Safe Harbor Targeted CRISPR-Cas9 Tools for Molecular-Genetic Imaging of Cells in Living Subjects
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Bibliographic record
Abstract
Abstract Noninvasive molecular-genetic imaging of cells expressing imaging reporter genes is an invaluable approach for longitudinal monitoring of the biodistribution and viability of cancer cells and cell-based therapies in preclinical models and patients. However, labeling cells with reporter genes often relies on using gene transfer methods that randomly integrate the reporter genes into the genome, which may cause unwanted and serious detrimental effects. To overcome this, we have developed CRISPR-Cas9 tools to edit cells at the adeno-associated virus site 1 (AAVS1) safe harbour with a large donor construct (∼6.3 kilobases) encoding an antibiotic resistance gene and reporter genes for bioluminescence (BLI) and fluorescence imaging. HEK293T cells were transfected with a dual plasmid system encoding the Cas9 endonuclease and an AAVS1-targeted guide RNA in one plasmid, and a donor plasmid encoding a puromycin resistance gene, tdTomato and firefly luciferase flanked by AAVS1 homology arms. Puromycin-resistant clonal cells were isolated and AAVS1 integration was confirmed via PCR and sequencing of the PCR product. In vitro BLI signal correlated well to cell number ( R 2 = 0.9988; p < 0.05) and was stable over multiple passages. Engineered cells (2.5 × 10 6 ) were injected into the left hind flank of nude mice and in vivo BLI was performed on days 0, 7, 14, 21, and 28. BLI signal trended down from day 0 to day 7, but significantly increased by day 28 due to cell growth ( p < 0.05). This describes the first CRISPR-Cas9 system for AAVS1 integration of large gene constructs for molecular-genetic imaging of cells in vivo . With further development, including improving editing efficiency, use of clinically relevant reporters, and evaluation in other cell populations that can be readily expanded in culture (e.g., immortalized cells or T cells), this CRISPR-Cas9 reporter gene system could be broadly applied to a number of in vivo cell tracking studies.
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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 | 0.001 | 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 it