Mercury and Other Heavy Metals Inﬂuence Bacterial Community … · acterization was based on GS 454 FLX pyrosequencing with 235 Mb of 16S rRNA gene sequence targeting the V4 region

APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Jan. 2011, p. 302–311 Vol. 77, No. 10099-2240/11/$12.00 doi:10.1128/AEM.01715-10Copyright © 2011, American Society for Microbiology. All Rights Reserved.

Mercury and Other Heavy Metals Influence Bacterial CommunityStructure in Contaminated Tennessee Streams�†

Tatiana A. Vishnivetskaya,1 Jennifer J. Mosher,1 Anthony V. Palumbo,1 Zamin K. Yang,1Mircea Podar,1 Steven D. Brown,1 Scott C. Brooks,2 Baohua Gu,2 George R. Southworth,2

Meghan M. Drake,1 Craig C. Brandt,1 and Dwayne A. Elias1*Biosciences1 and Environmental Sciences2 Divisions, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6038

Received 19 July 2010/Accepted 20 October 2010

High concentrations of uranium, inorganic mercury [Hg(II)], and methylmercury (MeHg) have been de-tected in streams located in the Department of Energy reservation in Oak Ridge, TN. To determine thepotential effects of the surface water contamination on the microbial community composition, surface streamsediments were collected 7 times during the year, from 5 contaminated locations and 1 control stream.Fifty-nine samples were analyzed for bacterial community composition and geochemistry. Community char-acterization was based on GS 454 FLX pyrosequencing with 235 Mb of 16S rRNA gene sequence targeting theV4 region. Sorting and filtering of the raw reads resulted in 588,699 high-quality sequences with lengths of>200 bp. The bacterial community consisted of 23 phyla, including Proteobacteria (ranging from 22.9 to 58.5%per sample), Cyanobacteria (0.2 to 32.0%), Acidobacteria (1.6 to 30.6%), Verrucomicrobia (3.4 to 31.0%), andunclassified bacteria. Redundancy analysis indicated no significant differences in the bacterial communitystructure between midchannel and near-bank samples. Significant correlations were found between the bac-terial community and seasonal as well as geochemical factors. Furthermore, several community memberswithin the Proteobacteria group that includes sulfate-reducing bacteria and within the Verrucomicrobia groupappeared to be associated positively with Hg and MeHg. This study is the first to indicate an influence of MeHgon the in situ microbial community and suggests possible roles of these bacteria in the Hg/MeHg cycle.

Contamination of surface waters with mercury (Hg) anduranium (U) poses environmental and human health concerns.Uranium contamination results from milling processes for nu-clear weapons and reactor fuel. Soluble U(VI) leaches fromthe mill tailings and migrates to surface water bodies, where itcan biomagnify in food chains (76, 79). Reduced uranium[U(IV)] is of lesser concern because it can be immobilized insubsurface sediments (1, 15, 27, 54, 55). Microorganisms capa-ble of U(VI) reduction include fermenters such as Clostridiumsp. (32), Fe(III) reducers (IRB) such as Shewanella putrefaciens(58; R. Ganesh, K. G. Robinson, and G. D. Reed, presented atthe 50th Purdue Industrial Waste Conference, 1995) andGeobacter spp. (13, 20, 53), and sulfate-reducing bacteria(SRB) (36, 55).

While the primary uses of U are limited, Hg has been usedextensively in the automotive, electronic, agricultural, dental,and health care industries. The widespread occurrence of Hgin the environment is now a global concern. In nature, Hg is atoxic, rare element (25) that exists as a metal and in bothinorganic (e.g., HgS) and organic (e.g., methylmercury[MeHg]) compounds. Total mercury levels in the environmentare affected by agricultural and industrial wastes dischargedinto waterways or released into the atmosphere from coalburning or trash incineration (4, 5, 22, 39). Coal burning for

electricity generation in particular continues to release tons ofHg into the atmosphere annually (34, 82). Once deposited intolakes and streams, about 98% of the Hg becomes immobilizedin sediments.

Although inorganic mercury is neurotoxic, it does not bio-accumulate, and Hg poisoning is reversible with chelationtreatment (16, 72). Methylmercury is several times more car-cinogenic and neurotoxic than inorganic mercury (56, 69), andit does bioaccumulate (22, 75, 76, 79). Furthermore, MeHgpoisoning is irreversible (22, 75), and it is particularly danger-ous because it can cross the blood-brain barrier. The acutehealth effects include nervous system disease, brain and kidneydamage, and damage to respiratory and gastrointestinal sys-tems.

Bacterial mercury resistance has been described for manyphyla, such as Firmicutes, Actinobacteria, and Proteobacteria(24, 60). A number of these organisms can reduce Hg(II) toHg(0) and/or degrade MeHg, but Hg methylation is thus farrestricted to SRB and IRB of the Deltaproteobacteria (19, 31,44, 45). In streams, MeHg is produced under anoxic condi-tions, and the methylation potential depends on substrateavailability and the presence/activity of Hg-methylating bacte-ria (11, 38). Although research into microbial mercury meth-ylation has been ongoing for several decades, relatively fewmethylating bacteria have been identified (18, 31, 44–46). Bar-tha and coworkers were perhaps the closest to determining thegenes involved in Hg methylation, using Desulfovibrio desulfu-ricans LS (10, 17, 18), but this strain was lost.

The Y-12 plant, located in the Department of Energy res-ervation in Oak Ridge, TN (Fig. 1), was constructed in 1942 toseparate uranium-235 (235U) from the heavier 238U isotope by

* Corresponding author. Mailing address: Biosciences Division, OakRidge National Laboratory, P.O. Box 2008, MS-6036, Oak Ridge, TN37831-6036. Phone: (865) 574-0956. Fax: (865) 576-8646. E-mail:[email protected].

� Published ahead of print on 5 November 2010.† The authors have paid a fee to allow immediate free access to

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electromagnetic separation processes (12). In the years follow-ing World War II, the Y-12 plant took on a number of newactivities and missions, including separation of naturally occur-ring stable isotopes of lithium by use of liquid Hg. Between1950 and 1963, approximately 11 million kilograms of Hg wereused at the Oak Ridge Y-12 National Security Complex forlithium isotope separation processes. About 3% of the Hg waslost to the air, soil, and rock under the facilities and to EastFork Poplar Creek, which originates in the plant site. Whereasa decrease in Hg concentration in East Fork Poplar Creek wasobserved over time, methylmercury concentrations in waterand in fish have not declined in response to improvements inwater quality and exhibit trends of increasing in some cases(12).

While several studies have been conducted at U- or Hg-contaminated sites, few have examined in detail the microbialcommunity composition, and none have examined the influ-ence that these metals may have on the structure of the mi-crobial community. Identifying the relevant methylating anddemethylating populations and determining the influences ofHg/MeHg on community structure remain daunting chal-lenges. The aim of the present work was to characterize thediversity and structure of bacterial populations in heavy metal-contaminated and control streams, with particular attention tothe influences of U, Hg, and MeHg. The coupling of detailedgeochemistry analyses with 454 pyrosequencing resulted in theidentification of individual bacterial groups that may play arole in the mercury methylation process. This report providesthe first comprehensive evidence that MeHg generation by thein situ active microbial community appears to directly influence

the resultant composition of that microbial community alongthe mercury/methylmercury gradient.

MATERIALS AND METHODS

Site locations and sample collection. Stream sediment samples were obtainedfrom six locations situated in or near the Department of Energy reservation inOak Ridge, TN (Fig. 1). Locations included five contaminated streams: threelocations in East Fork Poplar Creek (EFK6.3, EFK13.8, and EFK23.4; thenumber indicates the stream distance, in kilometers, from the mouth of thestream), one location in Bear Creek (BCK12.3), and one location in White OakCreek (WCK3.9). Hinds Creek (HCK20.6) was an uncontaminated stream withsimilar general chemistry and hydrology. The locations were selected for theirproximity to sites that have been monitored for �25 years for Hg bioaccumula-tion and span a range of Hg and other contaminant concentrations. The longdata record on bioaccumulation and water and sediment chemistry deepens thepotential impact of this study when all data are considered.

Sampling occurred in October and November 2007 and in February, March,May, July, and September 2008. Samples were collected from all six locations,except in October 2007 and February and March 2008, when only EFK23.4 andHCK20.6 were sampled. Two samples were collected per location and per oc-casion: one from the stream middle and one adjacent to the stream bank (hereinreferred to as midchannel and near-bank sampling sites). Samples were collectedby skimming the upper 2 to 3 cm of sediment with a wide-mouthed container andimmediately transferring the material to a sterile wide-mouthed plastic 2-literbottle. Separate water samples were collected for analysis of dissolved metals andanions, dissolved inorganic carbon (DIC), soluble reactive phosphorus (SRP),dissolved Hg and MeHg, and total sediment Hg. Sediment and water sampleswere placed on ice until return to the analytical laboratory (�5 h), where theywere immediately centrifuged (3,700 � g, 4°C, 30 min). Gravel and pebbles wereremoved, and fine sediments were frozen (�80°C) until DNA extraction. A totalof 60 sediment samples were collected. Water samples for anion or metal anal-yses were filtered (0.45 �m) or filtered and acidified to a pH of �2 with HNO3,respectively, and were refrigerated until analysis.

Geochemical and physical parameters. The anions Cl�, NO3�, and SO4

2�

were analyzed by ion chromatography (Dionex DX 120 system, IonPac AS12A

FIG. 1. Locations of the sampling sites used in this study. The background site (HCK20.6) is located �23 km (linear distance) upstream fromsite EFK23.4. The industrial facility (Y-12 plant) is indicated schematically. (Adapted from reference 64 with permission of the publisher.)

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column, and NaHCO3/Na2CO3 eluent). Twenty-five metals were quantified viainductively coupled plasma mass spectrometry (Perkin-Elmer Elan 600 instru-ment), including Li, Be, Na, Mg, Al, K, Ca, Cr, Fe, Mn, Ni, Co, Cu, Zn, Ga, As,Se, Sr, Ag, Cd, Cs, Ba, Pb, Bi, and U. DIC was quantified by combustion catalyticoxidation at 680°C (Shimadzu TOC-V CSH instrument). SRP was quantified bythe molybdate blue method (3). Total Hg in stream water and sediments wasdetermined using a modification of EPA method 245.7 (30). Mercury was con-verted to inorganic Hg(II) by oxidation with aqueous BrCl2, reduced to Hg0 byusing SnCl2, and purged with Hg-free air to an RA 915� Zeeman effect atomicabsorption spectrometer. MeHg was analyzed by EPA draft method 1630 (29).

Parameters measured in the field included water pH, temperature, conductiv-ity (Myron L Ultrameter II 6P, calibrated daily), turbidity (Hach 2100P turbi-dimeter), and dissolved oxygen (DO) (HQ20 Hach portable LDO device).Hourly temperature and precipitation data were obtained from a nearby mete-orological station (Y-12 meteorological tower W [west]; lat 35.984664, long84.265502; altitude, 326 m above mean sea level). The average data for 5 con-secutive days before sampling events were used.

Environmental DNA extraction and pyrosequencing of bacterial 16S rRNAgenes. The total community genomic DNA (cgDNA) was extracted from 1 g (wetweight) of sediment by use of a PowerSoil DNA isolation kit (Mo Bio Labs, Inc.,Carlsbad, CA). Pyrosequencing of cgDNAs isolated from 59 samples (cgDNAfrom one sample collected at HCK20.3 in November 2007 was lost duringprocessing) was conducted using the method described at the RDP’s (RibosomalDatabase Project) Pyrosequencing Pipeline (http://pyro.cme.msu.edu/index.jsp).Briefly, the hypervariable V4 region (�290 bp) of the 16S rRNA gene wasamplified using primers identical to those in RDP’s Pyrosequencing Pipeline,containing sequences (adaptors) required for GS 454 FLX pyrosequencing, withthe forward primer containing a short tag sequence so that 40 samples could beanalyzed in one sequencing run. PCR mixtures (50 �l) consisted of forward andreverse primers (1.5 �l; 10 �M [each]), 1 �l template DNA (10 to 80 ng �l�1),and 0.6 �l (2.5 U �l�1) high-fidelity AccuPrime Pfx DNA polymerase (Invitro-gen, Carlsbad, CA). Samples were denatured (95°C, 2 min) and then amplified(30 cycles of 95°C for 15 s, 55°C for 30 s, and 68°C for 45 s), followed by a finalextension step (68°C, 3 min). The PCR amplicons were purified using AgencourtAMPure solid-phase paramagnetic bead technology (Agencourt Bioscience Cor-poration, Beverly, MA). The purity, concentration, and size of the PCR ampli-cons were estimated using DNA 1000 chips and an Agilent model 2100 bioana-lyzer (Agilent Technologies, Inc., Waldbronn, Germany). Sequencing reactionswere performed on a Life Sciences GS 454 FLX genome sequencer (RocheDiagnostics, Indianapolis, IN). Raw 454 FLX data (�235,670 Mb) were initiallyprocessed through RDP’s Pyrosequencing Pipeline (21). The raw reads weresorted by tag sequence into original samples; the key tag and 16S rRNA geneprimers were trimmed off, and low-quality sequences (N � 0; quality score of�20) were removed. The orientation of 16S rRNA gene sequences was checkedand reverse complemented if needed. A total of 5,580 to 16,706 high-qualitysequences of 200 to 220 bp were obtained per sample, and all sequences weredeposited with the NCBI.

Phylogenetic analyses. Sequences were aligned using the fast Infernal aligner,a SCFG-based, secondary structure-aware aligner (61), and clustered by thecomplete-linkage clustering (or farthest neighbor) method available at RDP’sPyrosequencing Pipeline (21). Before being submitted to the aligner, all se-quences that contained dots or dashes, non-IUPAC characters, or sequencesshorter than 150 bases were removed. The Shannon index and the Chao1 esti-mator of community diversity were calculated for each sample, at a 3% distance(http://pyro.cme.msu.edu/chao1/form.spr). Bacterial 16S rRNA gene sequenceswere assigned phylogenetically using a naïve Bayesian rRNA classifier, version2.0, with a bootstrap cutoff of 80% (http://rdp.cme.msu.edu/classifier/classifier.jsp) (80). A graphical representation of taxonomic data was obtainedvia a heat map created using Genesis 1.0 software (74).

Statistical analyses. Principal component analysis (PCA) was performed onthe geochemical data to identify sample groups (CANOCO 4.5; MicrocomputerPower). Constrained ordination techniques were used to identify patterns of 16SrRNA gene sequence variations among sites and correlations between 16S rRNAgene sequence distribution and geochemical measurements. Sequence abun-dances for each phylum were converted into weight percent values by dividingthem by the total abundance for each sample; weight percent values were naturallog transformed (ln � 1). Detrended correspondence analysis (DCA), an indirectgradient analysis based on segment length, was performed to determine themodality of the sequence data and environmental predictor variables. The anal-yses resulted in short (�2.0) segment lengths indicating linear data sets, soredundancy analysis (RDA) and partial redundancy analysis (pRDA)(CANOCO 4.5; Microcomputer Power) were performed. These constrainedordination analyses identified patterns of variation and correlated those patterns

to environmental descriptors for 36 samples for which complete geochemicalmeasurements, including Hg measurements, were available. Sequence data wereused as the response variables, and the predictor variables were the measuredenvironmental and geochemical parameters. Forward selection of the predictorvariables followed by Monte Carlo permutation tests was used to prevent arti-ficial inflation of variation due to autocorrelation in the constrained ordinationmodel (50). Stream water temperature was included as a covariable in thepRDA, as the initial RDA (not shown) indicated that temperature accounted for8 to 12% of the variation in microbial community structure. Since the samplingdates that have corresponding geochemical data occurred only from Maythrough September (regionally warmer months), we eliminated the variabilityattributed to seasonality (i.e., stream water temperature) to focus on the geo-chemical parameters.

RESULTS

Site characteristics and geochemistry. The streambed at 9 ofthe 12 sampling sites (EFK6.3 midchannel site, both EFK13.8sites, both EFK23.4 sites, both WCK3.9 sites, and bothHCK20.6 sites) was characterized by gravel and cobble depos-its with fine-grained particulates entrained between or layeredunderneath the larger stones. At the other 3 sites (EFK6.3bank site and both BCK12.3 sites), the streambed was com-prised of poorly sorted sand (�1 mm) and smaller particles.For all sites, only fine sediments were retained for processingand analysis.

The ranges of chemical and physical parameters for thesix sampling sites are summarized in Table 1. Metal resultsare reported only for constituents that exceeded the mini-mum detectable concentration. All five Hg-contaminatedsites, namely, EFK6.3, EFK13.8, EFK23.4, WCK3.9, andBCK12.3, exhibited higher dissolved and sediment-boundHg concentrations as well as higher MeHg concentrationsthan those in the Hinds Creek (HCK20.6) control site. EastFork Poplar Creek received large amounts of Hg dischargeover �13 years, beginning in the early 1950s, and thus ismore highly Hg contaminated than White Oak Creek orBear Creek. While the primary releases of Hg have de-creased substantially, diffuse secondary sources continue toadd Hg to the stream. White Oak Creek has a similar his-tory, but smaller amounts of Hg were discharged. Addition-ally, both East Fork Poplar Creek and White Oak Creekreceive process water treated with a Zn-containing corro-sion inhibitor (Table 1). Corrosion inhibitors are commonlyadded to cooling water to protect equipment and ensuregood heat exchange characteristics of the cooling system.The specific compositions of these additives are proprietary,but they have changed over time from acid chromate andnow include zinc pyrophosphates. Greener alternatives tothe zinc-based reagents are now being developed and intro-duced (http://www.prochemtech.com/Literature/Technical/Basic_Cooling_Water_Management_II.pdf). The presenceof the corrosion inhibitor did not affect the metals analysis;in other words, there were no positive or negative interfer-ences caused by its presence. A trend of decreasing inor-ganic mercury (138.28 to 40.1 ng liter�1) but increasingMeHg (0.83 to 2.54 ng liter�1) with increasing distancedownstream from the Y-12 plant (sites EFK23.4 andEFK6.3, respectively) was observed (Table 1). Additionally,a uranium and nitrate groundwater contaminant plume ispartially intercepted by Bear Creek. The effect of this dis-charge is observed in higher metal (Na, Mg, Ca, Ba, Sr, and

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U) and anion (Cl� and NO3�) concentrations, with the

conductivity being more than two times greater than that atthe other sites.

The geochemistry data were described with two PCA ordi-nation plots, since only 24 samples were analyzed for MeHgconcentration. Results for the 36 samples in which Hg wasmeasured are shown in Fig. 2A, and the variation in geochemi-cal parameters for the 24-sample subset, including Hg andMeHg concentrations, is shown in Fig. 2B. Both PCA scatterplots indicated different geochemical compositions betweenthe uncontaminated (HCK20.6) and contaminated sites. Thefirst PCA axes explain 44.5 and 41.6% of the variation ingeochemistry (Fig. 2A and B, respectively) and clearly showthat BCK12.3 differs significantly from the other four contam-inated sites by elevated concentrations of metals (Mg, Sr, Ba,and U) and anions (NO3

� and Cl�), DIC, and conductivity.The second PCA axes explain 22.4 and 25.2% of the sitevariations attributed to the concentrations of the dissolved andsedimentary Hg (Fig. 2A) and the dissolved and sedimentaryHg along with MeHg (Fig. 2B), respectively. Both uncontam-inated Hinds Creek and mildly contaminated White OakCreek were clearly separated from the more highly contami-nated streams (Fig. 2A and B).

Description of microbial community. Total cgDNA isolatedfrom the 59 samples yielded DNA concentrations ranging from0.38 to 14.5 mg g�1 sediment. The theoretical size of theprokaryotic cell population based on the total DNA recovered

ranged from 9 � 107 to 3.62 � 109 cells g�1 of wet sediment.These calculations were based upon the predicted effectivegenome size of 4.7 Mb for the soil bacterial/archaeal popula-tion (2, 65) and on the weight of 4.05 fg of a genome of this size(28). We did not include the eukaryotes in the population sizeestimate; however, inclusion of the eukaryotic componentwould reduce the cell population by 25% (65). The total bac-terial community contained 23 phyla and unclassified bacteria(Fig. 3) obtained from 235 Mb of sequencing data. Sorting andfiltering of the raw reads resulted in 588,699 high-quality se-quences with lengths of �200 bp. These sequences were orga-nized into a local BLAST database and are available forBLASTn search (http://genome.ornl.gov/�cdx/form.html). Ac-cording to the RDP Classifier, bacterial sequences constituted99.84% (587,719 sequences) of the data set, while 0.16% (927sequences) and 0.008% (51 sequences) of the sequences wereassigned to the unclassified root and to archaea, respectively.The group of unclassified bacteria, which included sequenceswith �80% confidence for relationship to any known bacterialphylum, constituted 23.55% (range, 13.16% to 39.21%) of thecommunity (138,410 sequences).

Eleven phyla present in all samples included Proteobacteria(ranging from 22.95 to 58.33% of the community in each sam-ple), followed by Acidobacteria (1.67 to 30.64%), Verrucomi-crobia (3.42 to 31.03%), Cyanobacteria (0.22 to 32.01%), Bac-teroidetes (0.03 to 14.42%), Chloroflexi (0.38 to 6.32%),Planctomycetes (0.03 to 3.92%), Gemmatimonadetes (0.05 to

TABLE 1. Chemical and physical parameters of the stream waters from each site for the May 2008, July 2008,and September 2008 sampling eventsa

ParameterRange of values for site

HCK20.6b EFK6.3 EFK13.8 EFK23.4 BCK12.3 WCK3.9

Element concn (mg/liter)Na 3.6–9.0 14.9–17.7 8.6–9.2 9.9–10.3 40.5–50.2 11.1–15.7Mg 14.1–19.0 10.2–12.3 10.9–12.3 11.9–12.9 19.5–25.5 13.1–16.6Ca 39.4–44.3 41.3–4.60 36.3–43.6 36.5–42.5 128.4–154.4 42.2–48.6Ba 64.1–99.9 35.6–70.4 45.5–65.4 40.9–56.8 167.9–230.0 47.9–64.2Sr 0.1–0.1 0.1–0.2 0.1–0.1 0.1–0.2 0.5–0.5 0.1–0.2Mn 2.0–150.9 24.3–3,770.0 15.9–184.0 24.7–81.3 1.3–15.9 6.3–43.7Fe 0.1–0.8 0.1–0.8 0.1–1.7 0.1–0.3 0.2–0.3 0.3–0.8Zn 1.4–8.1 5.6–14.2 3.0–18.5 11.2–33.0 1.5–6.5 12.7–38.5Al 72.9–1,080.7 68.5–1,320.5 118.4–3,612.4 60.9–260.0 30.3–57.3 198.8–1,076.8U 0.2–6.9 3.7–10.0 6.0–7.3 0.8–7.4 175.0–268.4 0.2–6.9

Dissolved Hg concn (ng/liter) 0.6–2.3 13.3–40.1 14.1–82.0 54.6–138.3 3.2–5.6 0.0–11.3Sediment Hg concn (ng/mg) 0.0–0.1 10.6–20.2 11.9–17.7 30.4–47.1 1.4–1.8 2.5–15.1Dissolved MeHg concn (ng/liter)c 0.0–0.1 0.5–2.5 0.2–0.4 0.4–0.8 0.0–0.1 0.0–0.9

Ion concn (mg/liter)Cl� 4.0–4.2 10.0–14.0 4.0–6.0 6.0–8.0 4.1–54.1 8.0–16.3NO3

� 0–4.2 8.0–16.6 0.0–6.4 2.0–8.3 266.0–370.7 0.0–10.2SO4

2� 16.0–18.1 34.0–46.8 32.0–36.6 34.5–38.0 38.0–50.0 34.2–98.8

DO concn (mg/liter) 7.0–9.0 8.0–8.3 8.4–9.1 9.0–10.1 8.3–9.4 8.3–9.2DIC (mg/liter) 38.9–60.4 34.3–40.8 34.1–42.2 31.7–40.3 59.0–76.0 34.4–43.1Conductivity (�S/cm) 348.0–518.0 438.0–626.0 334.0–556.0 340.0–540.0 1,170.0–1,835.0 395.0–592.0pH 7.8–7.9 7.6–8.0 7.9–8.0 8.1–8.3 7.8–7.9 8.1–8.9Temp (°C) 14.3–20.7 16.8–21.5 17.1–21.4 18.7–19.9 14.7–20.6 18.7–22.1Turbidity (NTRUd) 9.9–25.4 4.3–14.0 6.6–23.7 3.6–19.4 1.5–12.6 3.7–5.0

a Sedimentary Hg is the exception, as sediments were analyzed in that case.b Site HCK20.6 is considered uncontaminated, while sites EFK6.3, EFK13.8, EFK23.4, BCK12.3, and WCK3.9 are contaminated.c Only May and July 2008 samples were analyzed for MeHg.d Nephelometric turbidity ratio units.



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1.34%), WS3 (0.01 to 1.17%), OD1 (0.04 to 0.80%), and TM7(0.01 to 0.29%). The Firmicutes (0.03 to 5.26%), Actinobacteria(0.01 to 0.80%), and Chlamydia (0.01 to 0.25%) were found inall samples except those collected from the most Hg-contam-inated site (EFK23.4) in March, February, and September2008. The remaining 9 phyla were detected at lower abun-dances (0 to 0.41%) and in fewer samples (8 to 56 samples)(Fig. 3). There was no apparent relationship between the num-ber of groups detected per sample and the site or collectiontime. The Proteobacteria were detected in all samples and werethe most abundant. They were apportioned as Betaproteobac-teria (8.60 to 30.70%), Alphaproteobacteria (1.13 to 24.78%),Gammaproteobacteria (3.33 to 16.21%), Deltaproteobacteria(0.31 to 3.47%), and unclassified Proteobacteria (1.66 to5.52%), with members of the Epsilonproteobacteria being theleast common (0 to 0.28%), found in only 35 (59%) of 59samples (Fig. 3).

Bacterial community composition in relation to stream geo-chemistry. Since geochemistry data that included Hg wereobtained only for samples collected in May, July, and Septem-ber 2008 (Table 1), statistical analysis between bacterial com-munity structure and stream geochemistry was based on this36-sample subset. The subset contained 359,307 sequences(61.03%) of the total of 588,699 sequences (from all 59 sam-ples), with 358,689 (99.83%) of the sequences assigned to Bac-teria at the �80% confidence threshold. The unclassified rootand archaeal sequences numbered 587 (0.16%) and 31(0.009%), respectively. Diversity indices calculated at a 0.03distance level for each of 36 samples ranged from 6.0 to 7.2(Shannon index) and from 1,567.2 to 4,166.9 (Chao1 index).The diversity indices for midchannel and near-bank samplesfrom East Fork Poplar Creek varied slightly for each site andsampling event (Table 2).

Canonical axes 1 and 2 in the pRDA graph describe 17.3 and2.5% of the variation in the bacterial community structure,respectively (Fig. 4). Stream water temperature explains anadditional 8.8% of the variation (P � 0.002; F � 6.36). Thistriplot of samples, geochemical variables, and bacterial phylo-genetic taxonomic groups indicates significantly different mi-crobial communities in the sediments of Bear Creek fromthose at the other sites. The Bear Creek samples correlatedwith an increase in stream water U concentration. Uraniumand other correlated geochemical parameters differentiatedBCK12.3 from the other sites (Fig. 2A and B), and its geo-chemistry appeared to positively influence the presence ofChlamydiae and unclassified Bacteria. Many of the geochemicalparameters measured in this study were autocorrelated, soisolation of the influences from individual geochemical param-eters was not always possible. Forward selection of the inde-pendent variables followed by Monte Carlo permutations dur-ing the RDA selected the most significant (P � 0.05)environmental variable from the group of correlated variablesand discarded the remainder. For example, U is important fordescribing the influence of particular geochemical parameterson a given subset of the microbial community (Fig. 4). How-ever, since U was significantly correlated with NO3

�, Ca, Ba,Cl�, Mg, Sr, DIC, and conductivity values (r � 0.75), each ofthese parameters showed a similar statistical influence on thesubset of the community.

Similarly, pH was positively associated with the Gemmati-monadetes and Cyanobacteria, but since decreasing pH signif-icantly correlated with SO4

2� concentrations, the latter had acomparable effect. Deltaproteobacteria and Chloroflexi were as-sociated with decreasing pH values. Dissolved Hg (and theautocorrelated variable sediment Hg) displayed a significant(P � 0.002) correlation with the Verrucomicrobia. Seasonalvariation at the Hg-, U-, and NO3

�-contaminated BCK12.3stream was evident. May samples displayed higher abundancesof Proteobacteria, Actinobacteria, Planctomycetes, and TM7,whereas Gemmatimonadetes were more abundant in July.Chlamydiae and Acidobacteria levels were highest in the Sep-tember samples (Fig. 3). Conversely, bacterial communities inthe uncontaminated and Hg-contaminated May samples werecharacterized by an increase of Verrucomicrobia; however, Julysamples showed increases in Deltaproteobacteria, Chloroflexi,and unclassified Bacteria (Fig. 3 and 4).

FIG. 2. Scatter plot for PCA of geochemical data from 36 samplesover three sampling dates (A) and from a 24-sample subset of data thatincludes MeHg data (B). The percentage of total variance explained byeach axis is noted in the axis label. Individual parameters (r � 0.6)significantly associated with the variation are represented along eachaxis. Open symbols represent midchannel samples, and closed symbolsrepresent near-bank samples.



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Influence of total Hg and MeHg on microbial populations.One of the most novel findings in this study was that certainbacterial groups are positively correlated not only with Hg butalso with MeHg concentrations. pRDA canonical axes 1 and 2(Fig. 5) describe 29.4% of the variation in the bacterial com-munity from the 24-sample subset that included MeHg data.Stream water temperature explains an additional 12.3% of thevariation (P � 0.01; F � 3.27). We observed a similar clusterpattern for the set of 36 samples presented in Fig. 4. Again,Bear Creek was the most distinct from the other sites, primar-ily because of the strong positive (P � 0.01) correlations be-tween U and NO3

� concentrations and abundances of Chla-mydiae and unclassified Bacteria. Samples from East ForkPoplar Creek (EFK13.8 and EFK23.4 [nearest to the contam-ination source]) and White Oak Creek (WCK3.9; collected inMay) were significantly (P � 0.01) associated with dissolvedHg concentrations, displaying higher abundances of Deltapro-teobacteria. The Deltaproteobacteria were present in all sam-ples, although they made up a very small portion (0.75 to3.47%) of the total bacterial community. The samples furthestdownstream from the contamination source in East Fork Pop-lar Creek (EFK6.3) displayed the highest MeHg concentra-tions and the highest abundances of Verrucomicrobia and Ep-silonproteobacteria (Fig. 5). Overall, the abundances ofEpsilonproteobacteria were low, ranging from 0.00 to 0.28%,and these bacteria were detected in only 23 (64%) of 36 sam-ples. The abundances of Verrucomicrobia varied among sam-ples, from 4.70% to 31.02%, with the lowest abundances in theU- and NO3

�-contaminated BCK12.3 samples (5.21 to9.15%), and were slightly higher at the reference HCK20.6 site(11.42 to 18.96%). However, the highly Hg-contaminated areasof East Fork Poplar Creek (3 sites) and the less-contaminatedWCK3.9 site displayed greater abundances of Verrucomicrobia(4.70 to 31.02% and 11.57 to 25.60%, respectively), althoughthey did vary between sampling times.

DISCUSSION

The goals of this study were to determine the microbialcommunity structures at Hg- and U-contaminated areas and todetermine associations between these communities and theirgeochemical profiles. Furthermore, we tested if there was arelationship between particular members of the microbialcommunity and MeHg, particularly since no such relationshiphas been determined previously. In general, the results indi-cated that the composition of the streambed bacterial commu-nity was associated with season and stream water geochemis-try. Previous studies have shown seasonal effects on MeHg

FIG. 3. Heat map representation of phylogenetic data. The 16SrRNA gene sequences were assigned to phylogenetic bacterial taxo-nomic groups based on a naïve Bayesian rRNA classifier with an 80%confidence threshold, using RDP Classifier. The sample names areabbreviated as follows. The first letter or letter and number correspondto the site, as follows: H, HCK20.6; E1, EFK6.3; E2, EFK13.8; E3,EFK24.3; B, BCK12.3; and W, WCK3.9. The following letters MC orNB indicate a midchannel or near-bank sample. The last letter(s)indicates the month of collection, as follows: O, October; N, Novem-ber; F, February; MR, March; M, May; J, July; and S, September.



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production in sediments, with the highest rate occurring in thesummer, and have linked the methylation process to increasingmicrobial activity, which is usually enhanced at higher temper-atures (38, 73). Overall, higher abundances of Deltaproteobac-teria, OD1, Chloroflexi, and unclassified bacteria were observedon the warmer sampling dates, while in cooler months anincrease of Gammaproteobacteria and Cyanobacteria was evi-dent. These results are not surprising in that a semiannual shiftof �15°C could produce such differences in diversity. Theother likely contributing factor is that during the coldermonths, there is less leaf cover in the canopy of this heavily

forested area, and thus there is a larger amount of sunlight forthe photosynthetic Cyanobacteria. Whether this also explainsthe increase in the Gammaproteobacteria is unknown at thistime.

While Bear Creek also experienced temperature fluctuation,it was distinct from the other sites, not only geochemically butalso in the composition of the microbial community. Given thehigh levels of U, Hg, and NO3

� in Bear Creek, it is notsurprising that these parameters had a significant and complexinfluence on the microbial community. Based upon the micro-organisms known to reduce NO3

� and/or U(VI), it could be

FIG. 4. Triplot of RDA for bacterial phyla from the 36 streamsediments at six sites located on or near the Oak Ridge Reservation,with forward selection of predictor variables followed by Monte Carlopermutations. Solid arrows represent predictor (geochemical) vari-ables significantly associated (P � 0.05) with the variation in thebacterial community structure. Dashed arrows represent individualphyla (r � 0.6) significantly associated with the variation among sam-ples. The length of each arrow is correlated with the degree of rela-tionship between the response variables. The arrows point in the di-rection of the maximum change for the associated variable. Opensymbols represent midchannel samples, and closed symbols representnear-bank samples.

FIG. 5. Triplot of RDA for bacterial phyla of 24 stream sedimentsfrom six sites located on or near the Oak Ridge Reservation, TN, withforward selection of predictor variables followed by Monte Carlo permu-tations. Solid arrows represent predictor (geochemical) variables signifi-cantly associated (P � 0.05) with the variation in the bacterial communitystructure. Dashed arrows represent individual phyla (r � 0.6) significantlyassociated with the variation among samples. The length of each arrow iscorrelated with the degree of relationship between the response variables.The arrows point in the direction of the maximum change for the asso-ciated variable. Open symbols represent midchannel samples, and closedsymbols represent near-bank samples.

TABLE 2. Diversity indices for samples collected in May, July, and Septembera

Index Collectiondate (mo)

Diversity index

HCK20.6 WCK3.9 BCK12.3 EFK6.3 EFK13.8 EFK23.4

MC NB MC NB MC NB MC NB MC NB MC NB

Shannon May 6.29 5.98 6.41 6.25 6.39 6.63 6.37 6.28 6.44 6.40 6.21 6.16July 6.68 6.88 6.12 6.41 6.82 6.76 6.52 6.57 6.77 6.62 6.92 6.67September 6.71 6.82 6.73 6.58 6.88 6.78 6.73 6.87 7.24 6.89 6.33 6.38

Chao1 May 2,371 1,887 2,520 1,567 1,811 2,840 3,193 3,427 2,582 2,870 2,135 2,294July 3,041 3,816 2,181 3,178 3,110 3,185 3,151 3,261 2,995 2,359 3,057 2,976September 3,094 4,167 3,462 3,439 2,961 2,765 3,069 3,768 4,088 3,705 2,819 2,811

a Diversity indices were calculated at a 3% distance. MC, midchannel sample; NB, near-bank sample.



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assumed that the Deltaproteobacteria would have been moreprevalent here than at the other sites (1, 15, 27, 32, 33). How-ever, this group was consistently less abundant (Fig. 3). In-stead, Alphaproteobacteria and unclassified members of theProteobacteria correlated positively with these contaminants.The Alphaproteobacteria class includes bacteria typically foundin soils but not usually associated with U or NO3

� contamina-tion, such as species of Agrobacteria, Caulobacter, or Bradyrhi-zobium. However, it also includes members of the Sphin-gomonadaceae family which are known for their biodegradativecapabilities (37, 48), including Sphingomonas sp. BSAR-1,which bioprecipitates uranium in alkaline solutions (62). Atotal of 237 Sphingomonas-like sequences were identified inBear Creek samples, and future experiments could be targetedto isolate and test the possible contribution of this organism touranium immobilization.

Other sites contaminated with Hg but not with U or NO3�

displayed overall higher abundances of Deltaproteobacteria,Epsilonproteobacteria, and Verrucomicrobia that were positivelycorrelated with increased Hg and MeHg concentrations (Fig. 4and 5). These data suggest that these bacteria tolerate Hg/MeHg or may play a role in Hg biotransformations. However,with the exception of the Deltaproteobacteria (9, 26, 44, 47, 51,69), there is no evidence for other microorganisms havingassociations with Hg methylation. However, relatively few mi-crobial species (�50) have actually been tested for the ability tomethylate Hg, and this remains an area that should be addressedto more fully understand the diversity and abundance of bacteriathat can methylate or reduce Hg or demethylate MeHg. Theconstant decrease of Hg(II) concentrations along the downstreamstream course and the concomitant increase in MeHg concentra-tions over the �17-km distance suggest that Hg is both bioavail-able and accessible to the resident microorganisms (6–8).

Even though Epsilonproteobacteria have not previously beenassociated with Hg, the presence of these bacteria was corre-lated with Hg. Genera in this class include Wolinella, Campy-lobacter, Arcobacter, and Helicobacter, which are found in di-verse environments, such as the mammalian digestive system(http://www.nlm.nih.gov/cgi/mesh/2009/MB_cgi?mode�&term�Epsilonproteobacteria) and extreme environments such asdeep-sea hydrothermal vents (59). Other members include sul-fur-oxidizing bacteria, such as Lebetimonas acidiphila DSM16356 and Sulfurimonas denitrificans DSM1251 (71, 77). Thesequenced genome of S. denitrificans revealed genes similar tothe transposase accessory protein genes found in the mercuryresistance (mer) transposons of other bacteria (70), and our454 pyrosequencing data revealed 197 sequences related to thisorganism.

Finally, the most abundant phylum in the Hg/MeHg-con-taminated sites was the Verrucomicrobia. This little-knowngroup is widely distributed in soils, sediments, and aquatic andgastrointestinal habitats (49, 67, 81) and makes up as much as12% of soil bacterial communities (68). In comparison, theVerrucomicrobia constituted up to 31% (EFK6.3) of the com-munities explored in this study. The ecological roles of thisphylum remain largely unexplored (35), but its occurrence hasbeen correlated with increased concentrations of chemical el-ements and nutrients (37). Verrucomicrobia sequences havebeen recovered from numerous hydrocarbon-, mercury-, ura-nium-, and pesticide-contaminated environments, suggesting

that they are resistant to a number of contaminants, possessmetabolic plasticity, and may play a significant role in thedecontamination process (14, 57, 66). Culturable representa-tives display diverse metabolic characteristics and range fromaerobic heterotrophs involved in organic carbon transforma-tions (41, 67) to organisms thriving in metal-rich oligotrophicaquatic environments (78). While determining similar physiol-ogies from phylogenetic data by using shorter reads is difficult,overall, 1,116 pyrosequences in this study clustered with knownVerrucomicrobia species, using a cutoff of 0.15, with 750 se-quences clustered with Opitutaceae sp. TAV2 at a distancelevel of 0.11. Furthermore, a recently identified novel acido-philic methanotroph, Methylacidiphilum infernorum, clustersphylogenetically closely to Opitutaceae TAV2, which possessesan elaborate system of heavy metal resistance and Hg(II) re-duction genes (42). In order to determine if this clustering isthe case, future efforts will include isolation of Hg-resistantVerrucomicrobia strains and testing of their resistance to ele-vated Hg and their ability to transform Hg and MeHg. Giventhe methanotrophic properties of some phylum members (23,42, 43, 66), they may also participate in MeHg demethylationin order to use the methyl group as a carbon source via C1

metabolism. While the organomercurial lysase (merB) is widelyknown as the methylmercury demethylase, other genes may beresponsible. For example, the recently completed genome se-quencing of the Hg-methylating and MeHg-demethylating spe-cies Desulfovibrio desulfuricans ND132 by our group yielded nomer genes upon the initial annotation (unpublished data).

Mercury contamination and biotransformation to methyl-ated mercury by indigenous bacteria are of great concern glo-bally given the neurotoxic effects to both animals and humans.Efforts such as the present study are working to better under-stand the diverse bacteria capable of these biotransformationsand the influence that cocontaminants and other geochemicalparameters have on the generation of MeHg. This study pro-vides the first evidence of a positive correlation between sub-stantial and sustained levels of MeHg and specific members ofthe in situ microbial community. Given the body of literatureshowing that MeHg generation is exclusive to the Deltapro-teobacteria, it is surprising that this group made up such a smallpercentage of the microbial community for which higherMeHg values were detected. Just as surprising was the highincidence of Verrucomicrobia and the Epsilonproteobacteria.These results provide a valuable baseline study and suggestthat in situ mercury methylation may be more widespread thanpreviously believed, while also suggesting that the Deltapro-teobacteria may not be the major methylating organisms withinthe community.

ACKNOWLEDGMENTS

This research was supported by the United States Department ofEnergy under the Environmental Remediation Sciences Program(ERSP), Office of Biological and Environmental Research, Office ofScience. Oak Ridge National Laboratory is managed by University ofTennessee UT-Battelle LLC for the Department of Energy undercontract DE-AC05-00OR22725.

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Mercury and Other Heavy Metals Inﬂuence Bacterial Community … · acterization was based on GS 454 FLX pyrosequencing with 235 Mb of 16S rRNA gene sequence targeting the V4 region