Eukaryotic translation initiation factor eIF4E-5 is required for spermiogenesis in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Drosophila sperm development is characterized by extensive post-transcriptional regulation whereby thousands of transcripts are preserved for translation during later stages. A key step in translation initiation is the binding of eukaryotic initiation factor 4E (eIF4E) to the 5' mRNA cap. In addition to canonical eIF4E-1, Drosophila has multiple eIF4E paralogs, including four (eIF4E-3, -4, -5, and -7) that are highly expressed in the testis. Among these, only eIF4E-3 has been characterized genetically. Here, using CRISPR/Cas9 mutagenesis, we determined that eIF4E-5 is essential for male fertility. eIF4E-5 protein localizes to the distal ends of elongated spermatid cysts, and eIF4E-5 mutants exhibit defects during post-meiotic stages, including a mild defect in spermatid cyst polarization. eIF4E-5 mutants also have a fully penetrant defect in individualization, resulting in failure to produce mature sperm. Indeed, our data indicate that eIF4E-5 regulates non-apoptotic caspase activity during individualization by promoting local accumulation of the E3 ubiquitin ligase inhibitor Soti. Our results further extend the diversity of non-canonical eIF4Es that carry out distinct spatiotemporal roles during spermatogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".