<i>Listeria</i> phages induce Cas9 degradation to protect lysogenic genomes
Bibliographic record
Abstract
SUMMARY Bacterial CRISPR-Cas systems employ RNA-guided nucleases to destroy foreign DNA. Bacteriophages, in turn, have evolved diverse “anti-CRISPR” proteins (Acrs) to counteract acquired immunity. In Listeria monocytogenes , prophages encode 2-3 distinct anti-Cas9 proteins, with acrIIA1 always present; however, its mechanism is unknown. Here, we report that AcrIIA1 binds with high affinity to Cas9 via the catalytic HNH domain and, in Listeria , triggers Cas9 degradation. AcrIIA1 displays broad-spectrum inhibition of Type II-A and II-C Cas9s, including an additional highly-diverged Listeria Cas9. During lytic infection, AcrIIA1 is insufficient for rapid Cas9 inactivation, thus phages require an additional “partner” Acr that rapidly blocks Cas9-DNA-binding. The AcrIIA1 N-terminal domain (AcrIIA1 NTD ) is dispensable for anti-CRISPR activity; instead it is required for optimal phage replication through direct transcriptional repression of the anti-CRISPR locus. AcrIIA1 NTD is widespread amongst Firmicutes , can repress anti-CRISPR deployment by other phages, and has been co-opted by hosts potentially as an “anti-anti-CRISPR.” In summary, Listeria phages utilize narrow-spectrum inhibitors of DNA binding to rapidly inactivate Cas9 in lytic growth and the broad-spectrum AcrIIA1 to stimulate Cas9 degradation for protection of the Listeria genome in lysogeny.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".