Cooperation between Different CRISPR-Cas Types Enables Adaptation in an RNA-Targeting System
Bibliographic record
Abstract
CRISPR-Cas systems are immune systems that protect bacteria and archaea against their viruses, bacteriophages. Immunity is achieved through the acquisition of short DNA fragments from the viral invader's genome. These fragments, called spacers, are integrated into a memory bank on the bacterial genome called the CRISPR array. The spacers allow for the recognition of the same invader upon subsequent infection. Most CRISPR-Cas systems target DNA, but recently, systems that exclusively target RNA have been discovered. RNA-targeting CRISPR-Cas systems often lack genes necessary for spacer acquisition, and it is thus unknown how new spacers are acquired and if they can be acquired from DNA phages. Here, we show that an RNA-targeting system "borrows" acquisition machinery from another CRISPR-Cas locus in the genome. Most new spacers in this locus are unable to target phage mRNA and are therefore likely redundant. Our results reveal collaboration between distinct CRISPR-Cas types and raise further questions on how other CRISPR-Cas loci may cooperate.
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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) | 0.000 | 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 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".