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Impact Factor4.466
DOI number:10.1021/acs
Key Words:glycoproteomics; intact glycopeptide; neonatal mouse heart; regeneration; site-specific glycosylation.
Abstract:Myocardial infarction (MI) is one of the leading causes of deaths worldwide. Because of the incapability of regeneration, the cardiomyocyte loss with MI is replaced by fibrotic scar tissue, which eventually leads to heart failure. Reconstructing regeneration of an adult human heart has been recognized as a promising strategy for cardiac therapeutics. A neonatal mouse heart, which possesses transient regenerative capacity at the first week after birth, represents an ideal model to investigate processes associated with cardiac regeneration. In this work, an integrated glycoproteomic and proteomic analysis was performed to investigate the differences in glycoprotein abundances and site-specific glycosylation between postneonatal day 1 (P1) and day 7 (P7) of mouse hearts. By large-scale profiling and quantifying more than 2900 intact N-glycopeptides in neonatal mouse hearts, we identified 227 altered N-glycopeptides between P1 and P7 hearts. By extracting protein changes from the global proteome data, the normalized glycosylation changes for site-specific glycans were obtained, which showed heterogeneity on glycosites and glycoproteins. Systematic analysis of the glycosylation changes demonstrated an overall upregulation of sialylation and core fucosylation in P7 mice. Notably, the upregulated sialylation was a comprehensive result of increased sialylated glycans with Neu5Gc, with both Neu5Gc and core fucose, and decreased sialylated glycans with Neu5Ac. The upregulated core fucosylation resulted from the increase of glycans containing both core fucose and Neu5Gc but not glycans containing sole core fucose. These data provide a valuable resource for future functional and mechanism studies on heart regeneration and discovery of novel therapeutic targets. All mass spectrometry proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD017139.
Indexed by:Journal paper
Discipline:Natural Science
First-Level Discipline:Biology
Translation or Not:no
Included Journals:SCI
Pre One:49. Jianbo Pan#, Yingwei Hu#, Shisheng Sun#, Lijun Chen, Michael Schnaubelt, David Clark, Minghui Ao, Zhen Zhang, Daniel Chan, Jiang Qian, Hui Zhang*. Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer. Nature communications. 2020, 11 (1): 6139.
Next One:47. Ting Zhao, Li Jia, Jun Li, Chen Ma, Jingyu Wu, Jiechen Shen, Liuyi Dang, Bojing Zhu, Pengfei Li, Yuan Zhi, Rongxia Lan, Yintai Xu, Zhifang Hao, Yichao Chai, Qingshan Li, Liangshuo Hu, Shisheng Sun*. Heterogeneities of site-specific N-glycosylation in HCC tumors with low and high AFP concentrations. Frontiers in Oncology. 2020, 10: 496.