[Choice of statistical approaches and analysis of blood serum proteome profiles in an experiment with 24-hour head-down tilt (-15 degrees)]

Variability analysis of normal human proteoma requires a valid and crisp algorithm for mass-spectrometry data analysis. The goal was to test methods of statistical analysis of blood serum proteoma profiles in an experiment with 24-hr. HDT using the small sample nonparametric criteria. The investigation revealed peaks that appear to be a molecular response of organism to simulated microgravity. Further identification of fiducially mobile peaks with the help of tandem mass-spectrometry will enable disclosure of subtle mechanisms of adaptation to the spaceflight factors and improvement of human health evaluation in space missions of varying length.

Eukaryotic selenoproteins and selenoproteomes

Selenium is an essential trace element for which both beneficial and toxic effects in human health have been described. It is now clear that the importance of having adequate amounts of this micronutrient in the diet is primarily due to the fact that selenium is required for biosynthesis of selenocysteine, the twenty first naturally occurring amino acid in protein. In this review, we provide an overview of eukaryotic selenoproteins and selenoproteomes, which are sets of selenoproteins in these organisms. In eukaryotes, selenoproteins show a mosaic occurrence, with some organisms, such as vertebrates and algae, having dozens of these proteins, while other organisms, such as higher plants and fungi, having lost all selenoproteins during evolution. We also discuss selenoprotein functions and evolutionary trends in the use of these proteins in eukaryotes. Functional analysis of selenoproteins is critical for better understanding of the role of selenium in human health and disease.

Allergens are distributed into few protein families and possess a restricted number of biochemical functions

BACKGROUND

Existing allergen databases classify their entries by source and route of exposure, thus lacking an evolutionary, structural, and functional classification of allergens.

OBJECTIVE

We sought to build AllFam, a database of allergen families, and use it to extract common structural and functional properties of allergens.

METHODS

Allergen data from the Allergome database and protein family definitions from the Pfam database were merged into AllFam, a database that is freely accessible on the Internet at http://www.meduniwien.ac.at/allergens/allfam/. A structural classification of allergens was established by matching Pfam families with families from the Structural Classification of Proteins database. Biochemical functions of allergens were extracted from the Gene Ontology Annotation database.

RESULTS

Seven hundred seven allergens were classified by sequence into 134 AllFam families containing 184 Pfam domains (2% of 9318 Pfam families). A random set of 707 sequences with the same taxonomic distribution contained a significantly higher number of different Pfam domains (479 +/- 17). Classifying allergens by structure revealed that 5% of 3012 Structural Classification of Proteins families contained allergens. The biochemical functions of allergens most frequently found were limited to hydrolysis of proteins, polysaccharides, and lipids; binding of metal ions and lipids; storage; and cytoskeleton association.

CONCLUSION

The small number of protein families that contain allergens and the narrow functional distribution of most allergens confirm the existence of yet unknown factors that render proteins allergenic.

Self-correcting networks: function, robustness, and motif distributions in biological signal processing

Statistical properties of large ensembles of networks, all designed to have the same functions of signal processing, but robust against different kinds of perturbations, are analyzed. We find that robustness against noise and random local damage plays a dominant role in determining motif distributions of networks and may underlie their classification into network superfamilies.

siRNA screen of the human signaling proteome identifies the PtdIns(3,4,5)P3-mTOR signaling pathway as a primary regulator of transferrin uptake

A survey of 1,804 human dicer-generated signaling siRNAs using automated quantitative imaging identified the phosphatidylinositol-3,4,5-trisphosphate-mTOR signaling pathway as a primary regulator of iron-transferrin uptake.

Background

Iron uptake via endocytosis of iron-transferrin-transferrin receptor complexes is a rate-limiting step for cell growth, viability and proliferation in tumor cells as well as non-transformed cells such as activated lymphocytes. Signaling pathways that regulate transferrin uptake have not yet been identified.

Results

We surveyed the human signaling proteome for regulators that increase or decrease transferrin uptake by screening 1,804 dicer-generated signaling small interfering RNAs using automated quantitative imaging. In addition to known transport proteins, we identified 11 signaling proteins that included a striking signature set for the phosphatidylinositol-3,4,5-trisphosphate (PtdIns(3,4,5)P3)-target of rapamycin (mTOR) signaling pathway. We show that the PI3K-mTOR signaling pathway is a positive regulator of transferrin uptake that increases the number of transferrin receptors per endocytic vesicle without affecting endocytosis or recycling rates.

Conclusion

Our study identifies the PtdIns(3,4,5)P3-mTOR signaling pathway as a new regulator of iron-transferrin uptake and serves as a proof-of-concept that targeted RNA interference screens of the signaling proteome provide a powerful and unbiased approach to discover or rank signaling pathways that regulate a particular cell function.

Functional protein divergence in the evolution of Homo sapiens

BACKGROUND

Protein-coding regions in a genome evolve by sequence divergence and gene gain and loss, altering the gene content of the organism. However, it is not well understood how this has given rise to the enormous diversity of metazoa present today.

RESULTS

To obtain a global view of human genomic evolution, we quantify the divergence of proteins by functional category at different evolutionary distances from human.

CONCLUSION

This analysis highlights some general systems-level characteristics of human evolution: regulatory processes, such as signal transducers, transcription factors and receptors, have a high degree of plasticity, while core processes, such as metabolism, transport and protein synthesis, are largely conserved. Additionally, this study reveals a dynamic picture of selective forces at short, medium and long evolutionary timescales. Certain functional categories, such as 'development' and 'organogenesis', exhibit temporal patterns of sequence divergence in eukaryotes relative to human. This framework for a grammar of human evolution supports previously postulated theories of robustness and evolvability.

Estradiol in vivo regulation of brain mitochondrial proteome

We used a combined proteomic and functional biochemical approach to determine the overall impact of 17beta-estradiol (E2) on mitochondrial protein expression and function. To elucidate mitochondrial pathways activated by E2 in brain, two-dimensional (2D) gel electrophoresis was conducted to screen the mitoproteome. Ovariectomized adult female rats were treated with a single injection of E2. After 24 h of E2 exposure, mitochondria were purified from brain and 2D analysis and liquid chromatography-tandem mass spectrometry protein identification were conducted. Results of proteomic analyses indicated that of the 499 protein spots detected by image analysis, a total of 66 protein spots had a twofold or greater change in expression. Of these, 28 proteins were increased in expression after E2 treatment whereas 38 proteins were decreased in expression relative to control. E2 regulated key metabolic enzymes including pyruvate dehydrogenase, aconitase, and ATP-synthase. To confirm that E2-inducible changes in protein expression translated into functional consequences, we determined the impact of E2 on the enzymatic activity of the mitochondrial electron transport chain. In vivo, E2 treatment enhanced brain mitochondrial efficiency as evidenced by increased respiratory control ratio, elevated cytochrome-c oxidase activity and expression while simultaneously reducing free radical generation in brain. Results of these analyses provide insights into E2 mechanisms of regulating brain mitochondria, which have the potential for sustaining neurological health and prevention of neurodegenerative diseases associated with mitochondrial dysfunction such as Alzheimer's disease.

BNDB - the Biochemical Network Database

Background

Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored in numerous databases that have been established over the last decades and are essential resources for scientists nowadays. However, the diversity of the databases and the underlying data models make it difficult to combine this information for solving complex problems in systems biology. Currently, researchers typically have to browse several, often highly focused, databases to obtain the required information. Hence, there is a pressing need for more efficient systems for integrating, analyzing, and interpreting these data. The standardization and virtual consolidation of the databases is a major challenge resulting in a unified access to a variety of data sources.

Description

We present the Biochemical Network Database (BNDB), a powerful relational database platform, allowing a complete semantic integration of an extensive collection of external databases. BNDB is built upon a comprehensive and extensible object model called BioCore, which is powerful enough to model most known biochemical processes and at the same time easily extensible to be adapted to new biological concepts. Besides a web interface for the search and curation of the data, a Java-based viewer (BiNA) provides a powerful platform-independent visualization and navigation of the data. BiNA uses sophisticated graph layout algorithms for an interactive visualization and navigation of BNDB.

Conclusion

BNDB allows a simple, unified access to a variety of external data sources. Its tight integration with the biochemical network library BN++ offers the possibility for import, integration, analysis, and visualization of the data. BNDB is freely accessible at .

Proteomic characterization of the site-dependent functional difference in the rat small intestine

To investigate the site-dependent functional difference in the small intestine, proteomic analysis was carried out on the three distinct parts of the rat small intestine. Male Wistar rats (7 weeks old) were fed a semi-purified diet ad libitum for 1 week. Intestinal tissues from the proximal, middle and distal regions of the small intestine were subjected to two-dimensional polyacrylamide gel electrophoresis, and the abundance of each spot was determined fluorometrically. MALDI-TOF/MS and LC-MS/MS analysis of the tryptic peptides were performed to identify the proteins. Many of the 180 identified proteins showed a distinctive distribution pattern along the small intestine. Glutathione S-transferase, Catechol O-methyltransferase and Villin 2 decreased gradually from the jejunum to the ileum, in contrast, non-specific dipeptidase and Keratin 19 increased gradually toward the ileum. The voltage-dependent anion channel 2 was most abundant in the duodenum while the L- and I-Fatty acid binding protein (FABP) and Cellular retinol binding protein (CRBP-II) were in the jejunum, and the Bile acid binding protein (BABP) was only observed in the ileum. The findings of these and of another proteins identified in this study may contribute to further understanding of the small intestinal function, and to clinical applications of small intestinal diseases.

CSF metabolic and proteomic profiles in patients prodromal for psychosis

BACKGROUND

The initial prodromal state of psychosis (IPS) is defined as an early disease stage prior to the onset of overt psychosis characterized by sub-threshold or more unspecific psychiatric symptoms. Little is known regarding the biochemical changes during this period.

METHODOLOGY/PRINCIPAL FINDINGS

We investigated the metabolic/proteomic profiles of cerebrospinal fluid (CSF) of first-onset drug naïve paranoid schizophrenia patients (n = 54) and individuals presenting with initial prodromal symptoms (n = 24), alongside healthy volunteers (n = 70) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy and surface enhanced laser desorption ionization (SELDI) mass spectrometry, respectively. Partial least square discriminant analysis (PLS-DA) showed that 36%/29% of IPS patients displayed proteomic/metabolic profiles characteristic of first-onset, drug naïve schizophrenia, i.e., changes in levels of glucose and lactate as well as changes in a VGF-derived peptide (VGF23-62) and transthyretin protein concentrations. However, only 29% (n = 7) of the investigated IPS patients (who to date have been followed up for up to three years) have so far received a diagnosis of schizophrenia. The presence of biochemical alterations in the IPS group did not correlate with the risk to develop schizophrenia.

CONCLUSIONS/SIGNIFICANCE

Our results imply that schizophrenia-related biochemical disease processes can be traced in CSF of prodromal patients. However, the biochemical disturbances identified in IPS patients, at least when measured at a single time point, may not be sufficient to predict clinical outcome.

ATM and ATR substrate analysis reveals extensive protein networks responsive to DNA damage

Cellular responses to DNA damage are mediated by a number of protein kinases, including ATM (ataxia telangiectasia mutated) and ATR (ATM and Rad3-related). The outlines of the signal transduction portion of this pathway are known, but little is known about the physiological scope of the DNA damage response (DDR). We performed a large-scale proteomic analysis of proteins phosphorylated in response to DNA damage on consensus sites recognized by ATM and ATR and identified more than 900 regulated phosphorylation sites encompassing over 700 proteins. Functional analysis of a subset of this data set indicated that this list is highly enriched for proteins involved in the DDR. This set of proteins is highly interconnected, and we identified a large number of protein modules and networks not previously linked to the DDR. This database paints a much broader landscape for the DDR than was previously appreciated and opens new avenues of investigation into the responses to DNA damage in mammals.

Comparative transcriptome analysis of Desulfovibrio vulgaris grown in planktonic culture and mature biofilm on a steel surface

Biofilm build-up of sulphate-reducing bacteria (SRB) on metal surfaces may lead to severe corrosion of iron. To understand the processes at molecular level, in this study, a whole-genome oligonucleotide microarray was used to examine differential expression patterns between planktonic populations and mature biofilm of Desulfovibrio vulgaris on a steel surface. Statistical analysis revealed that 472 genes were differentially expressed (1.5-fold or more with a q value less than 0.025) by comparing the biofilm cells with the planktonic cells. Among the differentially expressed genes were several that corresponded to genes identified in many aerobic bacterial biofilms (i.e., Pseudomonas species and Escherichia coli) such as genes encoding flagellin, a flagellar motor switch protein, chemotaxis proteins involved in cell motility, as well as genes involved in exopolysaccharide biosynthesis. In addition, the biofilm-bound cells of D. vulgaris exhibited decreased transcription of genes involved in protein synthesis, energy metabolism and sulfate reduction, as well as genes involved in general stress responses. These findings were all consistent with early suggestion that the average physiology of the biofilm cells were similar to cells reduced in growth. Most notably, up-regulation of large number of outer membrane proteins was observed in the D. vulgaris biofilm. Although their function is still unknown, the higher expression of these genes in the biofilm could implicate important roles in the formation and maintenance of multi-cellular consortium on a steel surface. The study provided insights into the metabolic networks associated with the formation and maintenance of a D. vulgaris biofilm on a steel surface.

A Grid Environment for High-Throughput Proteomics

We connect in a grid-enabled pipeline an ontology-based environment for proteomics spectra management with a machine learning platform for unbiased predictive analysis. We exploit two existing software platforms (MS-Analyzer and BioDCV), the emerging proteomics standards, and the middleware and computing resources of the EGEE Biomed VO grid infrastructure. In the setup, BioDCV is accessed by the MS-Analyzer workflow as a Web service, thus providing a complete grid environment for proteomics data analysis. Predictive classification studies on MALDI-TOF data based on this environment are presented.

Schistosome biology and proteomics: progress and challenges

The recent availability of schistosomal genome-sequence information allows protein identification in schistosome-derived samples by mass spectrometry (proteomics). Over the last few years, several proteome studies have been performed that addressed important questions in schistosome biology. This review summarizes the applied experimental approaches that have been used so far, it provides an overview of the most important conclusions that can be drawn from the performed studies and finally discusses future challenges in this research area.

PQuad—a visual analysis platform for proteomic data exploration of microbial organisms

The visual Platform for Proteomics Peptide and Protein data exploration (PQuad) is a multi-resolution environment that visually integrates genomic and proteomic data for prokaryotic systems, overlays categorical annotation and compares differential expression experiments. PQuad requires Java 1.5 and has been tested to run across different operating systems.

AVAILABILITY

http://ncrr.pnl.gov/software.

Proteomic analysis of the oxidative stress response in Candida albicans

An efficient oxidative stress response (OSR) is important for the facultative pathogenic yeast Candida albicans to survive within the human host. We used a large scale 2-D protein gel electrophoresis approach to analyze the stress response mechanisms of C. albicans after treatment with hydrogen peroxide and the thiol oxidizing agent, diamide. Quantitation of in vivo protein synthesis after pulse labeling of the proteins with radioactive L-[35S]-methionine resulted in characteristic proteome signatures for hydrogen peroxide and diamide with significant overlap of 21 up-regulated proteins for both stressors. Among the induced proteins were enzymes with known antioxidant functions like catalase or thioredoxin reductase and a set of oxidoreductases. 2-D gel analysis of mutants in the CAP1 gene revealed that the synthesis of 12 proteins is controlled by the oxidative stress regulator Cap1p. Stressing its importance for the C. albicans OSR, all 12 proteins were also induced after oxidative challenge by hydrogen peroxide or diamide.

Bioinformatic insights from metagenomics through visualization

Cutting-edge biological and bioinformatics research seeks a systems perspective through the analysis of multiple types of high-throughput and other experimental data for the same sample. Systems-level analysis requires the integration and fusion of such data, typically through advanced statistics and mathematics. Visualization is a complementary computational approach that supports integration and analysis of complex data or its derivatives. We present a bioinformatics visualization prototype, Juxter, which depicts categorical information derived from or assigned to these diverse data for the purpose of comparing patterns across categorizations. The visualization allows users to easily discern correlated and anomalous patterns in the data. These patterns, which might not be detected automatically by algorithms, may reveal valuable information leading to insight and discovery. We describe the visualization and interaction capabilities and demonstrate its utility in a new field, metagenomics, which combines molecular biology and genetics to identify and characterize genetic material from multi-species microbial samples.

Flux balance analysis of a genome-scale yeast model constrained by exometabolomic data allows metabolic system identification of genetically different strains

A systems approach to biology requires a principled approach to pathway identification. In this study, the two nuclear petite yeast mutants K1Deltapet191a and K1Deltapet191ab and their parental industrial strain K1 were cultured in glucose-containing microaerobic chemostats. Exometabolomic profiles were used to infer the differences in the fermentation characteristics and respiration capacity of the strains. The ability of the metabolite measurement information to describe genetically different strains was investigated using a genome-scale yeast model. Flux balance analysis (FBA) of the model reveals that the objective function of minimal oxygen consumption enables the identification of the effect of genotypic differences when combined with the knowledge of the extracellular state of metabolism. The predicted decrease in oxygen consumption flux of K1Deltapet191a and K1Deltapet191ab strains with respect to the parental strain is about 80% and 100%, respectively, which coincides with the respiratory deficiencies of the strains. The expected increase in ethanol production rates in response to the decrease in the respiratory capacity was also predicted to be very close to the experimental values. This study shows the predictive power of the integrated analysis of genome-scale models with exometabolomic profiles, since accurate predictions could be made without any information about the respiration capacity of the strains. The FBA approach thereby enables identification of responsive pathways and so permits the elucidation of the genetic characteristics of strains in terms of expressed metabolite profiles.

Proteomics Uncovers a Role for Redox in Drought Tolerance in Wheat

Proteomic analysis offers a new approach to identify a broad spectrum of genes that are expressed in living systems. We applied a proteomic approach to study changes in wheat grain in response to drought, a major environmental parameter adversely affecting development and crop yield. Three wheat genotypes differing in genetic background were cultivated in field under well-watered and drought conditions by following a randomized complete block design with four replications. The overall effect of drought was highly significant as determined by grain yield and total dry matter. About 650 spots were reproducibly detected and analyzed on 2-DE gels. Of these, 121 proteins showed significant change under drought condition in at least one of the genotypes. Mass spectrometry analysis using MALDI-TOF/TOF led to the identification of 57 proteins. Two-thirds of identified proteins were thioredoxin (Trx) targets, in accordance with the link between drought and oxidative stress. Further, because of contrasting changes in the tolerant and susceptible genotypes studied, several proteins emerge as key participants in the drought response. In addition to providing new information on the response to water deprivation, the present study offers opportunities to pursue the breeding of wheat with enhanced drought tolerance using identified candidate genetic markers. The 2-DE database of wheat seed proteins is available for public access at http://www.proteome.ir.

A proteome study of the proliferation of culturedMedicago truncatula protoplasts

A proteome study of the first five days of Medicago truncatula protoplast cultures was done to investigate molecular changes taking place during protoplast proliferation. A total of 1556 protein spots were analysed, of which 886 protein spots showed significant (p<0.005) changes in abundance at some time during the first five days of protoplast culture. Of the 886 significantly changing protein spots, 89 proteins were identified by MALDI-TOF MS. The majority of the identified proteins were part of four main cellular processes that may be involved in protoplast proliferation: energy metabolism, defence or stress response, secondary metabolism and protein synthesis and folding. The accumulation pattern of these proteins indicates extensive changes in the energy metabolism of the cells, accompanied by the activation of stress response pathways and modifications of the cell wall. In addition, seven PR10-like (pathogenesis related) proteins were identified. The accumulation pattern of these seven PR10-like proteins suggests that they could have a developmental role during protoplast proliferation.

Proteomic and transcriptomic analysis of rice mature seed-derived callus differentiation

Callus differentiation is a key developmental process for rice regeneration from cells. To better understand this complex developmental process, we used a 2-D gel electrophoresis approach to explore the temporal patterns of protein expression at the early stages during rice callus differentiation. This global analysis detected 60 known proteins out of 79 gel spots identified by MS/MS, of which many had been shown to play a role in plant development. Two new proteins were revealed to be associated with the callus differentiation and have been confirmed by Western blot analysis. The results of proteomics experiments were further verified at the mRNA level using microarray and real-time PCR. Comparison of the differentially expressed protein levels with their corresponding mRNA levels at the two callus early differentiation stages showed a good correlation between them, indicating that a substantial proportion of protein changes is a consequence of changed mRNA levels, rather than post-transcriptional effects during callus differentiation, though microarray revealed more expression changes on RNA levels. These findings may contribute to further understanding of the mechanisms that lead to callus differentiation of rice and other plants as well.

Lipid raft proteome of the human neutrophil azurophil granule

Detergent-resistant membrane domains (DRMs) are present in the membranes of azurophil granules in human neutrophils (Feuk-Lagerstedt et al., J. Leukoc. Biol. 2002, 72, 970). Using a proteomic approach, we have now identified 106 proteins in a DRM preparation from these granule membranes. Among these proteins were the lipid raft structural proteins flotillin-1 and -2, cytoskeletal proteins such as actin, vimentin and tubulin, and membrane fusion promoting proteins like annexins and dysferlin. Our results suggest that the azurophil granule membrane, in similarity to the plasma membrane, is an elaborate structure that takes part in intracellular signaling and functions other than the mere delivery of bactericidal effector molecules to the phagosome.

Identification and Characterization of Modification Enzymes by Biochemical Analysis of the Proteome

The use of proteomic libraries designed to express the complete set of proteins from an organism has resulted in the identification of many RNA modification enzymes whose function was previously unknown. Here we describe a generalized procedure for the biochemical analysis of a yeast proteomic library for identification of nucleic acid-modifying enzymes, by use of the yeast MORF (Moveable Open Reading Frame) library (Gelperin et al., 2005) as the source of protein activity, and the known yeast tRNA methyltransferase Trm4 as a test case. The procedures outlined in this chapter can be applied to any proteomic expression library from any organism, many of which will become increasingly available as the number of sequenced genomes increases and as genomic cloning techniques improve.