The α/β Hydrolase CGI-58 and Peroxisomal Transport Protein PXA1 Coregulate Lipid Homeostasis and Signaling in <i>Arabidopsis</i>
Bibliographic record
Abstract
COMPARATIVE GENE IDENTIFICATION-58 (CGI-58) is a key regulator of lipid metabolism and signaling in mammals, but its underlying mechanisms are unclear. Disruption of CGI-58 in either mammals or plants results in a significant increase in triacylglycerol (TAG), suggesting that CGI-58 activity is evolutionarily conserved. However, plants lack proteins that are important for CGI-58 activity in mammals. Here, we demonstrate that CGI-58 functions by interacting with the PEROXISOMAL ABC-TRANSPORTER1 (PXA1), a protein that transports a variety of substrates into peroxisomes for their subsequent metabolism by β-oxidation, including fatty acids and lipophilic hormone precursors of the jasmonate and auxin biosynthetic pathways. We also show that mutant cgi-58 plants display changes in jasmonate biosynthesis, auxin signaling, and lipid metabolism consistent with reduced PXA1 activity in planta and that, based on the double mutant cgi-58 pxa1, PXA1 is epistatic to CGI-58 in all of these processes. However, CGI-58 was not required for the PXA1-dependent breakdown of TAG in germinated seeds. Collectively, the results reveal that CGI-58 positively regulates many aspects of PXA1 activity in plants and that these two proteins function to coregulate lipid metabolism and signaling, particularly in nonseed vegetative tissues. Similarities and differences of CGI-58 activity in plants versus animals are discussed.
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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 | 0.001 |
| Research integrity | 0.000 | 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".