Massive dominance of Epsilonproteobacteria in formation waters from a Canadian oil sands reservoir containing severely biodegraded oil.

The subsurface microbiology of an Athabasca oil sands reservoir in western Canada containing severely biodegraded oil was investigated by combining 16S rRNA gene- and polar lipid-based analyses of reservoir formation water with geochemical analyses of the crude oil and formation water. Biomass was filtered from formation water, DNA was extracted using two different methods, and 16S rRNA gene fragments were amplified with several different primer pairs prior to cloning and sequencing or community fingerprinting by denaturing gradient gel electrophoresis (DGGE). Similar results were obtained irrespective of the DNA extraction method or primers used. Archaeal libraries were dominated by Methanomicrobiales (410 of 414 total sequences formed a dominant phylotype affiliated with a Methanoregula sp.), consistent with the proposed dominant role of CO(2) -reducing methanogens in crude oil biodegradation. In two bacterial 16S rRNA clone libraries generated with different primer pairs, > 99% and 100% of the sequences were affiliated with Epsilonproteobacteria (n = 382 and 72 total clones respectively). This massive dominance of Epsilonproteobacteria sequences was again obtained in a third library (99% of sequences; n = 96 clones) using a third universal bacterial primer pair (inosine-341f and 1492r). Sequencing of bands from DGGE profiles and intact polar lipid analyses were in accordance with the bacterial clone library results. Epsilonproteobacterial OTUs were affiliated with Sulfuricurvum, Arcobacter and Sulfurospirillum spp. detected in other oil field habitats. The dominant organism revealed by the bacterial libraries (87% of all sequences) is a close relative of Sulfuricurvum kujiense - an organism capable of oxidizing reduced sulfur compounds in crude oil. Geochemical analysis of organic extracts from bitumen at different reservoir depths down to the oil water transition zone of these oil sands indicated active biodegradation of dibenzothiophenes, and stable sulfur isotope ratios for elemental sulfur and sulfate in formation waters were indicative of anaerobic oxidation of sulfur compounds. Microbial desulfurization of crude oil may be an important metabolism for Epsilonproteobacteria indigenous to oil reservoirs with elevated sulfur content and may explain their prevalence in formation waters from highly biodegraded petroleum systems.

Methods for recovery of microorganisms and intact microbial polar lipids from oil-water mixtures: laboratory experiments and natural well-head fluids.

Most of the world's remaining petroleum resource has been altered by in-reservoir biodegradation which adversely impacts oil quality and production, ultimately making heavy oil. Analysis of the microorganisms in produced reservoir fluid samples is a route to characterization of subsurface biomes and a better understanding of the resident and living microorganisms in petroleum reservoirs. The major challenges of sample contamination with surface biota, low abundances of microorganisms in subsurface samples, and viscous emulsions produced from biodegraded heavy oil reservoirs are addressed here in a new analytical method for intact polar lipids (IPL) as taxonomic indicators in petroleum reservoirs. We have evaluated the extent to which microbial cells are removed from the free water phase during reservoir fluid phase separation by analysis of model reservoir fluids spiked with microbial cells and have used the resultant methodologies to analyze natural well-head fluids from the Western Canada Sedimentary Basin (WCSB). Analysis of intact polar membrane lipids of microorganisms using liquid chromatography-mass spectrometry (LC-MS) techniques revealed that more than half of the total number of microorganisms can be recovered from oil-water mixtures. A newly developed oil/water separator allowed for filtering of large volumes of water quickly while in the field, which reduced the chances of contamination and alterations to the composition of the subsurface microbial community after sample collection. This method makes the analysis of IPLs (or indirectly microorganisms) from well-head fluids collected in remote field settings possible and reliable. To the best of our knowledge this is the first time that IPLs have been detected in well-head oil-water mixtures.

The biogeographical distribution of closely related freshwater sediment bacteria is determined by environmental selection.

The role of environmental selection in governing the structure of communities of freshwater sulfur bacteria (Achromatium spp) was experimentally tested by mixing sediments from two geographically separated lakes (Rydal Water (RY) and Hell Kettles (HK)) that harboured Achromatium spp. Community profiles of Achromatium spp in sediment microcosms at day 0 and after 60 days were compared to determine whether initial Achromatium community composition or subsequent selection by the sediment environment had greater influence in dictating the final Achromatium community structure. It was found that Achromatium spp from the HK community became established in mixed sediments at the expense of members of the RY community. This selection for the HK Achromatium community was more pronounced when sediment composition was manipulated to resemble HK sediments. Our findings definitively demonstrate that environmental selection is the primary determinant of Achromatium community structure in these sediments.

Development of a rapid assay for determining the relative abundance of bacteria.

A sandwich hybridization assay for high-throughput, rapid, simple, and inexpensive quantification of specific microbial populations was evaluated. The assay is based on the hybridization of a target rRNA with differentially labeled capture and detector probes. Betaproteobacterial ammonia-oxidizing bacteria (AOB) were selected as the target group for the study, since they represent a phylogenetically coherent group of organisms that perform a well-defined geochemical function in natural and engineered environments. Reagent concentrations, probe combinations, and washing, blocking, and hybridization conditions were optimized to improve signal and reduce background. The detection limits for the optimized RNA assay were equivalent to approximately 10(3) to 10(4) and 10(4) to 10(5) bacterial cells, respectively, for E. coli rRNA and RNA extracted from activated sludge, by using probes targeting the majority of bacteria. Furthermore, the RNA assay had good specificity, permitted discrimination of rRNA sequences that differed by a 2-bp mismatch in the probe target region, and could distinguish the sizes of AOB populations in nitrifying and nonnitrifying wastewater treatment plants.

Composition and diversity of ammonia-oxidising bacterial communities in wastewater treatment reactors of different design treating identical wastewater.

Autotrophic ammonia-oxidising bacteria (AOB) are a crucial component of the microbial communities of nitrifying wastewater treatment systems. Nitrification is known to occur in reactors of different configuration, but whether AOB communities are different in reactors of different design is unknown. We compared the diversity and community structure of the betaproteobacterial AOB in two full-scale treatment reactors - a biological aerated filter (BAF) and a trickling filter - receiving the same wastewater. Polymerase chain reaction (PCR) of 16S ribosomal RNA (rRNA) gene fragments with AOB-selective primers was combined with denaturing gradient gel electrophoresis (DGGE) to allow comparative analysis of the dominant AOB populations. The phylogenetic affiliation of the dominant AOB was determined by cloning and sequencing PCR-amplified 16S rRNA gene fragments. DGGE profiles were compared using a probability-based similarity index (Raup and Crick). The use of a probability-based index of similarity allowed us to evaluate if the differences and similarities observed in AOB community structure in different samples were statistically significant or could be accounted for by chance matching of bands in DGGE profiles, which would suggest random colonisation of the reactors by different AOB. The community structure of AOB was different in different sections of each of the reactors and differences were also noted between the reactors. All AOB-like sequences identified, grouped within the genus Nitrosomonas. A greater diversity of AOB was detected in the trickling filters than in the BAF though all samples analysed appeared to be dominated by AOB most closely related to Nitrosococcus mobilis. Numerical analysis of DGGE profiles indicated that the AOB communities in depth profiles from the filter beds were selected in a non-random manner.