TLR2 Activation Limits Rhinovirus-Stimulated CXCL-10 by Attenuating IRAK-1–Dependent IL-33 Receptor Signaling in Human Bronchial Epithelial Cells
Bibliographic record
Abstract
Airway epithelial cells are the major target for rhinovirus (RV) infection and express proinflammatory chemokines and antiviral cytokines that play a role in innate immunity. Previously, we demonstrated that RV interaction with TLR2 causes ILR-associated kinase-1 (IRAK-1) depletion in both airway epithelial cells and macrophages. Further, IRAK-1 degradation caused by TLR2 activation was shown to inhibit ssRNA-induced IFN expression in dendritic cells. Therefore, in this study, we examined the role of TLR2 and IRAK-1 in RV-induced IFN-β, IFN-λ1, and CXCL-10, which require signaling by viral RNA. In airway epithelial cells, blocking TLR2 enhanced RV-induced expression of IFNs and CXCL-10. By contrast, IRAK-1 inhibition abrogated RV-induced expression of CXCL-10, but not IFNs in these cells. Neutralization of IL-33 or its receptor, ST2, which requires IRAK-1 for signaling, inhibited RV-stimulated CXCL-10 expression. In addition, RV induced expression of both ST2 and IL-33 in airway epithelial cells. In macrophages, however, RV-stimulated CXCL-10 expression was primarily dependent on TLR2/IL-1R. Interestingly, in a mouse model of RV infection, blocking ST2 not only attenuated RV-induced CXCL-10, but also lung inflammation. Finally, influenza- and respiratory syncytial virus-induced CXCL-10 was also found to be partially dependent on IL-33/ST2/IRAK-1 signaling in airway epithelial cells. Together, our results indicate that RV stimulates CXCL-10 expression via the IL-33/ST2 signaling axis, and that TLR2 signaling limits RV-induced CXCL-10 via IRAK-1 depletion at least in airway epithelial cells. To our knowledge, this is the first report to demonstrate the role of respiratory virus-induced IL-33 in the induction of CXCL-10 in airway epithelial cells.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".