Massive dominance of <i>Epsilonproteobacteria</i> in formation waters from a Canadian oil sands reservoir containing severely biodegraded oil
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".