Disabling a Type I-E CRISPR-Cas Nuclease with a Bacteriophage-Encoded Anti-CRISPR Protein
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT CRISPR (clustered regularly interspaced short palindromic repeat)-Cas adaptive immune systems are prevalent defense mechanisms in bacteria and archaea. They provide sequence-specific detection and neutralization of foreign nucleic acids such as bacteriophages and plasmids. One mechanism by which phages and other mobile genetic elements are able to overcome the CRISPR-Cas system is through the expression of anti-CRISPR proteins. Over 20 different families of anti-CRISPR proteins have been described, each of which inhibits a particular type of CRISPR-Cas system. In this work, we determined the structure of type I-E anti-CRISPR protein AcrE1 by X-ray crystallography. We show that AcrE1 binds to the CRISPR-associated helicase/nuclease Cas3 and that the C-terminal region of the anti-CRISPR protein is important for its inhibitory activity. We further show that AcrE1 can convert the endogenous type I-E CRISPR system into a programmable transcriptional repressor. IMPORTANCE The CRISPR-Cas immune system provides bacteria with resistance to invasion by potentially harmful viruses, plasmids, and other foreign mobile genetic elements. This study presents the first structural and mechanistic insight into a phage-encoded protein that inactivates the type I-E CRISPR-Cas system in Pseudomonas aeruginosa . The interaction of this anti-CRISPR protein with the CRISPR-associated helicase/nuclease proteins Cas3 shuts down the CRISPR-Cas system and protects phages carrying this gene from destruction. This interaction also allows the repurposing of the endogenous type I-E CRISPR system into a programmable transcriptional repressor, providing a new biotechnological tool for genetic studies of bacteria encoding this type I-E CRISPR-Cas system.
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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) | 0.000 | 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) | 0.000 | 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 it