The Telomerase/Vault-Associated Protein Tep1 Is Required for Vault RNA Stability and Its Association with the Vault Particle
Bibliographic record
Abstract
Vaults and telomerase are ribonucleoprotein (RNP) particles that share a common protein subunit, TEP1. Although its role in either complex has not yet been defined, TEP1 has been shown to interact with the mouse telomerase RNA and with several of the human vault RNAs in a yeast three-hybrid assay. An mTep1(-/-) mouse was previously generated which resulted in no apparent change in telomere length or telomerase activity in six generations of mTep1-deficient mice. Here we show that the levels of the telomerase RNA and its association with the telomerase RNP are also unaffected in mTep1(-/-) mice. Although vaults purified from the livers of mTep1(-/-) mice appear structurally intact by both negative stain and cryoelectron microscopy, three-dimensional reconstruction of the mTep1(-/-) vault revealed less density in the cap than previously observed for the intact rat vault. Furthermore, the absence of TEP1 completely disrupted the stable association of the vault RNA with the purified vault particle and also resulted in a decrease in the levels and stability of the vault RNA. Therefore, we have uncovered a novel role for TEP1 in vivo as an integral vault protein important for the stabilization and recruitment of the vault RNA to the vault particle.
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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".