A Genetic Screen in Drosophila Reveals Novel Cytoprotective Functions of the Autophagy-Lysosome Pathway
Bibliographic record
Abstract
The highly conserved autophagy-lysosome pathway is the primary mechanism for breakdown and recycling of macromolecular and organellar cargo in the eukaryotic cell. Autophagy has recently been implicated in protection against cancer, neurodegeneration, and infection, and interest is increasing in additional roles of autophagy in human health, disease, and aging. To search for novel cytoprotective features of this pathway, we carried out a genetic mosaic screen for mutations causing increased lysosomal and/or autophagic activity in the Drosophila melanogaster larval fat body. By combining Drosophila genetics with live-cell imaging of the fluorescent dye LysoTracker Red and fixed-cell imaging of autophagy-specific fluorescent protein markers, the screen was designed to identify essential metazoan genes whose disruption causes increased flux through the autophagy-lysosome pathway. The screen identified a large number of genes associated with the protein synthesis and ER-secretory pathways (e.g. aminoacyl tRNA synthetases, Oligosaccharyl transferase, Sec61alpha), and with mitochondrial function and dynamics (e.g. Rieske iron-sulfur protein, Dynamin-related protein 1). We also observed that increased lysosomal and autophagic activity were consistently associated with decreased cell size. Our work demonstrates that disruption of the synthesis, transport, folding, or glycosylation of ER-targeted proteins at any of multiple steps leads to autophagy induction. In addition to illuminating cytoprotective features of autophagy in response to cellular damage, this screen establishes a genetic methodology for investigating cell biological phenotypes in live cells, in the context of viable wild type organisms.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".