Mechanistic dissection of premature translation termination induced by acidic residues-enriched nascent peptide
Bibliographic record
Abstract
Ribosomes polymerize nascent peptides through repeated inter-subunit rearrangements between the classic and hybrid states. The peptidyl-tRNA, the intermediate species during translation elongation, stabilizes the translating ribosome to ensure robust continuity of elongation. However, the translation of acidic residue-rich sequences destabilizes the ribosome, leading to a stochastic premature translation cessation termed intrinsic ribosome destabilization (IRD), which is still ill-defined. Here, we dissect the molecular mechanisms underlying IRD in Escherichia coli. Reconstitution of the IRD event reveals that (1) the prolonged ribosome stalling enhances IRD-mediated translation discontinuation, (2) IRD depends on temperature, (3) the destabilized 70S ribosome complex is not necessarily split, and (4) the destabilized ribosome is subjected to peptidyl-tRNA hydrolase-mediated hydrolysis of the peptidyl-tRNA without subunit splitting or recycling factors-mediated subunit splitting. Collectively, our data indicate that the translation of acidic-rich sequences alters the conformation of the 70S ribosome to an aberrant state that allows the noncanonical premature termination.
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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 | 0.001 |
| 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".