The combination of stable isotope labeling (SIL) with mass spectrometry (MS) allows comparison of the abundance of thousands of proteins in complex mixtures. However, interpretation of the large data sets generated by these techniques remains a challenge because appropriate statistical standards are lacking. Here, we present a generally applicable model that accurately explains the behavior of data obtained using current SIL approaches, including 18O, iTRAQ, and SILAC labeling, and different MS instruments. The model decomposes the total technical variance into the spectral, peptide, and protein variance components, and its general validity was demonstrated by confronting 48 experimental distributions against 18 different null hypotheses. In addition to its general applicability, the performance of the algorithm was at least similar than that of other existing methods. The model also provides a general framework to integrate quantitative and error information fully, allowing a comparative analysis of the results obtained from different SIL experiments. The model was applied to the global analysis of protein alterations induced by low H2O2 concentrations in yeast, demonstrating the increased statistical power that may be achieved by rigorous data integration. Our results highlight the importance of establishing an adequate and validated statistical framework for the analysis of high-throughput data.

MS-based quantitative proteomics plays an increasingly important role in biological and medical research and the development of these techniques remains one of the most important challenges in mass spectrometry. Numerous stable isotope labeling approaches have been proposed. However, and particularly in the case of 18 O-labeling, a standard protocol of general applicability is still lacking, and statistical issues associated to these methods remain to be investigated. In this work we present an improved high-throughput quantitative proteomics method based on whole proteome concentration by SDS-PAGE, optimized in-gel digestion, peptide 18 O-labeling, and separation by off-gel isoelectric focusing followed by liquid chromatography-LIT-MS. We demonstrate that the off-gel technique is fully compatible with 18 The analysis of differential protein expression is fundamental for the understanding of biological processes and plays an increasingly important role in biological and medical research (1). In recent years, numerous stable isotope labeling (SIL) 1 techniques have emerged as alternatives to the historically used two-dimensional-based approaches for semiquantitative proteomic studies. In these techniques the quantification is done in the same mass spectrometer where peptides are analyzed by tandem mass spectrometry (MS/MS), so relative quantification and peptide identification is performed at the same time. The differences among the several existing SIL approaches are mainly related to the way labels are introduced and the method used to perform the quantification by MS. Thus, in the SILAC method (2) labels are introduced metabolically at the protein level before peptides are generated from protein by enzymatic digestion, minimizing variability introduced by peptide preparation, whereas in the others labeling is performed postdigestion at the peptide level, either chemically in the iTRAQ method (3), or enzymatically in the 18 O labeling method (4 -6). In the iTRAQ method, quantification is made at the MS/MS level, allowing the possibility of performing multiplexed comparisons (7) whereas in SILAC and 18 O methods peptides are quantified at the MS level and are mainly used for pairwise comparisons. In other SIL approaches, such as the ICAT method (8), labeled peptides are specifically recovered after an affinity purification approach; this allows reducing peptide complexity, which is particularly appropriate to selectively analyze peptide subpopulations, such as reduced or oxidized cys-containing peptides (9). The 18 O labeling method has the advantage that labels are intro-

Summary S-acylation, S-glutathionylation, S-nitrosylation, and S-sulfenylation are prominent, chemically distinct, modifications that regulate protein function, redox-sensing, and trafficking. Although the biological significance of these modifications is increasingly appreciated, their integration in the proteome remain unknown. Novel MS-based technologies identified 2,596 predominately unique sites in 1,319 mouse liver proteins under physiological conditions. Structural analysis localized the modifications in unique, evolutionary conserved protein segments, outside commonly annotated functional regions. Contrary to expectations, propensity for modification did not correlate with biophysical properties that regulate cysteine reactivity. However, the in vivo chemical reactivity is fine-tuned for specificity, demonstrated by the nominal complementation between the four modifications and quantitative proteomics that showed a reduction in S-nitrosylation is not correlated with increased S-glutathionylation. A comprehensive survey uncovered clustering of modifications within biologically related protein networks. The data provide the first evidence for the occurrence of distinct, endogenous protein networks that undergo redox signaling through specific cysteine modifications.

Nitroxidative stress in cells occurs mainly through the action of reactive nitrogen and oxygen species (RNOS) on protein thiol groups. Reactive nitrogen and oxygen species-mediated protein modifications are associated with pathophysiological states, but can also convey physiological signals. Identification of Cys residues that are modified by oxidative stimuli still poses technical challenges and these changes have never been statistically analyzed from a proteome-wide perspective. Here we show that GELSILOX, a method that combines a robust proteomics protocol with a new computational approach that analyzes variance at the peptide level, allows a simultaneous analysis of dynamic alterations in the redox state of Cys sites and of protein abundance. GELSILOX permits the characterization of the major endothelial redox targets of hydrogen peroxide in endothelial cells and reveals that hypoxia induces a significant increase in the status of oxidized thiols. GELSILOX also detected thiols that are redox-modified by ischemia-reperfusion in heart mitochondria and demonstrated that these alterations are abolished in ischemia-preconditioned animals.

The striatum of the brain coordinates motor function. Dopamine-related drugs may be therapeutic to patients with striatal neurodegeneration, such as Huntington's disease (HD) and Parkinson's disease (PD), but these drugs have unwanted side effects. In addition to stimulating the release of norepinephrine, amphetamines, which are used for narcolepsy and hyperactivity disorder (ADHD), trigger dopamine release in the striatum. The GTPase Ras homolog-enriched in the striatum (Rhes) inhibits dopaminergic signaling in the striatum, is implicated in HD, and has a role in striatal motor control. We found that the guanine nucleotide exchange factor (GEF) RasGRP1 inhibited Rhes-mediated control of striatal motor activity in mice. RasGRP1 stabilized Rhes, increasing its synaptic accumulation in cultured striatal neurons.. Whereas partially Rhes-deficient (Rhes +/− ) mice had an enhanced locomotor response to amphetamine, this phenotype was attenuated by coincident depletion of RasGRP1. By proteomic analysis of striatal lysates from Rhes-heterozygous mice with wild-type or partial or complete knockout of Rasgrp1, we identified a diverse set of Rhes-interacting proteins, the "Rhesactome," and determined that RasGRP1 ** This manuscript has been accepted for publication in Science Signaling. This version has not undergone final editing. Please refer to the complete version of record at http://www.sciencesignaling.org/. The manuscript may not be reproduced or used in any manner that does not fall within the fair use provisions of the Copyright Act without the prior, written permission of AAAS.

Statistical models for the analysis of protein expression changes by stable isotope labeling are still poorly developed, particularly for data obtained by 16

We propose that CsA induced endothelial damage may be related to increased mitochondrial superoxide formation and subsequent peroxynitrite-dependent nitroxidative damage, specifically targeting MnSOD. The inactivation of this key antioxidant enzyme by tyrosine nitration represents a pathophysiological cellular mechanism contributing to self-perpetuation and amplification of CsA-related vascular toxicity.

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