Monitoring the changes in a bacterial community in petroleum-polluted soil bioaugmented with hydrocarbon-degrading strains

Monitoring the changes in a bacterial community in petroleum-polluted soil bioaugmented with hydrocarbon-degrading strains

Applied Soil Ecology 105 (2016) 76–85 Contents lists available at ScienceDirect Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoi...

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Applied Soil Ecology 105 (2016) 76–85

Contents lists available at ScienceDirect

Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil

Monitoring the changes in a bacterial community in petroleum-polluted soil bioaugmented with hydrocarbon-degrading strains _ Magdalena Pacwa-Płociniczaka,* , Grazyna Anna Płazab , Zofia Piotrowska-Segeta a b

 ska 28, 40-032 Katowice, Poland Department of Microbiology, University of Silesia, Jagiellon Department of Environmental Microbiology, Institute for Ecology of Industrial Areas, Kossutha 6, 40-844 Katowice, Poland

A R T I C L E I N F O

Article history: Received 16 September 2015 Received in revised form 12 February 2016 Accepted 11 April 2016 Available online xxx Keywords: Petroleum hydrocarbons Bioaugmentation qPCR DGGE PLFA CLPP

A B S T R A C T

Bioaugmentation is a strategy used to enhance degradation of petroleum compounds in contaminated soils, however little is known about the interactions between introduced bacteria and autochthonous microflora. Therefore the objective of the study was to assess any changes in the structure and metabolic activity of the soil bacterial communities as a result of the introduction of Bacillus subtilis T0-1 or Pseudomonas sp. P-1, as well their consortium, into petroleum-contaminated soil. The bioaugmentation experiment was carried out under laboratory conditions using soil taken from an industrial area located around a refinery in Czechowice-Dziedzice. After the bioaugmentation process, a significant (P < 0.05) decrease in the TPH content was reported in all inoculated soils. Inoculation of the soil with the bacterial consortium resulted in a three times greater removal of TPH compared to soils inoculated with single strains. It has been reported that all of the strains had an ability to survive in the environment during the experimental period. The introduction of bacterial strains led to increase in the number of 16S rRNA gene copies in soil on 1 and 7 days of the experiment as well as alkB gene copies during 91 days of the study compared to the non-treated soil. Analysis of the 16S rRNA and alkB genes-based DGGE fingerprints showed that introduced bacteria changed the genetic diversity of the total bacterial communities as well as the communities that have the genes involved in the degradation of hydrocarbons. Analysis of the PLFA profiles showed that the bacterial strains caused short-term changes in the amounts of fatty acids characteristic for Gram-positive and Gram-negative bacteria. The CLPPs indicated differences in soil metabolic activity between the inoculated and non-inoculated soils after the bioaugmentation process. ã 2016 Elsevier B.V. All rights reserved.

1. Introduction The contamination of soil by petroleum hydrocarbons, which are known to belong to the family of carcinogens and neurotoxic organic pollutants (Abioye, 2011), is a serious problem prevalent across the globe. Currently, a variety of technologies can be applied for the remediation of environments that have been polluted with such compounds. Among them, bioaugmentation, which is the addition of specific strains or the microbial consortium that has the

* Corresponding author. E-mail addresses: [email protected] (M. Pacwa-Płociniczak), [email protected] (G.A. Płaza), zofi[email protected] (Z. Piotrowska-Seget). http://dx.doi.org/10.1016/j.apsoil.2016.04.005 0929-1393/ ã 2016 Elsevier B.V. All rights reserved.

desired catabolic properties into the contaminated soil, is recommended as an efficient, economic, versatile and environmentally sound solution (Liu et al., 2011). The bacteria used in the bioaugmentation of petroleum-polluted soils very often have the ability to produce surface active compounds. Inoculation with bacteria that are able to degrade hydrocarbons and produce biosurfactants increase the bioavailability of hydrophobic compounds and thus accelerate hydrocarbon biodegradation (PacwaPłociniczak et al., 2011). However, it has been observed that bioaugmentation does not always bring the desired effects. One of the reasons for the failure may be the interactions between the indigenous populations of microorganisms and the introduced strains (Mao et al., 2012). Whilst the design and implementation of remediation technologies are relatively well established, analysis of the changes in the microbial activity and community structure

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in bioaugmented hydrocarbon-polluted ecosystems has still been a challenge for scientists. These shortfalls in understanding the dynamics and shifts in soil during the degradation of hydrocarbons are constantly compared to the ecological “black box” of biological remediation systems (Whiteley and Bailey, 2000). The presence of hydrocarbons in soil selectively promotes the growth of the microorganisms capable of utilising them. Thus, in long-term contaminated soils, changes towards the dominance of hydrocarbon degrading microorganisms can be observed (Vázquez et al., 2009). On the other hand, in soils subjected to the bioremediation process, shifts in the structure of the microbial communities might occur once again, especially if a bioaugmentation strategy was applied. Studies on the diversity of soil microbial communities during bioremediation are necessary in order to evaluate the impact of introduced bacterial strains may have on the structure of that community (Vázquez et al., 2009). Additionally, the ability to monitor the diversity and structural composition of the soil microbial communities may provide good information about the health and condition of the soil during the degradation of contaminants (Whiteley and Bailey, 2000). The lack of knowledge about changes in the structure of microbial communities in soil subjected to bioremediation comes from the fact that many of the microbes may not have been isolated in the laboratory or may have specific community associations that prevent the isolation of pure cultures for analysis. Nonetheless, the application of cultureindependent molecular and biochemical techniques can facilitate complex analyses of environmental samples (Whiteley and Bailey, 2000). The aim of the study was to assess any shifts in the genetic, structural and functional diversity of the soil autochthonous microbial communities as a result of the introduction of Bacillus subtilis T0-1 or Pseudomonas sp. P-1, as well their consortium, into petroleum-hydrocarbon contaminated soil. 2. Materials and methods 2.1. Study area and soil collection The soil, which was historically contaminated, was obtained from an industrial area located around an oil refinery in Czechowice-Dziedzice, Upper Silesia, Poland. Nearly a century of continued use of a sulfuric acid-based oil refining technology by the Czechowice Oil Refinery has produced an estimated 120 thousand tons of acidic, highly weathered petroleum sludge that has been deposited into a waste lagoon. The soil that was used for the bioremediation experiment was collected from a site adjacent to lagoon. The soil (prepared from eight different sub-samples taken from an area of 25 m2) was collected from the surface to a depth of

Table 1 Selected physicochemical properties of the soil used in the experiment. Parameter

Value

Sand (%) Silt (%) Clay (%) Textural classification Density (g cm3) pHH2O Organic matter (%) Ntot (%) Corg (%) P (mg kg1) Fe (mg kg1)

31  3.1 45  4.5 24  2.4 silty clay loam 1.145  0.002 4.02  0.01 6.81  0.03 0.079  0.001 1.58  0.12 505.40  29.32 20740.00  782.56

Stand. Dev. of three independent experiments.

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about 0.2 m. Prior to experiment, the soil was passed through 1.2 mm sieve and stored at 4  C. The soil used in the study was classified as silty clay loam (Orthic Luvisols, according to FAO system) (FAO, 2014). Its detailed chemical and physical parameters are listed in Table 1. 2.2. Isolation and selection of rifampicin-resistant mutants and preparation of the inoculum Hydrocarbon-degrading and biosurfactant-producing Bacillus subtilis T0-1 and Pseudomonas sp. P-1 strains were isolated from the soil used in this study (Płaza et al., 2011; Pacwa-Płociniczak et al., 2014). In order to monitor the survival of the strains after their introduction into the contaminated soil, spontaneous rifampicinresistant mutants of the strains were selected according to Płociniczak et al. (2013). To prepare the inoculum for bioaugmentation, the rifampicin-resistant mutants of T0-1 and P-1 strains were grown on a molasses medium on an orbital shaker at 120 rpm (28  C) for 48 h. The number of bacteria in the inoculum was evaluated based on the turbidimetry and plating techniques. The proper volume of bacterial suspensions was centrifuged (12,000 rpm, 4  C, 20 min) and the harvested bacteria were washed twice with sterile saline and resuspended in 40 mL of sterile saline. 2.3. Experimental design The bioremediation study was carried out under laboratory conditions. The experiment had a completely randomised block design with three replications that had four treatments: (1) soil inoculated with strain T0-1, (2) soil inoculated with strain P-1, (3) soil inoculated with mixture of T0-1 and P-1 strains and (4) the control soil treated with sterile saline instead of a bacterial suspension. Four hundred grams of contaminated soil was placed into pots and then 40 mL of the bacterial solutions of the T0-1, P1 and T0-1 + P-1 strains were added into the soil up to 107 bacterial cells g1 dry weight (dw) soil. Afterwards soils (inoculated with bacteria and control) were gently mixed for equal distribution of bacteria in soil. The soil pots were incubated for 91 d at room temperature On days 1, 3, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84 and 91 the soil samples were collected with diameter auger and immediately analysed for the survival of the T0-1 and P-1 strains. For other analyses, soil samples of 15 g were taken on days 1, 7, 42 and 91, and immediately stored at 20  C. 2.4. Total petroleum hydrocarbons (TPH) The total petroleum hydrocarbon concentration in the soil before and after the bioremediation study was quantified as hydrocarbons with a carbon number between 10 and 40 (TPHc10-40) following the ISO 16703:2011 protocol. Five grams of soil was briefly shaken with 10 mL of acetone and after the addition of 5 mL of n-heptane containing a C10 and C40 standard solution, and then the mixture was shaken for 1 h. After the solid material settled, the supernatant was transferred into glass tubes with Teflon seals and then, the organic phase was washed twice by shaking thoroughly for 5 min with 20 mL of water in order to remove the acetone. The organic layer was cleaned up using dual-layer Florisil/Na2SO4 columns (Supelco, USA). TPH was analysed using a gas chromatograph (Hewlett-Packard 6890, USA) equipped with a flame ionisation detector (FID) with an Rxi—5 ms capillary column (25 m  0.2 mm ID  0.33 mm); the injection volume was 2 mL and hydrogen was used as the carrier gas (2.1 mL min1). The operation program was started with injector and detector temperatures of 300  C. Oven temperature was initially programmed at 60  C, held for 10 min, increased to 320  C at 30  C min1 and then held for 10 min.

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2.5. Monitoring bacterial strains Estimation of the colony-forming units (cfu) of the rifampicinresistant T0-1 and P-1 strains was performed using the dilutionplate method on Luria-Bertani (LB) agar with the addition of 100 mg mL1 of rifampicin. A suspension of non-inoculated soil plated on LB + rifampicin agar was used as a control and no bacterial growth was observed. 2.6. Quantitative PCR DNA was extracted in three replicates directly from 0.3 g (fresh weight) of soil taken from the pots bioaugmented with the T0-1, P1 and T0-1 + P-1 strains and from the control pots at 1, 7, 42 and 91 d of the experiment. DNA was extracted using a PowerSoil1 DNA Isolation Kit (MO BIO) according to the manufacturer’s instruction. For the quantification of 16S rRNA and alkB gene copies, realtime PCR was performed using the specific primers pE (50 -AAA CTC AAA GGA ATT GAC GG-30 ) and pF (50 -ACG AGC TGA CGA CAG CCA TG-30 ) (Edwards et al., 1989) and alkH1F (50 -CIG IIC ACG AII TIG GIC ACA AGA AGG-30 ) and alkH3R (50 -IGC ITG ITG ATC III GTG ICG CTG IAG-30 ) (Kukla et al., 2014), respectively. The 20 mL reaction mixtures contained buffers supplemented with LightCycler1 480 SYBR Green I Master (Roche Diagnostic, Germany), 0.2 mmol of each primer and 0.2 mg of DNA. The template DNA was amplified and monitored using a LightCycler1 480 Real-Time PCR System (Roche Diagnostics). The amplifications were run at temperature programmes of 10 min at 94  C and 30 cycles of 10 s at 94  C followed by annealing for 20 s at 57  C and extension for 30 s at 72  C for 16S rRNA and 10 min at 94  C and 30 cycles of 1 min at 94  C followed by annealing for 1 min at 55  C and extension for 1 min at 72  C for alkB. Fluorescence data were acquired at the end of each extension step at 81  C in order to avoid detection of primer dimers. For the melting curve analysis of the products, the temperature was raised from 65 to 95  C and the melting temperatures were determined. The DNA standards were prepared from a serial dilution of ready-to-use TA cloning vector pTZ57R/T (Thermo Scientific) carrying the target gene product.

containing a linear denaturing gradient from 45 to 70% (for 16S rRNA) and 55–80% (for alkB) (80% denaturant solution contained 7 M urea and 40% deionised formamide). Gels were run at 200 V, 60  C for 30 min and then at 80 V, 60  C for 17 h. After electrophoresis, gels were stained with a SYBR1Gold nucleic acid gel stain (10 000-fold diluted with 1  TAE buffer, Molecular Probes) for 30 min and photographed using a gel photo system (ChemiDoc, Bio-Rad, Hercules, CA, USA). PCR-DGGE patterns were analysed using BioNumerics software, version 7.5 (Applied Maths, Austin, TX), with which hierarchical cluster comparisons were carried out to group similar profiles and to generate a binary matrix of band classes. All of the images were normalised using external control samples, and the comparison among whole profiles was performed using the Dice similarity coefficient (Dsc). The dendrogram was generated using the method of an unweighted pair group with mathematical averages (UPGMA) at 0.5% position tolerance. 2.8. PLFA and CLPP analyses PLFAs were isolated from 2 g of soil as described by Pennanen et al. (1999). The fatty acid methyl esters were separated and identified according to Płociniczak et al. (2013). The sum of 16:1v9, 16:1v7t, cy17:0 18:1 v7, cy19:0 and i15:0, a15:0, i16:0, i17:0, a17:0 was used to determine the biomass of Gram-negative (GN)  et al., 2013). and Gram-positive (GP) bacteria, respectively (Cycon Community-level physiological profiles were assessed using a Biolog EcoPlateTM system (Biolog Inc., CA, USA) according to  et al. (2013) using Biolog MicroStationTM microplate Cycon reader. Each 96-well plate was inoculated with 125-ml aliquots of soil suspensions (101 dilution in a 0.85% NaCl solution) and then incubated at 24  C in the dark. The readings were taken at 590 nm after inoculation and at 12 h intervals for 168 h using a microplate reader (Biolog MicroStationTM). The absorbance values were used to calculate the following microbial indices: substrate richness (Rs), functional diversity based on the Shannon-Wiener biodiversity index (H0 ) and evenness (I0 ). Moreover, kinetic analysis was performed using AWCD (Average Well Colour Development) data.

2.7. DGGE analysis 2.9. Statistical analysis The universal bacterial primers MF341-GC (50 -CGC CCG CCG CGC CCC GCG CCC GTC CCG CCG CCC CCG CCCG CCT ACG GGA GGC AGC AG-30 -GC clamp underlined) (Muyzer et al., 1993 modified, Muyzer and Smalla, 1998) and MR907 (50 -CCG TCA ATT CMT TTG AGT TT-30 ) (Ishii et al., 2000 modified), which target the V3V5 region of the 16S rRNA gene were used to amplify fragments of about 570 bp. The alkB sequences (549 bp) were amplified using the primers alkH1FGC (50 CGC CCG CCG CGC CCC GCG CCC GTC CCG CCG CCC CCG CCCG CIG IIC ACG AII TIG GIC ACA AGA AGG-30 -GC clamp underlined) and alkH3R (50 -IGC ITG ITG ATC III GTG ICG CTG IAG-30 ) (Kukla et al., 2014). The PCR reactions were run in a C1000 TouchTM Thermal Cycler (BioRad) with a mixture containing a 10  reaction buffer (DyNAzyme, including 1.5 mM MgCl2, Finnzymes), 200 mM of dNTP, 0.2 mM of each primer, 1U of DyNAzyme II DNA polymerase (Finnzymes) and 0.2 mg of DNA. PCR amplification was performed at 94  C for 5 min and 35 cycles of 20 s at 94  C followed by annealing for 20 s at 56  C and an extension step of 30 s at 72  C then a final extension for 5 min at 72  C for 16S rRNA and 94  C for 5 min and 31 cycles of 1 min at 94  C followed by annealing for 1 min at 55  C and an extension step of 1 min at 72  C and then a final extension for 3 min at 72  C for alkB. DGGE analysis of the amplified products was performed using a DCodeTM Universal Mutation Detection System (Bio-Rad, Hercules, CA, USA). The PCR products were loaded onto 6% (w/v) polyacrylamide gels in a 1  Tris-acetate-EDTA buffer (pH 7.4)

Statistical analysis was done using STATISTICA 10.0 PL software (StatSoft, Tulsa, USA). Analysis of variance (ANOVA) followed by a post-hoc comparison of means using the least significant difference (LSD) test was carried out to estimate the statistical significance of any differences in the data that was measured. Heatmaps and hierarchical clustering were performed using the MetaboAnalyst 3.0 software based on the Euclidean distance measure and the Ward clustering algorithm (Xia et al., 2015). For the pot experiments, data were represented as mean  standard deviation (SD) of 3 replicates.

Table 2 Concentration and removal of TPH in bioremediation treatments. Treatment

TPH concentration (mg kg1)

TPH removal (%)

Control (0 days) Control (91 days) T0-1 (91 days) T0-1 + P-1 (91 days) P-1 (91 days)

7776  80b 7720  101b 7340  68c 6602  299a 7401  122c

– 0.7 5.6 15.1 4.8

Values within a column followed by the same letter are not significantly different at P < 0.05  Stand. Dev. of three independent experiments.

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3. Results 3.1. TPH removal and the survival of introduced strains The contaminated soil had a high initial TPH concentration (7775.67 mg kg1 dw of soil). The TPH concentration did not decrease significantly (P > 0.05) in the control soil during the 91day experiment. At the end of the experiment, significant TPH removal was observed for all of the bioaugmented soils. However, bioaugmentation of soil with the consortium of strains (T0-1 + P-1) resulted in a three times greater TPH removal (P < 0.05) than in the soils treated with single strains of P-1 and T0-1 (Table 2). The GCFID chromatograms of hydrocarbon compounds (data not shown) extracted from the analysed soil gave qualitative information on the composition of the petroleum contamination. Analysis of contamination profiles showed domination of C20-40 hydrocarbons, a major component of the lubricating oil. It has been also noticed that studied pollution contained only a small amounts of C10-20 hydrocarbons. Peak patterns of the GC chromatograms obtained from the inoculated soils on day 91 revealed the highest reduction in the peak area of hydrocarbons with retention times characteristic for hydrocarbons with the range of C22-28. Rifampicin-resistant T0-1 and P-1 strains were used to check the ability of the inoculants to survive in contaminated soil. It was observed that both strains, which were introduced as single strains as well as their consortium, survived in the soil during the experimental period. Counting of bacteria in the soil 1 day after bioaugmentation with single strains T0-1 and P-1 showed that the number of their cells decreased from 1.21 107 cfu g1 of dry soil (calculated on the basis of the inoculum) to 9.16  106 and 6.85  105 cfu g1 of dry soil, respectively. In the soil treated with the consortium, the number of T0-1 and P-1 cells 1 day after inoculation decreased from 6.05  106 cfu g1 of dry soil (calculated based on the inoculum) to 2.91 106 and 1.12  106 cfu g1 of dry soil, respectively. In the next weeks the number of bacterial cells increased in all of the studied setups, in comparison to day 1, and remained at a level of about 1.10  107 and 4.5  106 cfu g1 of dry soil in the soils treated with T0-1 and P-1, respectively, until the end of the experiment. In soil bioaugmented with T0-1 + P-1, the numbers of inoculants reached values of about 5.95  106 and 2.5  106 cfu g1 of dry soil in soils for T0-1 and P-1 cells, respectively (Fig. S1 in Supplementary material).

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the experiment, no significant (P < 0.05) differences in the number of 16S rRNA gene copies were observed in the soils treated with T01 and T0-1 + P-1, whereas in the soil bioaugmented with the strain P-1, the amount of this gene was statistically (P < 0.05) higher than in the control. Quantification of the alkB gene copies showed a significantly (P < 0.05) higher content of this gene in the soils inoculated with the T0-1 and P-1 strains, as well as those treated with their consortium, compared to the non-treated soil, during whole experimental period (Fig. 1B). No statistically (P < 0.05) important differences in the amount of this gene were observed between all soils inoculated with bacteria on the first part of the experiment. However, such differences appeared in the second part of the studied period. On day 42 the highest number of alkB gene copies was calculated for soil T0-1 and the lowest was estimated for soil P-1. At the end of the experiment the lowest amount of this gene was still observed in the soil treated with strain P-1, however the highest content of alkB gene was estimated for soil bioaugmented with bacterial consortium. 3.3. Impact of the introduced strains on the genetic bacterial diversity Analysis of 16S rRNA and alkB genes-based DGGE fingerprints showed that the profiles of the soils inoculated with the tested strains and their mixture did not differ significantly from the patterns obtained for the non-inoculated control soil at days 1, 7, 42 and 91 of the experiment. The only differences were seen between samples that had derived from different days of the experiment. Cluster analysis (UPGMA) of the DGGE patterns of the PCRamplified 16S rRNA gene fragment obtained at days 7, 42 and 91 showed a separation of the samples into two main clusters

3.2. Impact of the introduced strains on the copy number of 16S rRNA and alkB genes To estimate any changes in the total bacterial number and number of bacteria with the potential to degrade aliphatic hydrocarbons in soil, real-time PCR using primers specific for the genes encoding 16S ribosomal RNA (16S rRNA) and alkane hydroxylase (alkB) was applied. The most significant (P < 0.05) changes in the number of copies of the 16S rRNA gene g1 dry soil were observed in the soils inoculated with bacteria at the beginning of the experiment (Fig. 1A). It was observed that on days 1 and 7 the 16S rRNA gene content was significantly (P < 0.05) higher in the T0-1, P-1 and T0-1 + P-1 treated soils than in the control soil. On these days, statistically (P < 0.05) important differences in the number of gene copies calculated for soils subjected for bioaugmentation process were only observed on day 7. In this day statistically (P < 0.05) higher gene number was estimated for soil treated with strain T0-1, compared with soil inoculated with strain P-1. No significant (P < 0.05) differences were observed in this day between soil treated with consortium T0-1 + P-1 and other soils subjected for bioaugmentation process. The amount of this gene calculated in the soil 42 days after the bacterial inoculation was at the same level compared with non-inoculated soil. At the end of

Fig. 1. Number of 16S rRNA (A) and alkB (B) gene copies in soils during the bioaugmentation experiment. The data presented are the means and standard deviations (SD) of three replicates. Different letters (within each group) indicate significant differences (P < 0.05, LSD test).

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Fig. 2. UPGMA cluster analysis based on the similarity between the DGGE profiles of the PCR-amplified 16S rRNA gene fragments of the bacterial communities from analysed the soils on days 1 (A), 7 (B), 42 (C) and 91 (D).

Fig. 3. UPGMA cluster analysis based on the similarity between the DGGE profiles of the PCR-amplified alkB gene fragments of the bacterial communities from analysed the soils on days 1 (A), 7 (B), 42 (C) and 91 (D).

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based on the structure of their bacterial communities (Fig. 2B–D). The first cluster included all of the inoculated samples. In this cluster soil T0-1 + P-1 was grouped together with soil T0-1 at days 7 and 91 or together with soil P-1 at day 42. The second cluster was composed of DGGE profiles that had derived from the control soil. In the cluster analysis of the DGGE profiles of the 16S rRNA gene fragment one day after the bacterial inoculation, the soils treated with the P-1 and T0-1 + P-1 strains and the control soil generated a common cluster and were separated from the soil bioaugmented with T0-1 strain (Fig. 2A). In the dendrograms that were created from the DGGE profiles of the PCR amplified alkB gene fragment, two major groups (the first composed of T0-1 and T0-1 + P-1 soils and the second containing P-1 and control samples) were obtained at days 1, 7 and 42 of the experiment (Fig. 3A–C). Cluster analysis of the DGGE patterns of alkB gene fragment obtained on day 91 of the bioaugmentation study showed a separation of the soils inoculated with bacteria from the control soil (Fig. 3D). 3.4. Impact of the introduced strains on the structural and functional diversity of microbial communities Analysis of the PLFA profiles showed that the introduction of single strains of T0-1 and P-1, as well as their consortium, into the soil caused short-term shifts in the amounts of fatty acids that are characteristic for Gram-positive (GP) and Gram-negative (GN) bacteria (Fig. 4). The most significant (P < 0.05) changes were observed on day 7, when the biomass of the PLFAs specific for GP and GN bacteria was statistically (P < 0.05) higher in the soils treated with bacteria (T0-1, P-1 and T0-1 + P-1) as compared to the control soil. On this day, the amount of fatty acids characteristic for GP bacteria reached a value of 4.61 nmol g1 soil in control samples, whereas in soils treated with T0-1, P-1 and T0-1 + P1 increased to 6.78; 10.23 and 6.23 nmol g1 soil, respectively. The biomass of PLFAs specific for GN bacteria was estimated on this day at a level of 18.77 nmol g1 soil for non-bioaugmented soil and 24.64; 36.08 and 22.32 nmol g1 soil for soils inoculated with T0-1, P-1 and T0-1 + P-1, respectively. An increase (P < 0.05) in the

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amount of Gram-negative bacterial fatty acids was also observed in the soil treated with strain P-1 on the first day after inoculation. At the end of the experiment in the soil bioaugmented with P-1, the PLFA biomass of Gram-positive bacteria was significantly (P < 0.05) lower than in the control soil, whereas no significant differences (P < 0.05) were observed in the case of the soils treated with the strain T0-1 and the consortium of T0-1 and P-1 strains. Changes in the metabolic activity of the soil microbial communities extracted from the contaminated soil during the bioaugmentation process were evaluated using community-level physiological profiling (CLPP) approach. The percentage of total carbon source utilisation for 31 substrates is presented in a heat map form (Fig. 5). Analysis showed that the substrates whose degradation constituted a high contribution to the total carbon utilisation varied in all of the studied soils in the first part of the experiment. Afterwards, the conformability of metabolic patterns of soils treated with bacteria T0-1, P-1 or T0-1 + P-1 began to increase and 91 days after bacteria inoculation similar substrates were preferably metabolised by microorganisms in these soils (D-Galacturonic Acid, 4-Hydroxy Benzoic Acid, L-Serine, Tween 80 and Glycogen). Due to the fact that such substrates were preferentially degraded, the metabolic profiles of bioaugmented soils clearly separated from the control soil. Moreover, the metabolic activity of soil inoculated with consortium differed from soils treated with single strains. In that case the degradation of L-threonine, phenylethylamine, a-cyclodextrin and D-glucosaminic acid constituted a higher contribution to the total carbon utilisation, compared with soils inoculated with T0-1 or P-1. Analysis of the substrate utilisation patterns of the microorganisms inhabiting the bioaugmented soil showed a significant (P < 0.05) increase in the AWCD value in the soils treated with T0-1, P-1 and T0-1 + P-1 at the beginning and at the end of the experiment, as compared with the non-treated soil. No significant differences were observed in the values of the Shannon-Wiener (H0 ) and substrate richness (Rs) indices between treated and untreated soils during the experimental period. On the other hand,

Fig. 4. The Gram-negative (GN) bacterial biomass and Gram-positive (GP) bacterial biomass expressed as the amount of marker PLFA values in the soils during the bioaugmentation experiment. The data presented are the means and standard deviations (SD) of three replicates. Different letters (within each group) indicate significant differences (P < 0.05, LSD test).

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Fig. 5. Heatmap visualisation of the percentage of total carbon source utilisation for 31 substrates. Hierarchical clustering was performed based on the Euclidean distance and the Ward clustering algorithm.

Table 3 The values of the biodiversity indices for the 31 sole carbon source substrates of the ECO plates. 0

Day

Sample

AWCD

H

Rs

EH

1

T0-1 T0-1 + P-1 P-1 Control

0.24  0.01a 0.23  0.01a 0.23  0.01a 0.21  0.02b

1.25  0.04a 1.26  0.03a 1.25  0.03a 1.22  0.01a

26.33  1.53a 27.33  2.31a 25.33  2.08a 27.00  2.00a

0.85  0.04a 0.88  0.01a 0.89  0.03a 0.85  0.02a

7

T0-1 T0-1 + P-1 P-1 Control

0.22  0.02a 0.22  0.01a 0.23  0.02a 0.25  0.02a

1.28  0.06a 1.24  0.06a 1.27  0.04a 1.27  0.04a

27.00  3.61a 26.33  3.06a 27.33  3.06a 26.00  1.73a

0.90  0.02a 0.87  0.02a 0.88  0.01a 0.90  0.01a

42

T0-1 T0-1 + P-1 P-1 Control

0.24  0.05a 0.25  0.04a 0.24  0.02a 0.27  0.05a

1.25  0.04a 1.27  0.06a 1.28  0.06a 1.25  0.06a

24.67  3.06a 26.33  4.04a 28.00  2.65a 26.00  2.65a

0.90  0.01a 0.89  0.02a 0.89  0.02a 0.88  0.03a

91

T0-1 T0-1 + P-1 P-1 Control

0.26  0.04a 0.26  0.04a 0.29  0.03a 0.18  0.04b

1.15  0.06b 1.20  0.07ab 1.27  0.01a 1.20  0.04ab

22.33  4.04a 24.33  4.16a 25.67  2.08a 27.33  2.08a

0.86  0.01bc 0.88  0.02ab 0.90  0.02a 0.84  0.01c

Values within a column and sampling days followed by the same letter are not significantly different at P < 0.05,  Stand. Dev. of three independent experiments.

statistically (P < 0.05) higher values of the evenness (EH) index were calculated for soils inoculated with P-1 or T0-1 + P-1 bacteria, in comparison to the results obtained for control soil on day 91 of the experiment (Table 3). 4. Discussion 4.1. TPH removal and the survival of introduced strains In the presented study, we investigated the impact of the introduction of hydrocarbon-degrading and biosurfactant-producing single strains T0-1 and P-1 and their consortium on the structure of the autochthonous microbial communities in soil contaminated with petroleum hydrocarbons during the bioremediation process. We observed that at the end of the experiment, the TPH concentration in all of the bioaugmented soils was statistically lower, as compared to the non-treated control soil. Additionally, we observed that TPH loss in soil after the introduction of the bacterial consortium (T0-1 + P-1) was significantly (P < 0.05) higher compared to the soils treated with single T0-1 or P-1 strains. Many studies indicated that the application of bacterial consortia for bioaugmentation of hydrocarbon-polluted soils resulted in efficient hydrocarbon removal (Mao et al., 2012; Chia et al., 2013; Suja et al., 2014; Szulc et al., 2014). This is considered due to the fact that intermediates of a catabolic pathway of one strain may be further

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degraded by other strains possessing suitable catabolic pathway (Mrozik and Piotrowska-Seget, 2010). For example, Jacques et al. (2008) observed much higher efficacy of anthracene degradation in artificially contaminated soil by defined microbial consortium of six strains (Mycobacterium fortuitum, Bacillus cereus,Microbacterium sp., Gordonia polyisoprenivorans, Microbacteriaceae bacterium and a fungus Fusarium oxysporum) as compared with the efficiency of any bacterial or fungal isolates from this consortium when used separately. However, not in all cases bioaugmentation with bacterial consortia brings better effect in comparison to use of single strains (Hassanshahian et al., 2014; Festa et al., 2016). For example in bioaugmentation experiment conducted by Festa et al. (2016) a significant higher degradation rate of phenanthrene was observed when single Sphingobium sp. AM strain was used in comparison to application of bacterial consortium. These results suggest the presence of unfavourable interactions between the bacterial genera that are the component of consortium. In our studies not very high efficiency of the bioaugmentation process was observed. This could be due to the very high initial concentration of TPH in studied soil. As reported by Margesin et al. (2007), the content of TPH in soil has a significant impact on the loss of these compounds during the bioremediation process. The authors observed that relative TPH losses were significantly higher in the soils with low initial TPH amount. The low rate of petroleum compounds degradation can be also caused by the fact, that the main component of pollution was a lubricating oil. Since it contains long chain (C16-36) saturated hydrocarbons and more than 75% cyclic alkanes, it is known to be recalcitrant to microbial degradation. In addition, due to the presence of toxic metals, PAHs, etc. in lubricating oil, the microbial degradation of this contaminant is inhibited (Bhattacharya et al., 2015). Another factor that could have affected the efficiency of the TPH removal was the very low value of pH in the used soil since bacterial degradation of hydrocarbons is favourable in pH values of around 7 (Margesin and Shinner, 2001). It was found that the biodegradation of organic compounds also proceeds well in natural acidic environments (with pH values of 4.5–5), but when the pH value has changed, for example by industrial activity degradation of these compounds is disturbed (Norris et al., 1994). Hua et al. (2014), who studied effect of physical environmental factors on the trans-membrane transport of octadecane in hydrocarbon-degrading Pseudomonas sp. DG17, observed that in strongly acidic conditions, the transport and degradation of this hydrocarbon was blocked. One of the most important factor that determine the final results of bioaugmentation is the survival of the inoculants in the polluted soil (Ramos et al., 1991). It has been reported by many authors (van Elsas et al., 1986; Mrozik et al., 2011; Płociniczak et al., 2013) that the number of bacteria introduced into the soil decreases immediately after inoculation. In our studies, the number of introduced single strain T0-1 and P-1 bacteria as well as their consortium T0-1 + P-1 decreased during the first day however, afterward the number of inoculants increased and remained at a stable level until the end of the experiment. A similar observation was made by Nasseri et al. (2010), who investigated the impact of the bioaugmentation technique on the removal of PAHs in contaminated soil. They reported an initial decrease in the number of introduced Pseudomonas strains and then a four- to sixfold increase in the number of inoculants. Observed in our studies the stable number of inoculants in the soil might be due to the fact that the strains were isolated from tested soil. Bioaugmentation approach with using of autochthonous microflora is now increasingly recommended since such bacteria may overcame barriers related with field conditions and nutrient concentrations (Nikolopoulou et al., 2013).

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4.2. Impact of the introduced strains on the copy number of 16S rRNA and alkB genes The other very important factor that can influence the success of bioaugmentation is the interaction between the indigenous populations of microorganisms and introduced strains. In studies on the bioremediation of hydrocarbon-contaminated sites (Baek et al., 2009; Vázquez et al., 2009), monitoring the changes in the copy number of selected genes in the soil during the experimental period was carried out in order to analyse any changes in the total bacterial population (16S rRNA) and in the microbial population bearing catabolic genes for the enzymes potentially involved in the degradation of hydrocarbons (alkB, nahAc). In our experiment, the introduction of the single strains T0-1 and P-1 and their mixture into hydrocarbon-contaminated soil led to 1.9-2.5-fold and 1.4-1.7fold increase in the number of 16S rRNA gene copies in this environment on days 1 and 7 of the experiment, respectively, in comparison to the non-treated soil. A large increase in the copies of 16S rRNA gene at the beginning of the experiment, which exceeded the number of introduced strains, could be due to the fact that the bacterial cells that did not survive after introduction into contaminated soil could have become a source of nutrients for the indigenous microflora. It has been proven that microbial biomass residues (necromass) constitute a significant source of soil organic matter (Miltner et al., 2012). Therefore, the enhanced growth of autochthonous microorganisms could be the result of the delivery of readily available carbon sources. After the depletion of these nutrients, the number of 16S rRNA gene copies stabilised at the level estimated for the control soil. On days 1 and 7 the number of the alkB gene in the bioaugmented soils was the sum of the autochthonous and vital introduced bacteria. A significant increase in the number of copies of this gene was observed in the soils treated with T0-1, P-1 and T0-1 + P-1 at days 42 and 91 of the experiment. Since Li et al. (2009) reported enhanced biodegradation of PAHs in contaminated soil 30 days after introduction of a microbial consortium, we suggest that the increase in the number of copies of the alkB gene in the second part of the experiment could be related to the proliferation of bacteria containing alkB gene in the tested soil. In our studies in soils treated with single strains the decrease in the alkB gene content was observed on day 91, compared with the day 42. In turn, in soil treated with consortium from day 42 the number of alkB gene copies remained at high level until the end of the experiment. Our results suggest that the high amount of genes encoding enzymes involved in hydrocarbon degradation is responsible for the higher hydrocarbon removal in consortium treated soil as compared with soils inoculated with T0-1 or P-1. 4.3. Impact of the introduced strains on the genetic bacterial diversity The introduction of the T0-1, P-1 and T0-1 + P-1 strains into the soil contaminated with hydrocarbons changed the genetic diversity of the total bacterial communities. Differences between the profiles deriving from the bioaugmented and non-bioaugmented soils were already observed at day 7 after the bacterial inoculation. Shifts in the composition of the microbial population in the hydrocarbon-contaminated soil that had been inoculated with bacteria were also reported by Viñas et al. (2005). However, the changes observed in the 16S rRNA DGGE profiles only appeared after day 200 of the experiment. Nimnoi et al. (2011) also observed no distinguishable changes in the DGGE profiles of the 16S rRNA gene obtained from the rhizosphere soils after the inoculation with bacterial strains. However, Federici et al. (2011) observed that augmentation of heavy metal and aromatic hydrocarbon-contaminated soil with Lentinus tigrinus led to an increase in the number of bands in the DGGE patterns of 16S rRNA fragments, which

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indicated increased bacterial diversity in this soil during a 60-daylong experiment. Our results and cited literature suggest that changes in bacterial community structure (16S rRNA) are necessary to increase the rate of hydrocarbon removal from soil. However, Festa et al. (2016) showed significant hydrocarbon elimination in soils bioaugmented with single strain or consortium of five strains, although the changes in the bacterial biodiversity were only observed when single strain was used. It has been recommended by many authors that changes in the structure of the hydrocarbon-degrading bacterial communities should also be investigated in soils that have been contaminated with hydrocarbons and subjected to bioaugmentation (Vázquez et al., 2009; Yergeau et al., 2009). In our studies the DGGE analysis of alkB gene fingerprints showed that the introduction of T0-1, P1 and T0-1 + P-1 strains into contaminated soil induced shifts in the population bearing genes involved in the degradation of alkanes. The changes in alkB profiles differed between bioaugmented soils during first 42 days. Afterward, it was observed that the structure of bacterial communities from soils T0-1 and P-1 was more similar than between them and T0-1 + P-1 soil. This suggest that application of consortium caused shifts that increased the catabolic potential of soil to the greatest extent. DGGE analysis of alkB gene patterns showed that this community was less numerous and diverse than the community of total bacteria in this soil, which is in agreement with the results of Baek et al. (2007) who reported that not all of the bacterial population in the soil contaminated with crude oil was able to degrade alkanes. 4.4. Impact of the introduced strains on the structural and functional diversity of microbial communities Relationship between introduced strains and the autochthonous bacterial communities in the soil contaminated with hydrocarbons subjected to the bioaugmentation process was also studied using the PLFA and CLPP approaches. The PLFA study showed that the soil used in our experiment was dominated by Gram-negative bacteria. The predominance of GN bacteria within the microbial community in oil-contaminated soil was also reported by other authors (MacNaughton et al., 1999; Margesin et al., 2007). The introduction of Gram-positive T0-1 and Gram-negative P-1 strains, as well as their mixture, caused a significant increase in the amount of PLFAs specific for both GP and GN bacteria only at the beginning of the experiment (7 days). These results indicate that the bacteria used in our studies did not exert a long-lasting effect on the autochthonous bacterial community, which may result from the fact that they were members of the existing population. Similarly, the slight changes in the PLFA patterns that were obtained from the PAH-contaminated sediments bioaugmented with a bacterial consortium including Paenibacillus validus PR-P1, Sphingomonas spp. PR-P12 and Arthrobacter spp. PR-P3 strains were observed by Launen et al. (2002). Lack of differences in PLFA profiles in comparison to DGGE and qPCR methods showed that molecular methods are more sensitive and valuable for monitoring changes in the structure of bacterial communities in soil subjected for bioaugmentation. However, in some cases the introduction of bacteria to soil contaminated with hydrocarbons may affect the PLFA profiles. For example, Zhang et al. (2011) reported that the introduction of two PAH-degrading microorganisms (Bacillus sp. and Fusarium sp.) into PAH-polluted soil led to a distinct increase in the amount of fatty acids specific for GP bacteria over the course of the study. The analysis of community level physiological profiles (CLPP) of the cultivable bacterial communities indicated differences in the soil metabolic activity between the inoculated and non-inoculated soils after the bioaugmentation process. We observed a significant

increase in the microbial activity at the end of the bioremediation experiment, expressed as the average well colour development (AWCD), in the soils treated with T0-1, P-1 and T0-1 + P-1. In these samples, changes in the types of substrates that were preferably degraded by soil bacteria were also reported. Higher values of AWCD in the PAH-contaminated soil treated with Paracoccus sp. HPD-2 strain after the experimental period, in comparison to the control soil, was also observed by Teng et al. (2010). Moreover, they reported a higher microbial functional diversity based on the Shannon-Wiener index in the soil subjected to bioaugmentation. In turn, Alisi et al. (2009) noticed that the values of both AWCD and RS were higher in the soil contaminated with diesel oil 42 days after the introduction of a bacterial consortium, compared to the noninoculated soil. In our studies we did not observe any significant changes in the microbial functional diversity or in the richness of the metabolised substrates, expressed as Shannon-Wiener and Rs indexes, respectively. However, we did find that EH, which is a measure of the uniformity of substrate utilisation, was statistically higher in the soils treated with the P-1 and T0-1 + P-1 strains, compared with the control soil. The obtained result indicates that the introduction of bacterial strains, independently of the treatment, into petroleum-contaminated soil enhances the activity of the bacterial communities towards hydrocarbon degradation in tested soils. 5. Conclusions The results of presented studies showed that the application of B. subtilis T0-1 and Pseudomonas sp. P-1 consortium had a greater potential to enhance the bioremediation of petroleum-contaminated soil than any of those strains used alone. It was also observed that all of the tested strains had the ability to survive in the contaminated environment during the experimental period. We did not observe any changes in the structural diversity of the bacterial communities in the soils inoculated with the T0-1, P-1 or T0-1 + P-1 strains. However, the shifts in the genetic diversity of the total bacterial communities and communities that had the genes involved in the degradation of hydrocarbons, as well as the increased number of alkB gene copies, enhanced metabolic activity and changes in the utilisation of selected substrates in the treated soils, were reported. Our results supported the thesis that bioaugmentation cause the shifts in microbial communities that promote removal of TPH and increase the number of genes coding enzymes involved in hydrocarbon degradation. Acknowledgments The research was supported by grant No. 2011/03/N/NZ9/02089 financed by the National Science Centre (Poland). The author MPP would like to thank Tomasz Płociniczak for his support with the GC analysis, Małgorzata Pawlik for her help with preparing the standards for qPCR and Sławomir Sułowicz and Sławomir Borymski for their assistance with the statistical analysis. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j. apsoil.2016.04.005. References Abioye, O.P., 2011. Biological remediation of hydrocarbon and heavy metals contaminated soil. In: Pascucci, S. (Ed.), Soil Contamination. In Tech, Rijeka, pp. 127–142. Alisi, C., Musella, R., Tasso, F., Ubaldi, C., Manzo, S., Cremisini, C., Sprocati, A.R., 2009. Bioremediation of diesel oil in a co-contaminated soil by bioaugmentation with

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