Structural Basis for Antibody Recognition in the Receptor-binding Domains of Toxins A and B from Clostridium difficile
Bibliographic record
Abstract
Clostridium difficile infection is a serious and highly prevalent nosocomial disease in which the two large, Rho-glucosylating toxins TcdA and TcdB are the main virulence factors. We report for the first time crystal structures revealing how neutralizing and non-neutralizing single-domain antibodies (sdAbs) recognize the receptor-binding domains (RBDs) of TcdA and TcdB. Surprisingly, the complexes formed by two neutralizing antibodies recognizing TcdA do not show direct interference with the previously identified carbohydrate-binding sites, suggesting that neutralization of toxin activity may be mediated by mechanisms distinct from steric blockage of receptor binding. A camelid sdAb complex also reveals the molecular structure of the TcdB RBD for the first time, facilitating the crystallization of a strongly negatively charged protein fragment that has resisted previous attempts at crystallization and structure determination. Electrospray ionization mass spectrometry measurements confirm the stoichiometries of sdAbs observed in the crystal structures. These studies indicate how key epitopes in the RBDs from TcdA and TcdB are recognized by sdAbs, providing molecular insights into toxin structure and function and providing for the first time a basis for the design of highly specific toxin-specific therapeutic and diagnostic agents.
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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) | 0.001 | 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".