Reversibly Constraining The Human U1 snRNP And The Spliceosome To A Pre‐mRNA Via An Engineered Site‐specific Disulfide Bond
Bibliographic record
Abstract
Pre‐messenger RNA splicing of protein‐coding RNA transcripts governs metazoan development. Pre‐mRNA splicing is catalyzed by the dynamic mega‐dalton spliceosome, formed by an ordered assembly of five U snRNPs (U1, U2, U4, U5 and U6 snRNPs) and non‐U snRNP proteins onto a pre‐mRNA substrate. The U snRNPs bind to and separate from the pre‐messenger RNA at key stages in the pre‐catalytic assembly of the spliceosome. The spliceosome assembly cycle is initiated with the recognition of the pre‐mRNA substrate 5′ splice site by the U1 snRNP which remains associated at this site during the recruitment of other U snRNPs. The U1 snRNP as well as the U4 snRNP and several other factors are subsequently displaced from their pre‐mRNA binding sites during the formation of a catalytic spliceosome. The mechanism, order, and importance of these displacement events is poorly understood, in part due to the challenges presented by the spliceosome's large size, dynamics, and crude source of material. In order to investigate the pre‐catalytic to catalytic transition undergone by the spliceosome, we have engineered a disulfide bond between a rationally designed U1‐C cysteine residue and a site‐specific thiol‐modified backbone of a pre‐mRNA substrate, allowing us to establish a reversible disulfide crosslink between a pre‐mRNA and the U1‐C protein alone as well as in the context of the U1 snRNP. This strategy will allow for a mechanistic elucidation of the critical pre‐catalytic to catalytic transition in spliceosome assembly, including examination of a possible sequential displacement of pre‐catalytic complexes in the activation of the spliceosome. Support or Funding Information National Science Foundation Award No. 1157892
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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".