LAB/NTAL Facilitates Fungal/PAMP-induced IL-12 and IFN-γ Production by Repressing β-Catenin Activation in Dendritic Cells
Bibliographic record
Abstract
Fungal pathogens elicit cytokine responses downstream of immunoreceptor tyrosine-based activation motif (ITAM)-coupled or hemiITAM-containing receptors and TLRs. The Linker for Activation of B cells/Non-T cell Activating Linker (LAB/NTAL) encoded by Lat2, is a known regulator of ITAM-coupled receptors and TLR-associated cytokine responses. Here we demonstrate that LAB is involved in anti-fungal immunity. We show that Lat2-/- mice are more susceptible to C. albicans infection than wild type (WT) mice. Dendritic cells (DCs) express LAB and we show that it is basally phosphorylated by the growth factor M-CSF or following engagement of Dectin-2, but not Dectin-1. Our data revealed a unique mechanism whereby LAB controls basal and fungal/pathogen-associated molecular patterns (PAMP)-induced nuclear β-catenin levels. This in turn is important for controlling fungal/PAMP-induced cytokine production in DCs. C. albicans- and LPS-induced IL-12 and IL-23 production was blunted in Lat2-/- DCs. Accordingly, Lat2-/- DCs directed reduced Th1 polarization in vitro and Lat2-/- mice displayed reduced Natural Killer (NK) and T cell-mediated IFN-γ production in vivo/ex vivo. Thus our data define a novel link between LAB and β-catenin nuclear accumulation in DCs that facilitates IFN-γ responses during anti-fungal immunity. In addition, these findings are likely to be relevant to other infectious diseases that require IL-12 family cytokines and an IFN-γ response for pathogen clearance.
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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 | 0.000 |
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 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".