人类心力衰竭患者外周血单核细胞的 S-亚硝基化蛋白质组图谱

International journal of proteomics Pub Date : 2016-01-01 Epub Date: 2016-08-18 DOI:10.1155/2016/1384523
Sue-Jie Koo, Heidi M Spratt, Kizhake V Soman, Susan Stafford, Shivali Gupta, John R Petersen, Maria P Zago, Muge N Kuyumcu-Martinez, Allan R Brasier, John E Wiktorowicz, Nisha Jain Garg
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引用次数: 0

摘要

一氧化氮(NO)能保护心脏免受缺血性损伤;然而,NO 和超氧化物依赖的半胱氨酸 S-亚硝基化(S-NO)会影响靶蛋白的功能,并在疾病预后中发挥作用。我们用硫醇标记的 FL-马来酰亚胺染料和 MALDI-TOF MS/MS 进行了 2D-GE 分析,以捕捉高频患者(与健康对照组相比,n = 30/组)的丰度和 S-NO 蛋白质组的定量变化。我们在高血脂患者(与对照组相比,折叠变化 | ≥1.5|,P ≤ 0.05)中分别发现了 93 个不同丰度(增加 59 个/减少 34 个)和 111 个 S-NO 修饰(增加 63 个/减少 48 个)的蛋白质点。蛋白质组数据集的Ingenuity通路分析表明,在高血脂患者中,参与吞噬细胞迁移、自由基产生和细胞死亡的通路被激活,脂肪酸代谢减少。数据集的多变量自适应回归样条建模确定了一组蛋白质,这些蛋白质在对心房颤动受试者进行分类时的预测成功率大于 90%。蛋白质组分析确定 ATP-合成酶、血栓软蛋白-1 (THBS1) 和长春花苷 (VCL) 为最高的差异丰度和 S-NO 修饰蛋白质,这些蛋白质在不同的高血脂受试者组中通过 Western 印迹和 ELISA 得到了验证。我们的结论是,蛋白质的不同丰度和S-NO修饰是调节细胞活力和自由基产生的一种机制,对THBS1和VCL的评估可能有助于预测心力衰竭。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

S-Nitrosylation Proteome Profile of Peripheral Blood Mononuclear Cells in Human Heart Failure.

S-Nitrosylation Proteome Profile of Peripheral Blood Mononuclear Cells in Human Heart Failure.

S-Nitrosylation Proteome Profile of Peripheral Blood Mononuclear Cells in Human Heart Failure.

S-Nitrosylation Proteome Profile of Peripheral Blood Mononuclear Cells in Human Heart Failure.

Nitric oxide (NO) protects the heart against ischemic injury; however, NO- and superoxide-dependent S-nitrosylation (S-NO) of cysteines can affect function of target proteins and play a role in disease outcome. We employed 2D-GE with thiol-labeling FL-maleimide dye and MALDI-TOF MS/MS to capture the quantitative changes in abundance and S-NO proteome of HF patients (versus healthy controls, n = 30/group). We identified 93 differentially abundant (59-increased/34-decreased) and 111 S-NO-modified (63-increased/48-decreased) protein spots, respectively, in HF subjects (versus controls, fold-change | ≥1.5|, p ≤ 0.05). Ingenuity pathway analysis of proteome datasets suggested that the pathways involved in phagocytes' migration, free radical production, and cell death were activated and fatty acid metabolism was decreased in HF subjects. Multivariate adaptive regression splines modeling of datasets identified a panel of proteins that will provide >90% prediction success in classifying HF subjects. Proteomic profiling identified ATP-synthase, thrombospondin-1 (THBS1), and vinculin (VCL) as top differentially abundant and S-NO-modified proteins, and these proteins were verified by Western blotting and ELISA in different set of HF subjects. We conclude that differential abundance and S-NO modification of proteins serve as a mechanism in regulating cell viability and free radical production, and THBS1 and VCL evaluation will potentially be useful in the prediction of heart failure.

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