Ribosome collision sensor Hel2 recognizes mistargeting secretory ribosome-nascent chain complexes
Bibliographic record
Abstract
Summary Ribosome collision due to translational stalling is recognized as a problematic event in translation by E3 ubiquitin ligase Hel2, leading to non-canonical subunit dissociation followed by targeting of the faulty nascent peptides for degradation. Although Hel2-mediated quality control greatly contributes to maintaining cellular protein homeostasis, its physiological role in dealing with endogenous substrates remains unclear. This study utilized genome-wide analysis, based on selective ribosome profiling, to survey the endogenous substrates for Hel2. This survey revealed that Hel2 preferentially binds to the pre-engaged secretory ribosome-nascent-chain complexes (RNCs), which translate upstream of targeting signals. Notably, Hel2 recruitment into secretory RNCs was elevated under signal recognition particle (SRP)-deficient conditions. Moreover, the mitochondrial defects caused by insufficient SRP were enhanced by hel2 deletion, along with the mistargeting of secretory proteins into mitochondria. Collectively, these findings provide novel insights into risk management in the secretory pathway that maintains cellular protein homeostasis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".