Dihydroxyacetone Phosphate Acyltransferase is a Peripheral Membrane Protein
Bibliographic record
Abstract
Dihydroxyacetone phosphate acyltransferase(DHAPAT) catalyzes the initial acylation step in the synthesis of ether basedphospholipids in peroxisomes. DHAPAT adds an acyl group to dihydroxyacetonephosphate, a metabolic intermediate from glycolysis, to yield 1‐acyl‐dihydroxyacetonephosphate (1‐acyl‐DHAP). Ether lipids are abundant in the central nervoussystem and DHAPAT deficiency has been associated with many human disordersincluding cataracts and blindness. We will present results from studies using the tractable model organism Xenopuslaevis that also point to a role of DHAPAT in eye development. Analysis of DHAPAT expression by in situ hybridization indicated it is expressed in the lens epithelium and in the proliferative region of the ciliary marginal zone. Given its relevance and how little is known about DHAPAT, we have initiated biochemical studies aimed at fully characterizing this enzyme in terms of structure, function and regulation. Using a yeast heterologous expression system we have been able to overproduce functional X. laevis DHAPAT. A first purification scheme comprised of subcellular fractionation, protein solubilization with different detergents and ionic strength conditions followed by Ni‐NTA affinity chromatography has been developed. Our studies indicate that X laevis DHAPAT is a peripheral membrane protein that can associate‐dissociate from membranes. We are currently exploiting this novel feature for this kind of acyltransferases in order to setup the conditions to improve its purification with the goal of initiating structural studies. Support or Funding Information This work was supported by operating grants from the Natural Sciences and Engineering Research Council of Canada to SM and VZ.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".