Tombusvirus recruitment of host translational machinery via the 3′ UTR
Bibliographic record
Abstract
RNA viruses recruit the host translational machinery by different mechanisms that depend partly on the structure of their genomes. In this regard, the plus-strand RNA genomes of several different pathogenic plant viruses do not contain traditional translation-stimulating elements, i.e., a 5'-cap structure and a 3'-poly(A) tail, and instead rely on a 3'-cap-independent translational enhancer (3'CITE) located in their 3' untranslated regions (UTRs) for efficient synthesis of viral proteins. We investigated the structure and function of the I-shaped class of 3'CITE in tombusviruses--also present in aureusviruses and carmoviruses--using biochemical and molecular approaches and we determined that it adopts a complex higher-order RNA structure that facilitates translation by binding simultaneously to both eukaryotic initiation factor (eIF) 4F and the 5' UTR of the viral genome. The specificity of 3'CITE binding to eIF4F is mediated, at least in part, through a direct interaction with its eIF4E subunit, whereas its association with the viral 5' UTR relies on complementary RNA-RNA base-pairing. We show for the first time that this tripartite 5' UTR/3'CITE/eIF4F complex forms in vitro in a translationally relevant environment and is required for recruitment of ribosomes to the 5' end of the viral RNA genome by a mechanism that shares some fundamental features with cap-dependent translation. Notably, our results demonstrate that the 3'CITE facilitates the initiation step of translation and validate a molecular model that has been proposed to explain how several different classes of 3'CITE function. Moreover, the virus-host interplay defined in this study provides insights into natural host resistance mechanisms that have been linked to 3'CITE activity.
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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 | 0.001 |
| 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".