Roles of Acyl-CoA:Diacylglycerol Acyltransferases 1 and 2 in Triacylglycerol Synthesis and Secretion in Primary Hepatocytes
Bibliographic record
Abstract
OBJECTIVE: Very low-density lipoprotein assembly and secretion are regulated by the availability of triacylglycerol. Although compelling evidence indicates that the majority of triacylglycerol in very low-density lipoprotein is derived from re-esterification of lipolytic products released by endoplasmic reticulum-associated lipases, little is known about roles of acyl-CoA:diacylglycerol acyltransferases (DGATs) in this process. We aimed to investigate the contribution of DGAT1 and DGAT2 in lipid metabolism and lipoprotein secretion in primary mouse and human hepatocytes. APPROACH AND RESULTS: We used highly selective small-molecule inhibitors of DGAT1 and DGAT2, and we tracked storage and secretion of lipids synthesized de novo from [(3)H]acetic acid and from exogenously supplied [(3)H]oleic acid. Inactivation of individual DGAT activity did not affect incorporation of either radiolabeled precursor into intracellular triacylglycerol, whereas combined inactivation of both DGATs severely attenuated triacylglycerol synthesis. However, inhibition of DGAT2 augmented fatty acid oxidation, whereas inhibition of DGAT1 increased triacylglycerol secretion, suggesting preferential channeling of separate DGAT-derived triacylglycerol pools to distinct metabolic pathways. Inactivation of DGAT2 impaired cytosolic lipid droplet expansion, whereas DGAT1 inactivation promoted large lipid droplet formation. Moreover, inactivation of DGAT2 attenuated expression of lipogenic genes. Finally, triacylglycerol secretion was significantly reduced on DGAT2 inhibition without altering extracellular apolipoprotein B levels. CONCLUSIONS: Our data suggest that DGAT1 and DGAT2 can compensate for each other to synthesize triacylglycerol, but triacylglycerol synthesized by DGAT1 is preferentially channeled to oxidation, whereas DGAT2 synthesizes triacylglycerol destined for very low-density lipoprotein assembly.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 0.000 |
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 teacher head, 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".