Plant <i>sn</i>‐Glycerol‐3‐Phosphate Acyltransferases: Biocatalysts Involved in the Biosynthesis of Intracellular and Extracellular Lipids
Bibliographic record
Abstract
Acyl-lipids such as intracellular phospholipids, galactolipids, sphingolipids, and surface lipids play a crucial role in plant cells by serving as major components of cellular membranes, seed storage oils, and extracellular lipids such as cutin and suberin. Plant lipids are also widely used to make food, renewable biomaterials, and fuels. As such, enormous efforts have been made to uncover the specific roles of different genes and enzymes involved in lipid biosynthetic pathways over the last few decades. sn-Glycerol-3-phosphate acyltransferases (GPAT) are a group of important enzymes catalyzing the acylation of sn-glycerol-3-phosphate at the sn-1 or sn-2 position to produce lysophosphatidic acids. This reaction constitutes the first step of storage-lipid assembly and is also important in polar- and extracellular-lipid biosynthesis. Ten GPAT have been identified in Arabidopsis, and many homologs have also been reported in other plant species. These enzymes differentially localize to plastids, mitochondria, and the endoplasmic reticulum, where they have different biological functions, resulting in distinct metabolic fate(s) for lysophosphatidic acid. Although studies in recent years have led to new discoveries about plant GPAT, many gaps still exist in our understanding of this group of enzymes. In this article, we highlight current biochemical and molecular knowledge regarding plant GPAT, and also discuss deficiencies in our understanding of their functions in the context of plant acyl-lipid biosynthesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".