Insulin-Like Peptides Regulate Feeding Preference and Metabolism in Drosophila
Bibliographic record
Abstract
Fruit flies have eight identified Drosophila insulin-like peptides (DILPs) that are involved in the regulation of carbohydrate concentrations in hemolymph as well as in accumulation of storage metabolites. In the present study, we investigated diet-dependent roles of DILPs encoded by the genes dilp1–5, and dilp7 in the regulation of insect appetite, food choice, accumulation of triglycerides, glycogen, glucose, and trehalose in fruit fly bodies and carbohydrates in hemolymph. We have found that the wild type and the mutant lines demonstrate compensatory feeding for carbohydrates. However, mutants on dilp2,3, dilp3, dilp5, and dilp7 showed higher consumption of proteins on high yeast diets. To evaluate metabolic differences between studied lines on different diets we applied response surface methodology. High nutrient diets led to a moderate increase in concentration of glucose in hemolymph of the wild type flies. Mutations on dilp genes changed this pattern. We have revealed that the dilp2 mutation led drop in glycogen levels independently on diet, lack of dilp3 led to dramatic increase in circulating trehalose and glycogen levels, especially at low protein consumption. Lack of dilp5 led to decreased levels of glycogen and triglycerides on all diets, whereas knockout on dilp7 caused increase in glycogen levels and simultaneous decrease in triglyceride levels at low protein consumption. Fruit fly appetite was influenced by dilp3 and dilp7 genes. Our data contribute to the understanding of Drosophila as a model for further studies of metabolic diseases and may serve as a guide for uncovering the evolution of metabolic regulatory pathways.
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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".