Metabolic control of glycosylation forms for establishing glycan-dependent protein interaction networks

X Xingyu Liu (Key Laboratory of Biomedical Polymers Ministry of Education, College of Chemistry and Molecular Sciences) L Li Yi (State Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University) Z Zongtao Lin S Siyu Chen (Jinan University ,) S Shunyang Wang (Department of Chemistry, University of California) Y Ying Sheng C Carlito B. Lebrilla (Department of Chemistry, University of California) B Benjamin A. Garcia Y Yixuan Xie (State Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University)

Abstract

Protein–protein interactions (PPIs) are crucial for comprehending the molecular mechanisms and signaling pathways underlying diverse biological processes and disease progression. However, investigating PPIs involving membrane proteins is challenging due to the complexity and heterogeneity of glycosylation. To tackle this challenge, we developed an approach termed glycan-dependent affinity purification coupled with mass spectrometry (GAP–MS), specifically designed to characterize changes in glycoprotein PPIs under varying glycosylation conditions. GAP–MS integrates metabolic control of glycan profiles in cultured cells using small molecules referred to as glycan modifiers with affinity purification followed by mass spectrometry analysis (AP–MS). Here, GAP–MS was applied to characterize and compare the interaction networks under five different glycosylation states for four bait glycoproteins: BSG, CD44, EGFR, and SLC3A2. This analysis identified a network comprising 156 interactions, of which 131 were determined to be glycan dependent. Notably, the GAP–MS analysis of BSG provided distinct information regarding glycosylation-influenced interactions compared to the commonly used glycosylation site mutagenesis approach combined with AP–MS, emphasizing the unique advantages of GAP–MS. Collectively, GAP–MS presents distinct insights over existing methods in elucidating how specific glycosylation forms impact glycoprotein interactions. Additionally, the glycan-dependent interaction networks generated for these four glycoproteins serve as a valuable resource for guiding future functional investigations and therapeutic developments targeting the glycoproteins discussed in this study.

Article Details

Volume / Issue Vol. 122, Issue 25
Published June 24, 2025
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (9)

X

Xingyu Liu

Key Laboratory of Biomedical Polymers Ministry of Education, College of Chemistry and Molecular Sciences

L

Li Yi

State Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University

Z

Zongtao Lin

S

Siyu Chen

Jinan University ,

S

Shunyang Wang

Department of Chemistry, University of California

Y

Ying Sheng

C

Carlito B. Lebrilla

Department of Chemistry, University of California

B

Benjamin A. Garcia

Y

Yixuan Xie

State Key Laboratory of Genetic Engineering, Greater Bay Area Institute of Precision Medicine (Guangzhou), School of Life Sciences and Institutes of Biomedical Sciences, Fudan University