Isolation and Characterization of Anti-SLP Single Domain Antibodies for the Therapy of C. difficile Infection
Bibliographic record
Abstract
Clostridium difficile is the leading cause of death from gastrointestinal infections in Canada. Current antiobiotic treatment is non-ideal due to the high incidence of relapse and the rise in hyper-virulent antibiotic-resistant strains. Surface layer proteins (SLPs) cover the entire bacterial surface and mediate adherence to host cells. Passive and active immunization against SLPs greatly enhances survival in hamsters, suggesting that antibody-mediated bacterial neutralization may be an effective alternative therapeutic strategy. Using a recombinant-antibody phage display library, and SLPs from strain QCD 32g58 as bait antigen, we isolated and extensively characterized 11 SLP-specific recombinant single-domain antibodies (sdAbs), in terms of affinity and specificity, intrinsic stability, and ability to inhibit cell motility. Several sdAbs exhibit promising characteristics for a potential oral therapeutic based on their high affinity, high thermal stability, and resistance to pepsin digestion. Our study provides the basis of a proof-of-principle model with which to develop specific, broadly neutralizing and intrinsically stable antibodies for the oral therapy of C. difficile infections, as an alternative to conventional antibiotic treatment.
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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".