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PubMed2006

ProteomeCommons.org IO Framework: reading and writing multiple proteomics data formats.

MOTIVATION: Effective use of proteomics data, specifically mass spectrometry data, relies on the ability to read and write the many mass spectrometer file formats. Even with mass spectrometer vendor-specific libraries and vendor-neutral file formats, such as mzXML and mzData it can be difficult to extract raw data files in a form suitable for batch processing and basic research. Introduced here are the ProteomeCommons.org Input and Output Framework, abbreviated to IO Framework, which is designed to abstractly represent mass spectrometry data. This project is a public, open-source, free-to-use framework that supports most of the mass spectrometry data formats, including current formats, legacy formats and proprietary formats that require a vendor-specific library in order to operate. The IO Framework includes an on-line tool for non-programmers and a set of libraries that developers may use to convert between various proteomics file formats. AVAILABILITY: The current source-code and documentation for the ProteomeCommons.org IO Framework is freely available at http://www.proteomecommons.org/current/531/

Algorithms↗
PubMed2006

Photoaffinity labeling combined with mass spectrometric approaches as a tool for structural proteomics.

Protein chemistry, such as crosslinking and photoaffinity labeling, in combination with modern mass spectrometric techniques, can provide information regarding protein-protein interactions beyond that normally obtained from protein identification and characterization studies. While protein crosslinking can make tertiary and quaternary protein structure information available, photoaffinity labeling can be used to obtain structural data about ligand-protein interaction sites, such as oligonucleotide-protein, drug-protein and protein-protein interaction. In this article, we describe mass spectrometry-based photoaffinity labeling methodologies currently used and discuss their current limitations. We also discuss their potential as a common approach to structural proteomics for providing 3D information regarding the binding region, which ultimately will be used for molecular modeling and structure-based drug design.

Azides↗
PubMed2003

Proteome analysis of Escherichia coli K-12 by two-dimensional native-state chromatography and MALDI-MS.

To identify proteins expressed in Escherichia coli K-12 MG1655 during exponential growth in defined medium, we separated soluble proteins of E. coli over two dimensions of native-state high-performance liquid chromatography, and examined the components of the protein mixtures in each of 380 fractions by peptide mass fingerprinting. To date, we have identified the products of 310 genes covering a wide range of cellular functions. Validation of protein assignments was made by comparing the assignments of proteins to specific first-dimension fractions to proteins visualized by two-dimensional gel electrophoresis. Co-fractionation of proteins suggests the possible identities of components of multiprotein complexes. This approach yields high-throughput gel-independent identification of proteins. It can also be used to assign identities to spots visualized by two-dimensional gels, and should be useful to evaluate differences in expressed proteome content and protein complexes among strains or between different physiological states.

Chromatography, High Pressure Liquid↗
PubMed2006

The nuclear proteome of chickpea (Cicer arietinum L.) reveals predicted and unexpected proteins.

Nuclear proteins constitute a highly organized, complex network that plays diverse roles during cellular development and other physiological processes. The yeast nuclear proteome corresponds to about one-fourth of the total cellular proteins, suggesting the involvement of the nucleus in a number of diverse functions. In an attempt to understand the complexity of plant nuclear proteins, we have developed a proteome reference map of a legume, chickpea, using two-dimensional gel electrophoresis (2-DE). Approximately, 600 protein spots were detected, and LC-ESI-MS/MS analyses led to the identification of 150 proteins that have been implicated in a variety of cellular functions. The largest percentage of the identified proteins was involved in signaling and gene regulation (36%), while 17% were involved in DNA replication and transcription. The chickpea nuclear proteome indicates the presence of few new nuclear proteins of unknown functions vis-à-vis many known resident proteins. To the best of our knowledge, this is the first report of a nuclear proteome of an unsequenced genome.

Chromatography, Liquid↗
PubMed2006

Using the yeast two-hybrid assay to discover protein partners for the leucine-rich amelogenin peptide and for tuftelin-interacting protein 11.

The established structural proteins of the enamel matrix are amelogenin, ameloblastin, and enamelin. Historically, tuftelin and tuftelin-interacting protein 11 (TFIP11) have also been discussed as possible enamel proteins. Protein complexes are achieved by protein-protein interactions, and it is protein complexes that control biomineralization. The purpose of our recent studies was to catalog protein partners for these proteins that are, or have been, implicated in tooth formation. We used the sensitive yeast two-hybrid assay to identify proteins that interact directly with amelogenin, ameloblastin, enamelin, the leucine-rich amelogenin peptide (LRAP) and TFIP11. In this manuscript we refer to, or document, potential protein partners for the proteins listed above. The yeast two-hybrid assay may ultimately prove to be a valuable proteomics methodology for using to decipher molecular events that ultimately result in enamel biomineralization.

Amelogenin↗
PubMed2005

An emerging role for comprehensive proteome analysis in human pregnancy research.

Elucidation of underlying cellular and molecular mechanisms is pivotal to the comprehension of biological systems. The successful progression of processes such as pregnancy and parturition depends on the complex interactions between numerous biological molecules especially within the uterine microenvironment. The tissue- and stage-specific expression of these bio-molecules is intricately linked to and modulated by several endogenous and exogenous factors. Malfunctions may manifest as pregnancy disorders such as preterm labour, pre-eclampsia and fetal growth restriction that are major contributors to maternal and perinatal morbidity and mortality. Despite the immense amount of information available, our understanding of several aspects of these physiological processes remains incomplete. This translates into significant difficulties in the timely diagnosis and effective treatment of pregnancy-related complications. However, the emergence of powerful mass spectrometry-based proteomic techniques capable of identifying and characterizing multiple proteins simultaneously has added a new dimension to the field of biomedical research. Application of these high throughput methodologies with more conventional techniques in pregnancy-related research has begun to provide a novel perspective on the biochemical blueprint of pregnancy and its related disorders. Further, by enabling the identification of proteins specific to a disease process, proteomics is likely to contribute, not only to the comprehension of the underlying pathophysiologies, but also to the clinical diagnosis of multifactorial pregnancy disorders. Although the application of this technology to pregnancy research is in its infancy, characterization of the cellular proteome, unearthing of functional networks and the identification of disease biomarkers can be expected to significantly improve maternal healthcare in the future.

Female↗
PubMed2006

Protein profile of osteoarthritic human articular cartilage using tandem mass spectrometry.

Articular cartilage contains both chondrocyte cells and extracellular matrix (ECM) components. Currently, comprehensive information concerning the protein composition of human articular cartilage tissue is somewhat lacking. In this report we detail the use of tandem mass spectrometry (MS/MS) for a preliminary global identification of proteins from human articular knee cartilage tissue from patients diagnosed with osteoarthritis. Knee cartilage supernatant was fractionated using one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis (1D-SDS-PAGE), in-gel digested and peptide sequences were then determined by performing on-line nano-liquid chromatography (LC)/MS/MS experiments using an ion trap mass spectrometer. Altogether, over 100 different proteins from nearly 700 unique peptide sequences were detected by MS/MS. The majority of the proteins identified are involved in ECM organization (35%), signal transduction and cell communication (14%), immune response (11%) and metabolism and energy pathways (11%). Proteins observed included several well-known cartilage components as well as lower abundant lesser known ECM proteins. Possible degradation products in the cartilage sample, such as from cartilage link protein, could also be detected by our mass spectrometry methods. We show here that mass spectrometry can be utilized as a tool for a fast, accurate and sensitive analysis of a complex mixture of cartilage proteins. It is believed that this type of proteomic analysis will aid future work centered on investigating the pathology of this and other related joint diseases.

Adult↗
PubMed2006

Proteomic profiling of rat bone marrow mesenchymal stem cells induced by 5-azacytidine.

Mesenchymal stem cells (MSCs) can differentiate into different types of cells and thus have tremendous potential for cell therapy and tissue engineering. 5-Azacytidine (5-aza), a DNA demethylation reagent, has been reported to induce MSCs to differentiate into cardiomyocytes in vitro. To determine a global effect of 5-aza on MSCs, we investigated the protein expressions of rat MSCs with two-dimensional gel electrophoresis (2-DE). We have generated a proteome reference map of rat MSCs, and have successfully identified 34 proteins with MALDI-TOF-MS analysis. Nine proteins showed distinct regulation in MSCs after 5-aza treatment. The proteins regulated by 5-aza included cytoskeletal proteins, cadmium-binding proteins, and metabolic proteins, etc. These proteins have been reported to be involved in cell proliferation and differentiation through different signaling pathways, and the molecular mechanism of MSCs differentiation is discussed at the proteome level.

Animals↗
PubMed2004

Proteomic analysis of mouse jejunal epithelium and its response to infection with the intestinal nematode, Trichinella spiralis.

Infection with the intestinal nematode Trichinella spiralis induces profound, but stereotypic pathological changes to the epithelium, which are common to many nematode infections. This study describes changes in jejunal epithelial protein expression that reflect these stereotypic responses. Adult male BALB/c mice were infected with T. spiralis, and groups (n = 4) examined on day 14/15 (time of worm rejection) were compared with uninfected controls (n = 4). Jejunal epithelium was harvested and extracted for two-dimensional gel electrophoresis. Tryptic peptide mass fingerprinting was used to create a reference map consisting of a total of 52 landmark spots. Of these, 16 were observed to change in intensity during infection. The changes observed at day 14/15 were of relevance to such mechanisms as lipid utilization and transport (increase in triacylglycerol lipase, and reduction in intestinal fatty acid binding protein) and innate immunity (appearance of intelectin-2). As a result, candidate molecules have been identified for further focused studies on their role in the host response to intestinal nematode infection.

Animals↗
PubMed2006

Prefractionation by digitonin extraction increases representation of the cytosolic and intracellular proteome of Leishmania infantum.

Proteome coverage is limited by the dynamic range of proteins present in a sample and often is confined to the analysis of abundant proteins. We have developed a protein prefractionation protocol, based on the differential solubilization of membranes using digitonin, that has allowed an increase in the resolution and depth of comparative proteomic studies. This prefractionation protocol can also be used to infer the subcellular localization of hypothetical proteins as tested experimentally using green fluorescent fusion proteins. The abundant tubulins and associated proteins of the cytoskeleton were removed from the sample using digitonin extraction, hence facilitating the visualization of lower abundance proteins. The digitonin prefractionation protocol was applied for a comparative proteomic analysis of the promastigote and amastigote life cycle stages of Leishmania infantum and has allowed the identification of novel proteins expressed in a stage-specific manner.

Animals↗
PubMed2004

High throughput approaches in neuroscience.

Traditional approaches to understanding biological problems are now being advanced with the use of high throughput technologies, which analyse multiple samples simultaneously, or thousands of analytes in a single sample. The application of these technologies in neurochemistry and neuroscience is beginning to be explored and is assisting in the development of new models of drug action, neuroanatomical investigations, and in identifying molecular pathways involved in neurological and psychiatric disease. Tools such as microarray-based gene expression profiling and 2D and multidimensional proteomic methods are uncovering functional components to a wide variety of neuroscience paradigms and the application of these technologies is set to become standard in analysis.

Animals↗
PubMed2002

Dynamics of protein turnover, a missing dimension in proteomics.

Functional genomic experiments frequently involve a comparison of the levels of gene expression between two or more genetic, developmental, or physiological states. Such comparisons can be carried out at either the RNA (transcriptome) or protein (proteome) level, but there is often a lack of congruence between parallel analyses using these two approaches. To fully interpret protein abundance data from proteomic experiments, it is necessary to understand the contributions made by the opposing processes of synthesis and degradation to the transition between the states compared. Thus, there is a need for reliable methods to determine the rates of turnover of individual proteins at amounts comparable to those obtained in proteomic experiments. Here, we show that stable isotope-labeled amino acids can be used to define the rate of breakdown of individual proteins by inspection of mass shifts in tryptic fragments. The approach has been applied to an analysis of abundant proteins in glucose-limited yeast cells grown in aerobic chemostat culture at steady state. The average rate of degradation of 50 proteins was 2.2%/h, although some proteins were turned over at imperceptible rates, and others had degradation rates of almost 10%/h. This range of values suggests that protein turnover is a significant missing dimension in proteomic experiments and needs to be considered when assessing protein abundance data and comparing it to the relative abundance of cognate mRNA species.

Amino Acids↗
PubMed2003

Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network.

We here describe PRODISTIN, a new computational method allowing the functional clustering of proteins on the basis of protein-protein interaction data. This method, assessed biologically and statistically, enabled us to classify 11% of the Saccharomyces cerevisiae proteome into several groups, the majority of which contained proteins involved in the same biological process(es), and to predict a cellular function for many otherwise uncharacterized proteins.

Cluster Analysis↗
PubMed2006

Optimizing search conditions for the mass fingerprint-based identification of proteins.

The two central problems in protein identification by searching a protein sequence collection with MS data are the optimal use of experimental information to allow for identification of low abundance proteins and the accurate assignment of the probability that a result is false. For comprehensive MS-based protein identification, it is necessary to choose an appropriate algorithm and optimal search conditions. We report a systematic study of the quality of PMF-based protein identifications under different sequence collection search conditions using the Probability algorithm, which assigns the statistical significance to each result. We employed 2244 PMFs from 2-DE-separated human blood plasma proteins, and performed identification under various search constraints: mass accuracy (0.01-0.3 Da), maximum number of missed cleavage sites (0-2), and size of the sequence collection searched (5.6 x 10(4)-1.8 x 10(5)). By counting the number of significant results (significance levels 0.05, 0.01, and 0.001) for each condition, we demonstrate the search condition impact on the successful outcome of proteome analysis experiments. A mass correction procedure utilizing mass deviations of albumin matching peptides was tested in an attempt to improve the statistical significance of identifications and iterative searching was employed for identification of multiple proteins from each PMF.

Blood Proteins↗
PubMed2001

Identification of differentially regulated proteins in metronidozole resistant Helicobacter pylori by proteome techniques.

Resistance to metronidazole (MTZ) is common among Helicobacter pylori strains in many societies, and results from loss of function mutations in genes for one or more cellular nitroreductases. When functional, these enzymes convert MTZ from a harmless prodrug to mutagenic and bacteriocidal products (probably hydroxylamine-type compounds), and in the process may generate active reactive oxygen metabolites. Here we examine the protein profiles of a derivative of strain 26695 that is resistant to moderate levels of MTZ because of mutation in rdxA (HP0954), the gene for the most important of these nitroreductases. The strain was grown with and without 18 micrograms/mL of MTZ to assess whether sublethal exposure triggers an adaptive response. Bacterial lysates were subjected to two-dimensional (2-D) electrophoresis and protein bands were identified by mass spectrometry and sequence analysis. Several proteins were decreased at least two-fold during growth with MTZ, yet the levels of various isoforms of alkylhydroperoxide reductase (AHP) (encoded by ahpC HP1563) were increased. AHP is an essential enzyme, and had been linked to resistance to oxygen toxicity in various prokaryotic and eukaryotic systems; we propose that the ability of an rdxA mutant strain to increase AHP abundance during exposure to MTZ is critically important in the realization of the resistance phenotype. More generally, these results highlight the potential of proteome analysis to tracing out how pathogenic bacteria cope with the challenges imposed on them by therapy or host responses to infection.

Bacterial Proteins↗
PubMed2003

The proteomics standards initiative.

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparison, exchange and verification. Progress has been made in the development of common standards for data exchange in the fields of both mass spectrometry and protein-protein interaction. A proteomics-specific extension is being created for the emerging American Society for Tests and Measurements mass spectrometry standard, which will be supported by manufacturers of both hardware and software. A data model for proteomics experimentation is under development and discussions on a public repository for published proteomics data are underway. The Protein-Protein Interactions group expects to publish the Level 1 PSI data exchange format for protein-protein interactions soon and discussions as to the content of Level 2 have been initiated.

Biochemistry↗
PubMed2005

Discover true association rates in multi-protein complex proteomics data sets.

Experimental processes to collect and process proteomics data are increasingly complex, while the computational methods to assess the quality and significance of these data remain unsophisticated. These challenges have led to many biological oversights and computational misconceptions. We developed a complete empirical Bayes model to analyze multi-protein complex (MPC) proteomics data derived from peptide mass spectrometry detections of purified protein complex pull-down experiments. Our model considers not only bait-prey associations, but also prey-prey associations missed in previous work. Using our model and a yeast MPC proteomics data set, we estimated that there should be an average of 28 true associations per MPC, almost ten times as high as was previously estimated. For data sets generated to mimic a real proteome, our model achieved on average 80% sensitivity in detecting true associations, as compared with the 3% sensitivity in previous work, while maintaining a comparable false discovery rate of 0.3%.

Algorithms↗
PubMed2004

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↗