EGO-like complex regulates TOR (Target of Rapamycin) activity and localization in <i>Neurospora</i>
Bibliographic record
Abstract
Abstract The TOR (Target of Rapamycin) signalling pathway is found in all eukaryotes and integrates nutrient and stress signals to control cell growth. It is well-studied in yeast and mammals but is less well understood in filamentous fungi. We previously identified TOR pathway components VTA (homologous to the vacuole-bound EGO complex of yeast) and GTR2 (homologous to Rag GTPases) as essential to maintaining circadian rhythms in the filamentous fungus Neurospora crassa . Therefore we are interested in defining the TOR pathway and its regulation in N. crassa . In yeast and mammals, TOR kinase is activated by carbon sources and amino acids. We report here that on high glucose medium, TOR is insensitive to added amino acids. On low glucose, TOR is activated by added glucose and amino acids. VTA and GTR2 knockouts block the activation of TOR by amino acids but not by glucose, identifying their function in an amino acid-sensing pathway. Live cell microscopy of KOG1 (a component of TOR complex 1) and GTR2 localizes them to punctate bodies near the vacuole. This localization is lost and the proteins are largely cytoplasmic under starvation conditions, in the presence of TOR inhibitor Torin II, and in the VTA knockout. This indicates that VTA acts as the vacuolar anchor for activated TOR complex. Co-immunoprecipitation of KOG1-FLAG and GTR2-FLAG confirms their cytoplasmic localization in VTA knockout and identifies TORC1 complex components TCO89 and LST8. These results focus attention on amino acid sensing through VTA and GTR2 as potentially regulating circadian rhythmicity in N. crassa .
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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) | 0.002 | 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".