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Proteomics Data (proteomic + data)
Selected AbstractsThe cell wall and secretory proteome of a tobacco cell line synthesising secondary wallPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 9 2009David J. Millar Abstract The utility of plant secondary cell wall biomass for industrial and biofuel purposes depends upon improving cellulose amount, availability and extractability. The possibility of engineering such biomass requires much more knowledge of the genes and proteins involved in the synthesis, modification and assembly of cellulose, lignin and xylans. Proteomic data are essential to aid gene annotation and understanding of polymer biosynthesis. Comparative proteomes were determined for secondary walls of stem xylem and transgenic xylogenic cells of tobacco and detected peroxidase, cellulase, chitinase, pectinesterase and a number of defence/cell death related proteins, but not marker proteins of primary walls such as xyloglucan endotransglycosidase and expansins. Only the corresponding detergent soluble proteome of secretory microsomes from the xylogenic cultured cells, subjected to ion-exchange chromatography, could be determined accurately since, xylem-specific membrane yields were of poor quality from stem tissue. Among the 109 proteins analysed, many of the protein markers of the ER such as BiP, HSP70, calreticulin and calnexin were identified, together with some of the biosynthetic enzymes and associated polypeptides involved in polymer synthesis. However 53% of these endomembrane proteins failed identification despite the use of two different MS methods, leaving considerable possibilities for future identification of novel proteins involved in secondary wall polymer synthesis once full genomic data are available. [source] Computational physiology and the physiome projectEXPERIMENTAL PHYSIOLOGY, Issue 1 2004Edmund J. Crampin Bioengineering analyses of physiological systems use the computational solution of physical conservation laws on anatomically detailed geometric models to understand the physiological function of intact organs in terms of the properties and behaviour of the cells and tissues within the organ. By linking behaviour in a quantitative, mathematically defined sense across multiple scales of biological organization , from proteins to cells, tissues, organs and organ systems , these methods have the potential to link patient-specific knowledge at the two ends of these spatial scales. A genetic profile linked to cardiac ion channel mutations, for example, can be interpreted in relation to body surface ECG measurements via a mathematical model of the heart and torso, which includes the spatial distribution of cardiac ion channels throughout the myocardium and the individual kinetics for each of the approximately 50 types of ion channel, exchanger or pump known to be present in the heart. Similarly, linking molecular defects such as mutations of chloride ion channels in lung epithelial cells to the integrated function of the intact lung requires models that include the detailed anatomy of the lungs, the physics of air flow, blood flow and gas exchange, together with the large deformation mechanics of breathing. Organizing this large body of knowledge into a coherent framework for modelling requires the development of ontologies, markup languages for encoding models, and web-accessible distributed databases. In this article we review the state of the field at all the relevant levels, and the tools that are being developed to tackle such complexity. Integrative physiology is central to the interpretation of genomic and proteomic data, and is becoming a highly quantitative, computer-intensive discipline. [source] Microbial biodegradation of polyaromatic hydrocarbonsFEMS MICROBIOLOGY REVIEWS, Issue 6 2008Ri-He Peng Abstract Polycyclic aromatic hydrocarbons (PAHs) are widespread in various ecosystems and are pollutants of great concern due to their potential toxicity, mutagenicity and carcinogenicity. Because of their hydrophobic nature, most PAHs bind to particulates in soil and sediments, rendering them less available for biological uptake. Microbial degradation represents the major mechanism responsible for the ecological recovery of PAH-contaminated sites. The goal of this review is to provide an outline of the current knowledge of microbial PAH catabolism. In the past decade, the genetic regulation of the pathway involved in naphthalene degradation by different gram-negative and gram-positive bacteria was studied in great detail. Based on both genomic and proteomic data, a deeper understanding of some high-molecular-weight PAH degradation pathways in bacteria was provided. The ability of nonligninolytic and ligninolytic fungi to transform or metabolize PAH pollutants has received considerable attention, and the biochemical principles underlying the degradation of PAHs were examined. In addition, this review summarizes the information known about the biochemical processes that determine the fate of the individual components of PAH mixtures in polluted ecosystems. A deeper understanding of the microorganism-mediated mechanisms of catalysis of PAHs will facilitate the development of new methods to enhance the bioremediation of PAH-contaminated sites. [source] Incorporating gene functional annotations in detecting differential gene expressionJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2006Wei Pan Summary., The importance of incorporating existing biological knowledge, such as gene functional annotations in gene ontology, in analysing high throughput genomic and proteomic data is being increasingly recognized. In the context of detecting differential gene expression, however, the current practice of using gene annotations is limited primarily to validations. Here we take a direct approach to incorporating gene annotations into mixture models for analysis. First, in contrast with a standard mixture model assuming that each gene of the genome has the same distribution, we study stratified mixture models allowing genes with different annotations to have different distributions, such as prior probabilities. Second, rather than treating parameters in stratified mixture models independently, we propose a hierarchical model to take advantage of the hierarchical structure of most gene annotation systems, such as gene ontology. We consider a simplified implementation for the proof of concept. An application to a mouse microarray data set and a simulation study demonstrate the improvement of the two new approaches over the standard mixture model. [source] Proteopathogen, a protein database for studying Candida albicans , host interactionPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 20 2009Vital Vialás Abstract There exist, at present, public web repositories for management and storage of proteomic data and also fungi-specific databases. None of them, however, is focused to the specific research area of fungal pathogens and their interactions with the host, and contains proteomics experimental data. In this context, we present Proteopathogen, a database intended to compile proteomics experimental data and to facilitate storage and access to a range of data which spans proteomics workflows from description of the experimental approaches leading to sample preparation to MS settings and peptides supporting protein identification. Proteopathogen is currently focused on Candida albicans and its interaction with macrophages; however, data from experiments concerning different pathogenic fungi species and other mammalian cells may also be found suitable for inclusion into the database. Proteopathogen is publicly available at http://proteopathogen.dacya.ucm.es [source] Comparative proteomic analysis of human mesenchymal and embryonic stem cells: Towards the definition of a mesenchymal stem cell proteomic signaturePROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 2 2009Stephane Roche Abstract Mesenchymal stem cells (MSC) are adult multipotential progenitors which have a high potential in regenerative medicine. They can be isolated from different tissues throughout the body and their homogeneity in terms of phenotype and differentiation capacities is a real concern. To address this issue, we conducted a 2-DE gel analysis of mesenchymal stem cells isolated from bone marrow (BM), adipose tissue, synovial membrane and umbilical vein wall. We confirmed that BM and adipose tissue derived cells were very similar, which argue for their interchangeable use for cell therapy. We also compared human mesenchymal to embryonic stem cells and showed that umbilical vein wall stem cells, a neo-natal cell type, were closer to BM cells than to embryonic stem cells. Based on these proteomic data, we could propose a panel of proteins which were the basis for the definition of a mesenchymal stem cell proteomic signature. [source] Protein probabilities in shotgun proteomics: Evaluating different estimation methods using a semi-random sampling modelPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 23 2006Xiaofang Xue Abstract The calculation of protein probabilities is one of the most intractable problems in large-scale proteomic research. Current available estimating methods, for example, ProteinProphet, PROT_PROBE, Poisson model and two-peptide hits, employ different models trying to resolve this problem. Until now, no efficient method is used for comparative evaluation of the above methods in large-scale datasets. In order to evaluate these various methods, we developed a semi-random sampling model to simulate large-scale proteomic data. In this model, the identified peptides were sampled from the designed proteins and their cross-correlation scores were simulated according to the results from reverse database searching. The simulated result of 18 control proteins was consistent with the experimental one, demonstrating the efficiency of our model. According to the simulated results of human liver sample, ProteinProphet returned slightly higher probabilities and lower specificity than real cases. PROT_PROBE was a more efficient method with higher specificity. Predicted results from a Poisson model roughly coincide with real datasets, and the method of two-peptide hits seems solid but imprecise. However, the probabilities of identified proteins are strongly correlated with several experimental factors including spectra number, database size and protein abundance distribution. [source] Multiple approaches to data-mining of proteomic data based on statistical and pattern classification methodsPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 9 2003Jacob W. Tatay Abstract The data-mining challenge presented is composed of two fundamental problems. Problem one is the separation of forty-one subjects into two classifications based on the data produced by the mass spectrometry of protein samples from each subject. Problem two is to find the specific differences between protein expression data of two sets of subjects. In each problem, one group of subjects has a disease, while the other group is nondiseased. Each problem was approached with the intent to introduce a new and potentially useful tool to analyze protein expression from mass spectrometry data. A variety of methodologies, both conventional and nonconventional were used in the analysis of these problems. The results presented show both overlap and discrepancies. What is important is the breadth of the techniques and the future direction this analysis will create. [source] Comparative proteomic analysis of differentially expressed proteins in primary retinoblastoma tumorsPROTEOMICS - CLINICAL APPLICATIONS, Issue 4 2010Kandalam Mallikarjuna Abstract Purpose: To understand the disease mechanism and to identify the potential tumor markers that would help in therapeutics, comparative proteomic analysis of 29 retinoblastoma (RB) tumors was performed using 14 non-neoplastic retinas (age ranged from 45 to 89 years) as control tissues. Experimental design: 2-DE and MALDI-TOF-TOF MS/MS were used to identify differentially expressed proteins. Results: Twenty-seven distinct differentially expressed proteins were identified, including 16 upregulated 11 downregulated proteins. Significantly, higher mRNA levels of apolipoprotein A1 (p<0.001), transferrin (TF; p<0.001), CRABP2 (p<0.001), ,-crystallin A (CRYAA; p<0.001) were observed in RBs when compared with normal retinas and hence are consistent with the proteomic data. Immunohistochemistry was also performed for selected proteins on paraffin RB blocks to confirm protein expression. RB with invasion showed significantly higher expression by 2-DE-MS/MS analysis of CRABP2 (p<0.001), peroxiredoxin 6 (p=0.025), apolipoprotein A1 (p<0.001), recoverin (p<0.001). Conclusions and clinical relevance: Thus, this study provides a dynamic protein profile of RB tumors, which could provide clues to study the mechanisms of RB oncogenesis and possibly be developed as potential biomarkers for prognosis and therapy. [source] Proteomic profiling reveals comprehensive insights into adrenergic receptor-mediated hypertrophy in neonatal rat cardiomyocytesPROTEOMICS - CLINICAL APPLICATIONS, Issue 12 2009Zijian Li Abstract Myocardial adrenergic receptors (ARs) play important roles in cardiac hypertrophy. However, the detailed molecular mechanism of AR-mediated cardiac hypertrophy remains elusive to date. To gain full insight into how ARs are involved in the regulation of cardiac hypertrophy, protein expression profiling was performed with comparative proteomics approach on neonatal rat cardiomyocytes. Forty-six proteins were identified as differentially expressed in hypertrophic cardiomyocytes induced by AR stimulation. To better understand the biological significance of the obtained proteomic data, we utilized the ingenuity pathway analysis tool to construct biological networks and analyze function and pathways that might associate with AR-mediated cardiac hypertrophy. Pathway analysis strongly suggested that ROS may be involved in the development of AR-mediated cardiac hypertrophy, which was then confirmed by further experimentation. The results showed that a marked increase in ROS production was detected in AR-mediated cardiac hypertrophy and blocking of ROS production significantly inhibited AR-mediated cardiac hypertrophy. We further proved that the ROS production was through NADPH oxidase or the mitochondrial electron transport chain and this ROS accumulation resulted in activation of extracellular signal-regulated kinase 1/2 leading to AR-mediated cardiac hypertrophy. These experimental results support the hypothesis, from the ingenuity pathway analysis, that AR-mediated cardiac hypertrophy is associated with the dysregulation of a complicated oxidative stress-regulatory network. In conclusion, our results provide a basis for understanding the detailed molecular mechanisms of AR-mediated cardiac hypertrophy. [source] Proteomic profiling of animal models mimicking skeletal muscle disordersPROTEOMICS - CLINICAL APPLICATIONS, Issue 9 2007Philip Doran Abstract Over the last few decades of biomedical research, animal models of neuromuscular diseases have been widely used for determining pathological mechanisms and for testing new therapeutic strategies. With the emergence of high-throughput proteomics technology, the identification of novel protein factors involved in disease processes has been decisively improved. This review outlines the usefulness of the proteomic profiling of animal disease models for the discovery of new reliable biomarkers, for the optimization of diagnostic procedures and the development of new treatment options for skeletal muscle disorders. Since inbred animal strains show genetically much less interindividual differences as compared to human patients, considerably lower experimental repeats are capable of producing meaningful proteomic data. Thus, animal model proteomics can be conveniently employed for both studying basic mechanisms of molecular pathogenesis and the effects of drugs, genetic modifications or cell-based therapies on disease progression. Based on the results from comparative animal proteomics, a more informed decision on the design of clinical proteomics studies could be reached. Since no one animal model represents a perfect pathobiochemical replica of all of the symptoms seen in complex human disorders, the proteomic screening of novel animal models can also be employed for swift and enhanced protein biochemical phenotyping. [source] Statistical Issues Arising in the Women's Health InitiativeBIOMETRICS, Issue 4 2005Ross L. Prentice Summary A brief overview of the design of the Women's Health Initiative (WHI) clinical trial and observational study is provided along with a summary of results from the postmenopausal hormone therapy clinical trial components. Since its inception in 1992, the WHI has encountered a number of statistical issues where further methodology developments are needed. These include measurement error modeling and analysis procedures for dietary and physical activity assessment; clinical trial monitoring methods when treatments may affect multiple clinical outcomes, either beneficially or adversely; study design and analysis procedures for high-dimensional genomic and proteomic data; and failure time data analysis procedures when treatment group hazard ratios are time dependent. This final topic seems important in resolving the discrepancy between WHI clinical trial and observational study results on postmenopausal hormone therapy and cardiovascular disease. [source] Cold adaptation in the marine bacterium, Sphingopyxis alaskensis, assessed using quantitative proteomicsENVIRONMENTAL MICROBIOLOGY, Issue 10 2010Lily Ting Summary The cold marine environment constitutes a large proportion of the Earth's biosphere. Sphingopyxis alaskensis was isolated as a numerically abundant bacterium from several cold marine locations, and has been extensively studied as a model marine bacterium. Recently, a metabolic labelling platform was developed to comprehensively identify and quantify proteins from S. alaskensis. The approach incorporated data normalization and statistical validation for the purpose of generating highly confident quantitative proteomics data. Using this approach, we determined quantitative differences between cells grown at 10°C (low temperature) and 30°C (high temperature). Cold adaptation was linked to specific aspects of gene expression: a dedicated protein-folding system using GroESL, DnaK, DnaJ, GrpE, SecB, ClpB and PPIase; polyhydroxyalkanoate-associated storage materials; a link between enzymes in fatty acid metabolism and energy generation; de novo synthesis of polyunsaturated fatty acids in the membrane and cell wall; inorganic phosphate ion transport by a phosphate import PstB homologue; TonB-dependent receptor and bacterioferritin in iron homeostasis; histidine, tryptophan and proline amino acid metabolism; and a large number of proteins without annotated functions. This study provides a new level of understanding on how important marine bacteria can adapt to compete effectively in cold marine environments. This study is also a benchmark for comparative proteomic analyses with other important marine bacteria and other cold-adapted organisms. [source] OVNIp: An open source application facilitating the interpretation, the validation and the edition of proteomics data generated by MS analyses and de novo sequencingPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 9 2010Dominique Tessier Abstract Several academic software are available to help the validation and reporting of proteomics data generated by MS analyses. However, to our knowledge, none of them have been conceived to meet the particular needs generated by the study of organisms whose genomes are not sequenced. In that context, we have developed OVNIp, an open-source application which facilitates the whole process of proteomics results interpretation. One of its unique attributes is its capacity to compile multiple results (from several search engines and/or several databank searches) with a resolution of conflicting interpretations. Moreover, OVNIp enables automated exploitation of de novo sequences generated from unassigned MS/MS spectra leading to higher sequence coverage and enhancing confidence in the identified proteins. The exploitation of these additional spectra might also identify novel proteins through a MS-BLAST search, which can be easily ran from the OVNIp interface. Beyond this primary scope, OVNIp can also benefit to users who look for a simple standalone application to both visualize and confirm MS/MS result interpretations through a simple graphical interface and generate reports according to user-defined forms which may integrate the prerequisites for publication. Sources, documentation and a stable release for Windows are available at http://wwwappli.nantes.inra.fr:8180/OVNIp. [source] Proteomics Data Collection , 3rd ProDaC Workshop April 22nd 2008, Toledo, SpainPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 20 2008Martin Eisenacher Abstract The "Coordination Action" ProDaC (Proteomics Data Collection) , funded by the EU within the 6th framework programme , was created to support the dissemination, utilization and publication of proteomics data. Within this international consortium, standards are developed and maintained to support extensive data collection by the proteomics community. An important part of ProDaC are workshops organized on a regular basis (two per year) to allow discussions and communication between the ProDaC partners and to report on the progress of the project. The kick-off meeting took place in October 2006 in Long Beach, CA, USA. The 1st ProDaC workshop was held in Lyon, France (April 2007) and the 2nd in Seoul, Korea in October 2007. ProDaC organized the 3rd ProDaC workshop at the Beatriz Hotel, Toledo, on 22nd April, 2008, directly before the HUPO - PSI spring meeting (Human Proteome Organisation - Proteomics Standards Initiative). The work package coordinators presented talks about the progress achieved during the past six months. Additionally four external speakers presented their work on data conversion and data repositories. The concluding discussion session was chaired by the Journal's representative. [source] Flow cytometry-assisted purification and proteomic analysis of the corticotropes dense-core secretory granulesPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 18 2008Daniel J. Gauthier Abstract The field of organellar proteomics has emerged as an attempt to minimize the complexity of the proteomics data obtained from whole cell and tissue extracts while maximizing the resolution on the protein composition of a single subcellular compartment. Standard methods involve lengthy density-based gradient and/or immunoaffinity purification steps followed by extraction, 1-DE or 2-DE, gel staining, in-gel tryptic digestion, and protein identification by MS. In this paper, we present an alternate approach to purify subcellular organelles containing a fluorescent reporter molecule. The gel-free procedure involves fluorescence-assisted sorting of the secretory granules followed by gentle extraction in a buffer compatible with tryptic digestion and MS. Once the subcellular organelle labeled, this procedure can be done in a single day, requires no major modification to any instrumentation and can be readily adapted to the study of other organelles. When applied to corticotrope secretory granules, it led to a much enriched granular fraction from which numerous proteins could be identified through MS. [source] Proteomics Data Collection , The 1st ProDaC workshop 26 April 2007 Ecole Normale Supérieur, Lyon, FrancePROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 17 2007Martin Eisenacher Dr. Abstract Proteomics Data Collection (ProDaC) is an EU funded "Coordination Action" within the 6th framework programme. It aims to simplify the publication, dissemination and utilization of proteomics data by establishing standards that will support broad data collection from the research community. The 1st ProDaC workshop 2007 (succeeding the kick-off meeting last year at the HUPO World Congress 2006) took place at the Ecole Normale Supérieur in Lyon, France. These workshops take place as regular meetings on a half-year basis. On Thursday April 26th 2007 the progress of the first six months of the project was presented by the leaders of each of the seven work packages. [source] Proteome informatics for cancer research: From molecules to clinicPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 6 2007Vladimir Brusic Dr. Abstract Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy. [source] The HUPO Proteomics Standards Initiative , Overcoming the Fragmentation of Proteomics DataPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue S2 2006Henning Hermjakob Proteomics is a key field of modern biomolecular research, with many small and large scale efforts producing a wealth of proteomics data. However, the vast majority of this data is never exploited to its full potential. Even in publicly funded projects, often the raw data generated in a specific context is analysed, conclusions are drawn and published, but little attention is paid to systematic documentation, archiving, and public access to the data supporting the scientific results. It is often difficult to validate the results stated in a particular publication, and even simple global questions like ,In which cellular contexts has my protein of interest been observed?" can currently not be answered with realistic effort, due to a lack of standardised reporting and collection of proteomics data. The Proteomics Standards Initiative (PSI), a work group of the Human Proteome Organisation (HUPO), defines community standards for data representation in proteomics to facilitate systematic data capture, comparison, exchange and verification. In this article we provide an overview of PSI organisational structure, activities, and current results, as well as ways to get involved in the broad-based, open PSI process. [source] SPLASH: Systematic proteomics laboratory analysis and storage hubPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 6 2006Siaw Ling Lo Abstract In the field of proteomics, the increasing difficulty to unify the data format, due to the different platforms/instrumentation and laboratory documentation systems, greatly hinders experimental data verification, exchange, and comparison. Therefore, it is essential to establish standard formats for every necessary aspect of proteomics data. One of the recently published data models is the proteomics experiment data repository [Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D. et,al., Nat. Biotechnol. 2003, 21, 247,254]. Compliant with this format, we developed the systematic proteomics laboratory analysis and storage hub (SPLASH) database system as an informatics infrastructure to support proteomics studies. It consists of three modules and provides proteomics researchers a common platform to store, manage, search, analyze, and exchange their data. (i),Data maintenance includes experimental data entry and update, uploading of experimental results in batch mode, and data exchange in the original PEDRo format. (ii),The data search module provides several means to search the database, to view either the protein information or the differential expression display by clicking on a gel image. (iii),The data mining module contains tools that perform biochemical pathway, statistics-associated gene ontology, and other comparative analyses for all the sample sets to interpret its biological meaning. These features make SPLASH a practical and powerful tool for the proteomics community. [source] Correlation-associated peptide networks of human cerebrospinal fluidPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 11 2005Jens Lamerz Dr. Abstract Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides. [source] Strategic shotgun proteomics approach for efficient construction of an expression map of targeted protein families in hepatoma cell linesPROTEINS: STRUCTURE, FUNCTION AND BIOINFORMATICS, Issue 12 2003Chih-Lei Lee Abstract An expression map of the most abundant proteins in human hepatoma HepG2 cells was established by a combination of complementary shotgun proteomics approaches. Two-dimensional liquid chromatography (LC)-nano electrospray ionization (ESI) tandem mass spectrometry (MS/MS) as well as one-dimensional LC-matrix-assisted laser desorption/ionization MS/MS were evaluated and shown that additional separation introduced at the peptide level was not as efficient as simple prefractionation of protein extracts in extending the range and total number of proteins identified. Direct LC-nanoESI MS/MS analyses of peptides from total solubilized fraction and the excised gel bands from one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis fractionated insolubilized fraction afforded the best combination in efficient construction of a nonredundant cell map. Compiling data from multiple variations of rapid shotgun proteomics analyses is nonetheless useful to increase sequence coverage and confidence of hits especially for those proteins identified primarily by a single or two peptide matches. While the returned hit score in general reflects the abundance of the respective proteins, it is not a reliable index for differential expression. Using another closely related hepatoma Hep3B as a comparative basis, 16 proteins with more than two-fold difference in expression level as defined by spot intensity in two-dimensional gel electrophoresis analysis were identified which notably include members of the heat shock protein (Hsp) and heterogeneous nuclear ribonucleoprotein (hnRPN) families. The observed higher expression level of hnRNP A2/B1 and Hsp90 in Hep3B led to a search for reported functional roles mediated in concert by both these multifunctional cellular chaperones. In agreement with the proposed model for telomerase and telomere bound proteins in promoting their interactions, data was obtained which demonstrated that the expression proteomics data could be correlated with longer telomeric length in tumorigenic Hep3B. This biological significance constitutes the basis for further delineation of the dynamic interactions and modifications of the two protein families and demonstrated how proteomic and biological investigation could be mutually substantiated in a productive cycle of hypothesis and pattern driven research. [source] Neuroproteomics and its applications in research on nicotine and other drugs of abusePROTEOMICS - CLINICAL APPLICATIONS, Issue 11 2007Ming D. Li Dr. Abstract The rapidly growing field of neuroproteomics is able to track changes in protein expression and protein modifications underlying various physiological conditions, including the neural diseases related to drug addiction. Thus, it presents great promise in characterizing protein function, biochemical pathways, and networks to understand the mechanisms underlying drug dependence. In this article, we first provide an overview of proteomics technologies and bioinformatics tools available to analyze proteomics data. Then we summarize the recent applications of proteomics to profile the protein expression pattern in animal or human brain tissues after the administration of nicotine, alcohol, amphetamine, butorphanol, cocaine, and morphine. By comparing the protein expression profiles in response to chronic nicotine exposure with those appearing in response to treatment with other drugs of abuse, we identified three biological processes that appears to be regulated by multiple drugs of abuse: energy metabolism, oxidative stress response, and protein degradation and modification. Such similarity indicates that despite the obvious differences among their chemical properties and the receptors with which they interact, different substances of abuse may cause some similar changes in cellular activities and biological processes in neurons. [source] Systems biology analysis of sjögren's syndrome and mucosa-associated lymphoid tissue lymphoma in parotid glandsARTHRITIS & RHEUMATISM, Issue 1 2009Shen Hu Objective To identify key target genes and activated signaling pathways associated with the pathogenesis of Sjögren's syndrome (SS) by conducting a systems analysis of parotid glands manifesting primary SS or primary SS/mucosa-associated lymphoid tissue (MALT) lymphoma phenotypes. Methods A systems biology approach was used to analyze parotid gland tissue samples obtained from patients with primary SS, patients with primary SS/MALT lymphoma, and subjects without primary SS (non,primary SS controls). The tissue samples were assessed concurrently by gene-expression microarray profiling and proteomics analysis, followed by weighted gene-coexpression network analysis. Results Gene-coexpression modules related to primary SS and primary SS/MALT lymphoma were significantly enriched with genes known to be involved in the immune/defense response, apoptosis, cell signaling, gene regulation, and oxidative stress. Detailed functional pathway analyses indicated that primary SS,associated modules were enriched with genes involved in proteasome degradation, apoptosis, signal peptides of the class I major histocompatibility complex (MHC), complement activation, cell growth and death, and integrin-mediated cell adhesion, while primary SS/MALT lymphoma,associated modules were enriched with genes involved in translation, ribosome biogenesis and assembly, proteasome degradation, class I MHC signal peptides, the G13 signaling pathway, complement activation, and integrin-mediated cell adhesion. Combined analyses of gene expression and proteomics data implicated 6 highly connected "hub" genes for distinguishing primary SS from non,primary SS, and 8 hub genes for distinguishing primary SS/MALT lymphoma from primary SS. Conclusion Systems biology analyses of the parotid glands from patients with primary SS and those with primary SS/MALT lymphoma revealed pathways and molecular targets associated with disease pathogenesis. The identified gene modules/pathways provide further insights into the molecular mechanisms of primary SS and primary SS/MALT lymphoma. The identified disease-hub genes represent promising targets for therapeutic intervention, diagnosis, and prognosis. [source] Proteomics: Recent Applications and New TechnologiesBASIC AND CLINICAL PHARMACOLOGY & TOXICOLOGY, Issue 5 2006Mollisa M. Elrick Proteomic analyses have recently been conducted on tissues, biofluids, subcellular components and enzymatic pathways as well as various disease and toxicological states, in both animal models and man. In addition, several recent studies have attempted to integrate proteomics data with genomics and/or metabonomics data in a systems biology approach. The translation of proteomic technology and bioinformatics tools to clinical samples, such as in the areas of disease and toxicity biomarkers, represents one of the major opportunities and challenges facing this field. An ongoing challenge in proteomics continues to be the analysis of the serum proteome due to the vast number and complexity of proteins estimated to be present in this biofluid. Aside from the removal of the most abundant proteins, a number of interesting approaches have recently been suggested that may help reduce the overall complexity of serum analysis. In keeping with the increasing interest in applications of proteomics, the tools available for proteomic analyses continue to improve and expand. For example, enhanced tools (such as software and labeling procedures) continue to be developed for the analysis of 2D gels and protein quantification. In addition, activity-based probes are now being used to tag, enrich and isolate distinct sets of proteins based on enzymatic activity. One of the most active areas of development involves microarrays. Antibody-based microarrays have recently been released as commercial products while numerous additional capture agents (e.g. aptamers) and many additional types of microarrays are being explored. [source] Recent Progress in Biomolecular EngineeringBIOTECHNOLOGY PROGRESS, Issue 1 2000Dewey D. Y. Ryu During the next decade or so, there will be significant and impressive advances in biomolecular engineering, especially in our understanding of the biological roles of various biomolecules inside the cell. The advances in high throughput screening technology for discovery of target molecules and the accumulation of functional genomics and proteomics data at accelerating rates will enable us to design and discover novel biomolecules and proteins on a rational basis in diverse areas of pharmaceutical, agricultural, industrial, and environmental applications. As an applied molecular evolution technology, DNA shuffling will play a key role in biomolecular engineering. In contrast to the point mutation techniques, DNA shuffling exchanges large functional domains of sequences to search for the best candidate molecule, thus mimicking and accelerating the process of sexual recombination in the evolution of life. The phage-display system of combinatorial peptide libraries will be extensively exploited to design and create many novel proteins, as a result of the relative ease of screening and identifying desirable proteins. Even though this system has so far been employed mainly in screening the combinatorial antibody libraries, its application will be extended further into the science of protein-receptor or protein-ligand interactions. The bioinformatics for genome and proteome analyses will contribute substantially toward ever more accelerated advances in the pharmaceutical industry. Biomolecular engineering will no doubt become one of the most important scientific disciplines, because it will enable systematic and comprehensive analyses of gene expression patterns in both normal and diseased cells, as well as the discovery of many new high-value molecules. When the functional genomics database, EST and SAGE techniques, microarray technique, and proteome analysis by 2-dimensional gel electrophoresis or capillary electrophoresis in combination with mass spectrometer are all put to good use, biomolecular engineering research will yield new drug discoveries, improved therapies, and significantly improved or new bioprocess technology. With the advances in biomolecular engineering, the rate of finding new high-value peptides or proteins, including antibodies, vaccines, enzymes, and therapeutic peptides, will continue to accelerate. The targets for the rational design of biomolecules will be broad, diverse, and complex, but many application goals can be achieved through the expansion of knowledge based on biomolecules and their roles and functions in cells and tissues. Some engineered biomolecules, including humanized Mab's, have already entered the clinical trials for therapeutic uses. Early results of the trials and their efficacy are positive and encouraging. Among them, Herceptin, a humanized Mab for breast cancer treatment, became the first drug designed by a biomolecular engineering approach and was approved by the FDA. Soon, new therapeutic drugs and high-value biomolecules will be designed and produced by biomolecular engineering for the treatment or prevention of not-so-easily cured diseases such as cancers, genetic diseases, age-related diseases, and other metabolic diseases. Many more industrial enzymes, which will be engineered to confer desirable properties for the process improvement and manufacturing of high-value biomolecular products at a lower production cost, are also anticipated. New metabolites, including novel antibiotics that are active against resistant strains, will also be produced soon by recombinant organisms having de novo engineered biosynthetic pathway enzyme systems. The biomolecular engineering era is here, and many of benefits will be derived from this field of scientific research for years to come if we are willing to put it to good use. [source] | ||||||||||||||||