eEF1A Is a Novel Component of the Mammalian Nuclear Protein Export Machinery
Bibliographic record
Abstract
The cytoplasmic translation factor eEF1A has been implicated in the nuclear export of tRNA species in lower eukaryotes. Here we demonstrate that eEF1A plays a central role in nuclear export of proteins in mammalian cells. TD-NEM (transcription-dependent nuclear export motif), a newly characterized nuclear export signal, mediates efficient nuclear export of several proteins including the von Hippel-Lindau (VHL) tumor suppressor and the poly(A)-binding protein (PABP1) in a manner that is dependent on ongoing RNA polymerase II (RNA PolII)-dependent transcription. eEF1A interacts specifically with TD-NEM of VHL and PABP1 and disrupting this interaction, by point mutations of key TD-NEM residues or treatment with actinomycin D, an inhibitor of RNA PolII-dependent transcription, prevents assembly and nuclear export. siRNA-induced knockdown or antibody-mediated depletion of eEF1A prevents in vivo and in vitro nuclear export of TD-NEM-containing proteins. Nuclear retention experiments and inhibition of the Exportin-5 pathway suggest that eEF1A stimulates nuclear export of proteins from the cytoplasmic side of the nuclear envelope, without entering the nucleus. Together, these data identify a role for eEF1A, a cytoplasmic mediator of tRNA export in yeast, in the nuclear export of proteins in mammalian cells. These results also provide a link between the translational apparatus and subcellular trafficking machinery demonstrating that these two central pathways in basic metabolism can act cooperatively.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".