CRISPR RNA binding and DNA target recognition by purified Cascade complexes from Escherichia coli
Bibliographic record
Abstract
Clustered regularly interspaced short palindromic repeats (CRISPRs) and their associated Cas proteins comprise a prokaryotic RNA-guided adaptive immune system that interferes with mobile genetic elements, such as plasmids and phages. The type I-E CRISPR interference complex Cascade from Escherichia coli is composed of five different Cas proteins and a 61-nt-long guide RNA (crRNA). crRNAs contain a unique 32-nt spacer flanked by a repeat-derived 5' handle (8 nt) and a 3' handle (21 nt). The spacer part of crRNA directs Cascade to DNA targets. Here, we show that the E. coli Cascade can be expressed and purified from cells lacking crRNAs and loaded in vitro with synthetic crRNAs, which direct it to targets complementary to crRNA spacer. The deletion of even one nucleotide from the crRNA 5' handle disrupted its binding to Cascade and target DNA recognition. In contrast, crRNA variants with just a single nucleotide downstream of the spacer part bound Cascade and the resulting ribonucleotide complex containing a 41-nt-long crRNA specifically recognized DNA targets. Thus, the E. coli Cascade-crRNA system exhibits significant flexibility suggesting that this complex can be engineered for applications in genome editing and opening the way for incorporation of site-specific labels in crRNA.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".