ECERIFERUM2-LIKE Proteins Have Unique Biochemical and Physiological Functions in Very-Long-Chain Fatty Acid Elongation
Bibliographic record
Abstract
The extension of very-long-chain fatty acids (VLCFAs) for the synthesis of specialized apoplastic lipids requires unique biochemical machinery. Condensing enzymes catalyze the first reaction in fatty acid elongation and determine the chain length of fatty acids accepted and produced by the fatty acid elongation complex. Although necessary for the elongation of all VLCFAs, known condensing enzymes cannot efficiently synthesize VLCFAs longer than 28 carbons, despite the prevalence of C28 to C34 acyl lipids in cuticular wax and the pollen coat. The eceriferum2 (cer2) mutant of Arabidopsis (Arabidopsis thaliana) was previously shown to have a specific deficiency in cuticular waxes longer than 28 carbons, and heterologous expression of CER2 in yeast (Saccharomyces cerevisiae) demonstrated that it can modify the acyl chain length produced by a condensing enzyme from 28 to 30 carbon atoms. Here, we report the physiological functions and biochemical specificities of the CER2 homologs CER2-LIKE1 and CER2-LIKE2 by mutant analysis and heterologous expression in yeast. We demonstrate that all three CER2-LIKEs function with the same small subset of condensing enzymes, and that they have different effects on the substrate specificity of the same condensing enzyme. Finally, we show that the changes in acyl chain length caused by each CER2-LIKE protein are of substantial importance for cuticle formation and pollen coat function.
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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 | 0.001 |
| Research integrity | 0.001 | 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".