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Record W4392298534 · doi:10.1016/j.celrep.2024.113891

SARS-CoV-2 targets ribosomal RNA biogenesis

2024· article· en· W4392298534 on OpenAlexafffund
V. Talya Yerlici, Audrey Astori, Nevraj S. Kejiou, Chris Jordan, Negin Khosraviani, Janet N.Y. Chan, Razqallah Hakem, Brian Raught, Alexander F. Palazzo, Karim Mekhail

Bibliographic record

VenueCell Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsBiogenesisSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Ribosomal RNACoronavirus disease 2019 (COVID-19)RNABiologyVirology2019-20 coronavirus outbreakComputational biologyGeneticsMedicineGeneOutbreak

Abstract

fetched live from OpenAlex

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hinders host gene expression, curbing defenses and licensing viral protein synthesis and virulence. During SARS-CoV-2 infection, the virulence factor non-structural protein 1 (Nsp1) targets the mRNA entry channel of mature cytoplasmic ribosomes, limiting translation. We show that Nsp1 also restrains translation by targeting nucleolar ribosome biogenesis. SARS-CoV-2 infection disrupts 18S and 28S ribosomal RNA (rRNA) processing. Expression of Nsp1 recapitulates the processing defects. Nsp1 abrogates rRNA production without altering the expression of critical processing factors or nucleolar organization. Instead, Nsp1 localizes to the nucleolus, interacting with precursor-rRNA and hindering its maturation separately from the viral protein's role in restricting mature ribosomes. Thus, SARS-CoV-2 Nsp1 limits translation by targeting ribosome biogenesis and mature ribosomes. These findings revise our understanding of how SARS-CoV-2 Nsp1 controls human protein synthesis, suggesting that efforts to counter Nsp1's effect on translation should consider the protein's impact from ribosome manufacturing to mature ribosomes.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.265
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2024
Admission routes2
Has abstractyes

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