A Two-Step Method for Obtaining Highly Pure Cas9 Nuclease for Genome Editing, Biophysical, and Structural Studies
Bibliographic record
Abstract
Cas9 is a site-specific RNA-guided endonuclease (RGEN) that can be used for precise genome editing in various cell types from multiple species. Ribonucleoprotein (RNP) complexes, which contains the Cas9 protein in complex with a guide RNA, are sufficient for the precise editing of genomes in various cells. This DNA-free method is more specific in editing the target sites and there is no integration of foreign DNA into the genome. Also, there are ongoing studies into the interactions of Cas9 protein with modified guide RNAs, as well as structure-activity studies of Cas9 protein and its variants. All these investigations require highly pure Cas9 protein. A single-step metal affinity enrichment yielding impure Cas9 is the most common method of purification described. This is sufficient for many gene editing applications of this protein. However, to obtain Cas9 of higher purity, which might be essential for biophysical characterization, chemical modifications, and structural investigations, laborious multi-step protocols are employed. Here, we describe a two-step Cas9 purification protocol that uses metal affinity enrichment followed by cation exchange chromatography. This simple method can yield a milligram of highly pure Cas9 protein per liter of culture in a single day.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".