Introduction

Anaerobic oxidation of aromatic hydrocarbons coupled to the reduction of sulfate can be an important process for the removal of these contaminants in polluted aquatic sediments and subsurface environments [2, 4, 5, 7, 10, 18, 20, 40], but quantifying this activity within sediments has proven difficult. For example, polycyclic aromatic hydrocarbons (PAHs) are anaerobically oxidized with the reduction of sulfate in a diversity of contaminated harbor sediments [14, 15, 36], but estimating the in situ rate of anaerobic PAH degradation with [14C]-labelled PAHs is not possible because there is not a consistent relationship between the rate that the [14C]-labelled PAHs are oxidized to 14CO2 and the rate of degradation of the bulk pool of PAHs [36]. Although the disappearance of PAHs can be monitored over time in anaerobic sediment incubations [36], the long incubation times required to document losses of the PAHs, as well as other factors such as the added [14C]-PAHs do not equilibrate with the PAH pools that are sorbed onto particles [4], may result in incubation conditions that fail to adequately mimic those in situ.

The advent of quantitative techniques for estimating the levels of gene transcripts in environments and the possibility that there may be a correspondence in levels of transcripts of genes for metabolic processes and the rates of those processes has suggested that monitoring transcript levels for key genes may provide an alternative method for assaying rates of metabolism [21]. For example, in early studies employing this approach, it was found that levels of nahA transcripts were positively correlated with aerobic [14C] naphthalene mineralization rates in hydrocarbon-contaminated soil [12], and levels of mRNA for merA were highest in mercury-contaminated water with the highest rates of Hg(II) reduction [28]. More recently, levels of transcripts for gltA, which encodes for a novel, eukaryotic-like citrate synthase in Geobacteraceae, were used to track the activity of Geobacter species during in situ bioremediation of uranium-contaminated groundwater [16].

Analysis of gene transcript levels to track anaerobic degradation of PAHs coupled to sulfate reduction in contaminated harbor sediments requires the ability to effectively extract and quantify mRNA from the sediments as well as knowledge of which genes to monitor. To our knowledge, quantitative analysis of gene transcripts in contaminated harbor sediments has not previously been reported. Analysis of mRNA in such environments may be problematic because of the presence of high concentrations of complex organic matter and metals, which may interfere with extraction and/or subsequent amplification steps. Furthermore, many of the genes, which encode important steps in anaerobic degradation of PAHs, have yet to be identified.

We evaluated the possibility of effectively extracting mRNA from contaminated harbor sediments and relating gene expression to the activity of sulfate reducers in the sediments. The dsrAB genes, which are present in nonsulfate and sulfate-reducing microorganisms, code for the dissimilatory (bi)sulfite reductase in sulfate reduction and are highly conserved among the sulfate-reducing microorganisms [31, 38]. It has been noted in some pure culture studies that levels of mRNA for the dsrAB genes increase in dissimilatory sulfate-reducing microorganisms as rates of sulfate reduction increase, suggesting that rates of sulfate reduction in the environment might be estimated from dsr transcript levels [30]. However, studies on fumarate and Fe(III) respiration in Geobacter sulfurreducens have demonstrated that although there may be a direct correlation between rates of respiration and levels of transcripts for key respiratory genes for a given set of environmental conditions, the number of transcripts at a given rate of respiration can vary dramatically under different environmental conditions [5]. For example, for the same rate of fumarate reduction, the numbers of transcripts for fumarate reductase were threefold higher under electron-acceptor limiting conditions versus electron-donor limiting conditions [5]. For a gene related to Fe(III) reduction, the transcript levels differed 20-fold between electron-donor limiting and electron-acceptor limiting conditions [5].

In this paper, we report that mRNA for dsr can effectively be recovered from contaminated harbor sediments and used to identify active sulfate reducers in those sediments. Furthermore, levels of dsr transcripts in the sediments could be related to the in situ activity of the sulfate reducers.

Materials and Methods

Sediment Collection and Incubation Experiments

All studies were conducted on laboratory incubations of Boston Harbor sediments collected in April 2004 from the previously described Island End River site in Everett, MA. These sediments are highly contaminated with petroleum hydrocarbons [8, 14, 36]. Sediment to a depth of about 20 cm was collected in a water depth of 2–3 m with a grab sampler, and black sulfide-containing sediments were filled into quart canning-jars. Seawater was collected from a depth of about 1 m above the sediment. In the laboratory, sediments were transferred to 1,000 ml Pyrex bottles in an anaerobic glove bag (Coy Laboratory Products, Grass Lake, MI) under N2. Seawater was bubbled with N2/CO2 [93:7(v/v)] for 5 min to remove dissolved oxygen. All the vessels were sealed with thick rubber stoppers and stored at 4 °C for ca. 72 h before starting the incubations.

For the sediment incubations, 7 g wet sediment and 7 ml seawater were added to 62 ml serum bottles under N2 in a glove bag. The bottles were sealed with butyl rubber stoppers secured with an aluminum cap. The sediments were briefly mixed on a vortex mixer, flushed with N2/CO2 [93:7 (v/v)], and then incubated at 9, 16, or 30 °C in the dark. After 7 days (167 h) of incubation at a given temperature, some of sediments were amended with acetate (10 mM) or molybdate (20.4 mM), a specific inhibitor of sulfate reduction [32]. For each sampling time duplicate bottles were sacrificed for sulfate measurements and extraction of RNA.

Extraction of Total RNA and mRNA

The procedure for extraction of RNA was a modification of previously described protocols [11, 25]. The modifications, which consisted of adding effective coprecipitants and RNase inhibitor, were applied to aid in quantitative recovery of small amounts of nucleic acids during ethanol precipitations and to maintain the integrity of RNA. The complete procedure was performed at 2 °C or on ice. To obtain sufficient amounts of total RNA, a total of 2.6 ml of the sediment slurry from duplicate sediment incubations was distributed equally into four precooled 2.0-ml reaction tubes containing 0.6 g of glass beads (ca. 0.1-mm diameter), 0.6 ml of cold TPM buffer [50 mM Tris–HCl (pH 7.0), 1.7% (wt/vol) polyvinylpyrrolidone K25 (Sigma-Aldrich), 20 mM MgCl2], and 10 μl of yeast tRNA (5 mg/ml; Ambion). The suspension was shaken for 60 s at 4,200 rpm in a Mini-bead beater (Biospec Products; Barthlesville, OK). After 10 min of centrifugation at 13,000×g, the supernatant was transferred to a new reaction tube containing 0.6 ml water-saturated phenol and 2 μl of RNase inhibitor (Ambion). The pellet was suspended in 0.6 ml of phenol-saturated lysis buffer [50 mM Tris–HCl (pH 7.0), 50 mM EDTA, 1% (w/v)] sodium dodecyl sulfate, 6% (v/v) water-saturated phenol, followed by a second round of bead beating. After centrifugation at 13,000×g, the supernatant was transferred to the tube containing phenol and the supernatant of the first bead-beating treatment, and the pooled supernatants were extracted with phenol, phenol–chloroform–isoamylalcohol [25:24:1 (v/v/v)], and chloroform–isoamylalcohol [24:1 (v/v)]. Total nucleic acids were precipitated (from the aqueous phase) with 1/10 volume sodium acetate (3 M, pH 5.2), 4 μl linear acrylamide (5 mg/ml; Ambion) and 3 vol of cold ethanol at −80 °C for 60 min, and recovered by centrifugation at 13,000×g for 60 min. The pellets were washed with 70% ethanol. After being dried, the pellet was resuspended in 20 μl of RNase-free water and the nucleic acids from the four reaction tubes were pooled. The integrity of the 16S and 23S rRNA fragments of extracted total RNA was checked with denaturing formaldehyde agarose gel electrophoresis. The extracted RNA was further purified by a Sephadex (G-100) column filtration as described previously [26] and was treated with RNase-free DNase to remove any contaminating DNA. To further purify and concentrate the RNA, it was precipitated with 3 M sodium acetate, 5 μg glycogen, and 3 vol of ethanol at −80 °C for 30 min. RNA was recovered by centrifugation at 13,000×g for 30 min at 2 °C. The pellet was washed with 70% ethanol, and resuspended in Tris–EDTA buffer (10 mM Tris, 1 mM EDTA; pH 7.6). The mRNA was enriched and isolated by a magnetic bead hybridization method with MICROB Express purification system, and large ribosomal RNA (16S and 23 rRNA) were removed by this protocol part (Ambion, Austin, TX). To remove any residue of small RNAs (including tRNA and 5S rRNA), the enriched mRNA was further purified with the glass fiber-based filtration method with the MEGAclear purification system (Ambion).

DNA contamination was checked with agarose gel electrophoresis following reverse transcription-polymerase chain reaction (RT-PCR) by performing control experiments in which no reverse transcriptase was added to extracted RNA before the PCR step. RNA concentration was determined by absorption at 260 nm with a Biophotometer (Eppendorf, Hamburg, Germany). Purified RNA was stored at −80 °C.

PCR Primers

The primers used in this study were as follows: the forward primers were DSR1F (AC[C/G]CACTGGAAGCACG) and DSR2F (CTGGAAGGA[C/T]GACATCAA) [38], and the reverse primers were DSR4R (GTGTAGCAGTTACCGCA) [38] and DSRQ2R (GTTGA[C/T]ACGCATGGT[A/G]TG) (this study). Primers were evaluated for quantitative PCR as described earlier [5]. The resulting conditions were experimentally checked using genomic DNA isolated from Desulfovibrio desulfuricans subsp. desulfuricans DSM 642 cultures. All primers were synthesized by Sigma Genosys Oligofactory (The Woodlands, TX). To determine whether the primers were suitable, gene-specific qualitative PCR was performed before quantitative PCR. PCR products were amplified from cDNA generated by RT with the appropriate primers using the following condition: 95 °C (5 min); 40 cycles of 95 °C (40 s); 52 °C (1 min); 72 °C (1 min) followed by a final extension at 72 °C for 10 min. The PCR products were checked using ethidium bromide stained agarose gel, and the specificity of PCR products was verified by sequence analysis of clone libraries. Only the primer combinations, which amplified well, were further used for the real-time PCR quantification and clone libraries.

Reverse Transcription-Polymerase Chain Reaction

cDNA of the mRNA for DSR genes, was generated with dsrA-specific or dsrAB-specific reverse primers with 0.5 μg of mRNA serving as the template. For RT reactions SuperScript™ III RNase H− Reverse Transcriptase (200 U; Invitrogen Life Technologies, Rockville, MD) was used according to the manufacturer’s instructions. Gene−specific reverse primers (1 μM; Sigma Genosys, The Woodlands, TX) were used for cDNA synthesis. The cDNA synthesis conditions were as follows: incubation at 52 °C for 60 min, and enzyme inactivation at 70 °C for 15 min. To remove RNA complementary to the cDNA, E. coli RNase H (2 U) was added and the reaction was incubated at 37 °C for 20 min, followed by rapid cooling to 4 °C. The cDNA samples were stored at −20 °C before PCR analysis.

DNA Extraction and PCR Amplification of 16S rRNA Gene

Total DNA was isolated from same sediment samples, which were used for total RNA extraction and taken after 7 days incubation at 9 °C, using FastDNA SPIN Kit for Soil (QBiogene, Irvine, CA) with a modification as follows: the sediment suspension was shaken for 30 S at 2,500 rpm in a Mini-bead beater (Biospec Products) instead of FastPrep Instrument.

The 16S rRNA genes were amplified from total DNA extracted from sediment with universal bacterial primers 338F [35] and 926R [17]. PCR was performed with the following conditions: an initial denaturation step at 94 °C for 2 min, followed by 30 cycles of 1 min at 94 °C, 1 min at 51 °C, and 2 min at 72 °C, and a final extension step of 10 min at 72 °C.

Cloning, Sequencing and Phylogenetic Analysis

Two clone libraries were generated with RT-PCR amplicons obtained from mRNA, which was isolated from sediment samples taken after 7 days incubation at 9 °C. One was generated with the dsrA-specific RT-PCR amplicons (123 bp length amplified with primers DSR1F and DSRQ2R) to confirm the specificity of the real-time PCR products. Another one was generated with the dsrAB-specific RT-PCR amplicons of long fragment (ca. 1.4 kbp length amplified with primers DSR2F and DSR4R) for the phylogenetic analysis. Additionally, another clone library was generated with the 16S rRNA gene amplicon obtained from environmental DNA, which was isolated from same sediment samples mentioned above. Amplicons were cloned into the pCR2.1-TOPO vector with the TOPO TA cloning kit (Invitrogen). A total of 62 clones from each dsr gene clone library and 63 clones from 16S rRNA gene clone library were randomly selected, and plasmid inserts were sequenced with M13 forward and/or reverse primers using an ABI 3730xl DNA Analyzer. Sequences were compared to ones in GenBank with the BLAST program [1]. The phylogenetic analysis of sequence data was performed using the ARB software package (version 2.5b (O. Strunk and W. Ludwig, Technische Universität München, Munich, Germany, http://www.biol.chemie.tu-muenchen.de/pub/ARB/).

The ARB_EDIT tool was used for automatic sequence alignment, and the sequences were checked and corrected manually. To ensure the correct phylogenetic placement of the obtained 16S rRNA clone sequences (∼589 nucleotides), new sequences were added to the ARB database consisting in 14,228 complete or partial (>400 nucleotides) bacterial 16S rRNA gene sequences from public databases. Phylogenetic placement was performed in comparison with sequences of Bacteria. Nucleotide base frequency filters were generated to include only nucleotide positions into the phylogenetic analysis with more than 50% invariance to avoid possible treeing artifacts. Tree topology was constructed using maximum-likelihood algorithm and verified by neighbor-joining analysis. The obtained partial environmental DSR clone sequences (∼1,168 nucleotides) were added to the database of DSR sequence in the ARB that was constructed in this study and consisted in 924 complete (>2,300 nucleotides) or partial (>360 nucleotides) DSR gene sequences from public databases. Phylogenetic placement of DSR clone sequences was performed in comparison with sequences of Deltaproteobacteria and Desulfotomaculum species. Trees were calculated from aligned nucleotide and deduced DSR amino acid sequences with the ARB software package using neighbor-joining, FITCH, and maximum likelihood methods. The trees constructed with amino acid and nucleotide sequences yielded similar results. Tree topology was constructed from nucleotide sequences using neighbor-joining analysis with Jukes-Cantor distance correction method and verified by maximum-likelihood algorithm. The significance levels of interior branch points obtained in neighbor-joining analysis were determined by bootstrap analyses (1,000 data resamplings).

Real-time PCR Quantification

Dilution series of purified RT-PCR products were used as calibration standards for the real-time PCR quantification. The cDNAs were amplified with the dsrA gene-specific primers and the resulting amplicons were purified. The purified RT-PCR products were quantified and prepared for serial dilution as described previously [5], and stored at −20 °C. The detection limits of all PCR assays were determined from four independent measurements with dilution series of purified RT-PCR products (standards) in real-time PCR (108 to 101 target molecules per reaction). All assays had a minimum sensitivity of 100 to 101 target molecules per reaction. The copy numbers of unknown samples were calculated after real-time amplification from the linear regression of the standard curve (Fig. 1).

Figure 1
figure 1

Standard curves for target dsrA amplicons. The symbols represent means ± SD of triplicates of PCR amplifications of the standards. The line is the trend line of the linear regression. The lower detection limit was about 3–7 copies of target mRNA

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The cDNA generated with dsrA gene-specific primer was quantified with real-time quantitative PCR, using SYBR Green. The levels of dsrA transcripts (per μg mRNA) were determined in the incubated sediments, where the reduction in sulfate was measured. PCR was performed with the primers DSR1F and DSRQ2R as described previously [5]. The temperature profile was composed of an initial incubation step for 2 min at 50 °C (activation of the polymerase) followed by a 10 min denaturation step at 95 °C, 40 cycles of denaturation for 30 s at 95 °C, annealing for 1 min at 52 °C, elongation for 30 s at 65 °C, and a final elongation step for 6 min at 65 °C. Four negative controls (reaction without template) were included in each real-time PCR run. The size of the PCR products was checked with agarose gel electrophoresis, and the specificity of PCR products was verified by sequence analysis of clone library.

Quantitative analysis of the cDNA was carried out with the GeneAmp 5700 Sequence Detection System (Applied Biosystem, Foster City, CA) using GeneAmp 5700 SDS software (Version 1.3). The precision and reproducibility of quantification were carefully optimized, and correct lengths of PCR products were checked as described previously [5].

Nucleotide Sequence Accession Numbers

The sequences generated in this study were deposited in the GenBank database under the following accession numbers: dsrAB mRNA clones, BHS-DSR1 to BHS-DSR62 under EF418125 to EF418186, BHS-DSRs1 to BHS-DSRs62 under EF656366 to EF656427, and 16S rRNA gene clones, BHS-16S1 to BHS-16S63 under EF418062 to EF418124.

Analytical Techniques

Sulfate was measured with a Dionex DX-100 ion chromatograph as described previously [24]. Acetate concentrations were measured by high-pressure liquid chromatography (HPLC) on a Hewlett-Packard series 1100 (Agilent Technologies, Albany, NY) with a Bio-Rad Aminex HPX-87H column (300 × 7.8 mm) and a mobile phase of 8 mM H2SO4 (flow rate 1 ml/min).

Results and Discussion

DSR mRNA and 16S rRNA Genes in Petroleum-contaminated Harbor Sediments

The phylogeny of sulfate reducers in sediment incubations was evaluated with sediments that had been incubated for 7 days at the in situ temperature of 9 °C. No amplicons were obtained from mRNA or DNA extracted from Boston harbor sediments with the primer pair DSR1F/DSR4R [38] which has previously successfully recovered dsrAB DNA sequences from other environments [9, 19, 29, 34] and amplified the dsrAB sequence from a pure culture of Desulfovibrio desulfuricans in this study. However, the primer pair DSR2F/DSR4R [38], which amplifies a smaller (1.4 kbp) fragment of dsrAB and targets a more limited subset of sulfate reducers, including Desulobacteraceae and Desulfovibrio species, successfully amplified portions of the dsrAB sequences from both mRNA and DNA extracted from the sediments. In clone library generated from mRNA with the DSR2F/DSR4R primer pair, all 62 clones analyzed grouped within the Desulfobacteraceae (Fig. 2). The sequences were most closely related (83–97% identical) to the sequence of Desulfosarcina variabilis, a benzoate-oxidizing sulfate-reducer [39], and also to the environmental DSR clone sequence, Nap51, retrieved from an aromatic naphthalene-degrading consortium [33]. Some sequences were most closely related (79.2–89% identical) to the sequence of Desulfosarcina cetonica, a cresol-oxidizing sulfate-reducer [27]. These results suggest that the active sulfate reducers in these contaminated sediments that we detected are related to Desulfobacteraceae.

Figure 2
figure 2

Phylogenetic tree indicating the relationship of selected dsrAB mRNA sequences retrieved from Boston Harbor sediments (BHS-DSR clones, in bold) to those of cultivated sulfate-reducing bacteria and to other environmental clone sequences from aromatic naphthalene-degrading consortia [33] and Guaymas Basin [9]. The tree was constructed using the neighbor-joining and maximum likelihood algorithm. Bootstrap values (1,000 data resamplings) of >50% are shown. The dsrAB gene sequence of Archaeoglobus fulgidus was used as outgroup reference. The scale bar indicates the estimated number of base changes per nucleotide sequence position. GenBank accession numbers of the sequences are indicated

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The amplicon of the DSR2F/DSR4R primer set is too large for quantitative PCR. Therefore, a new primer, DSRQ2R, was designed, which when combined with DSR1F targeted the same phylogenetic group of Desulfobacteraceae sequences that were amplified from the sediments with the DSR2F/DSR4R primer set but provided an amplicon of only 123 bp. All 62 clones from a library generated with the DSR1F/DSRQ2R primer set were in a subgroup of Desulfobacteraceae that were amplified with the DSR2F/DSR4R primers (data not shown).

Analysis of a16S rRNA gene clone library generated with environmental DNA suggested that members of the Desulfobacteraceae were abundant in the sediments. The most abundant microbes were Deltaproteobacteria accounting for ca. 40% of 16S rRNA gene sequences (Fig. 3). Two of the Deltaproteobacteria clone sequences (Fig. 4) were most closely related to Geobacter metallireducens, an organism known to oxidize aromatic hydrocarbons with the reduction in Fe(III) oxides [22, 23]. The remaining 24 sequences related to Deltaproteobacteria (Fig. 4) were closely related to sequences of dissimilatory sulfate-reducing pure cultures and also to environmental 16S rRNA gene sequences from sulfate-reducing, benzene-mineralizing consortia [33] and oil field microbial communities [37]. Ten clone sequences were closely related to sequences of Desulfosarcina cetonica and Desulfosarcina variabilis, corresponding to the results from the DSR clone library. Three clone sequences were closely related to the sequence of NaphS2, a naphthalene-degrading and sulfate-reducing pure culture [13], for which dsr sequences are not yet available. Previous studies demonstrated that enhanced capacity for naphthalene degradation in Boston Harbor sediments was associated with an enrichment of 16S rRNA gene sequences closely related to NaphS2 [15].

Figure 3
figure 3

Composition and relative proportions of sequences of 16S rRNA gene clone libraries assembled from anoxically incubated Boston Harbor sediments

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Figure 4
figure 4

Phylogenetic tree indicating the relationship of selected bacterial 16S rRNA gene clone sequences retrieved from Boston Harbor sediments (BHS-16S clones, in bold) to those of cultivated sulfate-reducing bacteria, and to other environmental clone sequences from aromatic benzene-mineralizing consortia [33] and from oil field samples [37]. The tree was constructed using the neighbor-joining and maximum likelihood algorithm. Bootstrap values (1,000 data resamplings) of >50% are shown. The 16S rRNA gene sequence of Archaeoglobus fulgidus was used as outgroup reference. The scale bar indicates the estimated number of base changes per nucleotide sequence position. GenBank accession numbers of the sequences are indicated

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Quantifying dsrA Transcript Levels

When the Boston Harbor sediments were incubated at the in situ temperature of 9 °C, sulfate was consumed over time (Fig. 5). With the exception of the data point at 402 h, the loss of sulfate over time suggested that rate of sulfate reduction was relatively steady over the 1,072 h of incubation (20.9 ± 2.1 nmol h−1 ml−1 sediment slurry). DsrA transcripts could be detected at each time point. The number of dsrA transcripts increased linearly over time from ca. 4.1 × 102 copies at time 0 to ca. 1.1 × 104 copies at the end of incubation despite the fact that the sulfate reduction rate remained relatively constant (Fig. 5). For example, during the clearly steady rate of sulfate reduction between 570 h and 1,072 h of incubation the level of dsrA transcripts increased ca. threefold. These results indicated that a range of dsrA transcript levels could be associated with a similar rate of sulfate reduction in these sediments.

Figure 5
figure 5

Expression of dsrA gene and sulfate concentration during incubation of Boston Harbor sediment slurries at 9 °C without addition (a) and with addition of acetate (b) or molybdate (c). Data are means ± SD of triplicate determinations on a pooled sample from duplicate sediment incubations. Arrows indicate addition of acetate or molybdate at 167 h

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In an attempt to evaluate dsrA transcript levels at another rate of sulfate reduction, 10 mM acetate was added to the sediments at 167 h of incubation to stimulate the rate of sulfate reduction (Fig. 5b). Rates of sulfate depletion were only slightly faster than in the sediments without added acetate. Levels of dsrA transcripts were comparable to those in the sediments without added acetate and also increased over time, with the exception of the final time point. At 1,072 h, as sulfate concentrations dropped below 3 mM, the level of dsrA transcripts declined substantially (Fig. 5b).

The addition of molybdate at 167 h of incubation inhibited sulfate reduction (Figs. 5c, 6c and 7c). The dsrA transcript levels were low when sulfate reduction was inhibited in this manner (Figs. 5c, 6c and 7c).

Sediments were incubated at elevated temperatures to provide additional rates of sulfate reduction. Incubation at 16 °C, the in situ temperature in October, or at 30 °C, resulted in higher rates of sulfate reduction (Figs. 6a and 7a). Rates of sulfate reduction calculated from the initial linear loss of sulfate in these sediments were 17.5 ± 3.0 and 49.5 ± 5.6 nmol h−1 ml−1 sediment slurry for 16 and 30 °C, respectively. Addition of acetate had a greater impact on the rates of sulfate reduction at these higher temperatures (Figs. 6b and 7b), and the rates were 50.1 ± 5.9 and 54.5 ± 8.6 nmol h−1 ml−1 sediment slurry for 16 and 30 °C, respectively. As was observed in the sediments incubated at 9 °C, there was an initial increase in dsrA transcript levels over time in the sediments incubated at 16 and 30 °C. The dsrA transcript levels initially increased at a faster rate at these temperatures than in the sediments incubated at 9 °C, and in the sediments incubated at 30 °C, the highest levels of dsrA transcripts were greater than in the sediments incubated at the cooler temperatures. However, as sediment incubations at 16 and 30 °C were continued, levels of dsrA transcripts became lower as sulfate was depleted from the sediments. These results indicate that expression of dsrA in these sediments is indicative of active sulfate reduction.

Figure 6
figure 6

Expression of dsrA gene and sulfate concentration during incubation of Boston Harbor sediment slurries at 16 °C without addition (a) and with addition of acetate (b) or molybdate (c). Data are means ± SD of triplicate determinations on a pooled sample from duplicate sediment incubations. Arrows indicate addition of acetate or molybdate at 167 h

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Figure 7
figure 7

Expression of dsrA gene and sulfate concentration during incubation of Boston Harbor sediment slurries at 30 °C without addition (a) and with addition of acetate (b) or molybdate (c). Data are means ± SD of triplicate determinations on a pooled sample from duplicate sediment incubations. Arrows indicate addition of acetate or molybdate at 167 h

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Previous studies have suggested that levels of transcripts for genes involved in anaerobic respiration might be influenced not only by the rate of respiration, but also by the concentration of electron acceptor that is available [5]. Therefore, to evaluate levels of dsrA transcripts under similar conditions of sulfate availability, the rate of sulfate reduction when sulfate concentrations were ca. 10 mM were calculated. This concentration was chosen because rates of sulfate depletion at concentrations near 10 mM appeared to be linear in all sediment incubations, which made it possible to calculate a rate of sulfate reduction from the differences in sulfate concentrations over time. Also included in this comparison (Fig. 8) was data on dsrA transcript levels when sulfate reduction stopped due to sulfate depletion to reflect the fact that dsrA does not appear to be expressed when sulfate is not being reduced. Within these parameters, there was a direct relationship between levels of dsrA transcripts and rates of sulfate reduction (Fig. 8).

Figure 8
figure 8

Relationship between sulfate reduction rates when sulfate concentrations were ca. 10 mM and levels of dsrA transcripts in Boston Harbor sediments. The sulfate reduction rates were calculated from the linear depletion of sulfate reduction over time. Levels of dsrA transcripts were calculated as the midpoint of the regression lines during the linear increase of dsrA mRNA levels, when sulfate concentration reached ca. 10 mM. Data points (filled circles) originated from the following: (c) 9 °C control; d) 9 °C + acetate; (e) 16 °C control; (f) 16 °C + acetate; (g) 30 °C control; (h) 30 °C + acetate. Data points (a, b) at sulfate reduction rate 0 are originated from the sulfate depletion phase after continued incubation at 16 and 30 °C with added acetate, respectively

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Implications

To our knowledge, these results demonstrate for the first time that it is possible to monitor the gene expression of sulfate-reducing microorganisms living in contaminated marine harbor sediments. The phylogeny of the dsr transcripts suggest wthat the active sulfate reducers in petroleum-contaminated Boston Harbor sediments are sulfate reducers that are closely related to sulfate reducers available in pure culture capable of metabolizing aromatic compounds. Thus, information on the physiology of these pure cultures may aid in better understanding the factors controlling the metabolism of the sulfate reducers involved in contaminant degradation in situ.

The results also demonstrate that expression of dsrA indicates that sulfate reduction is likely to be taking place in sediment slurries. However, there were not specific levels of dsrA transcripts that were consistently related with a specific rate of sulfate reduction. This may be a common phenomenon with respiratory genes. For example, there was substantially higher expression of genes for fumarate reductase or a gene encoding a cytochrome required for Fe(III) reduction in Geobacter sulfurreducens under electron-acceptor limiting conditions than under conditions under which the electron-donor limited metabolism [5]. Thus, it may not be surprising that the levels of dsrA transcripts increased as sulfate concentrations declined, although rates of sulfate reduction remained relatively constant. However, the results also suggest that it may be possible to estimate relative rates of sulfate reduction from dsrA transcript levels when important environmental conditions, such as sulfate availability, are comparable.

Expression of genes that are linked to the central metabolism of electron donors may be more closely linked to metabolic rates than genes encoding respiratory proteins. For example, there was a good correlation between levels of transcripts for the gene encoding the citrate synthase gene of G. sulfurreducens and rates of electron transfer to Fe(III) or electrodes [16]. Furthermore, in situ levels of Geobacteraceae citrate synthase gene transcripts closely tracked the availability of the primary electron donor, acetate, during in situ bioremediation of uranium-contaminated groundwater [16]. In contrast, levels of transcripts for a diversity of housekeeping genes remained relatively constant relative to total RNA at different metabolic rates [16]. Genomic sequencing of pure culture and contaminated environments will provide information on key genes involved in the degradation of important contaminants, such as polycyclic aromatic hydrocarbons. Focusing on genes encoding enzymes involved in key steps in the degradation of contaminants in sulfate-reducing sediments is also likely to provide a more direct measure of contaminant degradation by sulfate reducers. Unfortunately, the key genes involved in the degradation of important contaminants, such as polycyclic aromatic hydrocarbons have yet to be elucidated.