Identification of Phf16 and Pnpla3 as new adipogenic factors regulated by phytochemicals.
Seo-Hyuk ChangUi Jeong YunJin Hee ChoiSuji KimA Reum LeeDong Ho LeeMin-Ju SeoVanja PanicClaudio J VillanuevaNo-Joon SongKye Won ParkPublished in: Journal of cellular biochemistry (2018)
Adipocyte differentiation is controlled by multiple signaling pathways. To identify new adipogenic factors, C3H10T1/2 adipocytes were treated with previously known antiadipogenic phytochemicals (resveratrol, butein, sulfuretin, and fisetin) for 24 hours. Commonly regulated genes were then identified by transcriptional profiling analysis. Three genes (chemokine (C-X-C motif) ligand 1 [ Cxcl1], heme oxygenase 1 [ Hmox1], and PHD (plant homeo domain) finger protein 16 [ Phf16]) were upregulated while two genes (G0/G1 switch gene 2 [ G0s2] and patatin-like phospholipase domain containing 3 [ Pnpla3]) were downregulated by these four antiadipogenic compounds. Tissue expression profiles showed that the G0s2 and Pnpla3 expressions were highly specific to adipose depots while the other three induced genes were ubiquitously expressed with significantly higher expression in adipose tissues. While Cxcl1 expression was decreased, expressions of the other four genes were significantly increased during adipogenic differentiation of C3H10T1/2 cells. Small interfering RNA-mediated knockdown including Phf16 and Pnpla3 indicated that these genes might play regulatory roles in lipid accumulation and adipocyte differentiation. Specifically, the silencing of two newly identified adipogenic genes, Phf16 or Pnpla3, suppressed lipid accumulation and expression of adipocyte markers in both 3T3-L1 and C3H10T1/2 cells. Taken together, these data showed previously uncovered roles of Phf16 and Pnpla3 in adipogenesis, highlighting the potential of using phytochemicals for further investigation of adipocyte biology.
Keyphrases
- genome wide
- adipose tissue
- bioinformatics analysis
- genome wide identification
- insulin resistance
- poor prognosis
- transcription factor
- genome wide analysis
- gene expression
- fatty acid
- signaling pathway
- skeletal muscle
- single cell
- machine learning
- metabolic syndrome
- endoplasmic reticulum stress
- induced apoptosis
- protein protein