Fluorescent Visualization of Mango-tagged RNA in Polyacrylamide Gels via a Poststaining Method
Bibliographic record
Abstract
Native and denaturing polyacrylamide gels are routinely used to characterize ribonucleoprotein (RNP) complex mobility and to measure RNA size, respectively. As many gel-imaging techniques use nonspecific stains or expensive fluorophore probes, sensitive, discriminating, and economical gel-imaging methodologies are highly desirable. RNA Mango core sequences are small (19-22 nt) sequence motifs that, when closed by an arbitrary RNA stem, can be simply and inexpensively appended to an RNA of interest. These Mango tags bind with high affinity and specificity to a thiazole-orange fluorophore ligand called TO1-Biotin, which becomes thousands of times more fluorescent upon binding. Here we show that Mango I, II, III, and IV can be used to specifically image RNA in gels with high sensitivity. As little as 62.5 fmol of RNA in native gels and 125 fmol of RNA in denaturing gels can be detected by soaking gels in an imaging buffer containing potassium and 20 nM TO1-Biotin for 30 min. We demonstrate the specificity of the Mango-tagged system by imaging a Mango-tagged 6S bacterial RNA in the context of a complex mixture of total bacterial RNA.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".