Dissecting the Contingent Interactions of Protein Complexes with the Optimized Yeast Cytosine Deaminase Protein-Fragment Complementation Assay
Bibliographic record
Abstract
Here, we present a detailed protocol for studying in yeast cells the contingent interaction between a substrate and its multisubunit enzyme complex by using a death selection technique known as the optimized yeast cytosine deaminase protein-fragment complementation assay (OyCD PCA). In yeast, the enzyme cytosine deaminase (encoded by FCY1) is involved in pyrimidine metabolism. The PCA is based on an engineered form of yeast cytosine deaminase optimized by directed evolution for maximum activity (OyCD), which acts as a reporter converting the pro-drug 5-fluorocytosine (5-FC) to 5-fluorouracil (5-FU), a toxic compound that kills the cell. Cells that have OyCD PCA activity convert 5-FC to 5-FU and die. Using this assay, it is possible to assess how regulatory subunits of an enzyme contribute to the overall interaction between the catalytic subunit and the potential substrates. Furthermore, OyCD PCA can be used to dissect different functions of mutant forms of a protein as a mutant can disrupt interaction with one partner, while retaining interaction with others. As it is scalable to a medium- or high-throughput format, OyCD PCA can be used to study hundreds to thousands of pairwise protein-protein interactions in different deletion strains. In addition, OyCD PCA vectors (pAG413GAL1-ccdB-OyCD-F[1] and pAG415GAL1-ccdB-OyCD-F[2]) have been designed to be compatible with the proprietary Gateway technology. It is therefore easy to generate fusion genes with the OyCD reporter fragments. As an example, we will focus on the yeast cyclin-dependent protein kinase 1 (Cdk1, encoded by CDC28), its regulatory cyclin subunits, and its substrates or binding partners.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".