Photochemical reactivity of siderophores produced by marine heterotrophic bacteria and cyanobacteria based on characteristic Fe(III) binding groups
Bibliographic record
Abstract
Siderophores, high‐affinity Fe(III) ligands produced by microorganisms to facilitate iron acquisition, might contribute significantly to dissolved Fe(III) complexation in ocean surface waters. In previous work, we demonstrated the photoreactivity of the ferric ion complexes of several α‐hydroxy carboxylic acid—containing siderophores produced by heterotrophic marine bacteria. Here, we expand on our earlier studies and detail the photoreactivity of additional siderophores produced by both heterotrophic marine bacteria and marine cyanobacteria, making comparisons to synthetic and terrestrial siderophores that lack the α‐hydroxy carboxylate group. Our results suggest that, in addition to secondary photochemical reaction pathways involving reactive oxygen species, direct photolysis of Fe(III)‐siderophore complexes might be a significant source of Fe(II) and reactive Fe(III) in ocean surface waters. Our findings further indicate that the photoreactivity of siderophores is primarily determined by the chemical structure of the Fe(III) binding groups that they possess—hydroxamate, catecholate, or α‐hydroxy carboxylate moieties. Hydroxamate groups are photochemically resistant regardless of Fe(III) complexation. Catecholates, in contrast, are susceptible to photooxidation in the uncomplexed form but stabilized against photooxidation when ferrated. α‐Hydroxy carboxylate groups are stable as the uncomplexed acid, but when coordinated to Fe(III), these moieties undergo light‐induced ligand oxidation and reduction of Fe(III) to Fe(II). These photochemical properties appear to determine the reactivity and fate of Fe(III)‐binding siderophores in ocean surface waters, which in turn might significantly influence the biogeochemical cycling of iron.
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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".