MassIVE MSV000088088

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Simultaneously Identifying and Distinguishing Glycoproteins with O-GlcNAc and the Tn Antigen in Human Cancer Cells

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Description

Proteins modified with O-GlcNAc and O-GalNAc (the Tn antigen) play critically important roles in many physiological and pathological processes. Comprehensive and site-specific analysis of proteins modified with O-GlcNAc and the Tn antigen advances our understanding of glycoprotein functions and cellular activities. However, it is extraordinarily challenging to distinguish them because of the same chemical composition (identical molecular weights) and being localized on the same amino acid residues (S/T). Here, an effective method is developed through the integration of metabolic labeling, chemical and enzymatic reactions, and MS-based proteomics to simultaneously identify and distinguish glycoproteins modified with O-GlcNAc and the Tn antigen. In biologically duplicate experiments, 537 O-GlcNAcylated proteins and 103 glycoproteins modified with the Tn antigen were identified site-specifically in human cancer cells. Among O-GlcNAcylated proteins only in Jurkat cells, those involved in HTLV-1 infection were highly enriched, indicating that O-GlcNAcylation may play a role in regulating cellular response to the retrovirus. Glycoproteins in the spliceosome and with the nuclear localization signal (NLS) are also overrepresented. However, the O-GlcNAcylated proteins identified in all three cell lines were highly enriched with transcription and RNA binding functions. For glycoproteins with the Tn antigen, while many of them in Jurkat cells were highly enriched in the extracellular exosome, those in MCF7 and K562 cells were extensively found in the ER. The current method enables us to simultaneously analyze and unambiguously distinguish glycoproteins with O-GlcNAc and the Tn antigen, and it can be extensively applied for glycoscience research. [doi:10.25345/C5FG0C] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Glycoproteins, O-GlcNAcylation and O-GalNAcylation, Proteomics, Mass spectrometry, Simultaneous identification and distinction

Contact

Principal Investigators:
(in alphabetical order) 		Ronghu Wu, Georgia Institute of Technology, United States
Submitting User: xusenhan
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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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