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Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks

Title
Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks
Authors
Park, JM[Park, Jong-Moon]Park, JH[Park, Ji-Hwan]Mun, DG[Mun, Dong-Gi]Bae, J[Bae, Jingi]Jung, JH[Jung, Jae Hun]Back, S[Back, Seunghoon]Lee, H[Lee, Hangyeore]Kim, H[Kim, Hokeun]Jung, HJ[Jung, Hee-Jung]Kim, HK[Kim, Hark Kyun]Lee, H[Lee, Hookeun]Kim, KP[Kim, Kwang Pyo]Hwang, D[Hwang, Daehee]Lee, SW[Lee, Sang-Won]
DGIST Authors
Jung, HJ[Jung, Hee-Jung]; Hwang, D[Hwang, Daehee]
Issue Date
2015-12-11
Citation
Scientific Reports, 5
Type
Article
Article Type
Article
ISSN
2045-2322
Abstract
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.
URI
http://hdl.handle.net/20.500.11750/2798
DOI
10.1038/srep18189
Publisher
Nature Publishing Group
Related Researcher
  • Author Hwang, Dae Hee Systems Biology and Medicine Lab
  • Research Interests Multilayered spatiotemporal networks; Regulatory motifs or pathways; Metabolite-protein networks; Network stochasticity; Proteomics and informatics
Files:
There are no files associated with this item.
Collection:
New BiologyETC1. Journal Articles


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