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Record W4387706379 · doi:10.3897/aca.6.e108247

Elevated bacterial endospores associated with thermogenic hydrocarbon seeps in deep sea sediments.

2023· article· en· W4387706379 on OpenAlexafffundabout
Jayne E. Rattray, Gretta Elizondo, Kathryn Sloan, Natasha Morrison, Martin G. Fowler, Daniel A. Gittins, Jamie Webb, D C Campbell, Adam MacDonald, Casey R. J. Hubert

Bibliographic record

VenueARPHA Conference Abstracts · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsMara Renewables (Canada)University of CalgaryGeological Survey of Canada
FundersNatural Resources CanadaOffshore Energy Research Association
KeywordsEndosporeFirmicutesDipicolinic acidGeologySedimentEnvironmental chemistryOceanographyChemistrySporePaleontologyBacteria

Abstract

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Introduction and approach Bacterial endospore distributions in marine sediments are influenced by geological conduits providing routes for subsurface to surface microbial dispersal. To examine this phenomenon in more detail, endospore abundance was determined by quantifying the biomarker 2,6-pyridine dicarboxylic acid (dipicolinic acid or DPA) in 16 deep sea sediment cores from hydrocarbon prospective areas in the NW Atlantic Ocean. DPA is specific to endospore-forming bacteria from the phylum Firmicutes and constitutes a significant percentage of endospore dry weight. DPA is therefore a potential biomarker for sediment dwelling endospores and geological conduits. Piston cores (10), gravity cores (3) and box cores (3) were collected during two expeditions to the Scotian Slope in the NW Atlantic Ocean off the east coast of Canada aboard the CCGS Hudson in 2016 and 2018 (Campbell (2016), Campbell and Normandeau (2018), Campbell and MacDonald. (2016)). Sampling sites were 1970 to 2791 m water depth, with piston cores (n=3) ranging from 344 to 953 cmbsf and gravity cores (n=10) ranging from 43 to 739 cmbsf, box coring captured the top 25 cmbsf. To address the efficacy of DPA biomarker analysis as a tool for hydrocarbon seep location we established a modified Tb 3+ chelation method (Lomstein and Jørgensen (2012), Rattray (2021)). Sediment samples were extracted using acid hydrolysis, chelated with Tb3+ and analysed using HPLC fluorescence, measuring at 270 nm emission and 545 nm excitation. DPA concentrations were converted to Endospore numbers were calculated using 2.24 fmol DPA per endospore (Fichtel 2007), a conversion factor routinely used in other studies (Braun 2017, Gittins 2022, Heuer 2020, Lomstein 2012, Rattray 2022, Wörmer 2019, Lomstein and Jørgensen 2012). DPA concentrations were compared with measurements of over 250 different gaseous and liquid hydrocarbon compounds used to assess for the presence of thermogenic hydrocarbons. Results and discussion Samples and locations were assessed as being thermogenic hydrocarbon gas positive (stations 16-41, 18-07) or thermogenic hydrocarbon negative based on the abundance of C1-C5 hydrocarbons in sediments sampled from the same cores. Station 18-14 contained hydrocarbons from biogenic origin. Station 18-06 is the only site with higher endospore abundance but that was determined to be hydrocarbon negative. Deep water Scotian Slope sediment cores show high endospore abundance correlates with thermogenic hydrocarbon seeps (Fig. 1). Cores from locations lacking evidence for thermogenic hydrocarbons generally contained significantly lower endospore abundances, with the notable exception of site 18-06. This potential paleoenvironmental hydrocarbon seep site highlights the utility of a DPA proxy for potentially identifying ancient hydrocarbon seeps and investigating past geological systems. The association of high endospore abundances with thermogenic hydrocarbons and the quantity of gas expulsion points to an interesting new biological tool for understanding hydrocarbon seepage in the deep biosphere, based on DPA assays in marine sediments.

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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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.999

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)0.0060.001

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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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; both teacher heads agree on what is shown here.

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".

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Citations0
Published2023
Admission routes3
Has abstractyes

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