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Hydrocarbon seeps provide inputs of petroleum hydrocarbons to widespread areas of the Timor Sea. Alkanes constitute the largest proportion of chemical components found in crude oils, and therefore genes involved in the biodegradation of these compounds may act as bioindicators for this ecosystem's response to seepage. To assess alkane biodegradation potential, the diversity and distribution of alkane hydroxylase (alkB) genes in sediments of the Timor Sea were studied. Deduced AlkB protein sequences derived from clone libraries identified sequences only distantly related to previously identified AlkB sequences, suggesting that the Timor Sea maybe a rich reservoir for novel alkane hydroxylase enzymes. Most sequences clustered with AlkB sequences previously identified from marine Gammaproteobacteria though protein sequence identities averaged only 73% (with a range of 60% to 94% sequence identities). AlkB sequence diversity was lower in deep water (>400 m) samples off the continental slope than in shallow water (<100 m) samples on the continental shelf but not significantly different in response to levels of alkanes. Real-time PCR assays targeting Timor Sea alkB genes were designed and used to quantify alkB gene targets. No correlation was found between gene copy numbers and levels of hydrocarbons measured in sediments using sensitive gas chromatography-mass spectrometry techniques, probably due to the very low levels of hydrocarbons found in most sediment samples. Interestingly, however, copy numbers of alkB genes increased substantially in sediments exposed directly to active seepage even though only low or undetectable concentrations of hydrocarbons were measured in these sediments in complementary geochemical analyses due to efficient biodegradation.
Alkanes are saturated hydrocarbons that are widespread in marine environments due to a variety of anthropogenic and natural sources. They constitute the major fraction of hydrocarbon components found in crude oils and refined petroleum and are also produced by various marine organisms (e.g., zooplankton) as cellular components (2, 44). Alkanes are considered as pollutants, with short-chained alkanes acting as solvents toward cellular membranes and other lipid components (34) while longer-chained alkanes may contribute to the formation of oil films and slicks that may limit nutrient and oxygen exchange (21). Importantly, alkanes also serve as important carbon and energy sources for some microorganisms. In marine environments, alkanes succumb to various removal and dispersal processes such as dissolution, photochemical oxidation, evaporation, adsorption, and sedimentation. However, the greatest removal pathway for alkanes in marine sediments is via biodegradation by bacteria (13). This mechanism also mediates the transfer of oil-derived carbon to higher trophic levels (28, 37), and therefore these bacteria have an important role in carbon cycling in environments subject to long-term inputs of hydrocarbons such as marine seep-associated ecosystems. Alkane biodegradation is mediated by a diverse range of marine bacteria using various electron acceptors although degradation generally proceeds at greater rates under aerobic conditions than under anaerobic conditions, where the process is relatively slow (8, 26).
In the presence of oxygen, well-characterized alkane oxidation pathways are initiated by an activation step whereby oxygen is introduced to the alkane substrate before further catabolic steps can proceed. A number of oxygen-dependent alkane hydroxylase enzyme systems have been discovered that catalyze this initial step including the soluble di-iron methane monooxygenases and the membrane-bound copper-containing methane monooxygenases, both of which act upon short-chain alkanes (i.e., C1 up to C8). Integral membrane non-heme iron alkane hydroxylases (the alk system) that are related to the well-characterized AlkB of Pseudomonas putida GPo1 (also known as Pseudomonas oleovorans TF4-1 I) act upon longer-chain alkanes (i.e., C5 to C16) (40). Other systems exist that include alkane-hydroxylating cytochrome P450 enzymes in addition to other enzyme systems that are known to exist based purely on chemical analyses of metabolites formed during alkane degradation experiments (22, 25, 29); however, knowledge pertaining to the enzymes and genes involved as well as their importance in the environment is limited. Only recently have genes involved in the degradation of long-chain alkanes (e.g., C32 and C36) been identified in Acinetobacter sp. strain DSM 17874 (39) though there is no information about the presence or importance of such enzymes in the environment.
Although various chemical and microbiological aspects of petroleum oil and alkane biodegradation in marine systems have been relatively well studied, there is a general lack of knowledge concerning the diversity or abundance of the functional genes involved. The biochemical and molecular aspects of alkB genes and the enzymes they encode have been relatively well studied, and this has enabled the development of molecular tools for the study of alkB genes in the environment (19). Elevated levels of hydrocarbons or the introduction of hydrocarbons to environments has been shown to increase gene copy numbers, indicating the potential use of alkB genes as bioindicators of oil pollution and/or biodegradation (16, 33, 36, 43). However, to date only one study has used culture-independent molecular methods to examine the diversity of alkB genes in a marine environment (20), and no studies have examined hydrocarbon-degrading genes where natural hydrocarbon seepage occurs.
In this study, the diversity and relative abundance of alkB genes were examined in sediments of the Timor Sea, a region where natural seeps are sources of widespread petroleum hydrocarbons. It was hypothesized that (i) novel alkB genes may exist in this unique tropical marine environment, (ii) that variations in gene diversity would be found in sediments with different hydrocarbon levels, and (iii) that the abundance of certain alkB gene types may reflect the levels of measured hydrocarbons in sediments, and therefore this assay could be used as a complementary tool for monitoring petroleum inputs into sediments of the Timor Sea.
Samples were collected from the Timor Sea, northwestern Australia, during the RV Southern Surveyor cruise SS05/06 of June 2005. A heavily weighted Smith-MacIntyre (0.25-m2 surface area) grab sampler was used to obtain sediment grabs with undisturbed surface sediments. Grabs were then subsampled with a sterile core device (5-cm inner diameter and 30 cm in length) on shipboard. Locations of sediment grabs are indicated in Table Table11 and Fig. Fig.1.1. All cores were sectioned into 1-cm intervals and stored at −20°C on shipboard, at −180°C in liquid nitrogen during transport (5 days), and at −80°C in the laboratory prior to molecular analysis. Details of analytical methods for measuring hydrocarbon content have been reported previously (4).
The DNA extraction protocol was based on previously described procedures for the extraction of total DNA from soil samples (10, 45). Briefly, the sediment slurry (wet weight, 0.5 g) was placed in a 1.5-ml tube and suspended in 1.35 ml of extraction buffer (100 mM Tris-HCl [pH 8.0], 100 mM sodium EDTA [pH 8.0], 100 mM sodium phosphate [pH 8.0], 1.5 M NaCl, 1% [wt/vol] cetyltrimethylammonium bromide) to which 5 μl of fresh proteinase K (20 mg ml−1) was added. The sample was placed horizontally on a 200-rpm shaker at 37°C for 30 min. After the sample was subjected to shaking, 150 μl of sodium dodecyl sulfate (20%, wt/vol) was added, and the tube was placed at 65°C for 2 h and mixed by inversion every 15 min. The supernatant was decanted into a clean tube after centrifugation for 10 min at 6,000 × g and 25°C. The sediment pellet was again suspended in 450 μl of extraction buffer, and 50 μl of sodium dodecyl sulfate (20%, wt/vol) was added; the sample was incubated at 65°C and centrifuged as before, and the supernatant was added to the first aliquot. The crude extract was gently extracted with an equal volume of chloroform (containing 4% [vol/vol] isoamyl alcohol to minimize foaming) and centrifuged at 16,000 × g for 10 min at 25°C. The aqueous phase (upper layer) was transferred to a clean tube, and the DNA was precipitated by adding 0.6 volume of 2-propanol. The DNA was left to precipitate for 1 h at 20°C. The DNA was pelleted by centrifugation at 16,000 × g for 30 min at 20°C. The DNA pellet was rinsed with 500 μl of 70% (vol/vol) ethanol and air dried for 20 min. DNA was resuspended in 50 μl of deionized water and diluted 1:10 to facilitate PCR amplification. DNA concentrations were determined using a NanoDrop ND1000 (NanoDrop Technologies) in triplicate. All DNA extracts were stored at −20°C.
Partial alkB genes were amplified using the forward primer alkB-1f (5′-AAYACNGCNCAYGARCTNGGNCAYAA-3′) and the reverse primer alkB-1r (5′-GCRTGRTGRTCNGARTGNCGYTG-3′) (19). All PCRs (final volume of 25 μl) contained 1× Qiagen PCR Buffer (Qiagen), 1 U of HotStar Taq DNA Polymerase (Qiagen), 200 uM of each deoxynucleoside triphosphate, 25 pmol of each primer, 0.5 μl of purified bovine serum albumin 10 μg μl−1 (New England Biolabs), 0.5 μl of DNA template (~50 ng), and deionized water up to 25 μl. PCR cycling conditions included an initial enzyme activation step at 95°C for 15 min, followed by an additional 39 cycles of 94°C for 1 min, annealing at 55°C for 1 min, and extension at 72°C for 1 min. A final extension step of 72°C for 10 min was included to facilitate A tailing of the PCR products for cloning.
PCR products from three replicate reactions for each sample were pooled and subjected to agarose gel electrophoresis. Bands of expected sizes were excised and purified using a QIAquick Gel Extraction Kit (Qiagen) according to the manufacturer's instructions. Purified DNA was then cloned using a TOPO-TA Cloning Kit (Invitrogen) according to the manufacturer's instructions. Individual colonies were suspended in 100 μl of sterile deionized water using a sterile toothpick, vortexed briefly, allowed to stand for 60 min, and vortexed again, and this cell suspension was used as a template for PCR using the M13 primers to confirm inserts. Colony hybridization to identify positive alkB inserts in clones was performed as previously described (19). Generated PCR products were dried and sent to Macrogen, Inc. (Seoul, South Korea), for purification and sequencing using an ABI3730 XL automatic DNA sequencer using the M13F vector specific primer.
Retrieved alkB gene nucleotide sequences were initially checked using Chromas Lite software, version 2.01 (Technelysium), before being truncated to exclude primer and vector sequences. Nucleotide sequences were translated into protein sequences using the translate tool in the ExPASy (Expert Protein Analysis System) proteomics server of the Swiss Institute of Bioinformatics (http://us.expasy.org/tools/dna.html). Deduced protein sequences from each library were grouped into operational protein units (OPUs) using DOTUR software (31) with a distance threshold of 0.20 (80% sequence similarity). This cutoff value was selected after initial examination of phylogenetic trees that included all nucleotide sequences generated by neighbor-joining analysis. The phylogenetic comparison identified a general clustering of AlkB sequences at this level; i.e., when sequences from distinct clusters were aligned using BLAST (bl2seq), they generally exhibited more than 80% sequence identity. This approximate distance threshold was also used in a similar study of AlkB sequences in Antarctic sediments (20) and therefore allows comparisons between studies. Deduced protein sequences were aligned using ClustalX, version 1.83 (38), with related reference sequences identified from BLAST (1) searches, in addition to other sequences of various representative AlkB sequences identified from the literature. Distance matrices were calculated using the PROTDIST program in PHYLIP, version 3.6 (11; J. Felsenstein, University of Washington, Seattle, WA [http://evolution.genetics.Washington.edu/phylip.html]). Phylogenetic trees were generated from distance matrices using the neighbor-joining method (30) and Kimura substitution algorithm (18) using PHYLIP. Bootstrapping with 1,000 replicates was performed using SeqBoot as integrated in PHYLIP.
Rarefaction analysis (15), alternating conditional expectation (ACE) and Chao1 nonparametric richness estimates (7), Simpson index of diversity (23), and Shannon-Weaver index of diversity (32) were generated using DOTUR software (31). Statistical evaluations were obtained using 80% amino acid sequence similarity.
Real-time PCR assays were carried out using a Rotor-Gene 3000 real-time DNA amplification system (Corbett Research) using a Platinum SYBR green qPCR SuperMix-UDG kit (Invitrogen). PCRs (final volume of 25 μl) contained 12.5 μl of 2× Platinum SYBR green qPCR SuperMix-UDG (Invitrogen), 4.0 mM MgCl2, 5 pmol of each primer, 0.5 μl of purified bovine serum albumin (10 μg μl−1; New England Biolabs), 2.0 μl of DNA template (DNA extracts from 1:10 dilutions of crude extracts were used and exhibited no PCR inhibition), and deionized water up to 25 μl. Primers were designed to target specific clusters of abundant alkB genes detected in clone libraries to avoid problems associated with aberrant PCR efficiencies as a result of using highly degenerate primers for the amplification of diverse alkB genes. Two sets of primers targeting clusters A and C (see Fig. Fig.3)3) were designed after examination of alignments from ClustalX. The design of primers suitable for real-time PCR application was aided by using the program NetPrimer (http://www.premierbiosoft.com/netprimer/index.html). alkB genes from cluster A were amplified using the forward primer A-f (5′-TACGGGCACTTCGCGATTGA-3′) and the reverse primer A-r (5′-CGCCCAGTTCGAMACGATGTG-3′). alkB genes from cluster C were amplified using the forward primer C-f (5′-TCGTACTTGCCGTGCCTGTGTA-3′) and the reverse primer C-r (5′-CGATCAGCGTCAGTTGAATCAC-3′). Real-time PCR cycling conditions included an initial UDG incubation step at 50°C for 2 min and an enzyme activation step at 95°C for 2 min, followed by 40 cycles of 95°C for 20 s, annealing at 59°C for 20 s, and extension at 72°C for 40 s. Acquisition of fluorescence signal was performed during the 72°C extension step of each cycle. This was followed by a melt curve from 45°C to 95°C. In addition to melt curve analysis, PCR products were checked on a 1% agarose gel to ensure they were the expected sizes.
The DNA standards used in the real-time PCR assays consisted of serial dilutions of purified PCR products derived from cloned alkB genes. Clones F44 and G17 (see Fig. Fig.3)3) were used as standards for clusters A and C, respectively. Standards were PCR amplified directly from a colony using M13 vector-specific primers, checked using standard agarose gel electrophoresis, and gel purified using a QIAquick Gel Extraction Kit (Qiagen), according to the manufacturers instructions, and DNA concentrations were determined using a Quant-iT PicoGreen dsDNA quantitation kit (Molecular Probes) using fluorimetry. Measured concentrations of purified PCR products were then converted to copies per microliter, and the concentration was adjusted to 1 × 109 copies μl−1 prior to performing serial dilutions. A five-point standard curve (1 × 105 to 1.0 × 101 copies per reaction mixture) was run in duplicate with each run, and each run was performed twice (totaling four replicates per sample). Environmental samples and negative controls (no template DNA) were included in each run and were also performed in duplicate. Data and copy numbers of alkB targets in environmental samples were analyzed using the Rotor-Gene software, version 6.1.71 (Corbett Research), following the manufacturer's guidelines. Final copy numbers of alkB genes in environmental samples were calculated assuming 100% DNA extraction efficiency, and results are expressed as copy numbers per gram of sediment.
Nucleic acid sequences determined in this study have been deposited in the GenBank/EMBL/DDBJ databases under accession numbers GQ184383 to GQ184421, GQ184423 to GQ184432, and GQ184434.
Samples were collected from shallow continental shelf waters associated with the active Cornea seep area (grabs D, E, and H), from waters north of the Cornea seep area in a “paleo-riverbed” (grabs G and F), and from deeper waters off the continental slope (grabs B, J, K, L, and M) (Fig. (Fig.1).1). Details of sample coordinates and hydrocarbon concentrations are presented in Table Table1.1. Concentrations of measured total hydrocarbons (THC) were below detection limits in Cornea seep-associated sediments (grabs D, E, and H), while only 11.5 ng g−1 of total n-alkanes was measured in sediments of grab H that are presumed to be directly influenced by hydrocarbons actively seeping from underlying sediments to the water column, as detected by shipboard echo-sounder and towed video camera surveys. Concentrations of polycyclic aromatic hydrocarbons (oil PAHs) at the Cornea seep area were among the lowest in the Timor Sea, ranging from 3.2 to 62 ng g−1. Relatively low to mid-range concentrations of THC (0.19 to 0.66 μg g−1), total n-alkanes (40.5 to 57.8 ng g−1), and oil PAHs (5.2 to 5.4 ng g−1) were measured in grabs G and F taken from the paleo-riverbed sediments to the north of the Cornea seep area. The highest concentrations of petroleum hydrocarbons were measured in sediments (grab B) to the west of the Sahul Shoals, with relatively high THC (8.42 μg g−1), total n-alkanes (344 ng g−1), and oil PAHs (144.4 ng g−1). Relatively high concentrations of hydrocarbons in grabs from the other deep water locations within the Cartier Trough (grabs J, K, and L) were also found, and concentrations of THC (0.05 to 0.40 μg g−1), total n-alkanes (45.8 to 210.3 ng g−1), and oil PAHs (19.9 to 57.1 ng g−1) were determined.
Rarefaction analysis (Fig. (Fig.2)2) of a clone library constructed from a deep-water sample that possessed the highest measured hydrocarbon content (grab B) displayed similar AlkB deduced protein sequence diversity compared directly against a low-concentration site (grab M). The highest AlkB diversity of all samples was found within grab G from the paleo-river to the north of the Cornea seep area and was only slightly higher than diversity predicted in sediments closely associated with the largest seep plume identified in the Timor Sea (grab H) and those from another paleo-river sample (grab F). Rarefaction curves did not reach an asymptote for any of the libraries (Fig. (Fig.2),2), suggesting that a greater diversity of AlkB sequences was present in the samples than revealed by the sequencing effort. ACE and Chao estimators also suggested that more OPUs were present in the samples than were detected in the clone libraries (Table (Table2).2). Rarefaction curves for libraries F, G, and H (on the continental shelf) indicated higher diversity than for libraries B and M (off the continental shelf) (Fig. (Fig.2).2). Both Shannon-Weaver and Simpson indices of diversity were consistent with rarefaction analysis showing greater diversity of AlkB sequences in libraries G, F, and H than in libraries B and M (Table (Table22).
Phylogenetic analysis of AlkB deduced protein sequences revealed that none of the Timor Sea sequences was closely related to any previously identified AlkB sequences present in the public databases (Fig. (Fig.3).3). Overall, sequence similarity of Timor Sea AlkB sequences to sequences present in the public databases ranged from 60% to 94%, with an average sequence similarity of only 73%. Most Timor Sea AlkB sequences grouped in a large cluster of diverse sequences that were most closely related to marine and mostly gammaproteobacterium-derived AlkB sequences although a few soil-derived sequences also clustered within this group. Two sequences representing OPUs B4 and M61 affiliated with AlkB sequences derived from gram-positive actinobacterial Nocardia sp. strain CF8 and Prauserella rugosa strains. Other sequences belonging to OPUs G69, H12, and M60 also affiliated most closely with other marine-derived AlkB sequences. No trends in the clustering of sequences from different sites were apparent (e.g., high hydrocarbon concentrations versus low hydrocarbon concentrations or deep water versus shallow water), which was most evident by the fact that sequences from each site were well represented in clusters A and C, which were comprised of the most abundant sequences in each library. Importantly, all deduced AlkB protein sequences included in this analysis revealed the presence of two highly conserved regions (motif B, EHXXGHH, and motif C, NYXEHYG) identified as important for alkane hydroxylase activity (results not shown) (35, 42).
Previously designed primers targeting alkB genes belonging to marine alkane degrading bacteria Thalassolituus sp. and Alcanivorax borkumesus (5, 24) were unable to produce positive amplification products when applied to Timor Sea sediment samples. Therefore, quantitative real-time PCR primers were designed targeting the most abundant alkB gene sequences identified in Timor Sea clone libraries. Two sets of primers targeting clusters A and C (Fig. (Fig.3)3) proved to be functional under real-time PCR conditions, i.e., produced acceptable amplification efficiencies across all samples and standards, and were specific for the alkB genes from which they were designed for, as tested by PCR using plasmid DNA from target and nontarget clones as a template (results not shown).
When these primers were used for the evaluation of the relative abundance of these gene groups in Timor Sea sediments, gene copy numbers were found to be highest in sediments of grab H sampled from the area of the largest active seep plume in the Timor Sea. Approximately 2.9 × 105 and 1.1 × 105 copies of the alkB gene per g of sediment were recovered for primer sets targeting clusters A and C, respectively (Fig. (Fig.4).4). These gene copy numbers in sediments of grab H were higher than gene copy numbers identified in all other sediment samples. For example, other sediments from the Cornea seep area (grabs D and E) and sediments from the paleo-river to the north of the Cornea seep area (grabs G and F) displayed lower levels of alkB genes, revealing no more than 2.3 × 104to 3.3 × 104 alkB gene copies per g of sediment for both clusters A and C (Fig. (Fig.4).4). Low numbers or no copies of alkB genes were detected in all deep-water sediments with primers targeting cluster A, or alkB genes were below detection limits with primers targeting cluster C (Fig. (Fig.44).
In this study, sediment samples were taken from various geographically separated sites in the Timor Sea to explore and compare the diversity and abundance of the alkB functional gene in relation to levels of hydrocarbons measured in sediments. Phylogenetic analysis of Timor Sea AlkB sequences revealed a novel array of AlkB sequence types. Essentially all AlkB OPUs were divergent from previously characterized AlkB sequences, with average amino acid sequence identities of only 73% (range, 60% to 94%) to sequences available in public databases. These results suggest that the Timor Sea harbors a unique suite of AlkB sequences, probably with a range of substrate specificities and/or induction patterns enabling the degradation of various n-alkanes. Most sequences were related to AlkB sequences derived from marine Proteobacteria (mostly gammaproteobacterial). Effectively, all marine bacteria so far implicated in the degradation of alkanes (elucidated predominately through culture-dependent studies) belong to the Gammaproteobacteria (14), and therefore these results independently support the notion that members of the Gammaproteobacteria are responsible for the aerobic degradation of alkanes in marine environments. Results from this study are in contrast to analysis of alkB genes from soils which identified mostly gram-positive-derived genes (19) and suggest that markedly different alkane-degrading bacteria exist in the marine environment in comparison to terrestrial environments.
Interestingly, AlkB sequence diversity did not appear to be influenced by levels of measured alkanes since gene diversity was not substantially different in sediments with high concentrations of hydrocarbons versus sediments with low concentrations or in sediments in direct association with active seepage that are presumably exposed to high concentrations of hydrocarbons. For instance, in libraries from grab B (the highest hydrocarbon levels measured in the Timor Sea) and grab M (very low hydrocarbon levels) that were taken from comparable depths and away from any active seepage, differences in AlkB sequence diversity as assessed by rarefaction analysis and diversity statistics of clone libraries were minimal. In a study of AlkB sequence diversity in samples influenced by anthropogenic activities polluting Antarctic marine sediments, much lower AlkB sequence diversity was identified in heavily contaminated sediments than in less-contaminated sediments (20), suggesting an enrichment of specific gene types with increasing alkane concentrations and resulting lower diversity indices. Levels of alkanes in contaminated Antarctic sediments were an order of magnitude higher in contaminated sediments (e.g., 5 μg g−1 of total n-alkanes) than in control (e.g., 0.29 μg g−1 of total n-alkanes) sediments. These Antarctic control sediments had alkane concentrations comparable to the highest levels measured in the Timor Sea, suggesting that concentrations measured in Timor Sea sediments may not have been sufficient to cause significant shifts in gene diversity, as was observed in the Antarctic study.
In addition, ACE and Chao indices predicted over three times higher diversity in Timor Sea sediments than in Antarctic sediments. It is possible that because Timor Sea sediments have been exposed to naturally seeping hydrocarbons since the Pliocene era (27), a greater diversification of AlkB sequences has occurred in this ecosystem than in the historically pristine Antarctic environments. The high diversity in the Timor Sea may be “constitutively” present throughout the region, and therefore the detectable diversity may be relatively unaltered when sediments are exposed to alkane inputs. In contrast, Antarctic sediments which have been pristine in the past have apparently less diversity and therefore become dominated by certain AlkB sequence types when exposed to anthropogenic sources.
The only notable differences in AlkB sequence diversity identified in this study were between shallow water sites (i.e., grabs F, G, and H, on the continental shelf and in <100 m water) and deep water (i.e., grabs B and M, off the continental shelf and in >400 m water). All shallow-water samples generally displayed greater AlkB sequence diversity as assessed by rarefaction analysis and statistical analyses of clone libraries. Interestingly, no studies have investigated bacterial diversity in sediments over depth gradients in the ocean. It is possible that bacterial diversity decreases with increasing depth, driven by factors such as decreasing amounts of labile organic matter and therefore available substrates for nutrition, in addition to increasing barometric pressures and decreasing temperatures. If such changes in bacterial diversity do occur through depth, these may account for the reduction in the AlkB sequence diversity at depth that was observed in this study.
Quantification of alkB genes belonging to clusters A and C (Fig. (Fig.3)3) using real-time PCR identified significantly higher copy numbers in sediments associated with an actively venting seep (grab H) where hydrocarbons are seeping from the underlying sediments and into the water column. Interestingly, hydrocarbon concentrations in sediments exposed to active seepage (and in other sediments from the Cornea seep area, i.e., grabs D and E) were relatively low or even undetectable. This suggests that rapid microbial degradation of hydrocarbons is occurring and that this rapid degradation removes detectable quantities of hydrocarbons before they can be measured by geochemical analyses. The quantification of alkB gene copy numbers in sediments therefore provides an insight into the microbial response to the seepage of hydrocarbons and acts as a useful complementary tool for understanding this ecosystem's response to hydrocarbons in addition to using geochemical measurements that suggest little or no exposure to hydrocarbons. Interestingly, no considerable increases in gene copy numbers were detected in sediments that had high, measured hydrocarbon concentrations (i.e., grab B which had the highest hydrocarbon concentrations measured in the Timor Sea), in comparison to other samples from comparable water depths that had low or undetectable hydrocarbon concentrations (e.g., grab M). Quantitative molecular methods targeting hydrocarbon-degrading genes in environmental samples have generally identified some correlations between hydrocarbon-degrading gene copy numbers and hydrocarbon concentrations (6, 9) although other studies have found only weak correlations (17). Within this study it is likely that hydrocarbon concentrations in the Timor Sea (with the exception of sediments exposed directly to active seepage, e.g., grab H) may not be high enough to evoke dramatic shifts in gene copy numbers such as occur in study sites where such correlations have been made. Quantitative mRNA-based approaches may be useful as a more sensitive tool for monitoring subtle changes in gene copy numbers in marine sediments exposed to low levels of hydrocarbons. The assay developed here, however, may be sensitive enough to be applied as a tool for monitoring, for example, the spatial effects of oil released from extraction operations in the Timor Sea which have been studied previously by Burns and Codi (3).
Since the actual hydrocarbon concentrations measured in sediments did not appear to have a significant influence on gene copy numbers, other factors appear important in determining gene copy numbers in this oceanic environment. Water depth in combination with fluxes of hydrocarbons from the water column to sediments may be important in determining numbers of alkB genes in this ecosystem, at least in sediments not exposed directly to active seepage (e.g., all grabs excluding grab H). For example, alkB gene copy numbers were very low or undetectable in deep-water (>400 m) sediment samples (i.e., grabs B, K, L, and M) off the continental shelf and well away from any known active seepage but were easily detectable in all samples (grabs D, E, F, G, and H) from shallow-water sediments (ca. 100 m) on the continental shelf. Complementary research using a layered-sediment trap approach to measure fluxes of hydrocarbons from the water column to sediments revealed that only a small flux of alkanes actually reach deeper waters of more than 400 m; e.g., up to 85% of n-alkanes are degraded as they settle at a water depth from 100 m to 400 m (unpublished results). Therefore, it seems that fluxes of alkanes to deep-water sediments are probably not large enough to sustain detectable numbers of alkB genes using the real-time PCR assays applied here.
This study provides new insights into the diversity of alkane-degrading enzymes in the marine environment. The identification of novel AlkB sequence diversity points to the existence of a diverse range of what are most likely gammaproteobacterial species/gene types capable of degrading alkanes in the Timor Sea. Such AlkB enzymes are worthy of further investigation for biotechnological applications since these enzymes have various applications in the synthetic production of various compounds such as secondary metabolites, pharmaceuticals, and agrochemical intermediates (41). High copy numbers of alkB genes were identified in association with an actively venting seep, demonstrating enhanced alkane-degrading capacity at this site. However, despite high measured gene copy numbers, this did not equate to distinct changes in observed alkB gene diversity compared to other sampled sediments. Chronic exposure of sediments to hydrocarbon inputs appeared not to alter alkB gene copy numbers within the sediments though efficient and rapid biodegradation of hydrocarbons was occurring, mediated by microbial communities that are well adapted to the readily available carbon source. It is anticipated that future examination of alkB gene transcripts could be used as a more sensitive tool for assessing the response of alkB gene diversity and copy numbers to hydrocarbons in this environment.
We thank the crew and scientific support staff of the RV Southern Surveyor during cruise SS05/06 to the Timor Sea for collection of samples during June 2005. We especially thank Gregg Brunskill and Irena Zagorskis for their help in sampling and geochemical analyses. We thank Tim Simmonds for help in preparation of the manuscript figures.
We thank the Australian Biological Resources Study and Commonwealth Scientific and Industrial Research Organization for stipends and financial support.
Published ahead of print on 9 October 2009.