A Safe Harbor-Targeted CRISPR/Cas9 Homology Independent Targeted Integration (HITI) System for Multi-Modality Reporter Gene-Based Cell Tracking
Bibliographic record
Abstract
Abstract Imaging reporter genes can provide valuable, longitudinal information on the biodistribution, growth and survival of engineered cells in preclinical models and patients. A translational bottleneck to using reporter genes in patients is the necessity to engineer cells with randomly-integrating vectors. CRISPR/Cas9 targeted knock-in of reporter genes at a genomic safe harbor locus such as adeno-associated virus integration site 1 (AAVS1) may overcome these safety concerns. Here, we built Homology Independent Targeted Integration (HITI) CRISPR/Cas9 minicircle donors for precise AAVS1-targeted simultaneous knock-in of fluorescence, bioluminescence, and MRI ( Oatp1a1 ) reporter genes. Our results showed greater knock-in efficiency at the AAVS1 site using HITI vectors compared to homology-directed repair donor vectors. Characterization of select HITI clones demonstrated functional fluorescence and bioluminescence reporter activity as well as significantly increased Oatp1a1-mediated uptake of the clinically-approved MRI agent gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid. As few as 10 6 Oatp1a1-expressing cells in a 50 µl subcutaneous injection could be detected in vivo with contrast-enhanced MRI. Contrast-enhanced MRI also improved the conspicuity of both sub-cutaneous and metastatic Oatp1a1-expressing tumours prior to them being palpable or even readily visible on pre-contrast images. Our work demonstrates the first CRISPR/Cas9 HITI system for knock-in of large DNA donor constructs at a safe harbor locus, enabling multi-modal longitudinal in vivo imaging of cells. This work lays the foundation for safer, non-viral reporter gene tracking of multiple cell types.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".