Iron‐free pyoverdin binds to its outer membrane receptor FpvA in <i>Pseudomonas aeruginosa</i>: a new mechanism for membrane iron transport
Bibliographic record
Abstract
Under iron limitation, Pseudomonas aeruginosa secretes a fluorescent siderophore called pyoverdin, which, after complexing iron, is transported back into the cell via its outer membrane receptor FpvA. Previous studies demonstrated co-purification of FpvA with iron-free PaA and reported similar binding affinities of iron-free pyoverdin and ferric-pyoverdin to purified FpvA. The fluorescence resonance energy transfer between iron-free PaA and the FpvA receptor here reveals the existence of an FpvA-pyoverdin complex in P. aeruginosa in vivo, suggesting that the pyoverdin-loaded FpvA is the normal state of the receptor in the absence of iron. Using tritiated ferric-pyoverdin, it is shown that iron-free PaA binds to the outer membrane but is not taken up into the cell, and that in vitro and, presumably, in vivo ferric-pyoverdin displaces the bound iron-free pyoverdin on FpvA-PaA to form FpvA-PaA-Fe complexes. In vivo, the kinetics of formation of this FpvA-PaA-Fe complex are more than two orders of magnitude faster than in vitro and depend on the presence of TonB. In P. aeruginosa, two tonB genes have been identified (tonB1 and tonB2). TonB1 is directly involved in ferric-pyoverdin uptake, and TonB2 seems to be able partially to replace TonB1 in its role in iron acquisition. However, no effect of TonB1 or TonB2 on the apparent affinity of free pyoverdin to FpvA was observed, and a 17-fold difference was measured between the affinities of the two forms of pyoverdin (PaA and PaA-Fe) to FpvA in the absence of TonB1 or TonB2. The mechanism of iron uptake in P. aeruginosa via the pyoverdin pathway is discussed in view of these new findings.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".