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Dual Labeling Biotin Switch Assay to Reduce Bias Derived From Different Cysteine Subpopulations: A Method to Maximize
Heaseung Sophia Chung1, Christopher I Murray1, Vidya Venkatraman1
1From 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.).
Rationale:
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.
Objective:
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.
Methods And Results:
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.
Conclusions:
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.
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