Structural Biology of Bacterial Iron Uptake Systems
Bibliographic record
Abstract
Numerous bacterial proteins are involved in microbial iron uptake and transport and considerable variation has been found in the uptake schemes used by different bacterial species. However, whether extracting iron from host proteins such as transferrin, lactoferrin or hemoglobin or importing low molecular weight iron-chelating compounds such as heme, citrate or siderophores, Gram-negative pathogenic bacteria typically employ a specific outer membrane receptor, a periplasmic binding protein and two inner membrane associated proteins: a transporter coupled with an ATP-hydrolyzing protein. Often, studies have shown that proteins with similar function but little amino acid sequence homology are structurally related. Elucidation of the structures of the Escherichia coli outer membrane siderophore transport proteins FepA and FhuA have provided the first insights into the conformational changes required for ligand transport through the bacterial outer membrane. The variations between the structures of the prototypical periplasmic ferric binding protein FbpA from Neisseria and Haemophilus influenzae and the unusual E coli periplasmic siderophore binding protein FhuD reveal that the different periplasmic ligand binding proteins exercise distinct mechanisms for ligand binding and release. The structure of the hemophore HasA from Serratia marcescens shows how heme may be extracted and utilized by the bacteria. Other biochemical evidence also shows that the proteins that provide energy for iron transport at the outer membrane, such as the TonB-ExbB-ExbD system, are structurally very similar across bacterial species. Likewise, the iron-sensitive gene regulatory protein Fur is found in most bacteria. To date, no structural information is available for Fur, but the structure for the related protein DxtR has been determined. Together, these three-dimensional structures complement our knowledge of iron transport systems from other pathogenic bacteria, including Pseudomonas aeruginosa, which has a number of homologous iron uptake proteins. More importantly, the current structures for iron transport proteins provide rational starting points for design of novel antimicrobial agents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".