Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “proteomics database”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,333 records · Page 74Linked to original sources

Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study.

The Human Proteome Organization (HUPO) recently completed the first large-scale collaborative study to characterize the human serum and plasma proteomes. The study was carried out in different locations and used diverse methods and instruments to compare and integrate tandem mass spectrometry (MS/MS) data on aliquots of pooled serum and plasma from healthy subjects. Liquid chromatography (LC)-MS/MS data sets from 18 laboratories were matched to the International Protein Index database, and an initial integration exercise resulted in 9,504 proteins identified with one or more peptides, and 3,020 proteins identified with two or more peptides. This article uses a rigorous statistical approach to take into account the length of coding regions in genes, and multiple hypothesis-testing techniques. On this basis, we now present a reduced set of 889 proteins identified with a confidence level of at least 95%. We also discuss the importance of such an integrated analysis in providing an accurate representation of a proteome as well as the value such data sets contain for the high-confidence identification of protein matches to novel exons, some of which may be localized in alternatively spliced forms of known plasma proteins and some in previously nonannotated gene sequences.

Blood Proteins↗

Proteome analysis in the bovine adrenal medulla using liquid chromatography with tandem mass spectrometry.

Liquid chromatography/mass spectrometry (LC/MS)-based proteomics has been used to identify soluble proteins in the bovine adrenal medulla. This gland is a major source of hormones, opioids, neurotransmitters, and several vital proteins. The adrenal medulla proteins were first purified using ammonium sulfate precipitation. The resulting proteins were then pre-fractionated with a C-4 high-performance liquid chromatography (HPLC) column. Each 2-min HPLC fraction was digested with trypsin, and separated further and analyzed using capillary liquid chromatography/tandem mass spectrometry (capLC/nanospray-MS/MS) to map the proteome of the adrenal medulla. The parent mass and sequence ion information thus obtained for tryptic peptides was used to search the NCBInr database using the SEQUEST search engine. A total of 195 proteins were identified, of which 71 had good scores (delta correlation value greater than 0.1, preliminary score above 200, and cross-correlation value above 2.5). The prominent proteins thus identified are secretogranin I precursor, chromogranin A, proenkephalin A precursor, myosin X, hemoglobin beta chain, hemoglobin alpha chain, heat shock protein 10 kDa, and replicase.

Adrenal Medulla↗

Serum proteomic pattern analysis for early cancer detection.

The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancers at their early stages. The early detection of cancer has the potential to dramatically reduce mortality. Recently, the use of mass spectrometry to develop profiles of patient serum proteins has been reported as a promising method to achieve this goal. In this paper, we analyzed the ovarian cancer and prostate cancer data sets using support vector machine (SVM) to detect cancer at the early stages based on serum proteomic pattern. The results showed that SVM, in general, performed well on these two data sets, as measured by sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Linear kernel worked the best on ovarian cancer data with a sensitivity of 0.99 and an accuracy of 0.97, while polynomial kernel worked the best on prostate cancer data with a sensitivity of 0.79 and an accuracy of 0.82. When redial kernel was applied to either of the two data sets, all the samples were predicted as cancer samples, with a sensitivity of 1 and a specificity of 0. Furthermore, feature selection did not improve SVM performance.

Artificial Intelligence↗

Phosphoproteomics by mass spectrometry and classical protein chemistry approaches.

The general fields of biological sciences have seen phenomenal transformations in the past two decades at the level of data acquisition, understanding biological processes, and technological developments. Those advances have been made partly because of the advent of molecular biology techniques (which led to genomics) coupled to the advances made in mass spectrometry (MS) to provide the current capabilities and developments in proteomics. However, our current knowledge that approximately 30,000 human genes may code for up to 1 million or more proteins disengage the interface between the genome sequence database algorithms and MS to generate a major interest in independent de novo MS/MS sequence determination. Significant progress has been made in this area through procedures to covalently modify peptide N- and C-terminal amino-acids by sulfonation and guanidination to permit rapid de novo sequence determination by MS/MS analysis. A number of strategies that have been developed to perform qualitative and quantitative proteomics range from 2D-gel electrophoresis, affinity tag reagents, and stable-isotope labeling. Those procedures, combined with MS/MS peptide sequence analysis at the subpicomole level, permit the rapid and effective identification and quantification of a large number of proteins within a given biological sample. The identification of proteins per se, however, is not always sufficient to interpret biological function because many of the naturally occurring proteins are post-translationally modified. One such modification is protein phosphorylation, which regulates a large array of cellular biochemical pathways of the biological system. Traditionally, the study of phosphoprotein structure-function relationships involved classical protein chemistry approaches that required protein purification, peptide mapping, and the identification of the phosphorylated peptide regions and sites by N-terminal sequence analysis. Recent advances made in mass spectrometry have clearly revolutionized the studies of phosphoprotein biochemistry, and include the development of specific strategies to preferentially enrich phosphoproteins by covalent-modifications that incorporate affinity tags that use the physicochemical properties of phosphoaminoacids. The phosphoserine/phosphothreonine-containing proteins/peptides are derivatized under base-catalyzed conditions by thiol agents; mono- and di-thiol reagents both have been used in such studies. The thiol agent may have: (i) an affinity tag for protein enrichment; (ii) stable-isotopic variants for relative quantitation; or (iii) a combination of the moieties in (i) and (ii). These strategies and techniques, together with others, are reviewed, including their practical application to the study of phosphoprotein biochemistry and structure-function. The consensus of how classical protein chemistry and current MS technology overlap into special case of proteomics, namely "phosphoproteomics," will be discussed.

Amino Acid Sequence↗

Pharmacogenomics, genetic testing and ethnic variability: tackling the ethical questions.

Dr Winkelmann is the Head of the Cooperation Unit for Pharmacogenomics and Applied Genomics in Heidelberg, which was founded in 2001 by the Department of Internal Medicine VI and the Coordination Centre for Clinical Trials at the University of Heidelberg. His main interests are sophisticated phenotyping procedures for patient characterization and the conduct of multicenter clinical trials according to international standards with state-of-the-art data management. He currently applies new genomic tools in order to achieve progress in personalized medicine using collaborating networks of general practitioners for patient enrollment. The focus of his research group is on the common complex genetic cardiovascular and metabolic diseases ranging from coronary artery disease, dyslipidemia and hypertension, to metabolic syndrome and diabetes mellitus. In collaboration with partners from biotech, the genomic techniques used in clinical studies include haplotyping of candidate genes, gene expression profiling of peripheral leucocytes and proteomics in order to identify new biomarkers of effect in therapeutic studies or pathway/target gene identification in disease-specific family studies using microarray-based linkage approaches. An innovative web-based remote data entry system with an integrated pedigree drawing tool is used in the family studies. Dr Winkelmann is also involved as the clinical database coordinator for a European Framework VI research initiative of leading European centers in cardiovascular genetics for identification of risk genes for atherothrombosis in coronary artery disease by transcriptome and proteome analysis and high throughput exon resequencing at the Wellcome Trust Sanger Institute, Cambridge, UK.

Cardiovascular Diseases↗

Metabolomics, genomics, proteomics, and the identification of enzymes and their substrates and products.

A large proportion of the genes in any plant genome encode enzymes of primary and specialized (secondary) metabolism. Not all plant primary metabolites, those that are found in all or most species, have been identified. Moreover, only a small portion of the estimated hundreds of thousand specialized metabolites, those found only in restricted lineages, have been studied in any species. The correlative analysis of extensive metabolic profiling and gene expression profiling has proven a powerful approach for the identification of candidate genes and enzymes, particularly those in secondary metabolism. The final characterization of substrates, enzymatic activities, and products requires biochemical analysis, which has been most successful when candidate proteins have homology to other enzymes of known function. The challenges are to identify new types of enzymes and to develop biochemical techniques that are suitable for large-scale analysis.

Databases, Factual↗

Intrinsic disorder and functional proteomics.

The recent advances in the prediction of intrinsically disordered proteins and the use of protein disorder prediction in the fields of molecular biology and bioinformatics are reviewed here, especially with regard to protein function. First, a close look is taken at intrinsically disordered proteins and then at the methods used for their experimental characterization. Next, the major statistical properties of disordered regions are summarized, and prediction models developed thus far are described, including their numerous applications in functional proteomics. The future of the prediction of protein disorder and the future uses of such predictions in functional proteomics comprise the last section of this article.

Algorithms↗

Analyzing chromatin remodeling complexes using shotgun proteomics and normalized spectral abundance factors.

Mass spectrometry-based approaches are commonly used to identify proteins from multiprotein complexes, typically with the goal of identifying new complex members or identifying post-translational modifications. However, with the recent demonstration that spectral counting is a powerful quantitative proteomic approach, the analysis of multiprotein complexes by mass spectrometry can be reconsidered in certain cases. Using the chromatography-based approach named multidimensional protein identification technology, multiprotein complexes may be analyzed quantitatively using the normalized spectral abundance factor that allows comparison of multiple independent analyses of samples. This study describes an approach to visualize multiprotein complex datasets that provides structure function information that is superior to tabular lists of data. In this method review, we describe a reanalysis of the Rpd3/Sin3 small and large histone deacetylase complexes previously described in a tabular form to demonstrate the normalized spectral abundance factor approach.

Chromatin Assembly and Disassembly↗

A dataset of human fetal liver proteome identified by subcellular fractionation and multiple protein separation and identification technology.

A high throughput process including subcellular fractionation and multiple protein separation and identification technology allowed us to establish the protein expression profile of human fetal liver, which was composed of at least 2,495 distinct proteins and 568 non-isoform groups identified from 64,960 peptides and 24,454 distinct peptides. In addition to the basic protein identification mentioned above, the MS data were used for complementary identification and novel protein mining. By doing the analysis with integrated protein, expressed sequence tag, and genome datasets, 223 proteins and 15 peptides were complementarily identified with high quality MS/MS data.

Cell Membrane↗

JVirGel: Calculation of virtual two-dimensional protein gels.

We developed JVirGel, a collection of tools for the simulation and analysis of proteomics data. The software creates and visualizes virtual two-dimensional (2D) protein gels based on the migration behaviour of proteins in dependence of their theoretical molecular weights in combination with their calculated isoelectric points. The utilization of all proteins of an organism of interest deduced from genes of the corresponding genome project in combination with the elimination of obvious membrane proteins permits the creation of an optimized calculated proteome map. The electrophoretic separation behaviour of single proteins is accessible interactively in a Java(TM) applet (small application in a web browser) by selecting a pI/MW range and an electrophoretic timescale of interest. The calculated pattern of protein spots helps to identify unknown proteins and to localize known proteins during experimental proteomics approaches. Differences between the experimentally observed and the calculated migration behaviour of certain proteins provide first indications for potential protein modification events. When possible, the protein spots are directly linked via a mouse click to the public databases SWISS-PROT and PRODORIC. Additionally, we provide tools for the serial calculation and visualization of specific protein properties like pH dependent charge curves and hydrophobicity profiles. These values are helpful for the rational establishment of protein purification procedures. The proteomics tools are available on the World Wide Web at http://prodoric.tu-bs.de/proteomics.php.

Computer Graphics↗

Proteomic method for identification of tyrosine-nitrated proteins.

Biologic nitration of protein tyrosine (to form 3-nitrotyrosine) is a recently described phenomenon that is associated with many diseases. We have devised a proteomic methodology to identify these modified proteins. This utilizes protein fractionation by two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), partial transfer onto polyvinylidene difluoride (PVDF) membranes, and Western blot analysis using an antinitrotyrosine antibody to identify the proteins. Alignment of the Western blots with the partially transferred 2-D PAGE gels enables identification of immunopositive protein spots. These are then excised and trypsin digested. Proteins are then identified using either matrix-assisted laser desorption ionization-time of flight mass spectrometry or capillary liquid chromatography tandem electrospray mass spectrometry. Nonspecific crossreactivity of the antibodies is determined using reduction of protein bound 3-nitrotyrosine to 3-amino tyrosine using sodium dithionite.

Animals↗

Isolation and characterisation of a Lactobacillus helveticus ITG LH1 peptidase-rich sub-proteome.

Lactobacillus helveticus strains, one of the most nutritionally fastidious lactic acid bacteria, have a potent proteolytic system that makes them very interesting for different uses in the dairy industry. Its applications concern from cheese ripening to the preparation of fermented milk products with biologically active peptides. The cell-free extract (CFE) of Lactobacillus helveticus strain ITG LH1 was analysed by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), using IPG immobiline dry strips (pH 4-7). With the aim to study the proteolytic enzymes expressed by Lactobacillus helveticus ITG LH1 grown in milk medium, a two step-chromatography methodology, based on ion exchange and affinity chromatography, was developed for the preparation of a peptidase-rich sub-proteome from the CFE of stationary growing cells. Several affinity chromatography columns were tested and among them a HiTrap Chelating column was selected as it provided the best performance for the enrichment in peptidases. Peptidase activities were studied using different beta-Naphtylamide (beta-NA) derivatives and specific activities were increased 50- to 100-fold by this chromatographic procedure. Sub-proteome characterisation was performed by 2D-PAGE, pH 4-7, followed by protein digestion with trypsin, analysis by MALDI-TOF mass spectrometry and subsequent database searches using peptide mass fingerprints. Among the most abundant proteins seven peptidases were present, namely the two general aminopeptidases (PepN, PepC), three dipeptidases (PepDA, PepV, PepQ) and two endopeptidases (PepO, PepO3), all of them corresponding to the catalytic classes of metallo- or cysteine-peptidases. Several stress proteins (such as heat shock proteins DnaK and GroEL) and other enzymes implied in bacterial metabolism, namely in the carbohydrate pathways (such as LDH), were also identified in the peptidase-rich sub-proteome.

Aminopeptidases↗

Analysis of secreted proteins from Aspergillus flavus.

MS/MS techniques in proteomics make possible the identification of proteins from organisms with little or no genome sequence information available. Peptide sequences are obtained from tandem mass spectra by matching peptide mass and fragmentation information to protein sequence information from related organisms, including unannotated genome sequence data. This peptide identification data can then be grouped and reconstructed into protein data. In this study, we have used this approach to study protein secretion by Aspergillus flavus, a filamentous fungus for which very little genome sequence information is available. A. flavus is capable of degrading the flavonoid rutin (quercetin 3-O-glycoside), as the only source of carbon via an extracellular enzyme system. In this continuing study, a proteomic analysis was used to identify secreted proteins from A. flavus when grown on rutin. The growth media glucose and potato dextrose were used to identify differentially expressed secreted proteins. The secreted proteins were analyzed by 1- and 2-DE and MS/MS. A total of 51 unique A. flavus secreted proteins were identified from the three growth conditions. Ten proteins were unique to rutin-, five to glucose- and one to potato dextrose-grown A. flavus. Sixteen secreted proteins were common to all three media. Fourteen identifications were of hypothetical proteins or proteins of unknown functions. To our knowledge, this is the first extensive proteomic study conducted to identify the secreted proteins from a filamentous fungus.

Aspergillus flavus↗

Improvement of the two-dimensional gel electrophoresis analysis for the proteome study of Halobacterium salinarum.

Inherent problems exist in the use of two-dimensional gel electrophoresis (2-DE) for sample preparation and separation of proteins from Halobacterium salinarum. In particular, proteins from cells grown in 25% NaCl are difficult to resolve by 2-DE due to the abundance of salt. To remove salts, a 3 kDa molecular weight cut-off column was used. When soluble proteins were separated by 2-DE, most of the proteins were concentrated in the acidic range. For separation of proteins in the pH 3-6 range, ultrazoom immobilized pH gradient strips were used. In addition, sample separation using a IPGphor/Multiphor combined system was a more effective method for the proteome analysis of acidic proteins than using IPGphor for the isoelectric focusing step.

Databases, Protein↗

Biosequence exegesis.

Annotation of large-scale gene sequence data will benefit from comprehensive and consistent application of well-documented, standard analysis methods and from progressive and vigilant efforts to ensure quality and utility and to keep the annotation up to date. However, it is imperative to learn how to apply information derived from functional genomics and proteomics technologies to conceptualize and explain the behaviors of biological systems. Quantitative and dynamical models of systems behaviors will supersede the limited and static forms of single-gene annotation that are now the norm. Molecular biological epistemology will increasingly encompass both teleological and causal explanations.

Animals↗

Proteomic analysis of the effect of heat stress on hexaploid wheat grain: characterization of heat-responsive proteins from non-prolamins fraction.

The effect of heat stress on hexaploid wheat grain proteome was recently analyzed in our previous works. Proteomic tools allowed the characterization of heat-responsive proteins of total endosperm, composed mainly of prolamins. The present work completes this study; our aim was to analyze the effect of heat stress on the water-soluble fraction, composed essentially of albumins and globulins. These proteins were separated by two-dimensional electrophoresis (2-DE), visualized by Coomassie Brilliant Blue (CBB) staining and analyzed by Melanie-3 software. Of the 43 heat-changed proteins, 24 were found to be up-regulated whereas 19 spot proteins were down-regulated. All of these proteins were subjected to matrix-assisted laser desorption/ionization-time of flight-mass spectrometry (MALDI-TOF-MS) followed by database searching which allowed the identification of 42 spots. Of these, some were enzymes involved in different metabolic pathways of plants, such as granule-bound starch synthase and glucose-1-phosphate adenyltransferase, involved in the starch synthesis pathway; beta-amylase, involved in carbohydrate metabolism, and the ATP synthase beta-chain that was related to four heat-decreased proteins. Moreover, five heat up-regulated proteins showed similarities with small heat shock proteins while three other spots were related to elongation factors or eucaryotic translation initiation factors. Proteins involved in abiotic stresses or in plant defense mechanism were also identified and are discussed.

Databases, Protein↗

Regeneration of the secondary vascular system in poplar as a novel system to investigate gene expression by a proteomic approach.

Wood formation is a complex process composing many biological events. To access its key developmental stages, we have established a regeneration system that can mimic the initiation and differentiation of cambium cells for Chinese white poplar. Anatomical studies showed that new cambium and xylem re-appeared in sequence within a few weeks after being debarked. This provides the opportunity to follow key stages of wood formation by sampling clonal trees at different regeneration times. We used this system in combination with a proteomic approach to analyze proteins expressed in different regeneration stages. PMFs for 244 proteins differentially displayed were obtained and queried against public databases. Putative functions of 199 of these proteins were assigned and classified. Regulatory genes for cell cycle progression, differentiation and cell fate were expressed in the formation of cambial tissue, while 27 genes involved in secondary wall formation were predominantly found in the xylem developing stage. This indicates that the change of gene expression pattern is corresponding to the progression of second vascular system regeneration when and where the key events of wood development occur. Further exploration of these interesting genes may provide insight into the molecular mechanisms of wood formation.

Electrophoresis, Gel, Two-Dimensional↗

Proteomic analysis of injured spinal cord tissue proteins using 2-DE and MALDI-TOF MS.

Spinal cord injury (SCI) induces a progressive pathophysiology affecting cell survival and neurological integrity via complex and evolving molecular cascades whose interrelationships are not fully understood. Acute injury to the spinal cord undergoes sequential pathological change including hemorrhage, edema, axonal and neuronal necrosis, and demyelination. In the present study, we aimed to establish the proteomic profiles and characterization of the total protein expressed in traumatic injured spinal cord tissue by using 2-DE and matrix assisted laser desorption/ionization-TOF MS (MALDI-TOF MS). We performed proteomic analysis using 2-DE and MS to describe total proteins and differential proteins expression between normal and traumatic injured spinal cord tissues. The study discovered 947 total proteins and analyzed 219 and 270 proteins from normal and injured tissue, respectively. After 24 h of traumatic damage induction, the injured spinal cord tissue up-regulated over 39 proteins including neurofilament light chain, annexin 5, heat shock protein, tubulin beta, peripherin, glial fibrillary acidic protein delta, peroxiredoxin 2, and apolipoprotein A. Twenty-one proteins showed reduction. The majority of the modulated proteins belonged to the 13 functional categories. Proteins that were identified with neural functional category in injured tissue were considered most likely to be involved in wound healing response coupled with neurogenesis and gliogenesis.

Animals↗