It takes two (Las1 HEPN endoribonuclease domains) to cut RNA correctly
Bibliographic record
Abstract
The ribosome biogenesis factor Las1 is an essential endoribonuclease that is well-conserved across eukaryotes and a newly established member of the higher eukaryotes and prokaryotes nucleotide-binding (HEPN) domain-containing nuclease family. HEPN nucleases participate in diverse RNA cleavage pathways and share a short HEPN nuclease motif (Rφ XXX H) important for RNA cleavage. Most HEPN nucleases participate in stress-activated RNA cleavage pathways; Las1 plays a fundamental role in processing pre-rRNA. Underscoring the significance of Las1 function in the cell, mutations in the human LAS1L (LAS1-like) gene have been associated with neurological dysfunction. Two juxtaposed HEPN nuclease motifs create Las1's composite nuclease active site, but the roles of the individual HEPN motif residues are poorly defined. Here using a combination of in vivo experiments in Saccharomyces cerevisiae and in vitro assays, we show that both HEPN nuclease motifs are required for Las1 nuclease activity and fidelity. Through in-depth sequence analysis and systematic mutagenesis, we determined the consensus HEPN motif in the Las1 subfamily and uncovered its canonical and specialized elements. Using reconstituted Las1 HEPN-HEPN′ chimeras, we defined the molecular requirements for RNA cleavage. Intriguingly, both copies of the Las1 HEPN motif were important for nuclease function, revealing that both HEPN motifs participate in coordinating the RNA within the Las1 active site. We also established that conformational flexibility of the two HEPN domains is important for proper nuclease function. The results of our work reveal critical information about how dual HEPN domains come together to drive Las1-mediated RNA cleavage.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".