[methods in enzymology] nitric oxide, part f volume 440 || quantitative proteome mapping of...

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Quantitative Proteome Mapping of

Nitrotyrosines

Diana J. Bigelow* and Wei-Jun Qian†

Contents

1. In

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troduction

Enzymology, Volume 440 # 200

-6879, DOI: 10.1016/S0076-6879(07)00811-7 All r

ogy and Biochemistry Group, Division of Biological Sciences, Pacific Northwest Nry, Richland, Washingtonof Biological Sciences, Environmental Molecular Sciences Laboratory, Pacific Northy, Richland, Washington

1

8 Elsevie

ights rese

ational

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2. M
ultidimensional LC-MS/MS Provides Large Data Sets for
Identification of Nitrotyrosine-Modified Proteins
193
3. R
etention of Complexity in Samples Prepared from Global
Proteomic Analysis
195
4. C
onfident Identification of Nitrotyrosine-Containing Peptides 1 97
5. C
omparative Quantitation of Nitrotyrosine-Modified
Peptide/Proteins
198
6. S
ummary 2 03
Refe
rences 2 03
Abstract

An essential first step in the understanding disease and environmental pertur-

bations is the early and quantitative detection of the increased levels of the

inflammatory marker nitrotyrosine, as compared with its endogenous levels

within the tissue or cellular proteome. Thus, methods that successfully address

a proteome-wide quantitation of nitrotyrosine and related oxidative modifica-

tions can provide early biomarkers of risk and progression of disease, as well as

effective strategies for therapy. Multidimensional separations LC coupled with

tandem mass spectrometry (LC-MS/MS) has, in recent years, significantly

expanded our knowledge of human (and mammalian model system) pro-

teomes, including some nascent work in identification of posttranslational

modifications. This chapter discusses the application of LC-MS/MS for quanti-

tation and identification of nitrotyrosine-modified proteins within the context of

complex protein mixtures presented in mammalian proteomes.

r Inc.

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tional

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192 Diana J. Bigelow and Wei-Jun Qian

1. Introduction

Recent advances in the sensitivity ofmass spectrometry instrumentation,coupled with improved separations methods, now offer increasing opportu-nities for understanding cell and tissue responses at a whole proteome level.Current technologies allow the abundance of thousands of proteins to bemonitored simultaneously. Thus, the entire proteome of simple organisms canbe resolved, and for larger mammalian proteomes, these capabilities offersignificant access into the changing protein landscape of cells and tissues inresponse to stress and disease, as well as a means to monitor the efficacy oftherapeutic interventions. Moreover, sensitive identification of changes inboth abundance and posttranslational modification of proteins can provideearly and valuable biomarkers of disease, as well as insights into molecularmechanisms of disease progression.

Despite the important role of posttranslational modifications in theactivation of signal transduction pathways or as markers of inflammatoryevents, proteomics strategies to address this dynamic aspect of the proteomehave not been fully exploited. In particular, in view of the frequentcontribution of inflammation and oxidative stress in pathological tissuechanges, 3-nitrotyrosine modifications are of particular interest in moni-toring initiation and progression of disease. Indeed, since an antinitrotyr-osine antibody became available over a decade ago, increased proteinnitration has been reported in over 100 human pathologies and their animalor cell models (Pacher et al., 2007; Ye et al., 1996). However, associatedinformation has lagged regarding the identity of nitrated proteins in specificpathophysiological conditions, the extent of their nitration, and how theirmodification alters protein and cellular function. Thus, the picture ofpathways that explain the correlations between nitrotyrosine and diseaseis substantially incomplete. As an additional confounding factor, the celldeath that often accompanies chronic pathology is likely to contribute to alimited understanding of mechanisms related to disease progression. Thus,detection of proteome changes at early stages in disease progression isessential in understanding disease and in the development of effectivetherapeutic strategies; an initial step requires the establishment of a baselineof endogenous oxidative stress from a quantitative identification ofnitrotyrosine-modified proteins in tissues in the absence of pathology.From such analyses, additional information can be gained regarding thecellular distribution of nitrated proteins as a signature of reactive nitrogenchemistries in the cell, as well as potential vulnerabilities to inflammationand redox regulation of specific proteins and pathways; moreover, exami-nation of nitrotyrosine sites suggests protein structural features that enhancenitration in vivo.

Nitrotyrosine Proteomics 193

2. Multidimensional LC-MS/MS Provides Large

Data Sets for Identification of

Nitrotyrosine-Modified Proteins

In order to establish a quantitative baseline level of protein nitration,several criteria must be met, i.e., (i) samples must be sufficiently complexso that their composition reflects that of the original cell or tissue; (ii)analytical techniques must be sensitive enough to provide the large datasets necessary to identify relatively low abundance modifications of multipleproteins; and (iii) methods must include a means to identify precise sites ofmodification sites. In large part, multidimensional LC or other high resolu-tion methods for separation of peptides coupled with tandem mass spec-trometry (LC/LC-MS/MS) have provided the best solution to theserequirements. Typically, these methods from global proteomic analysesutilize complex protein samples of interest, e.g., cellular, tissue, or organellehomogenates, subjected to proteolytic digestion. The resulting peptides areseparated according to physical properties, e.g., charge, size, or hydropho-bicity, followed by a second dimension of separation, often inline with verysensitive mass spectrometry (MS). For each MS run (corresponding toone fraction from second-dimension separation), the five most abundantparent masses are selected for further fragmentation for MS/MS spectrafrom which peptide sequence information is obtained. Because most sepa-ration schemes provide more high-quality parent masses per fraction thanthe MS/MS capacity of the associated spectrometer, undersampling remainsa technical limitation to this analytic approach (Qian et al., 2006). Never-theless, the size of the data sets provided by current LC/LC-MS/MScapabilities are sufficiently large to challenge the overall throughput; forexample, a recent global proteomic analysis of brain resulted in �751,000individual MS/MS spectra (Wang et al., 2006). Subsequently, these experi-mental MS/MS spectra are matched with theoretical mass spectra calculatedbased on sequences from a given protein database for an organism of choiceby means of automated database-searching algorithms (e.g., SEQUEST,MASCOT, X!Tandem) that provide peptide sequence identification(Craig and Beavis, 2004; Perkins et al., 1999; Yates et al., 1995).

An alternative method, which has been commonly used for theidentification of nitrotyrosine-modified proteins, consists of MS identifica-tion of peptides extracted from proteins bands/spots on one- or two-dimensional electrophoresis gels after in-gel proteolysis. This approach hasseveral shortcomings for quantitative global analysis of nitrated proteins,related primarily to high losses of protein during peptide extraction(Aulak et al., 2001; Castegna et al., 2003; Kanski et al., 2005a). Typically,nitrated proteins identified from gel-based approaches have been limited to


abundant and soluble proteins, which are detectable by the nitrotyrosineantibody and for which constituent peptides can be eluted from two-dimensional gels in sufficient amounts for MS identification (Aulak et al.,2001; Castegna et al., 2003; Kanski et al., 2005a,b; Turko et al., 2003). Thus,in view of the common comigration of multiple proteins on electrophoresisgels and the incomplete sequence coverage of extracted proteins, consider-able uncertainty exists regarding the identity of a nitrated peptide if, as isfrequently the case, the nitrated sequence is not among the extractedpeptides from a gel spot. Moreover, LC-MS/MS approaches avoid biasesintroduced through the use of antibodies for either enrichment or detectionof nitrated proteins, as LC-MS/MS identification of nitrated peptides isbased on the appearance of nitrotyrosine sites within a specific peptidesequence. Of note, several studies have shown substantial differential sensi-tivity to various proteins of antinitrotyrosine antibodies from differentsources, differences that could lead to failure to detect major nitratedproteins (Barreiro et al., 2002; Sacksteder et al., 2006). Moreover, mem-brane proteins, which are typically lost by aggregation during the isoelectricfocusing step of two-dimensional gels, are identified more abundantly whenseparations involve peptides rather than proteins (Wu and Yates, 2003). Forexample, membrane proteins comprised 26% of the proteins identified in aglobal screen of mouse brain, consistent with predictions that 20 to 30%of all open reading frames encode for membrane proteins (Ahram andSpringer, 2004; Krogh et al., 2001; Wallin and von Heijne, 1998).However, it should be noted that transmembrane sequences themselvesare in relatively low abundance in most LC-MS/MS proteomics screens(Blonder et al., 2002). In view of model studies that have shown morefrequent nitration of intramembrane tyrosine probes as compared withtyrosines in aqueous solution, it might be expected that numerous nitrotyr-osines present in vivo are being missed by current proteomics screens (Zhanget al., 2001). Thus, development of methods that enhance the recovery ofhydrophobic membrane-spanning sequences will be important improve-ments for a more complete understanding of protein nitration in vivo.Otheradvantages of this analytical approach include its sensitivity and dynamicrange, which provides identification of both high and low abundancecellular peptides and proteins. Finally, utilizing the same complex proteinmixture to identify both nitrated peptides and their nonnitrated analogsmakes a semiquantitative estimate of nitrotyrosine stoichiometry possible.Thus, this chapter focuses on the discussion of current applications ofLC-MS/MS for quantitative mapping of nitrotyrosine sites within cellsand tissues. In view of several excellent reviews available regardingdevelopments in high-resolution mass spectrometric instrumentation andseparation capabilities for proteomics, this chapter focuses on specificexperimental strategies related to sample requirements, confident peptideidentification, and quantitation of nitrotyrosine-modified peptide/proteins


(Domon and Aebersold, 2006; Ong and Mann, 2005; Qian et al., 2006;Sadygov et al., 2004; Shen and Smith, 2005; Smith et al., 2006).

3. Retention of Complexity in Samples Prepared

from Global Proteomic Analysis

As in any cost- and labor-intensive analyses, such as proteomics,sample quality is the most important factor. In order that nitroproteomicanalyses are informative of the tissue, organelle, or cell of interest, samplesshould reflect the original protein composition. Thus, although severalchemical and immunoaffinity methods have been developed to selectivelyenrich nitrated proteins for proteomic analysis, these approaches lack infor-mation regarding the extent of nitration within the original cell or tissue(Zhan and Desiderio, 2004; Zhang et al., 2007). A sample preparation thatretains as much native complexity as is practical and is still compatible withits application to separation matrices is an essential first step in any proteomicanalysis; in particular, this principle applies to the quantitative analysis ofnitrotyrosines for which quantitation in context of the total protein issought. Tissue homogenates that include the removal of connective tissueand other large particles (‘‘cell debris’’) are commonly used as a source ofpeptides for global analyses. However, recent proteomics studies haveincluded a limited number of additional fractionation steps prior to high-sensitivity separations that provide subproteomes to further reduce samplecomplexity, thus enhancing the detection of low abundance proteins andoverall proteomic coverage.

For example, Wang and co-workers (2006) subjected a portion oftryptic peptides from brain homogenate to cysteine-peptidyl enrichment(thiopropyl Sepharose) prior to cysteine alkylation; the remaining portionwas analyzed without cysteine alkylation, essentially depleting this latterportion of cysteinyl-peptides to provide complementary proteomic samples.From the combined analysis of these two samples, from 1564 to 1859 addi-tional proteins were identified as compared with the yield from either one ofthese samples. Similarly, the proteome coverage of humanmammary epithelialcells was increased from 10 to 34% with cysteine-peptidyl enrichment (Liuet al., 2005).

Other simple fractionation steps prior to proteolysis have been employedthat permit the identification of more proteins from the combined results ofeach subproteome as compared with a single global fraction, such as a tissuehomogenate (Foster et al., 2006; Wu et al., 2007). Figure 11.1 shows acomparison of results from two different protein fractionation strategiesapplied to mouse heart homogenates prior to LC-MS/MS analyses. Oneof these involves a single centrifugation step of the tissue homogenate that

3298 unique proteins

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Figure 11.1 Fractionation of mouse heart homogenates reduces sample complexityand increases proteome coverage.Venn diagrams indicate protein identifications result-ing from different fractionation strategies applied to LC-MS/MS proteomic analyses ofmouse hearts. (Left) Heart homogenates were centrifuged at 48,000 g; the resultingmembrane pelletswere solubilizedwith either 2%CHAPSor 30%TFEprior to proces-sing for LC-MS/MS analysis in parallel to that for the supernatant fraction (Soluble).Combined analysis resulted in the identification of 3298 unique proteins; the total pro-tein identified for each fraction is indicated in parentheses. Numbers inside the circlesindicate identified proteins that are unique or in common with one or two other frac-tions. (Right) Heart homogenates were differentially centrifuged at 15,000 g, resultingin amitochondrially enriched pellet (Mito), and at 48,000 g, resulting in an sarcoplasmicreticulum-enriched pellet (SR); and the 48,000 g supernatant was designated as acytosolic-enriched (Cyt) fraction. Sampleswere digested and processed for LC-MS/MSanalysis, resulting in the identification of 3432 unique proteins from the combinedresults; proteins unique or commonwith one or two other fractions are indicatedwithinthe circles as indicated for each fraction. For proteomic analysis, strong cation exchangewas used for the first dimension of peptide separation, followed by separation of theresulting 30 fractions on a reversed-phase (C18) capillary HPLC system coupled onlinewith an LTQ ion trap mass spectrometer (ThermoFinnigan San Jose, CA) using anin-house manufactured electrospray ionization interface. MS/MS data were searchedagainst the mouse International Protein Index (IPI) database (version 1.25, availableonline at http://www.ebi.ac.uk/IPI) and a sequence-reversed IPI database (to assessfalse positives) using SEQUEST (ThermoFinnigan).


largely separates membrane vesicles from soluble supernatant proteins;the resulting membrane pellet is solubilized with either the detergent3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate (CHAPS)or the organic solvent trifluoroethanol (TFE). In particular, the use of twodifferent solubilization agents permits enhanced numbers of unique proteinsidentified in the membrane fractions so that their total number approxi-mates that of the soluble fraction. As an alternative method, differential

http://www.ebi.ac.uk/IPI


centrifugation was used to prepare fractions enriched in mitochondria,sarcoplasmic reticulum membranes, and cytosolic proteins (Fig. 11.1).This approach, too, increased the total proteins identified relative to eitherfraction alone or as compared with a single homogenate fraction, in whichapproximately 900 proteins were initially identified (data not shown).Sequence coverage was also improved. Similar to overall protein identifica-tion, nitrotyrosine-modified protein identification was also enhanced bythese initial fractionation strategies. Any number of fractionation schemesmight be devised with several caveats, i.e, (i) all subproteomes should beanalyzed, avoiding the discarding of fractions, so that the combined resultsreflect the original proteome of interest and that (ii) within the LC-MScapabilities, fractionation/separations resolution increases have to be bal-anced with their concomitant decreases in overall sample throughput. Inparticular, the number of subproteome fractionations at the front end ofglobal analysis increases total MS runs rapidly and therefore decreasesthroughput. For example, in the case when each experimental sampleincludes approximately 30 first-dimension separation fractions applied tothe second-dimension separation online with the mass spectrometer, thethree subproteome samples used in Fig. 11.1 require 90 MS runs perexperimental sample, an analysis that requires significant instrumental andcomputational time under current system capabilities.

4. Confident Identification of

Nitrotyrosine-Containing Peptides

The automated database searching used to identify native peptides canbe adjusted to accommodate searches for specific posttranslational modifica-tions of interest by including the addition of an appropriate mass to thecorresponding amino acid within peptide sequences. For example, in thecase of nitrotyrosine, searches are performed for the addition of 44.98 Daapplied to tyrosines within peptide sequences. Searches for additional mod-ifications may be desired to widen the search for nitrated peptides, as, forexample, cysteine carboxamidomethylation is a usual step in sample proces-sing for MS analysis, requiring searches for 57.02 Da applied to cysteines. Ina recent LC-MS proteomic analysis, almost two-thirds of nitrated peptidesalso contained at least one Cys residue; these are peptides that would eludeidentification without consideration of appropriate modifications oncysteines. Additionally, methionine sulfoxides (with their additional massof 15.99 Da) should be included in searches for nitrated peptides, as thesemethionine modifications commonly result from nitrating chemistries, suchas peroxynitrite, and are frequently present within nitrated peptides.In biological samples where oxidative stress and inflammation are expected,


other stable oxidative modifications may be informative and necessary forthe efficient identification of nitrotyrosine modifications, as, for example,sulfinic (RSO2H) and sulfonic (RSO3H) acid derivatives of cysteines,methionine sulfones (MetSO2), nitrotryptophans, and bromo- and chlor-otyrosines. However, the substantial computational times required forsimultaneous searching of multiple modifications within large data setsplace practical limits on most global proteomic searches to no more thanthree or four modifications at a time.

The confidence of peptide identifications by automated database search-ing is based on the use of stringent criteria for filtering data. To addresspossible false-positive peptide identifications, sequence-reversed proteindatabase searches have been used in order to establish filtering criteria thatensure low levels (e.g., <2%) of false-positive peptide identifications.Moreover, especially in the case of low abundance modifications such asnitrotyrosines, nitrated peptide identifications can be validated by manualinspection of the corresponding MS/MS spectra to ensure that (i) spectralpeaks are clearly defined above the spectral noise; (ii) that no major uniden-tified peaks are present, and that (iii) major peak assignments are consistentwith predicted patterns as illustrated by MS/MS spectra for the nitrated andunmodified versions of the peptide, DSYVAIANACCAPR (Fig. 11.2).As observed by comparison of these two spectra, all detected y fragmentions match for the two spectra, but all b ions containing the nitrotyrosinefrom the nitrated peptide (b3–b12) have masses that are 44.98 Da higher thanthe corresponding b ions from the nonnitrated peptide.

5. Comparative Quantitation of

Nitrotyrosine-Modified Peptide/Proteins

Pathophysiological or environmental perturbations often alter theprotein abundances, including posttranslational modifications such as nitro-tyrosines in cells, tissues, or biological fluids. The ability to quantitativelymeasure relative protein abundance and their modification differencesbetween different conditions is essential for identifying key moleculartargets or candidate biomarkers involved in different diseases. Currentquantitative characterization of relative protein abundance differences canbe categorized as two general approaches: (1) MS peptide ion intensity-based quantitation, often in combination with stable isotope labeling, and(2) MS/MS spectrum count (or peptide hit)-based quantitation. In thesecond approach, quantitation information is derived from the number ofMS/MS sampling identifying a given protein within a complex mixture.Spectrum counts correspond to the number of MS/MS spectra observed foreach distinct peptide, which may include repetitive identification or the

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Figure 11.2 MS/MS spectra of the nitrated (A) and nonnitrated (B) peptide, DSY-VAIANACCAPR, from the vesicular inhibitory amino acid transporter.Y# indicatesnitrotyrosine modification, andC! indicates a cysteinyl residuemodified by carboxami-domethylation.The two spectra match well on all detected b and y fragment ions, withthe exception that b ions containing nitrotyrosine, i.e., b3^b12, from the nitrated peptidehave masses 44.98 Da higher than the corresponding b ions from the nonnitratedpeptide, as illustrated by arrows for b12.


same peptide in one or multiple first-dimension fractions. These values havebeen demonstrated to provide a reproducible and semiquantitative measureof peptide concentration in complex samples (Qian et al., 2005).


Because nitrotyrosine is often measured within the context of the globalproteome, both approaches can theoretically be applied for quantitativemeasurements of differences in nitration levels. However, the use of stableisotope labeling for the quantitation of nitrotyrosine modifications has notbeen reported to date. As discussed here, MS/MS spectrum counts derivedfrom current LC-MS/MS capabilities provide the most reliable quantitationof nitrotyrosine modification extent.

For MS ion intensity-based quantitation, most approaches have involvedthe use of stable isotope labeling to achieve good accuracy in quantifyingthe relative abundance differences.Many stable isotope-labelingmethods havebeen introduced successfully for quantitative proteomics and are reviewedelsewhere (Ong andMann, 2005; Qian et al., 2004). In general, stable isotopelabels can be introduced into proteins or peptides by metabolic labeling,chemical labeling on specific functional groups, and enzymatic transfer of18O from water to the C terminus of peptides. All of these methods incorpo-rate either a light or a heavy version of the stable isotope into chemicallyidentical peptides from two different samples, and the resulting peptide pairsare differentiated by MS due to the mass difference between the light and theheavy isotope-coded pair. The ratio of MS ion intensities for the peptide paircan then accurately indicate the abundance ratios of the peptide/protein fromthe two different samples. More recently, there has been a significant interestin applying ‘‘label-free’’ direct quantitation due to the greater flexibility forcomparative analyses and simpler sample processing procedures compared tolabeling approaches (Qian et al., 2006;Wang et al., 2003). The isotope labelingand label-free approaches are complementary, and each approach has differentsources of variations. While the stable isotope-labeling approach is generallymore accurate in quantitation as compared with the label-free approach as aconsequence of the unbiased measurement of peptide pairs by MS and theminimum variations from sample processing postlabeling, isotopic ratios oftenhave a limited dynamic range for quantitating large changes as a consequenceof the overlap of isotopic envelopes between light and heavy members of thepair. However, the label-free approach is often more ideal for the quantitationof more dramatic changes in protein abundances or in estimating the stoichi-ometry of posttranslational modification of low abundance modifications asnitrotyrosines.With the proper use of replicate analyses and data normalizationto mitigate changes in instrumental performance between analyses, accuratecomparative quantitation can be achieved for biological and clinicalapplications.

The MS/MS spectrum counting approach has been reported as analternative approach for relative quantitation based on the correlation ofprotein abundances with the number of MS/MS spectra (or peptide hits)identifying a given proteins (Liu et al., 2004; Qian et al., 2005; Zybailovet al., 2005). It should be noted that the spectrum count approach is asemiquantitative method for comparative analyses because the spectrum


counts may not have a linear correlation with protein abundances. Addi-tionally, the spectrum count approach will become problematic whenproteins are observed with only a few counts in both conditions. Despitethese potential disadvantages, this approach has been increasingly applied forseveral reasons, including (1) the experiments can be performed on acommon ion-trap instrument without the need of high-resolution MSmeasurements, (2) the approach can be easily coupled with multiple dimen-sional LC separations, and (3) the reproducibility in terms of spectrumcounts is observed for both one-dimensional LC (Liu et al., 2004, 2006)and two-dimensional LC-MS/MS (Qian et al., 2005). Moreover, the spec-trum count information provides an estimation of the relative abundances ofdifferent proteins within the same sample (Wang et al., 2006).

Specifically, when protein modifications such as nitrotyrosine are ofinterest, the extent of modification or the stoichiometry of modificationscan be estimated by comparing spectrum counts of the modified peptides tototal peptides from the global proteome for a given proteins. Here, the largedynamic range of spectrum counts is valuable, as typical levels of nitratedpeptides relative to their nonnitrated analogs are quite low,<1/1000, levelsthat would disallow reliable quantitation from isotopic ratios. Anotherlimitation of using stable isotope ratios for the quantitation of posttransla-tional modifications is that the number of peptide pairs resolved by thismethod is generally considerably smaller than the peptides identified bylabel-free approaches, which would further reduce the number of detectednitrotyrosine-modified peptides that are quantifiable. A more commonproblem for spectrum count-associated quantitation of nitrotyrosines isthe detection either of only a few counts of nitrated peptides or of differ-ences derived from different experimental conditions. These low levels mayresult from incomplete sampling because of stringent criteria for identifica-tion and their low abundance; guidelines for the evaluation and statisticalsignificance of spectrum counts at low levels have been discussed previously(Qian et al., 2005).

Reproducibility for LC-MS/MS proteomic analyses can be excellent; arecent study comparing results of proteomic analyses of nine individuallyprocessed technical replicates of human plasma samples showed very lowvariation in peptide intensities with an overall Pearson’s correlation coeffi-cient of 0.94� 0.02 (Qian et al., 2006). In comparison, plasma samples fromnine individual human patients exhibited significantly more variation with acorrelation coefficient of 0.85 � 0.06; however, analyses from nine indi-vidual mouse plasma samples showed only a slightly reduced correlation(0.92 � 0.05) as compared with technical replicates. Studies such as thesehighlight the importance of minimizing any instrumental contribution tothe variability in proteomics results in order to enhance the detection ofexperimental differences.


As an illustration of spectrum counts used to quantitate nitrotyrosinelevels in several tissues, we compared the results of three multidimensionalLC-MS/MS proteomic screens of mouse brain, heart, and skeletal muscle,identifying endogenous nitrotyrosine-modified peptides and associatedproteins from SEQUEST searches that consider methionine sulfoxidesand carboxymethylated cysteines as well as nitrotyrosines. Calculating theratio of the sum of spectrum counts associated with all nitrotyrosine-containing peptides relative to the sum of all tyrosine-containing peptides,we found significantly different levels of endogenous protein nitration inthese three tissues that correlate well with the differential staining intensitiesexhibited by nitrotyrosine immunoblots of these samples where the greatestabundance of nitrated proteins is found in skeletal muscle followed by heartfollowed by brain (Fig. 11.3). Notably, the nitrotyrosine immunoblot of

− + MPTP

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Figure 11.3 Different levels of protein nitration in heart, skeletal (Sk) muscle, andbrain. Homogenate proteins from heart, hind limb skeletal muscle, and brainwere sepa-rated on SDS-PAGE prior to immunoblotting with the antinitrotyrosine antibody(A) for comparison with relative levels of nitrotyrosine-containing peptides identifiedfrom multidimensional LC-MS/MS analyses of parallel samples (B). Immunoblotsshow heart and skeletal muscle homogenates from three individual animals; shown areimmunoblots for normal (�) and for (þ) MPTP-lesioned brains, prepared as describedpreviously (Sacksteder et al., 2006). Proteomic-derived values for nitrotyrosine levelswere determined from the ratios of (i) the sumof spectrumcounts associatedwith iden-tified nitrotyrosines in peptides to (ii) the sum of total spectrum counts for identifiedtyrosines in peptides. Proteomic analyses were performed essentially as described inFig.11.1and detailed by Sacksteder and co-workers (2006), with the exception that mus-cle homogenates were prefractionated according to the scheme outlined in the left sideof Fig.11.1.


homogenate from the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-lesioned brain, a neurotoxin-induced model of Parkinson’s dis-ease, exhibits more intense staining relative to normal brain of the samemajor nitrated bands, highlighting the importance of identifying nitration-sensitive proteins as potential indicators of neurodegeneration and pathol-ogy. Indeed, from LC-MS/MS identification of endogenously nitratedproteins in normal brain, more than half of the identified nitrated proteinshave been previously reported to be associated with neurodegeneration,further supporting the link between nitration-sensitive proteins and theirvulnerability to disease.

6. Summary

Multidimensional LC MS/MS offers expanding possibilities in thequantitative mapping of the nitroproteome as a signature of inflammatoryevents in normal and disease-progressing tissues. Recent global proteomicshave begun to identify significantly greater numbers of nitrated proteinswithin the context of the complex mixture, as well as to define endogenouslevels of inflammation in different tissues. The detection of multiplenitrotyrosine-modified proteins in tissues is just the tip of the iceberg withregard to posttranslational modifications of the proteome. Future work willbe aimed toward greater coverage of these modified proteins.

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