Fluorescent labeling of RNA and DNA on the Hoogsteen edge using sulfinate chemistry
Bibliographic record
Abstract
We have devised a single pot, low-cost method to add azide groups to unmodified nucleic acids without the need for enzymes or chemically modified nucleoside triphosphates. This involves reacting an azide-containing sulfinate salt with the nucleic acid, leading to replacement of C-H bonds on the nucleobase aromatic rings with C-R, where R is the azide-containing linker derived from the original sulfinate salt. With the addition of azide functional groups, the modified nucleic acid can easily be reacted with any alkyne-labeled compound of interest, including fluorescent dyes as shown in this work. This methodology enables the fluorescent labeling of a wide variety of nucleic acids, including natively folded RNAs, under mild conditions with minimal effects upon biochemical function and ribozyme catalysis. To demonstrate this, we show that a pair of labeled complementary ssDNA oligonucleotides (oligos) can hybridize to form dsDNA, even when labeled with multiple fluorophores per oligo. In addition, we also demonstrate that two different group II introns can splice when prelabeled internally with fluorophores, using our method. Broadly, this demonstrates that sulfinate modification of RNA is compatible with ribozyme function and Watson-Crick pairing, while preserving the labile backbone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".