Species-specific protein–protein interactions govern the humanization of the 20S proteasome in yeast
Bibliographic record
Abstract
Yeast and humans share thousands of genes despite a billion years of evolutionary divergence. While many human genes can functionally replace their yeast counterparts, nearly half of the tested shared genes cannot. For example, most yeast proteasome subunits are "humanizable," except subunits comprising the β-ring core, including β2c (HsPSMB7, a constitutive proteasome subunit). We developed a high-throughput pipeline to humanize yeast proteasomes by generating a large library of Hsβ2c mutants and screening them for complementation of a yeast β2 (ScPup1) knockout. Variants capable of replacing ScPup1 included (1) those impacting local protein-protein interactions (PPIs), with most affecting interactions between the β2c C-terminal tail and the adjacent β3 subunit, and (2) those affecting β2c proteolytic activity. Exchanging the full-length tail of human β2c with that of ScPup1 enabled complementation. Moreover, wild-type human β2c could replace yeast β2 if human β3 was also provided. Unexpectedly, yeast proteasomes bearing a catalytically inactive HsPSMB7-T44A variant that blocked precursor autoprocessing were viable, suggesting an intact propeptide stabilizes late assembly intermediates. In contrast, similar modifications in human β2i (HsPSMB10), an immunoproteasome subunit and the co-ortholog of yeast β2, do not enable complementation in yeast, suggesting distinct interactions are involved in human immunoproteasome core assembly. Broadly, our data reveal roles for specific PPIs governing functional replaceability across vast evolutionary distances.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".