A luciferase reporter mouse model to optimize in vivo gene editing validated by lipid nanoparticle delivery of adenine base editors
Bibliographic record
Abstract
The rapid development of CRISPR genome editing technology has provided the potential to treat genetic diseases effectively and precisely. However, efficient and safe delivery of genome editors to affected tissues remains a challenge. Here, we developed luminescent ABE (LumA), a luciferase reporter mouse model containing the R387X mutation (c.A1159T) in the luciferase gene located in the Rosa26 locus of the mouse genome. This mutation eliminates luciferase activity but can be restored upon A-to-G correction by SpCas9 adenine base editors (ABEs). The LumA mouse model was validated through intravenous injection of two FDA-approved lipid nanoparticle (LNP) formulations consisting of either MC3 or ALC-0315 ionizable cationic lipids, encapsulated with ABE mRNA and LucR387X-specific guide RNA (gRNA). Whole-body bioluminescence live imaging showed consistent restoration of luminescence lasting up to 4 months in treated mice. Compared with mice carrying the wild-type luciferase gene, the ALC-0315 and MC3 LNP groups showed 83.5% ± 17.5% and 8.4% ± 4.3% restoration of luciferase activity in the liver, respectively, as measured by tissue luciferase assays. These results demonstrated successful development of a luciferase reporter mouse model that can be used to evaluate the efficacy and safety of different genome editors, LNP formulations, and tissue-specific delivery systems for optimizing genome editing therapeutics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".