The Nutrient-Responsive Molecular Chaperone Hsp90 Supports Growth and Development in Drosophila
Bibliographic record
Abstract
Animals can sense internal nutrients, such as amino acids/proteins, and are able to modify their developmental programs in accordance with their nutrient status. In the fruit fly, Drosophila melanogaster, amino acid/protein is sensed by the fat body, an insect adipose tissue, through a nutrient sensor, target of rapamycin (TOR) complex 1 (TORC1). TORC1 promotes the secretion of various peptide hormones from the fat body in an amino acid/protein-dependent manner. Fat-body-derived peptide hormones stimulate the release of insulin-like peptides, which are essential growth-promoting anabolic hormones, from neuroendocrine cells called insulin-producing cells (IPCs). Although the importance of TORC1 and the fat body-IPC axis has been elucidated, the mechanism by which TORC1 regulates the expression of insulinotropic signal peptides remains unclear. Here, we show that an evolutionarily conserved molecular chaperone, heat shock protein 90 (Hsp90), promotes the expression of insulinotropic signal peptides. Fat-body-selective Hsp90 knockdown caused the transcriptional downregulation of insulinotropic signal peptides. IPC activity and systemic growth were also impaired in fat-body-selective Hsp90 knockdown animals. Furthermore, Hsp90 expression depended on protein/amino acid availability and TORC1 signaling. These results strongly suggest that Hsp90 serves as a nutrient-responsive gene that upregulates the fat body-IPC axis and systemic growth. We propose that Hsp90 is induced in a nutrient-dependent manner to support anabolic metabolism during the juvenile growth period.
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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".