Pex30p, Pex31p, and Pex32p Form a Family of Peroxisomal Integral Membrane Proteins Regulating Peroxisome Size and Number in<i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
The peroxin Pex23p of the yeast Yarrowia lipolytica exhibits high sequence similarity to the hypothetical proteins Ylr324p, Ygr004p, and Ybr168p encoded by the Saccharomyces cerevisiae genome. Ylr324p, Ygr004p, and Ybr168p are integral to the peroxisomal membrane and act to control peroxisome number and size. Synthesis of Ylr324p and Ybr168p, but not of Ygr004p, is induced during incubation of cells in oleic acid-containing medium, the metabolism of which requires intact peroxisomes. Cells deleted for YLR324w exhibit increased numbers of peroxisomes, whereas cells deleted for YGR004w or YBR168w exhibit enlarged peroxisomes. Ylr324p and Ybr168p cannot functionally substitute for one another or for Ygr004p, whereas Ygr004p shows partial functional redundancy with Ylr324p and Ybr168p. Ylr324p, Ygr004p, and Ybr168p interact within themselves and with Pex28p and Pex29p, which have been shown also to regulate peroxisome size and number. Systematic deletion of genes demonstrated that PEX28 and PEX29 function upstream of YLR324w, YGR004w, and YBR168w in the regulation of peroxisome proliferation. Our data suggest a role for Ylr324p, Ygr004p, and Ybr168p--now designated Pex30p, Pex31p, and Pex32p, respectively--together with Pex28p and Pex29p in controlling peroxisome size and proliferation in Saccharomyces cerevisiae.
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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) | 0.001 | 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".