Structural and functional insights into iron acquisition from lactoferrin and transferrin in Gram-negative bacterial pathogens
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Iron is an essential element for various lifeforms but is largely insoluble due to the oxygenation of Earth's atmosphere and oceans during the Proterozoic era. Metazoans evolved iron transport glycoproteins, like transferrin (Tf) and lactoferrin (Lf), to keep iron in a non-toxic, usable form, while maintaining a low free iron concentration in the body that is unable to sustain bacterial growth. To survive on the mucosal surfaces of the human respiratory tract where it exclusively resides, the Gram-negative bacterial pathogen Moraxella catarrhalis utilizes surface receptors for acquiring iron directly from human Tf and Lf. The receptors are comprised of a surface lipoprotein to capture iron-loaded Tf or Lf and deliver it to a TonB-dependent transporter (TBDT) for removal of iron and transport across the outer membrane. The subsequent transport of iron into the cell is normally mediated by a periplasmic iron-binding protein and inner membrane transport complex, which has yet to be determined for Moraxella catarrhalis. We identified two potential periplasm to cytoplasm transport systems and performed structural and functional studies with the periplasmic binding proteins (FbpA and AfeA) to evaluate their role. Growth studies with strains deleted in the fbpA or afeA gene demonstrated that FbpA, but not AfeA, was required for growth on human Tf or Lf. The crystal structure of FbpA with bound iron in the open conformation was obtained, identifying three tyrosine ligands that were required for growth on Tf or Lf. Computational modeling of the YfeA homologue, AfeA, revealed conserved residues involved in metal binding.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it