Structural Determinants of SlpA-Mediated Phage Recognition in Clostridioides difficile
Bibliographic record
Abstract
The emergence of Clostridioides difficile as a leading cause of healthcare-associated nosocomial intestinal infections calls for novel therapeutic strategies, particularly in the context of antibiotic resistance and recurrent disease. Phage therapy is a promising approach, but its clinical application against C. difficile remains hindered by our lack of understanding of the factors driving host specificity. Indeed, it is crucial to understand how phages specifically interact with their host to be able to select the best candidates for cocktail preparation. The main surface layer protein SlpA is a key phage receptor, but the molecular details governing phage-receptor interactions remain unclear. By dissecting the structural features of SlpA required for phage infection through engineered isoforms and domain modifications, we reveal how specific regions of SlpA mediate phage adsorption and infection. These new insights into phage–receptor interactions will be instrumental in guiding the future engineering of broad-host-range therapeutic phages. This dataset comprises genome sequences of the wiltdype R20291 strain, as well as two mutants derived from this strain. One is the FM2.5 slpA null mutant, carying a point mutation in the slpA gene causing a severe truncation of the protein and the absence of an S-layer at the surface of the cell. The other mutant is a newly created deletion mutant in wich the complete slpA gene was removed using CRISPR-Cas. The 3 strains have been resequenced by Oxford Nanopore long read, and Aviti short reads.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".