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Cytosolic Sensing of Viruses
Open accessAbstract
Cells are equipped with mechanisms that allow them to rapidly detect and respond to viruses. These defense mechanisms rely partly on receptors that monitor the cytosol for the presence of atypical nucleic acids associated with virus infection. RIG-I-like receptors detect RNA molecules that are absent from the uninfected host. DNA receptors alert the cell to the abnormal presence of that nucleic acid in the cytosol. Signaling by RNA and DNA receptors results in the induction of restriction factors that prevent virus replication and establish cell-intrinsic antiviral immunity. In light of these formidable obstacles, viruses have evolved mechanisms of evasion, masking nucleic acid structures recognized by the host, sequestering themselves away from the cytosol or targeting host sensors, and signaling adaptors for deactivation or degradation. Here, we detail recent advances in the molecular understanding of cytosolic nucleic acid detection and its evasion by viruses.
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Metadata
- Authors
- Goubau, D., Deddouche, S., & Reis e Sousa, C.
- Venue
- Immunity
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 38
- Issue
- 5
- Pages
- 855-869
- ISSN
- 1074-7613 (ISSN-L)
- OpenAlex
- W2063310200
- Cited by
- 843
- References
- 14
- FWCI
- 37.13
- Type
- journal article
- Language
- en
- Open access
- bronze
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 387 d)
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- This page
- CoChat. (2026). Citation check: Cytosolic Sensing of Viruses. https://app.cochat.ai/papers/10.1016/j.immuni.2013.05.007
- The paper
- Goubau, D., Deddouche, S., & Reis e Sousa, C. (2013). Cytosolic Sensing of Viruses. Immunity. https://doi.org/10.1016/j.immuni.2013.05.007
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.