CD1d‐independent activation of mouse and human <i>i</i>NKT cells by bacterial superantigens
Why this work is in the frame
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Bibliographic record
Abstract
Invariant NKT (iNKT) cells are infrequent but important immunomodulatory lymphocytes that exhibit CD1d-restricted reactivity with glycolipid Ags. iNKT cells express a unique T-cell receptor (TCR) composed of an invariant α-chain, paired with a limited range of β-chains. Superantigens (SAgs) are microbial toxins defined by their ability to activate conventional T cells in a TCR β-chain variable domain (Vβ)-specific manner. However, whether iNKT cells are directly activated by bacterial SAgs remains an open question. Herein, we explored the responsiveness of mouse and human iNKT cells to a panel of staphylococcal and streptococcal SAgs and examined the contribution of major histocompatibility complex (MHC) class II and CD1d to these responses. Bacterial SAgs that target mouse Vβ8, such as staphylococcal enterotoxin B (SEB), were able to activate mouse hybridoma and primary hepatic iNKT cells in the presence of mouse APCs expressing human leukocyte antigen (HLA)-DR4. iNKT cell-mediated cytokine secretion in SEB-challenged HLA-DR4-transgenic mice was CD1d-independent and accompanied by a high interferon-γ:interleukin-4 ratio consistent with an in vivo Th1 bias. Furthermore, iNKT cells from SEB-injected HLA-DR4-transgenic mice, and iNKT cells from SEB-treated human PBMCs, showed early activation by intracellular cytokine staining and CD69 expression. Unlike iNKT cell stimulation by α-galactosylceramide, stimulation by SEB did not induce TCR downregulation of either mouse or human iNKT cells. We conclude that Vβ8-targeting bacterial SAgs can activate iNKT cells by utilizing a novel pathway that requires MHC class II interactions, but not CD1d. Therefore, iNKT cells fulfill important effector functions in response to bacterial SAgs and may provide attractive targets in the management of SAg-induced illnesses.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it