An enzyme-coupled high-throughput assay for screening RNA methyltransferase activity in<i>E. Coli</i>cell lysate
Bibliographic record
Abstract
Post-transcriptional modifications of RNA diversify the genetically encoded sequences and play important roles in fundamental cellular processes like mRNA and rRNA maturation. Most RNA methylations are catalyzed by S-adenosylmethionine-dependent RNA methyltransferases. An assay for rapid and easy detection of this enzymatic activity would be highly desirable to identify novel RNA methyltransferases, test S-adenosylmethionine analogs or screen RNA methyltransferase inhibitors. We have developed an enzyme-coupled assay to determine the activity of trimethylguanosine synthases, a class of RNA methyltransferases responsible for RNA cap hypermethylation in eukaryotes. We show that this assay can be used in E. coli cell lysate to measure the activity of recombinantly produced trimethylguanosine synthase. Potential hits are validated for formation of hypermethylated product using HPLC and MALDI-TOF-MS. Furthermore, we demonstrate how this assay can be implemented to screen methyltransferase inhibitors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".