Phosphatidylinositol-4-kinase IIα licenses phagosomes for TLR4 signaling and MHC-II presentation in dendritic cells
Bibliographic record
Abstract
ABSTRACT Toll like receptor (TLR) recruitment to phagosomes in dendritic cells (DCs) and downstream TLR signaling are essential to initiate antimicrobial immune responses. However, the mechanisms underlying TLR localization to phagosomes are poorly characterized. We show herein that phosphatidylinositol-4-kinase IIα (PI4KIIα) plays a key role in initiating phagosomal TLR4 responses in murine DCs by generating a phosphatidylinositol-4-phosphate (PtdIns4P) platform conducive to the binding of the TLR sorting adaptor TIRAP. PI4KIIα is recruited to LPS-containing phagosomes in an adaptor protein AP-3 dependent manner, and both PI4KIIα and PtdIns4P are also detected on phagosomal membrane tubules. Knockdown of PI4KIIα – but not of the related PI4KIIβ – impairs TIRAP and TLR4 localization to phagosomes, reduces proinflammatory cytokine secretion, and impairs phagosomal tubule formation and MHC-II presentation. Phagosomal TLR responses in PI4KIIα-deficient DCs are restored by re-expression of wild-type PI4KIIα, but not of variants lacking kinase activity or AP-3 binding. Our data indicate that PI4KIIα is an essential regulator of phagosomal TLR signaling in DCs by ensuring optimal TIRAP recruitment to phagosomes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".