Methanotrophic bacteria in warm geothermal spring sediments identified using stable-isotope probing
Bibliographic record
Abstract
We investigated methanotrophic bacteria in sediments of several warm geothermal springs ranging in temperature from 22 to 45 °C. Methane oxidation was measured at potential rates up to 141 μmol CH4 d−1 g−1 sediment. Active methanotrophs were identified using 13CH4 stable-isotope probing (SIP) incubations performed at close to in situ temperatures for each site. Quantitative (q) PCR of pmoA genes identified the position of the heavy (13C-labelled) DNA fractions in density gradients, and 16S rRNA gene pyrotag sequencing of the heavy fractions was performed to identify the active methanotrophs. Methanotroph communities identified in heavy fractions of all samples were predominated by species similar (≥ 95% 16S rRNA gene identities) to previously characterized Gammaproteobacteria and Alphaproteobacteria methanotrophs. Among the five hottest samples (45 °C), members of the Gammaproteobacteria genus Methylocaldum dominated in two cases, while three others were dominated by an OTU closely related (96.8% similarity) to the Alphaproteobacteria genus Methylocapsa. These results suggest that diverse methanotroph groups are adapted to warm environments, including the Methylocapsa-Methylocella-Methyloferula group, which has previously only been detected in cooler sites. DNA stable-isotope probing of warm geothermal springs (~45 °C) identified the predominantly active methanotrophs as highly similar to the Alphaproteobacteria genera Methylocapsa (example above), Methylosinus and Methylocystis, or the Gammaproteobacteria genus Methylocaldum. DNA stable-isotope probing of warm geothermal springs (~45 °C) identified the predominantly active methanotrophs as highly similar to the Alphaproteobacteria genera Methylocapsa (example above), Methylosinus and Methylocystis, or the Gammaproteobacteria genus Methylocaldum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".