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.

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.

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.

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.

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.

The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

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.

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.

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.

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.

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.

Reduced insulin/insulin-like growth factor-1 signaling and dietary restriction inhibit translation but preserve muscle mass in Caenorhabditis elegans.

Reduced signaling through the C. elegans insulin/insulin-like growth factor-1-like tyrosine kinase receptor daf-2 and dietary restriction via bacterial dilution are two well-characterized lifespan-extending interventions that operate in parallel or through (partially) independent mechanisms. Using accurate mass and time tag LC-MS/MS quantitative proteomics, we detected that the abundance of a large number of ribosomal subunits is decreased in response to dietary restriction, as well as in the daf-2(e1370) insulin/insulin-like growth factor-1-receptor mutant. In addition, general protein synthesis levels in these long-lived worms are repressed. Surprisingly, ribosomal transcript levels were not correlated to actual protein abundance, suggesting that post-transcriptional regulation determines ribosome content. Proteomics also revealed the increased presence of many structural muscle cell components in long-lived worms, which appeared to result from the prioritized preservation of muscle cell volume in nutrient-poor conditions or low insulin-like signaling. Activation of DAF-16, but not diet restriction, stimulates mRNA expression of muscle-related genes to prevent muscle atrophy. Important daf-2-specific proteome changes include overexpression of aerobic metabolism enzymes and general activation of stress-responsive and immune defense systems, whereas the increased abundance of many protein subunits of the proteasome core complex is a dietary-restriction-specific characteristic.

Tandem mass spectrometry identifies many mouse brain O-GlcNAcylated proteins including EGF domain-specific O-GlcNAc transferase targets.

O-linked N-acetylglucosamine (O-GlcNAc) is a reversible posttranslational modification of Ser and Thr residues on cytosolic and nuclear proteins of higher eukaryotes catalyzed by O-GlcNAc transferase (OGT). O-GlcNAc has recently been found on Notch1 extracellular domain catalyzed by EGF domain-specific OGT. Aberrant O-GlcNAc modification of brain proteins has been linked to Alzheimer's disease (AD). However, understanding specific functions of O-GlcNAcylation in AD has been impeded by the difficulty in characterization of O-GlcNAc sites on proteins. In this study, we modified a chemical/enzymatic photochemical cleavage approach for enriching O-GlcNAcylated peptides in samples containing ∼100 µg of tryptic peptides from mouse cerebrocortical brain tissue. A total of 274 O-GlcNAcylated proteins were identified. Of these, 168 were not previously known to be modified by O-GlcNAc. Overall, 458 O-GlcNAc sites in 195 proteins were identified. Many of the modified residues are either known phosphorylation sites or located proximal to known phosphorylation sites. These findings support the proposed regulatory cross-talk between O-GlcNAcylation and phosphorylation. This study produced the most comprehensive O-GlcNAc proteome of mammalian brain tissue with both protein identification and O-GlcNAc site assignment. Interestingly, we observed O-ß-GlcNAc on EGF-like repeats in the extracellular domains of five membrane proteins, expanding the evidence for extracellular O-GlcNAcylation by the EGF domain-specific OGT. We also report a GlcNAc-ß-1,3-Fuc-α-1-O-Thr modification on the EGF-like repeat of the versican core protein, a proposed substrate of Fringe ß-1,3-N-acetylglucosaminyltransferases.

Antibody-free, targeted mass-spectrometric approach for quantification of proteins at low picogram per milliliter levels in human plasma/serum.

Sensitive detection of low-abundance proteins in complex biological samples has typically been achieved by immunoassays that use antibodies specific to target proteins; however, de novo development of antibodies is associated with high costs, long development lead times, and high failure rates. To address these challenges, we developed an antibody-free strategy that involves PRISM (high-pressure, high-resolution separations coupled with intelligent selection and multiplexing) for sensitive selected reaction monitoring (SRM)-based targeted protein quantification. The strategy capitalizes on high-resolution reversed-phase liquid chromatographic separations for analyte enrichment, intelligent selection of target fractions via on-line SRM monitoring of internal standards, and fraction multiplexing before nano-liquid chromatography-SRM quantification. Application of this strategy to human plasma/serum demonstrated accurate and reproducible quantification of proteins at concentrations in the 50-100 pg/mL range, which represents a major advance in the sensitivity of targeted protein quantification without the need for specific-affinity reagents. Application to a set of clinical serum samples illustrated an excellent correlation between the results obtained from the PRISM-SRM assay and those from clinical immunoassay for the prostate-specific antigen level.

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.

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.

A highly sensitive targeted mass spectrometric assay for quantification of AGR2 protein in human urine and serum.

Anterior gradient 2 (AGR2) is a secreted, cancer-associated protein in many types of epithelial cancer cells. We developed a highly sensitive targeted mass spectrometric assay for quantification of AGR2 in urine and serum. Digested peptides from clinical samples were processed by PRISM (high pressure and high resolution separations coupled with intelligent selection and multiplexing), which incorporates high pH reversed-phase liquid chromatography (LC) separations to fractionate and select target fractions for follow-on LC-selected reaction monitoring (LC-SRM) analyses. The PRISM-SRM assay for AGR2 showed a reproducibility of <10% CV and limit of quantification (LOQ) values of ∼130 pg/mL in serum and ∼10 pg per 100 µg of total protein mass in urine, respectively. A good correlation (R(2) = 0.91) was observed for the measurable AGR2 concentrations in urine between SRM and enzyme-linked immunosorbent assay (ELISA). On the basis of an initial cohort of 37 subjects, urinary AGR2/PSA concentration ratios showed a significant difference (P = 0.026) between noncancer and cancer. Large clinical cohort studies are needed for the validation of AGR2 as a useful diagnostic biomarker for prostate cancer. Our work validated the approach of identifying candidate secreted protein biomarkers through genomics and measurement by targeted proteomics, especially for proteins where no immunoassays are available.

Phosphate-containing polyethylene glycol polymers prevent lethal sepsis by multidrug-resistant pathogens.

Antibiotic resistance among highly pathogenic strains of bacteria and fungi is a growing concern in the face of the ability to sustain life during critical illness with advancing medical interventions. The longer patients remain critically ill, the more likely they are to become colonized by multidrug-resistant (MDR) pathogens. The human gastrointestinal tract is the primary site of colonization of many MDR pathogens and is a major source of life-threatening infections due to these microorganisms. Eradication measures to sterilize the gut are difficult if not impossible and carry the risk of further antibiotic resistance. Here, we present a strategy to contain rather than eliminate MDR pathogens by using an agent that interferes with the ability of colonizing pathogens to express virulence in response to host-derived and local environmental factors. The antivirulence agent is a phosphorylated triblock high-molecular-weight polymer (here termed Pi-PEG 15-20) that exploits the known properties of phosphate (Pi) and polyethylene glycol 15-20 (PEG 15-20) to suppress microbial virulence and protect the integrity of the intestinal epithelium. The compound is nonmicrobiocidal and appears to be highly effective when tested both in vitro and in vivo. Structure functional analyses suggest that the hydrophobic bis-aromatic moiety at the polymer center is of particular importance to the biological function of Pi-PEG 15-20, beyond its phosphate content. Animal studies demonstrate that Pi-PEG prevents mortality in mice inoculated with multiple highly virulent pathogenic organisms from hospitalized patients in association with preservation of the core microbiome.

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.

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.

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.