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Analysis of signaling pathways using functional proteomics.

Advances in analytical methods for protein analysis by mass spectrometry provide new tools for global analysis of the expressed protein profile of cells (referred to as proteomics). Currently, available methodology samples only part of the proteome. This is sufficient for analysis of signal transduction, because signaling pathways contain enzymes, which modify high-abundance proteins other than those of the pathway. Thus, modulation of the signaling through a pathway will produce a "footprint" in the proteome that is characteristic of a specific cell phenotype. Comparison of different samples to identify these differences in posttranslational modification or protein expression is referred to as functional proteomics. This review surveys the methods in widest use in functional proteomics, as well as a few promising new ones. Although proteomic analyses were first conducted 26 years ago, a renewed interest is fueled by several recent advances. Most important are the availability of public genome and protein databases and the development of high-sensitivity, easy-to-use mass spectrometers and database search engines capable of exploiting these databases. Other important advances include improved two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), computer programs for analysis of the 2D-PAGE gel images, protocols for proteolytic digestion of proteins in excised gel pieces, and low-flow chromatography methods. Despite the limitations of these methods, they can distinguish subtle changes in the phenotype of cells, providing the basis for future studies in regulation of the phenotype.

Animals↗

Proteomic analysis of Bacillus anthracis Sterne vegetative cells.

Mass spectrometry and proteomics have found increasing use as tools for the rapid detection of pathogenic bacteria, even when they are in a mixture of non-pathogenic relatives. The success of this technique is greatly augmented by the availability of publicly accessible proteomic databases for specific pathogenic bacteria. To aid proteomic detection analyses for the causative agent of anthrax, we have constructed a comprehensive proteomic catalogue of vegetative Bacillus anthracis Sterne cells using liquid chromatography tandem-mass spectrometry. Proteins were separated by molecular weight or isoelectric point prior to tryptic digestion. Alternatively, the whole protein extract was digested and tryptic peptides were separated by cation exchange chromatography prior to Reverse Phase-LC-MS/MS. The use of three complementary, pre-analytical separation techniques resulted in the identification of 1048 unique proteins, including 694 cytosolic, 153 membrane (including 27 cell wall), and 30 secreted proteins, accounting for 19% of the total predicted proteome. Each identified protein was functionally categorized using the gene attribute database from TIGR CMR. These results provide a large proteomic catalogue of vegetative B. anthracis cells and, coupled with the recent proteomic catalogue of B. anthracis spore proteins, form a thorough summary of proteins expressed in the active and dormant stages of this organism.

Bacillus anthracis↗

Local weighting schemes for protein multiple sequence alignment.

This paper describes three weighting schemes for improving the accuracy of progressive multiple sequence alignment methods: (1) global profile pre-processing, to capture for each sequence information about other sequences in a profile before the actual multiple alignment takes place; (2) local pre-processing; which incorporates a new protocol to only use non-overlapping local sequence regions to construct the pre-processed profiles; and (3) local-global alignment, a weighting scheme based on the double dynamic programming (DDP) technique to softly bias global alignment to local sequence motifs. The first two schemes allow the compilation of residue-specific multiple alignment reliability indices, which can be used in an iterative fashion. The schemes have been implemented with associated iterative modes in the PRALINE multiple sequence alignment method, and have been evaluated using the BAliBASE benchmark alignment database. These tests indicate that PRALINE is a toolbox able to build alignments with very high quality. We found that local profile pre-processing raises the alignment quality by 5.5% compared to PRALINE alignments generated under default conditions. Iteration enhances the quality by a further percentage point. The implications of multiple alignment scoring functions and iteration in relation to alignment quality and benchmarking are discussed.

Amino Acid Motifs↗

Plant-based microarray data at the European Bioinformatics Institute. Introducing AtMIAMExpress, a submission tool for Arabidopsis gene expression data to ArrayExpress.

ArrayExpress is a public microarray repository founded on the Minimum Information About a Microarray Experiment (MIAME) principles that stores MIAME-compliant gene expression data. Plant-based data sets represent approximately one-quarter of the experiments in ArrayExpress. The majority are based on Arabidopsis (Arabidopsis thaliana); however, there are other data sets based on Triticum aestivum, Hordeum vulgare, and Populus subsp. AtMIAMExpress is an open-source Web-based software application for the submission of Arabidopsis-based microarray data to ArrayExpress. AtMIAMExpress exports data in MAGE-ML format for upload to any MAGE-ML-compliant application, such as J-Express and ArrayExpress. It was designed as a tool for users with minimal bioinformatics expertise, has comprehensive help and user support, and represents a simple solution to meeting the MIAME guidelines for the Arabidopsis community. Plant data are queryable both in ArrayExpress and in the Data Warehouse databases, which support queries based on gene-centric and sample-centric annotation. The AtMIAMExpress submission tool is available at http://www.ebi.ac.uk/at-miamexpress/. The software is open source and is available from http://sourceforge.net/projects/miamexpress/. For information, contact miamexpress@ebi.ac.uk.

Academies and Institutes↗

Predicting Class II MHC-Peptide binding: a kernel based approach using similarity scores.

BACKGROUND: Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. RESULTS: The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP 1, MCHBN 2, and MHCBench 3. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. CONCLUSION: The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

Binding Sites↗

KISS: the kinetoplastid RNA editing sequence search tool.

Kinetoplastid mitochondrial mRNA editing is a post-transcriptional process of uridine insertion and deletion. Editing is mediated by small RNA molecules termed guide RNAs (gRNAs). Most gRNAs are encoded by numerous small circular DNA minicircles, while the protein coding mitochondrial genes are encoded on a separate, larger genome called the maxicircle. In order to provide a workbench for the analysis of RNA editing in kinetoplastids and a well-annotated set of guide RNAs for Trypanosoma brucei, we generated the kinetoplastid RNA editing sequence search tool (KISS) (http://gmod.mbl.edu/kiss/). KISS is a pipeline and database that uses BLAST comparisons and minicircle sequence motifs to annotate potential gRNAs and cognate mRNA editing sequence. KISS 1.0 contains all previously known minicircle and maxicircle data from Trypanosoma brucei plus >400 new minicircle sequences. Using an online format, KISS 1.0 allows the mapping and visualization of all known T. brucei gRNAs to minicircle genes and to potential mRNA substrates for RNA editing.

Animals↗

Proteomic analysis by multidimensional protein identification technology.

Multidimensional chromatography coupled to mass spectrometry is an emerging technique for the analysis of complex protein mixtures. One approach in this general category, multidimensional protein identification technology (MudPIT), couples biphasic or triphasic microcapillary columns to high-performance liquid chromatography, tandem mass spectrometry, and database searching. The integration of each of these components is critical to the implementation of MudPIT in a laboratory. MudPIT can be used for the analysis of complex peptide mixtures generated from biofluids, tissues, cells, organelles, or protein complexes. The information described in this chapter will provide researchers with details for sample preparation, column assembly, and chromatography parameters for complex peptide mixture analysis.

Animals↗

A new hybrid approach to predict subcellular localization of proteins by incorporating gene ontology.

Based on the recent development in the gene ontology and functional domain databases, a new hybridization approach is developed for predicting protein subcellular location by combining the gene product, functional domain, and quasi-sequence-order effects. As a showcase, the same prokaryotic and eukaryotic datasets, which were studied by many previous investigators, are used for demonstration. The overall success rate by the jackknife test for the prokaryotic set is 94.7% and that for the eukaryotic set 92.9%. These are so far the highest success rates achieved for the two datasets by following a rigorous cross-validation test procedure, suggesting that such a hybrid approach may become a very useful high-throughput tool in the area of bioinformatics, proteomics, as well as molecular cell biology. The very high success rates also reflect the fact that the subcellular localization of a protein is closely correlated with: (1). the biological objective to which the gene or gene product contributes, (2). the biochemical activity of a gene product, and (3). the place in the cell where a gene product is active.

Algorithms↗

Customizable neuroinformatics database system: XooNIps and its application to the pupil platform.

The developing field of neuroinformatics includes technologies for the collection and sharing of neuro-related digital resources. These resources will be of increasing value for understanding the brain. Developing a database system to integrate these disparate resources is necessary to make full use of these resources. This study proposes a base database system termed XooNIps that utilizes the content management system called XOOPS. XooNIps is designed for developing databases in different research fields through customization of the option menu. In a XooNIps-based database, digital resources are stored according to their respective categories, e.g., research articles, experimental data, mathematical models, stimulations, each associated with their related metadata. Several types of user authorization are supported for secure operations. In addition to the directory and keyword searches within a certain database, XooNIps searches simultaneously across other XooNIps-based databases on the Internet. Reviewing systems for user registration and for data submission are incorporated to impose quality control. Furthermore, XOOPS modules containing news, forums schedules, blogs and other information can be combined to enhance XooNIps functionality. These features provide better scalability, extensibility, and customizability to the general neuroinformatics community. The application of this system to data, models, and other information related to human pupils is described here.

Computational Biology↗

RPG: the Ribosomal Protein Gene database.

RPG (http://ribosome.miyazaki-med.ac.jp/) is a new database that provides detailed information about ribosomal protein (RP) genes. It contains data from humans and other organisms, including Drosophila melanogaster, Caenorhabditis elegans, Saccharo myces cerevisiae, Methanococcus jannaschii and Escherichia coli. Users can search the database by gene name and organism. Each record includes sequences (genomic, cDNA and amino acid sequences), intron/exon structures, genomic locations and information about orthologs. In addition, users can view and compare the gene structures of the above organisms and make multiple amino acid sequence alignments. RPG also provides information on small nucleolar RNAs (snoRNAs) that are encoded in the introns of RP genes.

Amino Acid Sequence↗

AluGene: a database of Alu elements incorporated within protein-coding genes.

Alu elements are short interspersed elements (SINEs) approximately 300 nucleotides in length. More than 1 million Alus are found in the human genome. Despite their being genetically functionless, recent findings suggest that Alu elements may have a broad evolutionary impact by affecting gene structures, protein sequences, splicing motifs and expression patterns. Because of these effects, compiling a genomic database of Alu sequences that reside within protein-coding genes seemed a useful enterprise. Presently, such data are limited since the structural and positional information on genes and Alu sequences are scattered throughout incompatible and unconnected databases. AluGene (http://Alugene.tau.ac.il/) provides easy access to a complete Alu map of the human genome, as well as Alu-associated information. The Alu elements are annotated with respect to coding region and exon/intron location. This design facilitates queries on Alu sequences, locations, as well as motifs and compositional properties via a one-stop search page.

Alu Elements↗

Dynamic integration of gene annotation and its application to microarray analysis.

Comprehensive and structured annotations for all genes on a microarray chip are essential for the interpretation of its expression data. Currently, most chip gene annotations are one-line free text descriptions that are often partial, outdated and unsuitable for large-scale data analysis. Therefore the interpretation of microarray gene expression clusters is often limited. Although researchers can manually navigate a collection of databases for better annotations, it is only practical for limited number of genes. Existing meta-databases fail to provide comprehensive categorized annotations for hundreds of genes simultaneously. We have developed an automatic system to address this issue. GeneView system monitors various data sources, extracts gene information from a source whenever it is updated, comprehensively matches genes, and integrates them into a central database by categories, such as pathway, genetic mapping, phenotype, expression profile, domain structure, protein interaction, disease association, and references. The system consists of four major components: (1) relational database; (2) data processing; (3) user curation; (4) data query. We evaluated it by analyzing genes on cDNA and Affymetrix Oligo chips. In both cases, the system provided more accurate and comprehensive information than those provided by the vendors or the chip users, and helped identify new common functions among genes in the same expression clusters.

Cluster Analysis↗

Finding GeneRIFs via gene ontology annotations.

A Gene Reference Into Function (GeneRIF) is a concise phrase describing a function of a gene in the Entrez Gene database. Applying techniques from the area of natural language processing known as automatic summarization, it is possible to link the Entrez Gene database, the Gene Ontology, and the biomedical literature. A system was implemented that automatically suggests a sentence from a PubMed/MEDLINE abstract as a candidate GeneRIF by exploiting a gene's GO annotations along with location features and cue words. Results suggest that the method can significantly increase the number of GeneRIF annotations in Entrez Gene, and that it produces qualitatively more useful GeneRIFs than other methods.

Algorithms↗

Parallel tandem: a program for parallel processing of tandem mass spectra using PVM or MPI and X!Tandem.

A method for the rapid correlation of tandem mass spectra to a list of protein sequences in a database has been developed. The combination of the fast and accurate computational search algorithm, X!Tandem, and a Linux cluster parallel computing environment with PVM or MPI, significantly reduces the time required to perform the correlation of tandem mass spectra to protein sequences in a database. A file of tandem mass spectra is divided into a specified number of files, each containing an equal number of the spectra from the larger file. These files are then searched in parallel against a protein sequence database. The results of each parallel output file are collated into one file for viewing through a web interface. Thousands of spectra can be searched in an accurate, practical, and time effective manner. The source code for running Parallel Tandem utilizing either PVM or MPI on Linux operating system is available from http://www.thegpm.org. This source code is made available under Artistic License from the authors.

Algorithms↗

Genew: the Human Gene Nomenclature Database, 2004 updates.

Genew, the Human Gene Nomenclature Database http://www.gene.ucl.ac.uk/cgi-bin/nomenclature/searchgenes.pl is the only resource that provides data for all human genes that have approved symbols. It is managed by the HUGO Gene Nomenclature Committee (HGNC) as a confidential database, containing over 22 000 records, 75% of which are represented online by a publicly searchable text file. Since 2002, there have been significant improvements to the Genew search engine. Additionally we have increased our capacity to analyse confidential sequence data, which has enabled us to manage the large numbers of gene symbol requests that we receive from the chromosome sequencing consortia.

Animals↗

BmiGI: a database of cDNAs expressed in Boophilus microplus, the tropical/southern cattle tick.

We used an expressed sequence tag approach to initiate a study of the genome of the southern cattle tick, Boophilus microplus. A normalized cDNA library was synthesized from pooled RNA purified from tick larvae which had been subjected to different treatments, including acaricide exposure, heat shock, cold shock, host odor, and infection with Babesia bovis. For the acaricide exposure experiments, we used several strains of ticks, which varied in their levels of susceptibility to pyrethroid, organophosphate and amitraz. We also included RNA purified from samples of eggs, nymphs and adult ticks and dissected tick organs. Plasmid DNA was prepared from 11,520 cDNA clones and both 5' and 3' sequencing performed on each clone. The sequence data was used to search public protein databases and a B. microplus gene index was constructed, consisting of 8270 unique sequences whose associated putative functional assignments, when available, can be viewed at the TIGR website (http://www.tigr.org/tdb/tgi). A number of novel sequences were identified which possessed significant sequence similarity to genes, which might be involved in resistance to acaricides.

Acetylcholinesterase↗

ACLAME: a CLAssification of Mobile genetic Elements.

The ACLAME database (http://aclame.ulb.ac.be) is a collection and classification of prokaryotic mobile genetic elements (MGEs) from various sources, comprising all known phage genomes, plasmids and transposons. In addition to providing information on the full genomes and genetic entities, it aims to build a comprehensive classification of the functional modules of MGEs at the protein, gene and higher levels. This first version contains a comprehensive classification of 5069 proteins from 119 DNA bacteriophages into over 400 functional families. This classification was produced automatically using TRIBE-MCL, a graph-theory-based Markov clustering algorithm that uses sequence measures as input, and then manually curated. Manual curation was aided by consulting annotations available in public databases retrieved through additional sequence similarity searches using Psi-Blast and Hidden Markov Models. The database is publicly accessible and open to expert volunteers willing to participate in its curation. Its web interface allows browsing as well as querying the classification. The main objectives are to collect and organize in a rational way the complexity inherent to MGEs, to extend and improve the inadequate annotation currently associated with MGEs and to screen known genomes for the validation and discovery of new MGEs.

Bacteriophages↗

E-MSD: improving data deposition and structure quality.

The Macromolecular Structure Database (MSD) (http://www.ebi.ac.uk/msd/) [H. Boutselakis, D. Dimitropoulos, J. Fillon, A. Golovin, K. Henrick, A. Hussain, J. Ionides, M. John, P. A. Keller, E. Krissinel et al. (2003) E-MSD: the European Bioinformatics Institute Macromolecular Structure Database. Nucleic Acids Res., 31, 458-462.] group is one of the three partners in the worldwide Protein DataBank (wwPDB), the consortium entrusted with the collation, maintenance and distribution of the global repository of macromolecular structure data [H. Berman, K. Henrick and H. Nakamura (2003) Announcing the worldwide Protein Data Bank. Nature Struct. Biol., 10, 980.]. Since its inception, the MSD group has worked with partners around the world to improve the quality of PDB data, through a clean up programme that addresses inconsistencies and inaccuracies in the legacy archive. The improvements in data quality in the legacy archive have been achieved largely through the creation of a unified data archive, in the form of a relational database that stores all of the data in the wwPDB. The three partners are working towards improving the tools and methods for the deposition of new data by the community at large. The implementation of the MSD database, together with the parallel development of improved tools and methodologies for data harvesting, validation and archival, has lead to significant improvements in the quality of data that enters the archive. Through this and related projects in the NMR and EM realms the MSD continues to improve the quality of publicly available structural data.

Computational Biology↗