High-resolution single-molecule optical trapping measurements of transcription with basepair accuracy: instrumentation and methods
Bibliographic record
Abstract
Optical traps allow the single-molecule investigation of the chemo-mechanical properties of biomolecules1. We have developed an ultra-stable optical trapping system capable of ångstr&diaero;m-level position resolution and used it to monitor transcriptional elongation by single molecules of E. coli RNAP polymerase (RNAP). This optical trapping system uses the anharmonic region of the trapping potential, where differential stiffness vanishes, to generate a force-clamp that operates without feedback-associated noise2. We demonstrate methods of calibrating this anharmonic trapping region and strategies to eliminate common sources of noise associated with air currents. Records of transcriptional elongation obtained with this device showed discrete steps averaging ~3.7 Å, a distance equivalent to the mean rise per base found in B-DNA3. To determine the absolute position of the RNAP on the DNA template, we monitored transcription under conditions in which a single nucleotide species was held rate-limiting and then aligned the resulting transcriptional pauses with the occurrence of this rate-limiting species in the underlying template. The aligned pause patterns recorded from four molecules, each measured with a different ratelimiting nucleotide species, were used to determine the sequence of a short region of unknown DNA, demonstrating that the motion of a single processive nucleic acid enzyme may be used to extract sequence information directly from DNA4.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".