<i>Salmonella</i> Flagellin Activates NAIP/NLRC4 and Canonical NLRP3 Inflammasomes in Human Macrophages
Bibliographic record
Abstract
Abstract Infection of human macrophages with Salmonella enterica serovar Typhimurium (S. Typhimurium) leads to inflammasome activation. Inflammasomes are multiprotein complexes facilitating caspase-1 activation and subsequent gasdermin D–mediated cell death and IL-1β and IL-18 cytokine release. The NAIP/NLRC4 inflammasome is activated by multiple bacterial protein ligands, including flagellin from the flagellum and the needle protein PrgI from the S. Typhimurium type III secretion system. In this study, we show that transfected ultrapure flagellin from S. Typhimurium induced cell death and cytokine secretion in THP-1 cells and primary human monocyte-derived macrophages. In THP-1 cells, NAIP/NLRC4 and NLRP3 played redundant roles in inflammasome activation during infection with S. Typhimurium. Knockout of NAIP or NLRC4 in THP-1 cells revealed that flagellin, but not PrgI, now activated the NLRP3 inflammasome through a reactive oxygen species– and/or cathepsin-dependent mechanism that was independent of caspase-4/5 activity. In conclusion, our data suggest that NLRP3 can be activated by flagellin to act as a “safety net” to maintain inflammasome activation under conditions of suboptimal NAIP/NLRC4 activation, as observed in THP-1 cells, possibly explaining the redundant role of NLRP3 and NAIP/NLRC4 during S. Typhimurium infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".