The NSP5, ORF6 and NSP13 of SARS‐CoV‐2 Cooperate to Modulate Inflammatory Cell Death Activation
Bibliographic record
Abstract
Programmed cell death is a pivotal mechanism of cell-autonomous immune defense against viral infections. Recent studies indicate that both blocking and promoting cell death negatively affect coronavirus replication, implying that coronaviruses may fine-tune cell death pathways to optimize their propagation. However, the mechanisms underlying this remain poorly understood. Here, it is verified that coronaviruses induce the formation of a Z-DNA-binding protein 1 (ZBP1)-initiated cell death complex involving ZBP1, Z-RNA, receptor-interacting serine/threonine-protein kinase 3 (RIPK3), and caspase-8, thereby triggering apoptosis, pyroptosis, and necroptosis in human bronchial epithelial cells. To impede the activation of apoptosis and pyroptosis, NSP5 and ORF6 of SARS-CoV-2 concurrently inhibit caspase-8 activity by targeting its large and small subunits, respectively. Additionally, NSP13, the viral helicase, interacts with RIPK3 to impair its binding to ZBP1, thus suppressing ZBP1-initiated necroptosis. This inhibitory effect on cell death is likely conserved across β-coronaviruses. Furthermore, co-infection of influenza A virus and SARS-CoV-2 is demonstrated to exacerbate disease severity, although the mechanisms remain unclear. These findings suggest that β-coronavirus-induced inhibition of cell death enhances influenza A virus replication and worsens inflammation during their co-infection, ultimately increasing mortality in mice. This research provides valuable insights into the regulation of coronavirus-induced cell death, offering potential therapeutic strategies for combating highly pathogenic coronavirus infections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".