Sequential Regulation of Diacylglycerol Acyltransferase 2 Expression by CAAT/Enhancer-binding Protein β (C/EBPβ) and C/EBPα during Adipogenesis
Bibliographic record
Abstract
Diacylglycerol acyltransferase 2 (DGAT2) catalyzes the final step of triacylglycerol (TG) synthesis. Despite the existence of an alternative acyltransferase (DGAT1), mice lacking DGAT2 have a severe deficiency of TG in adipose tissue, indicating a nonredundant role for this enzyme in adipocyte TG synthesis. We have studied the regulation of DGAT2 expression during adipogenesis. In both isolated murine preadipocytes and 3T3-L1 cells the temporal pattern of DGAT2 expression closely mimicked that of genes whose expression is regulated by CAAT/enhancer-binding protein beta (C/EBPbeta). Inhibition of C/EBPbeta expression in differentiating preadipocytes reduced DGAT2 expression, and electrophoretic mobility shift assay and chromatin immunoprecipitation experiments identified a promoter element in the DGAT2 gene that is likely to mediate this effect. The importance of C/EBPbeta in adipocyte expression of DGAT2 was confirmed by the finding of reduced DGAT2 expression in the adipose tissue of C/EBPbeta-null animals. However, DGAT2 expression is maintained at high levels during the later stages of adipogenesis, when C/EBPbeta levels decline. We show that, at these later stages of differentiation, C/EBPalpha is capable of substituting for C/EBPbeta at the same promoter element. These observations provide novel insight into the transcriptional regulation of DGAT2 expression. Moreover, they further refine the complex and serial roles of the C/EBP family of transcription factors in inducing and maintaining the metabolic properties of mature adipocytes.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".