Distinct domains of Me31B interact with different eIF4E isoforms in the male germ line of <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
ABSTRACT Eukaryotic translation initiation factor 4E (eIF4E) is a key factor involved in different aspects of mRNA metabolism. Drosophila melanogaster genome encodes eight eIF4E isoforms, and the canonical isoform eIF4E-1 is a ubiquitous protein that plays a key role in mRNA translation. eIF4E-3 is specifically expressed in testis and controls translation during spermatogenesis. In eukaryotic cells, translational control and mRNA decay is highly regulated in different cytoplasmic ribonucleoprotein foci, which include the processing bodies (PBs). In this study, we show that Drosophila eIF4E-1 and eIF4E-3 occur in PBs where might play a role in mRNA storage and translational repression. We also demonstrate that the DEAD-box RNA helicase Me31B, a component of PBs, physically interacts with eIF4E-1 and eIF4E-3 both in the yeast two-hybrid system and FRET in Drosophila S2 cells. Moreover, truncated and point mutated Me31B proteins indicate that the binding sites of Me31B for eIF4E-1 and eIF4E-3 are located in different domains. Residues Y401-L407 (at the carboxy-terminal) are essential for interaction with eIF4E-1, whereas residues F63-L70 (at the amino-terminal) are critical for interaction with eIF4E-3. Thus, Me31B represents a novel type of eIF4E-interacting protein. Our observations suggest that Me31B might recognize different eIF4E isoforms in different tissues, which could be the key to silencing specific messengers. They provide further evidence that alternative forms of eIF4E and their interactions with various partners add complexity to the control of gene expression in eukaryotes.
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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".