Microb Ecol DOI 10.1007/s00248-014-0421-6
ENVIRONMENTAL MICROBIOLOGY
Insights into Biodegradation Through Depth-Resolved Microbial Community Functional and Structural Profiling of a Crude-Oil Contaminant Plume Nicole Fahrenfeld & Isabelle M. Cozzarelli & Zach Bailey & Amy Pruden
Received: 14 November 2013 / Accepted: 7 April 2014 # Springer Science+Business Media New York (outside the USA) 2014
Abstract Small-scale geochemical gradients are a key feature of aquifer contaminant plumes, highlighting the need for functional and structural profiling of corresponding microbial communities on a similar scale. The purpose of this study was to characterize the microbial functional and structural diversity with depth across representative redox zones of a hydrocarbon plume and an adjacent wetland, at the Bemidji Oil Spill site. A combination of quantitative PCR, denaturing gradient gel electrophoresis, and pyrosequencing were applied to vertically sampled sediment cores. Levels of the methanogenic marker gene, methyl coenzyme-M reductase A (mcrA), increased with depth near the oil body center, but were variable with depth further downgradient. Benzoate degradation N (bzdN) hydrocarbon-degradation gene, common to facultatively anaerobic Azoarcus spp., was found at all locations, but was highest near the oil body center. Microbial community structural differences were observed across sediment cores, and bacterial classes containing known hydrocarbon
Electronic supplementary material The online version of this article (doi:10.1007/s00248-014-0421-6) contains supplementary material, which is available to authorized users. N. Fahrenfeld (*) Civil and Environmental Engineering, Rutgers, The State University of New Jersey, 96 Frelinghuysen Rd, Piscataway, NJ, USA e-mail:
[email protected] I. M. Cozzarelli U.S. Geological Survey National Research Program, 12201 Sunrise Valley Drive, Reston, VA, USA Z. Bailey Biomedical Engineering and Sciences, Virginia Tech, 317 Kelly Hall, Blacksburg, VA, USA A. Pruden Civil and Environmental Engineering, Virginia Tech, 418 Durham Hall, Blacksburg, VA, USA
degraders were found to be low in relative abundance. Depth-resolved functional and structural profiling revealed the strongest gradients in the iron-reducing zone, displaying the greatest variability with depth. This study provides important insight into biogeochemical characteristics in different regions of contaminant plumes, which will aid in improving models of contaminant fate and natural attenuation rates.
Introduction There is a need for improved resolution of microbial community structure and function with depth [1–6] in order to advance understanding of the role of microbial biodegradation processes in the subsurface. Niches may exist where certain microbial functional groups dominate and, in turn, impact biodegradation rates. For example, inverse correlations have been observed between iron reducers and methanogens [3]. These regions of functional niches have been demonstrated at the Bemidji Oil Spill site to display tight linkage to the corresponding geochemistry [7]. For example, higher methanogen levels were associated with greater hydrocarbon flux [2], while submeter changes in microbial community profiles were observed to correspond to hydrologic factors, such as changes in permeability [3]. Functional differences with depth are intrinsically tied to microbial community structure. One study using terminal restriction fragment length polymorphism (tRFLP) and quantitative polymerase chain reaction (qPCR) targeting the bssA gene marker for anaerobic toluene degraders demonstrated a significant shift in community structure with depth in PAH-contaminated sediments and across different dominant electron-acceptor zones [1]. The Bemidji Oil Spill site, which resulted from a pipeline rupture in 1979, represents an ideal location for field studies focused on resolving fine-scale differences in factors driving
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hydrocarbon degradation with depth, as over 30 years of biogeochemical monitoring data is available [8]. The pervading challenge of predicting degradation rates based on dominant redox conditions was highlighted in a recent study of hydrocarbon biodegradation rates using in situ microcosms at the site. In iron-reducing in situ microcosms, there was a significant lag in benzene and ethylbenzene degradation of at least 200 days [9], while no lag was observed in adjacent wetland sediments [10]. Faster degradation rates in the wetland sediments were unexpected given the prevailing methanogenic redox conditions. Thus, the Bemidji aquifer plume and adjacent wetland were examined in this study by using depth-resolved microbial community profiling in order to better understand the interplay between biogeochemical processes and microbial community function. Previous microbiological studies at the Bemidji site have focused on broad-scale bacterial community analysis and isolation of hydrocarbon degraders. Geobacteraceae, Geothrix fermentans, Betaprotetobacteria related to Azoarcus evansii, and several novel lineages have been identified at the site [11]. However, microbial community structure has not been investigated at the same small scales that have been shown to be important in other studies [1]. Structural differences are intrinsically tied to functional capabilities and previous functional characterization at the site with depth relied on a most probable number (MPN)-based methodology [2, 3], which enumerates only cultivable bacterial populations. Therefore, applying molecular techniques will expand understanding of the role of both previously cultured and uncultured organisms as well as metabolic potential at important “plume fringes” where redox zones shift [12]. The purpose of this study was to profile bacterial community structure and genetic markers of key functional processes with depth across a hydrocarbon gradient at the Bemidji plume and to compare with an adjacent methanogenic wetland. Dissimilatory sulfite reductase (dsrA) genes and the methyl coenzyme-M reductase A (mcrA) genes were targeted as markers of sulfate reduction and methanogenesis, respectively, processes that were expected to be elevated near the oil body center where oxygen is depleted. Anaerobic aromatic hydrocarbon-degrading functional potential was assayed targeting benzoate degradation N (bzdN) genes, known to be present in Azoarcus spp., to gain insight into the distribution of this poorly understood class of hydrocarbon degrader. The results of the study provide better understanding of fine-scale microbial variation with depth, especially in different regions of contaminant plumes, and relationship to biogeochemical characteristics. Improvement of tools for understanding hydrocarbon fate and attenuation rates is expected to be of increasing importance as oil pipelines age and are expanded, which will likely lead to future spills.
Materials and Methods Site Background and Sample Collection Sediment cores were collected from the Bemidji, MN, oil spill research site in June 2012 (Fig. 1a, b). Aquifer sediments were contaminated with ~5×105 L of crude oil in 1979 following a rupture of an oil pipeline [8]. Surface contamination occurred in a spray zone, the most heavily contaminated surface sediments were excavated, and a hydrocarbon plume extends in the north easterly direction with nonaqueous phase liquid oil in the North Pool. A wetland is located south west of the South Oil Pool. Sediment cores were collected from the aquifer from two redox zones: Fe-reducing (115 m, two cores) and methanogenic (18 m, one core) (Fig. 1). All cores were collected starting at approximately 0.30 m below the water table and driven an additional 2.1 m. The freezing drive shoe uses liquid CO2 to freeze the core in situ, to ensure that the sediment was retained within the core liner [7, 13]. A fourth core was collected by a direct manual push in an adjacent wetland (one core) that was exposed to oil. Cores were cut into 1-m sections in the field, sealed with plastic wrap, taped to preserve anaerobic conditions, and wrapped in foil to prevent exposure to light. Cores were frozen on site and shipped frozen with dry ice to the laboratory. Frozen cores were processed within 24 h in an anaerobic glovebox. As cores were opened in the glovebox, sediment samples were collected at selected intervals, targeting regions with varying particle sizes for DNA extraction and chemical analyses. Subsamples (3–7 per core, in duplicate, 0.2–0.6 m apart to capture changes in particle size) were preserved (−80 °C for chemical, −20 °C for molecular) prior to analyses. Water samples were collected from monitoring wells by using a submersible Keck pump. Samples for measurement of dissolved oxygen (DO), pH, hydrogen sulfide (H2S), methane (CH4), and dissolved hydrocarbons were collected without filtration. The pH was determined in the field with an electrode (YSI), and DO was determined by colorimetric CHEMets visual kits (CHEMetrics, Inc., Midland, Va). Concentrations of H2S were determined in the field by using the methylene blue procedure with a V-2000 Photometer (CHEMetrics, Inc). Samples for dissolved CH4 analyses were collected with glass syringes and inserted into baked-glass serum bottles containing tri sodium phosphate preservative by using a method modified from Baedecker and Cozzarelli [19]. Samples for hydrocarbon analyses were collected into 40-mL baked glass bottles, filled without headspace, and preserved to pH 2 with hydrochloric acid (HCl). Samples collected for nonvolatile dissolved organic carbon (NVDOC) were filtered through 0.20-μm Supor® filters (Pall, Port Washington, NY) into baked-glass bottles, preserved with HCl to a pH of 2. Samples collected for
Insights into Biodegradation Fig. 1 a Map of Bemidji site illustrating rupture (star), water with >10 ppb dissolved benzene, toluene, ethylbenzene, and xylenes (BTEX) (as of 1996, red line), and core sampling locations within the plume and in adjacent wetland (triangles). b Map of generalized geochemical zones along a cross section of the plume (1995, adapted from Essaid et al. 2011)
alkalinity and anions were filtered through 0.20-μm Nuclepore filters. Cations were filtered through 0.1-μm Nuclepore filters and preserved to pH 2 with nitric acid (HNO3). All samples were stored on ice before and during transport to the laboratory. Molecular Analyses DNA was extracted from sediment (0.5 g) by using a FastDNA™ SPIN Kit for Soil (MP Biomedicals, Solon, OH) according to the manufacturer’s instructions. Quantitative PCR (qPCR) was performed for 16S ribosomal RNA (rRNA) [14], mcrA [15], and dsrA [15] genes as previously described. Additionally, qPCR was performed for bzdN genes by using primers designed by Kuntze et al. [16]. A 25-μL reaction mixture consisted of 1X SosoFast™ Evagreen® Supermix (Bio-Rad, Hercules, CA), primers (final concentration 0.3 μM), and 1-μL DNA extract. qPCR was performed (at 1:10 dilution) on aquifer sediment core DNA extracts. All qPCR standard curves were constructed from serial dilutions of cloned genes ranging from 108 to 102 gene copies per microliter, which were quantified using agarose gel densitometry using SYBR® Green nucleic acid stain (Molecular Probes, Inc., Eugene, OR) and 10-kb ladder (Promega,
Madison, WI) as standard on a Gel Doc XR Imager with Image Lab Software (Bio-Rad, Hercules, CA). Samples were analyzed in triplicate with a blank in each batch. Gene copy numbers were normalized to 16S rRNA gene copies prior to analysis. Normalization to 16S rRNA gene copies aids in adjusting for minor variations in sample processing and also serves as an indicator of the total bacterial population carrying the functional genes of interest. To obtain standards for the bzdN qPCR assay, PCR product was cloned using the TOPO® TA Cloning Kit for Sequencing (Invitrogen, Carlsbad, CA). Clones (20 per reaction) were randomly selected for confirmation of specificity by DNA sequencing. A restriction digest was performed using restriction enzyme MspI. Unique samples were purified with ExoSAP-IT® (Affymetrix, Santa Clara, CA) and subject to Sanger sequencing (Virginia Bioinformatics Institute, Blacksburg, VA). Sequencing results were compared to public databases via Basic Local Alignment Search Tool (BLAST, NCBI, http://blast.ncbi.nlm.nih.gov/Blast.cgi). For denaturing gradient gel electrophoresis (DGGE), 16S rRNA genes were PCR-amplified using forward primer 8f and reverse primer 1492r [17], followed by a nested PCR reaction using 341f-GC and 533r primers [18]. PCR was performed using a GenScript Taq kit in a 25-μL reaction volume on
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1:110 dilution of DNA extracts, which was shown to reduce inhibition. DGGE was performed by using DCode™ system (Bio-Rad, Hercules, CA). The gels were prepared using 8 % acrylamide with a denaturing gradient form and 35–65 % for cores and electrophoresed at 50 V for 18 h. The gels were stained with 1X SYBR Gold (Molecular Probes) and documented using a Gel Doc XR system (Bio-Rad). DGGE fingerprints were digitized using Image Lab software (Bio-Rad). Pyrosequencing was performed on 16S rRNA gene products obtained from two randomly selected DNA extracts for each site (Research and Testing, Lubbock, TX), with results presented only for samples yielding an acceptable number of sequences meeting the quality criteria (n=1,923 sequences per sample). For pyrosequencing, diluted DNA extracts were amplified with barcode-labeled forward primer 341f and 907r as follows: initial denaturation at 95 °C for 5 min, 30 cycles of 94 °C for 30 s, 54 °C for 45 s, and 72 °C for 60 s, followed by a final extension 72 °C for 10 min. PCR product from each sample was quantified and mixed proportionally with each other prior to pyrosequencing on a Roche 454 FLX Titanium platform (Roche, Nutley, NJ). Sequences have been submitted to EMBL database and are available under accession number PRJEB5193. The average number of sequences per sample was 7,630. Error reduction (shhh.flows), primer and barcode removal (trim.seqs), sequence quality improvement (pre.cluster), chimeras check (chimera.uchime), and contaminant removal (remove.lineage) were performed following Schloss standard operation protocol using Mothur v.1.31.2 [19]. Sequences were clustered into operational taxonomic units (OTUs) based on sequence dissimilarity (3 % cutoff) or taxonomic information. The taxonomic affiliation of the OTUs was determined against Ribosomal Database Project (RDP) references using the Mothur version of the“Bayesian”rRNA classifier with a confidence threshold of 80 %. Normalized OTU outputs generated by subsampling (i.e., n=1,923 sequences) were used to calculate relative abundance, richness, and the inverse Simpson diversity index (chao-invsimpson). Normalized OTU outputs were used for cluster and multidimensional scaling (MDS) analyses, as described below. Laboratory Chemical Analyses Sediment samples for chemical analysis were dried and sieved (
