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Record W4389068196 · doi:10.1093/femsec/fiad153

Microbial degradation of naphthenic acids using constructed wetland treatment systems: metabolic and genomic insights for improved bioremediation of process-affected water

2023· article· en· W4389068196 on OpenAlexafffund
Paula C. J. Reis, Sara Correa‐García, Julien Tremblay, Aurélie Beaulieu-Laliberté, Douglas G. Muench, Jason M. E. Ahad, Étienne Yergeau, Jérôme Comte, Christine Martineau

Bibliographic record

VenueFEMS Microbiology Ecology · 2023
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsGeological Survey of CanadaUniversity of CalgaryNatural Resources CanadaUniversité de MontréalNational Research Council CanadaInstitut National de la Recherche Scientifique
FundersGenome AlbertaGenome Canada
KeywordsBioremediationEnvironmental chemistryDegradation (telecommunications)Microbial biodegradationChemistryBiodegradationMetabolic pathwayMicroorganismBiochemical engineeringBiochemistryBiologyContaminationEcologyOrganic chemistryBacteriaMetabolismComputer science

Abstract

fetched live from OpenAlex

Naphthenic acids (NAs) are a complex mixture of organic compounds released during bitumen extraction from mined oil sands that are important contaminants of oil sands process-affected water (OSPW). NAs can be toxic to aquatic organisms and, therefore, are a main target compound for OSPW. The ability of microorganisms to degrade NAs can be exploited for bioremediation of OSPW using constructed wetland treatment systems (CWTS), which represent a possible low energy and low-cost option for scalable in situ NA removal. Recent advances in genomics and analytical chemistry have provided insights into a better understanding of the metabolic pathways and genes involved in NA degradation. Here, we discuss the ecology of microbial NA degradation with a focus on CWTS and summarize the current knowledge related to the metabolic pathways and genes used by microorganisms to degrade NAs. Evidence to date suggests that NAs are mostly degraded aerobically through ring cleavage via the beta-oxidation pathway, which can be combined with other steps such as aromatization, alpha-oxidation, omega-oxidation, or activation as coenzyme A (CoA) thioesters. Anaerobic NA degradation has also been reported via the production of benzoyl-CoA as an intermediate and/or through the involvement of methanogens or nitrate, sulfate, and iron reducers. Furthermore, we discuss how genomic, statistical, and modeling tools can assist in the development of improved bioremediation practices.

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 score0.006
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.012
GPT teacher head0.238
Teacher spread0.226 · 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

Citations17
Published2023
Admission routes2
Has abstractyes

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