Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases

Pan Fang (), Xiangming Yu, MengYang Ding, Cong Qifei, Hongyu Jiang, Qi Shi, Weiwei Zhao, Weimin Zheng, Yingning Li, Zixiang Ling, Wei-Jun Kong, Pengyuan Yang and Huali Shen ()
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Pan Fang: Suzhou Medical College of Soochow University
Xiangming Yu: Suzhou Medical College of Soochow University
MengYang Ding: Suzhou Medical College of Soochow University
Cong Qifei: The Second Affiliated Hospital of Soochow University
Hongyu Jiang: Suzhou Medical College of Soochow University
Qi Shi: Suzhou Medical College of Soochow University
Weiwei Zhao: Suzhou Medical College of Soochow University
Weimin Zheng: Nanjing Medical University
Yingning Li: Suzhou Medical College of Soochow University
Zixiang Ling: Suzhou Medical College of Soochow University
Wei-Jun Kong: Tongji University
Pengyuan Yang: Fudan University
Huali Shen: Fudan University

Nature Communications, 2025, vol. 16, issue 1, 1-16

Abstract: Abstract The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieve an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multiple workflows. The largest N-glycoproteomic dataset to date is established on mice, which contains 91,972 precursor glycopeptides, 62,216 glycoforms, 8939 glycosites and 4563 glycoproteins. The database consists of 6.8 million glyco-spectra (containing oxonium ions), among which 160,928 spectra is high-quality with confident N-glycopeptide identifications. The large-scale and high-quality dataset enhances the performance of current artificial intelligence models for glycopeptide tandem spectrum prediction. Using this ultradeep dataset, we observe tissue specific microheterogeneity and functional implications of protein glycosylation in mice. Furthermore, the region-resolved brain N-glycoproteomes for Alzheimer’s Diseases, Parkinson Disease and aging mice reveal the spatiotemporal signatures and distinct pathological functions of the N-glycoproteins. A comprehensive database resource of experimental N-glycoproteomic data from this study and previous literatures is further established. This N-glycoproteome atlas serves as a promising tool for revealing the role of protein glycosylation in biological systems.

Date: 2025
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DOI: 10.1038/s41467-025-60437-6

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