<i>Escherichia coli</i> Heat-Labile Enterotoxin Promotes Protective Th17 Responses against Infection by Driving Innate IL-1 and IL-23 Production
Bibliographic record
Abstract
Escherichia coli heat-labile enterotoxin (LT) is a powerful mucosal adjuvant; however, it is associated with toxic effects when delivered intranasally, and its mechanism of action is poorly understood. In this article, we demonstrate that LT acts as a highly effective adjuvant when administered parenterally, promoting Ag-specific IL-17, as well as IFN-γ, IL-4, and IL-10 production in response to coadministered Ags. We found that the adjuvant activity of LT was mediated in part by inducing dendritic cell (DC) activation; LT promoted CD80 and CD86 expression by DCs and enhanced IL-1α, IL-1β, and IL-23 production. An LT mutant, LTK63, that lacks enzyme activity was less effective than the wild-type toxin in promoting DC maturation and the development of Ag-specific Th17 cells. LT enhanced IL-23 and IL-1α production from DCs via activation of ERK MAPK and IL-1β secretion through activation of caspase-1 and the NLRP3 inflammasome. These cytokines played a major role in promoting Th17 responses by LT and LTK63. The induction of Th17 cells in vivo in response to LT and LTK63 as adjuvants was significantly reduced in IL-1RI-deficient mice. Finally, using a murine respiratory infection model, we demonstrated that LT can act as a highly effective adjuvant for a pertussis vaccine, promoting Ag-specific Th17 cells and protection against Bordetella pertussis challenge, which was significantly reduced in IL-17-defective mice. Our findings provide clear evidence that LT can promote protective immune responses in part through induction of innate IL-1 and, consequently, Th17 cells.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".