Sll1263, a Unique Cation Diffusion Facilitator Protein that Promotes Iron Uptake in the Cyanobacterium Synechocystis sp. Strain PCC 6803
Bibliographic record
Abstract
Cyanobacteria are known to survive in iron-deficient environments, but the ways in which they acquire Fe and acclimate are not completely understood. Here we report a novel gene sll1263 that is required for Synechocystis sp. strain PCC 6803 to grow under iron-deficient conditions. sll1263 encodes a putative cation diffusion facilitator protein (CDF) that shows 50% amino acid similarity with ferrous iron efflux protein (FieF) of heterotrophic bacteria. In bacteria, the gene product is involved in metal export from the cell, but in Synechocystis sll1263 plays a role in iron uptake. The results show that expression of sll1263 was induced by iron-deficient conditions and its inactivation significantly decreased the growth rate of an sll1263(-) mutant. Other genes known to be required for Fe acquisition were also strongly up-regulated in the mutant even in the presence of high Fe. Overexpression of sll1263 increased growth under iron deficiency but reduced growth under high-iron stress, suggesting that the gene product was involved in iron uptake rather than detoxification. Expression of FieF in the sll1263(-) mutant was unable to rescue the Fe-deficient phenotype, but Sll1263 completely restored it. Measurements of cellular iron content and the iron uptake rate showed that they were significantly less in the sll1263(-) mutant than in the wild type, consistent with a role for sll1263 in iron uptake. We hypothesize that the low-iron habitats and high-iron requirements of cyanobacteria may be the reason why cyanobacterial CDF protein functions in Fe uptake and not efflux as in non-photosynthetic bacteria.
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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) | 0.001 | 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".