Advancing the genetic engineering toolbox by combining AsCas12a knock-in mice with ultra-compact screening
Bibliographic record
Abstract
Cas12a is a next-generation gene editing tool that enables multiplexed gene targeting. Here, we present a mouse model that constitutively expresses enhanced Acidaminococcus sp. Cas12a (enAsCas12a) linked to an mCherry fluorescent reporter. We demonstrate efficient single and multiplexed gene editing in vitro, using primary and transformed cells from enAsCas12a mice. We further demonstrate successful in vivo gene editing, using normal and cancer-prone enAsCas12a stem cells to reconstitute the haematopoietic system of wild-type mice. We also present compact, genome-wide Cas12a knockout libraries, with four crRNAs per gene encoded across one (Scherzo) or two (Menuetto) vectors, and demonstrate the utility of these libraries across methodologies: in vitro enrichment and drop-out screening in lymphoma cells and immortalised fibroblasts, respectively, and in vivo screens to identify lymphoma-driving events. Finally, we demonstrate CRISPR multiplexing via simultaneous gene knockout (via Cas12a) and activation (via dCas9-SAM) using primary T cells and fibroblasts. Our enAsCas12a mouse and accompanying crRNA libraries enhance genome engineering capabilities and complement current CRISPR technologies.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".