Activation of the NLRP1 inflammasome in human keratinocytes by the dsDNA mimetic poly(dA:dT)
Bibliographic record
Abstract
The accrual of cytosolic DNA leads to transcription of type I IFNs, proteolytic maturation of the IL-1 family of cytokines, and pyroptotic cell death. Caspase-1 cleaves pro-IL1β to generate mature bioactive cytokine and gasdermin D which facilitates IL-1 release and pyroptotic cell death. Absent in melanoma-2 ( AIM2 ) is a sensor of dsDNA leading to caspase-1 activation, although in human monocytes, cGAS-STING acting upstream of NLRP3 mediates the dsDNA-activated inflammasome response. In healthy human keratinocytes, AIM2 is not expressed yet caspase-1 is activated by the synthetic dsDNA mimetic poly(dA:dT). Here, we show that this response is not mediated by either AIM2 or the cGAS-STING-NLRP3 pathway and is instead dependent on NLRP1. Poly(dA:dT) is unique in its ability to activate NLRP1, as conventional linear dsDNAs fail to elicit NLRP1 activation. DsRNA was recently shown to activate NLRP1 and prior work has shown that poly(dA:dT) is transcribed into an RNA intermediate that stimulates the RNA sensor RIG-I. However, poly(dA:dT)-dependent RNA intermediates are insufficient to activate NLRP1. Instead, poly(dA:dT) results in oxidative nucleic acid damage and cellular stress, events which activate MAP3 kinases including ZAKα that converge on p38 to activate NLRP1. Collectively, this work defines a new activator of NLRP1, broadening our understanding of sensors that recognize poly(dA:dT) and advances the understanding of the immunostimulatory potential of this potent adjuvant.
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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) | 0.000 | 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) | 0.002 | 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".