Targeting surface-layer proteins with single-domain antibodies: a potential therapeutic approach against Clostridium difficile-associated disease
Bibliographic record
Abstract
Clostridium difficile is a leading cause of death from gastrointestinal infections in North America. Antibiotic therapy is effective, but the high incidence of relapse and the rise in hypervirulent strains warrant the search for novel treatments. Surface layer proteins (SLPs) cover the entire C. difficile bacterial surface, are composed of high-molecular-weight (HMW) and low-molecular-weight (LMW) subunits, and mediate adherence to host cells. Passive and active immunization against SLPs has enhanced hamster survival, suggesting that antibody-mediated neutralization may be an effective therapeutic strategy. Here, we isolated a panel of SLP-specific single-domain antibodies (VHHs) using an immune llama phage display library and SLPs isolated from C. difficile hypervirulent strain QCD-32g58 (027 ribotype) as a target antigen. Binding studies revealed a number of VHHs that bound QCD-32g58 SLPs with high affinity (K D = 3-6 nM) and targeted epitopes located on the LMW subunit of the SLP. The VHHs demonstrated melting temperatures as high as 75 °C, and a few were resistant to the gastrointestinal protease pepsin at physiologically relevant concentrations. In addition, we demonstrated the binding specificity of the VHHs to the major C. difficile ribotypes by whole cell ELISA, where all VHHs were found to bind 001 and 027 ribotypes, and a subset of antibodies were found to be broadly cross-reactive in binding cells representative of 012, 017, 023, and 078 ribotypes. Finally, we showed that several of the VHHs inhibited C. difficile QCD-32g58 motility in vitro. Targeting SLPs with VHHs may be a viable therapeutic approach against C. difficile-associated disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".