Methane assimilation and trophic interactions with marine Methylomicrobium in deep-water coral reef sediment off the coast of Norway
Bibliographic record
Abstract
Deep-water coral reefs are seafloor environments with diverse biological communities surrounded by cold permanent darkness. Sources of energy and carbon for the nourishment of these reefs are presently unclear. We investigated one aspect of the food web using DNA stable-isotope probing (DNA-SIP). Sediment from beneath a Lophelia pertusa reef off the coast of Norway was incubated until assimilation of 5 micromol 13CH4 g(-1) wet weight occurred. Extracted DNA was separated into 'light' and 'heavy' fractions for analysis of labelling. Bacterial community fingerprinting of PCR-amplified 16S rRNA gene fragments revealed two predominant 13C-specific bands. Sequencing of these bands indicated that carbon from 13CH4 had been assimilated by a Methylomicrobium and an uncultivated member of the Gammaproteobacteria. Cloning and sequencing of 16S rRNA genes from the heavy DNA, in addition to genes encoding particulate methane monooxygenase and methanol dehydrogenase, all linked Methylomicrobium with methane metabolism. Putative cross-feeders were affiliated with Methylophaga (Gammaproteobacteria), Hyphomicrobium (Alphaproteobacteria) and previously unrecognized methylotrophs of the Gammaproteobacteria, Alphaproteobacteria, Deferribacteres and Bacteroidetes. This first marine methane SIP study provides evidence for the presence of methylotrophs that participate in sediment food webs associated with deep-water coral reefs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".