Proteolytic Processing of Nlrp1b Is Required for Inflammasome Activity
Bibliographic record
Abstract
Nlrp1b is a NOD-like receptor that detects the catalytic activity of anthrax lethal toxin and subsequently co-oligomerizes into a pro-caspase-1 activation platform known as an inflammasome. Nlrp1b has two domains that promote oligomerization: a NACHT domain, which is a member of the AAA+ ATPase family, and a poorly characterized Function to Find Domain (FIIND). Here we demonstrate that proteolytic processing within the FIIND generates N-terminal and C-terminal cleavage products of Nlrp1b that remain associated in both the auto-inhibited state and in the activated state after cells have been treated with lethal toxin. Functional significance of cleavage was suggested by the finding that mutations that block processing of Nlrp1b also prevent the ability of Nlrp1b to activate pro-caspase-1. By using an uncleaved mutant of Nlrp1b, we established the importance of cleavage by inserting a heterologous TEV protease site into the FIIND and demonstrating that TEV protease processed this site and induced inflammasome activity. Proteolysis of Nlrp1b was shown to be required for the assembly of a functional inflammasome: a mutation within the FIIND that abolished cleavage had no effect on self-association of a FIIND-CARD fragment, but did reduce the recruitment of pro-caspase-1. Our work indicates that a post-translational modification enables Nlrp1b to function.
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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 | 0.001 |
| 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".