SARS-CoV-2 Nsp2 recruits GIGYF2 near viral replication sites and supports viral protein production
Bibliographic record
Abstract
The SARS-CoV-2 genome encodes 16 nonstructural proteins (Nsps), with Nsp2 being the least conserved and understood. This study highlights a crucial role for Nsp2 in the early phase of the viral life cycle, particularly its interaction with GIGYF2, which relocates near double-membrane vesicles (DMVs) and enhances viral protein production. Deletion of the Nsp2-coding region from the viral genome led to a drastic reduction in viral RNA synthesis early in infection (3-4 h after infection). Interactome analysis in virus-infected cells identified GIGYF2, a host-encoded translational regulation protein, as a key Nsp2 partner. This interaction was confirmed for both SARS-CoV-1 and SARS-CoV-2. Depletion of GIGYF2 or its cofactor ZNF598 phenocopied the replication defects observed with Nsp2 deletion, suggesting their critical roles in viral reproduction. Upon infection, GIGYF2 and ZNF598 relocate to areas near DMVs, viral replication sites. This relocation does not occur with the Nsp2-deleted virus, indicating Nsp2's role in directing GIGYF2 to DMVs. Formaldehyde crosslinking and immunoprecipitation sequencing (fCLIP-seq) identified regions within viral RNAs that potentially interact with GIGYF2, including those encoding M and Orf6. Depletion of GIGYF2 resulted in decreased protein expression of M and Orf6. Our findings reveal the function of Nsp2 in supporting viral protein production by exploiting GIGYF2 as a host factor.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".