Discovery of new type I toxin–antitoxin systems adjacent to CRISPR arrays in Clostridium difficile
Bibliographic record
Abstract
Clostridium difficile, a major human enteropathogen, must cope with foreign DNA invaders and multiple stress factors inside the host. We have recently provided an experimental evidence of defensive function of the C. difficile CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) system important for its survival within phage-rich gut communities. Here, we describe the identification of type I toxin-antitoxin (TA) systems with the first functional antisense RNAs in this pathogen. Through the analysis of deep-sequencing data, we demonstrate the general co-localization with CRISPR arrays for the majority of sequenced C. difficile strains. We provide a detailed characterization of the overlapping convergent transcripts for three selected TA pairs. The toxic nature of small membrane proteins is demonstrated by the growth arrest induced by their overexpression. The co-expression of antisense RNA acting as an antitoxin prevented this growth defect. Co-regulation of CRISPR-Cas and type I TA genes by the general stress response Sigma B and biofilm-related factors further suggests a possible link between these systems with a role in recurrent C. difficile infections. Our results provide the first description of genomic links between CRISPR and type I TA systems within defense islands in line with recently emerged concept of functional coupling of immunity and cell dormancy systems in prokaryotes.
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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".