Free‐solution electrophoresis of DNA modified with drag‐tags at both ends
Bibliographic record
Abstract
In end-labeled free-solution electrophoresis (ELFSE), DNA molecules are labeled with a frictional modifier or "drag-tag", allowing their size-based electrophoretic separation in free solution. Among the interesting observations from early work with dsDNA using streptavidin as a drag-tag was that the drag induced by including a streptavidin label at both ends was significantly more than double that from a single streptavidin (Heller, C. et al.., J. Chromatogr. A 1998, 806, 113-121). This finding was assumed to be in error, and subsequent work focused on experiments in which only a single drag-tag is appended to one end of the DNA molecule. Recent theoretical work (McCormick, L. C., Slater, G. W., Electrophoresis 2005, 26, 1659-1667) has examined the contribution of end-effects to the free-solution electrophoretic mobility of charged-uncharged polymer conjugates, reopening the question of enhanced drag from placing a drag-tag at both ends. In this study, this effect is investigated experimentally, using custom-synthesized ssDNA oligonucleotides allowing the attachment of drag-tags to one or both ends, as well as dsDNA PCR products generated with primers appropriate for the attachment of drag-tags at one or both ends. A range of sizes of drag-tags are used, including synthetic polypeptoid drag-tags as well as genetically engineered protein polymer drag-tags. The enhanced drag arising from labeling both ends has been confirmed, with 6-9% additional drag for the ssDNA and 10-23% additional drag for the dsDNA arising from labeling both ends than would be expected from simply doubling the size of the drag-tag at one end. The experimental results for ssDNA labeled at both ends are compared to the predictions of the recent theory of end-effects, with reasonably good quantitative agreement. These experimental findings demonstrate the feasibility of enhancing ELFSE separations by labeling both ends of the DNA molecule, leading to greater resolving power and a wider range of applications for this technique.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".