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Liquid chromatography (LC)-selected reaction monitoring (SRM) is a powerful protein quantification technique in terms of sensitivity, reproducibility, and multiplexing capability. LC-SRM can accurately measure the concentrations of surrogate proteotypic peptides for targeted proteins in complex biological samples by using their stable heavy isotope-labeled counterparts as internal standards. Herein, we describe a step-by-step protocol of the application of LC-SRM to quantify candidate protein biomarkers in human urine.

The human urinary proteome provides an assessment of kidney injury with specific biomarkers for different kidney injury phenotypes. In an effort to fully map and decipher changes in the urine proteome and peptidome after kidney transplantation, renal allograft biopsy matched urine samples were collected from 396 kidney transplant recipients. Centralized and blinded histology data from paired graft biopsies was used to classify urine samples into diagnostic categories of acute rejection, chronic allograft nephropathy, BK virus nephritis, and stable graft. A total of 245 urine samples were analyzed by liquid chromatography-mass spectrometry using isobaric Tags for Relative and Absolute Quantitation (iTRAQ) reagents. From a group of over 900 proteins identified in transplant injury, a set of 131 peptides were assessed by selected reaction monitoring for their significance in accurately segregating organ injury causation and pathology in an independent cohort of 151 urine samples. Ultimately, a minimal set of 35 proteins were identified for their ability to segregate the 3 major transplant injury clinical groups, comprising the final panel of 11 urinary peptides for acute rejection (93% area under the curve [AUC]), 12 urinary peptides for chronic allograft nephropathy (99% AUC), and 12 urinary peptides for BK virus nephritis (83% AUC). Thus, urinary proteome discovery and targeted validation can identify urine protein panels for rapid and noninvasive differentiation of different causes of kidney transplant injury, without the requirement of an invasive biopsy.

Analysis of native or endogenous peptides in biofluids can provide valuable insights into disease mechanisms. Furthermore, the detected peptides may also have utility as potential biomarkers for non-invasive monitoring of human diseases. The non-invasive nature of urine collection and the abundance of peptides in the urine makes analysis by high-throughput 'peptidomics' methods , an attractive approach for investigating the pathogenesis of renal disease. However, urine peptidomics methodologies can be problematic with regards to difficulties associated with sample preparation. The urine matrix can provide significant background interference in making the analytical measurements that it hampers both the identification of peptides and the depth of the peptidomics read when utilizing LC-MS based peptidome analysis. We report on a novel adaptation of the standard solid phase extraction (SPE) method to a modified SPE (mSPE) approach for improved peptide yield and analysis sensitivity with LC-MS based peptidomics in terms of time, cost, clogging of the LC-MS column, peptide yield, peptide quality, and number of peptides identified by each method. Expense and time requirements were comparable for both SPE and mSPE, but more interfering contaminants from the urine matrix were evident in the SPE preparations (e.g., clogging of the LC-MS columns, yellowish background coloration of prepared samples due to retained urobilin, lower peptide yields) when compared to the mSPE method. When we compared data from technical replicates of 4 runs, the mSPE method provided significantly improved efficiencies for the preparation of samples from urine (e.g., mSPE peptide identification 82% versus 18% with SPE; p = 8.92E-05). Additionally, peptide identifications, when applying the mSPE method, highlighted the biology of differential activation of urine peptidases during acute renal transplant rejection with distinct laddering of specific peptides, which was obscured for most proteins when utilizing the conventional SPE method. In conclusion, the mSPE method was found to be superior to the conventional, standard SPE method for urine peptide sample preparation when applying LC-MS peptidomics analysis due to the optimized sample clean up that provided improved experimental inference from the confidently identified peptides.

Cell fusion in genetically identical Neurospora crassa germlings and in hyphae is a highly regulated process involving the activation of a conserved MAP kinase cascade that includes NRC-1, MEK-2 and MAK-2. During chemotrophic growth in germlings, the MAP kinase cascade members localize to conidial anastomosis tube (CAT) tips every ∼8 minutes, perfectly out of phase with another protein that is recruited to the tip: SOFT, a recently identified scaffold for the MAK-1 MAP kinase pathway in Sordaria macrospora. How the MAK-2 oscillation process is initiated, maintained and what proteins regulate the MAP kinase cascade is currently unclear. A global phosphoproteomics approach using an allele of mak-2 (mak-2Q100G) that can be specifically inhibited by the ATP analog 1NM-PP1 was utilized to identify MAK-2 kinase targets in germlings that were potentially involved in this process. One such putative target was HAM-5, a protein of unknown biochemical function. Previously, Δham-5 mutants were shown to be deficient for hyphal fusion. Here we show that HAM-5-GFP co-localized with NRC-1, MEK-2 and MAK-2 and oscillated with identical dynamics from the cytoplasm to CAT tips during chemotropic interactions. In the Δmak-2 strain, HAM-5-GFP localized to punctate complexes that did not oscillate, but still localized to the germling tip, suggesting that MAK-2 activity influences HAM-5 function/localization. However, MAK-2-GFP showed cytoplasmic and nuclear localization in a Δham-5 strain and did not localize to puncta. Via co-immunoprecipitation experiments, HAM-5 was shown to physically interact with NRC-1, MEK-2 and MAK-2, suggesting that it functions as a scaffold/transport hub for the MAP kinase cascade members for oscillation and chemotropic interactions during germling and hyphal fusion in N. crassa. The identification of HAM-5 as a scaffold-like protein will help to link the activation of MAK-2 cascade to upstream factors and proteins involved in this intriguing process of fungal communication.

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

BackgroundUrine exosomes are small vesicles exocytosed into the urine by all renal epithelial cell types under normal physiologic and disease states. Urine exosomal proteins may mirror disease specific proteome perturbations in kidney injury. Analysis methodologies for the exosomal fraction of the urinary proteome were developed for comparing the urinary exosomal fraction versus unfractionated proteome for biomarker discovery.MethodsUrine exosomes were isolated by centrifugal filtration of urine samples collected from kidney transplant patients with and without acute rejection (AR), which were biopsy matched. The proteomes of unfractionated whole urine (Uw) and urine exosomes (Ue) underwent mass spectroscopy-based quantitative proteomics analysis. The proteome data were analyzed for significant differential protein abundances in AR.ResultsA total of 1018 proteins were identified in Uw and 349 proteins in Ue. Two hundred seventy-nine overlapped between the two urinary compartments and 70 proteins were unique to the Ue compartment. Of 349 exosomal proteins identified from transplant patients, 220 had not been previously identified in the normal Ue fraction. Eleven Ue proteins, functionally involved in an inflammatory and stress response, were more abundant in urine samples from patients with AR, three of which are exclusive to the Ue fraction. Ue AR-specific biomarkers (1) were also detected in Uw, but since they were observed at significantly lower abundances in Uw, they were not significant for AR in Uw.ConclusionA rapid urinary exosome isolation method and quantitative measurement of enriched Ue proteins was applied. Perturbed proteins in the exosomal compartment of urine collected from kidney transplant patients were specific to inflammatory responses, and were not observed in the Ue fraction from normal healthy subjects. Ue-specific protein alterations in renal disease provide potential mechanistic insights and offer a unique panel of sensitive biomarkers for monitoring AR.

Abstract Background Central nervous system (CNS) infection is a nearly universal feature of untreated systemic HIV infection with a clinical spectrum that ranges from chronic asymptomatic infection to severe cognitive and motor dysfunction. Analysis of cerebrospinal fluid (CSF) has played an important part in defining the character of this evolving infection and response to treatment. To further characterize CNS HIV infection and its effects, we applied advanced high-throughput proteomic methods to CSF to identify novel proteins and their changes with disease progression and treatment. Results After establishing an accurate mass and time (AMT) tag database containing 23,141 AMT tags for CSF peptides, we analyzed 91 CSF samples by LC-MS from 12 HIV-uninfected and 14 HIV-infected subjects studied in the context of initiation of antiretroviral therapy and correlated abundances of identified proteins a) within and between subjects, b) with all other proteins across the entire sample set, and c) with "external" CSF biomarkers of infection (HIV RNA), immune activation (neopterin) and neural injury (neurofilament light chain protein, NFL). We identified a mean of 2,333 +/- 328 (SD) peptides covering 307 +/-16 proteins in the 91 CSF sample set. Protein abundances differed both between and within subjects sampled at different time points and readily separated those with and without HIV infection. Proteins also showed inter-correlations across the sample set that were associated with biologically relevant dynamic processes. One-hundred and fifty proteins showed correlations with the external biomarkers. For example, using a threshold of cross correlation coefficient (Pearson's) ≤ -0.3 and ≥0.3 for potentially meaningful relationships, a total of 99 proteins correlated with CSF neopterin (43 negative and 56 positive correlations) and related principally to neuronal plasticity and survival and to innate immunity. Pathway analysis defined several networks connecting the identified proteins, including one with amyloid precursor protein as a central node. Conclusions Advanced CSF proteomic analysis enabled the identification of an array of novel protein changes across the spectrum of CNS HIV infection and disease. This initial analysis clearly demonstrated the value of contemporary state-of-the-art proteomic CSF analysis as a discovery tool in HIV infection with likely similar application to other neurological inflammatory and degenerative diseases.

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript-mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications.

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson's disease (PD) are not completely understood. Here, we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 86 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA, following neurotoxin treatment. The combined protein and gene list provides a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response, and apoptosis. These results constitute one of the largest descriptive data sets integrating protein and transcript changes for these neurotoxin models with many similar end point phenotypes but distinct mechanisms.

Accurate assignment of monoisotopic precursor masses to tandem mass spectrometric (MS/MS) data is a fundamental and critically important step for successful peptide identifications in mass spectrometry based proteomics. Here we describe an integrated approach that combines three previously reported methods of treating MS/MS data for precursor mass refinement. This combined method, 'integrated post-experiment monoisotopic mass refinement' (iPE-MMR), integrates steps (1) generation of refined MS/MS data by DeconMSn; (2) additional refinement of the resultant MS/MS data by a modified version of PE-MMR; and (3) elimination of systematic errors of precursor masses using DtaRefinery. iPE-MMR is the first method that utilizes all MS information from multiple MS scans of a precursor ion including multiple charge states, in an MS scan, to determine precursor mass. With the combination of these methods, iPE-MMR increases sensitivity in peptide identification and provides increased accuracy when applied to complex high-throughput proteomics data. 10.1021/ac101388b

The phosphorylation of any site on a given protein can affect its activity, degradation rate, ability to dock with other proteins or bind divalent cations, and/or its localization. These effects can operate within the same protein; in fact, multisite phosphorylation is a key mechanism for achieving signal integration in cells. Hence, knowing the overall phosphorylation signature of a protein is essential for understanding the 'state' of a cell. However, current technologies to monitor the phosphorylation status of proteins are inefficient at determining the relative stoichiometries of phosphorylation at multiple sites. Here we report a new capability for comprehensive liquid chromatography mass spectrometry (LC/MS) analysis of intact phosphoproteins. The technology platform builds upon an integration of bottom-up and top-down approaches that is facilitated by intact protein reversed-phase (RP)LC concurrently coupled with Fourier transform ion cyclotron resonance (FTICR) MS and fraction collection. As the use of conventional RPLC systems for phosphopeptide identification has proven challenging due to the formation of metal ion complexes at various metal surfaces during LC/ MS and ESI-MS analysis, we have developed a 'metal-free' RPLC-ESI-MS platform for phosphoprotein characterization. This platform demonstrated a significant sensitivity enhancement for phosphorylated casein proteins enriched from a standard protein mixture and revealed the presence of over 20 casein isoforms arising from genetic variants with varying numbers of phosphorylation sites. The integrated workflow was also applied to an enriched yeast phosphoproteome to evaluate the feasibility of this strategy for characterizing complex biological systems and revealed ~16% of the detected yeast proteins to have multiple phosphorylation isoforms. The intact protein LC/MS platform for characterization of combinatorial post-translational modifications (PTMs), with special emphasis on multisite phosphorylation, holds great promise to significantly extend our understanding of the roles of multiple PTMs on signaling components that control the cellular responses to various stimuli.

Here, we report a new approach that integrates pulsed Q dissociation (PQD) and electron transfer dissociation (ETD) techniques for confident and quantitative identification of iTRAQ-labeled phosphopeptides. The use of isobaric tags for relative and absolute quantification enables a high-throughput quantification of peptides via reporter ion signals in the low m/z range of tandem mass spectra. PQD, a form of ion trap collision activated dissociation, allows for detection of low mass-to-charge fragment ions, and electron transfer dissociation is especially useful for sequencing peptides that contain posttranslational modifications. Analysis of the phosphoproteome of human fibroblast cells using a sensitive linear ion trap mass spectrometer demonstrated that this hybrid approach improves both identification and quantification of phosphopeptides. ETD improved phosphopeptide identification, while PQD provides improved quantification of iTRAQ-labeled phosphopeptides.

An efficient on-line digestion system that reduces the number of sample manipulation steps has been demonstrated for high-throughput proteomics. By incorporating a pressurized sample loop into a liquid chromatography-based separation system, both sample and enzyme (e.g., trypsin) can be simultaneously introduced to produce a complete, yet rapid digestion. Both standard proteins and a complex Shewanella oneidensis global protein extract were digested and analyzed using the automated online pressurized digestion system coupled to an ion mobility time-of-flight mass spectrometer, an ion trap mass spectrometer, or both. The system denatured, digested, and separated product peptides in a manner of minutes, malting it amenable to on-line high-throughput applications. In addition to simplifying and expediting sample processing, the system was easy to implement and no cross-contamination was observed among samples. As a result, the online digestion system offers a powerful approach for high-throughput screening of proteins that could prove valuable in biochemical research (rapid screening of protein-based drugs).

Protein proteolytic degradation is an essential component to proper cell function and its life cycle. Here, we study the protein degradation in yeast Saccharomyces cerevisiae cells on a proteome-wide scale by detection of the intermediate peptides produced from the intracellular degradation of proteins using sequencing-based tandem mass spectrometry. By tracing the detected ~1100 peptides and their ~200 protein-substrate origins we obtain evidence for new insights into the proteome-wide proteinselective degradation in yeast cells. This evidence shows that the yeast cytoplasm is the largest pool for the degradation of proteins with both biochemical and geometric specificities, whereas the yeast nucleus seems to be a proteolysis-inert organelle under the condition studied. Yeast V-ATPase subunits appear to be degraded during their disassembly, and yeast mitochondrial proteins functioning as precursors, transport carriers, and gates are preferentially degraded. Ubiquitylation may be unnecessary for the proteasomal degradation of yeast cytoplasmic regulatory and enzyme proteins according to our observations. This study shows that the intracellular peptides are informational targets for directly probing the protein degradation-involved molecular mechanisms and cell biology processes.

The high mass measurement accuracy and precision available with recently developed mass spectrometers is increasingly used in proteomics analyses to confidently identify tryptic peptides from complex mixtures of proteins, as well as post-translational modifications and peptides from nonannotated proteins. To take full advantage of high mass measurement accuracy instruments, it is necessary to limit systematic mass measurement errors. It is well known that errors in m/z measurements can be affected by experimental parameters that include, for example, outdated calibration coefficients, ion intensity, and temperature changes during the measurement. Traditionally, these variations have been corrected through the use of internal calibrants (well-characterized standards introduced with the sample being analyzed). In this paper, we describe an alternative approach where the calibration is provided through the use of a priori knowledge of the sample being analyzed. Such an approach has previously been demonstrated based on the dependence of systematic error on m/z alone. To incorporate additional explanatory variables, we employed multidimensional, nonparametric regression models, which were evaluated using several commercially available instruments. The applied approach is shown to remove any noticeable biases from the overall mass measurement errors and decreases the overall standard deviation of the mass measurement error distribution by 1.2--2-fold, depending on instrument type. Subsequent reduction of the random errors based on multiple measurements over consecutive spectra further improves accuracy and results in an overall decrease of the standard deviation by 1.8-3.7-fold. This new procedure will decrease the false discovery rates for peptide identifications using high-accuracy mass measurements.

We describe an improved artificial neural network (ANN)-based method for predicting peptide retention times in reversed-phase liquid chromatography. In addition to the peptide amino acid composition, this study investigated several other peptide descriptors to improve the predictive capability, such as peptide length, sequence, hydrophobicity and hydrophobic moment, and nearest-neighbor amino acid, as well as peptide predicted structural configurations (i.e., helix, sheet, coil). An ANN architecture that consisted of 1052 input nodes, 24 hidden nodes, and 1 output node was used to fully consider the amino acid residue sequence in each peptide. The network was trained using ~345 000 nonredundant peptides identified from a total of 12 059 LC-MS/MS analyses of more than 20 different organisms, and the predictive capability of the model was tested using 1303 confidently identified peptides that were not included in the training set. The model demonstrated an average elution time precision of ~1.5% and was able to distinguish among isomeric peptides based upon the inclusion of peptide sequence information. The prediction power represents a significant improvement over our earlier report (Petritis, K.; Kangas, L. J.; Ferguson, P. L.; Anderson, G. A.; Pasa-Tolic, L.; Lipton, M. S.; Auberry, K. J.; Strittmatter, E. F.; Shen, Y.; Zhao, R.; Smith, R. D. Anal Chem. 2003, 75, 1039-1048) and other previously reported models.

In skeletal muscle cells, voltage-dependent potentiation of [Ca.sup.2+] channel activity requires phosphorylation by cAMP-dependent protein kinase (PKA) anchored via an A-kinase anchoring protein (AKAP15), and the most rapid sites of phosphorylation are located in the C-terminal domain. Surprisingly, the site of interaction of the complex of PKA and AKAP15 with the [alpha]1-subunit of [Ca.sup.v]1.1 channels lies in the distal C terminus, which is cleaved from the remainder of the channel by in vivo proteolytic processing. Here we report that the distal C terminus is noncovalently associated with the remainder of the channel via an interaction with a site in the proximal C-terminal domain when expressed as a separate protein in mammalian nonmuscle cells. Deletion mapping of the C terminus of the [[alpha].sub.1]-subunit using the yeast two-hybrid assay revealed that a distal C-terminal peptide containing amino acids 1802-1841 specifically interacts with a region in the proximal C terminus containing amino acid residues 1556-1612. Analysis of the purified [alpha]1-subunit of [Ca.sub.v]1.1 channels from skeletal muscle by saturation sequencing of the intracellular peptides by tandem mass spectrometry identified the site of proteolytic processing as alanine 1664. Our results support the conclusion that a noncovalently associated complex of the [alpha]-subunit truncated at A1664 with the proteolytically cleaved distal C-terminal domain, AKAP15, and PKA is the primary physiological form of [Ca.sub.v]1.1 channels in skeletal muscle cells. calcium channels | contraction coupling | excitation | protein kinase | proteolysis

In proteomics, effective methods are needed for identifying the relatively limited subset of proteins displaying significant changes in abundance between two samples. One way to accomplish this task is to target for identification by MS/MS only the 'interesting' proteins based on the abundance ratio of isotopically labeled pairs of peptides. We have developed the software and hardware tools for online LC-FTICR MS/MS studies in which a set of initially unidentified peptides from a proteome analysis can be selected for identification based on their distinctive changes in abundance following a 'perturbation'. We report here the validation of this method using a mixture of standard proteins combined in different ratios after isotopic labeling. We also demonstrate the application of this method to the identification of Shewanella oneidensis peptides/proteins exhibiting differential abundance in suboxic versus aerobic cell cultures.

A new quantitative cysteinyl-peptide enrichment technology (QCET) was developed to achieve higher efficiency, greater dynamic range, and higher throughput in quantitative proteomics that use stable-isotope labeling techniques combined with high-resolution liquid chromatography (LC)-mass spectrometry (MS). This approach involves [sup.18]O labeling of tryptic peptides, high-efficiency enrichment of cysteine-containing peptides, and confident protein identification and quantification using the accurate mass and time tag strategy. Proteome profiling of naive and in vitro-differentiated human mammary epithelial cells using QCET resulted in the identification and quantification of 603 proteins in a single LC-Fourier transform ion cyclotron resonance MS analysis. Advantages of this technology include the following: (1) a simple, highly efficient method for enriching cysteinyl-peptides; (2) a high-throughput strategy suitable for extensive proteome analysis; and (3) improved labeling efficiency for better quantitative measurements. This technology enhances both the functional analysis of biological systems and the detection of potential clinical biomarkers.

Ultrasensitive nanoscale proteomics approaches for characterizing proteins from complex proteomic samples of < 50 ng of total mass are described. Protein identifications from 0.5 pg of whole proteome extracts were enabled by ultrahigh sensitivity (

Many cellular processes are regulated by reversible protein phosphorylation, and the ability to broadly identify and quantify phosphoproteins from proteomes would provide a basis for gaining a better understanding of these dynamic cellular processes. However, such a sensitive, efficient, and global method capable of addressing the phosphoproteome has yet to be developed. Here we describe an improved stable-isotope labeling method using a phosphoprotein isotope-coded solid-phase tag (PhIST) for isolating and measuring the relative abundances of phosphorylated peptides from complex peptide mixtures resulting from the enzymatic digestion of extracted proteins. The PhIST approach is an extension of the previously reported phosphoprotein isotope-coded affinity tag (PhIAT) approach developed by our laboratory, (1,2) where phosphoseryl and phosphothreonyl residues were derivatized by hydroxide ion-mediated [beta]-elimination followed by the Michael addition of 1,2-ethanedithiol (EDT). Instead of using the biotin affinity tag, peptides containing the EDT moiety were captured and labeled in one step using isotope-coded solid-phase reagents containing either light ([sup.12][C.sub.6], [sup.14]N) or heavy ([sup.13][C.sub.6], [sub.15]N) stable isotopes. The captured peptides labeled with the isotope-coded tags were released from the solid-phase support by UV photocleavage and analyzed by capillary liquid chromatography--tandem mass spectrometry. The efficiency and sensitivity of the PhIST labeling approach for identification of phosphopeptides from mixtures were determined using casein proteins. Its utility for proteomic applications was demonstrated by the labeling of soluble phosphoproteins from a human breast cancer cell line.

Abstract Background Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions. Results The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels. Conclusions This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.

A comprehensive proteomic data set identifying 7792 proteins from a whole mouse brain generated by LC/LC-MS/MS analyses was used to identify nitrated proteins. This analysis resulted in identification of 31 unique nitroyrosine sites within 29 different proteins and more than half of the nitrated proteins that are identified are involved in Parkinson's disease, Alzheimer's disease, or other neurodegenerative disorders.