The role of the synergistic phosphate anion in iron transport by the periplasmic iron-binding protein from <i>Haemophilus influenzae</i>
Bibliographic record
Abstract
The acquisition of iron from transferrin by Gram-negative bacterial pathogens is dependent on a periplasmic ferric-ion-binding protein, FbpA. FbpA shuttles iron from the outer membrane to an inner membrane transport complex. A bound phosphate anion completes the iron co-ordination shell of FbpA and kinetic studies demonstrate that the anion plays a critical role in iron binding and release in vitro. The present study was initiated to directly address the hypothesis that the synergistic anion is required for transport of iron in intact cells. A series of site-directed mutants in the anion-binding amino acids of the Haemophilus influenzae FbpA (Gln-58, Asn-175 and Asn-193) were prepared to provide proteins defective in binding of the phosphate anion. Crystal structures of various mutants have revealed that alteration of the C-terminal domain ligands (Asn-175 or Asn-193) but not the N-terminal domain ligand (Gln-58) abrogated binding of the phosphate anion. The mutant proteins were introduced into H. influenzae to evaluate their ability to mediate iron transport. All of the single site-directed mutants (Q58L, N175L and N193L) were capable of mediating iron acquisition from transferrin and from limiting concentrations of ferric citrate. The results suggest that the transport of iron by FbpA is not dependent on binding of phosphate in the synergistic anion-binding site.
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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 | 0.000 |
| 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".