Strategies for Rescuing Plasmid DNA from Yeast Two-Hybrid Colonies
Bibliographic record
Abstract
Once a yeast colony has been identified as containing a target plasmid insert of interest (as determined by growth on His− medium and a positive [blue] β-galactosidase assay; see Chapter 6 ), it becomes necessary to isolate the correct insert-containing plasmid. Isolating the plasmid DNA from yeast is not a trivial task, for several reasons. First, there is always contamination of the plasmid DNA by yeast genomic DNA since the isolation method breaks the yeast chromosomes. Second, most plasmids used tend to be large (>6 kb) and have a low copy number (∼50/cell), frequently resulting in low plasmid yields. And, finally, unlike bacteria, yeast are capable of replicating more than one plasmid at a time, making it difficult to identify the one containing the relevant insert. Thus, multiple steps are necessary to isolate the single insert-containing plasmid responsible for the interaction and activation and then to prepare it for analysis.
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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".