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Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
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Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
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Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis

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Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis
Journal Article

Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis

2019
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Overview
Protein glycosylation is a highly important, yet poorly understood protein post-translational modification. Thousands of possible glycan structures and compositions create potential for tremendous site heterogeneity. A lack of suitable analytical methods for large-scale analyses of intact glycopeptides has limited our abilities both to address the degree of heterogeneity across the glycoproteome and to understand how this contributes biologically to complex systems. Here we show that N-glycoproteome site-specific microheterogeneity can be captured via large-scale glycopeptide profiling methods enabled by activated ion electron transfer dissociation (AI-ETD), ultimately characterizing 1,545 N-glycosites (>5,600 unique N-glycopeptides) from mouse brain tissue. Our data reveal that N-glycosylation profiles can differ between subcellular regions and structural domains and that N-glycosite heterogeneity manifests in several different forms, including dramatic differences in glycosites on the same protein. Moreover, we use this large-scale glycoproteomic dataset to develop several visualizations that will prove useful for analyzing intact glycopeptides in future studies. Mass spectrometry facilitates large-scale glycosylation profiling but in-depth analysis of intact glycopeptides is still challenging. Here, the authors show that activated ion electron transfer dissociation is suitable for glycopeptide fragmentation and improves glycoproteome coverage.