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RESEARCH PAPER / 2025-03-13

A high-resolution N-glycoproteome landscape of aging mouse ovary.

Yongqi Wu, Zhida Zhang, Yongchao Xu, Yingjie Zhang, Lin Chen, Yiwen Zhang, Ke Hou, Muyao Yang, Zhehui Jin, Yinli Cai, Jiayu Zhao, Shisheng Sun

Laboratory for Disease Glycoproteomics, College of Life Sciences, Northwest University, Xi'an, 710069, PR China.Laboratory for Disease Glycoproteomics, College of Life Sciences, Northwest University, Xi'an, 710069, PR China. · pubmed

Abstract

Ovarian aging typically precedes the decline of other organ systems, yet its molecular mechanisms remain poorly understood. Glycosylation as one of the most important protein modifications has been especially unexplored in this context. Here, we present the first high-resolution glycoproteomic landscape of aging mouse ovaries, uncovering site-specific N-glycan signatures across subcellular components such as high proportions of complex glycans, core fucosylation, and LacdiNAc branches at the zone pellucida. We report three major glycosylation alterations in aged ovaries: the frequently changed core-fucosylation associated with cell adhesion and immune responses, the decreased LacdiNAc glycans on zona pellucida (ZP) responsible for fertility decline, and the increased sialylated glycans modified by Neu5Ac and Neu5Gc playing different roles in immune activation and responses. Integrated multi-omic analyses further highlight the unique role of glycosylation, distinct from phosphorylation, in regulating key signaling pathways, antigen processing and presentation, complement coagulation cascades, ROS biosynthetic and metabolic processes, as well as cell death. This study offers a novel glycobiological perspective on ovarian aging, broadening our understanding of its molecular mechanisms beyond traditional multi-omic approaches.

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Research summary

The paper identifies specific N-glycan alterations in aging mouse ovaries that contribute to our understanding of ovarian aging mechanisms. This research explores molecular changes associated with aging, which could inform strategies for addressing age-related fertility decline.

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