Conserved Interaction between Transferrin and Transferrin-binding Proteins from Porcine Pathogens
Bibliographic record
Abstract
Gram-negative porcine pathogens from the Pasteurellaceae family possess a surface receptor complex capable of acquiring iron from porcine transferrin (pTf). This receptor consists of transferrin-binding protein A (TbpA), a transmembrane iron transporter, and TbpB, a surface-exposed lipoprotein. Questions remain as to how the receptor complex engages pTf in such a way that iron is positioned for release, and whether divergent strains present distinct recognition sites on Tf. In this study, the TbpB-pTf interface was mapped using a combination of mass shift analysis and molecular docking simulations, localizing binding uniquely to the pTf C lobe for multiple divergent strains of Actinobacillus plueropneumoniae and suis. The interface was further characterized and validated with site-directed mutagenesis. Although targeting a common lobe, variants differ in preference for the two sublobes comprising the iron coordination site. Sublobes C1 and C2 participate in high affinity binding, but sublobe C1 contributes in a minor fashion to the overall affinity. Further, the TbpB-pTf complex does not release iron independent of other mediators, based on competitive iron binding studies. Together, our findings support a model whereby TbpB efficiently captures and presents iron-loaded pTf to other elements of the uptake pathway, even under low iron conditions.
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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".