Repression of mRNA translation initiation by GIGYF1 via blocking the eIF3-eIF4G1 interaction
Bibliographic record
Abstract
Summary Viruses commonly interfere with the function of the eukaryotic translation initiation factor 4G1 (eIF4G1), a pivotal factor in the recruitment of the eIF3 complex and ribosome to the mRNA. This results in the inhibition of general host protein synthesis and redirecting ribosomes toward viral mRNAs. Certain viruses also selectively repress the translation of mRNAs involved in the host antiviral response. GIGYF2 and its interacting cap-binding protein 4EHP enable the transcript-specific repression of mRNA translation mediated by microRNAs and RNA-binding proteins (RBPs). RNA viruses, such as SARS-CoV-2, exploit the GIGYF2/4EHP complex to selectively repress the translation of transcripts such as Ifnb1 mRNA, which encodes the antiviral cytokine Interferon β (IFN-β). Herein, we reveal that GIGYF1, a paralogue of GIGYF2, robustly represses cellular mRNA translation through a distinct mechanism independent of 4EHP. Upon recruitment to a target mRNA by RBPs, the C-terminal region of GIGYF1 binds to subunits of eIF3 at the interaction interface of eIF3-eIF4G1. This disrupts binding of eIF3 to eIF4G1, resulting in mRNA-specific translational repression. This mechanism exerts profound influences on the host cell’s response to viral infection. Depletion of GIGYF1 induces a robust immune response by derepressing Ifnb1 mRNA translation. Overall, our study highlights a unique mechanism of translational regulation by GIGYF1 that involves sequestering eIF3 and abrogating its binding to eIF4G1. This mechanism can be utilized by RBPs that interact with GIGYF1 to specifically repress the translation of their target mRNAs, significantly affecting critical biological processes, including host-pathogen interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".