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Plankton Benthos Res 1(4): 165–177, 2006 Plankton & Benthos Research © The Plankton Society of Japan Abundance and diversity of sulphate-reducing bacterioplankton in Lake Suigetsu, a meromictic lake in Fukui, Japan RYUJI KONDO*, KYOKO OSAWA, LISA MOCHIZUKI, YUKIYASU FUJIOKA & JUNKI BUTANI Department of Marine Bioscience, Fukui Prefectural University, Obama, Fukui 917–0003, Japan Received 10 July 2006; Accepted 14 September 2006 Abstract: The depth distribution of sulphate-reducing bacteria (SRB) in the water column of a meromictic lake, Lake Suigetsu, Fukui, Japan was investigated using quantitative competitive PCR targeting the gene coding for portions of the a -subunit of dissimilatory sulphite reductase (dsrA). The total bacterial cell density (DAPI count) was 513106 cells mL1 in the water column of the lake with maximum abundance occurring at the oxic-anoxic interface layer. SRB were not detected in oxic surface water using competitive PCR. SRB were found in the anoxic waters below the oxycline ranging from 104 to 105 cells mL1, accounting for 0.3–8.9% of the total bacteria. The SRB cell densities were higher than previously estimated using the most-probable-number (MPN) method. Sequencing of the cloned PCR product of dsrA showed the existence of different SRB groups in the anoxic water. The majority of the dsrA sequences were associated with the Desulfosarcina-Desulfococcus-Desulfonema group and members of the Desulfobulbaceae family. Other dsrA clones belonged to the Desulfomicrobium and Desulfovibrio species as well as to a deeply branched group in the dsrA tree with no representatives from previously isolated SRB groups. These SRB species appear to be important for the sulphur and carbon cycle in the anoxic waters of Lake Suigetsu. Key words: competitive PCR, dissimilatory sulphite reductase gene, meromictic lake, sulphate-reducing prokaryotes Introduction Microbial sulphate reduction is of great ecological and biogeochemical importance in anaerobic environments as it is the major terminal oxidation step for the flow of carbon and electrons. Sulphate-reducing prokaryotes are widely distributed in most aquatic and terrestrial environments that are depleted of oxygen e.g. marine and freshwater sediments, anoxic waters, sewage sludge digesters, waterlogged soils and the gastrointestinal tracts of humans and animals (Postgate 1984, Widdel 1988). Sulphate-reducing bacteria (SRB) are obligate anaerobic bacteria that play a significant role in the mineralisation of organic matter in anaerobic environments as well as in the biogeochemical cycling of sulphur. In environments rich in sulphate, sulphate reduction dominates mineralisation accounting for up to 50% of the organic matter decomposition in estuarine and coastal marine sediments (Jørgensen 1982). Dissimilatory sulphite reductase (DSR) is a key enzyme in the dissimilatory sulphate reduction by SRB. DSR catalyses the six-electron reduction of (bi)sulphite to sulphide. * Corresponding author: Ryuji Kondo; E-mail, [email protected] This is the final step of sulphate respiration, a reaction found only in dissimilatory sulphate-reducing prokaryotes. The ubiquity of DSR and its highly conserved sequence has made this enzyme ideal for assessing the diversity of sulphate-reducing prokaryotes in nature (Wagner et al. 1998, Zverlov et al. 2005). Using new assays for the PCR amplification of fragments from genes coding for a - (dsrA) and b subunits (dsrB) of DSR, studies of the diversity and distribution of SRB in aquatic environments are occurring (Chang et al. 2001, Joulian et al. 2001, Pérez-Jiménez et al. 2001, Thomsen et al. 2001). Shorter fragments of dsrA have been used to profile communities of SRB (Karr et al. 2005). We developed new PCR primers selective for dsrA genes of most mesophilic SRB belonging to d -Proteobacteria and used quantitative competitive PCR to rapidly and reproducibly detect and count SRB in situ as an alternative to culture-dependent methods (Kondo et al. 2004). Lake Suigetsu is a meromictic lake in Fukui, Japan, characterised by a permanent oxycline at a depth between 5 and 8 m separating the aerobic freshwater epilimnion from the anaerobic, saline, sulphidogenic hypolimnion (Kondo et al. 2000, Matsuyama 1973, Matsuyama & Saijo 1971, Takahashi & Ichimura 1968). Seawater from the Sea of Japan 166 R. KONDO et al. comes through Lakes Hiruga and Kugushi next to Lake Suigetsu. Thus the anoxic water chemistry of Lake Suigetsu is dominated by inorganic sulphur compounds with a high concentration of sulphate and steep gradients of sulphide at the chemocline (Kondo et al. 2000, Matsuyama 1973, Matsuyama & Saijo 1971). Because Lake Suigetsu is highly sulphidic, we assume microbiological sulphate reduction is responsible for the production of sulphide. Despite the importance of SRB in Lake Suigetsu, little is known about their distribution in the lake. The only study was conducted by Takeuchi & Takii (1987) who reported their vertical distribution in the water column of Lake Suigetsu by enumeration using the most-probable-number (MPN) method. MPN cell counts may underestimate because MPNs are selective and represent only a minor fraction of the actual microbial communities (Gibson et al. 1987, Jørgensen 1978). Here we examine the distribution and diversity of SRB in the water column of Lake Suigetsu using a quantitative competitive PCR targeting dsrA genes. We conclude SRB were more abundant than previously determined using a culture-dependent method and show a diverse group of SRB inhabit the anoxic waters of Lake Suigetsu. Materials and Methods Sample collection Water samples were collected from the central basin of Lake Suigetsu (35°35N, 135°53E) on 30th July 2003 and 26th January 2004 using a Kitahara’s water sampler (Rigosha). The samples were immediately added to an autoclaved BOD bottle to prevent contact with air. All samples were kept in an ice-cooled box and transported to the laboratory within a few hours of sampling. Temperature, salinity and dissolved oxygen (DO) concentration were measured using an oxygen metre (Model 85, YSI). Vertical profiles of turbidity (as kaolin mg L1; ppm) were obtained using a turbidity metre (Model PT-1, Alec Electronics). Bacterial counts The water sample for bacterioplankton counts was preserved using buffered formaldehyde at a 2% (v/v) final concentration. The bacterial cells in lake water were filtered onto black 0.2-m m polycarbonate membrane filters (Advantec), stained with 4,6-diamidino-2-phenylindole (DAPI) and counted using epifluorescence microscopy (Porter & Feig, 1980). DNA extraction A 50-mL water aliquot was filtered through a sterile polycarbonate membrane filter (0.2-m m, Advantec) to collect microbial biomass for subsequent nucleic acid extraction. The filters were stored at 85°C until processed. Nucleic acids were extracted from the filtered samples using the hydroxyapatite spin-column method (Purdy et al. 1996). After a final ethanol precipitation, the nucleic acid was resuspended in 50 m L TE buffer (10 mM Tris-HCl, 1 mM EDTA; pH 8.0). Nucleic acid purity and yield were determined using scanning spectrophotometry (Sambrook et al. 1989). Competitive PCR to enumerate SRB Competitive PCR was carried out as described elsewhere (Kondo et al. 2004). Briefly, the primers used were DSR1F (5-ACSCACTGGAAGCACGGCGG-3) (an improved primer than the DSR1F used by Wagner et al. 1998) and DSR-R (5-GTGGMRCCGTGCAKRTTGG). Competitor DNA which was about 20% shorter than the targeted region of dsrA was constructed using PCR with DNA from Desulfovibrio desulfuricans DSM642T as the template and the primer set of DSR1F; and Comp-DSR which consisted of D. vulgaris DSM644T dsrAB sequence positions 559–578 and the DSR-R primer sequence (position 622–644). PCR reactions were performed in 50 m L containing 0.2 mM dNTPs, 3.5 mM MgCl2, 0.4 m M each primer, 1PCR buffer, 1Q-solution, 2.5 U Taq DNA polymerase (QIAGEN) and the DNA from the water samples as the template. Also added were at least five dilutions of the serially diluted competitor DNA for each sample. Amplification was performed using a thermal cycler (GeneAmp PCR System 2400, Applied Biosystems): initial denaturation at 94°C for 1 min followed by 30 cycles: 94°C for 30 s, 60°C for 30 s and 72°C for 60 s with a final elongation step at 72°C for 7 min. Aliquots of PCR products were analysed by electrophoresis on 3% (w/v) agarose gel in 1TAE buffer (40 mM Tris-acetate, 1 mM EDTA; pH 8.0); and stained with ethidium bromide. The gels were photographed and band intensity was measured by densitometry (CS-9300PC, Shimadzu). To correct for differences in the intensity of the PCR fragments (Piatak et al. 1993), the intensity of the competitor DNA was multiplied by the ratio 221/177. Copy numbers of dsrA in the samples were calculated using regression analysis between the band intensity ratio of the PCR product from water DNA to those from competitor DNA using the known amounts of competitor DNA. The dsrA copy number was expressed as cells mL1 of water (equivalent to cell counts assuming one dsrA copy per cell) was calculated using dilution factors and the volume of nucleic acid extract. D. desulfuricans DSM642T was used to generate a calibration curve by analysis of filtered samples. D. desulfuricans DSM642T was grown in Postgate’s C medium (Postgate 1984) and a sample was counted using the DAPI stain method (described above). The cells were centrifuged at 14,400 g for 20 min at 4°C and resuspended to about 1011 cells mL1, serially diluted, and collected on sterile membrane filters. DNA extracts were performed for each serially diluted sample (as described above). 167 Sulphate-reducing bacteria in Lake Suigetsu Sequencing and phylogenetic analysis After PCR amplification without competitor DNA, unpurified dsrA PCR products were cloned using a TA Cloning Kit (Invitrogen) with the pCR II vector and Escherichia coli INVa F’ competent cells according to the manufacturer’s instructions. From each of these eight libraries, about 60 white colonies were randomly selected and the cloned inserts were reamplified using the vector primers M13 forward and reverse (25 cycles of 94°C for 30 sec, 50°C for 30 sec and 72°C for 30 sec); and the PCR products were purified using Wizard SV Gel and PCR Clean-Up System (Promega) according to the manufacturer’s instructions. Selected clones (52 or 53 clones from each sample) were sequenced at Macrogen, Inc. (Seoul, Korea) using the M13 forward primer. Partial dsrA sequences corresponding to D. vulgaris DSM644T dsrAB sequence position 421–641 were determined and aligned using CLUSTALX (Thompson et al. 1997). Maximum parsimony (MP) and neighbor joining (NJ) analyses were performed using PAUP* 4.0b10 (Swofford 2002). MP analysis was performed using the heuristic search algorithm with unordered unweighted characters; and gaps were treated as missing data. The likelihood ratio test was applied to select an appropriate substitution model in the maximum likelihood (ML) analysis using Modeltest 3.7 (Posada & Crandall 1998). The optimal model selected for the dsrA data set was GTRGI (general time reversible model estimating gamma distribution and the proportion of invariable sites; Rodriguez et al. 1990) with the following parameters: nucleotide frequencies A0.1745; C0.3053, G0.2512, T0.2691; gamma distribution with shape parameter0.7690; substitution rate A→C 2.2117, A→G4.4578, A→T2.6221, C→G1.6916, C→ T4.5735, G→T1.00; proportion of invariable sites 0.1341. This model was also used for the NJ analysis. The ML analysis was carried out using TREEPUZZLE 5.2 (Schmidt et al. 2002) with 5,000 puzzle steps. For bootstrap analysis (Felsenstein 1985), 1000 bootstrap data sets were generated from resampled data for MP and NJ analyses, with all other settings set by default. Statistical analysis and sequence population diversity To assign sequences to distinct phylotypes, sequences with similarities greater than 98% were considered to represent the same phylotypes. In previous similar analyses for 16S rDNA, the discriminator values are 97% or greater (Sakano & Kerfhof 1998, Humayoun et al. 2003). Sequence similarities of the region amplified by PCR in this study did not exceed 98% among pure SRB cultures available from the databases, except for some species; e.g. Desulfovibrio termitidis compared to Desulfovibrio vulgaris subsp. oxamicus (99% similarity), Desulfomicrobium apsheronum compared to Desulfomicrobium macestii (98% similarity) and Thermodesulfovibrio yellowstonii compared to Thermod- esulfovibrio islandicus (99% similarity). Thus the taxa (phylotypes) defined for this analysis may be distinct at least to the species level (or higher). Coverage (C) was calculated using the following formula: C1(n1/N), where n1 is the number of phylotypes that occurred only once in the clone library and N is the total number of clones examined (Mullins et al. 1995). Rarefaction curves (Heck et al. 1975) were produced using software available online at http://www.uga.edu/strata/ software.html. The phylogenetic compositions of libraries were compared using the Sorensen similarity index, Cs2j/(ab), where j is the number of phylotypes common to both samples and a and b are the numbers of phylotypes in libraries A and B, respectively (Magurran 1988). Statistical significance of differences in composition of pairs of libraries was tested using the LIBSHUFF programme (Singleton et al. 2001) which is available online at http://www. arches.uga.edu/~whitman/libshuff.html. Nucleotide sequence accession numbers Partial cloned dsrA sequences recovered from the water column of Lake Suigetsu were deposited in DDBJ under accession numbers AB240585 to AB240638. Only one representative sequence with 98% similarity was deposited. Results Water column profiles Figure 1 shows the depth distribution of the physicochemical properties of the central basin of Lake Suigetsu when our samples were collected. A steep thermocline was evident between 5 and 10 m (regardless of sampling date). Surface water was saturated with DO and the DO concentration decreased rapidly below 3 m to the limit of detection at 6 m in July 2003 and 7 m in January 2004. The salinity of the epilimnic water was 2–4 practical salinity units (psu) and 12–14 psu for hypolimnic water. This demonstrates stagnation of the anoxic saline water in deeper layers from approximately 6 m to the bottom at 34 m. Turbidity was about 2–5.6 ppm in the surface layer and increased to a maximum of 12.2 ppm at 6 m in July 2003 and 20.6 ppm at 7 m in January 2004. Depth distribution of bacterioplankton The vertical distribution of total bacteria in the water column of Lake Suigetsu is shown in Fig. 2. Bacterioplankton densities in the epilimnion were 8.18.8106 cells mL1 in July 2003 and 7.49.8106 cells mL1 in January 2004 with the peak at the oxycline. Bacterioplankton densities were less in the hypolimnion (5.05.8106 cells mL1 in July 2003 and 5.57.8106 cells mL1 in January 2004) than in the epilimnion. Different known numbers of D. desulfuricans DSM642T cells were collected on filters to generate a calibration curve 168 R. KONDO et al. Fig. 1. Depth distribution of water temperature (), salinity (), dissolved oxygen concentration () and turbidity () in the Lake Suigetsu water column on 30th July 2003 (A) and 26th January 2004 (B). Fig. 2. Depth profile of total bacterial counts (shaded bar) and SRB numbers (black bar) determined by competitive PCR in the Lake Suigetsu water column on 30th July 2003 (A) and 26th January 2004 (B). Error bars represent the standard error of the mean (n3). by analysis of filtered samples. The advantage of measuring the calibration curve with whole cells onto the filter is the reduced potential biases such as incomplete cell lysis, DNA degradation and DNA adsorption onto the filter are included in the calibration curve. DNA from each of the samples was coamplified under optimal competitive PCR conditions and the results show a linear relationship (r20.994) between the cell numbers collected on filters and those detected by PCR (Fig. 3). The assay slightly overestimated the number of D. desulfuricans cells filtered compared to the ideal (yx). This result indicates that PCR of DNA from 105 to 1010 cells could be used to quantify filtered samples. The depth distribution of SRB determined using competitive PCR is shown in Fig. 2. SRB were not detected in oxic surface water of Lake Suigetsu by PCR using the DSR1F and DSR-R primers. High densities of SRB from 1.9104 cells mL1 to 6.7105 cells mL1 were detected in the anoxic water layer using the competitive PCR. The highest densities were 2.2105 cells mL1 at 6 m depth in July 2003 and 6.7105 cells mL1 at 7 m depth in January 2004 Fig. 3. Calibration curve of SRB count by quantitative competitive PCR. Dotted line denotes yx. Error bars indicate the standard error of the mean (n3). Sulphate-reducing bacteria in Lake Suigetsu where the maximum turbidity was found. The cell densities estimated by competitive PCR were from 0.3 to 8.9% of the total bacterial cell densities. The ratios of SRB cells to total bacterial cells may have been higher in July 2003 (mean: 5.7%, range: 0.3–8.9%) than in January 2004 (mean: 1.3%, range: 0.7–2.1%). Diversity of SRB based on dsrA As expected, the 221-bp gene product was obtained from anoxic water samples using the primer set DSR1F/DSRR (Kondo et al. 2004). Clone libraries were made from the dsrA PCR products from water samples at 6 m, 10 m, 20 m and 30 m depth in July 2003, and 7 m, 10 m, 20 m and 30 m depth in January 2004 to identify the various SRB in Lake Suigetsu. A total of 419 clones (52 or 53 clones for each sample) were sequenced. As several clones had identical sequences, the clones were assembled into 134 different sequences. Fifty-four distinct phylotypes were recognised (Table 1 and Fig. 4) using our definition (98% identity). To obtain a reliable description of the phylogenetic relationship of the SRB population in the water column of Lake Suigetsu, we included in our analysis the most characterised dsrA sequences of cultured SRB and uncultured environmental clones available in the databases. Several phylogenetic approaches were taken to analyse the partial dsrA sequences. Although differences in tree topologies were obtained among these approaches, a similar ordering of taxa was found among the different phylogenetic analyses. Similar orders of taxa were also found between our partial dsrA sequences and almost complete dsrAB (Zverlov et al. 2005). This ensured that biases imposed from phylogenetic analyses of shorter dsrA sequences are less evident in the resulting tree. Phylogenetic analyses revealed the presence of ten lineages of cloned dsrA sequences designated as clusters A to J (Fig. 4). These groupings were stable and were consistently recovered using the MP and ML methods. Although some taxa were related to SRB reference cultures, others represent previously undescribed SRB. The largest cluster of clone sequences grouped in cluster E (38% of all clones) includes Desulfococcus multivorans, Desulfonema limicola and Desulfonema ishimotoi within the d -Proteobacteria. This cluster also contains environmental dsrA sequences retrieved from estuarine sediments (INOC-DSR3, INOC-DSR26, VN4, VN11), a mesophilic sulphide-rich spring (ZDSR2), a salt marsh (PIM02A05) and a deep-sea hydrothermal vent chimney (INDO-40). These environmental clones were reported to be closely related to the genera Desulfococcus, Desulfonema and Desulfosarcina (Bahr et al. 2005, Elshahed et al. 2003, Joulian et al. 2001, Leloup et al. 2006, Nakagawa et al. 2004). Cluster D was related to the genus Desulfosarcina. An environmental clone from the shallow-water sediment in Kysing Fjord, INOC-DSR20 (Joulian et al. 2001), was included in this cluster. Cluster C was not clustered with any of the isolated 169 SRB groups on the dsrA tree. Clones in cluster C were slightly more similar in sequence to dsrA from Desulfosarcina variabilis (77–80%) than from Desulfomusa hansenii (75–77%) (Table 1). Clusters C, D and E were affiliated with the Desulfococcus-Desulfonema-Desulfosarcina group in the family Desulfobacteraceae. The second most abundant group, cluster G, comprises 91 sequences from the water column. This cluster was affiliated with members of the Desulfobulbaceae family. Clone sequences in cluster G showed 81 to 82% similarities to a groundwater clone retrieved from a uranium mill tailing site (Table 1). These sequences were recovered in higher abundances from the water column in July 2003 as compared to January 2004 (Table 1). Cluster H was 17% of all clones. These sequences were phylogenetically distant from any of the isolated SRB lineages but were related to dsrA clones recovered from uncultured SRB in environmental samples including one from uranium mill tailing groundwater (Chang et al. 2001), an acidic fen (Loy et al. 2004), Lake Fryxell (Karr et al. 2005), Guaymas Basin (Dhillon et al. 2003) and the Seine estuary (Leloup et al. 2004, 2006). Cluster F comprises 25 sequences from all samples except for the 20 m sample in July 2003. Two sequences (phylotype-46) were closely related to Desulfomonile tiedjei (82% similar). However, phylotypes-5 and -51 were more similar to Desulfonema ishimotoi (73%) and the sulphatereducing bacterium Hxd3 (80%), respectively, than to Desulfomonile tiedjei (72–75%). Cluster J contained 17 dsrA sequences unique to Lake Suigetsu. These sequences were phylogenetically distant from any isolated SRB group. Clones in phylotype-14 showed low sequence similarity (70%) to dsrA from Desulfotomaculum nigrificans being the closest cultured relative; whereas clones of phylotype-49 showed 79% sequence similarity to an estuarine sediment clone, CF5 (Table 1). The remaining 11 sequences form the small clusters A, B and I. Cluster A contains most of the dsrA sequences from cultured Desulfovibrio within the d -Proteobacteria. A single clone from 10 m depth sample collected in January 2004 was detected in this cluster. Cluster B comprises seven sequences. This cluster is affiliated with the genus Desulfomicrobium of the d -Proteobacteria. Six of these clones were recovered from water samples collected in January 2004; whereas only one clone was detected from the 30 m sample in July 2003. Cluster I contains no cultured representatives. Cloned sequences in this cluster showed sequence similarities (72 to 80%) to an environmental clone sequence retrieved from an acidic fen (Loy et al. 2004). Depth distribution of SRB groups The relative abundance of the different phylotypes in the libraries was calculated for all eight samples (Fig. 5). Of the sequenced clones, 48% grouped with the DesulfosarcinaDesulfococcus-Desulfonema group (clusters C, D and E) 170 R. KONDO et al. Table 1. Assignment of dsrA clones from the water samples of Lake Suigetsu to distinct phylotypes. No. of clones from samples collected at the following depth: Phylotype July 2003 Most similar dsrA sequence in DDBJ as determined by BLAST searcha January 2004 6m 10 m 20 m 30 m 7m 10 m 20 m 30 m 1 20 15 16 13 4 7 2 3 2 1 3 6 7 4 1 1 5 2 1 6 6 8 1 9 9 6 5 6 9 4 1 3 3 6 6 8 18 7 14 8 7 1 8 1 9 1 10 1 11 3 12 1 13 1 3 14 2 1 15 1 16 1 17 2 1 18 1 1 19 1 1 8 1 7 1 4 7 5 1 3 2 4 7 3 1 2 3 1 1 21 1 22 1 23 1 24 1 9 1 1 2 1 1 20 2 2 2 1 1 2 1 1 1 2 1 25 1 1 26 1 1 1 1 Clusterb (accession no., % identity) Uranium mill tailing clone UMTRAdsr853-36 (AY015529, 81) Uranium mill tailing clone UMTRAdsr617-8 (AY015542, 77) Seine estuary clone VN11 (AY953403, 92) Deep-sea hydrothermal vent chimney clone INDO-40 (AB124917, 81) Desulfonema ishimotoii (AY626030, 73) Seine estuary clone VN4 (AY953396, 82) Seine estuary clone VN4 (AY953396, 80) Guaymas basin clone B04P026 (AY197455, 76) Kysing Fjord clone INOC-DSR20 (AF360755, 91) Petroleum-contaminated sediment clone Nap51 (AF327309, 82) Desulfotomaculum ruminis (U58118, 74) Desulfosarcina variabilis (AF360643, 79) Uranium mill tailing clone UMTRAdsr853-36 (AY015529, 81) Desulfotomaculum. nigrificans (AF482466, 70) Acidic fen clone dsrSbII-25 (AY167481, 80) Sulfide-rich spring clone ZDSR2 (AY327244, 81) Desulfosarcina variabilis (AF360643, 80) Uranium mill tailing clone UMTRAdsr617-8 (AY015542, 74) Seine estuary clone VN4 (AY953396, 78) Kysing Fjord clone INOC-DSR20 (AF360755, 89) Uranium mill tailing clone UMTRAdsr617-8 (AY015542, 72) Desulfotomaculum thermosapovorans (AF271769, 71) Desulfosarcina variabilis (AF360643, 77) Deep-sea hydrothermal vent chimney clone INDO-40 (AB124917, 80) Acidic fen clone dsrSbI-64 (AY167474, 78) Uranium mill tailing clone UMTRAdsr624-20 (AY015544, 89) G H E E F E E H D E H D G J I E C H E D H H C D H H 171 Sulphate-reducing bacteria in Lake Suigetsu Table 1. continued. No. of clones from samples collected at the following depth: Phylotype July 2003 6m a b 10 m 20 m 27 1 28 1 29 1 30 1 Most similar dsrA sequence in DDBJ as determined by BLAST searcha January 2004 30 m 7m 10 m 20 m 30 m 1 1 31 1 32 33 1 1 34 35 36 1 1 2 37 2 1 1 1 1 3 38 1 39 2 2 3 3 40 1 41 1 42 1 43 1 44 1 45 2 1 46 47 2 2 1 48 1 2 49 1 50 51 52 1 2 1 1 53 1 54 1 Altchul et al. (1997) Cluster of dsrA clones as inferred from Fig. 4. Clusterb (accession no., % identity) Uranium mill tailing clone UMTRAdsr624-20(AY015544, 89) Seine estuary clone VN9 (AY953401, 75) Petroleum-contaminated sediment clone Nap51 (AF327309, 71) Guaymas basin clone B04P026 (AY197455, 74) Sulfide-rich spring clone ZDSR2 (AY327244, 75) SRB AK01 (AF327301, 87) Uranium mill tailing clone UMTRAdsr853-36 (AY015529, 82) SRB Hxd3 (AF327308, 85) Desulfovibrio longus (AB061540, 82) Kysing Fjord clone INOC-DSR20 (AF360755, 91) Deep-sea hydrothermal vent chimney clone INDO-40 (AB124917, 81) Guaymas basin clone B04P037 (AY197458, 77) Deep-sea hydrothermal vent chimney clone INDO-40 (AB124917, 78) Lake Fryxell clone LFdsrC24 (AY273288, 84) Desulfotomaculum thermosapovorans (AF271769, 73) Acidic fen clone dsrSbII-25 (AY167481, 76) Acidic fen clone dsrSbII-25 (AY167481, 72) Desulfovibrio aminophilus (AY626029, 87) Petroleum-contaminated sediment clone Nap30 (AF327311, 97) Desulfomonile tiedjei (AF334595, 82) New England salt marsh clone PIMO2A05 (AY741562, 90) Kysing Fjord clone INOC-DSR26 (AF360761, 81) Estuarine sediment clone CF5 (AF442721, 79) SRB AK01 (AF327301, 84) SRB Hxd3 (AF327308, 80) Uranium mill tailing clone UMTRAdsr626-8 (AY015543, 87) Desulfosarcina variabilis (AF360643, 80) Guaymas basin clone B04P026 (AY197455, 76) H H E H E D G E B D E H D H H I I A E F E E J E F H D H 172 R. KONDO et al. Fig. 4. Phylogenetic tree showing the relationships of the analysed dsrA clones retrieved from the waters of Lake Suigetsu with the dsrA from characterised sulphate-reducing prokaryotes. Environmental sequences determined in this study are shown in boldface. Bootstrap values based on 1000 replicates for NJ and MP, and quartet-puzzling support values for ML are shown for branches with more than 50% support. The distance scale indicates the expected number of changes per sequence position. Numbers in parentheses are the number of clones within each phylotype followed by DDBJ accession numbers. Sulphate-reducing bacteria in Lake Suigetsu 173 Fig. 5. Depth and seasonal distribution of dsrA clones in the water column of Lake Suigetsu in July 2003 (a) and January 2004 (b). Discussion Fig. 6. Rarefaction curves generated for dsrA in clone libraries from samples collected at 6 (), 10 (), 20 () and 30 m () in July 2003 and at 7 (), 10 (), 20 () and 30 m () in January 2004. within the d -Proteobacteria. Some sequences recovered from all samples, except for the sample collected at 6 m in July 2003, fell within these groups. The second most abundant group, cluster G, comprises 91 sequences from the water column of the lake. Six metre samples were primarily sequences related to cluster G of the Desulfobulbaceae family. Cluster G was frequently detected from samples collected in July 2003. The dsrA sequences from cluster H were also detected irrespective of water depth or season. Using the 98% similarity cut-off value, the coverage values for each library were from 75 to 91% indicating that the libraries were reasonably well sampled for diversity (Mullins et al. 1995). Analysis of the dsrA clonal libraries in which rarefaction curves were used did not reveal a great change in the diversity of sulphate-reducing populations among the samples (Fig. 6). The similarity of the phylotype populations in these libraries ranged from 39 to 65%. LIBSHUFF analysis indicates the libraries from all samples were not significantly different, indicating that there is no difference in the diversity of SRB populations in Lake Suigetsu in the water below the oxycline or during seasons. Lake Suigetsu has attracted considerable interest, especially in bacterial sulphate reduction with reference to the carbon cycle, because of the large accumulation of sulphide in the deeper layers of the lake (Kondo et al. 2000); however, little is known about the distribution and structure of the SRB population in the lake. Since no suitable media are available to enumerate all SRB simultaneously, we developed a method to quantify the microorganisms responsible for sulphate reduction directly from natural samples (Kondo et al. 2004). We determined here the distribution and diversity of SRB in the water column of Lake Suigetsu using a competitive PCR. The technique was used to estimate the dsrA copy number in the waters from Lake Suigetsu. Assuming the cells have a single copy of the DSR gene, the copy number should indicate the cell number of SRB in the water samples. However, DSR gene copy number may vary with species. Desulfobacter vibrioformis, Desulfobulbus rhabdoformis (Larsen et al. 2000), Desulfovibrio vulgaris (Karkhoff-Schweizer et al. 1995), Desulfobacula toluolica (Zverlov et al. 2005) and Archaeoglobus fulgidus (Dahl et al. 1993) have only a single copy of the DSR gene but SRB existing in nature may have multiple copies of the DSR gene. Furthermore, some bacterial species incapable of sulphate reduction such as Desulfitobacterium halogenans (Klein et al. 2001), Desulfitobacterium hafniense (Nonaka et al. 2006), Bilophila wadsworthia (Lane et al. 2001) and Sporotomaculum hydroxybenzoicum (Zverlov et al. 2005) have the DSR gene. Therefore, our competitive PCR analysis probably overestimates the SBR population in situ. Collection of Desulfovibrio desulfuricans DSM642T cells on the filter, followed by competitive PCR quantification, demonstrates the usefulness of the technique in situ. There was a good correlation between the cell numbers filtered and those detected by the assay. The slope of the calibration curve was found to be 1.05; suggesting D. desulfuricans DSM642T has a single copy of the DSR gene. The detection 174 R. KONDO et al. limit of dsrA is approximately 103 copies in a PCR reaction (Kondo et al. 2004). With the dilution factor of the water samples taken into account this would translate to a detection limit of approximately 103 copies (cells) mL1 using our standard PCR conditions. By competitive PCR, SRB were not detected in oxic surface water (Fig. 2); however, SRB were detected even in the oxic layer of the lake using the MPN method (Takeuchi & Takii 1987). Koizumi et al. (2004) detected SRB by quantitative oligonucleotide probe membrane hybridisation in oxic and microaerophilic surface waters of Lake Kaiike, a small saline meromictic lake in Japan similar to Lake Suigetsu. No amplification of dsrA was observed with DNA extracted from water samples of the oxic surface waters possibly because there was either a low density of SRB in the oxic waters or there were mismatches in the primer regions of the SRB existing in Lake Suigetsu. High SRB densities (0.26.7105 cells mL1) were detected in the waters below the oxycline in Lake Suigetsu using the competitive PCR. Takeuchi & Takii (1987) report densities of SRB in the water column of the lake were 100102 cells mL1 using the MPN method. Cell densities by competitive PCR were considerably higher than those estimated by the MPN method. Several studies demonstrate the number of viable SRB in aquatic sediments are underestimated by a factor of more than 1,000 when standard MPN methods are used with selective enriched media (Gibson et al. 1987, Jørgensen 1978). Thus, the cell density estimates using the molecular techniques are several orders of magnitude higher than the MPN estimates. SRB cell densities estimated by competitive PCR ranged from 0.3 to 8.9% of the total bacterial densities. This apparent high ratio may be due to overestimation using the competitive PCR. However, sulphate reducers within the d -Proteobacteria were detected as intensely stained bands by rRNA-based denaturing gradient gel electrophoresis (DGGE) analysis (Kondo, unpublished data). Muyzer et al. (1993) found DGGE gel bands correspond to different 16S rRNA gene sequences and thus reflect distinct microbial populations in the community. Moreover, only numerically dominant populations will be detected by DGGE. As bacterial sulphate reduction activity is correlated with the rRNA content in cells (Neletin et al. 2003), the intensely of the DGGE bands of SRB from Lake Suigetsu rRNA samples indicate that the SRB must constitute a significant fraction of the bacterial community and are active. Thus SRB in the water column of Lake Suigetsu appear to play an important role in the anaerobic degradation of organic matter as well as the cycling of sulphur. Clone libraries were made from the dsrA PCR products at several water depths to identify the various SRB in the water column. We used a short fragment (221 bp) of dsrA to reconstruct phylogenetic trees. Sequence length has a profound effect on reliable reconstruction of phylogenetic trees (Kumar & Gadagkar 2000). Pérez-Jiménez et al. (2001) tested whether the length of dsrAB used for the analysis had a significant effect on the tree topology by reconstructing phylogenetic trees for alignments of different length dsrAB sequences and found that the general topology of all trees was consistent with the previous dsrAB tree based on fulllength dsrAB fragments (Minz et al. 1999, Wagner et al. 1998). Karr et al. (2005) also found that branching patterns of phylogenetic trees generated based on shorter dsrA sequences were consistent with trees generated based on the entire dsrAB operon. Although slight differences in tree topologies were obtained between our partial sequences and complete dsrAB (Zverlov et al. 2005), similar orderings of taxa were found between these two analyses. Furthermore, we include in our analysis well-defined environmental dsrAB sequences (e.g. Chang et al. 2001, Thomsen et al. 2001, Leloup et al. 2006) which were chosen from the databases based on BLAST (Altschul et al. 1997) similarities. These indicate that the dsrA fragment we have targeted can be used to analyse SRB communities in situ. Our molecular characterisation of SRB showed the presence of novel dsrA sequences related to the d -Proteobacteria and to a deeply branched group in the dsrA tree with no representatives from previously isolated SRB. Most members of the Lake Suigetsu SRB community are related to complete oxidizing genera, Desulfococcus, Desulfonema and Desulfosarcina in the family Desulfobacteraceae (Fig. 4; clusters C, D and E). Some sequences recovered from all samples, except for the 6 m samples in July 2003, fell primarily within this group (Fig. 5). Sequences from this group were abundantly recovered from the surface sediment of Aarhus Bay, Denmark (Thomsen et al. 2001), a New England salt marsh (Bahr et al. 2005) and the Colne estuary, UK (Kondo et al. 2004). Desulfonema and Desulfosarcina species are marine organisms that require NaCl to grow, while Desulfococcus species are freshwater organisms but also grow well in brackish and marine media (Widdel & Bak 1992). Water salinity below the cline was approximately half that of seawater (Fig. 1). If the physiological features of the dsrA phylotypes in this study are similar to those of cultured species, we infer that SRB related to the NaCl-requiring complete oxidizers, Desulfonema and Desulfosarcina, and primarily freshwater-inhabiting Desulfococcus could be present together and may play an important role in the terminal oxidation of organic matter to CO2 in Lake Suigetsu. The second most abundant group, cluster G, comprises 91 sequences (22% of all clones). Sequences recovered from the 6 m sample in July 2003 were predominantly from cluster G. This cluster is affiliated with incomplete oxidizers of the Desulfobulbaceae family and has been referred to as the UMTRA DSR cluster D (Chang et al. 2001). Clone sequences in cluster G were closely related to an environmental sequence retrieved from a uranium mill tailing site (Chang et al. 2001). Sequences from this cluster were also recovered from freshwater or brackish environments such as estuarine sediments (Bahr et al. 2005, Kondo et al. 2004, Leloup et al. 2006) and a wetland (Castro et al. 2002), but not marine environments (Dhillon et al. 2003, Thomsen et 175 Sulphate-reducing bacteria in Lake Suigetsu al. 2001). Members of the Desulfobulbaceae family can use alternative electron acceptors leading to sulphate and can disproportionate sulphur oxianions while Desulfobulbus is known to be able to grow by fermentation of lactate or ethanol and CO2 without sulphate. Sulphate concentrations below the oxycline are 2–8 mM (Kondo et al. 2000) which is sufficiently high as not to limit sulphate reduction. However, we previously reported that thiosulphate was detected in anoxic waters below the oxycline (6–7 m) of Lake Suigetsu, ranging from 1 m M or less to 60 m M (Kondo et al. 2000). This suggests thiosulphate may be used as an electron acceptor or may be disproportionated by microorganisms belonging to cluster G, including the thiosulphate-disproportionating bacterium Desulfocapsa. Cluster H contains dsrA sequences that were phylogenetically distant from any isolated SRB group. Cluster H compressed 11.5–26.9% of the cloned sequences in each sample. This cluster has been referred to as the UMTRA DSR cluster F (Chang et al. 2001). The dominance of sequences related to this cluster was reported in ground water from a uranium mill tailing site (Chang et al. 2001), a freshwater wetland (Castro et al. 2002), acidic fens (Loy et al. 2004) and a hydrothermal vent site (Dhillon et al. 2003). This cluster is not related to any cultured SRB and its physiology is unknown. As their importance is not sufficiently understood, further study is required to isolate SRB belonging to this cluster and to investigate whether this SRB cluster is active in the lake. The coverage values for each library were from 75 to 91% indicating that the libraries were reasonably well sampled for diversity (Mullins et al. 1995). Although there were no significant differences among the water depths and sampling dates, a minor change in the composition of dsrA phylotypes between seasons was recognised – that is, dsrA sequences related to cluster G were recovered with relatively higher frequency from summer samples (29–40%) than from winter samples (3.8–21.7%). The vertical profiles of water temperature, salinity and DO concentration clearly demonstrated the stagnation of anoxic saline water in the deeper layers from approximately 6 m to the bottom of the lake at 34 m (Fig. 1). Salinity and temperature below the oxycline were stable regardless of the season (Fig. 2, Kondo et al. 2000). This implies that environmental factors other than temperature and salinity influence the composition of the SRB population. In the surface water of Lake Suigetsu, cyanobacterial blooms of Microcystis and/or Anabaena occur during the summer season while the dinoflagellate, Heterocapsa dominates during the winter season. Thus, the compositions of organic matter in the deeper layers supplied from the euphotic layer of the lake may vary with season. Composition of organic matter available for the SRB as an electron donor may cause minor differences in the composition of the SRB. In conclusion, using dsrA-selective competitive PCR to enumerate SRB, we show SRB in Lake Suigetsu were more abundant than previously determined using culture- dependent methods; and show the highest cell densities of SRB were observed in water just below the oxycline in the lake. Sequences of cloned PCR products show the different SRB groups in the water. The complete oxidizers, Desulfococcus, Desulfonema and Desulfosarcina, species may be important in the sulphur and carbon cycles in Lake Suigetsu as may be members within the family Desulfobulbaceae and a deeply branched group in the dsrA tree with no representatives from previously isolated SRB. 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