Transcriptome Analysis of Environmental Pseudomonas Isolates Reveals Mechanisms of Biodegradation of Naphthenic Acid Fraction Compounds (NAFCs) in Oil Sands Tailings
Bibliographic record
Abstract
Naphthenic acid fraction compounds (NAFCs) are highly recalcitrant constituents of oil sands tailings. Although some microorganisms in the tailings can individually and synergistically metabolize NAFCs, the biochemical mechanisms that underpin these processes are hitherto unknown. To this end, we isolated two microorganisms, Pseudomonas protegens and Pseudomonas putida, from oils sands tailings and analyzed their transcriptomes to shed light on the metabolic processes employed by them to degrade and detoxify NAFCs. We identified 1048, 521 and 1434 genes that are upregulated in P. protegens, P. putida and a 1:1 co-culture of the strains, respectively. We subsequently enumerated the biochemical activities of enriched genes and gene products to reveal the identities of the enzymes that are associated with NAFC degradation. Separately, we analyzed the NAFCs that are degraded by the two pseudomonads and their 1:1 co-culture and determined the composition of the molecules using mass spectrometry. We then compared these molecular formulas to those of the cognate substrates of the enriched enzymes to chart the metabolic network and understand the mechanisms of degradation that are employed by the microbial cultures. Not only does the consortium behave differently than the pure cultures, but our analysis also revealed the mechanisms responsible for accelerated rate of degradation of NAFCs by the co-culture. Our findings provide new directions for engineering or evolving microorganisms and their consortia for degrading NAFCs more stably and aggressively.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 0.000 |
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".