4.8 Article

Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics

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ANALYTICAL CHEMISTRY
卷 95, 期 44, 页码 16059-16069

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AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.3c00247

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The complexity and heterogeneity of protein glycosylation present challenges in characterization and quantitation. This study introduces a metabolic isotope labeling strategy called GlyProSILC, which can label both the glycan motif and peptide backbone in the same batch of cells. It provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.
The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-N-15-glutamine, C-13(6)-arginine (Arg(6)), and C-13(6)-N-15(2)-lysine (Lys(8)). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.

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