Two distinct pathways for iron acquisition by iron-limited cyanobacterial cells: evidence from experiments using siderophores and synthetic chelators
Bibliographic record
Abstract
Iron-limited cyanobacterial cells are generally considered to acquire extracellular iron through a siderophore-dependent system, although evidence has started to accumulate that other, as yet poorly characterized, iron acquisition systems may also play a role. Iron-limited cells of the cyanobacterium Anabaena flos-aquae (Lyng.) Brèb. are well known to produce the relatively low Fe(III) affinity dihydroxamate siderophore schizokinen. In this set of experiments we show that iron-limited A. flos-aquae cells (i) acquired iron at substantial rates in the absence of the schizokinen and (ii) acquired iron from a bacterial siderophore (the trihydroxamate molecule desferrioxamine B (DFB)), and also a synthetic chelator (N, N-bis(2-(bis(carboxymethyl)amino)ethyl)glycine (DTPA)), with substantially higher affinities for Fe(III) than schizokinen, indicating that a schizokinen-independent iron acquisition pathway was operating. We suggest that there exists a siderophore-independent iron acquisition system that is able to acquire Fe(III) from high stability Fe(III)-chelates, which are not accessible to iron-limited cells via the schizokinen-based system. As well, we present two possible models for iron acquisition by iron-limited A. flos-aquae cells. Both of these models suggest that there are two major routes for Fe(III) entry into the periplasm of iron-limited cells: (1) the well-characterized siderophore (schizokinen) dependent process and (2) a siderophore-independent process that is able to access Fe(III) sources not biologically available to the schizokinen system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".