Quantification of Pseudouridine Levels in Cellular RNA Pools with a Modified HPLC-UV Assay
Bibliographic record
Abstract
Pseudouridine (Ψ) is the most abundant post-transcriptionally modified ribonucleoside. Different Ψ modifications correlate with stress responses and are postulated to coordinate the distinct biological responses to a diverse panel of cellular stresses. With the help of different guide RNAs, the dyskerin complex pseudouridylates ribosomal RNA, small nuclear RNA and selective messenger RNAs. To monitor Ψ levels quantitatively, a previously reported high performance liquid chromatography method coupled with ultraviolet detection (HPLC-UV) was modified to determine total Ψ levels in different cellular RNA fractions. Our method was validated to be accurate and precise within the linear range of 0.06-15.36 pmol/μL and to have absolute Ψ quantification levels as low as 3.07 pmol. Using our optimized HPLC assay, we found that 1.20% and 1.94% of all ribonucleosides in nuclear-enriched RNA and small non-coding RNA pools from the HEK293 cell line, and 1.77% and 0.98% of ribonucleosides in 18S and 28S rRNA isolated from the HeLa cell line, were pseudouridylated. Upon knockdown of dyskerin expression, a consistent and significant reduction in total Ψ levels in nuclear-enriched RNA pools was observed. Our assay provides a fast and accurate quantification method to measure changes in Ψ levels of different RNA pools without sample derivatization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".