N-Terminal Proteomics Reveals Distinct Protein Degradation Patterns in Different Types of Human Atherosclerotic Plaques

蛋白质组学 终端(电信) 计算生物学 翻译后修饰 化学 细胞生物学 生物 计算机科学 生物化学 电信 基因
作者
Lasse G. Lorentzen,Karin Yeung,Auguste Zitkeviciute,Karen C. Yang-Jensen,Nikolaj Eldrup,Jonas Eiberg,Michael J. Davies
出处
期刊:Journal of Proteome Research [American Chemical Society]
被引量:2
标识
DOI:10.1021/acs.jproteome.4c00548
摘要

Atherosclerotic plaque rupture is a major cause of cardiovascular events. Plaque destabilization is associated with extracellular matrix (ECM) modification involving proteases which generate protein fragments with new N-termini. We hypothesized that rupture-prone plaques would contain elevated fragment levels, and their sequences would allow identification of active proteases and target proteins. Plaques from 21 patients who underwent surgery for symptomatic carotid artery stenosis were examined in an observational/cross-sectional study. Plaques were analyzed by liquid chromatography-mass spectrometry for the presence of N-terminal fragments. 33920 peptides were identified, with 17814 being N-terminal species. 5735 distinct N-terminal peptides were quantified and subjected to multidimensional scaling analysis and consensus clustering. These analyses indicated three clusters, which correlate with gross macroscopic plaque morphology (soft/mixed/hard), ultrasound classification (echolucent/echogenic), and the presence of hemorrhage/ulceration. Differences in the fragment complements are consistent with plaque-type-dependent turnover and degradation pathways. Identified peptides include signal and pro-peptides from synthesis and those from protein fragmentation. Sequence analysis indicates that targeted proteins include ECM species and responsible proteases (meprins, cathepsins, matrix metalloproteinases, elastase, and kallikreins). This study provides a large data set of peptide fragments and proteases present in plaques of differing stability. These species may have potential as biomarkers for improved atherosclerosis risk profiling.

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