Efficient trans-cleavage by the Schistosoma mansoni SMalpha1 hammerhead ribozyme in the extreme thermophile Thermus thermophilus
Bibliographic record
Abstract
The catalytic hammerhead structure has been found in association with repetitive DNA from several animals, including salamanders, crickets and schistosomes, and functions to process in cis the long multimer transcripts into monomer RNA in vivo. The cellular role of these repetitive elements and their transcripts is unknown. Moreover, none of these natural hammerheads have been shown to trans-cleave a host mRNA in vivo. We analyzed the cis- and trans-cleavage properties of the hammerhead ribozyme associated with the SMalpha DNA family from the human parasite Schistosoma mansoni. The efficiency of trans-cleavage of a target RNA in vitro was affected mainly by both the temperature-dependent chemical step and the ribozyme-product dissociation step. The optimal temperature for trans-cleavage was 70 degrees C. This result was confirmed when both the SMalpha1 ribozyme and the target RNA were expressed in the extreme thermophile Thermus thermophilus. Moreover, SMalpha1 RNA showed a remarkable thermostability, equal or superior to that of the most stable RNAs in this species, suggesting that SMalpha1 RNA has been selected for stability. Computer analysis predicts that the monomer and multimer transcripts fold into highly compact secondary structures, which may explain their exceptional stability 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 | 0.000 | 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) | 0.000 | 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".