Iron acquisition and its control in pseudomonas aeruginosa many roads lead to rome
Bibliographic record
Abstract
Iron plays an important role in the pathogenesis and rhizosphere competence of the fluorescent group of pseudomonads and it is, thus, fitting that the characteristic fluorescence of these organisms is attributable to an iron-chelating molecule, pyoverdine. Pseudomonas aeruginosa is likely the best-studied member of this group, and while it synthesizes two siderophores, pyochelin and pyoverdine, it is also able to use a number of heterologous siderophores of fungal and bacterial origin and its genome is rich with homologues of iron-siderophore receptor genes, reflecting the enormous flexibility of the organism vis-a-vis iron carriers that it can use in nature. The ability to utilize a variety of heterologous siderophores is shared by other fluorescent pseudomonads and likely reflects both the importance of this vital nutrient for growth and survival and the need to compete with other microorganisms in the aquatic and terrestrial environments that they inhabit. Expression of the various receptors is, however, regulated, with receptor production responding positively to available siderophores only, and selection from multiple available siderophores based on their successful chelation of iron and subsequent transport. Thus, the superior siderophore in a given environment will upregulate the cognate receptor at the expense of other receptors. Such siderophore-dependent regulation of receptor gene expression is common in bacteria, particularly the fluorescent pseudomonads, and typically requires a signal transduction cascade that involves the receptor itself, whose binding to the siderophore initiates the cascade, as well as a regulatory protein pair that includes an environmentally-responsive so-called extracytoplasmic function (ECF) sigma factor, which activates receptor gene expression, and an anti-sigma factor that controls sigma factor activity. Despite the plethora of ferric siderophore receptors in P. aeruginosa, its genome sequence reveals a striking lack of obvious periplasmic and cytoplasmic membrane transport components capable of accommodating these molecules. Unlike e.g. Escherichia coli, then, where ferric siderophore permeases providing transport to the cytoplasm are clearly in evidence, iron-siderophore complexes in P. aeruginosa may be dissociated in the periplasm, with a common iron carrier then responsible for iron uptake into the cell interior.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".