LC-SRM-Based Targeted Quantification of Urinary Protein Biomarkers.

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.

Quantification of mutant SPOP proteins in prostate cancer using mass spectrometry-based targeted proteomics.

BACKGROUND: Speckle-type POZ protein (SPOP) is an E3 ubiquitin ligase adaptor protein that functions as a potential tumor suppressor, and SPOP mutations have been identified in ~10% of human prostate cancers. However, it remains unclear if mutant SPOP proteins can be utilized as biomarkers for early detection, diagnosis, prognosis or targeted therapy of prostate cancer. Moreover, the SPOP mutation sites are distributed in a relatively short region with multiple lysine residues, posing significant challenges for bottom-up proteomics analysis of the SPOP mutations. METHODS: To address this issue, PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometry assays have been developed for quantifying wild-type SPOP protein and 11 prostate cancer-derived SPOP mutations. RESULTS: Despite inherent limitations due to amino acid sequence constraints, all the PRISM-SRM assays developed using Arg-C digestion showed a linear dynamic range of at least two orders of magnitude, with limits of quantification ranged from 0.1 to 1 fmol/µg of total protein in the cell lysate. Applying these SRM assays to analyze HEK293T cells with and without expression of the three most frequent SPOP mutations in prostate cancer (Y87N, F102C or F133V) led to confident detection of all three SPOP mutations in corresponding positive cell lines but not in the negative cell lines. Expression of the F133V mutation and wild-type SPOP was at much lower levels compared to that of F102C and Y87N mutations; however, at present, it is unknown if this also affects the biological activity of the SPOP protein. CONCLUSIONS: In summary, PRISM-SRM enables multiplexed, isoform-specific detection of mutant SPOP proteins in cell lysates, providing significant potential in biomarker development for prostate cancer.

Mining the human urine proteome for monitoring renal transplant injury.

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.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification.

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

Quantitative Profiling of Protein S-Glutathionylation Reveals Redox-Dependent Regulation of Macrophage Function during Nanoparticle-Induced Oxidative Stress.

Engineered nanoparticles (ENPs) are increasingly utilized for commercial and medical applications; thus, understanding their potential adverse effects is an important societal issue. Herein, we investigated protein S-glutathionylation (SSG) as an underlying regulatory mechanism by which ENPs may alter macrophage innate immune functions, using a quantitative redox proteomics approach for site-specific measurement of SSG modifications. Three high-volume production ENPs (SiO2, Fe3O4, and CoO) were selected as representatives which induce low, moderate, and high propensity, respectively, to stimulate cellular reactive oxygen species (ROS) and disrupt macrophage function. The SSG modifications identified highlighted a broad set of redox sensitive proteins and specific Cys residues which correlated well with the overall level of cellular redox stress and impairment of macrophage phagocytic function (CoO > Fe3O4 ≫ SiO2). Moreover, our data revealed pathway-specific differences in susceptibility to SSG between ENPs which induce moderate versus high levels of ROS. Pathways regulating protein translation and protein stability indicative of ER stress responses and proteins involved in phagocytosis were among the most sensitive to SSG in response to ENPs that induce subcytoxic levels of redox stress. At higher levels of redox stress, the pattern of SSG modifications displayed reduced specificity and a broader set pathways involving classical stress responses and mitochondrial energetics (e.g., glycolysis) associated with apoptotic mechanisms. An important role for SSG in regulation of macrophage innate immune function was also confirmed by RNA silencing of glutaredoxin, a major enzyme which reverses SSG modifications. Our results provide unique insights into the protein signatures and pathways that serve as ROS sensors and may facilitate cellular adaption to ENPs, versus intracellular targets of ENP-induced oxidative stress that are linked to irreversible cell outcomes.

Compensatory Islet Response to Insulin Resistance Revealed by Quantitative Proteomics.

Compensatory islet response is a distinct feature of the prediabetic insulin-resistant state in humans and rodents. To identify alterations in the islet proteome that characterize the adaptive response, we analyzed islets from 5 month old male control, high-fat diet fed (HFD), or obese ob/ob mice by LC-MS/MS and quantified ~1100 islet proteins (at least two peptides) with a false discovery rate < 1%. Significant alterations in abundance were observed for ~350 proteins among groups. The majority of alterations were common to both models, and the changes of a subset of ~40 proteins and 12 proteins were verified by targeted quantification using selected reaction monitoring and western blots, respectively. The insulin-resistant islets in both groups exhibited reduced expression of proteins controlling energy metabolism, oxidative phosphorylation, hormone processing, and secretory pathways. Conversely, an increased expression of molecules involved in protein synthesis and folding suggested effects in endoplasmic reticulum stress response, cell survival, and proliferation in both insulin-resistant models. In summary, we report a unique comparison of the islet proteome that is focused on the compensatory response in two insulin-resistant rodent models that are not overtly diabetic. These data provide a valuable resource of candidate proteins to the scientific community to undertake further studies aimed at enhancing ß-cell mass in patients with diabetes. The data are available via the MassIVE repository, under accession no. MSV000079093.

Analytical platform evaluation for quantification of ERG in prostate cancer using protein and mRNA detection methods.

BACKGROUND: The established methods for detecting prostate cancer (CaP) are based on tests using PSA (blood), PCA3 (urine), and AMACR (tissue) as biomarkers in patient samples. The demonstration of ERG oncoprotein overexpression due to gene fusion in CaP has thus provided ERG as an additional biomarker. Based on this, we hypothesized that ERG protein quantification methods can be of use in the diagnosis of prostate cancer. METHODS: An antibody-free assay for ERG3 protein detection was developed based on PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) mass spectrometry. We utilized TMPRSS2-ERG positive VCaP and TMPRSS2-ERG negative LNCaP cells to simulate three different sample types (cells, tissue, and post-DRE urine sediment). Enzyme-linked immunosorbent assay (ELISA), western blot, NanoString, and qRT-PCR were also used in the analysis of these samples. RESULTS: Recombinant ERG3 protein spiked into LNCaP cell lysates could be detected at levels as low as 20 pg by PRISM-SRM analysis. The sensitivity of the PRISM-SRM assay was approximately 10,000 VCaP cells in a mixed cell population model of VCaP and LNCaP cells. Interestingly, ERG protein could be detected in as few as 600 VCaP cells spiked into female urine. The sensitivity of the in-house ELISA was similar to the PRISM-SRM assay, with detection of 30 pg of purified recombinant ERG3 protein and 10,000 VCaP cells. On the other hand, qRT-PCR exhibited a higher sensitivity, as TMPRSS2-ERG transcripts were detected in as few as 100 VCaP cells, in comparison to NanoString methodologies which detected ERG from 10,000 cells. CONCLUSIONS: Based on this data, we propose that the detection of both ERG transcriptional products with RNA-based assays, as well as protein products of ERG using PRISM-SRM assays, may be of clinical value in developing diagnostic and prognostic assays for prostate cancer given their sensitivity, specificity, and reproducibility.

Sensitive targeted quantification of ERK phosphorylation dynamics and stoichiometry in human cells without affinity enrichment.

Targeted mass spectrometry is a promising technology for site-specific quantification of posttranslational modifications. However, a major constraint is the limited sensitivity for quantifying low-abundance PTMs, requiring the use of affinity reagents for enrichment. Herein, we demonstrate the direct site-specific quantification of ERK phosphorylation isoforms (pT, pY, pTpY) and their relative stoichiometry using a sensitive targeted MS approach termed high-pressure, high-resolution separations with intelligent selection, and multiplexing (PRISM). PRISM provides effective enrichment of target peptides into a given fraction from complex mixture, followed by selected reaction monitoring quantification. Direct quantification of ERK phosphorylation in human mammary epithelial cells (HMEC) was demonstrated from as little as 25 µg tryptic peptides from whole cell lysates. Compared to immobilized metal-ion affinity chromatography, PRISM provided ∼10-fold higher signal intensities, presumably due to the better peptide recovery of PRISM. This approach was applied to quantify ERK phosphorylation dynamics in HMEC treated by different doses of epidermal growth factor at both the peak activation (10 min) and steady state (2 h). The maximal ERK activation was observed with 0.3 and 3 ng/mL doses for 10 min and 2 h time points, respectively. The dose-response profiles of individual phosphorylated isoforms showed that singly phosphorylated pT-ERK never increases significantly, while the increase of pY-ERK paralleled that of pTpY-ERK. This data supports for a processive, rather than distributed model of ERK phosphorylation. The PRISM-SRM quantification of protein phosphorylation illustrates the potential for simultaneous quantification of multiple PTMs.

HAM-5 functions as a MAP kinase scaffold during cell fusion in Neurospora crassa.

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.

Proteomic approaches for site-specific O-GlcNAcylation analysis.

O-GlcNAcylation is a dynamic protein post-translational modification of serine or threonine residues by an O-linked monosaccharide N-acetylglucosamine (O-GlcNAc). O-GlcNAcylation was discovered three decades ago and its significance has been implicated in several disease states, such as metabolic diseases, cancer and neurological diseases. Yet it remains technically challenging to characterize comprehensively and quantitatively because of its low abundance, low stoichiometry and extremely labile nature under conventional collision-induced dissociation tandem MS conditions. Herein, we review the recent advances addressing these challenges in developing proteomic approaches for site-specific O-GlcNAcylation analysis, including specific enrichment of O-GlcNAc peptides/proteins, unambiguous site-determination of O-GlcNAc modification and quantitative analysis of O-GlcNAcylation.

Antibody-independent targeted quantification of TMPRSS2-ERG fusion protein products in prostate cancer.

Fusions between the transmembrane protease serine 2 (TMPRSS2) and ETS related gene (ERG) represent one of the most specific biomarkers that define a distinct molecular subtype of prostate cancer. Studies of TMPRSS2-ERG gene fusions have seldom been performed at the protein level, primarily due to the lack of high-quality antibodies suitable for quantitative studies. Herein, we applied a recently developed PRISM (high-pressure high-resolution separations with intelligent selection and multiplexing)-SRM (selected reaction monitoring) strategy for quantifying ERG protein in prostate cancer cell lines and tumors. The highly sensitive PRISM-SRM assays provided confident detection of 6 unique ERG peptides in both TMPRSS2-ERG positive cell lines and tissues, but not in cell lines or tissues lacking the TMPRSS2-ERG rearrangement, clearly indicating that ERG protein expression is significantly increased in the presence of the TMPRSS2-ERG gene fusion. Significantly, our results provide evidence that two distinct ERG protein isoforms are simultaneously expressed in TMPRSS2-ERG positive samples as evidenced by the concomitant detection of two mutually exclusive peptides in two patient tumors and in the VCaP prostate cancer cell line. Three peptides, shared across almost all fusion protein products, were determined to be the most abundant peptides, providing "signature" peptides for detection of ERG over-expression resulting from TMPRSS2-ERG gene fusion. The PRISM-SRM assays provide valuable tools for studying TMPRSS2-ERG gene fusion protein products in prostate cancer.

Polysialylated N-glycans identified in human serum through combined developments in sample preparation, separations, and electrospray ionization-mass spectrometry.

The N-glycan diversity of human serum glycoproteins, i.e., the human blood serum N-glycome, is both complex and constrained by the range of glycan structures potentially synthesizable by human glycosylation enzymes. The known glycome, however, has been further limited by methods of sample preparation, available analytical platforms, e.g., based upon electrospray ionization-mass spectrometry (ESI-MS), and software tools for data analysis. In this report several improvements have been implemented in sample preparation and analysis to extend ESI-MS glycan characterization and to include polysialylated N-glycans. Sample preparation improvements included acidified, microwave-accelerated, PNGase F N-glycan release to promote lactonization, and sodium borohydride reduction, that were both optimized to improve quantitative yields and conserve the number of glycoforms detected. Two-stage desalting (during solid phase extraction and on the analytical column) increased sensitivity by reducing analyte signal division between multiple reducing-end-forms or cation adducts. Online separations were improved by using extended length graphitized carbon columns and adding TFA as an acid modifier to a formic acid/reversed phase gradient, providing additional resolving power and significantly improved desorption of both large and heavily sialylated glycans. To improve MS sensitivity and provide gentler ionization conditions at the source-MS interface, subambient pressure ionization with nanoelectrospray (SPIN) was utilized. When these improved methods are combined together with the Glycomics Quintavariate Informed Quantification (GlyQ-IQ) recently described (Kronewitter et al. Anal. Chem. 2014, 86, 6268-6276), we are able to significantly extend glycan detection sensitivity and provide expanded glycan coverage. We demonstrated the application of these advances in the context of the human serum glycome, and for which our initial observations included the detection of a new class of heavily sialylated N-glycans, including polysialylated N-glycans.

Expediting SRM assay development for large-scale targeted proteomics experiments.

Because of its high sensitivity and specificity, selected reaction monitoring (SRM)-based targeted proteomics has become increasingly popular for biological and translational applications. Selection of optimal transitions and optimization of collision energy (CE) are important assay development steps for achieving sensitive detection and accurate quantification; however, these steps can be labor-intensive, especially for large-scale applications. Herein, we explored several options for accelerating SRM assay development evaluated in the context of a relatively large set of 215 synthetic peptide targets. We first showed that HCD fragmentation is very similar to that of CID in triple quadrupole (QQQ) instrumentation and that by selection of the top 6 y fragment ions from HCD spectra, >86% of the top transitions optimized from direct infusion with QQQ instrumentation are covered. We also demonstrated that the CE calculated by existing prediction tools was less accurate for 3+ precursors and that a significant increase in intensity for transitions could be obtained using a new CE prediction equation constructed from the present experimental data. Overall, our study illustrated the feasibility of expediting the development of larger numbers of high-sensitivity SRM assays through automation of transition selection and accurate prediction of optimal CE to improve both SRM throughput and measurement quality.

Detecting differential protein expression in large-scale population proteomics.

MOTIVATION: Mass spectrometry (MS)-based high-throughput quantitative proteomics shows great potential in large-scale clinical biomarker studies, identifying and quantifying thousands of proteins in biological samples. However, there are unique challenges in analyzing the quantitative proteomics data. One issue is that the quantification of a given peptide is often missing in a subset of the experiments, especially for less abundant peptides. Another issue is that different MS experiments of the same study have significantly varying numbers of peptides quantified, which can result in more missing peptide abundances in an experiment that has a smaller total number of quantified peptides. To detect as many biomarker proteins as possible, it is necessary to develop bioinformatics methods that appropriately handle these challenges. RESULTS: We propose a Significance Analysis for Large-scale Proteomics Studies (SALPS) that handles missing peptide intensity values caused by the two mechanisms mentioned above. Our model has a robust performance in both simulated data and proteomics data from a large clinical study. Because varying patients' sample qualities and deviating instrument performances are not avoidable for clinical studies performed over the course of several years, we believe that our approach will be useful to analyze large-scale clinical proteomics data. AVAILABILITY AND IMPLEMENTATION: R codes for SALPS are available at http://www.stanford.edu/%7eclairesr/software.html.

GlyQ-IQ: glycomics quintavariate-informed quantification with high-performance computing and GlycoGrid 4D visualization.

Glycomics quintavariate-informed quantification (GlyQ-IQ) is a biologically guided glycomics analysis tool for identifying N-glycans in liquid chromatography-mass spectrometry (LC-MS) data. Glycomics LC-MS data sets have convoluted extracted ion chromatograms that are challenging to deconvolve with existing software tools. LC deconvolution into constituent pieces is critical in glycomics data sets because chromatographic peaks correspond to different intact glycan structural isomers. The biological targeted analysis approach offers several key advantages to traditional LC-MS data processing. A priori glycan information about the individual target's elemental composition allows for improved sensitivity by utilizing the exact isotope profile information to focus chromatogram generation and LC peak fitting on the isotopic species having the highest intensity. Glycan target annotation utilizes glycan family relationships and in source fragmentation in addition to high specificity feature LC-MS detection to improve the specificity of the analysis. The GlyQ-IQ software was developed in this work and evaluated in the context of profiling the N-glycan compositions from human serum LC-MS data sets. A case study is presented to demonstrate how GlyQ-IQ identifies and removes confounding chromatographic peaks from high mannose glycan isomers from human blood serum. In addition, GlyQ-IQ was used to generate a broad human serum N-glycan profile from a high resolution nanoelectrospray-liquid chromatography-tandem mass spectrometry (nESI-LC-MS/MS) data set. A total of 156 glycan compositions and 640 glycan isomers were detected from a single sample. Over 99% of the GlyQ-IQ glycan-feature assignments passed manual validation and are backed with high-resolution mass spectra.

Cytomegalovirus pp65 limits dissemination but is dispensable for persistence.

The most abundantly produced virion protein in human cytomegalovirus (HCMV) is the immunodominant phosphoprotein 65 (pp65), which is frequently included in CMV vaccines. Although it is nonessential for in vitro CMV growth, pp65 displays immunomodulatory functions that support a potential role in primary and/or persistent infection. To determine the contribution of pp65 to CMV infection and immunity, we generated a rhesus CMV lacking both pp65 orthologs (RhCMVΔpp65ab). While deletion of pp65ab slightly reduced growth in vitro and increased defective particle formation, the protein composition of secreted virions was largely unchanged. Interestingly, pp65 was not required for primary and persistent infection in animals. Immune responses induced by RhCMVΔpp65ab did not prevent reinfection with rhesus CMV; however, reinfection with RhCMVΔUS2-11, which lacks viral-encoded MHC-I antigen presentation inhibitors, was prevented. Unexpectedly, induction of pp65b-specific T cells alone did not protect against RhCMVΔUS2-11 challenge, suggesting that T cells targeting multiple CMV antigens are required for protection. However, pp65-specific immunity was crucial for controlling viral dissemination during primary infection, as indicated by the marked increase of RhCMVΔpp65ab genome copies in CMV-naive, but not CMV-immune, animals. Our data provide rationale for inclusion of pp65 into CMV vaccines but also demonstrate that pp65-induced T cell responses alone do not recapitulate the protective effect of natural infection.

Metabolic reprogramming during purine stress in the protozoan pathogen Leishmania donovani.

The ability of Leishmania to survive in their insect or mammalian host is dependent upon an ability to sense and adapt to changes in the microenvironment. However, little is known about the molecular mechanisms underlying the parasite response to environmental changes, such as nutrient availability. To elucidate nutrient stress response pathways in Leishmania donovani, we have used purine starvation as the paradigm. The salvage of purines from the host milieu is obligatory for parasite replication; nevertheless, purine-starved parasites can persist in culture without supplementary purine for over three months, indicating that the response to purine starvation is robust and engenders parasite survival under conditions of extreme scarcity. To understand metabolic reprogramming during purine starvation we have employed global approaches. Whole proteome comparisons between purine-starved and purine-replete parasites over a 6-48 h span have revealed a temporal and coordinated response to purine starvation. Purine transporters and enzymes involved in acquisition at the cell surface are upregulated within a few hours of purine removal from the media, while other key purine salvage components are upregulated later in the time-course and more modestly. After 48 h, the proteome of purine-starved parasites is extensively remodeled and adaptations to purine stress appear tailored to deal with both purine deprivation and general stress. To probe the molecular mechanisms affecting proteome remodeling in response to purine starvation, comparative RNA-seq analyses, qRT-PCR, and luciferase reporter assays were performed on purine-starved versus purine-replete parasites. While the regulation of a minority of proteins tracked with changes at the mRNA level, for many regulated proteins it appears that proteome remodeling during purine stress occurs primarily via translational and/or post-translational mechanisms.

Optimization for peptide sample preparation for urine peptidomics.

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.

LC-MS proteomics analysis of the insulin/IGF-1-deficient Caenorhabditis elegans daf-2(e1370) mutant reveals extensive restructuring of intermediary metabolism.

The insulin/IGF-1 receptor is a major known determinant of dauer formation, stress resistance, longevity, and metabolism in Caenorhabditis elegans. In the past, whole-genome transcript profiling was used extensively to study differential gene expression in response to reduced insulin/IGF-1 signaling, including the expression levels of metabolism-associated genes. Taking advantage of the recent developments in quantitative liquid chromatography mass spectrometry (LC-MS)-based proteomics, we profiled the proteomic changes that occur in response to activation of the DAF-16 transcription factor in the germline-less glp-4(bn2);daf-2(e1370) receptor mutant. Strikingly, the daf-2 profile suggests extensive reorganization of intermediary metabolism, characterized by the upregulation of many core intermediary metabolic pathways. These include glycolysis/gluconeogenesis, glycogenesis, pentose phosphate cycle, citric acid cycle, glyoxylate shunt, fatty acid ß-oxidation, one-carbon metabolism, propionate and tyrosine catabolism, and complexes I, II, III, and V of the electron transport chain. Interestingly, we found simultaneous activation of reciprocally regulated metabolic pathways, which is indicative of spatiotemporal coordination of energy metabolism and/or extensive post-translational regulation of these enzymes. This restructuring of daf-2 metabolism is reminiscent to that of hypometabolic dauers, allowing the efficient and economical utilization of internal nutrient reserves and possibly also shunting metabolites through alternative energy-generating pathways to sustain longevity.

Perturbations in the urinary exosome in transplant rejection.

BACKGROUND: Urine 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. METHODS: Urine 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. RESULTS: A 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. CONCLUSION: A 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.