RESEARCH ARTICLE

Determinants of the microbial community structure of eutrophic, hyporheic river sediments polluted with chlorinated aliphatic hydrocarbons Kelly Hamonts1,2, Annemie Ryngaert1, Hauke Smidt3, Dirk Springael2 & Winnie Dejonghe1 1

Flemish Institute for Technological Research (VITO), Separation and Conversion Technology, Mol, Belgium; 2Division Soil and Water Management, KU Leuven, Heverlee, Belgium; and 3Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands

Correspondence: Winnie Dejonghe, Flemish Institute for Technological Research (VITO), Separation and Conversion Technology, Boeretang 200, 2400 Mol, Belgium. Tel.: +3214335690; fax: +3214321186; e-mail: [email protected] Received 19 May 2013; revised 29 October 2013; accepted 15 November 2013. Final version published online 10 December 2013. DOI: 10.1111/1574-6941.12260

MICROBIOLOGY ECOLOGY

Editor: Tillmann Lueders Keywords Dehalococcoides; sulfate-reducing bacteria; methanogenic archaea; Geobacteraceae; DGGE; organic carbon content.

Abstract Chlorinated aliphatic hydrocarbons (CAHs) often discharge into rivers as contaminated groundwater baseflow. As biotransformation of CAHs in the impacted river sediments might be an effective remediation strategy, we investigated the determinants of the microbial community structure of eutrophic, CAH-polluted sediments of the Zenne River. Based on PCR-DGGE analysis, a high diversity of Bacteria, sulfate-reducing bacteria, Geobacteraceae, methanogenic archaea, and CAH-respiring Dehalococcoides was found. Depth in the riverbed, organic carbon content, CAH content and texture of the sediment, pore water temperature and conductivity, and concentrations of toluene and methane significantly contributed to the variance in the microbial community structure. On a meter scale, CAH concentrations alone explained only 6% of the variance in the Dehalococcoides and sulfate-reducing communities. On a cm-scale, however, CAHs explained 14.5–35% of the variation in DGGE profiles of Geobacteraceae, methanogens, sulfate-reducing bacteria, and Bacteria, while organic carbon content explained 2–14%. Neither the presence of the CAH reductive dehalogenase genes tceA, bvcA, and vcrA, nor the community structure of the targeted groups significantly differed between riverbed locations showing either no attenuation or reductive dechlorination, indicating that the microbial community composition was not a limiting factor for biotransformation in the Zenne sediments.

Introduction Hyporheic zone sediments form the interface between groundwater and surface water in the riverbed. Hyporheic zones are often characterized by steep, vertical gradients of various physicochemical parameters, such as organic carbon content and redox potential, in the river sediments, which enable a broad spectrum of metabolic processes (e.g. Brunke & Gonser, 1997). Therefore, hyporheic sediments are often hot spots in both diversity (Beier et al., 2008) and productivity of organisms, which can considerably impact the nutrient or pollutant flow through a river system (Brunke & Gonser, 1997; Pusch et al., 1998; Fischer et al., 2005). Various studies have explored the microbial community structure of freshwater sediments (e.g. Findlay & Sinsabaugh, 2006; Hullar et al., FEMS Microbiol Ecol 87 (2014) 715–732

2006; Beier et al., 2008; Bai et al., 2012; Febria et al., 2012), including both unpolluted as well as heavy-metalpolluted sediments (e.g. Feris et al., 2003a), sediments impacted by discharge of wastewater treatment plant effluent (Wakelin et al., 2008), and sediments impacted by groundwater containing high concentrations of nitrate (e.g. Iribar et al., 2008). Those studies either focused on the total bacterial and archaeal community structures (Feris et al., 2003a, b; Koizumi et al., 2003a; Hullar et al., 2006; Beier et al., 2008; Febria et al., 2012), or on microbial populations performing specific functions such as ammonia-oxidizing bacteria (Bai et al., 2012), denitrifying bacteria (Iribar et al., 2008; Bai et al., 2012), sulfatereducing bacteria (Koizumi et al., 2003b; P
erez-Jim
enez & Kerkhof, 2005), and/or methanogens (Koizumi et al., 2003b; Chan et al., 2005). ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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At various locations and in particular at former industrial sites, surface water is impacted by discharge of groundwater contaminated with organic pollutants such as BTEX (benzene, toluene, ethylbenzene, xylene) and chlorinated aliphatic hydrocarbons (CAHs; e.g. Conant et al., 2004; Hamonts et al., 2009). Recently, it has been proposed that river sediments have a great potential to function as natural biobarriers by removing CAHs from polluted groundwater during passage through the hyporheic zone, in particular in case of eutrophic sediments (e.g. Hamonts et al., 2009, 2012). The high organic carbon level of such sediments stimulates the fermentation of organic matter, resulting in a supply of molecular hydrogen which serves as electron donor for organohalide-respiring bacteria (OHRB; McCarty, 1997). Due to the abundance of both electron donor (hydrogen) and electron acceptors (organohalides), eutrophic anaerobic river sediments might represent a suitable habitat for OHRB. CAH-respiring activity has been detected in anaerobic river sediments (Conant et al., 2004; Kittelmann & Friedrich, 2008a; Hamonts et al., 2009, 2012), and OHRB have been repeatedly isolated from such sediments (e.g. Krumholz et al., 1996; Sung et al., 2003). However, despite their potential role in natural attenuation of CAHs, the microbial community structure of hyporheic zone sediments infiltrated by CAH-contaminated groundwater is poorly studied. In particular, the environmental factors structuring the composition of OHRB in these CAH-polluted river sediments are not properly identified, and information on the relationship between the presence of OHRB and other groups which are known to compete for hydrogen, such as methanogens and iron- or sulfate-reducing bacteria (McCarty, 1997), is scarce. This information is necessary, however, to evaluate the potential of river sediments as natural biobarriers. The objectives of this study were therefore (1) to determine the environmental factors shaping the community structure of OHRB and potential competitors of OHRB for electron resources in CAH-polluted river sediments, and (2) to assess whether changes in the distribution of these communities in the sediments could explain differences in CAH-respiring activity. Research focused on a stretch of the Belgian Zenne River, where groundwater contaminated with cis-dichloroethene (cis-DCE), vinyl chloride (VC) and 1,1-dichloroethane (1,1-DCA) discharges and contaminates the river sediments (Hamonts et al., 2009). Microbial reductive dechlorination of the CAHs was observed in the Zenne riverbed, as well as dilution of the CAHs via surface water infiltration or mixing with unpolluted groundwater (Hamonts et al., 2009; Kuhn et al., 2009). As both the occurrence and the extent of the CAH attenuation processes showed large spatial variations in the Zenne riverbed (Hamonts et al., ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

K. Hamonts et al.

2009; Kuhn et al., 2009), the sediment microbial community was examined on an extensive sampling grid, consisting of 25 positions and three depths (10, 60 and 100 cm) in a 675 m2 area. In addition, detailed depth profiles (from 0 to 83 cm) of the community structure were obtained for four selected positions. For the OHRB, we focused on the Dehalococcoides community as these bacteria are to date the only known OHRB that are able to respire with VC and cis-DCE, the main groundwater pollutants in the Zenne riverbed. The other studied communities included the sulfate-reducing bacteria, ironreducing bacteria (Geobacteraceae), and methanogens, as these guilds are potential competitors of OHRB for electron resources, and because their presence reflects the different redox conditions in the Zenne sediments.

Materials and methods Study site and sample collection

The study site was a 45-m long stretch of the Zenne River in an industrial area in Vilvoorde, Belgium, where groundwater containing up to 2200 lg L 1 VC, 1200 lg L 1 cis-DCE, 150 lg L 1 1,1-DCA, and 450 lg L 1 chloroethane (CA) discharges into the river sediments (Fig. 1; Hamonts et al., 2009). The Zenne River received municipal sewage at various locations in the studied region, which created highly eutrophic conditions in the surface water and the riverbed. Sediment materials ranged from fine- to coarse-grained sand and gravel to silt and slick. The sediment samples used in this study were collected in December 2005 and May 2006 using a 4-cm-diameter piston sediment sampler. In May 2006, samples were collected every 5 m along three longitudinal transects of 45 m length, located either 2 m from the right riverbank, 2 m from the left riverbank or in the middle of the river (Fig. 1). These transects stretched from reference point post 26–45 m upstream. Along the left riverbank, samples were collected every 5 m between 20 and 40 m upstream of post 26. The piston samples were pushed out in a sampling gutter and subsampled on site at three depths (10– 20, 60 and 100 cm depth). For analysis of CAHs, c. 20 g of sediment was directly brought into two preweighted 40 mL glass vials containing 10 g of methanol, and the vials were immediately sealed with aluminum crimp caps containing Teflon-lined butyl-rubber septa. Sediment samples for DNA extraction were collected in 10-mL Falcon tubes, frozen on dry ice on site and stored at 80 °C. Samples for analysis of the organic carbon content (OCC) were collected in amber 60 mL jars and stored at 4 °C. In December 2005, sediment samples were collected at post 26 near the right riverbank, and 20 m FEMS Microbiol Ecol 87 (2014) 715–732

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Microbial community structure of CAH-polluted river sediment

Left riverbank Flow direction Zenne 15 m

Mid-river 5m

Right riverbank

Post 26

Post 25 200 m

50 m

45 m

32.5 m SB-2

20 m

0

3.5 m from Zenne

CAH-polluted groundwater SB-1 28.2 m from Zenne

B26 MW26

200 m from Zenne

Fig. 1. Schematic representation of the study site showing locations of aquifer and groundwater sampling (B26, SB-1, SB-2), of sediment and sediment pore water sampling in May 2006 (all circles) and of sediment sampling in December 2005 (filled circles), relative to reference post 26. Flow directions of the CAH plume and Zenne River are indicated.

upstream of post 26, close to post 25, near the right riverbank, near the left riverbank, and in the middle of the river (Fig. 1). After transferring the undisturbed core samples into 4.2-cm-inner-diameter polyvinylchloride tubes, they were frozen on dry ice on site. In the laboratory, the frozen cores were stored at 80 °C before dividing them into slices of c. 1 cm using an electrical saw. Slices were collected in sterile Petri dishes, kept on dry ice and stored at 80 °C. From each core, 24 slices were used for molecular and chemical analyses. Every 5 cm of the core, one slice was selected for analysis, while the upper part of each core was investigated in detail by analyzing all slices from 0 to 6–11 cm depth. Approximately 2 g of the frozen sediment slices was brought into a preweighted 10 mL glass vial containing 2.5 g of methanol for analysis of the concentration of CAHs. Sediment samples for DNA extraction (2 g) were subsequently retrieved from the frozen slice and stored at 80 °C, while the remainder of the slice was used to determine the OCC. Aquifer samples were drilled from 0 to 8 m below the ground surface (mbs) at location B26 in March 2005 and from 3.6 to 9.6 mbs at locations SB-1 and SB-2 in October 2005 (Fig. 1). Samples were collected in liners of 1 or 1.2 m length with an inner diameter of 3.5 or 5 cm, transported to the laboratory and stored at 4 °C under a FEMS Microbiol Ecol 87 (2014) 715–732

100% nitrogen atmosphere. Samples for DNA extraction (2 g) and for analysis of the OCC (10 g) were taken from the top or the bottom of the liners after removing a few cm of aquifer from the respective ends in an anaerobic glove bag flushed with nitrogen. Groundwater was sampled from monitoring wells SB-1, SB-2, and MW26, which are located near the test area at, respectively, 28.2 m, 3.5 m, and c. 200 m distance from the right riverbank (Fig. 1). Groundwater samples were collected as described in Hamonts et al. (2009) and sampled for DNA extraction in sterile 500-mL amber glass bottles by filling them from bottom to top and allowing overflow until the volume of the bottle was changed twice. Surface water samples for DNA extraction were collected in the test area in sterile 500-mL amber bottles, without leaving a headspace. In May 2006, sediment pore water was sampled near the sediment sampling locations (Fig. 1) at 20, 60, and 80–120 cm depth (Hamonts et al., 2009). Chemical analyses

Total CAH concentrations in the sediment were determined by GC-MS analysis after methanol extraction. Vials containing sediment suspended in methanol were spiked ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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with an internal standard solution to obtain 3 lg d8-toluene, d6-benzene, d4-1,2-dichloroethane, d10-ethylbenzene, and d4-1,4-dichlorobenzene per 0.5 g of methanol. After sonicating the vials for 30 min in an ultrasonic bath (Branson 5510, Branson, Danbury, CT), the methanol extract was diluted by transferring 0.5 g in a 10 mL glass vial containing 4.5 g mineral water and 100 lL concentrated H3PO4. CAH concentrations were measured by headspace-GC-MS analysis as described by Hamonts et al. (2009). Concentrations of benzene, toluene, and other volatile organic compounds were also determined by this analysis. Detection limits were typically between 8 and 20 lg kg 1 for fresh sediment samples and between 40 and 80 lg kg 1 for sediment collected from frozen slices. The total OCC of sediment and aquifer samples was calculated as the fraction of dry matter (dm) that was removed at 550 °C, after drying the sediment or aquifer overnight at 105 °C. Concentrations of CAHs and the dissolved hydrocarbons ethene, ethane, and methane in sediment pore water were determined by GC-MS or GC-FID as described by Hamonts et al. (2009). Concentrations of sulfate, nitrate, phosphate, and chloride were analyzed by ion chromatography using a Dionex DX-120 ion chromatograph equipped with a Dionex AS14A column (Dionex, Sunnyvale, CA) conform to method NBN EN ISO 10304. Detection limits were 0.25 mg L 1. DNA extraction

DNA extraction was performed within 1–2 months after sampling according to the protocol described by Hendrickx et al. (2005). DNA was extracted from 2 g of sediment or aquifer samples or from 0.45 lm filters (Millipore, Molsheim, France), obtained after filtration of 1 L of groundwater or surface water using a membrane filtration unit (Pall Life Sciences, New York). Water samples were filtered the day after sampling, and the filters stored for no longer than 2 months at 80 °C until DNA extraction. In case filters clogged due to the presence of municipal sewage in the surface water, the combined pellet obtained by centrifugation (30 min at 9500 g and 4 °C) of four 250 mL subsamples of surface water was suspended in 2 mL of surface water and used for DNA extraction. PCR amplification

The community structure of Bacteria, Dehalococcoides, and Geobacteraceae was analyzed using their respective 16S rRNA genes as markers. For analyses of the sulfatereducing bacteria and the methanogens, dsrB, coding for the dissimilatory sulfite reductase b-subunit, and mcrA, ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

K. Hamonts et al.

coding for the methyl coenzyme-M reductase, were used as markers, respectively (Luton et al., 2002; Geets et al., 2006). The Dehalococcoides community composition was further investigated by PCR detection of reductive dehalogenase genes such as tceA, vcrA, and bvcA that were previously identified in Dehalococcoides spp. (KrajmalnikBrown et al., 2004; M€ uller et al., 2004; Regeard et al., 2004; He et al., 2005; Sung et al., 2006). PCR was performed in 50 lL reactions with either 1.25 U Ex Taq polymerase (TaKaRa Bio Inc., Japan) and 5 lL of 109 Ex Taq reaction buffer (20 mM MgCl2), or 1.25 U Platinum Taq polymerase (Invitrogen, Merelbeke, Belgium), 5 lL of the corresponding 109 PCR buffer and 1.5 mM MgCl2. Both reaction mixtures contained 200 lM of each deoxynucleoside triphosphate and 1 lM of forward and reverse primers. Sequences of the primers are listed in Supporting Information Table S1, with indication of the applied Taq DNA polymerase. Direct PCRs were performed on 10-fold dilutions of extracted DNA, whereas 1 lL DNA generated in the first PCR round was used as template for the second PCR in (semi)nested PCRs. Nested PCR approaches were performed as described for the detection of the chloroethene dehalogenase genes tceA (Regeard et al., 2004) and bvcA (Krajmalnik-Brown et al., 2004). Seminested PCR was performed for DGGE of methanogens and Geobacteraceae, using forward primers without GC clamp in the initial PCR, followed by a second PCR using the same primer set with a GC clamp attached to the 5′ end of the forward primers (Table S1). PCR temperature profiles were adopted from others (references see Table S1), except for assays targeting methanogens and Geobacteraceae. PCR conditions for detection of the mcrA gene were simplified by exclusion of the ramp in annealing temperature in the protocol described by Luton et al. (2002). For detection of Geobacteraceae, the following PCR conditions were used: an initial denaturation of 5 min at 94 °C, followed by 35 cycles of 1 min at 94 °C, 1 min at 55 °C and 1 min at 72 °C, and a final extension at 72 °C for 7 min. For detection of tceA (Regeard et al., 2004), the reported annealing temperature was adjusted to 56 °C. For Dehalococcoides-specific DGGE, DNA amplicons obtained with the Dehalococcoides-specific primers DeF and DeR (Cupples et al., 2003) were subjected to a nested PCR using the primers GC968F and Dhc1350R (Table S1). For cloning of the 16S rRNA gene of Dehalococcoides, amplicons obtained after PCR using the primers DHC1F and DeR were subjected to a nested PCR using the primer set DeF and Dhc1350R (Table S1). PCR conditions for the primer sets GC-968F/ Dhc1350R, DHC1F/DeR, and DeF/Dhc1350R consisted of an initial denaturation of 5 min at 95 °C, followed by 35 cycles of 30 s at 95 °C, 40 s at 56 °C, and 1 min at 72 °C, and a final extension at 72 °C for 5 min. PCRs FEMS Microbiol Ecol 87 (2014) 715–732

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Microbial community structure of CAH-polluted river sediment

were performed in a T3 Thermocycler (Biometra, Goettingen, Germany), and amplification products were analyzed on 2% (wt/vol) agarose gels. Denaturing gradient gel electrophoresis (DGGE)

In all cases, amplicons were separated by DGGE as previously described (Muyzer et al., 1993). An 8% (wt/vol) polyacrylamide gel with a denaturing gradient of 35–65% (where 100% denaturant contains 7 M urea and 40% formamide) was loaded with 15 lL of the PCR products. Electrophoresis was performed at a constant voltage of 120 V for 15 h in 19 TAE buffer [40 mM Tris-Acetate (pH 7.4), 20 mM sodium acetate, 1 mM EDTA] at 60 °C on an INGENYphorU-2DGGE apparatus (INGENY International BV, Goes, the Netherlands). The gels were stained with 19 SYBR gold nucleic acid gel stain (Molecular Probes Europe BV, Leiden, The Netherlands) and then photographed. Gel images were analyzed with BIONUMERICS software version 2.50 (Applied Maths, Kortrijk, Belgium). All band patterns were normalized to positional markers in each gel, thereby eliminating variation between individual gels. Shannon–Weaver’s diversity indices H’ were calculated from the DGGE profiles to evaluate the diversity within the different investigated microbial communities, as described by Koizumi et al. (2003a). Multivariate statistical analysis

The DGGE data were analyzed using PRIMER-E Ltd software version 6 (Plymouth, UK). Resemblance matrices for community profiles were constructed using species presence/absence data extracted from DGGE profiles, by calculating similarities between each pair of samples using the Bray–Curtis coefficient (Clarke & Warwick, 2001). Analysis of similarities (ANOSIM) (Clarke, 1993) was performed to test for significant differences in the sediment community profiles between riverbed positions where different attenuation processes occurred, as determined by Hamonts et al. (2009). Permutation-based multivariate analysis of variance (PERMANOVA) was used to test for statistical differences of the effects of the location in the riverbed (transect and distance from post 26) and depth in the sediment on the microbial community structure (Anderson, 2001), with 999 permutations of the data used to test for the level of significance. Distance-based linear models were constructed to test which environmental variables significantly explained the observed variation in the microbial community structure using the DISTLM procedure (McArdle & Anderson, 2001). Following variables were tested: depth in the riverbed, texture of the FEMS Microbiol Ecol 87 (2014) 715–732

sediment, OCC of the sediment, concentration of CAHs, and toluene extracted from the sediment, pH, T, and conductivity of the sediment pore water and pore water concentrations of CAHs, benzene, toluene, ethene, ethane, nitrate, sulfate, methane, phosphate, and chloride. Data of quantitative variables, except for pH values, were transformed using y’ = ln (y + 1) before analysis. The significance of the variables was determined by 9999 permutations at P < 0.05. Variables that contributed significantly to the variation were assigned to groups as reported in sections Community structure analysis of the Zenne River sediments and Sediment depth profiles, and variation partitioning was subsequently carried out to estimate the pure vs. combined effects of the explanatory factors on the microbial community structure, as described by Anderson & Gribble (1998). The significance of each pure effect was tested by 9999 random permutations. For significant PERMANOVA results, canonical analysis of principle coordinates (CAP) (Anderson & Willis, 2003) was used to visualize the differences in the community structures and their relationships to the predictor variables identified using DISTLM. Cloning and sequence analysis

Selected PCR products were cloned using the TOPO TA Cloning Kit (Invitrogen) according to the manufacturer’s instructions. PCR products used for cloning were those obtained with primer sets GC-DSRp2060F/DSR4R, 561F/Geo825R, mcrAF/mcrAR, or DeF/Dhc1350R (Table S1). DGGE patterns of cloned fragments were compared with fingerprints of the communities of origin to relate cloned fragments with DGGE bands. For the Dehalococcoides-specific primer set DeF/Dhc1350R, a selection of clones was sequenced on both strands using the primers M13F and M13R. All other clones were sequenced on one strand using M13F. Sequences were screened for chimeras with the Mallard program (Ashelford et al., 2006) and the Pintail tool available at http://www.bioinformat ics-toolkit.org/Web-Pintail/. The closest sequence match was identified with a BLASTN (for 16S rRNA genes) or a BLASTX (for dsrB and mcrA genes) search of GenBank (www.ncbi.nlm.nih.gov/blast). Sequences of dsrB and mcrA fragments were translated into the correct frame using the EMBOSS TRANSEQ tool available at http://www.ebi. ac.uk/Tools/emboss/transeq/index.html. Both nucleotide and protein sequences were aligned using CLUSTALW2 (Larkin et al., 2007) and edited manually. Phylogenetic trees were constructed using the MEGA4 software available at http://www.megasoftware.net/ (Tamura et al., 2007). Sequences of the dsrB and mcrA gene fragments and of the 16S rRNA gene fragments of Dehalococcoides and Geobacteraceae generated in this study were deposited in ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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the European Nucleotide Archive under the accession numbers HF913760-69, HF913770-75, HF913730-46, and HF913747-59, respectively (http://www.ebi.ac.uk/ena/data/ view/).

Results Community structure analysis of the Zenne River sediments

DGGE analysis was performed to assess and compare the microbial community structure of Bacteria, Dehalococcoides, Geobacteraceae, sulfate-reducing bacteria, and methanogenic archaea in Zenne River sediments collected at 25 positions and three depths within the test area. For all studied communities, highly similar DGGE profiles were detected at 10 cm depth in the riverbed across the test area (Supporting Information, Fig. S1 for Bacteria and sulfate-reducing bacteria). In contrast, a more varying microbial community structure was observed at 60 and 100 cm depth, although a number of bands appeared to be common at all investigated locations and depths. The DGGE profiles of Bacteria, sulfate-reducing bacteria, and Dehalococcoides significantly changed with depth in the riverbed (Table 1; Fig. 2). Methanogens and Geobacteraceae were not included in the analysis due to their low diversity. Post hoc pairwise comparisons indicated that the community structure of Bacteria and sulfate-reducing bacteria differed between all three studied depths, whereas the Dehalococcoides community at 60 cm depth was not significantly different from the community at 100 cm depth (data not shown). The community composition of

Bacteria and sulfate-reducing bacteria of sediment collected along the right river transect significantly differed from the community structure observed in the middle of the river (Table 1; post hoc pairwise comparisons not shown). However, as indicated by the square root of the components of variation, the depth in the riverbed was the strongest discriminator of the community composition for all studied populations (Table 1). Environmental variables that significantly differed with depth in the riverbed included pore water concentrations of CAHs (VC and 1,1-DCA) and methane, the pore water temperature, toluene extracted from sediment, and OCC of the sediment (Supporting information Table S2). Except for 1,1DCA, each of these variables alone explained a significant proportion of the observed variation in the DGGE profiles of at least one of the studied populations (Table 2; Fig. 2). Both the OCC of the sediment and the presence of slick explained significant portions of the variation in all tested population structures, ranging from 5% to 10% for OCC and from 7% to 17% for slick (Table 2; Fig. 2). The concentration of VC extracted from the sediment explained a significant fraction of around 6% of the variance in both the community composition of Dehalococcoides and the sulfate reducers (Table 2). Other variables that explained significant portions of the Dehalococcoides community structure (Table 2), but did not significantly differ with depth in the riverbed (Table S2), were conductivity and chloride measured in the sediment pore water. Partitioning of the variation into the relative effects of OCC of the sediment, the sediment texture and other variables that significantly contributed to the variation in each studied population (see Table 2 and Table S3),

Table 1. Summary of PERMANOVA testing of the effects of sample location (transect, distance from post 26) and depth in the riverbed on the DGGE profiles of Bacteria, sulfate-reducing bacteria, and Dehalococcoides obtained for Zenne River sediment samples from 25 locations and three depths in the test area. P-values indicating significant effects are shown in boldface (P ≤ 0.05)

Sulfate-reducing bacteria

Bacteria

Transect Distance from post 26 Depth Transect 9 Distance from post 26 Transect 9 Depth Distance from post 26 9 Depth Residual

‡

Bacteria, sulfatereducing bacteria, and Dehalococcoides*

Dehalococcoides

Pperm†

√CV

Pperm

√CV

Pperm

Pperm

√CV

0.003 0.320 0.001 0.314

9 4 23 6

0.002 0.274 0.001 0.094

8 4 25 8

0.995 0.078 0.004 0.935

8 9 14 12

0.018 0.514 0.001 0.322

9 2 19 6

0.109 0.327

7 6

0.001 0.078

12 9

0.999 0.482

12 2

0.269 0.137

6 10

34

26

√CV

37

29

*Analysis was performed using concatenated DGGE profiles of the different groups. Probability of the effect occurring by chance. ‡ Square root of the components of variation, a measure of the size of the effect in units of the community dissimilarities. Negative values indicate effectively zero components. †

ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

FEMS Microbiol Ecol 87 (2014) 715–732

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0.2

detected in the community composition of Dehalococcoides, nor the other tested populations (Table S4).

0.1

Sediment depth profiles

CAP2

0

Depth (cm) 10 60 100

T OCCSlick

–0.1

Methane Toluene

–0.2

Fine to medium sand

–0.3 –0.4 –0.3

–0.2

–0.1

0

0.1

0.2

CAP1 Fig. 2. CAP analysis of variation in concatenated DGGE profiles of Bacteria, sulfate-reducing bacteria, and Dehalococcoides obtained for sediment samples collected at 25 locations and three depths (10, 60, and 100 cm) in the riverbed. Vectors represent correlations of environmental variables that contributed significantly to the observed variation in the community structure. T, the pore water temperature, and OCC, organic carbon content of the sediment.

indicated that the tested variables were not independent (Fig. 3). Although OCC explained a significant fraction of the observed variance when all other variables were ignored (Table 2), the isolated effect of OCC on the community composition was not significant (Fig. 3; Table S3). A high OCC of on average 1.72  0.76% dm was measured in the sediment at 10 cm depth, in contrast to 0.88  0.81% dm at 60 cm and 0.84  0.40% dm at 100 cm depth (n = 25). A similar trend with depth was observed for sediment structure, as the top 10 cm sediment consisted mostly of slick (20 of the 25 samples), in contrast to the sediment at 60 and 100 cm depth (only 1 of the 50 samples). Hence, OCC and texture are dependent variables. In contrast to the OCC, however, the isolated effect of the sediment texture was significant and explained the largest fraction (up to 14%) of the observed variation (Fig. 3). It should be noted that 64–72% of the variation in the studied community structures remained unexplained by the model (Fig. 3). To assess whether variations in the community structures of the target microbial groups in the sediments could explain differences in CAH-respiring activity, we tested for differences in the community composition of sediment collected at positions where either no attenuation, microbial reductive dechlorination, dilution of the CAHs via surface water mixing or dilution via mixing with unpolluted groundwater occurred, as determined in Hamonts et al. (2009). No significant differences were FEMS Microbiol Ecol 87 (2014) 715–732

Four sediment cores were studied in detail for depthrelated changes in the community composition and for the parameters OCC and concentration of CAHs. Cores of 68–83 cm length were collected near the right riverbank around post 26 (Post 26 Right) and near the right riverbank, mid-river, and the left riverbank 20 m upstream of post 26, close to post 25 (Post 25 Right, Middle, Left; Fig. 1). At post 26, low concentrations of VC and 1,1-dichloroethane (1,1-DCA) discharged into the riverbed, whereas much higher concentrations of VC and 1,1-DCA infiltrated the sediment around post 25 (Hamonts et al., 2009). The top 4–30 cm of the sediment layer in the four cores was black and consisted of slick or fine to coarse-grained sand, whereas the sediment underneath this black layer (up to 68–83 cm) consisted of gray sand. The DGGE profiles of Bacteria, Geobacteraceae, sulfatereducing bacteria, and methanogens all showed a major shift in the profile between the black and gray sediment. As shown in Fig. S2 for the core sampled near the right riverbank at post 25, the patterns retrieved from the black sediment clustered together and were separated from those of the gray sediment with only a few exceptions. In the Dehalococcoides DGGE patterns, a single dominant band was present throughout the black and gray sediment slices, except for the pattern at 53 cm depth where two additional bands were present and at 39 and 48 cm depth, where the dominant band was absent and other bands appeared in the gel (Fig. S2e). The shift in the microbial community structure between the black and gray sediment correlated with the OCC of the sediment in all four investigated cores (Fig. S3). Black sediment slices had an average OCC of 2.72  1.70% dm (n = 43), significantly higher than the OCC of 0.67  0.39% dm measured for gray sediment slices (n = 53; P < 0.001). The reduction in OCC was associated with the shift from black to gray sediment, independent of the depth in the riverbed at which this change occurred (Fig. S3). For the two cores where CAH concentrations were measured above detection limit (Post 25 Right, Post 25 Middle), the variation in the DGGE profiles was partitioned into the relative effects of the OCC, CAH content, and depth in the riverbed (Fig. 4, Table S5). The pure effects of OCC and CAH content were significant for all tested populations except for Dehalococcoides (Fig. 4, Table S5), due to the low diversity of bands on the Dehalococcoides DGGE profiles (Fig. S2e for Post 25 Right). The OCC had the highest impact on the microbial ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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Table 2. Results of distLM analysis for individual environmental variables to determine their influence on the DGGE patterns of Bacteria, Dehalococcoides, and sulfate-reducing bacteria obtained for Zenne River sediment samples from 25 locations and three depths in the test area. The percentage of variation in the target population structures that was explained by each environmental variable alone, ignoring all other variables, is reported

Environmental variables OCC‡ Volatile organic carbons§ VC cis-DCE 1,1-DCA CA Benzene Toluene VC sediment cis-DCE sediment 1,1-DCA sediment Toluene sediment Redox indicators Nitrate Sulfate Methane Other T Conductivity pH Ethene Ethane Chloride Phosphate Texture Slick Fine sand Fine to medium sand Medium sand Medium to coarse sand Clay-loam

Bacteria 6.43***

Sulfate-reducing bacteria

Dehalococcoides

Bacteria, sulfate-reducing bacteria, and Dehalococcoides†

10.33***

4.60*

6.55***

1.84 1.15 3.19 1.84 1.14 3.81* 2.57 1.72 1.22 4.36*

1.09 1.65 1.39 1.87 0.44 2.23 5.62** 1.56 1.16 4.91*

2.32 1.88 0.20 2.12 0.31 1.60 6.05* 1.42 1.49 2.85

1.72 1.72 2.82 1.68 0.65 5.28** 2.22 1.54 1.21 3.90*

2.40 1.98 3.63*

2.22 1.28 1.61

0.63 0.05 0.44

1.59 2.04 4.16*

2.89 1.79 2.45 2.82 1.70 1.02 2.32

9.79*** 2.22 2.53 2.34 1.51 1.38 0.80

2.79 6.78* 0.86 3.32 1.30 5.54* 1.26

5.13** 3.31* 1.94 2.62 2.20 1.89 1.39

16.89*** 1.65 7.73** 1.41 3.85 1.68

7.19** 2.24 4.15 2.04 4.90 6.26

10.30*** 1.68 5.30** 1.80 2.60 2.44

11.39*** 0.64 2.48 3.10 2.88 2.97

Statistical significance is indicated by ***(P ≤ 0.001), **(P ≤ 0.01), and *(P ≤ 0.05), as determined by 9999 permutations † Analysis was performed using concatenated DGGE profiles of the different groups. ‡ Organic carbon content of the sediment. § Unless noted, variables were measured in pore water samples.

structure of the methanogens, accounting for 14% of the total variation in the DGGE profiles (Fig. 4, Table S5). For the Bacteria, sulfate-reducing bacteria, and Geobacteraceae, the OCC explained 8%, 3%, and 2% of the total variation in the DGGE profiles, respectively. The CAH content explained a larger fraction of the variation, ranging from 15% for the Geobacteraceae to 22% for the methanogens, 30% for the sulfate reducers, and 35% for the Bacteria. In addition, depth in the riverbed significantly explained another 4% of the variation for Bacteria and methanogens, but not for the other microbial groups. Together, the OCC, CAH content, and depth in the riverbed explained 18–69% of the total variation in the microbial DGGE profiles (Fig. S4, Table S5). ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

Diversity of the sediment microbial community

Shannon–Weaver indices of diversity (H’), based on the number and relative intensity of bands in individual lanes, were calculated from the DGGE profiles retrieved from the 75 sediment samples collected in May 2006 and the 96 sediment slices from the 4 cores collected in December 2005. The Shannon–Weaver indices varied throughout the horizontal and vertical DGGE profiles. The H’ for Bacteria, Dehalococcoides and Geobacteraceae ranged from 2.00 to 3.42, from 0 to 1.60 and from 0.68 to 2.52, respectively (Table 3). The H’ for sulfate-reducing bacteria and for methanogens ranged from 2.48 to 3.55 and from 0.57 to 2.60, respectively. In vertical DGGE FEMS Microbiol Ecol 87 (2014) 715–732

723

Microbial community structure of CAH-polluted river sediment

Bacteria

(a)

(b)

OCC

VOC + others

1.28ns

OCC

VOC + others

6.60ns

0.19

Sulfate-reducing bacteria

0.90ns

9.09ns

0.33

4.18

8.43

0.78

1.16

0.66

13.92

3.60

13.05

71.89% unknown

63.93% unknown

Texture (c)

Texture (d)

Dehalococcoides

OCC

VOC + others

1.02ns

6.77ns

0

Bacteria, sulfate-reducing bacteria and Dehalococcoides

OCC

VOC + others

0.59ns

0.19

0.47 3.18

12.48

4.87 4.89

0.90

13.79

0.11

13.05

69.95% unknown

Texture

67.80% unknown

Texture

Fig. 3. Venn diagrams showing the partitioning of variation observed in DGGE profiles of (a) Bacteria, (b) sulfate-reducing bacteria, (c) Dehalococcoides, and (d) concatenated profiles of these populations, obtained for sediment samples collected at 25 locations and three depths in the riverbed, into the relative effects of the organic carbon content (OCC), texture, and other environmental variables that contributed significantly. Numbers represent the percentage of variation explained by each parameter; ns indicates that the pure effect was not significant (P > 0.05).

profiles of the sediment slices, H’ decreased with depth in some cores but no general pattern was observed for any of the investigated populations (data not shown). The H’ significantly differed with sediment texture (P = 0.0251) for the sulfate-reducing bacteria, but not for the other tested populations (P > 0.05). Sequence analysis of dsrB, mcrA and Geobacteraceae 16S rRNA gene fragments

Fragments of the dsrB gene of sulfate-reducing bacteria, the mcrA gene of methanogens and the 16S rRNA gene of Geobacteraceae, generated from sediment samples for FEMS Microbiol Ecol 87 (2014) 715–732

DGGE, were cloned and sequenced to obtain more information on the genotypes of the different groups in the samples. The obtained dsrB and mcrA sequences were translated and phylogenetic trees were constructed based on these partial protein sequences (Figs S4 and S5). DsrB protein sequences obtained from the CAH-polluted Zenne River sediments had an amino acid identity of 75– 99% with DsrB proteins from reported cultivated isolates and 81–99% amino acid identity with DsrB protein sequences recovered from estuarine sediment, marine sediment, rice field soil, wastewater or leachate-polluted groundwater. The Zenne DsrB protein sequences clustered within four different families associated with ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

724

K. Hamonts et al.

(a)

Bacteria

(b)

OCC

CAH 7.73

1.16

Sulfate-reducing bacteria

OCC

34.78

CAH 3.43

0.85

30.22

2.46ns

1.76 0.46

2.65ns

0.22

3.07

2.16ns

4.39 49.51% unknown

55.16% unknown

Depth (c)

Depth

Methanogens

OCC

(d)

CAH 13.66

1.93

Geobacteraceae

OCC

22.12

CAH 2.36

0.22

14.25 8.49

14.49

0 5.74ns

4.75

1.42

4.32ns

3.79

57.16% unknown

31.02% unknown

Depth

Depth (f)

(e)

Dehalococcoides

OCC

CAH 9.18ns

6.13ns

12.75 ns

Bacteria, sulfate-reducing bacteria, methanogens, Geobacteraceae and Dehalococcoides

OCC

CAH 5.51

0.57 2.82

0 0

32.08

2.02

0

1.85

3.95

0

51.21% unknown

71.94% unknown

Depth

ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

Depth

FEMS Microbiol Ecol 87 (2014) 715–732

725

Microbial community structure of CAH-polluted river sediment

Fig. 4. Venn diagrams showing the partitioning of variation observed in DGGE profiles of (a) Bacteria, (b) sulfate-reducing bacteria, (c) methanogens, (d) Geobacteraceae, (e) Dehalococcoides, and (d) concatenated profiles of these populations, obtained for slices of two sediment cores, into the relative effects of the organic carbon content (OCC), CAH content and depth in the riverbed. Numbers represent the percentage of variation explained by each parameter; ns indicates that the pure effect was not significant (P > 0.05). For the CAH content, following variables were retained for the model: VC, 1,1-DCA, and CAHtotal for Bacteria, sulfate-reducing bacteria, methanogens, and all concatenated profiles; VC and CAHtotal for Dehalococcoides; 1,1-DCA for Geobacteraceae.

Table 3. Mean Shannon–Weaver diversity indices calculated from the indicated DGGE band patterns of Zenne River sediment samples obtained for five different communities Target group

Mean Shannon–Weaver diversity indices*

Bacteria Dehalococcoides Geobacteraceae Sulfate-reducing bacteria Methanogens

2.95 0.27 1.68 3.11 1.47

    

0.25 0.47 0.43 0.26 0.52

(n (n (n (n (n

= = = = =

169) 98) 162) 160) 165)

*Mean values  standard deviations are indicated, with the number of indices between parentheses. As a PCR signal was not always obtained and DGGE patterns with a poor resolution on the gel images were excluded from evaluation, the numbers differ between target groups.

Desulfobacteraceae, Desulfovibrionales, Desulfobulbaceae, and Syntrophobacteraceae (P
erez-Jim
enez & Kerkhof, 2005; Miletto et al., 2007) (Fig. S4). In addition, two Zenne sediment clones (DSRP25L3_11 and DSRP25L3_12) grouped into a distinct branch along with clones retrieved from leachate-polluted groundwater and estuary sediments. A third sediment clone (DSRP25L3_14) that branched with a clone retrieved from marine sediment, clustered closely to but not within the Desulfobulbaceae and Syntrophobacteraceae (Fig. S4). For the methanogens, McrA protein sequences retrieved from Zenne River sediment clustered within McrA protein sequences associated with the Methanomicrobiales and the Methanobacteriales (Fig. S5). The sequences were most closely related to uncultured clones (96–98% amino acid identity) and McrA of the isolates Methanospirillum hungatei JF-1 (87% amino acid identity) and Methanobacterium formicicum (92% amino acid identity). Geobacteraceae 16S rRNA gene sequences retrieved from Zenne River sediment were most closely related to the 16S rRNA gene of Geobacter hephaestius, Geobacter daltonii FRC-32 strain FRC-32 and Geobacter sp. strain CdA-2 (Fig. S6). Phylogenetic analysis of Dehalococcoides 16S rRNA genes

In the Dehalococcoides DGGE profiles of the Zenne River sediment samples, 1–5 different bands were observed (Fig. S7). One dominant band was common in almost all sediment samples. The 16S rRNA gene fragment generated for Dehalococcoides mccartyi strain CBDB1 migrated FEMS Microbiol Ecol 87 (2014) 715–732

at the same height as this dominant band (Fig. S7). As the sequence of the region of the Dehalococcoides 16S rRNA gene that was PCR amplified and analyzed on DGGE is identical in all strains belonging to the Pinellas subgroup (Hendrickson et al., 2002), this dominant band was referred to as the ‘Pinellas band’. 16S rRNA fragments of the reported Dehalococcoides mccartyi strains CBDB1, FL2, BAV1, and GT (Adrian et al., 2000; He et al., 2003a, 2005; Sung et al., 2006), belonging to the Pinellas subgroup (Hendrickson et al., 2002), would all migrate to this position in the gel. In contrast, the fragment generated for D. mccartyi strain 195 (Maym
o-Gatell et al., 1997), representing the Cornell subgroup (Hendrickson et al., 2002), migrated to a different position on the gel compared with the Pinellas band (Fig. S7). Taking the high similarity of 16S rRNA gene sequences of the currently reported Dehalococcoides spp. into account, the rather high diversity of bands in Fig. S7 was surprising. Therefore, sequences of near-full-length Dehalococcoides 16S rRNA fragments (E. coli positions 49–1350), retrieved from Zenne River sediment, were determined. An alignment of those sequences (1212–1214 bp) indicated that the sequences were unique, that is, different from each other and from 16S rRNA genes of reported Dehalococcoides strains. The Zenne River sediment sequences were closely related to sequences of Dehalococcoides mccartyi isolates belonging to the Pinellas subgroup (Fig. S8), with similarities ranging from 96.6% (41 bp difference) to 99.9% (1 bp difference). According to the defined base substitutions in variable regions 2 and 6 of the 16S rRNA gene (Hendrickson et al., 2002), these clones belonged to the Pinellas subgroup. Detection of Dehalococcoides reductive dehalogenase genes

The TCE reductive dehalogenase gene tceA of D. mccartyi strain 195 or FL2 (Regeard et al., 2004; He et al., 2005) and the VC reductive dehalogenase genes bvcA of strain BAV1 (Krajmalnik-Brown et al., 2004) and vcrA of strain VS or GT (M€ uller et al., 2004; Sung et al., 2006) were detected in sediment samples collected at 25 locations and three depths in the Zenne riverbed in May 2006 (Fig. 5). At many locations, the tceA, bvcA and vcrA genes were all detected in the same sediment sample. Despite detection of the ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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K. Hamonts et al.

(a) 16S rRNA gene Dehalococcoides Left ri verba nk Mid-r iver Right riverb ank

Flow

directi

(b) tceA gene

on Ze

nne Depth in sediment:

Depth in sediment:

10 cm

60 cm

10 cm

VC log (μg kg–1)

100 cm

60 cm

2.7

100 cm

2.4 2.1

Post 26

(c) vcrA gene

1.8

(d) bvcA gene

1.5 Depth in sediment: 10 cm

1.2 0.9

Depth in sediment: 10 cm

0.6 60 cm

60 cm

0.3 0 100 cm

100 cm

Fig. 5. Schematic representation of the results of PCR detection of the 16S rRNA gene of Dehalococcoides (a) and the CAH reductive dehalogenase genes tceA (b), vcrA (c), and bvcA (d) in sediment samples collected at 25 locations and three depths in the Zenne riverbed in May 2006. Dots represent the sampling locations in the riverbed; colored dots indicate detection of the corresponding gene, whereas white dots indicate that no PCR product was obtained. The plots show the interpolated VC concentrations extracted from the sediment samples. Interpolation was performed using log transformation kriging analysis.

Dehalococcoides 16S rRNA gene in all investigated sediment samples, the reductive dehalogenase genes were not detected in all samples. Moreover, their detection did not correlate with the presence or absence of detectable VC (Fig. 5) or cis-DCE concentrations (data not shown), nor with the occurrence of reductive dechlorination in the riverbed, as determined by Hamonts et al. (2009).

Discussion Microbial community structure of the Zenne River sediments

The community structure of Bacteria, Dehalococcoides, Geobacteraceae, sulfate-reducing bacteria, and methanogens changed with depth in the eutrophic CAH-polluted Zenne River sediments. Such depth-related change has been reported previously for marine sediments (Urukawa et al., 2000; Bowman et al., 2003; Sørensen et al., 2007; Edlund et al., 2008) and freshwater river or lake sediments (Koizumi et al., 2003a; Beier et al., 2008; Zhao et al., 2008). In marine sediments, the shift in community composition with depth was attributed to sediment burial and ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

exhaustion of labile nutrients and useable electron sinks (Bowman et al., 2003). In particular, changes were attributed to variations with depth in redox potential (Urukawa et al., 2000; Sørensen et al., 2007; Edlund et al., 2008), sulfide concentrations (Urukawa et al., 2000; Sørensen et al., 2007), organic carbon (Edlund et al., 2008), and nitrogen content (Edlund et al., 2008). In river sediments, surface influences like the penetration of stream water, exposure to light and the deposition of particles available as substrate, apparently resulted in a different microbial structure in the top layer of the riverbed compared with the deeper layers (Beier et al., 2008). In our study, the decrease in organic matter with depth in the Zenne River sediments was most strongly correlated with the shift in the microbial community structure from a homogeneous community in the black organic-rich layer at the top of the riverbed to a more varying community in the gray sediment underneath this layer. For decades, the Zenne River received municipal sewage at various locations in the vicinity of our test area. Due to a continuous deposition of organic matter from the eutrophic Zenne surface water, an organic-rich sediment layer was created in the top of the riverbed. This eutrophic sediment, the thickness of which varies from 4 to 30 cm, feeds a FEMS Microbiol Ecol 87 (2014) 715–732

Microbial community structure of CAH-polluted river sediment

highly diverse and uniform microbial community throughout the investigated 675 m2 stretch of the Zenne River. Overall, little is known about the effect of CAH concentrations and other physicochemical parameters on the microbial structure in river sediments impacted by discharging CAH-polluted groundwater. However, a few studies have investigated the determinants of the microbial community structure in CAH-polluted aquifers. Imfeld et al. (2008) showed that the CAH concentrations explained 56.3% of the variance in the microbial community structure in CAH-polluted groundwater of the Bitterfeld aquifer. Rossi et al. (2012) found that the CAH concentrations measured in groundwater from five geographically distant aquifers in Europe explained 28.9% of the variance in the bacterial community composition when all aquifers were considered together, but a large proportion of this variance was confounded with the distance between the aquifers and the environmental conditions. Removing the effect of these covariables, CAH concentrations still explained 5.9% of the observed variance (Rossi et al., 2012). Apart from the CAHs, concentrations of other terminal electron acceptors such as oxygen, nitrate, sulfate, and iron(II) were found to be important factors in shaping the bacterial community structure in CAHpolluted aquifers (Rossi et al., 2012; Shani et al., 2013). Our study showed that the microbial community structure of CAH-polluted river sediments was affected by the depth in the riverbed, the OCC, CAH content, texture of the sediment, the local pore water temperature and conductivity, and concentrations of toluene and methane (Table 2, Figs 3 and 4). The percentage of variation in the microbial structure that was explained by these variables depended on the specific microbial group that was targeted and on the spatial scale that was studied. When analyzed on a cm-scale in vertical profiles of sediment cores, the CAH content of the sediment alone explained up to 35% of the variation in the community profiles (Fig. 4). However, no significant effect was obtained for sediment samples collected every 5 m in an extensive horizontal sampling grid (Fig. 3). This could be due to the sampling method, as the sediment subsamples used for DNA vs. methanol extraction obtained from the sediment slices were only physically separated by c. 1 cm, whereas subsamples collected from sediment sampled from the extensive sampling grid in the test area could be separated by up to 5 cm. Fine-scale variations in the CAH concentrations could thus have caused this bias. Another possible explanation for this spatial discrepancy is the fact that variables such as the sediment texture become more important in structuring the communities at a larger scale and thereby cause other variables such as the CAH and OCC content to concomitantly lose their predominant role in shaping the microbial community structure (Fig. 3). Similarly, Rossi et al. (2012) FEMS Microbiol Ecol 87 (2014) 715–732

727

observed that in CAH-polluted aquifers, key redox reactions shaped the microbial community structure at medium scale (50 km), while CAHs shaped the structure at a large scale (1000 km). In the Zenne River sediments, redox indicators (nitrate, sulfate, methane) were less important in shaping the microbial community structure than the OCC and CAH content of the sediment and the sediment texture (Table 2). Again, a spatial discrepancy caused by the sampling method could be responsible, as these variables were measured in pore water samples collected from a larger volume in the riverbed than the sediment used for DNA extraction, and hence, small-scale variations in these variables could have been missed. Even at the cm-scale, where a larger fraction of the variance in the microbial structure was explained by measuring fewer variables (Fig. 4 vs. Fig. 3), a large percentage of the variance (31–72%) remained unexplained. This is in accordance to previous studies in CAH-polluted aquifers (Imfeld et al., 2008; Rossi et al., 2012) and could be partly due to the high heterogeneity in the complex river sediment and aquifer systems. Variables that were not measured in this study but could explain additional variance in the microbial community structure include pore water concentrations of iron, magnesium, calcium, and other cations, as well as dissolved organic carbon. The CAH content of the sediment did not only affect the community composition of Dehalococcoides and the total bacterial community, but also explained a significant portion of the variation in the community profiles of sulfate-reducing bacteria, methanogens, and Geobacteraceae (Table 2, Fig. 4). This could indicate that the presence of CAHs results in competition between the obligate hydrogenotrophic Dehalococcoides and the other targeted communities for electron donors, inherent toxicity of the CAHs toward these communities, or the formation of cooperative microbial consortia structured around Dehalococcoides by selecting specific strains of sulfate reducers, methanogens, or Geobacteraceae to, for example, provide cobamide for reductive dechlorination and growth (e.g. Yan et al., 2012). As no correlation was found between the community structures of Bacteria, sulfate-reducing bacteria, and Dehalococcoides, and the occurrence of reductive dechlorination in the riverbed, we did not detect any changes in the community profiles that could explain the lack of reductive dechlorination activity observed at certain locations in the Zenne sediments. Diversity of the sediment microbial community

In contrast to the structure of the sediment microbial community, no depth-related pattern was observed for the diversity, as indicated by Shannon–Weaver indices. ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

728

This is in contrast to other studies where the diversity of the microbial community slightly decreased with depth in lake sediments (Koizumi et al., 2003a; Zhao et al., 2008). Nevertheless, the bacterial diversity in the Zenne River sediments was similar or even higher than that found in other river or lake sediments. The number of bands per bacterial DGGE profile, on average 21  5 for the Zenne River sediment samples, is within the range of the 16–32 DGGE bands that were on average detected in hyporheic zone sediment of free-stone rivers in the western United States (Feris et al., 2003b). Furthermore, a higher bacterial diversity was detected in the Zenne River sediment compared with two lake sediments (Koizumi et al., 2003a; Zhao et al., 2008). In the Zenne riverbed, the Shannon– Weaver indices varied throughout both the vertical and horizontal sampling positions for all investigated populations. Therefore, it appears that the hyporheic community did not respond to the OCC at the level of total community diversity, but only at the level of community composition. Similarly, Feris et al. (2003a) demonstrated that the degree of heavy-metal contamination influenced the microbial structure but not the diversity in river sediments. Although DGGE is a powerful tool to monitor the structure and the diversity of microbial communities, it can underestimate the diversity of the community as only the dominant taxa (those representing more than 0.1–1% of the target organisms in terms of relative proportion) are displayed (Muyzer et al., 1993; Fromin et al., 2002). Moreover, DNA fragments from different taxa can migrate to the same position in the gel, and multiple bands can occur for one taxon (Muyzer & Smalla, 1998). In our study, however, DGGE was not used to reveal the total diversity of the investigated communities, but rather to compare the community diversity (and structure) at different locations. Furthermore, sequencing of bands confirmed the specificity of the used primers for PCR and showed that none of the bands represented nontarget fragments. Sequences corresponding to different DGGE bands represented different (sub)phyla of the sulfatereducing bacteria or methanogens, or were identified as unique sequences closely related to Dehalococcoides spp. Therefore, we suggest that valid conclusions were drawn regarding the studied populations. Dehalococcoides spp. at the Zenne site

Dehalococcoides spp. were detected in all Zenne River sediment samples. Although Dehalococcoides was represented by a single dominant Pinellas band in 65% of the sediment DGGE profiles, there appears to be an appreciable amount of minor variation within the Dehalococcoides population of the Zenne River sediments. The Dehalococcoides sediment clones revealed many closely ª 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved

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related but unique 16S rRNA gene sequences associated with the Pinellas subgroup. Unique Dehalococcoides 16S rRNA gene sequences were previously retrieved from CAH-polluted groundwater (Hendrickson et al., 2002; Bowman et al., 2006), CAH-polluted pond sediment (Hendrickson et al., 2002), or from enrichment cultures from CAH-polluted habitats (Richardson et al., 2002). Since to date, complete reductive dechlorination of PCE to nontoxic ethene is only associated with Dehalococcoides strains, many Dehalococcoides species that are not cultivated yet may thus contribute to the chloroethene degradation observed in situ. Dehalococcoides 16S rRNA gene sequences recovered from groundwater samples collected near our Zenne River study site were still related to reported Dehalococcoides isolates (85–88% sequence identity), but belonged to a distinct cluster within subphylum II of the Chloroflexi (Fig. S8). Therefore, care must be taken in using ‘Dehalococcoides-specific’ primers as Chloroflexi different from organohalide-respiring Dehalococcoides but still belonging to the subphylum Dehalococcoidetes can be amplified. These Chloroflexi 16S rRNA gene fragments were probably obtained from the groundwater because of the low number of Dehalococcoides 16S rRNA genes present in these samples (maximum 104 copies mL 1 but mostly nondetectable), compared with the Zenne sediment (103–106 copies g 1; unpublished results). Despite their sequence dissimilarity with described organohalide-respiring Dehalococcoides spp., the Chloroflexi detected in the discharging CAH-polluted groundwater could be involved in CAH degradation. Members of the Chloroflexi, different from the Dehalococcoides isolates, have been shown to be responsible for degradation of chlorinated compounds, such as PCE (Kittelmann & Friedrich, 2008a, b) and PCBs (Fagervold et al., 2005; Watts et al., 2005). Although Dehalococcoides spp. are almost 100% similar on 16S rRNA sequence level, they can have important metabolic differences. Reported isolates vary significantly in their spectrum of halogenated compounds that they can use as electron acceptors, as well as in their ability to either respire or cometabolically degrade chlorinated compounds. Strains 195, FL2, BAV1, VS, and GT can degrade cis-DCE and VC, the main CAH pollutants in the Zenne riverbed. However, strain 195 and FL2 only cometabolically reduce VC to ethene (Maym
o-Gatell et al., 2001; He et al., 2005), whereas strains BAV1, VS, and GT couple the reduction in VC to energy conservation (Cupples et al., 2003; He et al., 2003b; Sung et al., 2006). Current 16S rRNA gene-based analysis does not provide sufficient information to distinguish between the different members of the Dehalococcoides group. Analysis of their reductive dehalogenase genes, however, may provide information on their metabolic diversity (van der Zaan et al., 2010). In Dehalococcoides mccartyi strain 195 and FEMS Microbiol Ecol 87 (2014) 715–732

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FL2, the reduction in both cis-DCE and VC is mediated by the TCE reductive dehalogenase TceA (Magnuson et al., 2000; He et al., 2005). The VC reductase BvcA reduces VC to ethene in strain BAV1 (Krajmalnik-Brown et al., 2004), while the VC reductase VcrA reduces cis-DCE and VC to ethene in strain VS and GT (M€ uller et al., 2004; Sung et al., 2006). Through PCR detection of the corresponding reductive dehalogenase genes tceA, bvcA, and vcrA, the chloroethene-degrading properties of the Zenne River sediment were examined. Interestingly, at many locations, the presence of Dehalococcoides 16S rRNA genes was related to the presence of all the investigated CAH reductive dehalogenase genes, indicating that Dehalococcoides species with different metabolic cis-DCE and VC degrading properties were present in the Zenne River sediments. Particularly, the detection of bvcA and vcrA-like genes was interesting, as this implies that reduction in the discharging groundwater pollutants to ethene is coupled to energy conservation in the Zenne River sediments. However, the tceA, bvcA, and vcrA genes were all detected at locations in the riverbed where reductive dechlorination occurred (as determined by Hamonts et al., 2009), as well as at locations where no attenuation of the CAHs was observed (Fig. 5; Hamonts et al., 2009). Absence of VC- and cis-DCE-respiring activity despite the presence of Dehalococcoides spp. containing those reductive dehalogenase genes could be due to competition of Dehalococcoides with other guilds for H2, or the absence of bacteria that could provide cobamide (Yan et al., 2012). Analysis of the abundance and activity of those syntrophs or competitors in the Zenne riverbed would allow us to investigate these interactions in more detail. However, based on the community structure data obtained in this manuscript, the high reductive dechlorination activity observed in microcosms performed with Zenne sediments (Hamonts et al., 2009), and the high spatial variability in the extent of reductive dechlorination observed in situ in contrast to the microcosms (Hamonts et al., 2009), we hypothesize that not the microbial community structure of the Zenne River sediments, but the CAH discharge rate is the limiting factor for reductive dechlorination in the Zenne sediments. High spatial variations in the groundwater discharge rate, and consequently in the residence time of the CAHpolluted groundwater in the river sediments, most likely explained the observed spatial variability in the CAHrespiring activity, despite the presence of a widespread CAH dechlorination potential. Based on the results of our study, monitoring the microbial community structure in CAH-polluted sediments in combination with in situ measurements of the groundwater discharge rate or the actual reductive dechlorination activity is highly recommended for a correct evaluation of the efficiency of CAH attenuation in eutrophic river sediments. The isotope approaches FEMS Microbiol Ecol 87 (2014) 715–732

described in previous studies (Hamonts et al., 2009, 2012; Kuhn et al., 2009) were demonstrated to be a useful tool for this purpose.

Conclusions The eutrophic, hyporheic, and CAH-polluted sediments of the Zenne River were shown to be a metabolically diverse environment. A large diversity of sulfate-reducing bacteria, but also Geobacteraceae, methanogens, and Dehalococcoides species were found. The microbial community of the sediment was structured by depth in the riverbed, the OCC, CAH content, texture of the sediment, the local pore water temperature and conductivity, and concentrations of toluene and methane. The percentage of variation in the microbial structure that was explained by these variables depended on the specific microbial group that was targeted and on the spatial scale that was studied. The CAH content of the sediment affected the community composition of CAH-respiring Dehalococcoides, as well as the sulfate-reducing bacteria, methanogens, and Geobacteraceae, reflecting either the inherent toxicity of the CAHs, competition between Dehalococcoides and the targeted populations for electron donors, or the formation of cooperative microbial consortia. No relationship was found between the occurrence of reductive dechlorination in the riverbed and either the microbial community structure of the target populations in the sediment, or the presence of Dehalococcoides species capable of the degradation of cis-DCE and VC. Based on these results and results from previous studies (Hamonts et al., 2009, 2012; Kuhn et al., 2009), we therefore hypothesize that not the microbial community composition of the Zenne River sediments but the groundwater discharge rate, is the limiting factor for reductive dechlorination in the Zenne riverbed.

Acknowledgements This work was funded by EC-project no 511254 (SEDBARCAH) and by a VITO PhD grant to K.H. We thank A. Bossus, A. Denayer, T. Lowet, and M. Maesen for technical assistance.

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Supporting Information Additional Supporting Information may be found in the online version of this article: Fig. S1. PCR-DGGE community profiles of Bacteria (a) and sulfate-reducing bacteria (b) in Zenne River sediment sam-

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ples collected at different depths (10, 60 and 100 cm) and positions (dots on riverbed profile) in the test area in May 2006. Fig. S2. PCR-DGGE community profiles of Bacteria (a), Geobacteraceae (b), sulfate-reducing bacteria (c), methanogens (d) and Dehalococcoides (e) according to depth in the sediment core collected near the right riverbank at post 25 in December 2005. Fig. S3. Vertical profiles of the organic carbon content of all black and gray sediment slices from cores collected at four different locations in the test area. Fig. S4. Phylogenetic analysis of DsrB protein sequences retrieved from CAH-polluted Zenne River sediments, from reference sequences of described sulfate-reducing bacteria, and from environmental clones or species identified as the closest GenBank matches and/or closest isolates of the Zenne sequences. Fig. S5. Phylogenetic analysis of methanogen McrA protein sequences from Zenne River sediments and aquifer, from reference sequences of described methanogen species, and from environmental clones identified as the closest GenBank matches of the Zenne sequences. Fig. S6. Phylogenetic placement of cloned Geobacteraceae 16S rRNA gene sequences within the Geobacteraceae. Fig. S7. UPGMA dendrogram of DGGE profiles of the Dehalococcoides population in Zenne River sediment samples (SED) collected in May 2006 and in aquifer (AQ) and groundwater (GW) samples. Fig. S8. Phylogenetic positioning of cloned, nearly-fulllength Dehalococcoides 16S rRNA gene sequences within the phylum Chloroflexi, according to Hugenholtz and Stackebrandt (2004). Table S1. Overview of PCR primers used in this study. Table S2. Summary of ANOVA testing of the effects of sample location (transect, distance from post 26) and depth in the riverbed on the environmental variables measured in sediment or pore water samples from 25 locations and three depths in the test area. Table S3. Computational procedure for partitioning the variation in the DGGE profiles of sediment obtained from 25 locations and three depths in the riverbed into the relative effects of the organic carbon content (OCC), texture and other environmental variables that contributed significantly (VOC&others) (see Table 2) using DISTLM. Table S4. ANOSIM results for testing for differences in the DGGE profiles between riverbed positions where the different attenuation processes, as determined in Hamonts et al. (2009), occurred. Table S5. Computational procedure for partitioning the variation in the DGGE profiles of sediment slices of two cores into the relative effects of the organic carbon content (OCC), CAH content and depth in the riverbed using DISTLM.

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