Liver-enriched Inhibitory Protein (LIP) Actively Inhibits Preadipocyte Differentiation through Histone Deacetylase 1 (HDAC1)
Bibliographic record
Abstract
The CCAAT/enhancer-binding protein β (C/EBPβ) is expressed as three isoforms (LAP*, liver-enriched activating protein (LAP), and liver-enriched inhibitory protein (LIP)) that differentially regulate gene expression. The interplay between LAP*, LAP, and LIP in regulating cellular processes is largely unknown, and LIP has been largely regarded to repress transcription through a passive heterodimerization-dependent mechanism. Recently, we have shown that p300/GCN5 and mSin3A/HDAC1 differentially regulate the ability of C/EBPβ to stimulate preadipocyte differentiation through activation of C/ebpα transcription. Here, we have mapped requirements for binding of mSin3A/HDAC1 to LAP/LAP* and LIP to a 4-amino acid motif in the central region of LAP/LAP* (residues 153-156) and the N terminus of LIP. Reducing mSin3A/HDAC1 binding to LAP/LAP* and LIP through deletion of this motif reduced the recruitment of HDAC1 to the C/ebpα promoter and increased preadipocyte differentiation stimulated by insulin and 1-methyl-3-isobutylxanthine. Additional studies showed that the interaction of HDAC1 with LIP provides for active repression of C/ebpα transcription and is largely responsible for the ability of LIP and HDAC1 to repress preadipocyte differentiation. Thus, although mSin3A/HDAC1 interacted readily with LAP/LAP* in addition to LIP and that expression of LAP/LAP* was sufficient to recruit HDAC1 to the C/ebpα promoter, mutations in C/ebpβ that abrogated HDAC1 association to LAP/LAP* in the absence of LIP provided no additional stimulation of differentiation or transcription beyond the deletion of LIP alone. The implication of these results for the interaction between p300/GCN5 and mSin3A/HDAC1 in regulating C/EBPα transcription and preadipocyte differentiation are discussed.
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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) | 0.000 | 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) | 0.002 | 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".