16.Kabelitz AMB 2009 Online

Appl Microbiol Biotechnol DOI 10.1007/s00253-009-1868-0

ENVIRONMENTAL BIOTECHNOLOGY

Enhancement of the microbial community biomass and diversity during air sparging bioremediation of a soil highly contaminated with kerosene and BTEX Nadja Kabelitz & Jirina Machackova & GwenaĂŤl Imfeld & Maria Brennerova & Dietmar H. Pieper & Hermann J. Heipieper & Howard Junca

Received: 6 October 2008 / Revised: 9 January 2009 / Accepted: 10 January 2009 # Springer-Verlag 2009

Abstract In order to obtain insights in complexity shifts taking place in natural microbial communities under strong selective pressure, soils from a former air force base in the Czech Republic, highly contaminated with jet fuel and at different stages of a bioremediation air sparging treatment, were analyzed. By tracking phospholipid fatty acids and 16S rRNA genes, a detailed monitoring of the changes in Electronic supplementary material The online version of this article (doi:10.1007/s00253-009-1868-0) contains supplementary material, which is available to authorized users.

quantities and composition of the microbial communities developed at different stages of the bioventing treatment progress was performed. Depending on the length of the air sparging treatment that led to a significant reduction in the contamination level, we observed a clear shift in the soil microbial community being dominated by Pseudomonads under the harsh conditions of high aromatic contamination to a status of low aromatic concentrations, increased biomass content, and a complex composition with diverse bacterial taxonomical branches.

N. Kabelitz : H. J. Heipieper (*) Department of Bioremediation, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, 04318 Leipzig, Germany e-mail: hermann.heipieper@ufz.de

Keywords BTEX . Air sparging . Bioremediation .

Biodiversity . Microbiota

J. Machackova Earth Tech CZ s.r.o., TrojskĂĄ 92, 171 00 Prague 7, Czech Republic

The spillage of organic compounds represents one of the biggest problems of contamination in soils and groundwater, especially in eastern European countries. Military areas particularly represent a major problem due to their high pollutant concentration. Therefore, massive attempts are being carried out to remediate such sites, commonly highly polluted with alkanes and benzene, toluene, ethylbenzene, and xylene (BTEX) compounds. One of the in situ bioremediation technologies directed toward volatile hydrocarbons, mainly BTEX and gasoline relying on the aerobic stimulation of the catabolic capabilities of the autochthonous bacteria, is air sparging (Marley et al. 1992; Reddy et al. 1995; Bass et al. 2000; Hall et al. 2000; Heron et al.

2002; Yang et al. 2005). However, despite the wide application of this technique to enhance the bioremediation of nonchlorinated aromatic contamination in situ, there is still a scarcity of knowledge on the biocatalysts being

G. Imfeld Department of Isotope Biogeochemistry, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, 04318 Leipzig, Germany M. Brennerova Institute of Microbiology (IMIC), Czech Academy of Sciences, Videnska 1083, 142 20 Prague 4-Krc, Czech Republic D. H. Pieper : H. Junca Biodegradation Research Group, Helmholtz Centre for Infection Research (HZI), Inhoffenstrasse 7, 38124 Braunschweig, Germany

Introduction

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stimulated and the overall microbiological characteristics of the process. In contrast, bioremediation studies often used to be restricted to follow the disappearance of hazardous pollutants (Frostegard et al. 1993a; Frostegard et al. 1996) and still regard this system as a black box. As it is known that traditional culture-dependent methods are highly biased when analyzing environmental samples (Amann et al.

1995), culture-independent methods have been applied since two decades in order to characterize microbial community structures and their shifts under changing environmental conditions. Lipid biomarker-based techniques (Guckert et al. 1991; White 1993; Frostegard et al.

1996; White et al. 1996; Zelles 1997; MacNaughton et al.

1999) provide culture-independent insights into several important characteristics of microbial communities such as viable biomass, community structure, nutritional status, or physiological stress responses of the bacteria (Guckert et al.

1991; Heipieper et al. 1996; Pennanen et al. 1996; MacNaughton et al. 1999). However, the insight gained from lipid biomarker analysis primarily concerns nutritional or physiological status with little differentiation among bacterial species. Complementary genetic methods targeting and discerning the sequence complexity of 16S rRNA genes as a bacterial taxonomical biomarker allow the monitoring of taxonomical shifts in microbial community structure at greater details (Janssen 2006).

The present study shows the monitoring of a former air force base in the Czech Republic highly contaminated with jet fuel that is currently under bioremediation by the air sparging technique (Bass et al. 2000; Hall et al. 2000). The site is a part of the Bohemian Cretaceous Basin, the most important resource of high-quality groundwater in the Czech Republic (Masak et al. 2003; Machackova et al.

2005). The endangered aquifer is the only source of drinking water in the region and the presence of extensive contamination limits future use and revitalization of the Fig. 1 Schematic representation of the clean-up procedure carried out since 1997 at Hradčany site (AS air sparging, VE venting, GWT ground water table)

site. Several principal source zones of petroleum pollution were identified at the site which has a size of 28.3 ha— three storage areas and the jet-fuelling depot. The pollutants migrated significant down-gradient distances due to more than 20 years of massive fuel leakages in source areas and high permeability of sandstones. The amount of total petrol hydrocarbon (TPH) released into soil and groundwater until 1997 is estimated as 7,150 t. At the start of the treatment, light nonaqueous-phase liquid (LNAPL) phase was frequently present in the wells with a thickness >0.5 m. The pollution consisted mainly of jet fuel (70%) with admixture of gasoline and diesel.

Figure 1 shows a scheme of the Hradčany site and the clean-up procedure carried out since 1997, when in situ technologies have been gradually applied. LNAPL soil vapour extraction (SVE) and air sparging (AS) with application of nutrient solutions (N, P, and K) have been applied to the site (Masak et al. 2003). The first clean-up phase focused on maximum removal of LNAPL by vacuum extraction, whereas the second phase aimed at creating favorable conditions enabling aerobic degradation in the entire contaminated profile by AS and SVE. In the time frame of 1997–2006, 3,667 t of TPH were removed from the site and it was estimated that biodegradation accounts for 93%, vacuum extraction of LNAPL for 5%, and SVE/ AS for 2% of the TPH amounts eliminated (Machackova et al. 2005). In this study, the development of microbial communities in samples taken from three locations of that site representing different stages of the treatment progress was studied using microbial community analyses by phospholipid fatty acid (PLFA) profiling and 16S rRNA gene library analysis.

The results presented in this polyphasic approach show links between the depletion of contaminants (in this case, a strong selector) in natural setups due to oxygen amendment and an increase of the abundance and complexity of the

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autochthonous microbial soil community. Most probably, the observed changes in the microbial community are related and associated with the successful remediation of the soil.

Materials and methods Sampling All samples were taken from a site of high kerosene contamination, located in the Czech Republic, referred here as the Hradčany site. Since the Second World War until 1990, the site was used as a military airport, and the military activities resulted in an extensive contamination of the soil and groundwater by petroleum products (mainly by jet fuel). The upper layers of the site (0.5–3 m) are formed by quaternary river sediments (sands, gravels); the aquifer is composed of middle- to fine-grained Middle Turonian sandstone with a thickness of 67 to 75 m. The base of the aquifer consists of Lower Turonian siltstones and marlites with a thickness of about 75 m. The groundwater table depth varies from 3 to 8 m below the surface. In 1997, a full-scale clean-up was initiated (Masak et al. 2003; Machackova et al. 2005). Soil samples were taken using spiral auger drilling technique. The actual level of the groundwater table (GWT) was measured prior to drilling in the adjacent monitoring point for preliminary setting of sampling depth. The three sampling sites are located within the Hradcãny area (approximately 30 ha) with a reasonable distance of several hundred meters between each other (HRB-3: highest contamination, beginning of clean-up; HRB-2: 2.5 years of treatment; HRB-1: 5 years of treatment). Samples were taken in the depth of 0.5 m above–1 m under the actual GWT level from the 0.2-m layer of maximum contamination. All samples represent very similar soils, both from the geological (soil scientific) and hydrogeological aspects. From each of the three sites, approximately 2 kg of soil were taken. The soil of each site was then homogenized in a sterile bucket and then packed into glass jars and stored at 4°C under aerobic conditions.

Sampling for petroleum hydrocarbon quantification was performed prior to soil mixing as petroleum contamination quickly volatilizes during homogenization. Two split samples for contamination content analyses were taken from the sampled interval. Content of TPH was measured by standard gas chromatography and infrared detection (ISO TR 11046 and ISO TR11046[2]); BTEX was analyzed by standard gas chromatographic methods (EPA 601).

Fatty acid extraction and separation The extraction of total fatty acids was performed with the soil samples (five split samples of each site) that were

previously lyophilized for 24 h and was carried out using accelerated solvent extraction in an ASE 200 apparatus (Dionex), allowing an efficient extraction of lipids from soils under high temperatures and pressures. Methanol, chloroform, and buffer were applied in ratios described by Bligh and Dyer (1959).

For the extraction, from each of the samples, 30 g of soil were lyophilized and filled in an extraction cell (volume= 22 mL) together with the mix of solvents, heated for 5 min, and pressurized to 120 bar. The temperature and pressure were kept constant for 10 min (static extraction, two cycles). The total amount of solvent used for each cell was about 25 mL. The extracts were collected and separated by addition of appropriate volumes of distilled water and chloroform. The chloroform phase, which contained the total fatty acids, was isolated and dried over anhydrous sodium sulfate. The PLFA fraction was separated by liquid chromatography using silica gel columns (Bakerbond spe, Baker). By subsequent elution with chloroform, acetone, and methanol, neutral glycolipids and phospholipids were collected separately according to Zelles (1997). The methanol fraction containing the PLFA was transesterified to the respective fatty acid methyl esters (FAMEs) with trimethylchlorosilane in methanol (1:9, v/v) at 60°C for 2 h. The solvent was evaporated under a gentle stream of nitrogen, and residues were resuspended in hexane.

Analysis of fatty acid composition by GC-MS and GC-FID Analysis of FAMEs in hexane was performed using a quadruple GC system (HP8690, Hewlett & Packard, Palo Alto, USA) equipped with a split/splitless injector. A BPX5 capillary column (SGE, Darmstadt Germany; length, 30 m; inner diameter, 0.32 mm; 0.25 μm film) was used for separation where the injector temperature was held at 240°C. The injection was splitless and He was used as carrier gas at a flow of 2 mL/min. The temperature program was: 40°C, 2 min isothermal; 4°C/min to 230°C; 5 min isothermal at 230°C. The pressure was held constant at 7,57 psi. Additionally, a GC system with flame ionization detector was used (Agilent 6890N) with a special FAME column (CP-Sil88 Varian Chromopack; length, 50 m; inner diameter, 0.25 mm; 0.2 μL film) to reach better separation.

The pressure program was as follows: start, 27,64 psi for 2 min; increase, 0.82 psi/min up to 45.7 psi; isobaric for 5.5 min. The temperature program started at 40°C (2 min), increased 8°C/min up to 220°C, and was held there for 5 min. Injector temperature was 240°C, detector temperature 270°C. The peak areas of the carboxylic acids in total ion chromatograms (TIC) were used to determine their relative amounts. The fatty acids were identified by their mass

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spectra and retention time compared to coinjections of authentic reference compounds obtained from Supelco (Bellefonte, USA).

Statistical analysis Principal component analyses (PCA) were applied on the basis of numerical data matrices converted using the program R (R: Copyright 2005, The R Foundation for Statistical Computing Version 2.1.1). The relative amounts of PLFA data were subjected to PCA to investigate the interrelationships between the soil samples and to determine the predominant PLFA species in the samples. In the first attempt, the investigated soil samples corresponded to the object represented in the multidimensional space and the PLFA values to the descriptors of the multivariate analysis. In a second PCA, reciprocal analysis was carried out with the soil samples corresponding to the descriptors of the analysis.

DNA extraction For DNA extraction, fractions of the soil samples were frozen with solid carbon dioxide at the time of sampling and maintained in this condition during transportation.

Later on, samples were stored at −70°C until further processing. DNA was extracted with the FastDNA Spin kit for soil (QBiogene, Carlsbad, CA, USA) from 800 mg of soil per reaction tube, according to the instructions of the manufacturer with the only exception that the final elution of DNA from the filter was with 75 μL of Tris–HCl buffer 3.33 mM pH 8.0. Five DNA extractions, equivalent to 4 g of soil, were performed for each soil sample, and extracted DNA were pooled together in a single reaction tube. The DNA was dried and the final volume adjusted to 40 μL with MilliQ water. DNA concentrations were quantified using the Quant-iT PicoGreen dsDNA quantitation kit (Invitrogen—Molecular Probes Europe BV, Leiden, The Netherlands).

PCR amplification, cloning, sequencing, and analyses The pooled DNA extracts were used as template in polymerase chain reaction (PCR) amplifications with primers targeting two highly conserved regions identified on bacterial 16S rRNA genes (Marchesi et al. 1998) [63F: 5′-CAG GCC TAA CAC ATG CAA GTC-3′ and 1387R: 5′-GGG CGG WGT GTA CAA GGC-3′]. The final amounts or concentrations of the reagents for PCR in a volume of 50 μL were: 1X colorless GoTaq reaction buffer (Promega, Madison, WI, USA), 5 U of GoTaq polymerase (Promega, Madison, WI, USA), 200 μM of dNTPs (MBI Fermentas, Germany), and 10 pmol of each primer

(synthesized by Invitrogen, Karlsruhe, Germany). For thermal cycling, a Hybaid PCR Express Thermocycler (Thermo Electron, Waltham, MA, USA) was used as follows: initial denaturation at 94°C for 4 min, 35 cycles of 95°C for 45 s, 55°C for 45 s, and 72°C for 1.5 min.

These cycles were followed by one elongation step at 72°C for 7 min. PCR products were purified by using the QIAquick PCR purification kit (Qiagen, Hilden, Germany) and cloned in pGEM-T easy vector system (Promega, Madison, WI, USA). Plasmid inserts were amplified by PCR with vector-specific M13 forward and reverse primers (Sambrook et al. 1989) on transformant colonies dissolved in water and previously incubated at 95°C for 10 min.

Amplified ribosomal DNA restriction analysis (ARDRA) was performed as previously described (Junca and Pieper 2004). The purified PCR products were used as DNA templates in independent sequencing reactions of both strands using the BigDye terminator v1.1 cycle sequencing kit (Applied Biosystems, Foster City, CA, USA) using M13 primers and primers annealing at four different conserved regions in two directions inside the 16S rRNA gene sequences as described previously (Lane 1991). Sequencing reactions were analyzed in an Applied Biosystems 3130xl Genetic Analyzer (Applied Biosystems, Foster City, CA, USA) and sequence contigs were assembled using Sequencher version 4.0.5 (Genes Codes, Ann Arbor, MI, USA). The sequences were cleaned of vector sequences using VecScreen Blast program (NCBI, USA) and oriented in 5′–3′ of the 16S rRNA genes using OrientationChecker (Bioinformatics Toolkit, Cardiff School of Biosciences, UK). Sequences were analyzed for potential chimeric sequences with the service available at the Ribosomal Database Project II (Cole et al. 2003). Additional potential chimeras were assessed with the program MALLARD (Ashelford et al. 2006). The final datasets were aligned with the multiple sequence alignment method MUSCLE (Edgar 2004). A block of sequence alignments was selected with GeneDoc multiple sequence alignment editor software (Nicolas 1997). A collection of the nearest neighbors to the sequences obtained against the 16S rRNA gene sequences reported and classified in the Ribosomal Database Project II were found using Seqmatch (Cole et al. 2003). Neighborjoining trees were calculated from the composite alignments together with calculated bootstrapped values of 1,000 trials using the functions implemented inside Clustal W (Thompson et al. 1994). Tree files were graphically displayed with MEGA 3.1 software (Kumar et al. 2004).

For calculation of rarefaction curves and Shannon diversity indexes, the program DOTUR was used (Schloss and Handelsman 2005) using the distance matrices computed with Dnadist program (Felsenstein 1989) from the nucleotide sequence alignments of the sequence libraries obtained in this study.

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Microbiological culture techniques Fractions of the soil samples were kept at 4°C after collection. Colony forming units were determined in R2A agar (Difco, Livonia, MI, USA) in triplicates after plating of the appropriate dilution that were carried out on phosphate buffer (50 mM, pH 7.0).

Results Biomass development in the Hradčany soil Soil samples from the Hradčany site representative for different steps of the air sparging bioremediation process were investigated for pollutant content. In general, the three sites can be characterized as follows: HRB-3, soil from an untreated site contains high organic contamination (concentrations of TPH=6,400 mg/kg and BTEX=4,400 mg/kg dry weight); HRB-2, soil from a 3-year clean-up site exhibits a moderate organic contamination (TPH=3,900 mg/kg and BTEX=190 mg/kg dry weight); and HRB-1, soil from a 5.5-year clean-up site contains low organic contamination (TPH=1,500 mg/kg and BTEX=9 mg/kg dry weight). From each site, five samples were investigated which were taken in the same drilling campaign. As the geological and hydrogeological specificities of all three sites were similar, the differences in microbiota are most likely due to the difference in pollution level and cannot be explained by geological or other aspects.

In order to compare the abundance and complexity of microbial biomass of the samples subject to different times of air sparging treatment, the overall abundance of PLFA was analyzed (Fig. 2a). On the other hand, in the nontreated soil, which contains very high toxic concentrations of BTEX compounds, PLFAs were only present in very low amounts; this content increased by more than two orders of magnitude in the air sparging treated soils. As PLFA are only present in living (micro)organisms (MacNaughton et al. 1999; Kindler et al. 2006), this is a clear indication that this bioremediation treatment leads to a significant increase in overall microbial biomass. The increase in biomass was also reflected in strong differences between the soil samples regarding quantities of heterotrophic bacteria as quantified by the number of colony forming units per gram of soil (CFU/g) (Fig. 2a) with HRB-3 exhibiting CFUs/g two orders of magnitude lower than HRB-1. Analysis of DNA concentrations by fluorescence quantification (see the “Materials and methods” section) revealed a concentration of 40 ng dsDNA per gram of HRB-1 soil, whereas DNA from HRB-2 was observable after gel electrophoresis but below the concentration of 0.5 ng/μL dsDNA which could be accurately quantified. Amounts of DNA extractable

from HRB-3 were even lower and only detectable after PCR amplification. Thus, compatible results were obtained when comparing, as biomarkers, total DNA extract concentrations, CFUs, or PLFA concentration, which all point to an increase in living microbial biomass.

Phospholipid fatty acid composition of Hradčany soils The PLFA composition of Hradcãny samples (Fig. 2b) showed significant differences depending on the time of air sparging treatment. In the untreated samples, saturated fatty acids (16:0, 18:0) are predominant next to 18:1Δ9cis fatty acid.

The major difference in the PLFA profiles between the three investigated soil sampling sites was the significantly higher relative abundance of 16:1Δ9cis and 18:1Δ11cis monounsaturated fatty acids as well as cyclo19:0 cyclopropane fatty acid in the treated compared to the untreated samples.

A PCA of the PLFA profiles underlined the results given above. The first PCA (Fig. 3a) allowed to clearly distinguish PLFA patterns associated with the soil from three sites differing in the level of BTEX and kerosene contamination and treatment duration. The data of all the three different sampling sites formed distinct clusters. This PCA showed a clear separation of the three conditions on the biplot of the first two principal components, emphasizing changes in the PLFA composition of the soils according to the length of treatment. A separation of the soil samples from the lowest level of contamination to the highest one is operating along the first principal component.

The second PCA stresses the dominant PLFAs that are associated with the difference in the analyzed soil samples (Fig. 3b). The amount of variation explained by the first and second principal components reached 86.3% of the total variation. This PCA relates the abundance of specific PLFAs (16:0; 18:0; 18:1cisΔ9) with the level of contamination (prior clean-up, HRB-3). On the other hand, other PLFAs (18:1cisΔ11, cyclo19:0, 16:1Δ9cis) increase in response to the treatment time and were particularly associated with the 3 years treated (HRB-2) samples. The other PLFAs were found in a close vicinity of the origin of the PCA plot, indicating that the relative amounts of these PLFAs were not substantially affected by the level of contamination and the length of treatment.

Molecular biological analysis of the microbiota composition of Hradčany soil To correlate shifts in lipid composition occurring at the investigated site with changes in bacterial taxonomical complexity, the microbial community structures of the three sampling points were assessed by 16S rRNA gene libraries.

PCR clone libraries of 16S rRNA gene were generated from total pooled DNA extracts of the soils and initial screenings

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Fig. 2 Effect of air sparging treatment on PLFA abundance and composition in Hradčany soils. a Biomass development, given as the overall abundance of PLFA (filled diamonds, represented by area counts) and colony forming units (open squares) in the Hradčany site caused by the air sparging treatment. b PLFA patterns of soils from the Hradčany site. No treatment (HRB-3), total BTEX concentration= 17,000 mg/kg; 3 years treatment (HRB-2), total BTEX concentration=960 mg/kg; 5.5 years treatment (HRB-1), total BTEX concentration=70 mg/kg. From each sampling point, five independent soil samples were extracted and analyzed for their PLFA content. Standard deviation of these five independent measurements are given as error bars

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performed by ARDRA. For HRB-3, ARDRA screening with AluI on 96 clones showed identical patterns in 82 of the clones, suggesting the predominance of a single taxonomic group in the library. A similar ARDRA screening on HRB-1 and HRB-2 clone libraries did not give evidence for any predominant pattern. Further screening by random sequencing was performed on 79 clones from HRB-1, 80 clones from HRB-2, and 28 clones from HRB-3. The relationships of 187 assembled sequences, comprising a common 1-kb length block covering variable regions V2 to V6 of the 16S rRNA genes (Neefs et al.

1993), corresponding to positions 103 to 1130 of Escherichia coli 16S rRNA gene (GenBank accession number J01695), are shown in Fig. 4a (expanded view and detailed labeling of these results are available as Electronic

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supplementary material). A global alignment of the sequences obtained together with the most closely related 16S rRNA gene sequences from type strains and selected sequences retrieved from public databases indicated the presence of sequences related to diverse evolutionary branches (Janssen 2006). The clones in the clone libraries were assigned to operational taxonomic units (OTUs) using >99% (OTU0.01), >95% (OTU0.05), and >90% (OTU0.1) sequence identity as criteria, as sequences with greater than those identities are typically excluding differences based on operon heterogeneity or are typically assigned to the same genus or order, respectively (Acinas et al. 2004b; Schloss and Handelsman 2004).

Rarefaction analysis on each sequence library showed that the higher number of clones sequenced from the HRB-

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Fig. 3 PCA analyses of PLFA patterns obtained from Hradčany soils. a Ordination plot representing the relationship between the contamination sites and the PLFA patterns. The cross indicates the origin of coordinates and values on the axes indicate the percentage of the total explained variation. b PCA showing loading values for individual PLFA. PLFAs found on the right in the plot had increased in the no treatment (HRB-3) soils, whereas the ones found in the lower part of the plot had increased the 5.5-year treatment (HRB-1) and 3-year treatment (HRB-2) soils

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Fig.

4 Taxonomical distribution of the 16S rRNA gene sequences retrieved from the contaminated soils DNA under different bioremediation treatments. a Neighbor-joining tree based on 16S rRNA gene sequences obtained from HRB soil DNA amplifications. Circles indicate sequences obtained by random screening of PCR clone libraries of amplifications from DNA extracts of HRB-1 (blue), HRB2 (green), and HRB-3 (orange) soils. Light purple trapezoids indicate sequences of closely related bacterial type strains or cultured strains.

In cases where sequences with a similarity higher than 60% to an observed HRB-derived sequence were not available from bacterial type strains, sequences from uncultured bacteria were included for orientation (violet triangles). Rarefaction curves for different distance levels (OTU0.01, OTU0.05, and OTU0.10) for each of the analyzed libraries were calculated by DOTUR (Schloss and Handelsman 2005) and are given below the dendrogram. Coverages (C) at 95% distances were calculated according to Turing’s formula (Good 1953) where C= 100 represents complete coverage. b Relative clone frequencies in major phylogenetic groups (Order–Class) of the clone libraries analyzed. HRB-derived 16S rRNA gene sequences were assigned to bacterial classes using the RDP-naïve Bayesian classifier according to the taxonomical hierarchy of Garrity and Lilburn (release 6.0) with the default confidence threshold of 80%. The colors used in the stack column diagram correspond to bacterial Orders as defined to the right of the columns. Orders were grouped as Classes as shown to the very right of the figure, except for Bacillales and Clostridiales that, for simplicity, were grouped in the higher rank (phylum) of Firmicutes.

Sequences that could not be classified and that were retrieved only in very low amounts were collectively indicated as “Unclassified ribosomal genes.” For additional details of the sequences obtained and control sequences used in this figure, see the accompanying Electronic supplementary material

1 and HRB-2 libraries were indeed necessary to obtain coverage comparable to the one for the HRB-3 library (see Fig. 4).

Almost all the sequences obtained from HRB-3 were tightly clustering (>95% overall sequence similarity) inside the genus Pseudomonas with the majority of these sequences closely related, but not identical (identities >1,022/1,030, 99%), to those found in Pseudomonas cedrina or Pseudomonas azotoformans type strains inside the Pseudomonas fluorescens group (Anzai et al. 2000). Such clusters of sequence microdiversity in ribosomal genes are commonly observed in amplifications of environmental samples (Acinas et al. 2004a); however, its interpretation and significance is still under discussion. Nevertheless, it is very likely that, due to a strong selection caused by the hazardous environmental conditions, only members of a bacterial genus tolerant to high solvent concentrations and possibly with the potential to aerobically degrade such compounds were observed. HRB-2 exhibited a wider sequence diversification compared to the contaminated nontreated state (HRB-3). A distinct Pseudomonas intragenus microdiversity was evidenced in this sampling area with sequences highly similar to abovementioned P. cedrina/P. azotoformans cluster still being predominant (22% of clones) but 5% of the clone sequences being closely related (identities >1,016/1,030, 98%) to the recently described Pseudomonas rhizosphaerae type strain (Peix et al. 2003).

Discussion The air sparging treatment of the Hradcãny site caused a significant increase in the amount of biomass and, at least partially as a consequence, a decrease in organic contamination of the soil. The increase in living microbial biomass could be shown by us; compatible results were obtained when comparing, as biomarkers, total DNA extract concentrations, CFUs, or PLFA concentration, which all point to an increase in living microbial biomass.

The major difference in the PLFA profiles between the three investigated soil sampling sites was the significantly higher relative abundance of 16:1Δ9cis and specifically 18:1Δ11cis monounsaturated fatty acids in the treated compared to the untreated samples. As cis-vaccenic acid (18:1Δ11cis) is synthesized via the so-called anaerobic pathway of fatty acid synthesis that is exclusively present in several Gram-negative bacteria (Keweloh and Heipieper 1996), this indicates the high abundance of Gram-negative bacteria in the treated samples. The predominance of Gramnegative bacteria in the treated samples is further supported by the high abundance of Gram-negative-specific cyclopropane fatty acids (cy17:0 and cy19:0) and the low abundance of Gram-positive-specific iso- and anteisobranched fatty acids (i15:0, a15:0, i16:0, and i17:0).

However, inspection of discriminatory fatty acids shows the presence of Gram-negative-specific cyclopropane fatty acids accounting for approximately 5% up to 40% of the total fatty acids, whereas abundance of Gram-positivespecific acids was negligible. This indicates also the untreated site to be dominated by Gram-negative organisms, and treatment to exert a significant effect on the composition of the Gram-negative microbial community fraction. In fact, taking the combined abundance of the Gram-positive-specific fatty acids and the Gram-negativespecific fatty acids as a measure of the ratio between Grampositive and Gram-negative bacteria (Margesin et al. 2007), the relative abundance of Gram-positive organisms was highest in the 5.5 years treated soil. The absence of polyunsaturated fatty acids shows that eukaryotes are practically absent in these soils, which indicates that a normal soil microflora has not been completely established by the so far carried out bioremediation process.

The PCA carried out with data that stresses the dominant PLFAs associated with the difference in the analyzed soil samples (Fig. 3b) clearly approves the tendencies visible from the fatty acid profiles. The relation of specific PLFAs (16:0; 18:0; 18:1cisΔ9) with the highest level of contamination (prior clean-up, HRB-3) suggests that a highly specific microbiota is associated with these hazardous environmental conditions. On the other hand, other PLFAs (18:1cisΔ11, cyclo19:0, 16:1Δ9cis) increase in response to the treatment time and were particularly associated with the

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3 years treatment (HRB-2) indicates a specific Gramnegative bacterial community accumulating during the air sparging treatment.

However, next to community shifts, changes in the membrane fatty acid patterns of bacteria can also occur as adaptive response to pollutant toxicity and environmental stress conditions (Frostegard et al. 1993b; Heipieper and de Bont 1994; Heipieper et al. 1996). Therefore, it is necessary to support the insights based on PLFA profiling also by other methods such as, e.g., molecular biological techniques.

Surprisingly, the expected trans–cis ratio of unsaturated fatty acids, a very useful parameter for stress monitoring in bacterial cultures (Guckert et al. 1986; Guckert et al. 1991; Heipieper et al. 1992; Heipieper et al. 1996), did not show significant changes in the samples analyzed (data not shown), probably due to its transient identity.

Although the PLFA analysis already demonstrated a shift in the microbial community as well as an increase in living biomass, a detailed molecular biological analysis of the microbiota was necessary. Here, a clear increase in the microbial biodiversity of the site caused by the air sparging treatment was visible. Whereas almost all the sequences obtained from HRB-3 were clustering inside the genus Pseudomonas, a tremendous increase in the identified bacterial diversity occurred in the samples taken from 3 and 5.5 years of treatment.

While Pseudomonas is a genus defined as ubiquitous and of high environmental importance, these conclusions are predominantly coming from observations using traditional culture-dependent techniques (Moore et al. 2006) which are generally accepted to include a severe bias toward easy to culture microorganisms (Amann et al.

1995). However, our study and some other recent reports (Duineveld et al. 2001; Kaplan and Kitts 2004; Gerdes et al.

2005; Popp et al. 2006; Ferguson et al. 2007) are showing that Pseudomonas may be defined as a predominant member in communities of aerobic or microaerophilic ecosystems where high concentrations of crude oil are acting as a strong selector.

However, whereas HRB-3 sequences affiliated with Pseudomonas spp. comprise roughly 80% of all clones, only 25% of HRB-2 clones were affiliated with that genus. Other predominant sequence types in HRB-2 were affiliated with the classes of Actinobacteria, Acidobacteria, and Alphaproteobacteria (predominantly members of the orders Rhizobiales and Rhodospirillales). The higher diversity observed in HRB-2 (Fig. 4) was also reflected by a higher Shannon diversity index (H′, calculated for OTU0.05) of 2.67±0.25 (95% confidence interval), compared to only 0.73±0.44 for HRB-3. An even slightly higher value compared to HRB-2 was observed for HRB-1 (2.86±0.21), indicating diversity and balance of community composition to increase with bioremediation treatment time.

However, whereas there is only a small increase in the Shannon diversity index from HRB-2 to HRB-1, both sites comprise very different microbial community compositions.

Most importantly, Pseudomonas spp. was barely detectable (one out of 79 sequences) in HRB-1. In contrast, sequences affiliated with Sphingomonadales, members of which had been observed in various aromatic contaminated sites and which had been related to primary stages on polycyclic aromatic biodegradation (Leys et al. 2004, 2005), were abundant only in HRB-1, comprising roughly 10% of the respective clone library, contrasting a single sequence in the HRB-2 clone library.

In addition, Betaproteobacteria-affiliated sequences, a group only marginally detected (one sequence only) in HRB-2, are a significant fraction of the HRB-1 library, accounting for 20% of the total amount of sequences.

Additional sequences exclusively observed in HRB-1 constitute a new branch inside the family Xanthomonadaceae (Gammaproteobacteria) with equal divergences (approximately 15% of difference) against sequences from strains of the genera Frateuria and Rhodanobacter.

Bacterial assemblages similar to that of HRB-1 and consisting of Pseudomonas, Sphingomonas, Xanthomonas, Acidovorax, and Burkholderia sequences have been previously observed, for instance, at anthropogenic hydrocarboncontaminated coastal soils in Antarctica (Saul et al. 2005), while bacterial communities predominantly composed of Pseudomonas, Sphingomonas, and Acidobacteria had been reported for instance in soil–groundwater ecosystems with petroleum contamination (Popp et al. 2006).

As shown in Fig. 4b, a comparison of community composition at the level of bacterial classes, which is used in many reports tracking shifts in microbial communities by FISH probes, T-RF sizes, or OTU definition (Pett-Ridge and Firestone 2005; Yu et al. 2005; Watt et al. 2006; Allen et al. 2007; McGarvey et al. 2007) among others, would direct to misleading conclusions as it would suggest the predominance and resilience of Gammaproteobacteria in the sites independent of the treatment. However, when comparisons are performed at the taxonomical scale Order, this shows to be an oversimplified assumption as strong shifts in composition inside the Order were observed. As an example, among the Gammaproteobacterial sequences, only those affiliated with Pseudomonadales were predominant in the HRB-2 site but practically absent from HRB-1 where Xanthomonadales and Unclassified Gammaproteobacteria are accounting for a relatively high amount of the total bacterial composition detected (>35%). This example shows how comparisons of taxonomical composition in bacterial communities should be at least at Order ranks.

Lower resolution comparisons of Classes or even Phyla can be misleading and fail to detect significant community changes.

Appl Microbiol Biotechnol

Integrating the information of overall microbial abundance (Fig. 2a) with the sequences obtained (Fig. 4), it is evident that even though the relative abundance of Pseudomonadales decreased in HRB-2 compared to HRB3, the total number of Pseudomonadales cells per gram of soil in HRB-2 is very likely by at least one order of magnitude higher. Thus, the initial predominance of Pseudomonadales in HRB-3 may indicate a physiological advantage. These cells not only survive under these harsh conditions of low oxygen, high loads of aromatic carbon pollutants, and high solvent concentrations, but obviously have been replicating under these conditions. This is in accordance with culture-dependent studies on Pseudomonadales (Heipieper and de Bont 1994; Sikkema et al. 1995; Heipieper et al. 1996), which have shown members of this group to be capable to replicate under harsh laboratory conditions and high solvent stress. It can thus be proposed that, at least at the site under study, Pseudomonads paved the road for other bacteria to be capable to replicate as shown by the increased diversity observed in HRB-2. Thus, for a certain time, Pseudomonas is sharing its habitat in a bacterial community of increasing complexity, as less restricting conditions for other phylotypes are being generated during the clean-up process, leading to the decrease in community predominance of Pseudomonas and the increase of other, previously not detectable phylotypes. Particularly interesting is the increase in Acidobacterial sequence types, which are supposed to be selected in low-nutrient soil or in soil with a high amount of recalcitrant substrates (Torsvik and Ovreas 2002). As, moreover, soils with a high content of nutrients showed positive selection for Alphaproteobacteria and specifically Gammaproteobacteria (Amann et al. 1995), the ratio between the number of Proteobacteria and Acidobacterium was suggested to be indicative of the nutritional status of soils (Smit et al. 2001) with supposedly high ratios being indicative for high input soil systems. In the soil systems studied here, Acidobacteria were absent from untreated soil, similar to the situation observed in other environments highly contaminated with petroleum hydrocarbons (Popp et al. 2006), and ratios reached values of 5.4 in HRB-2 and 13.8 in HRB-1, indicating a significant recovery of the system. However, as ratios of up to 10 have been reported in supposedly pristine soils (Kasai et al. 2005; Schloss and Handelsman 2006), obviously even such high values do not indicate the nutritional status.

The air sparging biodegradation technique applied in the Hradcãny site led to a drastic decrease in pollutant concentrations through the accelerated aerobic microbial activity. Next to an increase in the amount of potential degraders, this reduction in the concentration of toxic organic solvents also allows the reproduction of bacterial types sensitive to higher solvent concentrations that are not

necessarily able to degrade aromatics, but capable of surviving and growing in the cross-feeding mesh of metabolites excreted from the initial biomass of degraders.

In accordance with decreased concentrations of aromatics (and thus lower solvent stress), a higher variety of bacterial taxonomical types and higher biomass content was observed. This biodiversity restoration, which can be seen as an ecological succession, probably would not lead to the same microbial composition of the soil as it was before the aromatic contamination occurred (Curtis et al. 2002).

Here, it is shown that the bacterial community under adaptation in these soils, concomitantly with the observed degradation of the contaminants in situ, showed a dynamic succession of Gram-negative bacteria with the community being initially restricted to Pseudomonadales at very low densities, developing an increased diversity comprising new proteobacterial types and Gram-positive bacteria. Compatible trends were observed using ordination methods, which showed the clear separation of the different fatty acid clusters and indicated the predominance of Gram-negative bacteria able to resist the solvent concentrations at untreated contaminated soils and the diversification in samples where the treatment is applied. Future studies will focus on catabolic activities in these sites and the relationship with the phylogenetic changes observed by means of culturedependent and culture-independent studies.

Acknowledgments This work was supported by contract no.

003998 (GOCE) of the European Commission within its Sixth Framework Program project BIOTOOL. We would like to thank the excellent technical assistance of Silke Kahl.

References Acinas SG, Klepac-Ceraj V, Hunt DE, Pharino C, Ceraj I, Distel DL, Polz MF (2004a) Fine-scale phylogenetic architecture of a complex bacterial community. Nature 430:551–554 Acinas SG, Marcelino LA, Klepac-Ceraj V, Polz MF (2004b) Divergence and redundancy of 16S rRNA sequences in genomes with multiple rrn operons. J Bacteriol 186:2629–2635 Allen JP, Atekwana EA, Atekwana EA, Duris JW, Werkema DD, Rossbach S (2007) The microbial community structure in petroleum-contaminated sediments corresponds to geophysical signatures. Appl Environ Microbiol 73:2860–2870 Amann RI, Ludwig W, Schleifer KH (1995) Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 59:143–169 Anzai Y, Kim H, Park JY, Wakabayashi H, Oyaizu H (2000) Phylogenetic affiliation of the pseudomonads based on 16S rRNA sequence. Int J Syst Evol Microbiol 50:1563–1589 Ashelford KE, Chuzhanova NA, Fry JC, Jones AJ, Weightman AJ (2006) New screening software shows that most recent large 16S rRNA gene clone libraries contain chimeras. Appl Environ Microbiol 72:5734–5741 Bass DH, Hastings NA, Brown RA (2000) Performance of air sparging systems: a review of case studies. J Hazard Mater 72:101–119

Appl Microbiol Biotechnol Bligh EG, Dyer WJ (1959) A rapid method of total lipid extraction and purification. Can J Biochem Physiol 37:911–917 Cole JR et al (2003) The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy. Nucleic Acids Res 31:442–443 Curtis TP, Sloan WT, Scannell JW (2002) Estimating prokaryotic diversity and its limits. Proc Nat Acad Sci U S A 99:10494– 10499 Duineveld BM, Kowalchuk GA, Keijzer A, van Elsas JD, van Veen JA (2001) Analysis of bacterial communities in the rhizosphere of chrysanthemum via denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA as well as DNA fragments coding for 16S rRNA. Appl Environ Microbiol 67:172–178 Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113 Felsenstein J (1989) PHYLIP—Phylogeny Inference Package (Version 3.2). Cladistics 5:164–166 Ferguson AS et al (2007) Microbial analysis of soil and groundwater from a gasworks site and comparison with a sequenced biological reactive barrier remediation process. J Appl Microbiol 102:1227– 1238 Frostegard A, Baath E, Tunlid A (1993a) Shifts in the structure of soil microbial communities in limed forests as revealed by phospholipid fatty-acid analysis. Soil Biol Biochem 25:723–730 Frostegard A, Tunlid A, Baath E (1993b) Phospholipid fatty acid composition, biomass, and activity of microbial communities from 2 soil types experimentally exposed to different heavy metals. Appl Environ Microbiol 59:3605–3617 Frostegard A, Tunlid A, Baath E (1996) Changes in microbial community structure during long-term incubation in two soils experimentally contaminated with metals. Soil Biol Biochem 28:55–63 Gerdes B, Brinkmeyer R, Dieckmann G, Helmke E (2005) Influence of crude oil on changes of bacterial communities in Arctic seaice. FEMS Microbiol Ecol 53:129–139 Good IJ (1953) The population frequencies of species and the estimation of population parameters. Biometrika 40:237–264 Guckert JB, Hood MA, White DC (1986) Phospholipid ester-linked fatty acid profile changes during nutrient deprivation of Vibrio cholerae: increases in the trans/cis ratio and proportions of cyclopropyl fatty acids. Appl Environ Microbiol 52:794–801 Guckert JB, Ringelberg DB, White DC, Hanson RS, Bratina BJ (1991) Membrane fatty acids as phenotypic markers in the polyphasic taxonomy of methylotrophs within the Proteobacteria.

J Gen Microbiol 137:2631–2641 Hall BL, Lachmar TE, Dupont RR (2000) Field monitoring and performance evaluation of an in situ air sparging system at a gasoline-contaminated site. J Hazard Mater 74:165–186 Heipieper HJ, de Bont JAM (1994) Adaptation of Pseudomonas putida S12 to ethanol and toluene at the level of the fatty acid composition of membranes. Appl Environ Microbiol 60:4440–4444 Heipieper HJ, Diefenbach R, Keweloh H (1992) Conversion of cisunsaturated fatty acids to trans, a possible mechanism for the protection of phenol-degrading Pseudomonas putida P8 from substrate toxicity. Appl Environ Microbiol 58:1847–1852 Heipieper HJ, Meulenbeld G, van Oirschot Q, de Bont JAM (1996) Effect of environmental factors on the trans/cis ratio of unsaturated fatty acids in Pseudomonas putida S12. Appl Environ Microbiol 62:2773–2777 Heron G, Gierke JS, Faulkner B, Mravik S, Wood L, Enfield CG (2002) Pulsed air sparging in aquifers contaminated with dense nonaqueous phase liquids. Ground Water Monit Remediat 22:73–82 Janssen PH (2006) Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes. Appl Environ Microbiol 72:1719–1728

Junca H, Pieper DH (2004) Functional gene diversity analysis in BTEX contaminated soils by means of PCR-SSCP DNA fingerprinting: comparative diversity assessment against bacterial isolates and PCR-DNA clone libraries. Environ Microbiol 6:95– 110 Kaplan CW, Kitts CL (2004) Bacterial succession in a petroleum land treatment unit. Appl Environ Microbiol 70:1777–1786 Kasai Y, Takahata Y, Hoaki T, Watanabe K (2005) Physiological and molecular characterization of a microbial community established in unsaturated, petroleum-contaminated soil. Environ Microbiol 7:806–818 Keweloh H, Heipieper HJ (1996) Trans unsaturated fatty acids in bacteria. Lipids 31:129–137 Kindler R, Miltner A, Richnow HH, Kastner M (2006) Fate of gramnegative bacterial biomass in soil—mineralization and contribution to SOM. Soil Biol Biochem 38:2860–2870 Kumar S, Tamura K, Nei M (2004) MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief Bioinform 5:150–163 Lane DJ (1991) 16S/23S sequencing. In: Stackebrandt E, Goodfellow M (eds) Nucleic acid techniques in bacterial systematics. Wiley, Chichester Leys NM, Ryngaert A, Bastiaens L, Verstraete W, Top EM, Springael D (2004) Occurrence and phylogenetic diversity of Sphingomonas strains in soils contaminated with polycyclic aromatic hydrocarbons. Appl Environ Microbiol 70:1944–1955 Leys NM, Ryngaert A, Bastiaens L, Top EM, Verstraete W, Springael D (2005) Culture independent detection of Sphingomonas sp EPA 505 related strains in soils contaminated with polycyclic aromatic hydrocarbons (PAHs). Microb Ecol 49:443–450 Machackova J, Hercik F, Proksova S (2005) In situ bioremediation of jet fuel at the former soviet Hradčany Air Force Base. In: Proceedings of the Eight International In Situ and On Site Bioremediation Symposium, Battelle Memorial Institute, Baltimore, USA MacNaughton SJ, Stephen JR, Venosa AD, Davis GA, Chang YJ, White DC (1999) Microbial population changes during bioremediation of an experimental oil spill. Appl Environ Microbiol 65:3566–3574 Marchesi JR, Sato T, Weightman AJ, Martin TA, Fry JC, Hiom SJ, Dymock D, Wade WG (1998) Design and evaluation of useful bacterium-specific PCR primers that amplify genes coding for bacterial 16S rRNA. Appl Environ Microbiol 64:2333 Margesin R, Hammerle M, Tscherko D (2007) Microbial activity and community composition during bioremediation of diesel-oilcontaminated soil: effects of hydrocarbon concentration, fertilizers, and incubation time. Microb Ecol 53:259–269 Marley MC, Hazebrouck DJ, Walsh MT (1992) The application of in situ air sparging as an innovative soils and ground-water remediation technology. Ground Water Monit Remediat 12:137–145 Masak J, Machackova J, Siglova M, Cejkova A, Jirku V (2003) Capacity of the bioremediation technology for clean-up of soil and groundwater contaminated with petroleum hydrocarbons. J Environ Sci Health A 38:2447–2452 McGarvey JA, Miller WG, Zhang RH, Ma YG, Mitloehner F (2007) Bacterial population dynamics in dairy waste during aerobic and anaerobic treatment and subsequent storage. Appl Environ Microbiol 73:193–202 Moore E, Tindall B, Santos V, Pieper D, Ramos JL, Palleroni N (2006) Nonmedical Pseudomonas. In: Dworkin M, Falkow S, Rosenberg E, Schleifer KH, Erko Stackebrandt E (eds) The prokaryotes. Springer, Heidelberg, pp 646–703 Neefs JM, Vandepeer Y, Derijk P, Chapelle S, Dewachter R (1993) Compilation of small ribosomal subunit RNA structures. Nucleic Acids Res 21:3025–3049

Appl Microbiol Biotechnol Nicolas KB (1997) GeneDoc 2.6.02. Available at http://www.psc.edu/ biomed/genedoc/ Peix A, Rivas R, Mateos PF, Martinez-Molina E, Rodriguez-Barrueco C, Velazquez E (2003) Pseudomonas rhizosphaerae sp nov., a novel species that actively solubilizes phosphate in vitro. Int J Syst Evol Microbiol 53:2067–2072 Pennanen T, Frostegard A, Fritze H, Baath E (1996) Phospholipid fatty acid composition and heavy metal tolerance of soil microbial communities along two heavy metal-polluted gradients in coniferous forests. Appl Environ Microbiol 62:420–428 Pett-Ridge J, Firestone MK (2005) Redox fluctuation structures microbial communities in a wet tropical soil. Appl Environ Microbiol 71:6998–7007 Popp N, Schlomann M, Mau M (2006) Bacterial diversity in the active stage of a bioremediation system for mineral oil hydrocarboncontaminated soils. Microbiology 152:3291–3304 Reddy KR, Kosgi S, Zhou JN (1995) A Review of in-situ air sparging for the remediation of voc-contaminated saturated soils and groundwater. Hazard Waste Hazard Mater 12:97–118 Sambrook J, Fritsch EF, Maniatis T (1989) Molecular cloning: a laboratory manual, 2nd edn. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY Saul DJ, Aislabie JM, Brown CE, Harris L, Foght JM (2005) Hydrocarbon contamination changes the bacterial diversity of soil from around Scott Base, Antarctica. FEMS Microbiol Ecol 53:141–155 Schloss PD, Handelsman J (2004) Status of the microbial census.

Microbiol Mol Biol Rev 68:686–691 Schloss PD, Handelsman J (2005) Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Appl Environ Microbiol 71:1501–1506 Schloss PD, Handelsman J (2006) Toward a census of bacteria in soil.

PLoS Comput Biol 2:786–793

Sikkema J, de Bont JA, Poolman B (1995) Mechanisms of membrane toxicity of hydrocarbons. Microbiol Rev 59:201–222 Smit E, Leeflang P, Gommans S, van den Broek J, van Mil S, Wernars K (2001) Diversity and seasonal fluctuations of the dominant members of the bacterial soil community in a wheat field as determined by cultivation and molecular methods. Appl Environ Microbiol 67:2284–2291 Thompson JD, Higgins DG, Gibson TJ (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 22:4673–4680 Torsvik V, Ovreas L (2002) Microbial diversity and function in soil: from genes to ecosystems. Curr Opin Microbiol 5:240–245 Watt M, Hugenholtz P, White R, Vinall K (2006) Numbers and locations of native bacteria on field-grown wheat roots quantified by fluorescence in situ hybridization (FISH). Environ Microbiol 8:871–884 White DC (1993) In-situ measurement of microbial biomass, community structure and nutritional-status. Philos Trans R Soc Lond Ser A Math Phys Sci 344:59–67 White DC, Stair JO, Ringelberg DB (1996) Quantitative comparisons of in situ microbial biodiversity by signature biomarker analysis.

J Ind Microbiol Biotech 17:185–196 Yang XM, Beckmann D, Fiorenza S, Niedermeier C (2005) Field study of pulsed air sparging for remediation of petroleum hydrocarbon contaminated soil and groundwater. Environ Sci Technol 39:7279–7286 Yu CP, Ahuja R, Sayler G, Chu KH (2005) Quantitative molecular assay for fingerprinting microbial communities of wastewater and estrogen-degrading consortia. Appl Environ Microbiol 71:1433–1444 Zelles L (1997) Phospholipid fatty acid profiles in selected members of soil microbial communities. Chemosphere 35:275–294