Tang Xiaoyue, Li Juan, Zhao Wei-Gang, Sun Haidan, Guo Zhengguang, Jing Li, She Zhufang, Yuan Tao, Liu Shuai-Nan, Liu Quan, Fu Yong, Sun Wei
Core Facility of Instrument, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences/School of Basic Medicine, Peking Union Medical College, Beijing, China.
Department of Endocrinology, Key Laboratory of Endocrinology of Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.
PeerJ. 2019 Jul 25;7:e7352. doi: 10.7717/peerj.7352. eCollection 2019.
White adipose tissue (WAT) plays a significant role in energy metabolism and the obesity epidemic. In this study, we sought to (1) profile the mouse WAT proteome with advanced 2DLC/MS/MS approach, (2) provide insight into WAT function based on protein functional annotation, and (3) predict potentially secreted proteins. A label-free 2DLC/MS/MS proteomic approach was used to identify the WAT proteome from female mouse WAT. A total of 6,039 proteins in WAT were identified, among which 5,160 were quantified (spanning a magnitude of 10) using an intensity-based absolute quantification algorithm, and 3,117 proteins were reported by proteomics technology for the first time in WAT. To comprehensively analyze the function of WAT, the proteins were divided into three quantiles based on abundance and we found that proteins of different abundance performed different functions. High-abundance proteins (the top 90%, 1,219 proteins) were involved in energy metabolism; middle-abundance proteins (90-99%, 2,273 proteins) were involved in the regulation of protein synthesis; and low-abundance proteins (99-100%, 1,668 proteins) were associated with lipid metabolism and WAT beiging. Furthermore, 800 proteins were predicted by SignalP4.0 to have signal peptides, 265 proteins had never been reported, and five have been reported as adipokines. The above results provide a large dataset of the normal mouse WAT proteome, which might be useful for WAT function research.
白色脂肪组织(WAT)在能量代谢和肥胖流行中起着重要作用。在本研究中,我们旨在:(1)采用先进的二维液相色谱/串联质谱法(2DLC/MS/MS)分析小鼠WAT蛋白质组;(2)基于蛋白质功能注释深入了解WAT功能;(3)预测潜在的分泌蛋白。我们使用无标记的二维液相色谱/串联质谱蛋白质组学方法从小鼠雌性WAT中鉴定蛋白质组。共鉴定出WAT中的6039种蛋白质,其中5160种使用基于强度的绝对定量算法进行了定量分析(跨越10个数量级),并且有3117种蛋白质是蛋白质组学技术首次在WAT中报道。为了全面分析WAT的功能,根据丰度将蛋白质分为三个分位数,我们发现不同丰度的蛋白质具有不同的功能。高丰度蛋白质(前90%,共1219种蛋白质)参与能量代谢;中等丰度蛋白质(90%-99%,共2273种蛋白质)参与蛋白质合成的调节;低丰度蛋白质(99%-100%,共1668种蛋白质)与脂质代谢和WAT米色化有关。此外,通过SignalP4.0预测有800种蛋白质具有信号肽,其中265种蛋白质从未被报道过,还有5种已被报道为脂肪因子。上述结果提供了正常小鼠WAT蛋白质组的大量数据集,这可能对WAT功能研究有用。