Biodegradation of mixed polycyclic aromatic hydrocarbons by newly isolated Priestia megaterium KS01 and its enzymatic pathway profiling
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are environmentally persistent contaminants of concern due to their toxicity, mutagenicity, and resistance to natural attenuation. Biodegradation by specialized microorganisms represents an effective strategy for their removal from contaminated environments. In this study, a novel bacterial strain, Priestia megaterium KS01, was isolated from oil sand tailings, demonstrating significant potential for PAHs biodegradation. Hydrocarbon degradation efficiency decreased with increasing chain length (C 9 -C 12 ) and diesel concentrations (3%, 5%, and 10% v/v), consistent with reduced bioavailability and substrate inhibition. GC-MS profiling of representative PAHs showed distinct compound-specific behaviors. Approximately 40% methylated naphthalenes were removed efficiently at low diesel concentrations of 3% (v/v) but were strongly inhibited at higher loads (5% and 10% v/v). In contrast, acenaphthylene, acenaphthene, and fluorene exhibited enhanced degradation at elevated diesel concentrations of 10% (v/v), suggesting co-metabolic stimulation. Proteomic analysis identified key enzymes, including cytochrome P450, α/β-hydrolase fold proteins, and ring-cleaving dioxygenases, supporting the presence of dual monooxygenase- and dioxygenase-mediated pathways. Together, these results highlight the metabolic versatility of P. megaterium KS01 and its strong potential as a candidate for the bioremediation of PAH-contaminated environments. • Priestia megaterium KS01, isolated from oil sand tailings, efficiently degrades polycyclic aromatic hydrocarbons (PAHs). • Degradation decreased with higher chain length (C 9 –C 12 ) and diesel load (3–10% v/v). • Methylated naphthalenes degraded by nearly 40% at 3% (v/v) diesel in 15 days. • Acenaphthylene, acenaphthene, and fluorene showed co-metabolic stimulation at 10% (v/v) diesel. • Enzymatic analysis revealed dual monooxygenase- and dioxygenase-mediated PAH
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".