Synthetic Peptide Immunogens Elicit Polyclonal and Monoclonal Antibodies Specific for Linear Epitopes in the D Motifs of <i>Staphylococcus aureus</i> Fibronectin-Binding Protein, Which Are Composed of Amino Acids That Are Essential for Fibronectin Binding
Bibliographic record
Abstract
A fibronectin (Fn)-binding adhesin of Staphylococcus aureus contains three tandem 37- or 38-amino-acid motifs (D1, D2, and D3), which function to bind Fn. Plasma from patients with S. aureus infections contain antibodies that preferentially recognize ligand induced binding sites in the D motifs and do not inhibit Fn binding (F. Casolini, L. Visai, D. Joh, P. G. Conaldi, A. Toniolo, M. Höök, and P. Speziale, Infect. Immun. 66:5433-5442, 1998). To eliminate the influence of Fn binding on antibody development, we used synthetic peptide immunogens D1(21-34) and D3(20-33), which each contain a conserved pattern of amino acids that is essential for Fn binding but which cannot bind Fn without N- or C-terminal extensions. The D3(20-33) immunogen promoted the production of polyclonal antibodies that were 10-fold more effective as inhibitors of Fn-binding to the D3 motif than antibodies obtained by immunizing with an extended peptide D3(16-36), which exhibits functional Fn binding. The D3(20-33) immunogen also facilitated the production of a monoclonal antibody, 9C3, which was highly specific for the epitope SVDFEED, and abolished Fn binding by the D3 motif. When mixed with polyclonal anti-D1(21-34) immunoglobulin G, 70% inhibition of Fn binding to the three tandem D motifs was achieved compared to no more than 30% inhibition with either antibody preparation alone. Therefore, by immunizing with short synthetic peptides that are unable to bind Fn, we have effectively stimulated the production of antibodies specific for epitopes comprised of amino acids that are essential for Fn binding. Although these epitopes occur within a conserved pattern of amino acids that is required for Fn binding, the antibodies recognized specific linear epitope sequences and not a conserved structure common to all repeated motifs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".