The three major types of <scp>CRISPR</scp>‐<scp>Cas</scp> systems function independently in <scp>CRISPR RNA</scp> biogenesis in <scp><i>S</i></scp><i>treptococcus thermophilus</i>
Bibliographic record
Abstract
CRISPR-Cas systems are small RNA-based immune systems that protect prokaryotes from invaders such as viruses and plasmids. We have investigated the features and biogenesis of the CRISPR (cr)RNAs in Streptococcus thermophilus (Sth) strain DGCC7710, which possesses four different CRISPR-Cas systems including representatives from the three major types of CRISPR-Cas systems. Our results indicate that the crRNAs from each CRISPR locus are specifically processed into divergent crRNA species by Cas proteins (and non-coding RNAs) associated with the respective locus. We find that the Csm Type III-A and Cse Type I-E crRNAs are specifically processed by Cas6 and Cse3 (Cas6e), respectively, and retain an 8-nucleotide CRISPR repeat sequence tag 5' of the invader-targeting sequence. The Cse Type I-E crRNAs also retain a 21-nucleotide 3' repeat tag. The crRNAs from the two Csn Type II-A systems in Sth consist of a 5'-truncated targeting sequence and a 3' tag; however, these are distinct in size between the two. Moreover, the Csn1 (Cas9) protein associated with one Csn locus functions specifically in the production of crRNAs from that locus. Our findings indicate that multiple CRISPR-Cas systems can function independently in crRNA biogenesis within a given organism - an important consideration in engineering coexisting CRISPR-Cas pathways.
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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 | 0.001 |
| 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 | 0.001 |
| 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".