The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
SARS-CoV-2 N protein promotes NLRP3 inflammasome activation to induce hyperinflammation
Open accessAbstract
Excessive inflammatory responses induced upon SARS-CoV-2 infection are associated with severe symptoms of COVID-19. Inflammasomes activated in response to SARS-CoV-2 infection are also associated with COVID-19 severity. Here, we show a distinct mechanism by which SARS-CoV-2 N protein promotes NLRP3 inflammasome activation to induce hyperinflammation. N protein facilitates maturation of proinflammatory cytokines and induces proinflammatory responses in cultured cells and mice. Mechanistically, N protein interacts directly with NLRP3 protein, promotes the binding of NLRP3 with ASC, and facilitates NLRP3 inflammasome assembly. More importantly, N protein aggravates lung injury, accelerates death in sepsis and acute inflammation mouse models, and promotes IL-1β and IL-6 activation in mice. Notably, N-induced lung injury and cytokine production are blocked by MCC950 (a specific inhibitor of NLRP3) and Ac-YVAD-cmk (an inhibitor of caspase-1). Therefore, this study reveals a distinct mechanism by which SARS-CoV-2 N protein promotes NLRP3 inflammasome activation and induces excessive inflammatory responses.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Self-citationEarly transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K. S. M., Lau, E. H. Y., Wong, J. Y., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001316 · Cited by 16,575
Self-citationThe trinity of COVID-19: immunity, inflammation and intervention
Tay, M. Z., Poh, C. M., Rénia, L., MacAry, P. A., & Ng, L. F. P. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0311-8 · Cited by 4,360
Chu, D. K., Akl, E. A., Duda, S., Solo, K., Yaacoub, S., Schünemann, H. J., Chu, D. K., Akl, E. A., El-harakeh, A., Bognanni, A., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31142-9 · Cited by 3,843
The NLRP3 Inflammasome: an overview of mechanisms of activation and regulation
Kelley, N., Jeltema, D., Duan, Y., & He, Y. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20133328 · Cited by 3,539
Activation and regulation of the inflammasomes
Latz, E., Xiao, T. S., & Stutz, A. (2013) · Nature Reviews Immunology · doi:10.1038/nri3452 · Cited by 2,884
The Inflammasomes: Guardians of the Body
Martinon, F., Mayor, A., & Tschopp, J. (2009) · Annual Review of Immunology · doi:10.1146/annurev.immunol.021908.132715 · Cited by 2,436
Weber, A., Wasiliew, P., & Kracht, M. (2010) · Science Signaling · doi:10.1126/scisignal.3105cm1 · Cited by 962
Structural mechanism for NEK7-licensed activation of NLRP3 inflammasome
Sharif, H., Wang, L., Wang, W. L., Magupalli, V. G., Andreeva, L., Qiao, Q., Hauenstein, A. V., Wu, Z., Núñez, G., Mao, Y., et al. (2019) · Nature · doi:10.1038/s41586-019-1295-z · Cited by 824
Self-citationWrobel, A. G., Benton, D. J., Xu, P., Roustan, C., Martin, S. R., Rosenthal, P. B., Skehel, J. J., & Gamblin, S. J. (2020) · Nature Structural & Molecular Biology · doi:10.1038/s41594-020-0468-7 · Cited by 544
Inflammasome formation in the lungs of patients with fatal COVID-19
Toldo, S., Bussani, R., Nuzzi, V., Bonaventura, A., Mauro, A. G., Cannatà, A., Pillappa, R., Sinagra, G., Nana-Sinkam, P., Sime, P., et al. (2021) · Inflammation Research · doi:10.1007/s00011-020-01413-2 · Cited by 132
Cited by
Pyroptosis-Induced Inflammation and Tissue Damage
Vasudevan, S. O., Behl, B., & Rathinam, V. A. (2023) · Seminars in Immunology · doi:10.1016/j.smim.2023.101781 · Cited by 412
Cell deaths: Involvement in the pathogenesis and intervention therapy of COVID-19
Li, X., Zhang, Z., Wang, Z., Gutiérrez-Castrellón, P., & Shi, H. (2022) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-022-01043-6 · Cited by 67
Self-citationNAD+ in COVID-19 and viral infections
Zheng, M., Schultz, M. B., & Sinclair, D. A. (2022) · Trends in Immunology · doi:10.1016/j.it.2022.02.001 · Cited by 62
Viral sepsis: diagnosis, clinical features, pathogenesis, and clinical considerations
Xu, J.-Q., Zhang, W.-Y., Fu, J.-J., Fang, X.-Z., Gao, C.-G., Li, C., Yao, L., Li, Q.-L., Yang, X.-B., Ren, L.-H., et al. (2024) · Military Medical Research · doi:10.1186/s40779-024-00581-0 · Cited by 37
The comprehensive SARS-CoV-2 ‘hijackome’ knowledge base
Huuskonen, S., Liu, X., Pöhner, I., Redchuk, T., Salokas, K., Lundberg, R., Maljanen, S., Belik, M., Reinholm, A., Kolehmainen, P., et al. (2024) · Cell Discovery · doi:10.1038/s41421-024-00748-y · Cited by 12
Metadata
- Authors
- Pan, P., Shen, M., Yu, Z., Ge, W., Chen, K., Tian, M., Xiao, F., Wang, Z., Wang, J., Jia, Y., Wang, W., Wan, P., Zhang, J., Chen, W., Lei, Z., Chen, X., Luo, Z., Zhang, Q., Xu, M., Li, G., Li, Y., & Wu, J.
- Venue
- Nature Communications
- Published
- 2021-08-02
- Volume
- 12
- Issue
- 1
- Pages
- 4664-4664
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3191928958
- Cited by
- 501
- References
- 11
- FWCI
- 25.69
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
