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Record W4295037640 · doi:10.1021/acs.est.2c02624

Transient Oxygen Exposure Causes Profound and Lasting Changes to a Benzene-Degrading Methanogenic Community

2022· article· en· W4295037640 on OpenAlexafffund
Shen Guo, Courtney R. A. Toth, Fei Luo, Xu Chen, Johnny Xiao, Elizabeth A. Edwards

Bibliographic record

VenueEnvironmental Science & Technology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Toronto
FundersAlberta InnovatesGenome CanadaOntario GenomicsMitacsGovernment of OntarioImperial Oil Limited
KeywordsMethanogenesisBenzeneEnvironmental chemistryAnaerobic exerciseChemistryOxygenAnoxic watersArchaeaMicrobial population biologyBiodegradationEnrichment cultureMicrobiologyFood scienceBiologyBacteriaMethaneBiochemistryOrganic chemistryPhysiology

Abstract

fetched live from OpenAlex

We investigated the impact of oxygen on a strictly anaerobic, methanogenic benzene-degrading enrichment culture derived decades ago from oil-contaminated sediment. The culture includes a benzene fermenter from Deltaproteobacteria candidate clade Sva0485 (referred to as ORM2) and methanogenic archaea. A one-time injection of 0.1 mL air, simulating a small leak into 30 mL batch culture bottle, had no measurable impact on benzene degradation rates, although retrospectively, a tiny enrichment of aerobic taxa was detected. A subsequent 100 times larger injection of air stalled methanogenesis and caused drastic perturbation of the microbial community. A benzene-degrading Pseudomonas became highly enriched and consumed all available oxygen. Anaerobic benzene-degrading ORM2 cell numbers plummeted during this time; re-growth and associated recovery of methanogenic benzene degradation took almost 1 year. These results highlight the oxygen sensitivity of this methanogenic culture and confirm that the mechanism for anaerobic biotransformation of benzene is independent of oxygen, fundamentally different from established aerobic pathways, and is carried out by distinct microbial communities. The study also highlights the importance of including microbial decay in characterizing and modeling mixed microbial communities.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations11
Published2022
Admission routes2
Has abstractyes

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