High-Efficiency Transformation of Plasmid DNA into Yeast
Bibliographic record
Abstract
The yeast two-hybrid system was first introduced by Fields and Song () in 1989. They showed that plasmids expressing the GAL4 BD-SNF1 and GAL4 AD-SNF4 fusion proteins activated a GALl-lacZ reporter gene. The first application of the system involved cotransformation of two plasmids into the strain GGY1:: 171—one plasmid containing the GAL4 BD fused to sequences from the 3′ end of SIR4 and the other containing GAL4 AD fused to fragments of yeast genomic DNA (). The cotransformation was accomplished by the newly reported high-efficiency lithium acetate/single-stranded carrier DNA/polyethylene glycol (LiAc/ssDNA/PEG) protocol () to generate 220,000 transformants and identified two positive clones. The efficiency of this transformation protocol was 2×104 transformants/(g of plasmid·108 cells) (), and the frequency of cotransformation was shown to range from 30 to 40% (). Screening a mam-malian cDNA library by the yeast two-hybrid system requires a large number of transformants. For example, the detection of proteins that interacted with huntingtin, the Huntington disease protein, involved a screen of 4×107 transformants from an adult human brain cDNA library (). We have reported several modifications and improvements to the LiAc/ssDNA/PEG protocol so that it can easily generate the numbers of transformants required for such screens.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
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".