The Proteomic Landscape of the Suprachiasmatic Nucleus Clock Reveals Large-Scale Coordination of Key Biological Processes
Bibliographic record
Abstract
The suprachiasmatic nucleus (SCN) acts as the central clock to coordinate circadian oscillations in mammalian behavior, physiology and gene expression. Despite our knowledge of the circadian transcriptome of the SCN, how it impacts genome-wide protein expression is not well understood. Here, we interrogated the murine SCN proteome across the circadian cycle using SILAC-based quantitative mass spectrometry. Of the 2112 proteins that were accurately quantified, 20% (421 proteins) displayed a time-of-day-dependent expression profile. Within this time-of-day proteome, 11% (48 proteins) were further defined as circadian based on a sinusoidal expression pattern with a ∼24 h period. Nine circadianly expressed proteins exhibited 24 h rhythms at the transcript level, with an average time lag that exceeded 8 h. A substantial proportion of the time-of-day proteome exhibited abrupt fluctuations at the anticipated light-to-dark and dark-to-light transitions, and was enriched for proteins involved in several key biological pathways, most notably, mitochondrial oxidative phosphorylation. Additionally, predicted targets of miR-133ab were enriched in specific hierarchical clusters and were inversely correlated with miR133ab expression in the SCN. These insights into the proteomic landscape of the SCN will facilitate a more integrative understanding of cellular control within the SCN clock.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| 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".