Biofilm shows spatially stratified metabolic responsesto contaminant exposure

Bin Cao,1,2,3,4 Paul D. Majors,1 Bulbul Ahmed,2

Ryan S. Renslow,2 Crystal P. Silvia,1,5 Liang Shi,1

Staffan Kjelleberg,3 Jim K. Fredrickson1 andHaluk Beyenal2*1Biological Sciences Division, Pacific Northwest NationalLaboratory, Richland, WA, USA.2The Gene and Linda Voiland School of ChemicalEngineering and Bioengineering, Washington StateUniversity, Pullman, WA, USA.3Singapore Centre on Environmental Life SciencesEngineering (SCELSE), Nanyang TechnologicalUniversity, Singapore.4School of Civil and Environmental Engineering,Nanyang Technological University, Singapore.5University of Washington, Seattle, WA, USA.

Summary

Biofilms are core to a range of biological processes,including the bioremediation of environmental con-taminants. Within a biofilm population, cells withdiverse genotypes and phenotypes coexist, suggest-ing that distinct metabolic pathways may beexpressed based on the local environmental condi-tions in a biofilm. However, metabolic responses tolocal environmental conditions in a metabolicallyactive biofilm interacting with environmental contami-nants have never been quantitatively elucidated. Inthis study, we monitored the spatiotemporal metabolicresponses of metabolically active Shewanella onei-densis MR-1 biofilms to U(VI) (uranyl, UO2

2+) and Cr(VI)(chromate, CrO4

2-) using non-invasive nuclear mag-netic resonance imaging (MRI) and spectroscopy(MRS) approaches to obtain insights into adaptation inbiofilms during biofilm-contaminant interactions.While overall biomass distribution was not signifi-cantly altered upon exposure to U(VI) or Cr(VI), MRIand spatial mapping of the diffusion revealed localizedchanges in the water diffusion coefficients in the bio-films, suggesting significant contaminant-inducedchanges in structural or hydrodynamic propertiesduring bioremediation. Finally, we quantitatively dem-onstrated that the metabolic responses of biofilms to

contaminant exposure are spatially stratified, implyingthat adaptation in biofilms is custom-developed basedon local microenvironments.

Introduction

In most natural, medical and engineered settings, micro-organisms tend to grow as biofilms. A common featurethat makes biofilms distinct from well-mixed planktoniccultures is spatial heterogeneity, in regard to both chemi-cal gradients and microbial phenotypes. Gradients ofnutrients, metabolites and waste products may cause dif-ferential gene expression by cells in different regions inthe biofilm structure, resulting in stratified metabolism anda variety of physicochemical microenvironments (Coster-ton et al., 1995; Yu and Bishop, 1998; Sternberg et al.,1999; Werner et al., 2004; Teal et al., 2006).

The heterogeneous microenvironments in biofilms havebeen demonstrated to have important biological conse-quences that help diversify the community to better resistexternal stresses (Boles et al., 2004; Pamp et al., 2008),yet limited information is available on the relationshipbetween microenvironments and the differentiation ofbiofilm structure and metabolism. A comprehensive under-standing of the relationship between microenvironmentsand biofilm differentiation will inform the engineering ofbiofilm-mediated processes for better performance. To thisend, attempts have been made to quantify and spatiallyresolve physicochemical microenvironments and cellularmetabolism in biofilms, primarily through the use of micro-sensors and microscopic techniques based on in situresponsive fluorophores. Microsensors have been exten-sively used to characterize physicochemical microenviron-ments [e.g. diffusion coefficients, pH and dissolved O2

(DO)] in biofilms as well as to quantify O2 consumption andCO2 production as indicators of biofilm metabolism(Lewandowski et al., 1993; Rasmussen and Lewand-owski, 1998; Yu and Bishop, 1998; Li and Bishop, 2004;Krawczyk-Barsch et al., 2008; Kroukamp and Wolfaardt,2009; Bester et al., 2010). Another commonly usedmethod for in situ measurements of physicochemicalmicroenvironments and biofilm metabolism is chemicalmapping based on fluorescence from fluorescent proteinsexpressed by cells, dyes or magnetic optical sensor parti-cles that are introduced into biofilms (Wolfaardt et al.,1994; Nielsen et al., 2000; Werner et al., 2004; Teal et al.,2006; Saville et al., 2010; Fabricius-Dyg et al., 2012). In

Received 2 May, 2012; revised 16 July, 2012; accepted 21 July, 2012.*For correspondence. E-mail beyenal@wsu.edu; Tel. (+1) 509 3356607; Fax (+1) 509 335 4806.

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Environmental Microbiology (2012) 14(11), 2901–2910 doi:10.1111/j.1462-2920.2012.02850.x

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addition, microtoming has been coupled to microarrayanalysis to investigate the potential metabolic status of theinner and outer fractions of Geobacter sulfurreducensbiofilms on the anodes of microbial fuel cells (Franks et al.,2010). However, these methods require either physicalcontact with the biofilms during measurements or the useof genetically modified microorganisms, which makes theelucidation of real-time spatially resolved responses ofintact metabolically active biofilms a primary challenge.

A promising non-invasive approach to monitoring intactbiofilms is the use of nuclear magnetic resonance (NMR)techniques, including NMR imaging (MRI) and NMR spec-troscopy (MRS). MRI has been used to measure masstransport, including the flow hydrodynamics and diffusionproperties of metabolically active biofilms (Lewandowskiet al., 1992; 1993; Phoenix and Holmes, 2008; Renslowet al., 2010), while MRS can measure metabolite concen-trations in metabolically active biofilms (Majors et al.,2005a,b; McLean et al., 2008a,b). Very recently, Vogtet al. (2012) quantified the effects of uraninite particlesupon water NMR relaxation times and images. Critically,MRI and MRS techniques do not require contrast agents,are non-invasive, and have a relatively fast response; thus,they provide an approach to monitoring the real-timeresponses of metabolically active biofilms. In this study, weapplied spatially resolved MRI and MRS approaches andelucidated the spatiotemporal responses of metabolicallyactive biofilms to environmental perturbations usingShewanella oneidensis MR-1 as a model organism andU(VI) (uranyl, UO2

2+) and Cr(VI) (chromate, CrO42-) as

model environmental contaminants. The data reveal novelinsights into the interactions between biofilms and environ-mental contaminants as evidenced by microscale variationin the diffusion coefficients of water and spatially stratifiedresponses in the anaerobic metabolism of the cells inbiofilms to the presence of U(VI) and Cr(VI). The findingssuggest that adaptation in biofilms to contaminant expo-sure is developed based on local microenvironments.

Results and discussion

Biomass distribution and spatial mapping of waterdiffusion coefficients

We pre-grew S. oneidensis MR-1 biofilms on circularglass disks in a constant depth film fermenter (CDFF) andthen transferred the biofilms to a custom-built NMR-compatible flow cell that was housed in the NMR magnetchamber to allow for further growth and NMR measure-ments. The physical structure of each biofilm sample inthe NMR flow system was estimated using water-selectivethree-dimensional (3D) MRI techniques.

Spatially resolved biofilm structures are important formonitoring biofilm development as well as for estimatingbiomass distribution over time. Microorganisms express-

ing fluorescent proteins (e.g. GFP) in combination withconfocal laser scanning microscopy (CLSM) are an effec-tive non-invasive means for monitoring biofilm develop-ment over time (Lawrence et al., 1991; Davies et al.,1998). In the absence of microbially produced fluoro-phores, before CLSM can be applied, exogenous contrastagents, e.g. fluorescent dyes, must be introduced; thismay perturb the biology and can provide only a snapshotof biofilm structure. In contrast, biofilm imaging using 3DMRI is based on signals of spin-lattice relaxation weightedto emphasize intra- and extracellular water in close asso-ciation with the biofilm. Thus, it does not require externalcontrast agents to provide details of biomass distributionover time and it has no depth limitation for biofilmsamples. A set of representative 2D and 3D MRI imagesof the biofilms is shown in Fig. S1. Intensity, or brightness,in the images corresponds primarily to the volume fractionof water in that location. Through MRI imaging, we non-invasively obtained the biomass distribution before andafter exposure to 126 mM U(VI) (~10 h) or 200 mM Cr(VI)(~6 h). The overall biomass distribution did not changenoticeably with a total biovolume of ~3.16 mm3 (Fig. S1),suggesting that S. oneidensis monoculture biofilms canmaintain their structural integrity in the presence of thesetoxic contaminants.

To further investigate whether the U(VI) or Cr(VI) expo-sure had microscale physicochemical influences on thebiofilms, especially on the biofilm matrix, we spatiallymapped the diffusion coefficients of water in the biofilms.Exposure to either U(VI) or Cr(VI) caused a decrease inthe diffusion coefficients in the ~100 mm layer above thebiofilm–bulk liquid interface, where loosely associatedextracellular polymeric substances (EPS) can bind cationsand change the structure and hydrodynamic properties ofthe polymers in EPS, resulting in a decrease in waterdiffusion (Cao et al., 2011a). The diffusion coefficientsin the biofilm (overall average ~1.63 � 0.77 ¥ 10-9 m2 s-1)before and after U(VI) or Cr(VI) exposure were statisticallycompared using a paired Student’s t-test (Fig. 1).

Exposure to either U(VI) or Cr(VI) caused significantchanges in water diffusion in the biofilms, but the resultingpatterns were markedly different. U(VI) exposure causedthe development of discrete micro-zones with slightlydecreased or increased diffusion coefficients (Fig. 1A). Incontrast, Cr(VI) exposure resulted in horizontal channelsup to 1500 mm long with dramatically altered diffusioncoefficients and an overall increase in the diffusion coef-ficient in the base and near-base regions of the biofilm(Fig. 1B). Although the exact mechanism on how thesediffusion patterns formed upon exposure to U(VI) andCr(VI) remains unclear, at least two factors may havecontributed to the difference in diffusion patternsobserved: difference in toxicity of U(VI) and Cr(VI) toS. oneidensis MR-1 (Brown et al., 2006) as well as differ-

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ence in physicochemical properties of their reductiveproducts, i.e. U(IV) and Cr(III). Biofilms that are lessdense at the bottom (increased diffusion coefficients) aremore likely to detach (Bitton, 2005). The presence ofhigh-diffusion horizontal channels at the base of thebiofilm might be used to predict biofilm detachment uponchemical exposure.

Although MRI images showed that the overall biomassdistribution was not significantly altered, MRI-based diffu-sion measurements showed localized changes in waterdiffusion coefficients in response to U(VI) or Cr(VI) expo-sure, which may represent a change in physicochemicalmicroenvironments in the biofilm matrix. The primaryreactive sites for U(VI) and Cr(VI) reduction in MR-1 arethe c-type cytochromes at the outer membrane and in thematrix (Marshall et al., 2006; Belchik et al., 2011; Caoet al., 2011a). The reduction of U(VI) and Cr(VI) generatesU(IV) and Cr(III) species that may further interact with

polysaccharides in the biofilm matrix and cause changesin the structural configurations and hydrodynamic proper-ties of the polymeric matrix (Kazy et al., 2008; Cetin et al.,2009). This may in turn alter the diffusion properties andhence the nutrient flux to the cells in the biofilm. In ourrecent work, we demonstrated the importance of thebiofilm matrix in the bioremediation of toxic radionuclidecontaminants by quantifying the direct contribution of EPSto U(VI) bioimmobilization (Cao et al., 2011b). Here, ourresults suggest that interactions between the biofilmmatrix and U(VI) or Cr(VI) result in changes in diffusionproperties, which may influence cellular nutrient acquisi-tion and hence the metabolic activities of the biofilms. Inaddition to directly reducing and/or binding metal contami-nants, EPS also interact with contaminants (Kazy et al.,2008; Cetin et al., 2009) to alter the diffusion properties ofbiofilms, which may be another important function of EPSaffecting the fate of toxic contaminants during bioreme-

Fig. 1. Differences in the diffusion coefficientsof water in two representative S. oneidensisMR-1 biofilms (~200 mm thick) caused by (A)uranyl exposure (P < 0.05) or (B) chromateexposure (P < 0.01). Statistical comparisonwas performed using a paired Student’s t-test.The difference maps were generated bysubtracting the diffusion coefficients in thebiofilms after exposure to U(VI) or Cr(VI) fromthose measured before exposure.

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diation processes. This finding led to the question: Howwould the metabolic activities in specific regions in thebiofilms respond to contaminant-induced changes in theirphysicochemical microenvironments?

Spatiotemporal metabolic responses

To obtain temporal metabolic profiles, averaged concen-trations of metabolites in the flow cell were monitoredbefore, during and after exposure using MRS (Fig. 2). Priorto U(VI) exposure, the electron donor (lactate) and electronacceptor (fumarate) were actively consumed with a signifi-cant accumulation of metabolic by-products of theirmetabolism, acetate and succinate. Upon exposure toU(VI), lactate and fumarate consumption decreasedsharply (within 1 h). At the same time, the generation ofsuccinate and acetate nearly stopped. When the U(VI) wasremoved from the medium, metabolic activity within thebiofilm recovered nearly completely within 1 h, as indicatedby the resumed consumption of lactate and fumarate aswell as the accumulation of succinate and acetate. Simi-larly, exposing metabolically active biofilm to Cr(VI)showed significant inhibitory effects on its metabolism(within 0.5 h), which recovered over a 2 h period followingthe removal of the Cr(VI) from the medium (Fig. S2).

Based on metabolite concentrations measured inquasi-steady states (i.e. with the concentration of themetabolite remaining approximately constant), we esti-mated the empirical stoichiometry of the anaerobicmetabolism of lactate in S. oneidensis biofilms with fuma-

rate as the electron acceptor (Table 1): this is the amountof acetate and succinate produced relative to the amountof lactate and fumarate consumed with a normalization tolactate.

In the absence of U(VI) or Cr(VI), the stoichiometricratios for the anaerobic respiration of fumarate with lactatein the biofilms (succinate/fumarate = 0.90 � 0.01 andacetate/lactate = 0.47 � 0.03) were slightly lower thanthose reported for planktonic cultures (succinate/fumarate = 0.96 � 0.06 and acetate/lactate = 0.63 �

0.02) (Tang et al., 2007a), which could be due to thediversion of lactate to extensive EPS production in biofilms.During exposure to U(VI) and Cr(VI), the lactate metabo-lism of the biofilms was inhibited significantly: the acetate/lactate stoichiometric ratios decreased 76% and 93% inthe presence of U(VI) and Cr(VI) respectively. The moresevere inhibitory effects of Cr(VI) could be due to thedocumented microbial toxicity of Cr(III) produced duringCr(VI) reduction (Bencheikh-Latmani et al., 2007; Belchiket al., 2011). In a recent study an incomplete reduction of200 mM Cr(VI) was obtained in batch planktonic S. onei-densis cultures, which was also attributed to the toxiceffects of Cr(III) (Belchik et al., 2011). In contrast, thereduction products of U(VI) are mainly nano-sized precipi-tates with minimal toxicity to the cells in biofilms (Marshallet al., 2006).

Because the changes in microenvironments upon U(VI)or Cr(VI) exposure varied with location, as indicated bydiffusion coefficient mapping, we expected that theresponses of metabolic activities within the biofilms would

Fig. 2. Temporal metabolic activities of arepresentative S. oneidensis biofilm inresponse to U(VI), from MRS measurements.The biofilm was loaded into the NMR flowsystem at t = 0 and continuously fed withgrowth medium, with or without 126 mMUO2Cl2, at a flow rate of 0.5 ml h-1.

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also vary spatially. To quantify spatially resolved metabolicactivities in biofilms, concentration profiles of metabolitesin metabolically active biofilms at different biofilm depthswith a resolution of 30 mm (referred to as ‘depth-resolved’profiles) were obtained in the absence and presence ofU(VI) (Fig. 3). The results indicate that before U(VI) expo-sure, although nearly all the lactate and fumarate in thechamber and the biofilm were consumed, lower stoichio-metric ratios were observed at the bottom of the biofilm,suggesting a spatial stratification of cellular metabolicactivity in the biofilms. The subpopulations at the top ofthe biofilm appeared to have higher respiratory activitythan those at the bottom, which has also been suggestedby McLean and colleagues (2008b).

In the presence of U(VI), neither succinate nor acetatewas detected throughout the biofilm. Under anaerobicconditions, S. oneidensis MR-1 cells in planktonicculture couple lactate oxidation to acetate (~70%) withfumarate reduction, with the remaining lactate utilized inthe gluconeogenesis and C1 metabolism pathways(Tang et al., 2007b). Our depth-resolved metabolic pro-files show that, although the production of acetate in thebiofilm was not observed, lactate continued to be con-sumed throughout the biofilm, with higher consumptionrates towards the bottom of the biofilm, suggesting thatat deeper strata in the biofilm more lactate may havebeen consumed through gluconeogenesis and C1 meta-bolic pathways, although the reasons for this remainunclear. One possible reason could be the need forcarbon and energy sources for the enhanced productionof EPS in response to a U(VI) challenge that has beensuggested by previous studies (Marshall et al., 2006;Jiang et al., 2011).

We then attempted to elucidate the depth-resolvedmetabolic responses of the biofilm to Cr(VI) exposure. Abroad peak spanning the chemical shift range of 1.0–7.0 ppm was observed in the MRS spectra at variousdepths inside the biofilm; hence, the metabolites could notbe unambiguously identified or quantified. We hypoth-esized that this ‘broadening effect’ was due to a distortionof the magnetic field caused by paramagnetic solubleCr(III) species (Cr(III)aq). We predicted that if this hypoth-esis was correct, a high concentration of Cr(III)aq wouldhave accumulated in the biofilms. To test this prediction,local concentrations of Cr(III)aq within the biofilms werequantified.

Spatial mapping reveals high local concentrations ofCr(III)aq in biofilms

The local concentrations of Cr(III)aq within metabolicallyactive biofilms were measured using MRI-based T1

relaxation time mapping of 1H nuclei of water in the bio-films. Cr(VI) and Cr(OH)3(s) are diamagnetic and do notaffect the T1 relaxation time constant (Beauregard et al.,2010), while Cr(III)aq is strongly paramagnetic, resulting inconcentration-dependent T1 relaxation time constants.The inverses of T1 relaxation time constants are termedrelaxation rates (R1 = 1/T1), and a linear relationshipbetween R1 and Cr(III)aq can be established:

R R R Cr IIIt d Cr III aq aq1 1 1= + ( )[ ]( ) (1)

where R1t is the inverse of the value of T1 that is measuredusing MRI, R1d is the diamagnetic contribution to therelaxation rate, R1Cr(III)aq is the concentration factor of theCr(III)aq contribution to the relaxation rate, and [Cr(III)aq] is

Table 1. Concentrations of lactate and fumarate as well as acetate and succinate in quasi-steady states in the absence or presence of U(VI) orCr(VI).a

Mediumb

Metabolite concentration (mM) in quasi-steady states and empirical stoichiometry (in italics)

Lactate Fumarate Acetate Succinate

Biofilm 1c No U(VI) 0.82 � 0.66 0.05 � 0.15 4.69 � 0.46 13.54 � 0.611.00 lactate + 1.63 fumarate = 0.51 acetate + 1.47 succinate(succinate/fumarate = 0.90, acetate/lactate = 0.51)

With U(VI) 6.91 � 0.68 10.51 � 1.32 0.38 � 0.30 1.21 � 1.071.00 lactate + 1.45 fumarate = 0.12 acetate + 0.39 succinate(succinate/fumarate = 0.27, acetate/lactate = 0.12)

Biofilm 2c No Cr(VI) 1.27 � 0.95 1.21 � 0.82 3.83 � 0.51 12.56 � 0.881.00 lactate + 1.58 fumarate = 0.44 acetate + 1.44 succinate(succinate/fumarate = 0.91, acetate/lactate = 0.44)

With Cr(VI) 7.57 � 0.98 12.17 � 0.56 0.08 � 0.12 0.86 � 0.621.00 lactate + 1.16 fumarate = 0.03 acetate + 0.35 succinate(succinate/fumarate = 0.30, acetate/lactate = 0.03)

a. U(VI) (126 mM UO2Cl2) or Cr(VI) (200 mM K2CrO4) with a continuous medium flow at 0.5 ml h-1.b. The medium contained 10 mM lactate and 15 mM fumarate.c. The S. oneidensis MR-1 biofilms used in the MRS measurements were about 100 mm thick, and the measurements were repeated at least twicefor each set of conditions.Standard deviations were calculated from all the data points measured in quasi-steady states.

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the concentration of Cr(III)aq. For solutions of Cr(III)aq

(CrCl3(aq) in growth medium) in the NMR flow system, thevalues of R1d and R1Cr(III)aq were determined to be 0.36 s-1

and 1.10 s-1 mM-1 respectively.Figure 4 shows the surface-averaged relaxation rate in

the NMR flow cell and the depth-resolved Cr(III) concen-tration in a representative biofilm. Because Cr(VI) andCr(III)(s) species are diamagnetic and do not affect relaxa-tion, the changes in relaxation rate are attributed toCr(III)aq. Based on Eq. 1 with the predetermined param-eters R1d and R1Cr(III)aq, the concentrations of Cr(III)aq at

different depths were estimated and the resulting depth-resolved profile was determined. The local concentration ofCr(III)aq was very high (up to 2.5 mM) in the top ~100 mm ofthe biofilm, suggesting a relatively high Cr(VI) reductionactivity in this region. The presence of a localized highconcentration of Cr(III)aq in the biofilm is consistent with thehypothesized distortion of the magnetic field resulting inthe broad peaks in the depth-resolved MRSI spectra.

The non-invasive monitoring of spatiotemporalresponses of metabolically active S. oneidensis biofilmsto exposure to U(VI) and Cr(VI) has provided novel

Fig. 3. Depth-resolved metabolism measurements of a representative S. oneidensis MR-1 biofilm (~100 mm thick) in the (A) absence or (B)presence of 126 mM UO2Cl2. The depth resolution was 30 mm. The top and the bottom of the biofilm are indicated.

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insights into the interactions between biofilms and envi-ronmental contaminants. Our results suggest potentiallyimportant contaminant-induced changes in the structuralor hydrodynamic properties of the biofilm matrix during thebioimmobilization of these metals. We also quantitativelydemonstrate that the responses of cellular metabolism inbiofilms interacting with environmental contaminants arespatially stratified, and our findings imply that adaptationin biofilms to contaminant exposure is custom-developedbased on local microenvironments. The approaches usedin this study can potentially be applied to investigate thespatiotemporal responses of biofilms non-invasively andwill provide new avenues for elucidating interactionsbetween biofilms and environmental contaminants, anti-microbials or solid materials including electrodes.

Experimental procedures

Biofilm cultivation

Shewanella oneidensis MR-1 cells were grown with a modi-fied formulation of chemically defined M1 medium (Zacharaet al., 1998). The modified M1 medium (pH ~7.0) consisted of3.00 mM PIPES, 7.50 mM NaOH, 26.04 mM NH4Cl, 1.34 mMKCl, 4.35 mM NaH2PO4 and 0.68 mM CaCl2 supplementedwith trace amounts of minerals, vitamins and amino acids(Cao et al., 2011a). Sodium lactate (10 mM) and sodiumfumarate (15 mM) were added to the medium as an electrondonor and an electron acceptor respectively. Shewanellaoneidensis MR-1 biofilms were grown on 5-mm-diameter cir-cular glass coverslips using a constant depth film fermenter(CDFF) (Peters and Wimpenny, 1988; Renslow et al., 2010).Detailed protocols for CDFF operation have been describedelsewhere (Pratten, 2007). The CDFF was assembled andautoclaved, followed by the coverslips being rinsed with fresh

growth medium. The modified M1 medium was then inocu-lated with approximately 50 ml of an overnight MR-1 seedculture (OD600 ~0.50) at a flow rate of 0.3 ml min-1 and aturntable rotation rate of 2 r.p.m. Upon inoculation, cells wereallowed to attach for 3 h with both the medium flow and theturntable rotation stopped. For biofilm growth, a flow rate of0.3 ml min-1 was used to deliver growth medium and theturntable rotation rate was 3 r.p.m. The CDFF was operatedat room temperature (20–25°C). The pressure within theCDFF was kept at equilibrium with atmospheric air througha 0.22 mm filter. Under these cultivation conditions, maturebiofilms with a depth of 100–200 mm usually developed in5–7 days.

NMR-compatible flow cell for biofilm growth andmeasurements

Biofilm studies were performed using an NMR-compatibleflow cell (320 ml chamber volume) that is designed to supportone 5 mm circular coverslip with a pre-grown biofilm(Renslow et al., 2010). Growth medium was delivered at aflow rate of 0.5 ml h-1, which resulted in a laminar flow profile(McLean et al., 2008b; Renslow et al., 2010). The flow rateswere controlled using a pulseless dual syringe pump (Phar-macia P-500, Uppsala, Sweden), and the flow cell tempera-ture was maintained at 30 � 1°C by purging the magnet borewith N2 gas using a temperature-controlled gas stream deliv-ery unit (FTS Systems, Stone Ridge, NY, USA). Previousinvestigations showed that, in the absence of an alternativeelectron acceptor, no acetate (from lactate oxidation) couldbe detected when air-saturated medium was used (McLeanet al., 2008b), possibly because O2 was depleted near the topof the biofilm. Thus, the O2 concentration in this study was notcontrolled or measured. The biofilm was allowed to continuegrowing in the NMR chamber for 1–3 days before NMRspectra were collected. The exposure of biofilms to U(VI) orCr(VI) was performed by switching to growth medium sup-

Fig. 4. Relaxation rate of water 1H nuclei inthe NMR flow cell before and after exposureto 200 mM Cr(VI) for 6 h and the localizedaccumulation of Cr(III)aq in a representativeS. oneidensis MR-1 biofilm (~200 mm thick)after the exposure.

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plemented with 126 mM UO2Cl2 or 200 mM K2CrO4 respec-tively. The concentrations of U(VI) and Cr(VI) were chosenbased on our previous work (Beyenal et al., 2004; Belchiket al., 2011). All the measurements carried out in this studywere repeated at least twice using biofilm replicates from theCDFF.

NMR configuration and methods

All NMR measurements were performed at 500.44 MHz forprotons (1H) using a Bruker Avance digital NMR spectrometer(Bruker Instruments, Billerica, MA, USA) with an 11.7-T,89 mm vertical bore, actively shielded superconductingmagnet. ParaVision v5.1 imaging software (Bruker Biospin,Billerica, MA) was used to collect and process the data.Measurements included: (i) rapid multidirectional MRI toverify correct sample positioning and the absence of gasbubbles, (ii) two-dimensional Fourier transform (2DFT) MRI,(iii) three-dimensional Fourier transform (3DFT) MRI, (iv)diffusion-mapping 2DFT MRI, (v) T1-mapping 2DFT MRI, (vi)localized bulk MRS and (vii) depth-resolved MRS imaging(MRSI).

2D MRI. All 2DFT data employed field of view (FOV) dimen-sions of 10.24 mm by 5.12 mm. A total of 256 complex pointswere sampled at a rate of 100–200 Hz in the flow direction,with 256 phase-encoding (PE) steps in the biofilm-depthdirection, for an in-plane resolution of 40 mm by 20 mm. Theslice thickness was 2 mm, and Hermite 90-degree excitationpulses (10–12 kHz pulse bandwidth) and Gaussian 180-degree RF pulses (6–8 kHz RF pulse bandwidth) wereemployed.

Diffusion measurements. The NMR signal intensity ofprotons (1H) is measured to determine the diffusion coeffi-cients of water (Renslow et al., 2010). Diffusion mapping MRIprovides images of biofilms weighted with the local micro-structural characteristics of water diffusion. DtiStandard, aconventional diffusion measurement method in ParaVision,with a repetition time of 1500 ms, an echo time of 17.5 ms,and one average, was employed for diffusion mapping. Thepulse gradient width (∂) was 3 ms, and the diffusion timeinterval (D) was 10 ms. The imaging sequence was repeatedwith seven different b-factors: 0–1200 s mm-2 in 200 s mm-2

increments aligned normal to the biofilm surface, for a totalmeasurement time of 44.8 min. Two-dimensional diffusionmaps were generated by processing the individual images(Gaussian noise filtering followed by fast 2DFT processing)and then performing a semi-logarithmic analysis of theb-factor-dependent intensity value of each image pixel abovea preset noise threshold.

T1 relaxation measurements. T1 experiments employedParaVision’s saturation-recovery T1-mapping method(RAREVTR) with a variable repetition time of 3000, 300, 2000,200, 1000 and 100 ms, an echo time of 11.4 ms, and twoaverages with a rapid acquisition with refocused echoes(RARE) factor of 2. The total measurement time was 28.2 min.Two-dimensional relaxation maps were generated byprocessing the individual images (Gaussian noise filtering

followed by fast 2DFT processing) and then performing asemi-logarithmic analysis of the T1-dependent intensity valuesusing a saturation-recovery relaxation model.

3D MRI. 3DFT MRI employed ParaVision’s RAREspin-echo method with a repetition time/echo time (TR/TE)of 500/10.3 ms. The field of view (FOV) was10.24 mm ¥ 5.12 mm ¥ 5.12 mm, with 256 complex pointssampled in the flow direction, a frequency resolution of200 Hz, and 128 independently sampled PE steps in thetwo remaining directions, for an isotropic spatial resolutionof 30 mm. The total measurement time was 2.25 h. Three-dimensional images were generated using Gaussian noisefiltering and fast 3DFT processing.

Bulk MRS measurements. Bulk MRS data were collectedusing the Bruker ParaVision point-resolved spectroscopy(PRESS) method with a conventional water suppressionscheme: variable pulse power and optimized relaxationdelays (VAPOR). A total of 128 averages were collected witha TR/TE of 4000/10 ms, for a total measurement time of8.8 min. A cubic volume with a length of 3 mm per side wascentred on the coverslip, and a 90-degree Hermite RF exci-tation pulse (10 kHz pulse bandwidth) and two 180-degreeGaussian RF refocusing pulses (6 kHz pulse bandwidths)were employed. A total of 4096 complex data points wereproduced, with a spectral window of 7 kHz. The resultingwater-suppressed NMR spectrum corresponds to a bulkmetabolite spectrum of the biofilm and adjacent mediumstream.

Depth-resolved MRS measurements. Depth-resolved MRSIprofiles were collected using a gradient-echo 1D spectro-scopic imaging method with VAPOR water suppression. Sliceselection excitation was used to select a 3-mm-thick planecentred on the coverslip and normal to the flow direction.Depth profiling employed phase encoding in the directionnormal to the coverslip with a FOV of 5.12 mm. For improvedspatial localization, 189 PE steps were acquired with 2048PE iterations and distributed over a Hanning function (amaximum of 20 PE averages were collected at the centre ofk space), then Fourier transformed to 128 points, yielding aspatial (biofilm depth) resolution of 40 mm. A TR of 2000 mswas employed, for a total measurement time of 68 min. A totalof 4096 complex data points were sampled, with a spectralwindow of 7 kHz. VAPOR employed Hermite pulses with500 Hz bandwidths. A second FT in the spectroscopic dimen-sion yielded a two-dimensional data set with a spatial dimen-sion (biofilm and chamber depth) and a water-suppressed 1HNMR spectral dimension corresponding to a depth-resolvedmetabolite map of the sample chamber and biofilm.

Data analyses

Diffusion and T1 2D images were exported from ParaVision.The values at each pixel were extracted using ImageJ(Abramoff et al., 2004) and analysed using SigmaPlot (SystatSoftware, San Jose, CA). Statistical comparison of diffusionimages was performed using a paired Student’s t-test.Surface-averaged T1 relaxation rates were obtained by aver-

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aging the relaxation rates for each row of pixels. NMR spectrawere processed using Bruker TopSpin processing softwarefor exponential multiplication, Fourier transformation andfirst-order phase correction. The baseline was adjusted usinga cubic spline fitting procedure, and the individual peaks wereintegrated (TopSpin) and exported to Excel. Metabolite con-centrations were derived by calibration of the spectral signalintensities with the non-suppressed MRS measurements ofwater in the medium with an assumed concentration of 55 M.Metabolically invariant 3 mM PIPES buffer peaks in the rangeof 2.72 ppm and 3.38 ppm were used for an internal concen-tration reference.

Acknowledgements

The research was supported by the US DOE Office of Bio-logical and Environmental Research under the SubsurfaceBiogeochemistry Research (SBR) Program (Grant DE-FG92-08ER64560), the DOE-BER SBR Program’s Scientific FocusArea (SFA) at the Pacific Northwest National Laboratory(PNNL), and NIEHS/NIH (Grant 21R01ES017070-01). Aportion of the research was performed in the William R. WileyEnvironmental Molecular Sciences Laboratory, a national sci-entific user facility sponsored by the DOE’s Office of Biologi-cal and Environmental Research and located at PNNL. PNNLis operated by Battelle for the DOE under Contract DE-AC05-76RL01830.

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Supporting information

Additional Supporting Information may be found in the onlineversion of this article:

Fig. S1. Water-selective (A) 2D view facing the biofilmsurface and side views and (B) 3D MRI of S. oneidensisbiofilms in an NMR flow cell. The biofilms were grown inmodified M1 medium that was flowing against gravity (fromthe bottom towards the top of each image).Fig. S2. Temporal metabolic activities in a S. oneidensisbiofilm in the absence or presence of Cr(VI). The biofilm wasloaded into the flow cell at t = 0 and fed growth medium withor without chromate (200 mM) at a flow rate of 0.5 ml h-1.

Please note: Wiley-Blackwell are not responsible for thecontent or functionality of any supporting materials suppliedby the authors. Any queries (other than missing material)should be directed to the corresponding author for the article.

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