SARS-CoV-2 Nonstructural Proteins 1 and 13 Suppress Caspase-1 and the NLRP3 Inflammasome Activation
Bibliographic record
Abstract
Viral infection-induced activation of inflammasome complexes has both positive and negative effects on the host. Proper activation of inflammasome complexes induces down-stream effector mechanisms that inhibit viral replication and promote viral clearance, whereas dysregulated activation has detrimental effects on the host. Coronaviruses, including SARS-CoV and MERS-CoV, encode viroporins that activate the NLRP3 inflammasome, and the severity of coronavirus disease is associated with the inflammasome activation. Although the NLRP3 inflammasome activation is implicated in the pathogenesis of coronaviruses, these viruses must evade inflammasome-mediated antiviral immune responses to establish primary replication. Screening of a complementary DNA (cDNA) library encoding 28 SARS-CoV-2 open reading frames (ORFs) showed that two nonstructural proteins (NSPs), NSP1 and NSP13, inhibited caspase-1-mediated IL-1β activation. NSP1 amino acid residues involved in host translation shutoff and NSP13 domains responsible for helicase activity were associated with caspase-1 inhibition. In THP-1 cells, both NSP1 and NSP13 significantly reduced NLRP3-inflammasome-induced caspase-1 activity and IL-1β secretion. These findings indicate that SARS-CoV-2 NSP1 and NSP13 are potent antagonists of the NLRP3 inflammasome.
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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) | 0.001 | 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 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".