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Keywords:

  • Archaeon;
  • Oxic;
  • Subsurface;
  • Aquifer;
  • 16S rDNA;
  • Denaturing gradient gel electrophoresis

Abstract

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

Groundwater from an oxic, fractured basalt aquifer was examined for the presence of Archaea. DNA was extracted from cells concentrated from groundwater collected from five wells penetrating the eastern Snake River Plain Aquifer (Idaho, USA). Polymerase chain reaction (PCR) amplification of 16S rDNA was performed with Archaea-specific primers using both nested (ca. 200-bp product) and direct (ca. 600-bp product) PCR approaches. Estimates of the archaeal diversity were made by separating PCR products from all five wells by denaturing gradient gel electrophoresis (DGGE) and phylogenetic analysis of partial 16S rDNA sequences from two wells was performed following cloning procedures. Archaea were detected in all wells and the number of DGGE bands per well ranged from two to nine and varied according to PCR approach. There were 30 unique clonal 16S rDNA partial sequences (ca. 600 bp) within a total of 100 clones that were screened from two wells. Twenty-two of the 16S rDNA fragments recovered from the aquifer were related to the Crenarchaeota and Euryarchaeota kingdoms (one large clade of clones in the former and six smaller clades in the latter), with sequences ranging from 23.7 to 95.4% similar to those found in other investigations. The presence of potentially thermophilic or methanogenic Archaea in this fully oxic aquifer may be related to deep thermal sources or elevated dissolved methane concentrations. Many sequences were similar to those that represent non-thermophilic Crenarchaeota of which there are no known cultured members and therefore no putative function.


1Introduction

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

Since the domain Archaea was first described based on 16S rRNA sequences [1], archaeal sequences have been reported from open marine and coastal waters [2–4], ocean basins [5], deep sea sediments [6], estuaries [2], soils [7–9], freshwater lake sediments [10], a river [2], sulfurous [11] and freshwater lakes [12,13], and the deep subsurface [14–17]. DeLong [18] highlights these findings, suggesting that Archaea are an abundant life form on the planet. Some of these environments are not consistent with the physiological range of cultivated Archaea. It is often unknown whether Archaea or their genetic material [19] are simply present at residual levels or if they are indeed functionally significant members of these microbial communities.

We have been investigating the impacts of contaminants on bacterial communities in the upper eastern Snake River Plain Aquifer (SRPA) and questions arose as to whether our confinement of analyses to Bacteria was limiting our assessment of contaminant impact. Specifically, we were interested in the role that trichloroethylene (TCE) has on restructuring bacterial community diversity and wondered whether Archaea might survive better in the presence of this solvent, which attacks cell membranes. While it seemed unlikely that this environment (oxic, 13°C, relatively low dissolved solids, and organic carbon) was suitable for growth of anaerobic, halophilic or thermophilic organisms, there are indications that the base of the aquifer contains high temperature waters [20–22] and that methane may be evolving at depth (F.S. Colwell and J.P. McKinley, unpublished data).

Published findings of Archaea in terrestrial subsurface environments have been limited to locations that were either anoxic such as a fractured basalt aquifer [14] or porous media sediments [17] or were anoxic with elevated temperatures such as in a methanogen-dominated habitat [15] and a deep gold mine [16]. The purpose of this study was to determine if Archaea were present in an environment in which they have not previously been observed, a fully oxic, temperate, fractured rock groundwater system, and to determine the number of detectable Archaea populations using denaturing gradient gel electrophoresis (DGGE). After we detected this domain in the SRPA (using a nested polymerase chain reaction (PCR) approach) our secondary purpose was to use direct PCR amplification of an approximately 600-bp sequence and clonal analysis to relate the members of the domain to those previously described.

2Materials and methods

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

2.1Study sites and groundwater sample collection

Groundwater was collected following standard three well-volume purging from five wells penetrating the eastern SRPA (Fig. 1). In each well, the pump was placed just below the water table surface resulting in samples that were collected from 75 m to 200 m depth below land surface according to the local aquifer gradient. The SRPA is composed of multiple layers of fractured basalt hosting a calcium–sodium-bicarbonate groundwater that is slightly alkaline (ca. pH 8), oligotrophic, and generally saturated with dissolved oxygen [23] (Table 1). Wells TAN35 and TAN36 are located approximately 100 m downgradient from a defunct injection well (TSF-05) that was used until 1972 to dispose of solvents, sewage, and metal wastes into the aquifer; these wells are influenced by the resulting TCE plume (Table 1). TAN24A and MW2 are wells located on the fringe of the TCE plume, ca. 3.5 km downgradient of TSF-05, and well USGS103 is in a pristine region of the aquifer. Cells were collected from 100 l of groundwater filtered at the wellhead through Maxi Culture filter capsules (Pall Gelman Laboratory, Ann Arbor, MI, USA). These cells were subsequently maintained at −70°C until processed.

image

Figure 1. Location of the Idaho National Engineering and Environmental Laboratory in southeastern Idaho and the five wells sampled in this study.

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Table 1.  Characteristics of the five wells in the SRPA used in this study
  1. aDissolved organic carbon (mg l−1); data for USGS103 (Roy Bartholomay, personal communication), all other wells [49].

  2. bTemperature at time of sampling in degrees centigrade.

  3. cDissolved oxygen (mg l−1); data for USGS103 (Roy Bartholomay, personal communication), all other wells [49].

  4. dDepth of sampling in meters below land surface.

  5. eTCE concentration (mg l−1); data for USGS103 (Roy Bartholomay, personal communication), all other wells [49].

  6. fAcridine orange direct counts expressed as the number of total cells ml−1.

WellpHDOCaTemperaturebDOcSample depthdTCEeAODCf
USGS1038.10.315.58.020004.88×104
TAN357.11–414.01.4906901.50×105
TAN367.51–414.01.4906901.18×105
TAN24A8.31.114.38.0751.31.01×104
MW27.92.711.34–8750.43.62×104

2.2Cell recovery from capsule filters and DNA extractions

Capsule filters were gradually thawed at room temperature and 150 ml of sodium pyrophosphate (0.1%) was added to the capsule. The capsule ends were aseptically sealed and the filters were placed on a platform shaker (400 rpm, 5 min). Filter-sterilized (0.2 μm pore size), deionized water was used to reverse flush the filter and 4 l of discharge was collected and split into four aliquots, which were filtered through Durapore filters (Millipore Corporation, Bedford, MA, USA). DNA was extracted from cells collected onto Durapore filters using a bead-beating extraction protocol as previously described [24]. DNA from two Durapore filters was combined so that duplicate DNA samples were used for PCR and DGGE. Direct counts of acridine orange-stained cells [25] were conducted on unfiltered groundwater and water flushed from the capsule filters to estimate the cell extraction efficiency of the filter backflush technique.

2.3PCR

Two PCR protocols were used to amplify partial 16S rDNA sequences representative of Archaea (see Table 2 for primer sequences). A nested PCR approach using primers 46F and 1100R in the first round of PCR and the internal primers 340F with a GC clamp and 519R in the second round was used for DGGE analyses [13]. Each 100 μl reaction mixture contained the following: 0.05% IgePal (Sigma, St. Louis, MO, USA), nuclease-free water, 5 U Taq DNA polymerase, 1×PCR buffer, 1.5 mM MgCl2, (Promega Corporation, Madison, WI, USA), 0.25 μM each primer (Operon Technologies, Alameda, CA, USA), 0.25 mM each nucleotide (Boehringer-Mannheim/Roche Molecular Biochemicals, Indianapolis, IN, USA), and 1 μl of DNA template. Thermal cycler (Perkin Elmer 9700, Applied Biosystems, Foster City, CA, USA) conditions were 5 min initial denaturation at 94°C followed by 35 cycles of 1 min denaturation at 94°C, 1 min annealing at 53.5°C, and 1.83 min extension at 72°C with a final extension of 7 min at 72°C. For sequence analysis following cloning of archaeal 16S rDNA fragments, DNA from wells TAN36 and USGS103 was directly amplified using the same PCR reagents and thermal cycling parameters as above, except that the primers used were 340F with a GC clamp [13] and 915R [26]. A negative control consisting of nuclease-free water in place of DNA template was used in all PCR reactions.

Table 2.  Primers used for PCR of archaeal 16S rDNA from five wells in the SRPA
  1. af, forward primer; r and R, reverse primer.

  2. bNumbering based on Escherichia coli numbering scheme.

  3. cGC clamp sequence for PARCH340f, 5′-CGC CCG CCG CGC GCG GCG GGC GGG GCG GGG GCA CGG GGG G-3′ attached to 5′ end of the primer [13].

PrimeraTarget sitebSequence (5′ to 3′)SpecificityReference
PRA46f46–60YTA AGC CAT GCR AGTArchaea[13]
PARCH340fc340–357CCC TAC GGG GYG CAS CAGArchaea[13]
PARCH519r519–533TTA CCG CGG CKG CTGArchaea[13]
ARC915R915–934GTG CTC CCC CGC CAA TTC CTArchaea[26]
PREA1100r1100–1117YGG GTC TCG CTC GTT RCCArchaea[13]

2.4DGGE

In order to distinguish unique PCR products, 24 μl of whole community 16S rDNA PCR products (ca. 200 and 600 bp) and 10 μl of clone PCR products (ca. 600 bp) were loaded onto a polyacrylamide gel impregnated with a gradient of 20–60% or 40–60% urea/formamide [26,27]. The gels were electrophoresed using a Bio-Rad DCode Universal Mutation Detection system (Bio-Rad Laboratories, Hercules, CA, USA) at 60°C (65 V for 15 h for direct PCR products and 200 V for 4 h for nested PCR products). Gels were stained with ethidium bromide for 20–30 min, destained for 10 min, and photographed under UV illumination using either an EDAS 290 gel imaging system (Eastman Kodak Company, Rochester, NY, USA) or an Alpha Innotech MultiImage II system (Alpha Innotech, San Leandro, CA, USA).

2.5Cloning and sequencing of PCR products

The approximately 600-bp direct PCR products from wells TAN36 and USGS103 were cloned using the pGEM-T Easy Vector System (Promega Corporation). Fifty clones were screened for each sample using the DGGE migration distances to determine uniqueness. PCR products from the resulting 30 unique clones were purified using the Wizard PCR Preps DNA Purification System (Promega Corporation), and sequenced using the ABI Prism BigDye Terminator Cycle Sequencing Ready Reaction Kit and Model 377 Automated DNA Sequencer (Applied Biosystems). Initial sequence comparisons were conducted using the BLAST [28] and RDP II [29] similarity search programs and databases. The clones were named SRPA-A through SRPA-U for TAN36 and SRPA-AA through SRPA-II for USGS103 samples.

2.6Phylogenetic analysis of sequence data

The RDP II [29] Chimera Check program and secondary structure determination were used to check the partial 16S rRNA gene sequences for potential chimeric artifacts. Sequences were analyzed using BLAST in order to find the most similar available database sequences. Contigs for the small subunit rDNA were assembled and edited in SeqMan (DNAStar, Madison, WI, USA). Alignments combined our data with sequences available on GenBank using the Clustal W algorithm [30] as implemented in Megalign (DNAStar) with adjustments done by eye. Only those sequence regions that could be aligned with confidence were included in the analyses, and gaps were treated as missing nucleotides. Phylogenetic analyses of the 16S rDNA nucleotide data were performed on unambiguously aligned sequence data using the maximum likelihood, maximum parsimony, and neighbor-joining algorithms of PAUP* version 4.0b [31]. For maximum parsimony, a strict consensus tree was generated from a heuristic search with 10 random addition sequences. Heuristic searches were also done excluding invariant sites using LogDet distances to account for compositional biases [32,33]. The distance tools (neighbor joining of Kimura distances) of TREECON for Windows 1.3b [34] were also used. Three different methods of phylogenetic tree construction were used with the same dataset in order to test the robustness of the generated tree topology. Bootstrap values were calculated using 100 replicates under all models. Phylogenetic trees inferred using the two different software packages described above showed the same topologies.

3Results

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

As seen in Table 1, total cell densities were highest in wells TAN35 and TAN36 (low 105 cells ml−1) and lower for the other three wells (low to mid-range 104 cells ml−1). Backflush efficiency of cells from the filter capsules was 48.8%±19.6% (mean±1 S.D.). Archaeal 16S rDNA fragments were successfully amplified from all five wells using the nested PCR approach (Fig. 2). DGGE migration patterns of these products were similar among the five wells, with five to nine bands detected per well (Fig. 3). Direct PCR amplification of 16S rDNA from wells TAN36 and USGS103 resulted in fewer DGGE bands than in the nested approach (four versus nine and two versus five, respectively), but a larger fragment (ca. 600 bp) of the 16S rDNA was recovered using the direct PCR protocol, allowing for greater sequence analysis power. DGGE of the cloned approximately 600-bp direct PCR products from TAN36 showed a greater number of unique bands in the clones than in the original environmental samples (Fig. 4). Similar patterns were generated for well USGS103 samples (data not shown).

image

Figure 2. Nested PCR of community DNA from groundwater from five SRPA wells. Archaeal primers 46F and 1100R were used in the first PCR reaction (left-most side of each two lanes for a given sample) and archaeal primers 340F and 519R were used in the second round of PCR (right-most side of each two lanes for a given sample). A=100-bp ladder, B=negative control, C=USGS103, D=TAN24A, E=MW2, F=TAN35, G=TAN36.

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image

Figure 3. DGGE (20–60% urea/formamide gradient) of nested PCR products (ca. 200 bp) showing banding patterns of groundwater from five SRPA wells. A=USGS103, B=TAN24A, C=MW2, D=TAN35, E=TAN36.

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image

Figure 4. DGGE (40–60% urea/formamide gradient) of TAN36 community 16S rDNA PCR products (lanes I, II, and III) and cloned PCR products (all other lanes). CFB=Cytophaga-Flavobacterium-Bacteroides clones; Unk=unknown, sample not sequenced.

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Thirty of the 100 clones had unique DGGE migration patterns and were sequenced; of these, 22 possessed partial 16S rDNA sequences affiliated with Archaea and eight were related to Cytophaga-Flavobacterium-Bacteroides. The 22 clone sequences grouped into seven categories, all of which matched with archaeal sequences in the RDP II database (Table 3). Six of the seven sequence groups are affiliated with the kingdom Euryarchaeota (23.7–40.4% sequence similarity) and the other group with the Crenarchaeota (89.4–95.4% sequence similarity). Twelve of the 22 archaeal sequences were most similar to two uncultured organisms in the databases related to non-thermophilic Crenarchaeota from freshwater and estuarine sediments (Table 3). Table 3 shows that none of the seven sequence types, based on RDP II entries, were detected in both wells while four were detected only in USGS103 and three only in TAN36 groundwater. Each well contained Euryarchaeota while Crenarchaeota were found only in TAN36. Sequences of the eight non-archaeal clones shared 59.1–78.2% sequence similarity with cultured and uncultured members of the group Cytophaga-Flavobacterium-Bacteroides within the domain Bacteria.

Table 3.  RDP II sequence similarities for approximately 600-bp archaeal PCR products from DNA extracted from wells TAN36 and USGS103 and using primers 340F and 915R
  1. aIndicates sequences which were detected in TAN36 groundwater.

  2. bResults unpublished.

  3. cIndicates sequences which were detected in USGS103 groundwater.

  4. dIndicates sequences which were detected in both TAN36 and USGS103 groundwater.

  5. eResult of BLAST search shows either LMA229 or DOURO2 as possible sequence matches while RDP II shows only LMA229 (reference [54] is for DOURO2 source).

CloneDatabase matchSimilarity (%)PhylogenyEnvironment sampledReference
I, UaS15-431.0–34.0EuryarchaeotaMethanogenic rice soilUnp.b
CC, IIcpISA130.5–40.4EuryarchaeotaDeep sea hydrothermal vent[52]
C, D, SapISA1823.9–31.6EuryarchaeotaDeep sea hydrothermal vent[52]
EEdpISA1623.7EuryarchaeotaDeep sea hydrothermal vent[52]
GGcRot2029.6EuryarchaeotaAnoxic lake sediment[53]
HHcRsI1725.2EuryarchaeotaTermite gutUnp.
A, B, E, G, H, J, K, L, M, N, P, QaLMA22989.4–95.4CrenarchaeotaLake Michigan sediment[10]
 DOURO2e  Estuary sedimente[54]e

The distribution of the SRPA sequences within cultured (genus and species shown) and non-cultured members of the Crenarchaeota and Euryarchaeota is shown in Fig. 5. Many of the sequences from this study are loosely interspersed with environmental clones (SAGMA) recently obtained from deep subsurface samples from a South African gold mine [16], a high temperature, anoxic subsurface environment distinct from the SRPA.

image

Figure 5. Phylogenetic relationships of SRPA archaeal 16S rDNA sequences inferred by neighbor-joining analysis of 556 homologous DNA sequence positions. Numbers shown at nodes are bootstrap confidence values expressed as percentages of 100 bootstrap replications. The upper and lower values are from 100 bootstrap replicates under the maximum parsimony and neighbor-joining models respectively. Bootstrap values of less than 50% are not shown. The scale bar indicates the expected number of changes per nucleotide position (SAGMCG=South Africa gold mine Crenarchaeotic group).

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4Discussion

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

This study represents the first report of Euryarchaeota and Crenarchaeota occurring in a fully oxic, temperate groundwater environment. The detection of archaeal 16S rDNA sequences in the SRPA broadens the number of habitats known to contain Archaea and supports the view that these microorganisms are cosmopolitan in nature. Development of methods to increase biomass, and therefore detection, of Archaea was built into the design of this work. Concentration of the cells in groundwater samples was required to detect archaeal sequences in the SRPA. Starting with groundwater cell densities as low as 104 cells ml−1, the total number of cells used in DNA extractions was increased by four orders of magnitude (108–109 total cells) by capturing cells on filters. Concentration of cells from marine [3,4,35–37] and freshwater [13] environments has increased the level of detection of rare community members in these oligotrophic settings as well. We combined the cell concentration step with a bead-beating technique [38–42] to maximize cells lysis efficiency, presuming Archaea to be in low abundance. In the absence of bead-beating – using a chemical extraction procedure alone – no DNA was observed from 1 l of cells (from USGS103; data not shown).

In a study of the water column in a European lake, Øvreås et al. [13] used a nested PCR approach to detect Archaea. The same primer pairs used by those authors were used in this study. In all of our samples amplification was achieved, but PCR products were observed after the first round of PCR only for the two samples with the greatest biomass (Fig. 2). In DGGE analyses of the nested PCR products, five to nine bands were observed for the samples, with higher diversity observed for samples that had greater concentrations of DNA. However, five bands were shared by all samples, indicating that some Archaea were present in all aquifer locations regardless of TCE concentration, depth of sample, spatial location in the aquifer, O2 concentration and time of sampling (Fig. 3).

Direct PCR was used to produce longer fragments for sequencing and to reduce the level of PCR bias [36,43–46]. Using the number of DGGE bands as an estimate of community archaeal diversity in TAN36 and USGS103 samples, the direct PCR approach was inferior to the nested PCR, since the former method resulted in fewer DGGE bands. However, the number of unique clones was greater than unique DGGE bands from the original community PCR products in samples from both wells. This trend is likely due to the ability of the cloning procedure to detect rare sequences. Seven unique clone groups were obtained from the 22 total archaeal sequences recovered. All but one of these clone sequences shared less than 95% sequence similarity with sequences in the RDP II database indicating they represent new species to science. Eight clone sequences were 59.1–78.2% similar to uncultured members of the group Cytophaga-Flavobacterium-Bacteroides within the domain Bacteria. Why Archaea-specific primers also amplified bacterial DNA is unknown. The sequence of primer 915R, used also as a probe for fluorescent in situ hybridization [12], appears to be a reliable Archaea-specific sequence. However, primer 340F is relatively new, has not been extensively tested [13], and may be less specific than anticipated.

The functional significance of Archaea in the SRPA cannot be inferred from the 16S rDNA sequences with any confidence. There is an unusually steep geothermal gradient at the base of the SRPA [20,21,23] that is associated with the previous transit of a mantle hotspot through this region [47]. At depths greater than 1 km (depth varies with location), the SRPA is dominated by rhyolite (vs. basalt) that has relatively low permeability due in part to secondary mineralization facilitated by geothermal waters [48]. The higher temperature groundwater in the low permeability, deep aquifer moves more slowly than the high permeability upper aquifer, enhancing geochemical reactions. It is likely that these slow moving, higher temperature groundwaters become anoxic and may represent a source of thermophilic Archaea to the upper aquifer. Deep thermal water is thought to upwell into the shallow aquifer because the deep aquifer is under higher head [21] and limited convective processes. Hydrogen, often used as an electron donor by cultured Archaea, may be generated by geothermally catalyzed water–rock interactions. Elevated concentrations of dissolved methane (1–>1000 nM), frequently exceeding equilibrium values (2.5 nM) with atmospheric methane concentrations, have been detected in the aquifer suggesting the possibility that methanogenesis exists at some locations (F.S. Colwell and J.P. McKinley, unpublished data). However, none of the 16S rDNA sequences detected in this study are closely aligned to known (cultured) methanogens within the Euryarchaeota. An alternative explanation for dissolved methane concentrations in the aquifer might be the production of methane and other reduced electron donors from thermal decomposition of organic matter in sedimentary interbeds within the SRPA and in Paleozoic sediments that bound portions of the SRPA.

The Crenarchaeotic clade in Fig. 5 and Table 3 are all sequences from TAN36 and are related most closely to freshwater (clone LMA229 [10], Lake AR12 [50]) sequences. It is now recognized that the non-thermophilic Crenarchaeota are widely distributed [7,12,17,18]; however, there are as yet no cultured representatives and their functional role in the SRPA and other environments remains unknown. Phylogenetic affiliations of SRPA clones to the Euryarchaeota were more variable, with clones related to clones from a gold mine [16], freshwater lake sediments [51], anoxic crop soils [9], deep sea hydrothermal vents [52], anoxic ocean sediments [5], and termite gut microflora (unpublished data). This diversity of varied habitats from which clones similar to the clones of the oxic and relatively cold SRPA were discovered is intriguing and worth studying to determine why these patterns exist.

The effect of TCE on archaeal community members cannot be elucidated from the results reported here. TAN36 penetrates the TCE and waste plume while USGS103 does not. The appearance of Crenarchaeota in only TAN36 might be a result of their introduction via human activity or their enrichment based on the sewage introduced into the aquifer. Total cell counts are highest in the area near the injection well (e.g., TAN36) versus other wells within the plume or elsewhere in the SRPA; this may be due to bacterial enrichment on the high levels of dissolved organic carbon. However, Euryarchaeota members were found in both contaminated and pristine parts of the aquifer and their detection did not depend upon presence of a contaminant plume. Furthermore, the low similarities of SRPA clones to other clones indicate that they are unique. The effects of TCE on Archaea requires further work.

The detection of Archaea 16S rDNA sequences that are unrelated to cultured Archaea raises questions regarding the functional significance of these occurrences. While this study was limited to the detection of this domain in a new habitat, further research is planned to determine what roles these uncultured Archaea may play in environments such as the SRPA. The distinction between environmentally stable DNA and DNA from metabolically active cells as a source for these clonal sequences must be determined. It is imperative that future work addresses ways to grow previously non-cultured Archaea in the laboratory so that their physiologies and biochemistries can be understood. This will be the only way to confidently place ecological significance in DNA sequences recovered from various environments.

Acknowledgements

  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References

This work was supported by the United States Department of Energy, Office of Environmental Management with funding to the Idaho National Engineering and Environmental Laboratory (INEEL) operated by Bechtel BWXT, LLC. under contract DE-AC07-99ID13727. Derek Pouchnik (Washington State University) performed DNA sequence analyses and Mark Wilson (Humboldt State University) developed DNA extraction techniques.

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  1. Top of page
  2. Abstract
  3. 1Introduction
  4. 2Materials and methods
  5. 3Results
  6. 4Discussion
  7. Acknowledgements
  8. References
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