The yeast 2-μm plasmid Raf protein contributes to plasmid inheritance by stabilizing the Rep1 and Rep2 partitioning proteins
Bibliographic record
Abstract
The yeast 2-μm plasmid is a remarkable genetic parasite, managing efficient maintenance at high-copy number with minimal impact on the host. Equal partitioning of the plasmid upon host cell division requires plasmid proteins Rep1 and Rep2 and the plasmid STB locus. The Rep proteins and the plasmid-encoded Raf protein also regulate plasmid gene transcription. In this study, protein interaction assays, sequence analyses and mutational approaches were used to identify domains and residues in Rep2 and Raf required for association with Rep1 and Rep2 and to delineate the Rep2 DNA-binding domain. Rep2 and Raf displayed similarities in interactions with Rep1 and Rep2, in having Rep1 promote their STB association in vivo, and in stabilizing Rep protein levels. Rep2 mutants impaired for self-association were competent for transcriptional repression while those deficient for Rep1 association were not. Surprisingly, Rep2 mutants impaired for either Rep1 interaction or self-association were able to maintain efficient plasmid inheritance provided Raf was present and competent for Rep protein interaction. Our findings provide insight into the Rep protein complexes required for partitioning and transcriptional repression, and suggest that in addition to its transcriptional function, Raf stabilization of Rep partitioning proteins contributes to the remarkable persistence of the 2-μm plasmid.
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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 | 0.000 | 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) | 0.001 | 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".