Kalkhof Stefan, Büttner Petra, Krieg Laura, Wabitsch Martin, Küntzel Carolin, Friebe Daniela, Landgraf Kathrin, Hanschkow Martha, Schubert Kristin, Kiess Wieland, Krohn Knut, Blüher Matthias, von Bergen Martin, Körner Antje
Department of Molecular Systems Biology, UFZ, Helmholtz-Centre for Environmental Research, Leipzig, 04159, Germany.
Institute of Bioanalysis, University of Applied Sciences and Arts of Coburg, Coburg, 96450, Germany.
Proteomics. 2020 Aug;20(15-16):e1900405. doi: 10.1002/pmic.201900405.
Most information on molecular processes accompanying and driving adipocyte differentiation are derived from rodent models. Here, a comprehensive analysis of combined transcriptomic and proteomic alterations during adipocyte differentiation in Simpson-Golabi-Behmel Syndrome (SGBS) cells is provided. The SGBS cells are a well-established and the most widely applied cell model to study human adipocyte differentiation and cell biology. However, the molecular alterations during human adipocyte differentiation in SGBS cells have not yet been described in a combined analysis of proteome and transcriptome. Here a global proteomic and transcriptomic data set comprising relative quantification of a total of 14372 mRNA transcripts and 2641 intracellular and secreted proteins is presented. 1153 proteins and 313 genes are determined as differentially expressed between preadipocytes and the fully differentiated cells including adiponectin, lipoprotein lipase, fatty acid binding protein 4, fatty acid synthase, stearoyl-CoA desaturase, and apolipoprotein E and many other proteins from the fatty acid synthesis, amino acid synthesis as well as glucose and lipid metabolic pathways. Preadipocyte markers, such as latexin, GATA6, and CXCL6, are found to be significantly downregulated at the protein and transcript level. This multi-omics data set provides a deep molecular profile of adipogenesis and will support future studies to understand adipocyte function.
大多数关于伴随并驱动脂肪细胞分化的分子过程的信息都来自啮齿动物模型。在此，我们对辛普森-戈拉比-贝梅尔综合征（SGBS）细胞脂肪细胞分化过程中的转录组和蛋白质组联合变化进行了全面分析。SGBS细胞是一种成熟且应用最广泛的细胞模型，用于研究人类脂肪细胞分化和细胞生物学。然而，尚未在蛋白质组和转录组的联合分析中描述SGBS细胞中人类脂肪细胞分化过程中的分子变化。在此，我们展示了一个全局蛋白质组和转录组数据集，包括总共14372个mRNA转录本以及2641种细胞内和分泌蛋白的相对定量。确定了1153种蛋白质和313个基因在脂肪前体细胞和完全分化细胞之间差异表达，包括脂联素、脂蛋白脂肪酶、脂肪酸结合蛋白4、脂肪酸合酶、硬脂酰辅酶A去饱和酶和载脂蛋白E，以及许多来自脂肪酸合成、氨基酸合成以及葡萄糖和脂质代谢途径的其他蛋白质。发现脂肪前体细胞标志物，如乳清酸蛋白、GATA6和CXCL6，在蛋白质和转录水平上显著下调。这个多组学数据集提供了脂肪生成的深度分子图谱，并将支持未来理解脂肪细胞功能的研究。
