Functional Multimerization of the Human Telomerase Reverse Transcriptase
Bibliographic record
Abstract
The telomerase enzyme exists as a large complex (approximately 1,000 kDa) in mammals and at minimum is composed of the telomerase RNA and the catalytic subunit telomerase reverse transcriptase (TERT). In Saccharomyces cerevisiae, telomerase appears to function as an interdependent dimer or multimer in vivo (J. Prescott and E. H. Blackburn, Genes Dev. 11:2790-2800, 1997). However, the requirements for multimerization are not known, and it remained unclear whether telomerase exists as a multimer in other organisms. We show here that human TERT (hTERT) forms a functional multimer in a rabbit reticulocyte lysate reconstitution assay and in human cell extracts. Two separate, catalytically inactive TERT proteins can complement each other in trans to reconstitute catalytic activity. This complementation requires the amino terminus of one hTERT and the reverse transcriptase and C-terminal domains of the second hTERT. The telomerase RNA must associate with only the latter hTERT for reconstitution of telomerase activity to occur. Multimerization of telomerase also facilitates the recognition and elongation of substrates in vitro and in vivo. These data suggest that the catalytic core of human telomerase may exist as a functionally cooperative dimer or multimer in vivo.
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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 | 0.001 | 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 | 0.001 |
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".