Size and Carbon Content of Sub-seafloor Microbial Cells at Landsort Deep, Baltic Sea
Bibliographic record
Abstract
The discovery of a microbial ecosystem in ocean sediments has evoked interest in life under extreme energy limitation and its role in global element cycling. However, fundamental parameters such as the size and the amount of biomass of sub-seafloor microbial cells are poorly constrained. Here we determined the volume and the carbon content of microbial cells from a marine sediment drill core retrieved by the Integrated Ocean Drilling Program (IODP), Expedition 347, at Landsort Deep, Baltic Sea. To determine their shape and volume, cells were separated from the sediment matrix by multi-layer density centrifugation and visualized via epifluorescence microscopy (FM) and scanning electron microscopy (SEM). Total cell-carbon was calculated from amino acid-carbon, which was analyzed by high-performance liquid chromatography (HPLC) after cells had been purified by fluorescence-activated cell sorting (FACS). The majority of microbial cells in the sediment have coccoid or slightly elongated morphology. From the sediment surface to the deepest investigated sample (~60 m below the seafloor), the cell volume of both coccoid and elongated cells decreased by an order of magnitude from ~0.05 to 0.005 μm(3). The cell-specific carbon content was 19-31 fg C cell(-1), which is at the lower end of previous estimates that were used for global estimates of microbial biomass. The cell-specific carbon density increased with sediment depth from about 200 to 1000 fg C μm(-3), suggesting that cells decrease their water content and grow small cell sizes as adaptation to the long-term subsistence at very low energy availability in the deep biosphere. We present for the first time depth-related data on the cell volume and carbon content of sedimentary microbial cells buried down to 60 m below the seafloor. Our data enable estimates of volume- and biomass-specific cellular rates of energy metabolism in the deep biosphere and will improve global estimates of microbial biomass.
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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 | 0.000 |
| 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".