New insights into iron acquisition by cyanobacteria: an essential role for ExbB-ExbD complex in inorganic iron uptake
Bibliographic record
Abstract
Cyanobacteria are globally important primary producers that have an exceptionally large iron requirement for photosynthesis. In many aquatic ecosystems, the levels of dissolved iron are so low and some of the chemical species so unreactive that growth of cyanobacteria is impaired. Pathways of iron uptake through cyanobacterial membranes are now being elucidated, but the molecular details are still largely unknown. Here we report that the non-siderophore-producing cyanobacterium Synechocystis sp. PCC 6803 contains three exbB-exbD gene clusters that are obligatorily required for growth and are involved in iron acquisition. The three exbB-exbDs are redundant, but single and double mutants have reduced rates of iron uptake compared with wild-type cells, and the triple mutant appeared to be lethal. Short-term measurements in chemically well-defined medium show that iron uptake by Synechocystis depends on inorganic iron (Fe') concentration and ExbB-ExbD complexes are essentially required for the Fe' transport process. Although transport of iron bound to a model siderophore, ferrioxamine B, is also reduced in the exbB-exbD mutants, the rate of uptake at similar total [Fe] is about 800-fold slower than Fe', suggesting that hydroxamate siderophore iron uptake may be less ecologically relevant than free iron. These results provide the first evidence that ExbB-ExbD is involved in inorganic iron uptake and is an essential part of the iron acquisition pathway in cyanobacteria. The involvement of an ExbB-ExbD system for inorganic iron uptake may allow cyanobacteria to more tightly maintain iron homeostasis, particularly in variable environments where iron concentrations range from limiting to sufficient.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".