Plakoglobin regulates adipocyte differentiation independently of the Wnt/β-catenin signaling pathway
Bibliographic record
Abstract
The scaffold protein 14-3-3ζ is an established regulator of adipogenesis and postnatal adiposity. We and others have demonstrated the 14-3-3ζ interactome to be diverse and dynamic, and it can be examined to identify novel regulators of physiological processes, including adipogenesis. In the present study, we sought to determine if factors that influence adipogenesis during the development of obesity could be identified in the 14-3-3ζ interactome found in white adipose tissue of lean or obese TAP-tagged-14-3-3ζ overexpressing mice. Using mass spectrometry, differences in the abundance of novel, as well as established, adipogenic factors within the 14-3-3ζ interactome could be detected in adipose tissues. One novel candidate was revealed to be plakoglobin, the homolog of the known adipogenic inhibitor, β-catenin, and herein, we report that plakoglobin is involved in adipocyte differentiation. Plakoglobin is expressed in murine 3T3-L1 cells and is primarily localized to the nucleus, where its abundance decreases during adipogenesis. Depletion of plakoglobin by siRNA inhibited adipogenesis and reduced PPARγ2 expression, and similarly, plakoglobin depletion in human adipose-derived stem cells also impaired adipogenesis and reduced lipid accumulation post-differentiation. Transcriptional assays indicated that plakoglobin does not participate in Wnt/β-catenin signaling, as its depletion did not affect Wnt3a-mediated transcriptional activity. Taken together, our results establish plakoglobin as a novel regulator of adipogenesis in vitro and highlights the ability of using the 14-3-3ζ interactome to identify potential pro-obesogenic factors.
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 | 0.001 |
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".