Park Jong-Moon, Park Ji-Hwan, Mun Dong-Gi, Bae Jingi, Jung Jae Hun, Back Seunghoon, Lee Hangyeore, Kim Hokeun, Jung Hee-Jung, Kim Hark Kyun, Lee Hookeun, Kim Kwang Pyo, Hwang Daehee, Lee Sang-Won
Department of Pharmaceutics, College of Pharmacy, Gachon University, Incheon 406-799, Republic of Korea.
Department of Chemical Engineering, POSTECH, Pohang 790-784, Republic of Korea.
Sci Rep. 2015 Dec 11;5:18189. doi: 10.1038/srep18189.
Multi-dimensional proteomic analyses provide different layers of protein information, including protein abundance and post-translational modifications. Here, we report an integrated analysis of protein expression, phosphorylation, and N-glycosylation by serial enrichments of phosphorylation and N-glycosylation (SEPG) from the same tissue samples. On average, the SEPG identified 142,106 unmodified peptides of 8,625 protein groups, 18,846 phosphopeptides (15,647 phosphosites), and 4,019 N-glycopeptides (2,634 N-glycosites) in tumor and adjacent normal tissues from three gastric cancer patients. The combined analysis of these data showed that the integrated analysis additively improved the coverages of gastric cancer-related protein networks; phosphoproteome and N-glycoproteome captured predominantly low abundant signal proteins, and membranous or secreted proteins, respectively, while global proteome provided abundances for general population of the proteome. Therefore, our results demonstrate that the SEPG can serve as an effective approach for multi-dimensional proteome analyses, and the holistic profiles of protein expression and PTMs enabled improved interpretation of disease-related networks by providing complementary information.
多维蛋白质组学分析可提供不同层面的蛋白质信息,包括蛋白质丰度和翻译后修饰。在此,我们报告了一种通过对来自同一组织样本的磷酸化和N-糖基化进行连续富集(SEPG)来综合分析蛋白质表达、磷酸化和N-糖基化的方法。平均而言,SEPG在三名胃癌患者的肿瘤组织和相邻正常组织中鉴定出8625个蛋白质组的142,106条未修饰肽段、18,846条磷酸化肽段(15,647个磷酸化位点)以及4019条N-糖基化肽段(2634个N-糖基化位点)。对这些数据的综合分析表明,这种整合分析累加性地提高了胃癌相关蛋白质网络的覆盖范围;磷酸蛋白质组和N-糖蛋白质组分别主要捕获低丰度信号蛋白以及膜蛋白或分泌蛋白,而整体蛋白质组则提供了蛋白质组总体的丰度信息。因此,我们的结果表明,SEPG可作为多维蛋白质组分析的有效方法,并且蛋白质表达和翻译后修饰的整体概况通过提供互补信息,有助于更好地解读疾病相关网络。