The lysophosphatidic acid acyltransferases (acylglycerophosphate acyltransferases) family: one reaction, five enzymes, many roles
Bibliographic record
Abstract
PURPOSE OF REVIEW: Lysophosphatidic acid acyltransferases (LPAATs)/acylglycerophosphate acyltransferases (AGPATs) are a homologous group of enzymes that all catalyze the de novo formation of phosphatidic acid from lysophosphatidic acid (LPA) and a fatty acyl-CoA. This review seeks to resolve the apparent redundancy of LPAATs through examination of recent literature. RECENT FINDINGS: Recent molecular studies suggest that individual LPAAT homologues produce functionally distinct pools of phosphatidic acid, whereas gene ablation studies demonstrate unique roles despite a similar biochemical function. Loss of the individual enzymes not only causes diverse effects on down-stream lipid metabolism, which can vary even for a single enzyme from one tissue to the next, but also results in a wide array of physiological consequences, ranging from cognitive impairment, to lipodystrophy, to embryonic lethality. SUMMARY: LPAATs are critical mediators of cell membrane phospholipid synthesis, regulating the production of specific down-stream glycerophospholipid species through generation of distinct pools of phosphatidic acid that feed into dedicated biosynthetic pathways. Loss of any specific LPAAT can lead to alterations in cellular and organellar membrane phospholipid composition that can vary for a single enzyme in different tissues, with unique pathophysiological implications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".