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Record W4415929971 · doi:10.1016/j.jece.2025.120131

Biodegradation of mixed polycyclic aromatic hydrocarbons by newly isolated Priestia megaterium KS01 and its enzymatic pathway profiling

2025· article· en· W4415929971 on OpenAlexafffund
Khyati Joshi, Sara Magdouli, Satinder Kaur Brar

Bibliographic record

VenueJournal of environmental chemical engineering · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of OttawaYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiodegradationBioremediationBacillus megateriumHydrocarbonDiesel fuelPolycyclic aromatic hydrocarbonBioavailabilityFluorene

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.168
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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