rAAV-compatible MiniPromoters for restricted expression in the brain and eye
Bibliographic record
Abstract
BACKGROUND: Small promoters that recapitulate endogenous gene expression patterns are important for basic, preclinical, and now clinical research. Recently, there has been a promising revival of gene therapy for diseases with unmet therapeutic needs. To date, most gene therapies have used viral-based ubiquitous promoters-however, promoters that restrict expression to target cells will minimize off-target side effects, broaden the palette of deliverable therapeutics, and thereby improve safety and efficacy. Here, we take steps towards filling the need for such promoters by developing a high-throughput pipeline that goes from genome-based bioinformatic design to rapid testing in vivo. METHODS: For much of this work, therapeutically interesting Pleiades MiniPromoters (MiniPs; ~4 kb human DNA regulatory elements), previously tested in knock-in mice, were "cut down" to ~2.5 kb and tested in recombinant adeno-associated virus (rAAV), the virus of choice for gene therapy of the central nervous system. To evaluate our methods, we generated 29 experimental rAAV2/9 viruses carrying 19 different MiniPs, which were injected intravenously into neonatal mice to allow broad unbiased distribution, and characterized in neural tissues by X-gal immunohistochemistry for icre, or immunofluorescent detection of GFP. RESULTS: The data showed that 16 of the 19 (84 %) MiniPs recapitulated the expression pattern of their design source. This included expression of: Ple67 in brain raphe nuclei; Ple155 in Purkinje cells of the cerebellum, and retinal bipolar ON cells; Ple261 in endothelial cells of brain blood vessels; and Ple264 in retinal Müller glia. CONCLUSIONS: Overall, the methodology and MiniPs presented here represent important advances for basic and preclinical research, and may enable a paradigm shift in gene therapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".