Phosphorylation of the Eukaryotic Translation Initiation Factor 4E-Transporter (4E-T) by c-Jun N-Terminal Kinase Promotes Stress-Dependent P-Body Assembly
Bibliographic record
Abstract
Processing bodies (PBs, or P bodies) are cytoplasmic granules involved in mRNA storage and degradation that participate in the regulation of gene expression. PBs concentrate nontranslated mRNAs and several factors involved in mRNA decay and translational repression, including the eukaryotic translation initiation factor 4E-transporter (4E-T). 4E-T is required for PB assembly, but little is known about the molecular mechanisms that regulate its function. Here, we demonstrate that oxidative stress promotes multisite 4E-T phosphorylation. We show that the c-Jun N-terminal kinase (JNK) is targeted to PBs in response to oxidative stress and promotes the phosphorylation of 4E-T. Quantitative mass spectrometry analysis reveals that JNK phosphorylates 4E-T on six proline-directed sites that are required for the formation of the 4E-T complex upon stress. We have developed an image-based computational method to quantify the size, number, and density of PBs in cells, and we find that while 4E-T is required for steady-state PB assembly, its phosphorylation facilitates the formation of larger PBs upon oxidative stress. Using polysomal mRNA profiling, we assessed global and specific mRNA translation but did not find that 4E-T phosphorylation impacts translational control. Collectively, these data support a model whereby PB assembly is regulated by a two-step mechanism involving a 4E-T-dependent assembly stage in unstressed cells and a 4E-T phosphorylation-dependent aggregation stage in response to stress stimuli.
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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".