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

Author

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  • Nicholas M. Riley

    (University of Wisconsin-Madison
    University of Wisconsin-Madison
    Stanford University)

  • Alexander S. Hebert

    (University of Wisconsin-Madison)

  • Michael S. Westphall

    (University of Wisconsin-Madison)

  • Joshua J. Coon

    (University of Wisconsin-Madison
    University of Wisconsin-Madison
    University of Wisconsin-Madison
    Morgridge Institute for Research)

Abstract

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.

Suggested Citation

  • Nicholas M. Riley & Alexander S. Hebert & Michael S. Westphall & Joshua J. Coon, 2019. "Capturing site-specific heterogeneity with large-scale N-glycoproteome analysis," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09222-w
    DOI: 10.1038/s41467-019-09222-w
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    Cited by:

    1. Stacy A. Malaker & Nicholas M. Riley & D. Judy Shon & Kayvon Pedram & Venkatesh Krishnan & Oliver Dorigo & Carolyn R. Bertozzi, 2022. "Revealing the human mucinome," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Siyuan Kong & Pengyun Gong & Wen-Feng Zeng & Biyun Jiang & Xinhang Hou & Yang Zhang & Huanhuan Zhao & Mingqi Liu & Guoquan Yan & Xinwen Zhou & Xihua Qiao & Mengxi Wu & Pengyuan Yang & Chao Liu & Weiqi, 2022. "pGlycoQuant with a deep residual network for quantitative glycoproteomics at intact glycopeptide level," Nature Communications, Nature, vol. 13(1), pages 1-17, December.

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