New MiniPromoter Ple389 (ADORA2A) drives selective expression in medium spiny neurons in mice and non-human primates
Bibliographic record
Abstract
Compact cell type-specific promoters are important tools for basic and preclinical research and clinical delivery of gene therapy. In this work, we designed novel MiniPromoters to target D1 and D2 type dopaminoceptive medium spiny neurons in the striatum by manually identifying candidate regulatory regions or employing the OnTarget webserver. We then empirically tested the designs in rAAV-PHP.B for specificity and robustness in three systems: intravenous injection in mice, intracerebroventricular injection in mice, and intracerebroventricular injection in non-human primates. Twelve MiniPromoters were designed from eight genes: seven manually and five using OnTarget. When delivered intravenously in mice, three MiniPromoters demonstrated highly selective expression in the striatum, with Ple389 (ADORA2A) showing high levels of dopamine D2-receptor cell co-localization. The same three MiniPromoters also displayed enriched expression in the striatum when delivered intracerebroventricularly in mice with high levels of DARPP32 co-localization. Finally, Ple389 (ADORA2A) was intracerebroventricularly injected in non-human primates and showed enriched expression in the striatum as in the mouse. Ple389 (ADORA2A) demonstrated expression in the medium spiny neurons in all three systems tested and exhibited the highest level of D2-MSNs and DARPP32 co-labeling in mice, demonstrating its potential as a tool for gene therapy approaches for Parkinson and Huntington disease treatment.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".