Possible influence of bacterial quorum sensing on the hydrolysis of sinking particulate organic carbon in marine environments
Bibliographic record
Abstract
A central component of the ocean's biological carbon pump is the export of sinking, photosynthetically derived, particulate organic carbon (POC). Bacteria colonize these particles and produce enzymes that hydrolyse sinking POC thereby acting as one of the major controls on the biological pump. Here we provide evidence that a bacterial cell-cell communication mechanism, quorum sensing (QS), may influence the activity of hydrolytic enzymes on sinking particles. We collected sinking POC from a site off Vancouver Island, Canada and found that it contained acylated homoserine lactones (AHLs), a suite of well-known bacterial communication molecules. Furthermore, we observed that the addition of exogenous AHLs to incubations containing sinking POC affected the activity of key hydrolytic enzymes involved in POC degradation in some cases. Our results suggest that AHL-based QS could play an important role in regulating the degradation of sinking POC and that variability in AHL-triggered POC hydrolysis is a heretofore unrecognized process that impacts the marine biological carbon pump.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".