Protein interactomes for plant lipid biosynthesis and their biotechnological applications
Bibliographic record
Abstract
Plant lipids have essential biological roles in plant development and stress responses through their functions in cell membrane formation, energy storage and signalling. Vegetable oil, which is composed mainly of the storage lipid triacylglycerol, also has important applications in food, biofuel and oleochemical industries. Lipid biosynthesis occurs in multiple subcellular compartments and involves the coordinated action of various pathways. Although biochemical and molecular biology research over the last few decades has identified many proteins associated with lipid metabolism, our current understanding of the dynamic protein interactomes involved in lipid biosynthesis, modification and channelling is limited. This review examines advances in the identification and characterization of protein interactomes involved in plant lipid biosynthesis, with a focus on protein complexes consisting of different subunits for sequential reactions such as those in fatty acid biosynthesis and modification, as well as transient or dynamic interactomes formed from enzymes in cooperative pathways such as assemblies of membrane-bound enzymes for triacylglycerol biosynthesis. We also showcase a selection of representative protein interactome structures predicted using AlphaFold2, and discuss current and prospective strategies involving the use of interactome knowledge in plant lipid biotechnology. Finally, unresolved questions in this research area and possible approaches to address them are also discussed.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".