Solid-State Nanopore Real-Time Assay for Monitoring Cas9 Endonuclease Reactivity
Bibliographic record
Abstract
The field of nanopore sensing is now moving beyond nucleic acid sequencing. An exciting avenue is the use of nanopore platforms for the monitoring of biochemical reactions. Biological nanopores have been used for this application, but solid-state nanopore approaches have lagged. This is due to the necessity of using higher salt conditions (e.g., 4 M LiCl) to improve the signal-to-noise ratio which completely abolish the activities of many biochemical reactions. We pioneered a polymer electrolyte solid-state nanopore approach that maintains a high signal-to-noise ratio even at a physiologically relevant salt concentration. Here, we report the monitoring of the restriction enzyme SwaI and CRISPR-Cas9 endonuclease activities under physiological salt conditions and in real time. We investigated the dsDNA cleavage activity of these enzymes in a range of digestion buffers and elucidated the off-target activity of CRISPR-Cas9 ribonucleoprotein endonuclease in the presence of single base pair mismatches. This approach enables the application of solid-state nanopores for the dynamic monitoring of biochemical reactions under physiological salt conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".