Diacylglycerol Acyltransferase-2 (DGAT2) and Monoacylglycerol Acyltransferase-2 (MGAT2) Interact to Promote Triacylglycerol Synthesis
Bibliographic record
Abstract
Acyl CoA:1,2-diacylglycerol acyltransferase (DGAT)-2 is an integral membrane protein that catalyzes triacylglycerol (TG) synthesis using diacylglycerol and fatty acyl CoA as substrates. DGAT2 resides in the endoplasmic reticulum (ER), but when cells are incubated with fatty acids, DGAT2 interacts with lipid droplets presumably to catalyze localized TG synthesis for lipid droplet expansion. Previous studies have shown that DGAT2 interacts with proteins that synthesize its fatty acyl CoA substrates. In this study, we provide additional evidence that DGAT2 is present in a protein complex. Using a chemical cross-linker, disuccinimidyl suberate (DSS), we demonstrated that DGAT2 formed a dimer and was also part of a protein complex of ∼ 650 kDa, both in membranes and on lipid droplets. Using co-immunoprecipitation experiments and an in situ proximity ligation assay, we found that DGAT2 interacted with monoacylglycerol acyltransferase (MGAT)-2, an enzyme that catalyzes the synthesis of diacylglycerol. Deletion mutagenesis showed that the interaction with MGAT2 was dependent on the two transmembrane domains of DGAT2. No significant interaction of DGAT2 with lipin1, another enzyme that synthesizes diacylglycerol, could be detected. When co-expressed in cells, DGAT2 and MGAT2 co-localized in the ER and on lipid droplets. Co-expression also resulted in increased TG storage compared with expression of DGAT2 or MGAT2 alone. Incubating McArdle rat hepatoma RH7777 cells with 2-monoacylglycerol caused DGAT2 to translocate to lipid droplets. This also led to the formation of large cytosolic lipid droplets, characteristic of DGAT2, but not DGAT1, and indicated that DGAT2 can utilize monoacylglycerol-derived diacylglycerol. These findings suggest that the interaction of DGAT2 and MGAT2 serves to channel lipid substrates efficiently for TG biosynthesis.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".