A Sensitive Technique Unravels the Kinetics of Activation and <i>Trans</i> ‐Cleavage of CRISPR‐Cas Systems
Bibliographic record
Abstract
Abstract Activation of the CRISPR‐Cas13a system requires the formation of a crRNA‐Cas13a ribonucleoprotein (RNP) complex and the binding of an RNA activator to the RNP. These two binding processes play a crucial role in the performance of the CRISPR‐Cas13a system. However, the binding kinetics remain poorly understood, and a main challenge is the lack of a sensitive method for real‐time measurements of the dynamically formed active CRISPR‐Cas13a enzyme. We describe here a new method to study the binding kinetics and report the rate constants ( k on and k off ) and dissociation constant ( K d ) for the binding between Cas13a and its activator. The method is able to unravel and quantify the kinetics of binding and cleavage separately, on the basis of measuring the real‐time trans ‐cleavage rates of the CRISPR‐Cas system and obtaining the real‐time concentrations of the active CRISPR‐Cas ternary complex. We further discovered that once activated, the Cas13a system operates at a wide range of temperatures (7–37 °C) with fast trans ‐cleavage kinetics. The new method and findings are important for diverse applications of the Cas13a system, such as the demonstrated quantification of microRNA at ambient temperatures (e.g., 25 °C).
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".