Chemosphere 120 (2015) 100–107

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Occurrence of Pseudomonas aeruginosa in Kuwait soil Esmaeil AL-Saleh ⇑, Abrar Akbar Microbiology Program, Department of Biological Sciences, Faculty of Science, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait

h i g h l i g h t s  Factors resulting in the dominance of P. aeruginosa in different soil types in Kuwait was demonstrated.  Dominant P. aeruginosa showed high rates of oil utilization and tolerance to metals.  Unculturable P. aeruginosa in soil showed higher stability compared to the culturable fraction.

a r t i c l e

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Article history: Received 22 October 2012 Received in revised form 16 June 2014 Accepted 16 June 2014

Handling Editor: Tamara S. Galloway Keywords: Pseudomonas aeruginosa Biodegradation Crude oil Pollution Unculturable bacteria Phylogenetic

a b s t r a c t Environmentally ubiquitous bacteria such as Pseudomonas aeruginosa evolved mechanisms to adapt and prevail under diverse conditions. In the current investigation, strains of P. aeruginosa demonstrating high rates of crude oil utilization and tolerance to high concentrations of heavy metals were found in both crude oil-contaminated and uncontaminated sites in Kuwait, and were dominant in the contaminated sites. The incidence of P. aeruginosa in tested soils implies the definitive pattern of crude oil contamination in the selection of the bacterial population in petroleum-contaminated sites in Kuwait. Surprisingly, the unculturable P. aeruginosa in different soil samples showed significant high similarity coefficients based on 16S-RFLP analyses, implying that the unculturable fraction of existing bacterial population in environmental samples is more stable and, hence, reliable for phylogenetic studies compared to the culturable bacteria. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Crude oil is considered the main energy source worldwide. Accidental discharge of crude oil into the environment occurs frequently during petroleum production (Paine et al., 1996). Such discharges do cause damage to the ecosystems (Briggs et al., 1996), and constitute health hazards (Lipscomb et al., 1993, 1994). Bioremediation has proved to be a promising approach for the clean-up of crude oil pollution (Sohal and Srivastava, 1994; Alexander, 1999). It is a complex process that depends mainly on the composition of environmental microbial communities, their adaptive response to pollution and prevailing environmental conditions. Microbial communities within crude oil-contaminated sites are dominated by bacteria showing high rates of crude oil utilization and high adaptability to existing environmental conditions (AL-Saleh and Obuekwe, 2005; Obuekwe et al., 2009; AL-Saleh et al., 2009) which eventually influence the structure of the

⇑ Corresponding author. Tel.: +965 24985652; fax: +965 24847054. E-mail address: [email protected] (E. AL-Saleh). http://dx.doi.org/10.1016/j.chemosphere.2014.06.031 0045-6535/Ó 2014 Elsevier Ltd. All rights reserved.

microbial communities rendering it less diverse (Macnaughton et al., 1999). Previous studies based on culture-dependent techniques on Kuwait soils demonstrated the presence of culturable indigenous oil-degrading bacterial genera such as Bacillus, Paenibacillus, Pseudomonas, Rhodococcus and Streptomyces (AL-Saleh et al., 2009; Obuekwe et al., 2007, 2009; Radwan et al., 1995). Such isolates were shown to have high potentials for hydrocarbon bioremediation (Obuekwe and AL-Zarban, 1998; AL-Saleh and Obuekwe, 2005; Obuekwe et al., 2009). However, the applications of culture-dependent techniques can lead to inaccurate descriptions of microbial diversity and functionality (Zak et al., 1994; Torsvik et al., 1998; Ellis et al., 2003; Neufeld and Mohn, 2006) because unculturable microorganisms represent the larger fraction of microbial communities (Islam et al., 1993; Janssen, 2006). Any apparent microbial activity determined in environmental samples should be attributed to the actual communities present, including the unculturable microorganisms (Colwell and Grimes, 2000). Additionally, inaccurate description of crude oil-degrading microbial communities and their biodegradative potentials deduced from the application of culture-dependent techniques could result

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in imprecise and prolonged management of contaminated sites (Hawumba et al., 2010). The application of molecular methods is expected to solve the problems of inadequate characterization of isolated bacteria owing to the inability of culture-dependent techniques to differentiate among closely related species that metabolize a similar range of substrates (Stackebrandt and Ebers, 2006). Strains of Pseudomonas aeruginosa capable of growing on crude oil have frequently been isolated from various Kuwait environments (Obuekwe et al., 2008; AL-Saleh et al., 2009) which suggested that the members of the genus must be playing a major role in the bioremediation of crude oil contamination in Kuwait environment. Therefore, the objective of the current study was to assess the diversity of the dominant members of crude oildegrading bacterial community, in particular P. aeruginosa in crude oil-contaminated and uncontaminated sites in south of Kuwait using traditional and molecular approaches. 2. Materials and methods 2.1. Sampling site Samples were collected from the Burgan oil field, located in the desert of south-eastern Kuwait (Fig. 1). The field has been producing petroleum for over sixty years resulting in an area extensively polluted from oil released from petroleum production activities, while patches of apparently unpolluted sites were scattered over the field. Having been subjected to crude oil pollution for more than sixty years and under constant threat of pollution from production activities, the area was considered an appropriate site to investigate the effects of crude oil pollution on microbial community. 2.2. Soil sampling Soil samples were collected from the upper 10 cm of each of ten distantly-located locations (approximately 500 m apart). Collected soils were sandy loam characterized by brownish-black coloration and oily feel to the touch, due apparently to crude oil contamination. Similarly, ten samples were also collected from other locations in the visibly uncontaminated sites in the same general area. All soil samples were collected in sterile 1 L screw-capped bottles, kept in ice and transported immediately to the laboratory for immediate analyses, or stored at 20 °C in the case of samples

101

which would be used for molecular analyses. Chemical and microbiological analyses of all samples were completed within 48 h after collection. Oxygen contents of samples were analysed on site. In the current study, the terms contaminated and uncontaminated soil samples were used to indicate crude oil-contaminated and crude oil-uncontaminated soil samples. 2.3. Characterizations of soil samples Values of electrical conductivity, dissolved oxygen (DO), salinity and pH of soil samples were determined using Water Quality Checker (Horiba U-10, Horiba Instruments Limited, Northampton, UK) following standard methods (Alef and Nannipieri, 1995). For this purpose, the probe was calibrated with the appropriate standard solutions using the auto one-point calibration method following the manufacturer’s instructions. The calibrated probe was inserted into locations with high water content and pebblefree soils. Measurements were taken after stabilization of the quality checker reading. The method of Forster (1995) was adopted for the determination of total organic carbon (TOC). In brief, TOC was determined in a TOC analyser (Shimatzu, TOC 5000A with SSM 5000A module, Shimadzu Scientific Instruments, Columbia, USA) according to the NF ISO 10694 standard. TOC values were obtained by subtracting inorganic carbon (IC) from total carbon (TC). The concentrations of metals present in soil samples were determined following the method of Rowell (1994). Briefly, soil samples were acid-digested (130 mL conc. HCl and 120 mL water, of this solution 150 mL was added to 50 mL HNO3 and mixed) with heating in a reflux tube. The concentration of metals in the filtered, digested material was determined using flame atomic absorption spectroscopy and graphite furnace atomic absorption spectrometry (Varian AA-1475, California, USA), atomizing the metals with acetylene-air (1:1) flame. 2.4. Isolation and enumeration of bacteria in soils The culturable fractions of the crude oil-degrading bacteria (CODB) in soil samples were enumerated using minimal agar following standard serial dilution method (AL-Saleh and Obuekwe, 2005). Crude oil was supplied in the vapor phase, and plates were incubated inverted at 30 °C for up to 21 d. Grown colonies were counted, expressed as colony-forming unit (cfu) g 1soil, picked

Fig. 1. Map of Kuwait showing site of Burgan oil field and sampling locations. The map is adapted from Saif ud din et al. (2008).

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Table 1 Physico-chemical characteristics of representative soil samples. Crude oil contaminated soil

pH Conductivity (mS cm DO (g kg 1) Salinity (%) TOC (%) Metals (mg kg 1)

1

)

Al As Cd Cr Fe Mg Mn Ni Pb Zn

Crude oil uncontaminated soil

Location 1

Location 2

Location 3

Location 1

Location 2

Location 3

6.80 ± 0.29 45.70 ± 1.15 3.13 ± 0.27 2.33 ± 0.22 2.30 ± 0.11 1886.00 ± 0.04 2.70 ± 0.05 4.53 ± 0.04 44.20 ± 0.04 2721.00 ± 0.09 216.50 ± 0.08 682.30 ± 0.05 89.30 ± 0.05 111.40 ± 0.04 164.00 ± 0.05

6.62 ± 0.27 46.50 ± 1.22 3.23 ± 0.24 2.29 ± 0.20 2.15 ± 0.12 1907.00 ± 0.05 1.90 ± 0.04 3.80 ± 0.05 41.40 ± 0.03 2750.00 ± 0.08 222.50 ± 0.07 717.20 ± 0.06 81.90 ± 0.04 113.80 ± 0.06 166.00 ± 0.07

6.54 ± 0.29 45.10 ± 1.21 2.92 ± 0.24 2.32 ± 0.12 2.22 ± 0.10 1916.00 ± 0.04 2.10 ± 0.04 4.71 ± 0.05 43.00 ± 0.03 2915.00 ± 0.09 229.00 ± 0.08 676.00 ± 0.05 87.60 ± 0.06 116.10 ± 0.06 172.00 ± 0.05

7.21 ± 0.27 41.80 ± 1.25 7.43 ± 0.25 1.80 ± 0.22 0.35 ± 0.10 1940.00 ± 0.05 1.10 ± 0.05 3.70 ± 0.04 39.20 ± 0.04 2542.00 ± 0.07 210.10 ± 0.09 347.10 ± 0.04 45.10 ± 0.05 18.30 ± 0.05 145.00 ± 0.06

7.22 ± 0.29 40.50 ± 1.21 7.89 ± 0.27 1.78 ± 0.22 0.38 ± 0.12 1904.00 ± 0.04 1.00 ± 0.04 3.54 ± 0.04 36.70 ± 0.03 2572.00 ± 0.08 225.30 ± 0.08 335.70 ± 0.06 45.60 ± 0.05 20.10 ± 0.04 182.00 ± 0.07

7.14 ± 0.27 40.80 ± 1.18 7.78 ± 0.24 1.76 ± 0.17 0.31 ± 0.10 1915.00 ± 0.05 1.10 ± 0.04 3.81 ± 0.05 34.90 ± 0.03 2619.00 ± 0.09 222.60 ± 0.08 356.00 ± 0.05 45.70 ± 0.06 17.70 ± 0.05 173.00 ± 0.05

Data from three sampling locations out of ten for each of the contaminated and uncontaminated sites are displayed. Mean values for three replicates (n = 3) are shown with their corresponding standard deviations.

and re-streaked on nutrient agar plates for purification. Grown pure cultures were stored in 15% Luria–Bertani broth–glycerol at 70 °C. The culturable fractions of the total heterotrophic bacteria (THB) in soil were counted using standard plate dilution method and nutrient agar medium (Saadoun, 2002; AL-Saleh and Obuekwe, 2005). The counts of THB in soil samples were also determined using real-time PCR following the method of Nadkarni et al. (2002).

endonuclease (New England Biolabs, Hertx, UK) in 12 lL reaction mixtures as recommended by the manufacturer. Digitized restriction patterns of electrophoresed BstUI digests were sorted with Gelcompar II (Applied Maths, Belgium), to group similar patterns. Following each sorting, patterns were compared, and groups of indistinguishable patterns were recorded. Each phylotype was defined as a group of sequences that have indistinguishable BstUI restriction patterns.

2.5. Identification of crude oil-degrading bacteria 2.9. Utilization of crude oil by soil bacteria The 16S rRNA gene was amplified from extracted bacterial DNA by PCR using 27F and 1492R primers. PCR was performed in a thermocycler (Applied Biosystems, Warrington, UK) run on standard program (AL-Saleh et al., 2009). 2.6. Construction of 16S small-subunit rDNA libraries Clone libraries were prepared from 16S rRNA sequences amplified from extracted soil DNA using the above mentioned PCR method. Amplicons were cloned using TOPO TA PCR 2.1 cloning kit (Invitrogen, Life Technologies Ltd, Piasley, UK) and transformed into competent Escherichia coli DH5a. Potential positive clones were blue-white screened and those containing the correct size of insert were stored in 15% Luria–Bertani broth–glycerol at 70 °C for further analysis. Sequencing of positive clones was carried out by using M13 vector-specific primers. 2.7. Sequencing of amplified rDNA The amplified 16S rRNA sequences were sequenced using big dye terminator cycle sequencing kit (Applied Biosystems, Warrington, UK) according to manufacturer’s instructions. Obtained sequences were run against the data bases using the basic alignment search tool (BLAST) and assigned to recognized representatives of the main eubacteria based on scores of 97% or higher. The CODB isolated from crude oil uncontaminated soil samples were designated as CSK strains and those isolated from crude oil contaminated soil samples were designated as SK strains.

The ability of isolated CODB to utilize selected hydrocarbons as sole carbon and energy source was investigated. For this purpose, different aromatic and aliphatic hydrocarbons were supplied in the vapor phase by soaking sterile filter paper (Whatman, No. 1) with 5 drops of 20% of hydrocarbon solution prepared in dichloromethane and placed in the inner surface of the Petri dish lid to fresh bacterial cultures streaked on minimal agar plates. The inoculated plates were then incubated inverted at 30 °C for up to 21 d. Also, crude oil mineralization by soil microbiota was determined using respirometry (AL-Saleh and Obuekwe, 2005; AL-Saleh et al., 2009). The reaction vessels contained 49 mL of minimal medium and 1 mL of washed bacterial inoculum that was previously grown in nutrient broth, washed twice with minimal medium and adjusted to 1 OD600. Crude oil was supplied (200 lL) in the reaction vessels that were incubated at 30 °C with shaking at 300 rpm. The amounts of carbon dioxide evolved were measured using a Micro-Oxymax respirometer (Columbus Instruments, Columbus, USA). Soil samples were bioaugmented with selected CODB and rates of crude oil mineralization were determined. For this purpose, the reaction vessels contained 20 g soil that was first sterilized by autoclaving and the water content was adjusted to 30%. Bacterial inocula were added as mentioned above and reaction vessels incubated in a shaker at 30 °C. The amounts of evolved carbon dioxide were determined as mentioned previously.

2.10. Detection of alkB gene in isolated bacteria 2.8. Restriction fragment length polymorphism analysis of 16S rRNA (16S-RFLP) of isolated crude oil-degrading bacteria Amplified 16S rRNA sequences from extracted bacterial DNA and from clonal libraries were digested separately with BstUI

The gene, alkB, coding for alkane hydroxylase in isolated CODB was detected by PCR. For this purpose eight primer sets were used as described previously, and according to the conditions specified for each primer set (Churchill et al., 1999; Smits et al., 2002).

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E. AL-Saleh, A. Akbar / Chemosphere 120 (2015) 100–107 Table 2 Counts of total heterotrophic (THB) and crude oil-degrading (CODB) bacteria in representative soil samples. Crude oil-contaminated soil

PDM (cfu g 1 soil) RTPCR (gene copies g soil)

THB

CODB (cfu g soil)

1

1

Crude oil-uncontaminated soil

Location 1

Location 2

Location 3

Location 1

Location 2

Location 3

2.26 ± 0.04  109 2.33 ± 0.02  1010

2.48 ± 0.05  109 2.51 ± 0.02  1010

2.51 ± 0.04  109 2.63 ± 0.02  1010

2.15 ± 0.05  107 2.91 ± 0.03  108

2.18 ± 0.04  107 2.23 ± 0.02  108

2.21 ± 0.04  107 2.26 ± 0.02  108

2.59 ± 0.04  108

2.61 ± 0.05  108

2.58 ± 0.04  108

1.92 ± 0.04  106

1.87 ± 0.05  106

1.88 ± 0.05  106

Data from three sampling locations out of ten for each of the contaminated and uncontaminated sites are displayed. Mean values for three replicates (n = 3) are shown with their corresponding standard deviations THB, total heterotrophic bacteria; CODB, crude oil-degrading bacteria; PDM, plate dilution method, RTPCR, real-time PCR.

2.11. Statistical analysis Statistical analyses of the generated data were preformed using Microsoft Excel (MS 2003). Significant differences between the means were determined in one-way ANOVA with a p 6 0.05 and paired samples T-test by means of SPSS (version 15.0) module. Generally, all results are expressed as means calculated from three replicates with their corresponding standard deviations.

from 2.15  107–2.21  107 cfu g 1 soil. These findings were confirmed by real-time PCR which demonstrated the presence of higher 16S rRNA gene copies (2.33  1010–2.263  1010 g 1 soil) in contaminated soils compared to those (2.23  108–2.91  108 gene copies g 1 soil) in uncontaminated soil samples. Counts of CODB in contaminated soils (2.58–2.61  108– 2.61  108 cfu g 1 soil) were significantly higher (p < 0.05) than those (1.87  106–1.92  106 cfu g 1 soil) in the uncontaminated soils.

3. Results 3.2. Isolation and identification of CODB from soil 3.1. Characterization of soil samples Soil samples were characterized to provide the bases for comparing crude oil biodegradative potentials and community structure of the indigenous microbiota in the different soils. Values of dissolved oxygen and pHH2O determined for the contaminated soil samples were significantly different (p < 0.05), and lower than those determined for uncontaminated soil samples (Table 1). Similarly, the values of the conductivity, salinity and TOC of the contaminated soil samples were significantly higher (p < 0.05) than those of uncontaminated soil samples (Table 1). The distribution of heavy metals in soil samples (Table 1) differed. In general, iron, aluminum and manganese were the most abundant metals in both the contaminated and uncontaminated sites and were found to be significantly higher (p < 0.05) than those of any other metal. However, unlike iron and aluminum whose respective concentrations were similar in both types of soil, the concentrations of manganese were significantly higher (p < 0.05) in the contaminated than in the uncontaminated soil samples. The total concentrations of arsenic, cadmium, chromium, iron, manganese, nickel and lead in contaminated soil samples were higher than those determined in uncontaminated soil samples. Bacterial analyses showed that, the differences in THB counts of different soil samples were significant (p < 0.05). The highest counts of THB using plate-dilution method (Table 2) determined for contaminated soils were found to range from 2.26  109– 2.51  109 cfu g 1 soil, while those of uncontaminated soils ranged

The identification of the dominant and frequently occurring colonial forms of culturable, and also the unculturable CODB, originally present in soil samples, (Tables 3 and 4, and Fig. 2) showed that these CODB isolates belonged to only four genera. Of the total of 610 isolated CODB, 430 dominant colonial forms that were recovered from growth plates of contaminated soil samples, 66.3% (285 isolates) were members of the genus Pseudomonas which were mainly (96.5%) P. aeruginosa. Interestingly, all of the 155 detected unculturable clones from contaminated soils were members of P. aeruginosa (Table 3). The other culturable bacteria from contaminated soil samples belonged to Stenotrophomonas maltophilia, Defetia and Paenibacillus spp. The dominant colonial forms (90 isolates) in the uncontaminated soil samples belonged to three different genera, of which members of the Genus Pseudomonas constituted 53% of the total numbers (Table 4). As observed previously in contaminated soils, the unculturable bacteria detected in uncontaminated soils were all members of P. aeruginosa. Also, of the four culturable bacterial genera recovered from contaminated soils, two were dominant and belonged to Pseudomonas and Stenotrophomonas. However, the most predominant of the culturable bacterial genera in the uncontaminated soils were members of Pseudomonas, Streptomyces and Stenotrophomonas. Seven culturable bacterial genera, namely Streptomyces, Achromobacter, Amycolatopsis, Arthrobacter, Kocuria, Microbacterium and Staphylococcus were found in uncontaminated soils but were not detected in contaminated soils. On the other hand, only two

Table 3 Counts and identity of isolated (culturable) dominant colonial forms on culture plates and unculturable CODB from crude oil-contaminated soil. CODB

Number of isolates/clones

Strains designation

Identity

Culturable

275 10 155 10 5 5 Total of 460

SK1–SK275 SK276–SK285 SK286–SK440 SK441–SK450 SK451–SK455 SK456–SK460

Pseudomonas aeruginosa Pseudomonas spp. Stenotrophomonas maltophilia Delftia tsuruhatensis Delftia spp. Paenibacillus pabuli

Unculturable

155 Total of 155

SK461–SK615

Pseudomonas aeruginosa

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Table 4 Counts and identity of isolated (culturable) dominant colonial forms on culture plates and unculturable CODB from crude oil-uncontaminated soil. CODB

Number of isolates/clones

Strains designation

Identity

Culturable

48 6 6 6 6 18 24 6 6 6 6 6 6 Total of 150

CSK1–CSK48 CSK49–CSK54 CSK55–CSK60 CSK61–CSK66 CSK67–CSK72 CSK73–CSK90 CSK91–CSK114 CSK115–CSK120 CSK121–CSK126 CSK127–CSK132 CSK133–CSK138 CSK139–CSK144 CSK145–CSK150

Pseudomonas aeruginosa Pseudomonas frederiksbergensis Pseudomonas syringae Pseudomonas stutzeri Pseudomonas spp. Stenotrophomonas maltophilia Streptomyces marokkonensis Achromobacter xylosoxidans Amycolatopsis orientalis Arthrobacter spp. Kocuria spp. Microbacterium resistens Staphylococcus haemolyticus

Unculturable

58 Total of 58

CSK151–CSK208

Pseudomonas aeruginosa

culturable bacterial genera, Delftia and Paenibacillus found in contaminated soils, were not detected in uncontaminated soils. 3.3. Utilization of hydrocarbons by isolated CODB Crude oil mineralization rates were significantly higher (p < 0.05) among the representative dominant bacteria isolated from contaminated soils compared to those bacteria isolated from uncontaminated soil samples (Table 5). The representative dominant isolates used for the mineralization produced carbon dioxide from crude oil at rates that ranged from 0.11 to 37.5 lg min 1, while the isolates from uncontaminated sites produced carbon dioxide at rates that ranged from 0.01 to 0.45 lg min 1. There was a wide variation in the mineralization rates among members of the same species grown on crude oil, especially among the members of P. aeruginosa isolated from both contaminated and uncontaminated soils. The amendment of soils with CODB isolated from crude oil contaminated samples resulted in significantly higher (p < 0.05) mineralization rates (0.06–4.82 lg CO2 min 1 g 1 soil) than those (0.01–0.05 lg CO2 min 1 g 1 soil) obtained with CODB from uncontaminated soils (Table 5). Interestingly, isolates of P. aeruginosa were not able to utilize short-chain aliphatic hydrocarbons

(C9–C10), but almost all P. aeruginosa isolates (92.8–100%) grew readily on aliphatic hydrocarbons with chain lengths that ranged from C12 to C32. Screening of isolated P. aeruginosa strains for the presence of alkane hydroxylase (alkB) gene showed the higher (67.3%) prevalence of alkB gene in CODB isolated from contaminated soils when compared to that (41.7%) in uncontaminated soil. Growth of P. aeruginosa isolates on aromatic hydrocarbons varied widely (Table in the supplementary material). 3.4. Diversity of isolated CODB Comparison of the 16S rRNA sequences of selected P. aeruginosa isolated from crude oil-contaminated (21 strains) and uncontaminated (12 strains) soil samples showed the high similarity between the 16S rRNA sequences of the strains tested (Fig. 3). Although, P. aeruginosa strains were always isolated from both the contaminated and uncontaminated sites, variation in clonal diversity among these P. aeruginosa strains from the two environments was observed. The 16S-RFLP analyses of selected unculturable P. aeruginosa detected in uncontaminated and contaminated soils revealed the high similarity between the 16S rRNA sequences analysed (Fig. 4). 4. Discussion

Fig. 2. Counts of isolated (culturable) and detected (unculturable) P. aeruginosa and other bacteria in crude oil-contaminated and uncontaminated soils.

In the present study, the effects of existing crude oil pollution on the indigenous microbiota were investigated in contaminated and uncontaminated sites in Kuwait. Some of the chemical and physical characteristics of the soil samples, that can impact the number, and diversity of microorganisms, especially bacteria known to degrade hydrocarbons, were, investigated. Results obtained, shown in Table 3, indicated that several of the biological parameters investigated were significantly different between the contaminated and uncontaminated sites. The significantly (p < 0.05) higher counts of THB, and CODB present in the soil samples of crude oil-contaminated sites compared to the uncontaminated sites are pointers to the effect of crude oil contamination to the Kuwaiti sites. The dominance of P. aeruginosa strains among the bacteria isolated, coupled with the fact that only four genera of bacteria were isolated from oil-contaminated soils, compared to nine genera isolated from non-contaminated soils, indicated the detrimental effect of crude oil contamination on bacterial diversity (Tables 3 and 4, and Fig. 2). Although isolates other than P. aeruginosa from both contaminated and uncontaminated soil could mineralize crude oil, they exhibited mineralization rates that were much lower than most isolates of P. aeruginosa. This observation indi-

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Table 5 Rates of crude oil mineralization (carbon dioxide evolution) by pure cultures and soil-augmented culturable CODB isolated from contaminated and uncontaminated soil samples. Source of bacteria

Bacteria

Strains tested

Rate of carbon dioxide evolution Bacterial pure cultures (ng min

Contaminated soil

P. aeruginosa Paenibacillus pabuli

Uncontaminated soil

P. aeruginosa Staphylococcus haemolyticus Amycolatopsis orientalis Microbacterium resistens

100 5 8 2 2 2

1

)

Soil augmented with bacteria (ng min

37 500 ± 3.10–110 ± 2.50 2120 ± 3.10

4820 ± 3.10–650 ± 3.20 60 ± 2.70

450 ± 2.70–80 ± 2.53 430 ± 2.65 20 ± 2.66 10 ± 2.50

450 ± 2.62–60 ± 2.40 60 ± 2.54 10 ± 2.60 10 ± 2.55

1

g

1

soil)

Mean values for three replicates (n = 3) are shown with their corresponding standard deviations.

Fig. 3. Dendrogram constructed by UPGMA cluster analysis of similarity coefficients derived from RFLP analysis of 16S rDNA of selected culturable Pseudomonas aeruginosa isolated from soil samples and obtained with BstUI. The levels of linkage representing the Dice correlation/UPGMA are expressed as percentages and shown at each node. SK denotes strains isolated from contaminated soil while CSK denotes strains isolated from uncontaminated soil samples.

cated that the P. aeruginosa strains appeared more adapted to the contaminated environment than the other oil-utilizing strains. Moreover, P. aeruginosa isolates utilized a much wider range of

aliphatic hydrocarbons, including the generally recalcitrant longchain aliphatics, compared to the other hydrocarbon-utilizing isolates. Obviously, the combined ability to mineralize crude oil at higher rates, and utilization of a wider range of alkanes confers competitive advantage to the strains of P. aeruginosa over the other less capable strains found in the same sites. Such competitive advantage could account for the dominance of P. aeruginosa among the hydrocarbon utilizers in the Kuwait and other environments (Hasanuzzaman et al., 2004; AL-Saleh et al., 2009). In addition, the dominance of Gram-negative bacteria in contaminated sites have been reported by others (Kaplan and Kitts, 2004; Saadoun et al., 2008) and may be considered another corollary of hydrocarbon pollution in soils. Although bacterial dominance was estimated based on culturebased techniques, the higher counts of the THB in soil samples determined by real-time PCR compared to those determined by culture-dependent techniques (Table 2) emphasizes the potential for under-estimation of the real status of microbial community attributable to the inability of 99% of viable bacteria to grow on culture plates (van Elsas et al., 1997), and to the high sensitivity of molecular techniques for detection of microbes (Ibekwe and Grieve, 2003; Powell et al., 2006). However, over-estimation of 16S rRNA gene copies in environmental samples could result from bacteria harboring multiple 16S rRNA gene copies (Nadkarni et al., 2002). The detection of alkB gene in the P. aeruginosa isolates highlighted the prominent role played by these strains in the bioremediation of hydrocarbon pollution in Kuwait environment, as alkB gene encodes alkane hydroxylase, the key enzyme in alkane metabolism (van Beilen and Funhoff, 2007). Interestingly, the detected alkB gene in P. aeruginosa strains was found to be closely related to the alkB gene of the bacterium Mycobacterium tuberculosis (Smits et al., 2002). This observation suggested the high dissimilarity between related genes encoding aliphatic hydrocarbon degradation in Kuwait indigenous bacteria and those depicted in previous studies (van Beilen et al., 2001). Results of hydrocarbon utilization profile showed that P. aeruginosa strains isolates preferred long chain hydrocarbons compared to short chains. The preferred utilization of long-chain aliphatic hydrocarbons may be a response of adaptation to pollution from crude oil, as Kuwait crude oil is known to be of the heavy variety that is poor in short-chain aliphatics. It is known that Kuwait environment is continuously exposed to crude oil pollution (Al-Sarawi et al., 1998), and exposure to such continuous supply of available substrates would select for microbiota adapted to these dominant components, as noted by other workers (Berwick, 1984; Greenwood et al., 2009). It is noteworthy that crude oil contamination in an environment is almost invariably associated with some heavy metal contamination, as crude oils contain these metals naturally (Tissot and Welte, 1984; Alloway, 1990). Thus, the significantly high levels of metals particularly Ni, Mn, Fe, Pb, Cr and Cd found in the contaminated sites could be attributed to crude oil pollution. Their documented effects on the soil microbiota include decrease in microbial

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culturable P. aeruginosa strains isolated from both types of soil samples. On the other hand, very high similarity coefficients were observed among the non-culturable P. aeruginosa populations in both types of soil samples. These observations suggest that crude oil contamination has less detrimental effects on the diversity of unculturable P. aeruginosa populations of Kuwait soil samples. The existence of such a stable fraction (the non-culturable) of P. aeruginosa population, relative to the apparently less stable culturable form, can provide a basis for comparing the extents of change in the indigenous populations of the organism in Kuwait terrestrial environment as a consequence of crude oil pollution.

5. Conclusions Crude oil contamination selected gram-negative bacterial strains that were predominantly P. aeruginosa, with higher biodegradation potentials for crude oil and the ability to utilize wider range of alkanes in the presence of heavy metals. The diversity of bacterial community in the crude oil-contaminated site was also affected, in which the culturable fraction of petroleum-degrading P. aeruginosa population appeared more affected than the non-culturable P. aeruginosa strains that showed higher stability and thus more reliability for phylogenetic analyses. The current investigation demonstrated some of the exceptional competitive traits of P. aeruginosa that resulted in its dominance over other bacteria in the soils which implies that variation of soil microbiota usually results from the interaction of exogenous factors such as crude oil contamination and endogenous factors associated with the inborn capabilities of the soil indigenous microbiota. Fig. 4. Dendrogram constructed by UPGMA cluster analysis of similarity coefficients derived from RFLP analysis of 16S rDNA of selected unculturable Pseudomonas aeruginosa detected in soil samples and obtained with BstUI. The levels of linkage representing the Dice correlation/UPGMA are expressed as percentages and shown at each node. SK denotes strains isolated from contaminated soil while CSK denotes strains isolated from uncontaminated soil samples.

numbers, diversity and activity (Hughes and Poole, 1989; Jansen et al., 1994; Kozdrój and Van Elsas, 2001; Brakstad and Lødeng, 2004; AL-Saleh and Obuekwe, 2005; Obuekwe et al., 2009). Speciation and hydrolysis of such higher levels of the salts of the metals found in the crude oil-contaminated soil would contribute to the higher conductivity usually associated with oil contamination (Iwegbue et al., 2009) and lower pH (Elzahabi and Yong, 2001) as recorded in the crude oil-contaminated sites. The lower pH recorded in crude oil-contaminated sites is attributed to acidic degradation products associated with hydrocarbon degradation (Walter et al., 1997) by the higher numbers of hydrocarbon utilizers present in contaminated sites (AL-Saleh and Obuekwe, 2005; Obayori et al., 2008). Moreover, the heightened demand for oxygen for respiratory activities in the mineralization of crude oil in the contaminated sites would account for the lower dissolved oxygen content in the crude oil-contaminated sites. Thus, the significant differences in the levels of TOC, dissolved oxygen, pH, metal content, numbers of hydrocarbon degrades observed in the two types of sites in Kuwait are consistent with the effects of crude oil contamination in the environment (Stotzky and Pramer, 1972; Walker and Colwell, 1976; Atlas, 1981; Benka-Coker and Ekundayo, 1995; Peressutti et al., 2003; AL-Saleh and Obuekwe, 2009). Based on their determined crude oil biodegradation potentials and the consistent occurrence in the soils, it was expected that strains of P. aeruginosa would play significant roles in the bioremediation of crude oil-contaminated sites in Kuwait. Cluster analyses showed (Figs. 3 and 4) low similarity coefficients among the

Acknowledgments This project was funded by the College of Graduate Studies and from the Research Administration of Kuwait University project number YS04/07. Chemical analysis of soil by the SAF unit and sequencing of 16S rRNA by the Biotechnology Center – College of Science is highly appreciated.

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