Sensing the DNA-mismatch tolerance of catalytically inactive Cas9 via barcoded DNA nanostructures in solid-state nanopores
Bibliographic record
Abstract
Single-molecule quantification of the strength and sequence specificity of interactions between proteins and nucleic acids would facilitate the probing of protein-DNA binding. Here we show that binding events between the catalytically inactive Cas9 ribonucleoprotein and any pre-defined short sequence of double-stranded DNA can be identified by sensing changes in ionic current as suitably designed barcoded linear DNA nanostructures with Cas9-binding double-stranded DNA overhangs translocate through solid-state nanopores. We designed barcoded DNA nanostructures to study the relationships between DNA sequence and the DNA-binding specificity, DNA-binding efficiency and DNA-mismatch tolerance of Cas9 at the single-nucleotide level. Nanopore-based sensing of DNA-barcoded nanostructures may help to improve the design of efficient and specific ribonucleoproteins for biomedical applications, and could be developed into sensitive protein-sensing assays.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".