Viruses, IRESs, and a universal translation initiation mechanism
Bibliographic record
Abstract
Internal ribosome entry sites (IRESs) are cis-acting RNA elements capable of recruiting ribosomes and initiating translation on an internal portion of an mRNA. This is divergent from canonical eukaryotic translation initiation, where the 5’ cap is recognized by initiation factors (IFs) that recruit the ribosome to initiate translation of the encoded peptide. All known IRESs are capable of initiating translation in a cap-independent manner, and are therefore not constrained by the absence or presence of a 5’ m7G cap. In addition to being cap-independent, IRES-mediated translation often uses only a subset of IFs allowing them to function independently of canonical initiation. The ability to function independently of the canonical translation initiation pathway allows IRESs to mediate gene expression when cap-dependent translation has been inhibited. Recent reports of viral IRESs capable of initiating translation across taxonomic domains (Eukarya and Bacteria) have sparked interest in designing gene expression systems compatible with multiple organisms. The ability to drive translation independent of cellular context using a common mechanism would have a wide range of applications ranging from agriculture biotechnology to the development of antiviral drugs. Here we discuss IRES-mediated translation and critically compare the available mechanistic and structural information. A particular focus will be on IRES-meditated translation across domains of life (viral and cellular IRESs) , IRES bioengineering and the possibility of an evolutionary conserved translation initiation mechanism.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".