Escape from SARS-CoV-2 Nsp1-mediated host shutoff by TIAR transcript reveals general features of Nsp1 resistance
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune escape strategies include general inhibition of host gene expression referred to as host shutoff. Viral nonstructural protein 1 (Nsp1) is the main host shutoff factor that blocks protein translation and induces messenger RNA (mRNA) cleavage and degradation. Viral mRNAs are resistant to the translation shutoff and cleavage induced by Nsp1, and the 5' leader sequence present in all viral mRNAs has been shown to confer resistance. However, the exact molecular mechanism for escape from Nsp1 host shutoff has not been demonstrated. In our previous work, we analyzed the effects of Nsp1 on the expression and function of cellular proteins important for stress granule formation. We discovered that the host transcript for the TIA1 cytotoxic granule-associated RNA-binding protein-like 1 (TIAL1, commonly referred to as TIAR) is resistant to SARS-CoV-2 Nsp1 host shutoff. In this work, using reporter shutoff assays, we examined sequence and structural features of the TIAR 5' untranslated region (UTR) and discovered that the first 23 nt of the TIAR transcript are both necessary and sufficient to confer resistance to the Nsp1. Furthermore, our work revealed that the lack of guanosines within a window of 10-18 nt downstream from the 5' end is a defining feature of Nsp1-resistant transcripts shared between the SARS-CoV-2 leader sequence and the TIAR 5' UTR. Our findings are consistent with the model in which sequence features of 5' UTRs, rather than their secondary structure, confer resistance to Nsp1 host shutoff to both viral and cellular mRNAs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".