{"title":"Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases.","authors":"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, Huali Shen","doi":"10.1038/s41467-025-60437-6","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"16 1","pages":"5568"},"PeriodicalIF":15.7000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12215503/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-60437-6","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.