Copper‐dependent iron transport in coastal and oceanic diatoms
Bibliographic record
Abstract
We investigated the presence of plasmalemma‐bound copper‐containing oxidases associated with the inducible iron (Fe) transport system in two diatoms of the genus Thalassiosira. Under Fe‐limiting conditions, Thalassiosira oceanica, an oceanic isolate, was able to enzymatically oxidize inorganic Fe(II) extracellularly. This oxidase activity was dependent on copper (Cu) availability and diminished by exposure to a multi‐Cu oxidase (MCO) inhibitor. The rates of Fe uptake from ferrioxamine B by Fe‐limited T. oceanica were also dependent on Cu availability in the growth media. The effects of Cu limitation on Fe(II) oxidation and Fe uptake from ferrioxamine B were partially reversed after a short exposure to a Cu addition, indicating that the putative oxidases contain Cu. Limited physiological experiments were also performed with the coastal diatom Thalassiosira pseudonana and provided some evidence for putative Cu‐containing oxidases in the high‐affinity Fe transport system of this isolate. To support these preliminary physiological data, we searched the newly available T. pseudonana genome for a multi‐Cu‐containing oxidase gene and, using real‐time polymerase chain reaction (PCR), quantified its expression under various Fe and Cu levels. We identified a putative MCO gene with predicted transmembrane domains and found that transcription levels of this gene were significantly elevated in Fe‐limited cells relative to Fe‐replete cells. These data collectively suggest that putative MCOs are part of the inducible Fe transport system of Fe‐limited diatoms, which act to oxidize Fe(II) following reductive dissociation of Fe(III) from strong organic complexes.
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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 | 0.000 | 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".