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At least 469 records · Page 26Linked to original sources
PubMed2005

High abundance protein profiling of cystic fibrosis lung epithelial cells.

Protein profiles of cultured cystic fibrosis (CF) lung epithelial cells were analyzed by two-dimensional gel electrophoresis and mass spectrometry (MS). The analysis gave rise to a protein map over the pI range of 4-7, and a molecular weight range of ca. 100-10 kDa. The map contains 194 identified proteins, which were detectable by silver stain. All silver stained features were identified by matrix-assisted laser desorption/ionization-time of flight MS of tryptic peptides. Some proteins were found to be represented by multiple features on the 2-D gel. Among the high abundance proteins identified were sets of proteins associated with inflammation, including the classical NFkappaB, p65 (RelA) and NFkappaB, p65 (RelB). We suggest that this composite atlas of the high abundance CF lung epithelial proteome will serve as a reference database for future studies of candidate CF drugs, validating different approaches to CFTR gene therapy, and analogous investigations of other types of human lung disorders.

Cell Culture Techniques↗
PubMed2006

Web-based MS/MS data analysis.

This tutorial focuses on three MS/MS data analysis programs currently available via a web interface: Mascot, Phenyx and X!Tandem. Although these programs process the same input and often produce comparable outputs, subtle differences remain. The use of parameters that are requested in the on-line forms and the subsequent interpretation of results are illustrated and explained via a single example.

Amino Acids↗
PubMed2002

A method to identify and simultaneously determine the relative quantities of proteins isolated by gel electrophoresis.

Gel electrophoresis is often used for the primary analysis and purification of proteins, and peptide mapping by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a widely used technique for the rapid identification of unknown proteins. The identification is usually obtained by digesting the protein with an enzyme and matching the masses of the proteolytic peptides with those of each protein in a sequence database. Another important aspect in many proteomic experiments is the determination of the relative protein quantities (e.g. comparison between control and altered states). Usually, this is obtained by comparing the spot intensities of two independent gels. This procedure is time-consuming and not very accurate. Recently, several methodologies using isotope labeling of proteins for quantitative proteomic studies have been introduced (e.g. using ICAT reagents or growing cells in isotopically enriched nutrients). However, none of these methodologies is foolproof and there is still the need for simple and inexpensive alternatives for determining the relative quantities of proteins. Previously, we showed that a mixture of acrylamide and deuterated acrylamide could be used as cysteine alkylating reagent prior to electrophoresis, improving the coverage and the confidence of the protein identification procedure (Sechi S, Chait BT. Anal. Chem. 1998; 70: 5150). Here we show that a similar approach can be used to obtain relative quantitation at the femtomole level of proteins isolated by gel electrophoresis. Deuterated acrylamide is used to alkylate the cysteines in one sample and regular acrylamide is used to alkylate the cysteines in the second sample. The two samples are then mixed together in a 1:1 ratio and the relative protein quantities are determined from the ion intensity ratios of the two cysteine-containing peptides isotopic envelopes (regular/deuterated). The analysis of several proteins mixed in different ratios is reported showing that this approach can reliably be used for protein identification and quantification. Briefly, a simple and inexpensive method for quantifying and simultaneously identifying proteins isolated by gel electrophoresis using MALDI-MS is presented.

Alkylating Agents↗
PubMed2006

Puzzling over orphan enzymes.

Despite the current availability of several hundreds of thousands of amino acid sequences, more than 39% of the well-defined enzyme activities (EC numbers) are not associated with any sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found in nearly all classes of enzymes. Thus, there is an urgent need to explore the 1525 orphan enzymes (EC numbers without associated sequences), in order to progressively bridge this unwanted gap. Improving genome annotation could unveil a significant proportion of sequenceless enzymes. Peptide mass mapping and further genome mining would be useful to identify proper sequence for enzymes found in species for which genetic tools are missing. Finally, the whole community must help major public databases to begin addressing the problem of missing or incomplete information.

Chromosome Mapping↗
PubMed2007

Organization of proteomics data with YassDB.

In recent years the organization of mass spectrometry (MS) data obtained in large-scale proteomics projects became an important issue. This has catalyzed the development of a few different database schemes for storing MS data, as well as some dedicated user interfaces. However, many of these projects are still rather immature and often do not cover all needs. Because our needs were quite specific, it was necessary to build a database that accommodates all the major types of experiments generated in house and that could be easily extended by new modules made by collaborators or students. A database application named "YassDB" will be described in this chapter. The application is implemented in a "three-tier" application architecture, with a database layer, a middle layer consisting of web services and a client layer, containing the user interface. This offers high flexibility: it allows other applications, written in any language, to be written as clients to the database. The setup and use of the YassDB database application with two client programs "pProRep" and "VEMS" will be outlined.

Databases, Protein↗
PubMed2004

The -omics era and its impact.

OBJECTIVE: To review the advances in clinically useful molecular biologic techniques and to identify their applications, as presented at the 12th Annual William Beaumont Hospital DNA Symposium. DATA SOURCES: The 7 manuscripts submitted were reviewed and their major findings were compared with literature on the same or related topics. STUDY SELECTION: Manuscripts address the use of molecular techniques in the detection of severe acute respiratory syndrome (SARS) and bacterial ribosome mutations, which may lead to ribosome-targeted drug resistance; pharmacogenomics as a clinical laboratory service and example of warfarin dosing using CYP2C9 mutation analysis; definition of the potential of cytosine arabinoside incorporation into DNA to disrupt transcription using an in vitro model of oligonucleotides; use of laser capture microdissection to isolate solid tumor cells free of nontumor cells; and molecular methods used to classify lymphomas. DATA SYNTHESIS: Two current issues related to the use of molecular tests in the clinical laboratories are (1) decentralization of molecular-based testing to a variety of nonmolecular laboratories and (2) need for wider acceptance of molecular-based testing through its incorporation in clinical practice guidelines. Molecular methods have had a major impact on infectious disease through the rapid identification of new infectious agents, SARS, and the characterization of drug resistance. Pharmacogenomics identifies the genetic basis for heritable and interindividual variation in response to drugs. The incorporation of the nucleoside analog, cytosine arabinoside, into DNA leads to local perturbation of DNA structure and reduces the ability of transcription factors to bind to their specific DNA binding elements as measured by electrophoretic mobility shift assays. Laser capture microdissection of tumor cells can provide an adequate number of cells for whole genome amplification. Gene expression microassay profiles of various lymphomas have modified classification systems and predict prognosis and response to therapy. CONCLUSIONS: The current -omics era will continue to emphasize the use of microarrays and database software for genomic, transcriptomic, and proteomic screening to search for a useful clinical assay. The number of molecular pathologic techniques will expand as additional disease-associated mutations are defined.

Animals↗
PubMed2000

[A new approach to pharmacogenomics].

The medicine in the 21st century will be so called "evidence based medicine" or "personalized medicine," based on the principle of "right drug to right patient." Pharmacogenomics covers the entire spectrum of genes that determines drug behavior and sensitivity, and we anticipate it will bring major impact on the healthcare system as well as the drug discovery process in the near future. Three waves of genomic impact are predicted to arise as follows: The first wave will hit on existing drugs and late-phase development candidates within the next 2-3 years, aiming to minimize the risks in clinical trials (adverse events, resistance, etc.). The wave will then affect the candidate selection process in the early pre-development stage, and finally the disease gene finding to target discovery process. The driving force will be technologies such as SNPs database, differential gene expression (DGE) analysis, proteomics, serial analysis of gene expression (SAGE) and bioinformatics. This new approach of genomic discovery (so called "integrated approach") requires knowledge on how to implement and integrate new valuable technologies from an early stage of the discovery process. The implication of SNPs, high throughput proteomics and application of structural genomics will be the key issues in the pharmacogenomics era.

Genome↗
PubMedDate not supplied

[New effect biomarkers].

The major research goals for researchers developing biomarkers of effect are the development and validation of biomarkers that permit the prediction of the risk of disease in individuals and groups. One important objective is to prevent human cancer. This article reviews the most recent analytical methodologies, validation studies and field trials together with auditing and quality assessment of the necessary data based on scientific grounds. Consideration is given to new developments in the relatively young field of toxicogenomics, possibly leading to the identification of early changes that may lead to both cancer and non-cancer end points. Although the creation and development of reliable databases integrating information from genomic and proteomic research programmes should offer a contribution to the prediction of risks and prevention of diseases related to chemical exposure, the most promising future application of these technologies lies in the molecular diagnosis of diseases whose nosography will probably be redefined.

Biomarkers↗
PubMed2006

A machine learning approach to predicting peptide fragmentation spectra.

Accurate peptide identification from tandem mass spectrometry experiments is the cornerstone of proteomics. Although various approaches for matching database sequences with experimental spectra have been developed to date (e.g. Sequest, Mascot) the sensitivity and specificity of peptide identification have not yet reached their full potential. This is in part due to the tradeoffs between robustness and accuracy of the existing methods with respect to the non-uniform nature of peptide fragmentation and bond cleavages induced by different mass spectrometers. Accordingly, it is expected that new approaches to de novo predicting peptide fragmentation spectra will enable more accurate peptide identification. To address this problem, here we used a data-driven approach to learn peptide fragmentation rules in mass spectrometry, in the form of posterior probabilities, for various fragment-ion types of doubly and triply charged precursor ions. We show that the accuracy of our neural-network based methodology is useful for subsequent peptide database searches and that the most useful rules of fragmentation significantly differ across ion and precursor types.

Amino Acids↗
PubMed2006

Mining Alzheimer disease relevant proteins from integrated protein interactome data.

Huge unrealized post-genome opportunities remain in the understanding of detailed molecular mechanisms for Alzheimer Disease (AD). In this work, we developed a computational method to rank-order AD-related proteins, based on an initial list of AD-related genes and public human protein interaction data. In this method, we first collected an initial seed list of 65 AD-related genes from the OMIM database and mapped them to 70 AD seed proteins. We then expanded the seed proteins to an enriched AD set of 765 proteins using protein interactions from the Online Predicated Human Interaction Database (OPHID). We showed that the expanded AD-related proteins form a highly connected and statistically significant protein interaction sub-network. We further analyzed the sub-network to develop an algorithm, which can be used to automatically score and rank-order each protein for its biological relevance to AD pathways(s). Our results show that functionally relevant AD proteins were consistently ranked at the top: among the top 20 of 765 expanded AD proteins, 19 proteins are confirmed to belong to the original 70 AD seed protein set. Our method represents a novel use of protein interaction network data for Alzheimer disease studies and may be generalized for other disease areas in the future.

Algorithms↗
PubMed2003

Identification of glycosylphosphatidylinositol-anchored proteins in Arabidopsis. A proteomic and genomic analysis.

In a recent bioinformatic analysis, we predicted the presence of multiple families of cell surface glycosylphosphatidylinositol (GPI)-anchored proteins (GAPs) in Arabidopsis (G.H.H. Borner, D.J. Sherrier, T.J. Stevens, I.T. Arkin, P. Dupree [2002] Plant Physiol 129: 486-499). A number of publications have since demonstrated the importance of predicted GAPs in diverse physiological processes including root development, cell wall integrity, and adhesion. However, direct experimental evidence for their GPI anchoring is mostly lacking. Here, we present the first, to our knowledge, large-scale proteomic identification of plant GAPs. Triton X-114 phase partitioning and sensitivity to phosphatidylinositol-specific phospholipase C were used to prepare GAP-rich fractions from Arabidopsis callus cells. Two-dimensional fluorescence difference gel electrophoresis and one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis demonstrated the existence of a large number of phospholipase C-sensitive Arabidopsis proteins. Using liquid chromatography-tandem mass spectrometry, 30 GAPs were identified, including six beta-1,3 glucanases, five phytocyanins, four fasciclin-like arabinogalactan proteins, four receptor-like proteins, two Hedgehog-interacting-like proteins, two putative glycerophosphodiesterases, a lipid transfer-like protein, a COBRA-like protein, SKU5, and SKS1. These results validate our previous bioinformatic analysis of the Arabidopsis protein database. Using the confirmed GAPs from the proteomic analysis to train the search algorithm, as well as improved genomic annotation, an updated in silico screen yielded 64 new candidates, raising the total to 248 predicted GAPs in Arabidopsis.

Arabidopsis↗
PubMed2004

WILMA-automated annotation of protein sequences.

Large-scale annotation of sets of proteins is a frequently occurring task in association with genome sequencing projects. Here, we present an automated platform for the functional annotation of large sets of protein sequences. Various bioinformatics tools are used to achieve a comprehensive description of protein sequences and to link these results to standard Gene Ontology descriptors for molecular function, biological processes and cellular components. Access to the annotation is provided via a web-interface and database queries. These interfaces allow to formulate proteome wide queries as well as the investigation of details of individual results. WILMA annotations of the proteomes of Homo sapiens, Mus musculus, Arabidopsis thaliana and Caenorhabditis elegans are accessible at http://www.came.sbg.ac.at/wilma/

Amino Acid Sequence↗
PubMed2005

Proteomic analysis of protein components in periodontal ligament fibroblasts.

BACKGROUND: Characterization of periodontal ligament (PDL) fibroblast proteome is an important tool for understanding PDL physiology and regulation and for identifying disease-related protein markers. PDL fibroblast protein expression has been studied using immunological methods, although limited to previously identified proteins for which specific antibodies are available. METHODS: We applied proteomic analysis coupled with mass spectrometry and database knowledge to human PDL fibroblasts. RESULTS: We detected 900 spots and identified 117 protein spots originating in 74 different genes. In addition to scaffold cytoskeletal proteins, e.g., actin, tubulin, and vimentin, we identified proteins implicated with cellular motility and membrane trafficking, chaparonine, stress and folding proteins, metabolic enzymes, proteins associated with detoxification and membrane activity, biodegradative metabolism, translation and transduction, extracellular proteins, and cell cycle regulation proteins. CONCLUSIONS: Most of these identified proteins are closely related to the extensive PDL fibroblasts' functions and homeostasis. Our PDL fibroblast proteome map can serve as a reference map for future clinical studies as well as basic research.

Adolescent↗
PubMed2005

MiGenes: a searchable interspecies database of mitochondrial proteins curated using gene ontology annotation.

MOTIVATION: There has been an explosion of interest in the role of mitochondria in programmed cell death and other fundamental pathological processes underlying the development of human diseases. Nevertheless, the inventory of mitochondrial proteins encoded in the nuclear genome remains incomplete, providing an impediment to mitochondrial research at the interface with systems biology. We created the MiGenes database to further define the scope of the mitochondrial proteome in humans and model organisms including mice, rats, flies and worms as well as budding and fission yeasts. MiGenes is intended to stimulate mitochondrial research using model organisms. SUMMARY: MiGenes is a large-scale relational database that is automatically updated to keep pace with advances in mitochondrial proteomics and is curated to assure that the designation of proteins as mitochondrial reflects gene ontology (GO) annotations supported by high-quality evidence codes. A set of postulates is proposed to help define which proteins are authentic components of mitochondria. MiGenes incorporates >1160 new GO annotations to human, mouse and rat protein records, 370 of which represent the first GO annotation reflecting a mitochondrial localization. MiGenes employs a flexible search interface that permits batchwise accession number searches to support high-throughput proteomic studies. A web interface is provided to permit members of the mitochondrial research community to suggest modifications in protein annotations or mitochondrial status.

Animals↗
PubMed1999

Grasping at molecular interactions and genetic networks in Drosophila melanogaster using FlyNets, an Internet database.

FlyNets (http://gifts.univ-mrs.fr/FlyNets/FlyNets_home_page.++ +html) is a WWW database describing molecular interactions (protein-DNA, protein-RNA and protein-protein) in the fly Drosophila melanogaster. It is composed of two parts, as follows. (i) FlyNets-base is a specialized database which focuses on molecular interactions involved in Drosophila development. The information content of FlyNets-base is distributed among several specific lines arranged according to a GenBank-like format and grouped into five thematic zones to improve human readability. The FlyNets database achieves a high level of integration with other databases such as FlyBase, EMBL, GenBank and SWISS-PROT through numerous hyperlinks. (ii) FlyNets-list is a very simple and more general databank, the long-term goal of which is to report on any published molecular interaction occuring in the fly, giving direct web access to corresponding s in Medline and in FlyBase. In the context of genome projects, databases describing molecular interactions and genetic networks will provide a link at the functional level between the genome, the proteome and the transcriptome worlds of different organisms. Interaction databases therefore aim at describing the contents, structure, function and behaviour of what we herein define as the interactome world.

Animals↗