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PubMed2004

Serial analysis of gene expression (SAGE): unraveling the bioinformatics tools.

Serial analysis of gene expression (SAGE) is a powerful technique that can be used for global analysis of gene expression. Its chief advantage over other methods is that it does not require prior knowledge of the genes of interest and provides qualitative and quantitative data of potentially every transcribed sequence in a particular cell or tissue type. This is a technique of expression profiling, which permits simultaneous, comparative and quantitative analysis of gene-specific, 9- to 13-basepair sequences. These short sequences, called SAGE tags, are linked together for efficient sequencing. The sequencing data are then analyzed to identify each gene expressed in the cell and the levels at which each gene is expressed. The main benefit of SAGE includes the digital output and the identification of novel genes. In this review, we present an outline of the method, various bioinformatics methods for data analysis and general applications of this important technology.

Animals↗

PubMedDate not supplied

Transcriptomic analysis of the NCI-60 cancer cell lines.

Pharmacogenomics aims at molecular subsetting of patients for more effective therapy. Transcriptomic profiling of the 60 human cancer cell lines (the NCI-60) used by the US National Cancer Institute serves that aim because the cells have been treated with > 100,000 chemical compounds over the last 13 years. Patterns of potency can be mapped into molecular structures of the compounds or into molecular characteristics of the cells. We discuss conceptual and experimental aspects of the profiling, as well as a number of bioinformatic computer programs that we have developed for biological interpretation of the profiles.

Cell Line, Tumor↗

PubMed2004

Bioinformatics: harvesting information for plant and crop science.

Bioinformatics is an integral aspect of plant and crop science research. Developments in data management and analytical software are reviewed with an emphasis on applications in functional genomics. This includes information resources for Arabidopsis and crop species, and tools available for analysis and visualisation of comparative genomic data. Approaches used to explore relationships between plant genes and expressed sequences are compared, including use of ontologies. The impact of bioinformatics in forward and reverse genetics is described, together with the potential from data mining. The role of bioinformatics is explored in the wider context of plant and crop science.

Algorithms↗

PubMed2003

Dehydron: a structurally encoded signal for protein interaction.

We introduce a quantifiable structural motif, called dehydron, that is shown to be central to protein-protein interactions. A dehydron is a defectively packed backbone hydrogen bond suggesting preformed monomeric structure whose Coulomb energy is highly sensitive to binding-induced water exclusion. Such preformed hydrogen bonds are effectively adhesive, since water removal from their vicinity contributes to their stability. At the structural level, a significant correlation is established between dehydrons and sites for protein complexation, with the HIV-1 capsid protein P24 complexed with antibody light-chain FAB25.3 providing the most dramatic correlation. Furthermore, the number of dehydrons in homologous similar-fold proteins from different species is shown to be a signature of proteomic complexity. The techniques are then applied to higher levels of organization: The formation of the capsid and its organization in picornaviruses correlates strongly with the distribution of dehydrons on the rim of the virus unit. Furthermore, antibody contacts and crystal contacts may be assigned to dehydrons still prevalent after the capsid has been assembled. The implications of the dehydron as an encoded signal in proteomics, bioinformatics, and inhibitor drug design are emphasized.

Amino Acid Motifs↗

PubMed2004

Conserved RNA secondary structures in viral genomes: a survey.

SUMMARY: The genomes of RNA viruses often carry conserved RNA structures that perform vital functions during the life cycle of the virus. Such structures can be detected using a combination of structure prediction and co-variation analysis. Here we present results from pilot studies on a variety of viral families performed during bioinformatics computer lab courses in past years.

Algorithms↗

PubMed2004

Clinical quality needs complex adaptive systems and machine learning.

The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

Artificial Intelligence↗

PubMed2006

PROPHECY--a yeast phenome database, update 2006.

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics--the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale--connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at http://prophecy.lundberg.gu.se. Via phenotyping of 984 heterozygous diploids for all essential genes the genotypes analysed and presented in PROPHECY have been extended and now include all genes in the yeast genome. Further, phenotypic data from gene overexpression of 574 membrane spanning proteins has recently been included. To facilitate the interpretation of quantitative phenotypic data we have developed a new phenotype display option, the Comparative Growth Curve Display, where growth curve differences for a large number of mutants compared with the wild type are easily revealed. In addition, PROPHECY now offers a more informative and intuitive first-sight display of its phenotypic data via its new summary page. We have also extended the arsenal of data analysis tools to include dynamic visualization of phenotypes along individual chromosomes. PROPHECY is an initiative to enhance the growing field of phenome bioinformatics.

Chromosomes, Fungal↗

PubMed2004

Computational discovery of DNA motifs associated with cell type-specific gene expression in Ciona.

Temporally and spatially co-expressed genes are expected to be regulated by common transcription factors and therefore to share cis-regulatory elements. In the ascidian Ciona intestinalis, the whole-genome sequences and genome-scale gene expression profiles allow the use of computational techniques to investigate cis-elements that control transcription. We collected 5' flanking sequences of 50 tissue-specific genes from genome databases of C. intestinalis and a closely related species Ciona savignyi. We searched for DNA motifs over-represented in upstream regions of a group of co-expressed genes. Several motifs were distributed predominantly in upstream regions of photoreceptor, pan-neuronal, or muscle-specific gene groups. One muscle-specific motif, M2, was distributed preferentially in regions from -200 to -100 bp relative to the translational start sites. Promoters of muscle-specific genes of C. intestinalis were isolated, connected with a green fluorescent protein gene (GFP), and introduced into C. intestinalis embryos. In muscle cells, these promoters specifically drove GFP expression, which mutations of the M2 sites greatly reduced. When M2 sites were located upstream of a basal promoter, the reporter GFP was specifically expressed in muscle cells. These results suggest the validity of our computational prediction of cis-regulatory elements. Thus, bioinformatics can help identify cis-regulatory elements involved in chordate development.

Animals↗

PubMed1998

Mass spectrometric identification and microcharacterization of proteins from electrophoretic gels: strategies and applications.

The entire genomic DNA sequences of a number of prokaryotic and eukaryotic species are now available and many more, including the human genome, will be completed in the near future. The state-of-life of a cell at any given time, however, is defined by its protein composition, i.e., its proteome. Gel electrophoresis, mass spectrometry, and bioinformatics will be important tools for protein and proteome analysis in the post-genome era. Protein identification from electrophoretic gels by mass spectrometric peptide mapping or peptide sequencing combined with sequence database searching is established and has been applied to numerous biological systems. We describe current strategies and selected applications in molecular and cell biology. The next challenges are detailed structure/function analyses, which include studying the molecular composition of multiprotein complexes and characterization of secondary modifications of proteins. The advantages and limitations of a number of mass spectrometry-based strategies designed for microcharacterization of low amounts of protein from electrophoretic gels are discussed and illustrated by examples.

Amino Acid Sequence↗

PubMed2000

Two-dimensional electrophoresis of liver proteins: characterization of a drug-induced hepatomegaly in rats.

Two-dimensional electrophoresis (2-DE) of liver proteins was applied to further characterize an unusual drug-induced increase in hepatocellular rough endoplasmic reticulum (RER) in Sprague-Dawley rats given a substituted pyrimidine derivative. Absolute liver weights of drug-treated rats (9.9 +/- 0.4 g) increased above vehicle-treated controls (7.2 +/- 0.2 g) by 37%. Light microscopy revealed diffuse granular basophilia of the hepatocellular cytoplasm, uncharacteristic of hepatocytes and suggested cells rich in ribosomes, which was confirmed by electron microscopy. Immunostaining for cell proliferation, viz., 5-bromo-2'-deoxyuridine (BrdU) and proliferating cell nuclear antigen (PCNA), indicated marked hepatocellular proliferative activity. 2-DE of solubilized liver using an ISO-DALT gel system indicated significant (p<0.001) quantitative changes in at least 17 liver proteins (12 increased, 5 decreased) compared to controls. The protein with the largest increase was homologous to acute-phase reactant, contrapsin-like protein inhibitor-6. Other markedly upregulated proteins were methionine adenosyltransferase, a catalyst in methionine/ATP metabolism and mitochondrial HMG-CoA synthase, involved in cholesterol synthesis. The complementary strategies of 2-DE coupled either with database spot mapping or protein isolation and amino acid sequencing successfully identified a subset of proteins from xenobiotic-damaged rodent livers, the expression of which differed from controls. However, the current bioinformatics platform for rodent hepatic proteins and limited knowledge of specific protein functionality restricted application of this proteomics profile to further define a mechanistic basis for this unusual hepatotoxicity.

Animals↗

PubMed2006

Characterization of ribosomal proteins as biomarkers for matrix-assisted laser desorption/ionization mass spectral identification of Lactobacillus plantarum.

For rapid identification of bacteria by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), a bioinformatics approach using ribosomal subunit proteins as biomarkers has been proposed. This method compares the observed masses for biomarkers with calculated masses as predicted from the amino acid sequences registered on protein databases. To evaluate this approach, the expressed ribosomal proteins of a genome-sequenced bacterium, Lactobacillus plantarum NCIMB 8826, were characterized as a model sample. The protein expression of 42 ribosomal subunit proteins, together with 10 ribosome-associated proteins in the isolated ribosome fraction, was confirmed through two-dimensional gel electrophoresis combined with peptide mass fingerprinting. The observed masses of the proteins in the isolated ribosome fraction were then determined by MALDI-MS. We preliminarily selected 44 biomarkers whose observed masses were matched with the calculated masses predicted from the amino acid sequence registered in the protein databases by considering N-terminal methionine loss only. Of these, the finally selected reliable biomarkers were 34 proteins including 31 ribosomal subunit proteins and 3 ribosome-associated proteins that could be observed in the MALDI mass spectra of the cell lysate sample. These biomarkers were usable in MALDI-MS characterization of two industrial L. plantarum cultures.

Bacterial Proteins↗

PubMed2007

Direct identification of proteins from T47D cells and murine brain tissue by matrix-assisted laser desorption/ionization post-source decay/collision-induced dissociation.

The purpose of this study is to determine the feasibility of the direct matrix-assisted laser desorption/ionization (MALDI) identification of proteins in fixed T47D breast cancer cells and murine brain tissues. The ability to identify proteins from cells and tissue may lead to biomarkers that effectively predict the onset of defined disease states, and their dynamic behavior could be an important hint for drug target discoveries. Direct tissue application of trypsin allows protein identification in cells and tissues, while maintaining spatial integrity and intracellular organization. Using a chemical printer, matrix was co-registered on trypsinized human T47D breast cancer cells and cryo-preserved sections of murine brain tissue, followed by MALDI post-source decay (PSD) or MALDI collision-induced dissociation (CID), respectively. Mass-to-charge (m/z) data from the cells and brain tissues were processed using Mascot software interrogation of the National Center for Biotechnology Information (NCBI) database. Histone H2B was identified from cultured T47D human breast cancer cells. Tubulin beta2 was identified from mouse brain cortex following an induced stroke. These results suggest that MALDI PSD/CID, combined with bioinformatics, can be used for the direct identification of proteins from cells and tissues. Refinements in preparation techniques may improve this approach to provide a tool for quantitative proteomics and clinical analysis.

Animals↗

PubMed2003

Proteomics of bacterial pathogens.

The rapid growth of proteomics that has been built upon the available bacterial genome sequences has opened provided new approaches to the analysis of bacterial functional genomics. In the study of pathogenic bacteria the combined technologies of genomics, proteomics and bioinformatics has provided valuable tools for the study of complex phenomena determined by the action of multiple gene sets. The review considers some of the recent developments in the establishment of proteomic databases as well as attempts to define pathogenic determinants at the level of the proteome for some of the major human pathogens. Proteomics can also provide practical applications through the identification of immunogenic proteins that may be potential vaccine targets as well as in extending our understanding of antibiotic action. There is little doubt that proteomics has provided us with new and valuable information on bacterial pathogens and will continue to be an important source of information in the coming years.

Animals↗

PubMed2005

A bioinformatics framework for genotype-phenotype correlation in humans with Marfan syndrome caused by FBN1 gene mutations.

Mutations in the human FBN1 gene are known to be associated with the Marfan syndrome, an autosomal dominant inherited multi-systemic connective tissue disorder. However, in the absence of solid genotype-phenotype correlations, the identification of an FBN1 mutation has only little prognostic value. We propose a bioinformatics framework for the mutated FBN1 gene which comprises the collection, management, and analysis of mutation data identified by molecular genetic analysis (DHPLC) and data of the clinical phenotype. To query our database at different levels of information, a relational data model, describing mutational events at the cDNA and protein levels, and the disease's phenotypic expression from two alternative views, was implemented. For database similarity requests, a query model which uses a distance measure based on log-likelihood weights for each clinical manifestation, was introduced. A data mining strategy for discovering diagnostic markers, classification and clustering of phenotypic expressions was provided which enabled us to confirm some known and to identify some new genotype-phenotype correlations.

Computational Biology↗

PubMed1998

The complete genome of Bacillus subtilis: from sequence annotation to data management and analysis.

The completion of the entire 4.2-Mb genome sequence of the gram-positive bacterium Bacillus subtilis has been a milestone for biological studies on this model organism. This paper describes bioinformatics work related to this joint European and Japanese project: methods and strategies for gene annotation and detection of sequencing errors, using an integrated cooperative computer environment (Imagene); construction of a specialized database for data management and a WWW server for data retrieval (SubtiList); DNA sequence analysis, yielding striking results on oligonucleotide bias, repeated sequences, and codon usage, all landmarks of evolutionary events shaping the B. subtilis genome.

Amino Acid Sequence↗

PubMed2001

Bioinformatics in proteomics.

Several genome sequencing projects have recently been completed and the majority of human coding regions have been sequenced. In the next step many of the further studies will concentrate on proteins. Proteomics methods are essential for studying protein expression, activity, regulation and modifications. Bioinformatics is an integral part of proteomics research. The recent developments and applications in proteomics are discussed including mass spectrometry data analysis and interpretation, analysis and storage of the gel images to databases, gel comparison, and advanced methods to study e.g. protein co-expression, protein-protein interactions, as well as metabolic and cellular pathways. The significance of informatics in proteomics will gradually increase because of the advent of high-throughput methods relying on powerful data analysis.

Computational Biology↗

PubMed1998

Design and implementation of a CORBA-based genome mapping system prototype.

MOTIVATION: CORBA (Common Object Request Broker Architecture), as an open standard, is considered to be a good solution for the development and deployment of applications in distributed heterogeneous environments. This technology can be applied in the bioinformatics area to enhance utilization, management and interoperation between biological resources. RESULTS: This paper investigates issues in developing CORBA applications for genome mapping information systems in the Internet environment with emphasis on database connectivity and graphical user interfaces. The design and implementation of a CORBA prototype for an animal genome mapping database are described. AVAILABILITY: The prototype demonstration is available via: http://www.ri.bbsrc.ac.uk/ark_corba/. CONTACT: jian.hu@bbsrc.ac.uk

Chromosome Mapping↗

PubMed2006

A versatile method for deciphering plant membrane proteomes.

Proteomics is a very powerful approach to link the information contained in sequenced genomes, like that of Arabidopsis, to the functional knowledge provided by studies of plant cell compartments. This article summarizes the different steps of a versatile strategy that has been developed to decipher plant membrane proteomes. Initiated with envelope membranes from spinach chloroplasts, this strategy has been adapted to thylakoids, and further extended to a series of membranes from the model plant Arabidopsis: chloroplast envelope membranes, plasma membrane, and mitochondrial membranes. The first step is the preparation of highly purified membrane fractions from plant tissues. The second step in the strategy is the fractionation of membrane proteins on the basis of their physico-chemical properties. Chloroform/methanol extraction and washing of membranes with NaOH, NaCl or any other agent led to the simplification of the protein content of the fraction to be analysed. The next step is the genuine proteomic step, i.e. the separation of proteins by 1D-gel electrophoresis followed by in-gel proteolytic digestion of the polypeptides, analysis of the proteolytic peptides using mass spectrometry, and protein identification by searching through databases. The last step is the validation of the procedure by checking the subcellular location. The results obtained by using this strategy demonstrate that a combination of different proteomics approaches, together with bioinformatics, indeed provide a better understanding of the biochemical machinery of the different plant membranes at the molecular level.

Alkalies↗