Design and Application of an Internal Amplification Control to Improve

Sep 6, 2013 - Naval Facilities Engineering Command, Engineering Service Center, 1100 23rd Avenue, ESC-411, Port Hueneme, California. 93043-4370 ...
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Design and Application of an Internal Amplification Control to Improve Dehalococcoides mccartyi 16S rRNA Gene Enumeration by qPCR Janet K. Hatt,† Kirsti M. Ritalahti,‡,∥ Dora M. Ogles,⊥ Carmen A. Lebrón,¶ and Frank E. Löffler*,‡,§,∥ †

School of Civil and Environmental Engineering, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, Georgia 30332, United States ‡ Department of Microbiology and §Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996, United States ⊥ Microbial Insights, 10515 Research Drive, Knoxville, Tennessee 37932, United States ¶ Naval Facilities Engineering Command, Engineering Service Center, 1100 23rd Avenue, ESC-411, Port Hueneme, California 93043-4370, United States ∥ University of Tennessee and Oak Ridge National Laboratory (UT-ORNL) Joint Institute for Biological Sciences (JIBS) and Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States S Supporting Information *

ABSTRACT: Dehalococcoides mccartyi (Dhc) strains are keystone bacteria for reductive dechlorination of chlorinated ethenes to nontoxic ethene in contaminated aquifers. Enumeration of Dhc biomarker genes using quantitative real-time PCR (qPCR) in groundwater is a key component of site assessment and bioremediation monitoring. Unfortunately, standardized qPCR procedures that recognize impaired measurements due to PCR inhibition, low template DNA concentrations, or analytical error are not available, thus limiting confidence in qPCR data. To improve contemporary approaches for enumerating Dhc in environmental samples, multiplex qPCR assays were designed to quantify the Dhc 16S rRNA gene and one of two different internal amplification controls (IACs): a modified Dhc 16S rRNA gene fragment (Dhc*) and the firefly luciferase gene luc. The Dhc* IAC exhibited competitive inhibition in qPCR with the Dhc 16S rRNA gene template when the ratio of either target was 100-fold greater than the other target. A multiplex qPCR assay with the luc IAC avoided competitive inhibition and accurately quantified Dhc abundances ranging from ∼10 to 107 16S rRNA gene copies per reaction. The addition of ∼106 E. coli luc IAC to simulated groundwater amended with the Dhc-containing consortium KB-1 yielded reproducible luc counts after DNA extraction and multiplex qPCR enumeration. The application of the luc IAC assay improved Dhc biomarker gene quantification from simulated groundwater samples and is a valuable approach for “ground truthing” qPCR data obtained in different laboratories, thus reducing ambiguity associated with qPCR enumeration and reproducibility.

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INTRODUCTION

Rational decision-making for selecting the most efficient remediation technology requires accurate prognostic site assessment tools to determine the presence and abundance of the microbes contributing desired activities. Further, rational site management decision-making following technology implementation requires diagnostic monitoring of ongoing bioremediation. For sites impacted with chlorinated ethenes, this entails the accurate enumeration of Dhc. qPCR is widely used in disease diagnostics15,16 and has also become the method of choice to assess the presence and

Tetrachloroethene (PCE) and trichloroethene (TCE) used for dry cleaning and metal degreasing, respectively, are widespread groundwater contaminants (U.S. Environmental Protection Agency Superfund Site Information; http://www.epa.gov/ superfund/sites/siteinfo.htm1). Several bacterial species respire PCE and TCE to cis-1,2-dichloroethene (cDCE) in anoxic aquifers;2−6 however, these organisms do not transform cDCE further. Following the discovery of Dehalococcoides mccartyi (Dhc) strains that reductively dechlorinate dichloroethenes and vinyl chloride (VC) to nontoxic ethene,7−9 a direct link between Dhc and ethene formation was established.7,9−11 The utility of Dhc for bioremediation was recognized, and biostimulation alone or combined with bioaugmentation emerged as promising remedial strategies.12−14 © 2013 American Chemical Society

Received: Revised: Accepted: Published: 11131

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quantification of Dhc 16S rRNA genes in a multiplex qPCR format. Application of the optimized multiplex luc assay to simulated groundwater samples demonstrated the value of the IAC approach for accounting for target loss and signal reduction due to interferences (i.e., inhibition), thus leading to more accurate and robust qPCR data.

abundance of specific phylogenetic and/or functional genes linked to contaminant transformation and degradation, including Dhc biomarker genes.17−19 Environmental samples pose particular challenges for qPCR analysis because of generally low target gene abundances,13,20 the presence of compounds (e.g., humic acids, phenolic compounds, and heavy metals) that affect nucleic acid extraction and PCR amplification, and target-gene loss during sample collection, handling and storage.21−23 Not only do erroneous qPCR data compromise the efficient use of resources and time to achieve remediation cleanup goals but data variability also lessens confidence in the application of qPCR as a site assessment and bioremediation monitoring tool. Because of differences in methodology and procedures for all aspects of qPCR analysis, the results generated in different laboratories can vary considerably and may not be directly comparable. Methodological differences include different sample holding times prior to qPCR analysis, different procedures for biomass collection and DNA extraction, different primer sets for the same target genes, and different qPCR conditions (e.g., detection chemistries, temperature cycling programs, and simplex versus multiplex assays). The incorporation of an IAC in the qPCR workflow would allow the operator to (i) recognize the causes for variability in qPCR data generated from environmental samples (i.e., groundwater) and (ii) correct qPCR data for systematic errors associated with the analytical procedures. The use of IACs is well established in the medical and food safety fields, where accurate quantification and elimination of false negative PCR results is critical.15,16,24 IACs can be applied similarly for environmental analyses by incorporation at different stages of the analysis; for example, a whole cell IAC added to an environmental sample can assess signal loss during the entire sequence of sample processing and qPCR, whereas the addition of IAC DNA directly to the qPCR assay would determine the presence of inhibitors. If assaying gene expression, a known quantity of IAC mRNA can be added to RNA samples and target transcript loss can be quantified by reverse-transcriptase qPCR. To date, few studies targeting Dhc biomarker genes or transcripts have used an internal control to assess validity of qPCR quantification,25,26 and few IAC strategies have been applied to environmental water samples. One strategy for water samples involved using a single primer set that amplified both the target gene of interest and the introduced IAC consisting of a 4 base pair (bp) substituted target gene with different probes discriminating between the two products.27 Another strategy used an exogenous IAC that is amplified simultaneously with the gene of interest each by their own primer sets with independent probes providing discrimination between the two products.28,29 qPCR using the TaqMan detection chemistry allows for the detection and quantification of multiple targets using specific probes labeled with different fluorophores (i.e., multiplex assays) and is the ideal format for developing a qPCR assay including an IAC. Although optimization of multiplex reactions can be challenging, they offer several advantages including time, cost, and labor savings as well as improved precision (due to fewer error-prone pipetting steps). In this study, two different IAC strategies were designed and evaluated. First, a single primer set to amplify both the wild type (WT) Dhc 16S rRNA gene and the modified Dhc* 16S rRNA gene IAC combined with selective TaqMan probes in a multiplex reaction was tested. A second method relied on the common eastern firefly (Photinus pyralis) luc gene as an IAC for

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MATERIALS AND METHODS Plasmids and Bacterial Strains. The DCE- and VC-toethene-dechlorinating Dhc strain BAV1 was grown as described.7,30 E. coli strains were grown in Lennox lysogeny broth (LB-Lennox) alone 31 or supplemented with 100 μg ampicillin mL−1 at 37 °C with agitation (220 rpm). E. coli strain TOP10 (Life Technologies, Inc., Grand Island, NY) was the host strain for standard plasmids (Table S1) and as the recipient of an integrated Tn7 transposon carrying the luc gene to generate strain TOP10 attTn7::luc (Supporting Information). DNA Extraction and Multiplex qPCR. Standard methods were used for DNA extraction of plasmids and genomic DNA (Supporting Information). All primers and probes used for qPCR assays in this study are listed in Table S2, and the qPCR assays performed for different experiments are listed in Table S3 (Supporting Information). For Dhc quantification, a validated primer/probe set targeting the 16S rRNA gene of all known Dhc strains19 was used with the following modifications: the probe DhcMGB was shortened by 9 nucleotides and carried a minor groove binder (MGB) modification32,33 and a nonfluorescent quencher. The IAC assay utilized the same Dhc 16S primer set with both the probe DhcMGB and the probe IACMGB specifically targeting the Dhc* sequence consisting of a BAV1 16S rRNA gene fragment altered in four nucleotide positions carried on plasmid pDhc*16S (Supporting Information). All TaqMan qPCR assays used the Applied Biosystems Universal PCR Master Mix (MM) and were run in the Applied Biosystems 7500 Fast PCR System (Applied Biosystems, Foster City, CA). To optimize multiplex qPCR conditions, primer and probe concentrations were varied from 250−500 and 125−300 nM, respectively, and annealing temperatures ranged from 58−62 °C. The optimal reaction conditions in a 20 μL total volume included 1 × MM, 300 nM of the Dhc 16S primer set, 250 nM of the DhcMGB probe, 125 nM of the IACMGB probe, and 2 μL of template DNA at the concentrations as indicated. The optimal thermal cycling amplification profile for all qPCR assays included a single cycle incubation of 2 min at 50 °C to allow for the activation of the uracil-N-glycosylase (UNG) enzyme and an incubation step for 10 min at 95 °C to inactivate UNG, denature the template DNA, and activate the AmpliTaq Gold polymerase, then 40 cycles of 15 s at 94 °C and 1 min at 60 °C. Standard curves were included with every qPCR plate using 10-fold serial dilutions of DNA over an 8 orders of magnitude range beginning at a 1 ng μL−1 concentration (∼8 log gene copies) and decreasing to 10−8 ng μL−1. CT values were determined using automatic baseline settings and an arbitrarily set cycle threshold of 0.02 for both Dhc 16S and IAC quantification. The CT value is the cycle at which the amplification curve crosses the threshold and provides a measure of the target concentration in the assay tube. All samples were analyzed in triplicate qPCR reactions. The multiplex assay utilizing the luc IAC relied on the same Dhc 16S primer set for Dhc 16S rRNA gene amplification but utilized probe DhcProbe without the MGB modification, which 11132

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Table 1. ANOVA Results Comparing the Slopes of Regression Lines of the Standard Curves for Simplex and Multiplex qPCR Targeting the Dhc 16S rRNA Gene (Dhc) and IACs (Dhc* and luc)a assay comparison Dhc* multiplex Dhc vs Dhc* simplex vs multiplex Dhc simplex vs multiplex Dhc* luciferase (luc) multiplex Dhc vs luc simplex vs multiplex Dhc simplex vs multiplex luc

slope

y int

R2

slope

y int

R2

df

F ratio

p

−3.64 −3.61 −3.45

40.62 40.66 38.78

1.000 0.997 1.000

−3.56 −3.64 −3.56

39.08 40.62 39.08

0.995 1.000 0.995

1.40 1.52 1.34

2.46 0.07 0.68

0.13 0.79 0.42

−3.44 −3.55 −3.45

38.72 39.37 38.54

0.998 0.999 1.000

−3.33 −3.44 −3.33

37.96 38.72 37.96

0.999 0.999 0.999

1.60 1.50 1.47

3.65 2.21 2.57

0.06 0.14 0.12

a

Regression lines were drawn using the means of at least three independent 10-fold serial dilution series of plasmid DNA containing either a fragment of or the entire target gene.

Dhc Strain BAV1 and E. coli TOP10 attTn7::luc Cell Mixing Experiments. For cell mixing experiments, qPCR was used to estimate the Dhc culture cell density at 4.1 × 107 ± 1.2 × 106 cells mL−1. E. coli strain TOP10 attTn7::luc was grown in 5 mL of LB medium in a 16 mm glass test tube for 15 h at 37 °C with shaking at 220 rpm to reach cell densities ranging from 1 to 5 × 109 E. coli cells mL−1. Cells were serially diluted 10fold to desired densities in 15 or 50 mL conical tubes using phosphate-buffered saline (PBS), and mixing was carried out in 2 mL microcentrifuge tubes for each experiment. Three quantities of luc IAC in E. coli cells (to produce 3.3 × 102, 3.3 × 103, or 3.3 × 104 luc gene copies per reaction) were added to ∼107−103 Dhc cells mL−1 to produce the Dhc cell numbers indicated in Table 3. The recovery of both E. coli (Table S4, Supporting Information) and Dhc was determined by comparing the multiplex qPCR results to the known input cell quantities. Duplicate cell mixtures were generated for each dilution set, and duplicate 1 mL samples of Dhc and E. coli cell suspensions, as well as 1 mL PBS samples, served as controls and were extracted with the experimental samples. Cells were collected by centrifugation (15 min, 13000g) and stored at −80 °C until DNA was extracted as described (Supporting Information). E. coli cell suspensions were also diluted, plated on LB agar and grown overnight at 37 °C to determine CFUs. To calculate the percentage recovery of the IAC signal, the total luc gene copies were quantified from each sample, divided by the total luc gene copy input, and multiplied by a factor of 100. Quantification of Dhc in Simulated Groundwater Using Both Simplex and Multiplex qPCR Assays. The utility of the IAC approach was evaluated using samples of the PCE-to-ethene-dechlorinating consortium KB-1 in simulated groundwater with cell titers ranging from 104−105 and 107−108 Dhc cells mL−1. The simulated groundwater samples were provided by Dr. E. Edwards, University of Toronto, as described,35,36 except a non-Dhc-containing mixed culture was also added to each sample to produce the same abundance of background cells (∼1 × 104 cells mL−1) in all samples. Upon receipt, 1.0−5.0 × 106 E. coli TOP10 attTn7::luc cells were added to the simulated groundwater samples, and the biomass was collected onto Sterivex-GP membrane filters. The addition of ∼1 × 106 E. coli cells/sample was expected to produce ∼1 × 104 luc counts per μL DNA in each qPCR assay. The DNA was assayed using both simplex and multiplex qPCR assays as described above. Dhc abundance estimates were corrected by dividing the Dhc 16S rRNA gene copy numbers with the percentage recovery of the IAC. To further demonstrate the utility of the IAC, identical simulated groundwater samples were shared with an

was not required in this assay because cross-reactivity with the luc IAC target did not occur. The luciferase primers LucF/LucR and probe LucProbe targeted a 67 bp long sequence of the luciferase gene.26 To optimize multiplex qPCR conditions, different primer/probe concentrations ranging from 100−500 nM for primers and 125−300 nM for probes and annealing temperatures ranging from 58−60 °C were tested. To facilitate the use of luc as an amplification control, the plasmid pBAV1− 16Sluc was constructed (Supporting Information). The use of a single double-standard plasmid for standard curve generation in multiplex reactions eliminates the need for multiple plasmids to generate standard curves, and thus improves reproducibility. To determine the range of luc IAC gene copies for optimum performance of the multiplex reaction targeting the Dhc 16S, plasmid pBAV1−16S and pCC1-luc were mixed in opposing concentrations (10-fold dilutions of Dhc 16S rRNA genes starting at 3.4 × 107−3.4 × 101 gene copies and luc starting at 2.0 × 101−2.0 × 107 gene copies) and assayed in a multiplex reaction. The optimal reaction conditions in a 20 μL total volume included 1 × MM, 500 nM of Dhc 16S and 250 nM luc primer sets, 250 nM DhcProbe, 125 nM LucProbe, and 2 μL template DNA at concentrations as indicated in the dilution series above. Thermal cycling and standard curves were performed as described above, and the data were analyzed using automatic baseline settings and an arbitrarily set threshold value of 0.05 for both Dhc 16S and luc. Comparison of Direct and Indirect Methods for Cell Enumeration. PCR-independent methods were sought to accurately determine the Dhc and E. coli cell numbers in pure cultures. Indirect methods such as qPCR and counting colonyforming units (CFU) on agar plates were compared with direct methods including acridine orange (AO) or DAPI staining of cells and epifluorescence microscopic cell counts for quantification of Dhc and E. coli (Supporting Information). A single 1.7 L BAV1 culture was the source of all the Dhc cells used for the cell mixing experiments. All Dhc strains characterized to date contain a single 16S rRNA gene and strain BAV1 contains a single bvcA reductive dehalogenase gene, indicating that enumeration of either gene provides the Dhc cell count.19 To verify the accuracy of qPCR quantification from a laboratory culture, Dhc 16S rRNA and bvcA gene data were compared with Dhc cell counts following AO staining. To verify E. coli quantification, qPCR utilizing SYBR Green detection was used to quantify the unique E. coli dxs gene,34 whereas TaqMan-based chemistry was used to enumerate the luc gene. In addition, samples from the same cultures were diluted and either plated to determine CFU mL−1 or stained with DAPI to obtain direct cell counts. 11133

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independent laboratory, which used a simplex qPCR assay for Dhc 16S rRNA gene quantification 19 combined with the luc IAC approach. Biomass was collected onto Sterivex-GP membrane filters and the DNA extracted as described.35,36 The mean values of Dhc abundance estimates were tested for significance using an analysis of variance (ANOVA) and Tukey’s honestly significant difference (HSD) posthoc test.

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RESULTS AND DISCUSSION Application of the Dhc* IAC in Multiplex qPCR Assay Format for Dhc Enumeration. Ideally, the target gene and IAC amplification occur with identical efficiencies and amplify targets over the same dynamic range. Therefore, the initial approach used a single primer set targeting the Dhc 16S rRNA gene and the Dhc* IAC with probes discriminating between the WT Dhc sequence and the modified Dhc* IAC sequence. The amplification efficiencies were not significantly different (p > 0.05) in simplex assays of WT Dhc 16S rRNA gene and the Dhc* IAC, or in multiplex assays containing equal concentrations of both targets, as determined by the slopes of the regression lines for each standard curve (Table 1 and Figure 1A). When the WT Dhc 16S rRNA gene and Dhc* IAC target DNA samples were mixed, the assay amplified the two targets linearly over 7 orders of magnitude when both target DNA concentrations were within a 10-fold difference (Figure 1A). When the two target genes were mixed in differing ratios (with 10-fold dilutions of one target starting at 8 log copies, and the other starting at >8 log copies and decreasing to 2.0 × 105 luc IAC copies per assay resulted in the loss of the Dhc 16S rRNA gene signal are unclear but may be caused by reagent depletion.40 These data established that 0.05). Direct counts using DAPI staining produced cell counts of 2.80 × 109 ± 2.04 × 108 cells mL−1 compared to 3.05 × 109 ± 6.54 × 108 and 2.57 × 109 ± 3.86 × 108 cells mL−1 determined by dxs and luc qPCR, respectively, and 2.42 × 109 ± 7.40 × 107 cells mL−1 calculated from CFU counts (Supporting Information Figure S1B). These data indicated that E. coli growth was reproducible under the defined growth conditions, and several different methods accurately enumerated E. coli cells in cell suspensions. Application of the Whole Cell E. coli IAC for Dhc Quantification. The addition of whole E. coli cells carrying a single copy of the IAC gene per cell to the sample of interest can account for losses during the entire process from biomass collection, DNA extraction and qPCR. The total luc recovery from Dhc and E. coli cell suspension mixtures ranged from 23 to 124%, and lower recoveries (23−45%) were observed with

of Dhc 16S rRNA gene copies. Using the luc gene as an IAC is promising because (i) DNA containing the luc gene for producing standard curves (e.g., pGEM-luc) and luciferase mRNA for gene activity studies are commercially available, (ii) E. coli is easy to grow and maintain, and (iii) the luc gene is not expected to occur in groundwater. Linear amplification for simplex qPCR assays targeting the Dhc 16S rRNA and luc genes using the pBAV1-16S and pCC1-luc plasmids, respectively, both spanned 6 orders of magnitude (from ∼7 to 1 log copies). No cross-reactivity was observed in simplex assays using the Dhc 16S primer set with the pCC1-luc plasmid template or the luc primer set with the pBAV1−16S plasmid template. In simplex assays, the luc target concentrations ranging from ∼2.0 × 107 to 2.0 × 105 copies per assay affected quantification of the Dhc 16S rRNA gene target at concentrations ≤34 copies per assay. The addition of 0.05), indicating the suitability of luc for use as an IAC. In multiplex assays targeting both the Dhc 16S rRNA and luc genes, the amplification efficiencies calculated from the slopes of the regression lines were 95.3% and 99.7%, respectively, and amplification of each target in the multiplex assay did not differ significantly from the simplex assays for each target (Table 1). In multiplex assays with unequal concentrations of template, the Dhc 16S rRNA and luc gene targets were amplified linearly from 3.4 × 107 to 3.4 × 105 and 2.0 × 107 to 2.0 × 105 gene copies per assay, respectively (data not shown). Because the presence of >2.0 × 105 luc copies per assay resulted in either distortion or loss of Dhc 16S rRNA signal, the addition of ≤2.0 × 105 luc copies per assay was tested for use in multiplex assays (Table 2). No major changes in the CT values of the Dhc 16S rRNA gene target over its dynamic range were observed when 2.0 × 103 or 2.0 × 104 luc gene copies were added to the qPCR assays (Table 2); however, the CT value of Dhc 16S rRNA gene amplification differed by >1.0 cycle when 2.0 × 105 luc gene copies were mixed with ∼3.4 × 102 copies of the Dhc 16S rRNA gene (CT of 31.19 ± 0.68 compared to 32.9 ± 0.43) and no fluorescence was produced when 2.0 × 105 luc gene copies were mixed with 11135

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samples that received lower quantities of E. coli IAC cells (Table S3, Supporting Information). The Dhc recovery exhibited the same general trend regardless of the amount of E. coli added. When the DNA solution obtained from the cell mixture contained >400 Dhc 16S rRNA gene copies μL−1, the Dhc cells enumerated were within 2.2-fold of the expected Dhc titer on the basis of the quantity of Dhc cells added to the sample (Table 3). This 2.2-fold disparity may simply reflect the Table 3. Dhc Recovery As Quantified in Multiplex qPCR Assays Using DNA from Cell Mixtures with Varying Numbers of the E. coli Top10 attTn7::luc Cells Dhc 16S rRNA gene copies per μL of template DNA ± SD for the numbers of E. coli added to Dhc cellsa expected Dhc16S rRNA gene copies per μL of template DNAb 4.06 × 10

5

4.06 × 104 4.06 × 103 4.06 × 102 4.06 × 101 0

3.3 × 104

3.3 × 103

3.3 × 102

5.21 × 10 ± 6.83 × 104 3.89 × 104 ± 3.08 × 103 8.68 × 103 ± 5.31 × 102 2.02 × 103 ± 2.14 × 102 2.71 × 102 ± 3.83 × 101 BDc

6.40 × 10 ± 4.48 × 104 5.84 × 104 ± 1.46 × 103 8.87 × 103 ± 6.84 × 102 2.60 × 103 ± 4.06 × 102 4.53 × 102 ± 4.12 × 101 BDc

4.01 × 105 ± 2.13 × 103 3.78 × 104 ± 2.03 × 103 4.76 × 103 ± 7.86 × 102 1.01 × 103 ± 2.47 × 102 2.07 × 102 ± 2.20 × 101 BDc

5

5

Figure 2. Comparison of Dhc abundances from simulated groundwater incorporating the E. coli luc IAC as quantified by two independent laboratories. Mean values of Dhc 16S rRNA genes quantified in simulated groundwater with (A) 104−105 Dhc mL−1 (low Dhc) and (B) 107−108 Dhc mL−1 (high Dhc) using the simplex and multiplex qPCR methods are compared to simplex qPCR results from an independent laboratory (Lab 2). Open bars represent uncorrected abundance estimates, and solid bars represent abundance estimates corrected on the basis of the percent recovery of the luc IAC. Error bars represent the standard error of the mean. Lowercase letters represent groups of significantly different estimates by one-way ANOVA and Tukey’s HSD posthoc analyses (p < 0.05, n = 5).

Values ± SD represent the mean of the Dhc quantified by multiplex assay in triplicate of DNA extracted from two independent cell mixtures of Dhc and E. coli luc IAC for the numbers indicated. b Expected gene copies were determined by qPCR prior to mixing of Dhc and E. coli cells. cBD, below the detection limit of 25 copies target gene copies per assay. a

open bars). When the abundance estimates were modified on the basis of the percentage of luc IAC recovery, no significant difference in Dhc cell enumeration was observed (Figure 2A, filled bars). Similar results were observed for the high Dhc abundance samples (Figure 2B, open bars). When the abundance estimates were adjusted on the basis of the percentage of luc IAC recovery, the simplex method did not differ from either the multiplex method or the method used by the second laboratory (Figure 2B, filled bars). The adjusted abundance estimates determined using the multiplex method did differ significantly from the method used by the independent laboratory (2.17 × 107 ± 8.19 × 106 and 1.32 × 107 ± 6.89 × 106, respectively, ANOVA p < 0.05, n = 5); however, the estimates were within 1.7-fold of one another. Dhc cell titers >106 L−1 of groundwater are typically required for efficient ethene formation, and cell abundances in the range of 103−106 Dhc L−1 indicate the potential for detoxification.35,41 Differences of only a few fold between independent abundance estimates would therefore not impact qPCR data interpretation and decision making at bioremediation sites. IAC As a Means to Assess Data Accuracy. Currently, no simple methods are available to verify that Dhc biomarker gene quantification using qPCR reflects the true Dhc abundance in environmental samples. Biomarker gene loss can occur at several stages of the overall analytical process, but estimating the magnitude of signal loss at individual steps cannot be easily assessed. The application of the luc IAC will assist the identification of the critical steps in the qPCR analytical pipeline that affect biomarker gene loss and quantification. By using luc recovery as a proxy for Dhc recovery, total losses during sampling, biomass collection, and DNA extraction can

difference in amplification efficiency for the two targets. When the DNA solution from the cell mixture contained ≤400 Dhc 16S rRNA gene copies μL−1, the Dhc cells quantified in the samples were 5 to 10-fold higher than the expected Dhc cell titers. Some background fluorescence occurred in the mixed cell assays (Table 3, bottom row), but the signals never reached the detection limit of ∼25 Dhc 16S rRNA gene copies per assay as determined by the corresponding qPCR standard curve. The background fluorescence therefore did not explain the higher than expected abundance estimates for the samples containing 0.05, n = 5) (Figure 2A, 11136

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be quantified and the methods subsequently improved to more accurately reflect the true Dhc abundance in groundwater. Dhc biomarker gene-targeted qPCR is commonly applied for site assessment and bioremediation monitoring; however, qPCR data inconsistency between replicate samples and identical samples analyzed in different laboratories diminishes confidence in the qPCR approach. Determining the exact reasons for inconsistent qPCR data is difficult due to the many analytical steps and varied laboratory Standard Operating Procedures (SOPs) (e.g., different DNA extraction protocols, different qPCR primers). The application of the whole cell IAC promises to address these issues because inherent differences in SOPs can now be quantified, and the target gene qPCR data can be corrected according to the luc gene recovery. The incorporation of the whole cell IAC approach into qPCR SOPs therefore will improve data consistency and accuracy within and between different analytical laboratories, add confidence in Dhc abundance estimates, and support site management decisions.

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ASSOCIATED CONTENT

S Supporting Information *

Additional procedures including detailed information on DNA extraction methods, the design and construction of the plasmids pDhc*-16S, pBAV1-16Sluc, pCC1-luc, the E. coli strain TOP10attTn7::luc, and the qPCR primers and probes, as well as supporting data, are presented as Supporting Information. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*F. E. Löffler. University of Tennessee, Department of Microbiology, M409 Walters Life Science Building, Knoxville, TN 37996. Phone: (865) 974-4933. Fax: (865) 974-4007. Email: frank.loeffl[email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was supported by the Strategic Environmental Research and Development Program (SERDP) (project ER1561). We thank Elizabeth Edwards of the University of Toronto for providing consortium KB-1 samples and Allan Nevins for helping to construct pDhc*-16S.

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REFERENCES

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Environmental Science & Technology

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