Chung Heaseung Sophia, Murray Christopher I, Venkatraman Vidya, Crowgey Erin L, Rainer Peter P, Cole Robert N, Bomgarden Ryan D, Rogers John C, Balkan Wayne, Hare Joshua M, Kass David A, Van Eyk Jennifer E
From the Department of Biological Chemistry (H.S.C., C.I.M., R.N.C., J.E.V.E.), Division of Cardiology, Department of Medicine (V.V., P.P.R., D.A.K., J.E.V.E.), The Johns Hopkins NHLBI Proteomics Innovation Center on Heart Failure (H.S.C., V.V., D.A.K., J.E.V.E.), Department of Medicine, Mass Spectrometry and Proteomic Core Facility (R.N.C.), Johns Hopkins University School of Medicine, Baltimore, MD; Thermo Fisher Scientific, Rockford, IL (R.D.B., J.C.R.); Advanced Clinical Biosystems Research Institute, Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA (V.V., E.L.C., J.E.V.E.); Department of Medicine, Interdisciplinary Stem Cell Institute, University of Miami Miller School of Medicine, FL (W.B., J.M.H.); Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada (C.I.M.); and Division of Cardiology, Medical University of Graz, Austria (P.P.R.).
Circ Res. 2015 Oct 23;117(10):846-57. doi: 10.1161/CIRCRESAHA.115.307336. Epub 2015 Sep 3.
S-nitrosylation (SNO), an oxidative post-translational modification of cysteine residues, responds to changes in the cardiac redox-environment. Classic biotin-switch assay and its derivatives are the most common methods used for detecting SNO. In this approach, the labile SNO group is selectively replaced with a single stable tag. To date, a variety of thiol-reactive tags have been introduced. However, these methods have not produced a consistent data set, which suggests an incomplete capture by a single tag and potentially the presence of different cysteine subpopulations.
To investigate potential labeling bias in the existing methods with a single tag to detect SNO, explore if there are distinct cysteine subpopulations, and then, develop a strategy to maximize the coverage of SNO proteome.
We obtained SNO-modified cysteine data sets for wild-type and S-nitrosoglutathione reductase knockout mouse hearts (S-nitrosoglutathione reductase is a negative regulator of S-nitrosoglutathione production) and nitric oxide-induced human embryonic kidney cell using 2 labeling reagents: the cysteine-reactive pyridyldithiol and iodoacetyl based tandem mass tags. Comparison revealed that <30% of the SNO-modified residues were detected by both tags, whereas the remaining SNO sites were only labeled by 1 reagent. Characterization of the 2 distinct subpopulations of SNO residues indicated that pyridyldithiol reagent preferentially labels cysteine residues that are more basic and hydrophobic. On the basis of this observation, we proposed a parallel dual-labeling strategy followed by an optimized proteomics workflow. This enabled the profiling of 493 SNO sites in S-nitrosoglutathione reductase knockout hearts.
Using a protocol comprising 2 tags for dual-labeling maximizes overall detection of SNO by reducing the previously unrecognized labeling bias derived from different cysteine subpopulations.
S-亚硝基化（SNO）是半胱氨酸残基的一种氧化后修饰，可响应心脏氧化还原环境的变化。经典的生物素转换法及其衍生方法是检测SNO最常用的方法。在这种方法中，不稳定的SNO基团被选择性地替换为单个稳定标签。迄今为止，已引入了多种硫醇反应性标签。然而，这些方法尚未产生一致的数据集，这表明单个标签的捕获不完整，并且可能存在不同的半胱氨酸亚群。
研究现有单标签检测SNO方法中潜在的标记偏差，探索是否存在不同的半胱氨酸亚群，然后制定一种策略以最大化SNO蛋白质组的覆盖范围。
我们使用两种标记试剂获得了野生型和S-亚硝基谷胱甘肽还原酶基因敲除小鼠心脏（S-亚硝基谷胱甘肽还原酶是S-亚硝基谷胱甘肽产生的负调节因子）以及一氧化氮诱导的人胚肾细胞的SNO修饰半胱氨酸数据集：半胱氨酸反应性吡啶二硫醇和基于碘乙酰基的串联质量标签。比较发现，两种标签仅检测到不到30%的SNO修饰残基，而其余的SNO位点仅被一种试剂标记。对SNO残基的两个不同亚群的表征表明，吡啶二硫醇试剂优先标记碱性和疏水性更强的半胱氨酸残基。基于这一观察结果，我们提出了一种并行双标记策略，随后是优化的蛋白质组学工作流程。这使得能够对S-亚硝基谷胱甘肽还原酶基因敲除心脏中的493个SNO位点进行分析。
使用包含两种标签的双标记方案，通过减少先前未识别的来自不同半胱氨酸亚群的标记偏差，可最大化SNO的整体检测。
