Genomic diversity of SARS-CoV-2 can be accelerated by mutations in the nsp14 gene
Bibliographic record
Abstract
Coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), encode a proofreading exonuclease, nonstructural protein 14 (nsp14), that helps ensure replication competence at a low evolutionary rate compared with other RNA viruses. In the current pandemic, SARS-CoV-2 has accumulated diverse genomic mutations including in nsp14. Here, to clarify whether amino acid substitutions in nsp14 affect the genomic diversity and evolution of SARS-CoV-2, we searched for amino acid substitutions in nature that may interfere with nsp14 function. We found that viruses carrying a proline-to-leucine change at position 203 (P203L) have a high evolutionary rate and that a recombinant SARS-CoV-2 virus with the P203L mutation acquired more diverse genomic mutations than wild-type virus during its replication in hamsters. Our findings suggest that substitutions, such as P203L, in nsp14 may accelerate the genomic diversity of SARS-CoV-2, contributing to virus evolution during the pandemic.
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 | 0.000 |
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".