Inducible and Reversible Clock Gene Expression in Brain Using the tTA System for the Study of Circadian Behavior
Bibliographic record
Abstract
The mechanism of circadian oscillations in mammals is cell autonomous and is generated by a set of genes that form a transcriptional autoregulatory feedback loop. While these "clock genes" are well conserved among animals, their specific functions remain to be fully understood and their roles in central versus peripheral circadian oscillators remain to be defined. We utilized the in vivo inducible tetracycline-controlled transactivator (tTA) system to regulate Clock gene expression conditionally in a tissue-specific and temporally controlled manner. Through the use of Secretogranin II to drive tTA expression, suprachiasmatic nucleus- and brain-directed expression of a tetO::Clock(Delta19) dominant-negative transgene lengthened the period of circadian locomotor rhythms in mice, whereas overexpression of a tetO::Clock(wt) wild-type transgene shortened the period. Low doses (10 mug/ml) of doxycycline (Dox) in the drinking water efficiently inactivated the tTA protein to silence the tetO transgenes and caused the circadian periodicity to return to a wild-type state. Importantly, low, but not high, doses of Dox were completely reversible and led to a rapid reactivation of the tetO transgenes. The rapid time course of tTA-regulated transgene expression demonstrates that the CLOCK protein is an excellent indicator for the kinetics of Dox-dependent induction/repression in the brain. Interestingly, the daily readout of circadian period in this system provides a real-time readout of the tTA transactivation state in vivo. In summary, the tTA system can manipulate circadian clock gene expression in a tissue-specific, conditional, and reversible manner in the central nervous system. The specific methods developed here should have general applicability for the study of brain and behavior in the mouse.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".