Design of a Single Plasmid-Based Modified Yeast One-Hybrid System for Investigation of in Vivo Protein-Protein and Protein-DNA Interactions
Bibliographic record
Abstract
We have developed a modified yeast one-hybrid system (MY1H) useful for in vivo investigation of protein-protein and protein-DNA interactions. Our single-plasmid expression system is capable of differential protein expression levels; in addition to a GAL4 activation domain (AD) fusion protein, a second protein can be coexpressed at either comparable or higher transcriptional levels from expression vectors pCETT or pCETF, respectively. This second protein can play a structural, modifying, or inhibitory role that restores or blocks reporter gene expression. Our MY1H was validated by use of the well-characterized DNA-binding protein p53 and its inhibitory partners, large T antigen (LTAg) and 53BP2. By coexpressing LTAg or 53BP2 at comparable or higher levels than the GAL4AD-p53 fusion in the MY1H, we show that DNA binding of p53 decreases by different, measurable extents dependent on the expression level of inhibitory partner. As with the traditional Y1H, our system could also be used to investigate proteins that provide coactivational or bridging functions and to identify novel protein- or DNA-binding partners through library screening. Our MY1H provides a system for investigation of simultaneous protein-protein and protein-DNA interactions, and thus is a useful addition to current methods for in vivo investigation of such interactions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".