Translational repression of <i>Ccl5</i> and <i>Cxcl10</i> by 4E‐BP1 and 4E‐BP2 restrains the ability of mouse macrophages to induce migration of activated T cells
Bibliographic record
Abstract
Signaling through the mechanistic target of rapamycin complex 1 (mTORC1) is a major regulatory node of pro-inflammatory mediator production by macrophages (MΦs). However, it is still unclear whether such regulation relies on selective translational control by two of the main mTORC1 effectors, the eIF4E-binding proteins 1 and 2 (4E-BP1/2). By comparing translational efficiencies of immune-related transcripts of MΦs from WT and 4E-BP1/2 double-KO (DKO) mice, we found that translation of mRNAs encoding the pro-inflammatory chemokines CCL5 and CXCL10 is controlled by 4E-BP1/2. Macrophages deficient in 4E-BP1/2 produced higher levels of CCL5 and CXCL10 upon LPS stimulation, which enhanced chemoattraction of activated T cells. Consistent with this, treatment of WT cells with mTORC1 inhibitors promoted the activation of 4E-BP1/2 and reduced CCL5 and CXCL10 secretion. In contrast, the phosphorylation status of eIF4E did not affect the synthesis of these chemokines since MΦs derived from mice harboring a non-phosphorylatable form of the protein produced similar levels of CCL5 and CXCL10 to WT counterparts. These data provide evidence that the mTORC1-4E-BP1/2 axis contributes to regulate the production of chemoattractants by MΦs by limiting translation efficiency of Ccl5 and Cxcl10 mRNAs, and suggest that 4E-BP1/2 act as immunological safeguards by fine-tuning inflammatory responses in MΦs.
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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 | 0.001 | 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".