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Applied and Environmental Microbiology, January 2003, p. 461-467, Vol. 69, No. 1
0099-2240/03/$08.00+0 DOI: 10.1128/AEM.69.1.461-467.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.
Nina Tuxen,2 Kaare Johnsen,1,3 Lars H. Hansen,4 Hans-Jørgen Albrechtsen,2 Poul L. Bjerg,2 and Jens Aamand1*
Department of Geochemistry, Geological Survey of Denmark and Greenland, Øster Voldgade 10, DK-1350 Copenhagen K,1 Environment & Resources DTU, Technical University of Denmark, DK-2800 Lyngby,2 Danish Veterinary Institute, DK-1790 Copenhagen V,3 Department of General Microbiology, University of Copenhagen, DK-1307 Copenhagen K, Denmark4
Received 13 May 2002/ Accepted 30 October 2002
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Microbial acclimation is commonly defined as the processes taking place during the time period between entry of a chemical and the evidence of its detectable loss (2). With acclimated microbial communities this period is typically shortened following repeated exposure to the same chemical compound (2). Microbial acclimation is generally ascribed to the enrichment of specific degraders, enzyme induction, and genetic adaptation, but the presence of toxins, predation by protozoa, and diauxie also influence the process (2).
It is only in the past few years that microbial acclimation to herbicides in subsurface aquifer environments has been investigated (1, 24, 37). Most of these studies involved laboratory incubation and primarily focused on the activity and rate of herbicide degradation. None, however, dealt with the effects of herbicides on the indigenous subsurface microbial communities. In contrast, numerous studies have examined the effects of herbicides on surface soil microbial communities, e.g., microbial biomass and the abundance of specific degraders and catabolic genes (12, 19, 22, 36). Subsurface aquifers constitute environments that are physically, chemically, and biologically very different from surface soils. They have reduced concentrations and availability of oxygen, carbon, and inorganic nutrients and a 102 to 106 times lower bacterial density (17). Results from surface soil environments, thus, cannot readily be extrapolated to subsurface aquifer conditions. Furthermore, in agricultural fields herbicides are typically applied in concentrations in the milligrams per kilogram of soil range, and surface soil microbial communities may thus be naturally exposed to high contaminant concentrations. In contrast, herbicide concentrations in groundwater are low: typical concentrations measured from landfills are 10 to 250 µg l-1 (26, 43) (equivalent to 2 to 40 µg kg-1 of sediment), whereas herbicide concentrations in groundwater polluted due to agricultural use most often are <1 µg l-1 (15). To get a realistic picture of how herbicides affect subsurface microbial communities, studies need to be carried out at low contaminant concentrations. Besides, information retrieved from such studies is necessary in order to model the fate of real-world contaminant plumes properly and for suggesting possible actions for remediation of polluted groundwater.
In a natural gradient field injection experiment, a part of the Vejen aquifer (Denmark) was continuously exposed to herbicide concentrations of <40 µg l-1 (8) (equivalent to <7 µg kg-1 of sediment). After an initial lag phase of 80 to 100 days, fast degradation of mecoprop and dichlorprop was observed and herbicide concentrations decreased to below detection levels within the first meter from the injection wells (8). This indicated that the microbial community acclimated to the contamination. This was verified by laboratory experiments showing that sediments close to the injection wells had the highest potential for phenoxy acid herbicide degradation (38). The aim of the present study was to evaluate how the in situ herbicide exposure of the Vejen aquifer affected the indigenous microbial community composition. This was done by measuring the total microbial population density and the abundance of Pseudomonas bacteria and phenoxy acid degraders. Furthermore, the frequency and the composition of the 2,4-D degradation pathway genes tfdA and tfdB (14, 33) (Fig. 1) were estimated.
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FIG. 1. Illustration of the 2,4-D degradation pathway in R. eutropha JMP134, the archetype 2,4-D degrader (13). The catabolic genes tfdA, tfdB, and tfdC were originally discovered in strain JMP134 and encode a 2,4-D/2-oxoglutarate dioxygenase, a chlorophenol hydroxylase, and a chlorocatechol 1,2-dioxygenase, respectively (14, 33). Other tfd genes are involved in the further transformation to products of the tricarboxylic acid cycle (14).
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At the time of sampling (40 days after termination of the field injection), herbicides were no longer present in the aquifer due to advective flow and degradation (8). The field exposures of mecoprop and dichlorprop were expressed as the total amount (in micrograms) of each compound that passed through each sampling point during the whole injection period (38).
Sampling.
Sediment and groundwater were sampled from the herbicide-exposed area (samples A1, A2, B1, B2, C1, and C2) and from nonexposed areas outside the contaminant plume (NX1 to -4) (Fig. 2). Herbicide-exposed aquifer sediment was collected as three intact cores at different distances from the injection wells (0.5 m for A sites, 1.5 m for B sites, and 4.5 m for C sites). Two subsamples from each core were obtained, an upper sample (number 1) and a lower sample (number 2). The distance between the upper and lower samples was approximately 0.5 m. The nonexposed samples were collected similarly at upper (NX1 and NX3) and lower (NX2 and NX4) depths. All sediment cores were collected with a stainless steel piston sampler from the saturated zone, 5 to 6.25 m below the surface, and were stored (4°C) until partitioning. Two centimeters of each core end and the outermost 0.5 cm were aseptically removed by using a paring device modified from that described by Wilson et al. (41). Individual sediment samples were homogenized thoroughly and were stored at 4°C for a maximum of 9 days until setup of laboratory experiments. Sediments for DNA analysis were stored at -20°C. Groundwater was sampled adjacent to each sediment core by using a peristaltic pump and were stored at 4°C.
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FIG. 2. Field plot of the Vejen aquifer. Plan view showing the bromide tracer plume and the location of aquifer sampling points inside (A1, A2, B1, B2, C1, and C2) and outside (NX1 to -4) the herbicide-exposed area. The groundwater velocity is approximately 0.5 m day-1 (8), and the temperature is 10°C (38). At sampling (40 days after the field injection had been terminated), bromide as well as herbicides were no longer present within the monitoring network (8).
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Microbial populations.
Microbial population sizes were estimated by analyzing three replicate subsamples of each sediment sample. One gram of sediment was diluted in 9.0 ml of sterile NaCl (0.9% [wt/vol]) and vortexed for 1 min, and 10-fold dilutions were prepared. Direct counting of bacteria was performed by using epifluorescence microscopy (Olympus BX50; Hamburg, Germany) after staining with 4',6-diamidino-2-phenylindole (DAPI) (2 µg ml-1) for 10 min in darkness. Three replicates of each subsample were enumerated. The number of culturable heterotrophs was estimated by plating on water agar (15.0 g l-1 of BiTek agar [Difco, Detroit, Mich.] in Milli-Q water). The number of culturable Pseudomonas bacteria was estimated by plating on the Pseudomonas-specific (18, 20) Gould's S1 agar medium (18). All agar media were supplemented with nystatin (50 µg ml-1) to prevent fungal growth. Each subsample was plated in triplicate and was incubated at 20°C for 21 days (water agar) and 7 days (Gould's S1) before enumeration of CFU.
The number of mecoprop, dichlorprop, and 2,4-D degraders was estimated by a most probable number (MPN) assay relying on herbicide degradation. Two milliliters of a minimal medium (10) containing 2.5-mg liter-1 concentrations of mecoprop (>99%; Riedel-de Haën, Seelze, Germany), dichlorprop (>99%; Riedel-de Haën), or 2,4-D (Merck) was added to 20-ml glass vials. The vials were then supplied with 200-µl aliquots of each sediment dilution (10-1 to 10-5), set up in five replicates, and incubated at 20°C for 3 months. Samples were filter sterilized (0.2 µm) and stored at 4°C until high-performance liquid chromatography analyses were made for remaining concentrations of herbicides as previously described (11). A similar setup was used to determine the abundance of mecoprop- and 2,4-D-mineralizing bacteria, though these vials also included 14C-labeled herbicides and a NaOH trap to collect 14CO2 as described previously (11). MPN samples were scored as positive if more than 25% of the herbicides were degraded or mineralized.
DNA extraction.
Whole-community DNA was extracted from three subsamples of each sediment sample by a combination of bead beating and freeze-thaw procedures. Bead beating was applied on 500 mg of sediment by using the FastDNA Spin Kit for Soil (BIO 101, Vista, Calif.) followed by two freeze-thaw cycles (1 h at -80°C, 30 min at 37°C). DNA was purified by the use of a GeneClean procedure (BIO 101), and the resulting samples were stored at -20°C.
Detection of Bacteria- and Pseudomonas-specific 16S rDNA.
The DNA primers PRBA338f and PRUN518r (27) were used to amplify general bacterial 16S ribosomal DNA (rDNA) segments, while PSMGf (7) and 785r (3) were used to amplify Pseudomonas-specific 16S rDNA segments. The PSMG primer has been shown to be specific to Pseudomonas (7, 21, 35). PCR mixtures (50 µl) consisted of 1x GeneAmp PCR Buffer (Perkin-Elmer, Applied Biosystem, Foster City, Calif.), 100 µM concentrations of each deoxynucleoside triphosphate (Perkin-Elmer), 0.5 µM concentrations of each primer (Gibco-BRL Custom Primers; Life Technologies, Paisley, Scotland), and 1.25 U of AmpliTaq Gold DNA polymerase (Perkin-Elmer). Five-microliter aliquots of the DNA extracts were added to the reaction mixtures, and PCR was performed with the following program: 10 min at 95°C; 35 cycles of 30 s at 95°C, 30 s at 55°C (Bacteria) or 59°C (Pseudomonas), and 1 min at 72°C; 6 min at 72°C. DNA extracts (1 µl) of P. putida KT2442 and R. eutropha JMP134 cultures were used as positive and negative controls, respectively, for Pseudomonas-specific PCR. The abundance of 16S rDNA genes in DNA samples was estimated by MPN-PCR by analyzing three replicates of each sample dilution (100 to 10-4).
Detection of tfdA, tfdB, and tfdC genes.
PCR amplification of the 2,4-D degradation genes tfdA, tfdB (39), and tfdC (9) was performed with degenerate primers. PCR of tfdA- and tfdB-homologous genes was performed by using a program slightly modified from the methods described by Vallaeys et al. (39): 6 min at 94°C; 40 cycles of 45 s at 94°C, 30 s at 59°C (tfdA) or 49°C (tfdB), and 2 min at 72°C; 6 min at 72°C. PCR of tfdC-homologous genes was performed as described by Cavalca et al. (9). For all tfd PCRs, each tube contained a total of 50 µl of reaction mixture consisting of 1x GeneAmp PCR Buffer (Perkin-Elmer), 200 µM concentrations of each deoxynucleoside triphosphate (Perkin-Elmer), 1.0 µM concentrations of each primer (DNA Technology A/S, Aarhus, Denmark), and 2.5 U of AmpliTaq Gold DNA polymerase (Perkin-Elmer). Five-microliter aliquots of the DNA extracts were added to the reaction mixtures, and PCR was performed as described above. DNA extracts (1 µl) of 2,4-D-grown R. eutropha JMP134 and fructose-grown R. eutropha AEO106 cultures were used as positive and negative controls for the presence of tfd genes. The abundance of tfd genes in DNA samples was estimated by MPN-PCR by analyzing three replicates of each sample dilution (100 to 10-2).
The populations of tfd genes obtained from individual aquifer sediments were analyzed by restriction fragment length polymorphism (RFLP) by digestion of PCR products with HaeIII and CfoI (an isoschizomer of HhaI) (Roche Molecular Biochemicals, Mannheim, Germany) followed by separation on 3.5% agarose gels. The molecular sizes of the restriction fragments were calculated by using a standard curve derived from the 100- to 600-bp bands of a 100-bp molecular size marker.
Statistical analyses.
All measurements of microbial population density and gene abundance are expressed per gram (dry weight) of sediment. The statistical significance of differences was determined by using a Student's t test at the 0.05 significance level. The level of linear correlation between data was expressed by Pearson correlation coefficients (r).
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FIG. 3. Effect of in situ herbicide exposure on microbial community composition in the Vejen aquifer. A1, A2, B1, B2, C1, and C2 indicate sediment samples collected within the herbicide-exposed area of the aquifer, while NX1 to -4 indicate samples collected outside the contaminant plume. Field samples were collected in the saturated zone at two depths (1 = upper, 2 = lower) (see also Materials and Methods). (A) Bacterial population density estimated by DAPI staining (cells per gram of sediment) and by plating on water and Gould's S1 agar (CFU per gram of sediment). Each data point represents the means ± standard deviations of nine replicate measurements. The broken line indicates the detection limit (102 CFU g-1) for culturable estimates. (B) Abundance of Bacteria- and Pseudomonas-specific 16S rDNA gene segments determined by MPN-PCR. Each data point represents the mean ± 95% confidence interval of three replicate measurements. The broken line indicates the detection limit (40 gene copies g-1, assuming that one gene copy can give rise to a PCR product). (C) Population density of phenoxy acid degraders as measured by an MPN assay relying on herbicide degradation. Each data point represents the mean ± 95% confidence interval of five replicate measurements. The broken line indicates the detection limit (2 cells g-1). (D) Abundance of tfd genes determined by MPN-PCR. Each data point represents the mean ± 95% confidence interval of three replicate measurements. The broken line indicates the detection limit (40 gene copies g-1, assuming that one gene copy can give rise to a PCR product). (E) Accumulated exposure levels of mecoprop and dichlorprop in the Vejen aquifer during the in situ natural field injection (reprinted from reference 38 with permission of the publisher).
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Phenoxy acid degraders.
Mecoprop, dichlorprop, and 2,4-D degraders were found in all herbicide-exposed sediments (Fig. 3C). In contrast, at the nonexposed sites the number of specific degraders was below the detection limit (2 cells g-1). In general, the abundance of degraders was highest in sediments A1, A2, B2, and C2 (approximately 102 to 104 degraders g-1), whereas B1 harbored the significantly lowest number of phenoxy acid degraders (approximately 100 to 102 g-1) (P < 0.05). In correspondence with this, the mass of field-injected mecoprop and dichlorprop could at most explain increases in population densities of 2 x 105 cells g-1 sediment, assuming (i) a yield coefficient of 0.3 g of carbon in produced biomass per gram of carbon of degraded herbicide (38), (ii) a weight of 1.72 x 10-13 g of carbon per cell (4), and (iii) a homogenous distribution of produced biomass in the plume (2 m3). The calculations included the first meter from the injection where the major part of the phenoxy acids was degraded (8). We found that the estimated density of mecoprop and 2,4-D degraders was identical irrespective of whether the MPN assay was performed by high-performance liquid chromatography or mineralization analyses (data not shown). The phenoxy acid degraders of the Vejen aquifer thus had the potential to degrade the herbicides completely to CO2.
The Vejen aquifer had not been exposed to 2,4-D during the field injection, but the number of 2,4-D degraders corresponded well with the number of mecoprop and dichlorprop degraders (Fig. 3C). Most bacterial phenoxy acid degraders are able to transform several phenoxy acids. For example, mixed and pure bacterial cultures enriched on mecoprop typically show a broad substrate range, including dichlorprop, 2,4-D, and MCPA [2-(4-chloro-2-methylphenoxy)acetic acid] (23, 34, 42). However, isolates enriched on 2,4-D typically do not degrade phenoxypropionic acids (13, 40).
Increases in the density of specific degraders have also been observed in situ in subsurface environments and aquifers contaminated with fuel compounds (6, 25, 32), but they have been observed at much higher contaminant concentrations than the herbicide concentrations in the Vejen aquifer. Also, several studies have demonstrated an increased population density (104 to 108 g-1) of 2,4-D degraders following exposure to 2,4-D (in milligrams per kilogram levels) in laboratory microcosms of surface soil (12, 19). However, no studies have reported on increases in the density of specific microbial degraders following in situ exposure to low herbicide concentrations (<40 µg l-1) in groundwater aquifers.
tfd genes.
PCR amplification with tfd-specific primers was only seen in the herbicide-exposed sediments (Fig. 3D). tfdA-homologous genes were found in sediments A1, B2, and C2 (Fig. 3D), and RFLP analysis revealed a difference between the populations found in C2 and those in A1 and B2 (data not shown). tfdB-homologous genes were observed in sediments A1, A2, B2, and C2 (Fig. 3D). Here, RFLP patterns of the populations in B2 were different from those in the other three sediments (data not shown). The abundance of tfd gene copies was approximately 102 to 103 g-1 of sediment (Fig. 3D), which is lower than was estimated by the culture-dependent assay for measuring phenoxy acid degraders (Fig. 3C). However, as in the case of the MPN-PCR analysis of Bacteria-specific 16S rDNA gene segments, the copy number is probably several orders of magnitude higher. Although resulting in different abundance levels, the culture-dependent and the culture-independent MPN assays generally correlated: tfdA versus mecoprop (r = 0.97), dichlorprop (r = 0.76), and 2,4-D (r = 0.91) degraders; tfdB versus mecoprop (r = 0.50), dichlorprop (r = 0.91), and 2,4-D (r = 0.70) degraders. The lack of tfd genes in sediments B1 and C1 is probably due to a lower population density of phenoxy acid degraders in these samples. It cannot be excluded, however, that the sequence of the tfd genes in these sediments differs from those of the archetype 2,4-D degrader, R. eutropha JMP134. Several bacterial 2,4-D degraders have been reported not to have any homology with the tfd genes of strain JMP134 (9, 16, 39). This could also explain the lack of tfdA genes in sediment A2. Also, presently only tfd gene sequences from culturable 2,4-D degraders are known.
Amplification with tfdC-specific primers resulted in PCR products in sediments A1, A2, and B2 (Fig. 3D), but these were significantly shorter than the product of strain JMP134 (data not shown). Further characterization of the tfdC PCR products by cloning and sequencing followed by a search for known DNA sequences at the GenBank database (http://www.ncbi.nlm.nih.gov/) revealed no homology to known tfdC genes or other DNA sequences (data not shown). At the protein level, however, significantly high homology with bacterial ferredoxin NADP reductases was found (data not shown).
The tfd genes are widespread among bacterial 2,4-D degraders (9, 16, 39), and the enrichment of these catabolic genes following application of 2,4-D to surface soil has previously been observed (19, 22). The detection of tfdA and tfdB genes in acclimated microbial communities of the Vejen aquifer suggests, however, that tfd genes are possibly also responsible for the transformation of phenoxypropionic acid compounds. This is in agreement with the recent finding of tfdA-homologous genes in three bacterial mecoprop degraders (30).
In general, the PCR analysis of tfd genes complemented the MPN measurements of culturable phenoxy acid degraders, although it failed to detect their presence in sediments B1 and C1. It may thus be concluded that the culture-dependent MPN assay is a better tool than PCR in the evaluation of in situ microbial acclimation. However, if nonculturable contaminant degraders need to be detected, the application of molecular analyses is necessary. Also, these analyses can give a more refined picture of the presence and distribution of the catabolic genes responsible for the observed in situ degradation.
The abundance of herbicide degraders as well as the presence of tfd genes correlated with the phenoxy acid field exposure (Fig. 3E). Furthermore, it has previously been shown that the sediments exposed to the highest amount of phenoxy acids also were the most acclimated to mecoprop, dichlorprop, and 2,4-D (38).
Concluding remarks.
Continuous exposure to low herbicide concentrations (< 40 µg l-1) in the Vejen aquifer changed the microbial community composition toward a higher bacterial culturability, increased abundance of Pseudomonas bacteria, and increased abundance of phenoxy acid degraders as well as tfd genes. The most pronounced effects were observed with sediments A1, A2, and B2, which had been exposed to the highest levels of phenoxy acids in the field. Data suggest that the degradation of mecoprop and dichlorprop measured in situ (8) was attributable to acclimated microbial communities (38) enriched by a heterogeneous population of phenoxy acid degraders carrying tfd genes. To our knowledge, this is the first study to show that in situ exposure of subsurface aquifers to low herbicide concentrations can markedly change the indigenous microbial community composition, resulting in acclimated microbial communities. This information contributes to our understanding of the complex processes taking place in polluted aquifers and may be used to decide what actions should be taken for the remediation of polluted groundwater environments. Whether the continuous exposure to even smaller herbicide concentrations coming from agricultural use also will result in acclimated microbial communities is still to be investigated.
We gratefully acknowledge the assistance of Spire Maja Kiersgaard and Rasmus Rune Hansen with the field sampling and of Spire Maja Kiersgaard and Pia Bach Jacobsen with the high-performance liquid chromatography analyses and measurements of DAPI-stained bacteria. We also thank Roger Garrett for access to the MegaBACE 1000 sequencer.
Present address: Department of General Microbiology, University of Copenhagen, Sølvgade 83H, DK-1307 Copenhagen K, Denmark. ![]()
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