Arabidopsis ECERIFERUM2 Is a Component of the Fatty Acid Elongation Machinery Required for Fatty Acid Extension to Exceptional Lengths
Bibliographic record
Abstract
Primary aerial surfaces of land plants are coated by a lipidic cuticle, which forms a barrier against transpirational water loss and protects the plant from diverse stresses. Four enzymes of a fatty acid elongase complex are required for the synthesis of very-long-chain fatty acid (VLCFA) precursors of cuticular waxes. Fatty acid elongase substrate specificity is determined by a condensing enzyme that catalyzes the first reaction carried out by the complex. In Arabidopsis (Arabidopsis thaliana), characterized condensing enzymes involved in wax synthesis can only elongate VLCFAs up to 28 carbons (C28) in length, despite the predominance of C29 to C31 monomers in Arabidopsis stem wax. This suggests additional proteins are required for elongation beyond C28. The wax-deficient mutant eceriferum2 (cer2) lacks waxes longer than C28, implying that CER2, a putative BAHD acyltransferase, is required for C28 elongation. Here, we characterize the cer2 mutant and demonstrate that green fluorescent protein-tagged CER2 localizes to the endoplasmic reticulum, the site of VLCFA biosynthesis. We use site-directed mutagenesis to show that the classification of CER2 as a BAHD acyltransferase based on sequence homology does not fit with CER2 catalytic activity. Finally, we provide evidence for the function of CER2 in C28 elongation by an assay in yeast (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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".