figure 3). Kinetic Modeling. With exposure to increasing concentrations of U(VI), effective yield, Yeff, of the sulfate-reducing culture decreased (Table 1). An uncoupling inhibition term (eq 4) was therefore incorporated into the overall Monodbased model to account for the observed inhibition by U(VI). The uncoupling inhibition model fit the data well (Figures 1-3). Kinetic parameters were fit using nonlinear least-squares analysis. The inhibition coefficient for U(VI), KU, was 100 µM. The value for the half-saturation coefficient for ethanol, Ks, was low (0.015 mM) and below the detection limit for ethanol and the reaction product acetate (0.022 mM). The maximum specific rate of substrate utilization, qmax, was 0.23 ( 0.040 mmol ethanol/mg VSS/d, and the second-order U(VI) reduction rate coefficient, kU, was 0.056 ( 0.0041 L/mg VSS/d. Effect of U(VI) on Community Structure. The compositions of cultures exposed to increasing concentrations of U(VI) were compared using terminal restriction fragment length polymorphism (T-RFLP) analysis of the 16S rRNA gene. T-RFLP allows phylogenetic-based discrimination of bacteria by the sizing of restriction fragments created by digesting PCR-amplified genes with a restriction enzyme. As described in Nyman et al. (15), a clone library for 16S rDNA for this enrichment culture was constructed, and sequences of clones were compared to reference 16S rDNA sequences in GenBank. Sequences with >97% similarity were grouped, and four distinct groupings resulted. The first contained sequences most closely related to organisms from the Desulfovibrio genus, the second to organisms from the Bacteroides genus, the third to organisms from the Synergistes genus, and the fourth to organisms from the Clostridia class. T-RFLP was performed on representative clones from the four distinct phylogenetic groups. This indicated their primary and, in

FIGURE 4. Changes in percent relative abundance of identified phylogenetic groups in T-RFLP profiles from control, Level 1, and Level 2 enrichments (enrichments exposed to no U(VI), 49 µM U(VI), and 224 µM U(VI), respectively). Bars represent the average of T-RFLP profile results from three replicate enrichments for each level and for three replicate enrichments and three replicate T-RFLP profiles from one enrichment for controls. T-RF lengths representing each phylogenetic group are given in parentheses in base pairs. 16S rDNA was amplified with HEX-labeled 27f primer and then digested with Sau96I. Error bars represent one standard deviation. some cases, secondary restriction sites and gave characteristic restriction fragment lengths for the groupings of bacteria (15). Primary sites are the first restriction site from the 5′ end of the gene, but DNA may also be cleaved at other, secondary sites when single-stranded DNA created during PCR forms secondary structures that obstruct the primary site (26). The Desulfovibrio-like sequences had T-RF lengths of 74 and 331 base pairs, Clostridia-like sequences had a primary T-RF length of 235 base pairs, Synergistes-like sequences had T-RF lengths of 314 and 346 base pairs, and Bacteroides-like sequences had T-RF lengths of 184 and 331 base pairs. Figure 4 shows the change in percent relative abundance of each identified phylogenetic group for T-RFLP profiles from samples of control, Level 1, and Level 2 enrichments. T-RFLP profiles indicated a change in community structure as U(VI) concentration increased up to 224 µM (Figure 4). As shown in Figure 5, profiles from replicate enrichments were more similar to each other than to other profiles of enrichments maintained at different U(VI) concentrations, indicating a significant difference between control, Level 1, and Level 2 enrichments. Profiles for Levels 3 and 4 were similar to those of the controls and the inoculum (data not shown), likely because there was little growth in these enrichments over the time frame of the experiment because of inhibition by high concentrations of U(VI).

Discussion Specific T-RFs correlated with exposure to increased U(VI). In particular, the relative abundance of T-RFs associated with Clostridia-like organisms increased with increasing U(VI) concentration, whereas those associated with Desulfovibriolike organisms decreased. This finding suggests Clostridialike organisms may be more resistant to U(VI) than other members of the culture. Another study, however, indicated U(VI) reduction was associated with sulfate-reducing Desulfovibrio populations in this culture and not Clostridia-like organisms. A line of enrichments grown without sulfate, whose T-RFLP profiles were comprised largely of Clostridialike T-RFs, lost the ability to reduce U(VI) (15). Though Clostridia-like organisms in this culture (mostly closely related to Sporomusa and Acetonema species) did not reduce U(VI) VOL. 41, NO. 18, 2007 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 5. Dendrogram of T-RFLP profiles for control, Level 1, and Level 2 enrichments indicating similarity of T-RFLP profiles at various U(VI) concentrations. Profiles were clustered with Ward’s method using Hellinger-transformed relative peak height. The letters A, B, and C represent replicates for the controls, Level 1, or Level 2, and the suffixes 1, 2, and 3 indicate replicate T-RFLP analyses from the control A enrichment. with the chemical conditions provided herein, in previous work U(VI) reduction by a member of the Clostridia class, a Clostridium sp., was observed (7). Because of the potential U(VI) resistance observed in this study for members of the Clostridia class, more investigation into the U(VI)-reducing organisms of Clostridia may be warranted. The decrease in yield with increasing U(VI) observed in this study could be due to several reasons: (1) increased ATP requirement due to a stress response, (2) disruption of the cell membrane and proton motive force, or (3) cell lysis. In a microarray study with Shewanella oneidensis MR-1, U(VI) exposure led to upregulation of general and membrane stress proteins (27), indicating that the presence of U(VI) likely increases energy requirements for cell maintenance. Since the effective, or net, yield incorporates substrate used both for microbial growth and maintenance requirements, the increased energy requirements due to stress could result in a decreased effective yield. The inhibition could also be due to damage to cell membranes by U(VI); such damage would interfere with the establishment of a stable proton gradient across the membrane and thus disrupts processes needed for ATP synthesis. Phenolic hydrocarbon uncouplers can nonspecifically perturb membrane functions by accumulating in the membrane (20). It has been shown that reduced uranium precipitates accumulate on the membranes and within the periplasmic space of sulfate-reducing Desulfovibrio desulfuricans (28), so such nonspecific membrane disruption appears probable in sulfate-reducing bacteria. While these inhibitory processes have yet to be demonstrated at the molecular level, the fact that the uncoupling model provided an excellent fit to the data provides impetus for further study of potential membrane-associated inhibition mechanisms. Finally, accumulation of uranium precipitates at the membrane could cause cell lysis, which would result in a decrease in the effective yield. Though previous studies have noted the inhibition of microbial growth by U(VI), this is the first quantitative assessment of inhibition. From the uncoupling inhibition model, the level at which growth rates significantly decline due to U(VI) inhibition can be determined. At a U(VI) concentration equal to KU (∼100 µM, or 24 mg/L), effective yield, and consequently the growth rate, is reduced in half by inhibition. Background U(VI) concentrations within the source zone of the FRC Area 3 site range from 84 to 210 µM (20-50 mg/L) (28); hence, the growth of bacteria would be significantly inhibited at U(VI) concentrations in this ground6532

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water. In such instances, decreasing high U(VI) concentrations before the commencement of biostimulation, for example by enhanced sorption, might prevent inhibition and facilitate more rapid growth of a U(VI)-reducing community. Under this strategy, the sorption of U(VI) would reduce soluble uranium concentration to a level that is not inhibitory to U(VI)-reducing bacteria. As the bacteria grow free of inhibition, they would reduce soluble U(VI) and additional U(VI) would desorb to maintain equilibrium. This scenario promotes the effective growth of U(VI)-reducing bacteria and provides a means for immobilizing uranium: reduction. Upon biostimulation at the FRC Area 3 site, U(VI) reduction was concurrent with substrate utilization, and, presumably, microbial growth (3). Studies to date have determined U(VI) reduction rates under nongrowth conditions (11-13, 30-33), and the applicability of these parameters to reduction during growth was unknown. In this work, we determined the second-order U(VI) reduction rate coefficient under growth conditions to be 0.056 ( 0.0041 L/mg VSS/d, and found it nearly equal to the value determined previously under nongrowth conditions, 0.055 ( 0.010 L/mg VSS/d (15). U(VI) reduction rates assessed during nongrowth conditions may, therefore, represent those under growth conditions. There are many instances when transformation rates under growth conditions might be different than under nongrowth conditions. In cases of competitive inhibition, the substrate interferes with the inhibitor and decreases transformation rates. An example is the interference of methane in TCE transformation. The fact that the U(VI) reduction rate coefficients are the same under growth and nongrowth conditions is further evidence for the applicability of the uncoupling inhibition model in this case. The values for the coefficients determined for this enrichment with ethanol as the electron donor, 0.055 and 0.056 L/mg VSS/d, are similar to initial U(VI) rates determined for Desulfovibrio vulgaris with lactate as the electron donor (0.033-0.093 L/mg VSS/d, assuming protein was 60% of VSS, 30) and to first-order coefficients for Desulfovibrio desulfuricans and a sulfate-reducing mixed culture with lactate and hydrogen as electron donors (0.062-0.219 L/mg VSS/d, assuming VSS was 90% of dry weight cells, 11). This is the first study of the inhibitory effects of U(VI) on a microbial community. As the stimulation of subsurface microbial communities is proposed as a means for immobilizing uranium in the subsurface, an understanding of how U(VI) impacts community structure, and how the resulting community in turn modulates soluble U(VI) concentration, is critical to predicting the fate of U(VI) in groundwater.

Acknowledgments This work was funded by the Office of Biological and Environmental Research (BER) Environmental Remediation Sciences Program (ERSP), U.S. Department of Energy (DOE), under grant number DOEAC05-00OR22725. We thank David Watson of the Oak Ridge Field Research Center for providing oversight of field activities and the original sediment samples for use in the column, and Dr. Wei-Min Wu for providing the samples from the sacrificed column. We also thank three anonymous reviewers.

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Received for review December 16, 2006. Revised manuscript received July 9, 2007. Accepted July 11, 2007. ES062985B

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