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

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
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
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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.

小鼠超深n -糖蛋白组图谱揭示脑老化和神经退行性疾病的时空特征。
目前位点特异性n -糖蛋白组学的深度不足以完全表征生物样品中的糖基化事件。在此,我们通过整合多个工作流程实现了对小鼠组织n -糖蛋白组的超深度和精确分析。迄今为止最大的n -糖蛋白组学数据集建立在小鼠身上,其中包含91,972个前体糖肽,62,216个糖型,8939个糖位点和4563个糖蛋白。该数据库包含680万个糖谱(含氧离子),其中160,928个谱是高质量的,具有可靠的n -糖肽鉴定。大规模、高质量的数据集提高了当前糖肽串联谱预测的人工智能模型的性能。利用这个超深度数据集,我们观察了小鼠组织特异性的微观异质性和蛋白质糖基化的功能意义。此外,阿尔茨海默病、帕金森病和衰老小鼠的区域分辨脑n-糖蛋白组揭示了n-糖蛋白的时空特征和独特的病理功能。进一步建立了本研究和前人文献中实验n -糖蛋白组学数据的综合数据库资源。这个n -糖蛋白组图谱是揭示蛋白质糖基化在生物系统中的作用的一个有前途的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
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.
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