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Record W2015411335 · doi:10.1021/es4020184

Metagenomics of Hydrocarbon Resource Environments Indicates Aerobic Taxa and Genes to be Unexpectedly Common

2013· article· en· W2015411335 on OpenAlexafffundabout
Dongshan An, Sean M. Caffrey, Jung Soh, Akhil Agrawal, Damon C. Brown, Karen Budwill, Xiaoli Dong, Peter F. Dunfield, Julia M. Foght, Lisa M. Gieg, Steven Hallam, Niels W. Hanson, Zhiguo He, Thomas R. Jack, Jonathan L. Klassen, Kishori M. Konwar, Eugene Kuatsjah, Carmen Li, Steve Larter, Verlyn Leopatra, Camilla Nesbø, Thomas B. P. Oldenburg, Antoine Pagé, Esther Ramos-Padrón, Fauziah F. Rochman, Christoph W. Sensen, Payal Sipahimalani, Young Song, Sandra L. Wilson, Gregor Wolbring, Man-Ling Wong, Gerrit Voordouw

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of British ColumbiaCanada's Michael Smith Genome Sciences CentreUniversity of CalgaryAlberta InnovatesGenome British ColumbiaUniversity of Alberta
FundersGenome AlbertaCanada Research ChairsGenome British ColumbiaNatural Sciences and Engineering Research Council of CanadaSyncrudeGovernment of AlbertaGenome CanadaCanadian Institute for Advanced ResearchSuncor Energy IncorporatedConocoPhillips
KeywordsArchaeaMetagenomicsHydrocarbonMethaneMicrobial population biologyBacteriaBiologyAnaerobic exerciseEnergy sourceOil sandsMicrobial metabolismAnaerobic bacteriaCoalMethanogenesisEcologyEnvironmental scienceEnvironmental chemistryGeneFossil fuelChemistryPaleontologyBiochemistry

Abstract

fetched live from OpenAlex

Oil in subsurface reservoirs is biodegraded by resident microbial communities. Water-mediated, anaerobic conversion of hydrocarbons to methane and CO2, catalyzed by syntrophic bacteria and methanogenic archaea, is thought to be one of the dominant processes. We compared 160 microbial community compositions in ten hydrocarbon resource environments (HREs) and sequenced twelve metagenomes to characterize their metabolic potential. Although anaerobic communities were common, cores from oil sands and coal beds had unexpectedly high proportions of aerobic hydrocarbon-degrading bacteria. Likewise, most metagenomes had high proportions of genes for enzymes involved in aerobic hydrocarbon metabolism. Hence, although HREs may have been strictly anaerobic and typically methanogenic for much of their history, this may not hold today for coal beds and for the Alberta oil sands, one of the largest remaining oil reservoirs in the world. This finding may influence strategies to recover energy or chemicals from these HREs by in situ microbial processes.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.006
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.004
GPT teacher head0.184
Teacher spread0.179 · 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.

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

Citations206
Published2013
Admission routes3
Has abstractyes

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