A component of the TOR (Target Of Rapamycin) nutrient-sensing pathway plays a role in circadian rhythmicity in Neurospora crassa
Bibliographic record
Abstract
The TOR (Target of Rapamycin) pathway is a highly-conserved signaling pathway in eukaryotes that regulates cellular growth and stress responses. The cellular response to amino acids or carbon sources such as glucose requires anchoring of the TOR kinase complex to the lysosomal/vacuolar membrane by the Ragulator (mammals) or EGO (yeast) protein complex. Here we report a connection between the TOR pathway and circadian (daily) rhythmicity. The molecular mechanism of circadian rhythmicity in all eukaryotes has long been thought to be transcription/translation feedback loops (TTFLs). In the model eukaryote Neurospora crassa, a TTFL including FRQ (frequency) and WCC (white collar complex) has been intensively studied. However, it is also well-known that rhythmicity can be seen in the absence of TTFL functioning. We previously isolated uv90 as a mutation that compromises FRQ-less rhythms and also damps the circadian oscillator when FRQ is present. We have now mapped the uv90 gene and identified it as NCU05950, homologous to the TOR pathway proteins EGO1 (yeast) and LAMTOR1 (mammals), and we have named the N. crassa protein VTA (vacuolar TOR-associated protein). The protein is anchored to the outer vacuolar membrane and deletion of putative acylation sites destroys this localization as well as the protein's function in rhythmicity. A deletion of VTA is compromised in its growth responses to amino acids and glucose. We conclude that a key protein in the complex that anchors TOR to the vacuole plays a role in maintaining circadian (daily) rhythmicity. Our results establish a connection between the TOR pathway and circadian rhythms and point towards a network integrating metabolism and the circadian system.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".