Commensal bacteria trigger a full dendritic cell maturation program that promotes the expansion of non-Tr1 suppressor T cells
Bibliographic record
Abstract
Dendritic cells (DCs) orchestrate the immune response establishing immunity versus tolerance. These two opposite functions may be dictated by DC maturation status with maturity linked to immunogenicity. DCs directly interact with trillions of noninvasive intestinal bacteria in vivo, a process that contributes to gut homeostasis. We here evaluated the maturation program elicited in human DCs by direct exposure to commensal-related bacteria (CB) in the absence of inflammatory signals. We showed that eight gram(+) and gram(-) CB strains up-regulated costimulatory molecule expression in DCs and provoked a chemokine receptor switch similar to that activated by gram(+) pathogens. CB strains may be classified into three groups according to DC cytokine release: high IL-12 and low IL-10; low IL-12 and high IL-10; and low IL-12 and IL-10. All CB-treated DCs produced IL-1beta and IL-6 and almost no TGF-beta. Yet, CB instructed DCs to convert naive CD4+ T cells into hyporesponsive T cells that secreted low or no IFN-gamma, IL-10, and IL-17 and instead, displayed suppressor function. These data demonstrate that phenotypic DC maturation combined to an appropriate cytokine profile is insufficient to warrant Th1, IL-10-secreting T regulatory Type 1 (Tr1), or Th17 polarization. We propose that commensal flora and as such, probiotics manipulate DCs by a yet-unidentified pathway to enforce gut tolerance.
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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 | 0.000 |
| 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".