In silico prediction and in vivo testing of promoters targeting GABAergic inhibitory neurons
Bibliographic record
Abstract
Impairment of GABAergic inhibitory neuronal function is linked to epilepsy and other neurological and psychiatric disorders. Recombinant adeno-associated virus (rAAV)-based gene therapy targeting GABAergic neurons is a promising treatment for GABA-associated disorders. However, there is a need to develop rAAV-compatible gene-regulatory elements capable of selectively driving expression in GABAergic neurons throughout the brain. Here, we designed several novel GABAergic gene promoters. In silico analyses, including evolutionarily conserved DNA sequence alignments and transcription factor binding site searches among GABAergic neuronal genes, were carried out to reveal novel sequences for use as rAAV-compatible promoters. rAAVs (serotype 9) were injected into the CSF of neonatal mice and into the brain parenchyma of adult mice to assess promoter specificity. In mice injected neonatally, transgene expression was detected in multiple brain regions with very high neuronal specificity and moderate-to-high GABAergic neuronal selectivity. The GABA promoters differed greatly in their levels of expression and, in some brain regions, showed strikingly different patterns of GABAergic neuron transduction. This study is the first report of rAAV vectors that are functional in multiple brain regions using promoters designed by in silico analyses from multiple GABAergic genes. These novel GABA-targeting vectors may be useful tools to advance gene therapy for GABA-associated disorders.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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".