Rapid and Rigorous IL-17A Production by a Distinct Subpopulation of Effector Memory T Lymphocytes Constitutes a Novel Mechanism of Toxic Shock Syndrome Immunopathology
Bibliographic record
Abstract
Abstract Toxic shock syndrome (TSS) is caused by staphylococcal and streptococcal superantigens (SAgs) that provoke a swift hyperinflammatory response typified by a cytokine storm. The precipitous decline in the host’s clinical status and the lack of targeted therapies for TSS emphasize the need to identify key players of the storm’s initial wave. Using a humanized mouse model of TSS and human cells, we herein demonstrate that SAgs elicit in vitro and in vivo IL-17A responses within hours. SAg-triggered human IL-17A production was characterized by remarkably high mRNA stability for this cytokine. A distinct subpopulation of CD4+ effector memory T (TEM) cells that secrete IL-17A, but not IFN-γ, was responsible for early IL-17A production. We found mouse “TEM-17” cells to be enriched within the intestinal epithelium and among lamina propria lymphocytes. Furthermore, interfering with IL-17A receptor signaling in human PBMCs attenuated the expression of numerous inflammatory mediators implicated in the TSS-associated cytokine storm. IL-17A receptor blockade also abrogated the secondary effect of SAg-stimulated PBMCs on human dermal fibroblasts as judged by C/EBP δ expression. Finally, the early IL-17A response to SAgs was pathogenic because in vivo neutralization of IL-17A in humanized mice ameliorated hepatic and intestinal damage and reduced mortality. Together, our findings identify CD4+ TEM cells as a key effector of TSS and reveal a novel role for IL-17A in TSS immunopathogenesis. Our work thus elucidates a pathogenic, as opposed to protective, role for IL-17A during Gram-positive bacterial infections. Accordingly, the IL-17–IL-17R axis may provide an attractive target for the management of SAg-mediated illnesses.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".