The RNA Interference Effector Protein Argonaute 2 Functions as a Restriction Factor Against SARS-CoV-2
Bibliographic record
Abstract
Argonaute 2 (Ago2) is a key component of the RNA interference (RNAi) pathway, a gene-regulatory system that is present in most eukaryotes. Ago2 uses microRNAs (miRNAs) and small interfering RNAs (siRNAs) for targeting to homologous mRNAs which are then degraded or translationally suppressed. In plants and invertebrates, the RNAi pathway has well-described roles in antiviral defense, but its function in limiting viral infections in mammalian cells is less well understood. Here, we examined the role of Ago2 in replication of the betacoronavirus SARS-CoV-2, the etiologic agent of COVID-19. Microscopic analyses of infected cells revealed that a pool of Ago2 closely associates with viral replication sites and gene ablation studies showed that loss of Ago2 resulted in over 1,000-fold increase in peak viral titers. Replication of the alphacoronavirus 229E was also significantly increased in cells lacking Ago2. The antiviral activity of Ago2 was dependent on both its ability to bind small RNAs and its endonuclease function. Interestingly, in cells lacking Dicer, an upstream component of the RNAi pathway, viral replication was the same as in parental cells. This suggests that the antiviral activity of Ago2 is independent of Dicer processed miRNAs. Deep sequencing of infected cells by other groups identified several SARS-CoV-2-derived small RNAs that bind to Ago2. A mutant virus lacking the most abundant ORF7A-derived viral miRNA was found to be significantly less sensitive to Ago2-mediated restriction. This combined with our findings that endonuclease and small RNA-binding functions of Ago2 are required for its antiviral function, suggests that Ago2-small viral RNA complexes target nascent viral RNA produced at replication sites for cleavage. Further studies are required to elucidate the processing mechanism of the viral small RNAs that are used by Ago2 to limit coronavirus replication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".