Bacillus anthracis lethal toxin negatively modulates ILC3 function through perturbation of IL-23-mediated MAPK signaling
Bibliographic record
Abstract
Bacillus anthracis, the causative agent of anthrax, secretes lethal toxin that down-regulates immune functions.Translocation of B. anthracis across mucosal epithelia is key for its dissemination and pathogenesis.Group 3 innate lymphocytes (ILC3s) are important in mucosal barrier maintenance due to their expression of the cytokine IL-22, a critical regulator of tissue responses and repair during homeostasis and inflammation.We found that B. anthracis lethal toxin perturbed ILC3 function in vitro and in vivo, revealing an unknown IL-23-mediated MAPK signaling pathway.Lethal toxin had no effects on the canonical STAT3-mediated IL-23 signaling pathway.Rather lethal toxin triggered the loss of several MAP2K kinases, which correlated with reduced activation of downstream ERK1/2 and p38, respectively.Inhibition studies showed the importance of MAPK signaling in IL-23-mediated production of IL-22.Our finding that MAPK signaling is required for optimal IL-22 production in ILC3s may lead to new approaches for targeting IL-22 biology. Author summaryBacillus anthracis, the bacterium that causes the deadly disease anthrax, is commonly known for its use in bioterrorism.We have used B. anthracis to study the effect of MAPK signaling pathways in group 3 innate immune lymphocytes (ILC3s).B. anthracis enters the host through the lungs or gastrointestinal (GI) tract.To cause disease, the pathogen requires translocation across barrier tissue layers to disseminate.During this infection process, the bacterium produces many virulence factors, including a lethal toxin, that allow it to subvert the host immune response.In many immune cells, lethal toxin turns off signaling events through degradation of intermediate signaling components.In this study, we show that lethal toxin interferes in a specific signaling pathway, MAPK, which is significant because it is not usually associated with IL-23-mediated signaling.We specifically
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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) | 0.001 | 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".