Showing papers in "Journal of Proteome Research in 2016"

Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies.

Abstract: Missing values are a genuine issue in label-free quantitative proteomics. Recent works have surveyed the different statistical methods to conduct imputation and have compared them on real or simulated data sets and recommended a list of missing value imputation methods for proteomics application. Although insightful, these comparisons do not account for two important facts: (i) depending on the proteomics data set, the missingness mechanism may be of different natures and (ii) each imputation method is devoted to a specific type of missingness mechanism. As a result, we believe that the question at stake is not to find the most accurate imputation method in general but instead the most appropriate one. We describe a series of comparisons that support our views: For instance, we show that a supposedly "under-performing" method (i.e., giving baseline average results), if applied at the "appropriate" time in the data-processing pipeline (before or after peptide aggregation) on a data set with the "appropriate" nature of missing values, can outperform a blindly applied, supposedly "better-performing" method (i.e., the reference method from the state-of-the-art). This leads us to formulate few practical guidelines regarding the choice and the application of an imputation method in a proteomics context.

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1

Abstract: Every data-rich community research effort requires a clear plan for ensuring the quality of the data interpretation and comparability of analyses. To address this need within the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), we have developed through broad consultation a set of mass spectrometry data interpretation guidelines that should be applied to all HPP data contributions. For submission of manuscripts reporting HPP protein identification results, the guidelines are presented as a one-page checklist containing 15 essential points followed by two pages of expanded description of each. Here we present an overview of the guidelines and provide an in-depth description of each of the 15 elements to facilitate understanding of the intentions and rationale behind the guidelines, for both authors and reviewers. Broadly, these guidelines provide specific directions regarding how HPP data are to be submitted to mass spectrometry data repositories, how error analysis should be presented, and how detection of novel proteins should be supported with additional confirmatory evidence. These guidelines, developed by the HPP community, are presented to the broader scientific community for further discussion.

Evaluation and Improvement of Quantification Accuracy in Isobaric Mass Tag-Based Protein Quantification Experiments

Abstract: The multiplexing capabilities of isobaric mass tag-based protein quantification, such as Tandem Mass Tags or Isobaric Tag for Relative and Absolute Quantitation have dramatically increased the scope of mass spectrometry-based proteomics studies. Not only does the technology allow for the simultaneous quantification of multiple samples in a single MS injection, but its seamless compatibility with extensive sample prefractionation methods allows for comprehensive studies of complex proteomes. However, reporter ion-based quantification has often been criticized for limited quantification accuracy due to interference from coeluting peptides and peptide fragments. In this study, we investigate the extent of this problem and propose an effective and easy-to-implement remedy that relies on spiking a 6-protein calibration mixture to the samples. We evaluated our ratio adjustment approach using two large scale TMT 10-plex data sets derived from a human cancer and noncancer cell line as well as E. coli cells grown ...

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

Abstract: NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

Proteomics Quality Control: Quality Control Software for MaxQuant Results

Abstract: Mass spectrometry-based proteomics coupled to liquid chromatography has matured into an automatized, high-throughput technology, producing data on the scale of multiple gigabytes per instrument per day. Consequently, an automated quality control (QC) and quality analysis (QA) capable of detecting measurement bias, verifying consistency, and avoiding propagation of error is paramount for instrument operators and scientists in charge of downstream analysis. We have developed an R-based QC pipeline called Proteomics Quality Control (PTXQC) for bottom-up LC–MS data generated by the MaxQuant1 software pipeline. PTXQC creates a QC report containing a comprehensive and powerful set of QC metrics, augmented with automated scoring functions. The automated scores are collated to create an overview heatmap at the beginning of the report, giving valuable guidance also to nonspecialists. Our software supports a wide range of experimental designs, including stable isotope labeling by amino acids in cell culture (SILAC)...

Metabolic Profiling Regarding Pathogenesis of Idiopathic Pulmonary Fibrosis

Abstract: Idiopathic pulmonary fibrosis (IPF) is a progressive, eventually fatal disease characterized by fibrosis of the lung parenchyma and loss of lung function. IPF is believed to be caused by repetitive alveolar epithelial cell injury and dysregulated repair process including uncontrolled proliferation of lung (myo) fibroblasts and excessive deposition of extracellular matrix proteins in the interstitial space; however, the pathogenic pathways involved in IPF have not been fully elucidated. In this study, we attempted to characterize metabolic changes of lung tissues involved in the pathogenesis of IPF using gas chromatography-mass spectrometry-based metabolic profiling. Partial least-squares discriminant analysis (PLS-DA) model generated from metabolite data was able to discriminate between the control subjects and IPF patients (R(2)X = 0.37, R(2)Y = 0.613 and Q(2) (cumulative) = 0.54, receiver operator characteristic AUC > 0.9). We discovered 25 metabolite signatures of IPF using both univariate and multivariate statistical analyses (FDR 1). These metabolite signatures indicated alteration in metabolic pathways: adenosine triphosphate degradation pathway, glycolysis pathway, glutathione biosynthesis pathway, and ornithine aminotransferase pathway. The results could provide additional insight into understanding the disease and potential for developing biomarkers.

Global Proteome Analyses of Lysine Acetylation and Succinylation Reveal the Widespread Involvement of both Modification in Metabolism in the Embryo of Germinating Rice Seed

Abstract: Regulation of rice seed germination has been shown to mainly occur at post-transcriptional levels, of which the changes on proteome status is a major one. Lysine acetylation and succinylation are two prevalent protein post-translational modifications (PTMs) involved in multiple biological processes, especially for metabolism regulation. To investigate the potential mechanism controlling metabolism regulation in rice seed germination, we performed the lysine acetylation and succinylation analyses simultaneously. Using high-accuracy nano-LC-MS/MS in combination with the enrichment of lysine acetylated or succinylated peptides from digested embryonic proteins of 24 h after imbibition (HAI) rice seed, a total of 699 acetylated sites from 389 proteins and 665 succinylated sites from 261 proteins were identified. Among these modified lysine sites, 133 sites on 78 proteins were commonly modified by two PTMs. The overlapped PTM sites were more likely to be in polar acidic/basic amino acid regions and exposed on the protein surface. Both of the acetylated and succinylated proteins cover nearly all aspects of cellular functions. Ribosome complex and glycolysis/gluconeogenesis-related proteins were significantly enriched in both acetylated and succinylated protein profiles through KEGG enrichment and protein-protein interaction network analyses. The acetyl-CoA and succinyl-CoA metabolism-related enzymes were found to be extensively modified by both modifications, implying the functional interaction between the two PTMs. This study provides a rich resource to examine the modulation of the two PTMs on the metabolism pathway and other biological processes in germinating rice seed.

Unbiased Metabolomic Investigation of Alzheimer's Disease Brain Points to Dysregulation of Mitochondrial Aspartate Metabolism

Abstract: Alzheimer's disease (AD) is the most common cause of adult dementia. Yet the complete set of molecular changes accompanying this inexorable, neurodegenerative disease remains elusive. Here we adopted an unbiased lipidomics and metabolomics approach to surveying frozen frontal cortex samples from clinically characterized AD patients (n = 21) and age-matched controls (n = 19), revealing marked molecular differences between them. Then, by means of metabolomic pathway analysis, we incorporated the novel molecular information into the known biochemical pathways and compared it with the results of a metabolomics meta-analysis of previously published AD research. We found six metabolic pathways of the central metabolism as well as glycerophospholipid metabolism predominantly altered in AD brains. Using targeted metabolomics approaches and MS imaging, we confirmed a marked dysregulation of mitochondrial aspartate metabolism. The altered metabolic pathways were further integrated with clinical data, showing various degrees of correlation with parameters of dementia and AD pathology. Our study highlights specific, altered biochemical pathways in the brains of individuals with AD compared with those of control subjects, emphasizing dysregulation of mitochondrial aspartate metabolism and supporting future venues of investigation.

Toward Automated N-Glycopeptide Identification in Glycoproteomics

Abstract: Advances in software-driven glycopeptide identification have facilitated N-glycoproteomics studies reporting thousands of intact N-glycopeptides, i.e., N-glycan-conjugated peptides, but the automated identification process remains to be scrutinized. Herein, we compare the site-specific glycoprofiling efficiency of the PTM-centric search engine Byonic relative to manual expert annotation utilizing typical glycoproteomics acquisition and data analysis strategies but with a single glycoprotein, the uncharacterized multiple N-glycosylated human basigin. Detailed site-specific reference glycoprofiles of purified basigin were manually established using ion-trap CID–MS/MS and high-resolution Q-Exactive Orbitrap HCD–MS/MS of tryptic N-glycopeptides and released N-glycans. The micro- and macroheterogeneous basigin N-glycosylation was site-specifically glycoprofiled using Byonic with or without a background of complex peptides using Q-Exactive Orbitrap HCD–MS/MS. The automated glycoprofiling efficiencies were asses...

Tau Protein Quantification in Human Cerebrospinal Fluid by Targeted Mass Spectrometry at High Sequence Coverage Provides Insights into Its Primary Structure Heterogeneity

Abstract: Tau protein plays a major role in neurodegenerative disorders, appears to be a central biomarker of neuronal injury in cerebrospinal fluid (CSF), and is a promising target for Alzheimer's disease immunotherapies. To quantify tau at high sensitivity and gain insights into its naturally occurring structural variations in human CSF, we coupled absolute quantification using protein standard with the multiplex detection capability of targeted high-resolution mass spectrometry (MS) on a Quadrupole-Orbitrap instrument. Using recombinant tau we developed a step-by-step workflow optimization including an extraction protocol that avoided affinity reagents and achieved the monitoring of 22 tau peptides uniformly distributed along the tau sequence. The lower limits of quantification ranged (LLOQ) from 150 to 1500 pg/mL depending on the peptide. Applied to endogenous CSF tau, up to 19 peptides were detected. Interestingly, there were significant differences in the abundance of peptides depending on their position in the sequence, with peptides from the tau mid-domain appearing significantly more abundant than peptides from the N- and C-terminus domains. This MS-based strategy provided results complementary to those of previous ELISA or Western Blot studies of CSF tau and could be applied to tau monitoring in human CSF cohorts.

LaCyTools: A Targeted Liquid Chromatography–Mass Spectrometry Data Processing Package for Relative Quantitation of Glycopeptides

Abstract: Bottom-up glycoproteomics by liquid chromatography–mass spectrometry (LC–MS) is an established approach for assessing glycosylation in a protein- and site-specific manner. Consequently, tools are needed to automatically align, calibrate, and integrate LC–MS glycoproteomics data. We developed a modular software package designed to tackle the individual aspects of an LC–MS experiment, called LaCyTools. Targeted alignment is performed using user defined m/z and retention time (tr) combinations. Subsequently, sum spectra are created for each user defined analyte group. Quantitation is performed on the sum spectra, where each user defined analyte can have its own tr, minimum, and maximum charge states. Consequently, LaCyTools deals with multiple charge states, which gives an output per charge state if desired, and offers various analyte and spectra quality criteria. We compared throughput and performance of LaCyTools to combinations of available tools that deal with individual processing steps. LaCyTools yield...

AltitudeOmics: Red Blood Cell Metabolic Adaptation to High Altitude Hypoxia

Abstract: Red blood cells (RBCs) are key players in systemic oxygen transport. RBCs respond to in vitro hypoxia through the so-called oxygen-dependent metabolic regulation, which involves the competitive binding of deoxyhemoglobin and glycolytic enzymes to the N-terminal cytosolic domain of band 3. This mechanism promotes the accumulation of 2,3-DPG, stabilizing the deoxygenated state of hemoglobin, and cytosol acidification, triggering oxygen off-loading through the Bohr effect. Despite in vitro studies, in vivo adaptations to hypoxia have not yet been completely elucidated. Within the framework of the AltitudeOmics study, erythrocytes were collected from 21 healthy volunteers at sea level, after exposure to high altitude (5260 m) for 1, 7, and 16 days, and following reascent after 7 days at 1525 m. UHPLC–MS metabolomics results were correlated to physiological and athletic performance parameters. Immediate metabolic adaptations were noted as early as a few hours from ascending to >5000 m, and maintained for 16 da...

Measuring Biological Age via Metabonomics: The Metabolic Age Score.

Abstract: Chronological age is one of the most important risk factors for adverse clinical outcome. Still, two individuals at the same chronological age could have different biological aging states, leading to different individual risk profiles. Capturing this individual variance could constitute an even more powerful predictor enhancing prediction in age-related morbidity. Applying a nonlinear regression technique, we constructed a metabonomic measurement for biological age, the metabolic age score, based on urine data measured via 1H NMR spectroscopy. We validated the score in two large independent population-based samples by revealing its significant associations with chronological age and age-related clinical phenotypes as well as its independent predictive value for survival over approximately 13 years of follow-up. Furthermore, the metabolic age score was prognostic for weight loss in a sample of individuals who underwent bariatric surgery. We conclude that the metabolic age score is an informative measuremen...

Quantitation and Identification of Thousands of Human Proteoforms below 30 kDa

Abstract: Top-down proteomics is capable of identifying and quantitating unique proteoforms through the analysis of intact proteins. We extended the coverage of the label-free technique, achieving differential analysis of whole proteins <30 kDa from the proteomes of growing and senescent human fibroblasts. By integrating improved control software with more instrument time allocated for quantitation of intact ions, we were able to collect protein data between the two cell states, confidently comparing 1577 proteoform levels. To then identify and characterize proteoforms, our advanced acquisition software, named Autopilot, employed enhanced identification efficiency in identifying 1180 unique Swiss-Prot accession numbers at 1% false-discovery rate. This coverage of the low mass proteome is equivalent to the largest previously reported but was accomplished in 23% of the total acquisition time. By maximizing both the number of quantified proteoforms and their identification rate in an integrated software environment, t...

A Description of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Common Data Analysis Pipeline

Abstract: The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has produced large proteomics data sets from the mass spectrometric interrogation of tumor samples previously analyzed by The Cancer Genome Atlas (TCGA) program. The availability of the genomic and proteomic data is enabling proteogenomic study for both reference (i.e., contained in major sequence databases) and nonreference markers of cancer. The CPTAC laboratories have focused on colon, breast, and ovarian tissues in the first round of analyses; spectra from these data sets were produced from 2D liquid chromatography–tandem mass spectrometry analyses and represent deep coverage. To reduce the variability introduced by disparate data analysis platforms (e.g., software packages, versions, parameters, sequence databases, etc.), the CPTAC Common Data Analysis Platform (CDAP) was created. The CDAP produces both peptide-spectrum-match (PSM) reports and gene-level reports. The pipeline processes raw mass spectrometry data according to the following: (1) ...

Proteomics Analysis Reveals a Potential Antibiotic Cocktail Therapy Strategy for Aeromonas hydrophila Infection in Biofilm

Abstract: Antibiotic fitness and acquired resistance are the two critical factors when bacteria respond to antibiotics, and the correlations and mechanisms between these two factors remain largely unknown. In this study, a TMT-labeling-based quantitative proteomics method was used to compare the differential expression of proteins between the fitness and acquired resistance to chlortetracycline in Aeromonas hydrophila biofilm. Bioinformatics analysis showed that translation-related ribosomal proteins, such as 30s ribosome subunits, increased in both factors; fatty acid biosynthesis related proteins, such as FabB, FabD, FabG, AccA, and AccD, increased in biofilm fitness, and some pathways (including propanoate-metabolism-related protein, such as PrpB, AtoB, PflB, AcsA, PrpD, and GabT) displayed decreased abundance in acquired resistance biofilm. The varieties of selected proteins involved in fatty acid biosynthesis and propanoate metabolism were further validated by q-PCR assay or Western blotting. Furthermore, the antibiotic-resistance-function assays showed that fatty-acid biosynthesis should be a protective antibiotics-resistance mechanism and a cocktail of chlortetracycline and triclosan, a fatty-acid-biosynthesis inhibitor, exhibited more efficient antimicrobial capability than did each antibiotic individually on biofilm, specifically on chlortetracycline-sensitive biofilm. We therefore demonstrate that the up-regulation of fatty acid biosynthesis may play an important role in antibiotic resistance and suggest that a cocktail of chlortetracycline and triclosan may be a potential cocktail therapy for pathogenic infections in biofilm.

Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

Abstract: The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study “DiOGenes”. Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with...

Changes in Healthy Human IgG Fc-Glycosylation after Birth and during Early Childhood.

Abstract: Glycosylation on the fragment crystallizable (Fc) region of immunoglobulin G (IgG) has a large influence on the interaction of the antibody with Fc gamma receptors (FcγRs). IgG consists of four subclasses that all have distinct affinities for the different FcγRs. Knowledge about the Fc-glycosylation in healthy human is valuable as reference for new biomarkers and in the design of biopharmaceuticals that rely on IgG Fc-glycosylation. Previously, subclass-specific characterization of IgG Fc-glycosylation was performed for healthy adults, pregnant women, and newborns. For young healthy children, however, the subclass-specific description of IgG Fc-glycosylation is still lacking. Therefore, we performed the IgG subclass-specific analysis of the Fc-glycosylation of 130 healthy humans between birth and 40 years of age, including 22 samples derived from the umbilical cords of newborns. The analysis was performed by a previously published matrix-assisted laser desorption/ionization (MALDI)-time-of-flight (TOF)-mass spectrometry (MS) workflow, including a derivatization step for the linkage-specific stabilization of sialic acids. The characterization revealed that when children start to produce their own IgG they have a decreased galactosylation, sialylation, and bisection and an increased fucosylation compared with newborns. During childhood, the fucosylation and sialylation decrease, whereas bisection increases and galactosylation stays constant.

Serum and Muscle Metabolomics for the Prediction of Ultimate pH, a Key Factor for Chicken-Meat Quality

Abstract: Variations in muscle glycogen storage are highly correlated with variations in meat ultimate pH (pHu), a key factor for poultry meat quality. A total of two chicken lines were divergently selected on breast pHu to understand the biological basis for variations in meat quality (i.e., the pHu– and the pHu+ lines that are characterized by a 17% difference in muscle glycogen content). The effects of this selection on bird metabolism were investigated by quantifying muscle metabolites by high-resolution NMR (1H and 31P) and serum metabolites by 1H NMR. A total of 20 and 26 discriminating metabolites between the two lines were identified by orthogonal partial least-squares discriminant analysis (OPLS-DA) in the serum and muscle, respectively. There was over-representation of carbohydrate metabolites in the serum and muscle of the pHu– line, consistent with its high level of muscle glycogen. However, the pHu+ line was characterized by markers of oxidative stress and muscle catabolism, probably because of its low...

moCluster: Identifying Joint Patterns Across Multiple Omics Data Sets

Abstract: Increasingly, multiple omics approaches are being applied to understand the complexity of biological systems. Yet, computational approaches that enable the efficient integration of such data are not well developed. Here, we describe a novel algorithm, termed moCluster, which discovers joint patterns among multiple omics data. The method first employs a multiblock multivariate analysis to define a set of latent variables representing joint patterns across input data sets, which is further passed to an ordinary clustering algorithm in order to discover joint clusters. Using simulated data, we show that moCluster's performance is not compromised by issues present in iCluster/iCluster+ (notably, the nondeterministic solution) and that it operates 100× to 1000× faster than iCluster/iCluster+. We used moCluster to cluster proteomic and transcriptomic data from the NCI-60 cell line panel. The resulting cluster model revealed different phenotypes across cellular subtypes, such as doubling time and drug response. Applying moCluster to methylation, mRNA, and protein data from a large study on colorectal cancer patients identified four molecular subtypes, including one characterized by microsatellite instability and high expression of genes/proteins involved in immunity, such as PDL1, a target of multiple drugs currently in development. The other three subtypes have not been discovered before using single data sets, which clearly illustrates the molecular complexity of oncogenesis and the need for holistic, multidata analysis strategies.

HILIC and ERLIC Enrichment of Glycopeptides Derived from Breast and Brain Cancer Cells.

Abstract: Aberrant glycosylation has been linked to many different cancer types. The blood–brain barrier (BBB) is a region of the brain that regulates the entrance of ions, diseases, toxins, and so on. However, in breast cancer metastasis, the BBB fails to prevent the crossing of the cancer cells into the brain. Here we present a study of identifying and quantifying the glycosylation of six breast and brain cancer cell lines using hydrophilic interaction liquid chromatography (HILIC) and electrostatic repulsion liquid chromatography (ERLIC) enrichments and LC–MS/MS analysis. Qualitative and quantitative analyses of N-linked glycosylation were performed by both enrichment techniques for individual and complementary comparison. Potential cancer glycopeptide biomarkers were identified and confirmed by chemometric and statistical evaluations. A total of 497 glycopeptides were characterized, of which 401 were common glycopeptides (80.6% overlap) identified from both enrichment techniques. HILIC enrichment yielded 320 st...

Screening and Functional Analyses of Nilaparvata lugens Salivary Proteome.

Abstract: Most phloem-feeding insects secrete gelling and watery saliva during the feeding process. However, the functions of salivary proteins are poorly understood. In this study, our purpose was to reveal the components and functions of saliva in a rice sap-sucking insect pest, Nilaparvata lugens. The accomplishment of the whole genome and transcriptome sequencing in N. lugens would be helpful for elucidating the gene information and expression specificity of the salivary proteins. In this study, we have, for the first time, identified the abundant protein components from gelling and watery saliva in a monophagous sap-sucking insect species through shotgun proteomic detection combined with the genomic and transcriptomic analysis. Eight unknown secreted proteins were limited to N. lugens, indicating species-specific saliva components. A group of annexin-like proteins first identified in the secreted saliva displayed different domain structure and expression specificity with typical insect annexins. Nineteen genes...

JUMPg: An Integrative Proteogenomics Pipeline Identifying Unannotated Proteins in Human Brain and Cancer Cells.

Abstract: Proteogenomics is an emerging approach to improve gene annotation and interpretation of proteomics data. Here we present JUMPg, an integrative proteogenomics pipeline including customized database construction, tag-based database search, peptide-spectrum match filtering, and data visualization. JUMPg creates multiple databases of DNA polymorphisms, mutations, splice junctions, partially trypticity, as well as protein fragments translated from the whole transcriptome in all six frames upon RNA-seq de novo assembly. We use a multistage strategy to search these databases sequentially, in which the performance is optimized by re-searching only unmatched high-quality spectra and reusing amino acid tags generated by the JUMP search engine. The identified peptides/proteins are displayed with gene loci using the UCSC genome browser. Then, the JUMPg program is applied to process a label-free mass spectrometry data set of Alzheimer’s disease postmortem brain, uncovering 496 new peptides of amino acid substitutions,...

Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications

Abstract: The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list—the draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications (PTMs), and splice isoforms of those proteins; and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data sets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.1 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [www.thehpp.org/guidelines]. The Human Proteome presented as...

The Muscle Metabolome Differs between Healthy and Frail Older Adults

Abstract: Populations around the world are aging rapidly. Age-related loss of physiological functions negatively affects quality of life. A major contributor to the frailty syndrome of aging is loss of skeletal muscle. In this study we assessed the skeletal muscle biopsy metabolome of healthy young, healthy older and frail older subjects to determine the effect of age and frailty on the metabolic signature of skeletal muscle tissue. In addition, the effects of prolonged whole-body resistance-type exercise training on the muscle metabolome of older subjects were examined. The baseline metabolome was measured in muscle biopsies collected from 30 young, 66 healthy older subjects, and 43 frail older subjects. Follow-up samples from frail older (24 samples) and healthy older subjects (38 samples) were collected after 6 months of prolonged resistance-type exercise training. Young subjects were included as a reference group. Primary differences in skeletal muscle metabolite levels between young and healthy older subjects were related to mitochondrial function, muscle fiber type, and tissue turnover. Similar differences were observed when comparing frail older subjects with healthy older subjects at baseline. Prolonged resistance-type exercise training resulted in an adaptive response of amino acid metabolism, especially reflected in branched chain amino acids and genes related to tissue remodeling. The effect of exercise training on branched-chain amino acid-derived acylcarnitines in older subjects points to a downward shift in branched-chain amino acid catabolism upon training. We observed only modest correlations between muscle and plasma metabolite levels, which pleads against the use of plasma metabolites as a direct read-out of muscle metabolism and stresses the need for direct assessment of metabolites in muscle tissue biopsies.

Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update.

Abstract: The Chromosome-Centric Human Proteome Project (C-HPP) aims to identify “missing” proteins in the neXtProt knowledgebase. We present an in-depth proteomics analysis of the human sperm proteome to identify testis-enriched missing proteins. Using protein extraction procedures and LC–MS/MS analysis, we detected 235 proteins (PE2–PE4) for which no previous evidence of protein expression was annotated. Through LC–MS/MS and LC–PRM analysis, data mining, and immunohistochemistry, we confirmed the expression of 206 missing proteins (PE2–PE4) in line with current HPP guidelines (version 2.0). Parallel reaction monitoring acquisition and sythetic heavy labeled peptides targeted 36 ≪one-hit wonder≫ candidates selected based on prior peptide spectrum match assessment. 24 were validated with additional predicted and specifically targeted peptides. Evidence was found for 16 more missing proteins using immunohistochemistry on human testis sections. The expression pattern for some of these proteins was specific to the tes...

Metabolomic Signatures of Chronic Kidney Disease of Diverse Etiologies in the Rats and Humans

Abstract: Chronic kidney disease (CKD) has emerged as a major public health problem worldwide. It frequently progresses to end-stage renal disease, which is related to very high cost and mortality. Novel biomarkers can provide insight into the novel mechanism, facilitate early detection, and monitor progression of CKD and its response to therapeutic interventions. To identify potential biomarkers, we applied an UPLC-HDMS together with univariate and multivariate statistical analyses using plasma samples from patients with CKD of diverse etiologies (100 sera in discovery set and 120 sera in validation set) and two different rat models of CKD. Using comprehensive screening and validation workflow, we identified a panel of seven metabolites that were shared by all patients and animals regardless of the underlying cause of CKD. These included ricinoleic acid, stearic acid, cytosine, LPA(16:0), LPA(18:2), 3-methylhistidine, and argininic acid. The combination of these seven biomarkers enabled the discrimination of patie...

Serum Bile Acids Are Associated with Pathological Progression of Hepatitis B-Induced Cirrhosis

Abstract: Recent metabonomic studies have identified an important role of bile acids in patients with liver cirrhosis. Serum bile acids, such as glycocholate (GCA), glycochenodeoxycholate (GCDCA), taurocholate (TCA), and taurochenodeoxycholate (TCDCA), increased significantly in liver cirrhosis patients. Our recently published urinary metabonomic study showed that glycocholate 3-glucuronide, taurohyocholate, TCA, glycolithocholate 3-sulfate, and glycoursodeoxycholate (GUDCA) were markedly increased in hepatitis B-induced cirrhotic patients (n = 63) compared with healthy controls (n = 31). The urinary levels of GUDCA were able to differentiate among three stages of cirrhotic patients with Child-Pugh (CP) score A, B, and C. In this study, we recruited two new cohorts of patients with hepatitis-B-induced cirrhosis and healthy control subjects and quantitatively profiled their serum bile acids using ultra-performance liquid chromatography triple quadrupole mass spectrometry. Serum bile acid profile and corresponding di...

Omics Studies of the Murine Intestinal Ecosystem Exposed to Subchronic and Mild Social Defeat Stress.

Abstract: The microbiota–gut–brain axis plays an important role in the development of stress-induced mental disorders. We previously established the subchronic and mild social defeat stress (sCSDS) model, a murine experimental model of depression, and investigated the metabolomic profiles of plasma and liver. Here we used omics approaches to identify stress-induced changes in the gastrointestinal tract. Mice exposed to sCSDS for 10 days showed the following changes: (1) elevation of cholic acid and reduction of 5-aminovaleric acid among cecal metabolites; (2) downregulation of genes involved in the immune response in the terminal ileum; (3) a shift in the diversity of the microbiota in cecal contents and feces; and (4) fluctuations in the concentrations of cecal metabolites produced by gut microbiota reflected in plasma and hepatic metabolites. Operational taxonomic units within the family Lachnospiraceae showed an inverse correlation with certain metabolites. The social interaction score correlated with cecal meta...

The Peripheral Blood Eosinophil Proteome

Abstract: A system-wide understanding of biological processes requires a comprehensive knowledge of the proteins in the biological system. The eosinophil is a type of granulocytic leukocyte specified early in hematopoietic differentiation that participates in barrier defense, innate immunity, and allergic disease. The proteome of the eosinophil is largely unannotated with under 500 proteins identified. We now report a map of the nonstimulated peripheral blood eosinophil proteome assembled using two-dimensional liquid chromatography coupled with high-resolution mass spectrometry. Our analysis yielded 100,892 unique peptides mapping to 7,086 protein groups representing 6,813 genes as well as 4,802 site-specific phosphorylation events. We account for the contribution of platelets that routinely contaminate purified eosinophils and report the variability in the eosinophil proteome among five individuals and proteomic changes accompanying acute activation of eosinophils by interleukin-5. Our deep coverage and quantitative analyses fill an important gap in the existing maps of the human proteome and will enable the strategic use of proteomics to study eosinophils in human diseases.