Rapid TetOn-mediated gene expression in neurons across the lifespan with uTTOP
Bibliographic record
Abstract
Conditional expression of genes of interest is essential for interrogation of cellular development and function. Although tools exist for conditional gene expression, techniques for rapid-onset, temporally precise expression are lacking. The doxycyclineinducible TetOn expression system allows for this in numerous organ systems, however, transgenic TetOn expression cassettes become silenced in the nervous system during postnatal development. Here, we circumvent this silencing with uTTOP: in utero electroporation of Transposable TetOn Plasmids. When electroporated as transposable elements that integrate into the genome, the TetOn system allowed for robust DOX-dependent induction of expression across the postnatal lifespan of the mouse. We demonstrated induction in neurons of sensorimotor and retrospleninal cortex, hippocampus and the olfactory bulb. Latency to peak induction was ≤12 hours, a several fold increase in induction kinetics over existing methodology for in vivo conditional expression. To demonstrate the utility of uTTOP, we induced ectopic expression of Sonic hedgehog in adult mouse layer 2/3 cortical neurons, demonstrating that its expression can diversify expression of Kir4.1 in surrounding astrocytes. The rapid induction kinetics of uTTOP allowed us to show that Kir4.1 upregulation significantly lags onset of Shh expression by ∼2 days, a difference in expression time course that is likely not resolvable with current methods. Together, these data demonstrate that uTTOP is a powerful and flexible system for conditional gene expression in multiple brain areas across the mouse lifespan.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".