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.
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 | 0.000 | 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) | 0.001 | 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".