Th17 Cells Are the Dominant T Cell Subtype Primed by <i>Shigella flexneri</i> Mediating Protective Immunity
Bibliographic record
Abstract
The T cell response to Shigella, the causative agent of bacillary dysentery, remains poorly understood. Using a murine model of infection, we report that Shigella flexneri primes predominately IL-17A- and IL-22-producing Th17 cells. Shigella-specific Th1 cells are only significantly induced on secondary infection, whereas specific Th2 and CD8(+) T cells are undetectable. Apart from Th17 cells that are primed in a MHC class II- and IL-6-dependent, but IL12/23p40-independent manner, we identified gammadelta T cells as an additional but minor source of IL-17A. Priming of IL-17A(+) gammadelta T cells is dependent on IL12/23p40, but independent of MHC-class II and IL-6. Th17 cells have emerged as important players in inflammatory, autoimmune, and infectious diseases. Among the yet unresolved questions is their role in long-term immunity to pathogens. In this study, we show that the elicited S. flexneri-specific Th17 pool gives rise to an enhanced recall response up to 12 mo after priming, suggesting the presence of a long-term memory state. The clearance of primary infection is impaired in the absence of T cells, but independently of IL-17A. However, after reinfection, IL-17A produced by S. flexneri-specific Th17 cells becomes important to ultimately restrict bacterial growth. These findings bring new insights into the adaptive immune response to Shigella infection and highlight the importance of pathogen-specific Th17 cell immunity for secondary immune protection.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".