Arabidopsis <i>CER8</i> encodes LONG‐CHAIN ACYL‐COA SYNTHETASE 1 (LACS1) that has overlapping functions with LACS2 in plant wax and cutin synthesis
Bibliographic record
Abstract
Plant cuticle is an extracellular lipid-based matrix of cutin and waxes, which covers aerial organs and protects them from many forms of environmental stress. We report here the characterization of CER8/LACS1, one of nine Arabidopsis long-chain acyl-CoA synthetases thought to activate acyl chains. Mutations in LACS1 reduced the amount of wax in all chemical classes on the stem and leaf, except in the very long-chain fatty acid (VLCFA) class wherein acids longer than 24 carbons (C(24)) were elevated more than 155%. The C(16) cutin monomers on lacs1 were reduced by 37% and 22%, whereas the C(18) monomers were increased by 28% and 20% on stem and leaf, respectively. Amounts of wax and cutin on a lacs1-1 lacs2-3 double mutant were much lower than on either parent, and lacs1-1 lacs2-3 had much higher cuticular permeability than either parent. These additive effects indicate that LACS1 and LACS2 have overlapping functions in both wax and cutin synthesis. We demonstrated that LACS1 has synthetase activity for VLCFAs C(20)-C(30), with highest activity for C(30) acids. LACS1 thus appears to function as a very long-chain acyl-CoA synthetase in wax metabolism. Since C(16) but not C(18) cutin monomers are reduced in lacs1, and C(16) acids are the next most preferred acid (behind C(30)) by LACS1 in our assays, LACS1 also appears to be important for the incorporation of C(16) monomers into cutin polyester. As such, LACS1 defines a functionally novel acyl-CoA synthetase that preferentially modifies both VLCFAs for wax synthesis and long-chain (C(16)) fatty acids for cutin synthesis.
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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) | 0.001 | 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".