High bicarbonate assimilation in the dark by Arctic bacteria
Bibliographic record
Abstract
Although both autotrophic and heterotrophic microorganisms incorporate CO₂ in the dark through different metabolic pathways, this process has usually been disregarded in oxic marine environments. We studied the significance and mediators of dark bicarbonate assimilation in dilution cultures inoculated with winter Arctic seawater. At stationary phase, bicarbonate incorporation rates were high (0.5-2.5 μg C L⁻¹ d⁻¹) and correlated with rates of bacterial heterotrophic production, suggesting that most of the incorporation was due to heterotrophs. Accordingly, very few typically chemoautotrophic bacteria were detected by 16S rRNA gene cloning. The genetic analysis of the biotin carboxylase gene accC putatively involved in archaeal CO₂ fixation did not yield any archaeal sequence, but amplified a variety of bacterial carboxylases involved in fatty acids biosynthesis, anaplerotic pathways and leucine catabolism. Gammaproteobacteria dominated the seawater cultures (40-70% of cell counts), followed by Betaproteobacteria and Flavobacteria as shown by catalyzed reporter deposition fluorescence in situ hybridization (CARDFISH). Both Beta- and Gammaproteobacteria were active in leucine and bicarbonate uptake, while Flavobacteria did not take up bicarbonate, as measured by microautoradiography combined with CARDFISH. Within Gammaproteobacteria, Pseudoalteromonas-Colwellia and Oleispira were very active in bicarbonate uptake (ca. 30 and 70% of active cells, respectively), while the group Arctic96B-16 did not take up bicarbonate. Our results suggest that, potentially, the incorporation of CO₂ can be relevant for the metabolism of specific Arctic heterotrophic phylotypes, promoting the maintenance of their cell activity and/or longer survival under resource depleted conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".