Iron and vitamin interactions in marine diatom isolates and natural assemblages of the Northeast Pacific Ocean
Bibliographic record
Abstract
Abstract Trace metals and B‐vitamins play critical roles in regulating marine phytoplankton growth and composition. While some microorganisms are capable of producing certain B‐vitamins, others cannot synthesize them and depend on an exogenous supply. Therefore, external factors influencing vitamin synthesis, such as micronutrient concentrations, alter the extent to which B‐vitamins are available to auxotrophs in surface waters. We examined iron, B7 (biotin) and B12 (cobalamin) dynamics in diatoms through laboratory culture experiments and within natural diatom assemblages present along an iron gradient in the Northeast Pacific Ocean. In laboratory cultures of the diatom Pseudo‐nitzschia granii, biotin synthase (BIOB) expression decreased 2‐fold under iron limitation, suggesting iron status may affect B7 production in diatoms. Additionally in laboratory cultures of the diatom Grammonema cf. islandica, which contains a B12‐independent methionine synthase (METE), a 15‐fold increase in the expression of METE was observed when grown in the absence of B12 with no significant influence of iron status, suggesting METE expression can be driven by B12 status alone. Iron and B‐vitamin amendment experiments with natural diatom assemblages in iron‐limited waters of the Northeast Pacific Ocean provide evidence for vitamin‐associated molecular responses that suggest elevated B7 biosynthesis and the emergence of B12 limitation following iron addition. Furthermore B‐vitamin gene modules comprised of partial and/or complete B‐vitamin biosynthetic pathways in diatoms increased in response to iron addition, including genes potentially involved in the processing of B12 intermediates. Our results indicate that vitamins may play an important role in regulating phytoplankton growth and composition in this region, particularly following natural iron addition events.
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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 | 0.001 | 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".