S-Layer From Lactobacillus brevis Modulates Antigen-Presenting Cell Functions via the Mincle-Syk-Card9 Axis
Bibliographic record
Abstract
C-type lectin receptors (CLRs) are pattern recognition receptors that are crucial in the innate immune response. The gastrointestinal tract contributes significantly to the maintenance of immune homeostasis; it is the shelter for billions of microorganisms including many genera of Lactobacillus sp. Previously, it was shown that host-CLR interactions with gut microbiota play a crucial role in this context. The Macrophage-inducible C-type lectin (Mincle) is a Syk-coupled CLR that contributes to sensing of mucosa-associated commensals. In this study, we identified Mincle as a receptor for the Surface (S)-layer of the probiotic bacteria Lactobacillus brevis modulating GM-CSF bone marrow-derived cells (BMDCs) functions. We found that the S-layer/Mincle interaction led to a balanced cytokine response in BMDCs by triggering the release of both pro- and anti-inflammatory cytokines. In contrast, BMDCs derived from Mincle −/− , CARD9 −/− or conditional Syk −/− mice failed to maintain this balance, thus leading to an increased production of the pro-inflammatory cytokines TNF and IL-6, whereas the levels of the anti-inflammatory cytokines IL-10 and TGF-β were markedly decreased. Importantly, this was accompanied by an altered CD4 + T cell priming capacity of Mincle −/− BMDCs resulting in an increased CD4 + T cell IFN-γ production upon stimulation with L. brevis S-layer. Our results contribute to the understanding of how commensal bacteria regulate antigen-presenting cell (APC) functions and highlight the importance of the Mincle/Syk/Card9 axis in APCs as a key factor in host-microbiota interactions.
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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 | 0.000 | 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 | 0.000 |
| 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".