Abstract 1828 Biochemical characterization of DHAPAT, the first enzyme in ether lipid biosynthesis
Bibliographic record
Abstract
Ether lipids are a type of glycerophospholipid with an alkyl tail attached to the sn-1 position of the glycerol backbone. They are found enriched in the central nervous system. Defects in ether lipid synthesis lead to severe human conditions including Zellweger syndrome and rhizomelic chrondrodysplasia punctata. The latter presents with congenital cataracts, skeletal and facial deformities, and childhood mortality. The first acylation step in the synthesis of ether lipids occurs in peroxisomes, and is catalyzed by the enzyme DiHydroxyAcetone Phosphate AcylTransferase (DHAPAT EC2.3.1.42). DHAPAT has a peroxisomal targeting signal type 1 (PTS1) at the carboxy-end and no predicted membrane domains or lipid binding motifs. We have devised a functional assay in yeast where full length DHAPAT was able to support life of a yeast devoid of endogenous acyltransferases (ΔAT yeast). This was dependent on DHAPAT activity and the presence of the residues encoded by the first three exons. Despite being expressed at similar levels as the wild type, a catalytically dead mutant or an amino-end truncated version failed to support life of ΔAT yeast. Furthermore, a version lacking exon 2 (V2) resulted in the inability to rescue life of ΔAT yeast. Where full length DHAPAT localizes to both peroxisomes and lipid droplets in yeast, V2 localizes exclusively to peroxisomes. Interestingly, putative amphipathic helices (AHs) were identified within the region encoded by exons 2 and 3. In this work, we show that the amino-end containing these AHs binds membranes rich in phosphatidic acid and is able to direct GFP localization to lipid droplets in yeast. Our results suggest the amino-end of DHAPAT mediates its interaction with membranes and modulates its targeting priority to peroxisomes, which could be assisted by lipid droplets. This work has been financially supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) grant to VZ and the Alberta Graduate Excellence Scholarship, and Graeme Bell and Norma Kay Sullivan-Bell Graduate Scholarship in Biology to VL.
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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 | 0.002 |
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".