Regulation of TLR3 Activation by S100A9
Bibliographic record
Abstract
Recognition of viral dsRNA by endosomal TLR3 activates innate immune response during virus infection. Trafficking of TLR3 to the endolysosomal compartment arising from fusion of late endosome (LE) with lysosome is required for recognition and detection of pathogen associated molecular patterns, which results in activation of the TLR3-dependent signaling cascade. Existing knowledge about the mechanism(s) and cellular factor(s) governing TLR3 trafficking is limited. In the current study, we identified intracellular S100A9 protein as a critical regulator of TLR3 trafficking. S100A9 was required for maturation of TLR3 containing early endosome (EE) into LE, the compartment that fuses with lysosome to form the endolysosomal compartment. A drastic reduction in cytokine production was observed in S100A9-knockout (KO) primary macrophages following RNA virus infection and treatment of cells with polyinosinic-polycytidylic acid (polyIC; a dsRNA mimetic that acts as a TLR3 agonist). Mechanistic studies revealed colocalization and interaction of S100A9 with TLR3 following polyIC treatment. S100A9-TLR3 interaction was critical for maturation of TLR3 containing EE into LE because TLR3 could not be detected in the LE of polyIC-treated S100A9-KO macrophages. Subsequently, TLR3 failed to colocalize with its agonist (i.e., biotin-labeled polyIC) in S100A9-deficient macrophages. The in vivo physiological role of S100A9 was evident from loss of cytokine production in polyIC-treated S100A9-KO mice. Thus, we identified intracellular S100A9 as a regulator of TLR3 signaling and demonstrated that S100A9 functions during pre-TLR3 activation stages by facilitating maturation of TLR3 containing EE into LE.
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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) | 0.000 | 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 | 0.001 |
| 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 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".