A truncated SARS-CoV-2 nucleocapsid protein enhances virus fitness by evading antiviral responses
Bibliographic record
Abstract
ABSTRACT Viruses face a selective pressure to evade cellular antiviral responses to control the outcome of an infection. However, due to their limited genome size, viruses must adopt unique strategies to confront cellular sensors. Since emerging in humans, SARS-CoV-2 has accrued multiple mutations throughout its genome, some of which enhanced virus replication and led to the rise of viral variants. However, the biological consequences of many of these changes remain to be discovered. Here, we show that SARS-CoV-2 produces a truncated form of the nucleocapsid protein, called N* M210 . Due to the acquisition of a viral transcription regulatory sequence (TRS) in the N gene, certain variants, such as Omicron, produce a new viral mRNA that markedly increases N* M210 expression. We show that N* M210 is a dsRNA binding protein, which inhibits multiple arms of the cellular antiviral response, including blocking interferon induction and inhibiting stress granule formation. We created a panel of recombinant SARS-CoV-2 viruses (rSARS-2) with mutations in the N gene that increased or decreased N* M210 production. We show that N* M210 production increases virus fitness, as viruses that produce more N* M210 outcompeted wild-type rSARS-2. We demonstrate that the fitness advantage provided by N* M210 is partly due to its ability to potently block stress granules. We propose a model where, to evade the cellular antiviral response, SARS-CoV-2 has evolved a mechanism to increase the production of a truncated form of the N protein, which broadly limits the activation of dsRNA-induced antiviral responses, tipping the balance in favour of the virus in the battle for control of the cell. Highlights SARS-CoV-2 variants evolved to upregulate truncated N (N*) synthesis to increase virus fitness N* M210 is a potent dsRNA-binding protein that blocks cellular dsRNA sensing N* M210 inhibits stress granule formation independent of G3BP1 binding
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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".