MyD88 Adaptor-Like Is Not Essential for TLR2 Signaling and Inhibits Signaling by TLR3
Bibliographic record
Abstract
Although a clear role for the adaptor protein myeloid differentiation factor-88 (MyD88) adaptor-like (Mal, or TIRAP) in TLR4 signaling has been demonstrated, there is limited information on its role in TLR2 signaling. Here we have systematically analyzed the role of Mal in signaling by TLR2, TLR4, and as a control TLR3 in murine macrophages and dendritic cells. Mal was not required for the induction of IL-6 or NFkappaB activation at high concentrations of the TLR1/2 ligand Pam(3)Cys-Ser-(Lys)(4) or the TLR2/6 ligand macrophage-activating lipopeptide-2 and was required for these responses only at low ligand concentrations. Similarly, induction of IL-6 by Salmonella typhimurium, which is sensed by TLR2, required Mal only at low levels of bacteria. Mal was required for IL-6 induction at all concentrations of the TLR4 ligand LPS. Mal deficiency boosted IL-6 induction by the TLR3 ligand polyinosinic-polycytidylic acid. Activation of JNK, but not p38 or IkappaB degradation, was similarly potentiated in response to polyinosinic-polycytidylic acid in Mal-deficient macrophages. MyD88 was vital for all TLR2 and TLR4 responses and, similar to Mal, was also inhibitory for TLR3-dependent IL-6 and JNK induction. MyD88 interacted with the Toll/IL-1R domains of TLR1, TLR2, TLR4, and TLR6. Mal interacted with the Toll/Il-1R domains of TLR1, TLR2, and TLR4 but not with TLR6. Our study, therefore, reveals that Mal is dispensable in TLR2 signaling at high ligand concentrations in macrophages and dendritic cells, with MyD88 probably coupling to the TLR2 receptor complex at sufficient levels to allow activation. An inhibitory role for Mal in TLR3 signaling to JNK was also demonstrated.
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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".