Genetic variety of ORF3a shapes SARS‐CoV‐2 fitness through modulation of lipid droplet
Bibliographic record
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection leads to the accumulation of lipid droplets (LD), the central hubs of the lipid metabolism, in vitro or in type II pneumocytes and monocytes from coronavirus disease 19 (COVID-19) patients and blockage of LD formation by specific inhibitors impedes SARS-CoV-2 replication. Here, we showed that ORF3a is necessary and sufficient to trigger LD accumulation during SARS-CoV-2 infection, leading to efficient virus replication. Although highly mutated during evolution, ORF3a-mediated LD modulation is conserved in most SARS-CoV-2 variants except the Beta strain and is a major difference between SARS-CoV and SARS-CoV-2 that depends on the genetic variations on the amino acid position 171, 193, and 219 of ORF3a. Importantly, T223I substitution in recent Omicron strains (BA.2-BF.8) impairs ORF3a-Vps39 association and LD accumulation, leading to less efficient replication and potentially contributing to lower pathogenesis of the Omicron strains. Our work characterized how SARS-CoV-2 modulates cellular lipid homeostasis to benefit its replication during virus evolution, making ORF3a-LD axis a promising drug target for the treatment of COVID-19.
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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 | 0.000 |
| 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".