Biomedical subjects

Minoru Kanehisa

Publications and source records attributed to Minoru Kanehisa.

At least 19 recordsLinked to original sources

PubMed2007

Complete nucleotide sequence of the freshwater unicellular cyanobacterium Synechococcus elongatus PCC 6301 chromosome: gene content and organization.

The entire genome of the unicellular cyanobacterium Synechococcus elongatus PCC 6301 (formerly Anacystis nidulans Berkeley strain 6301) was sequenced. The genome consisted of a circular chromosome 2,696,255 bp long. A total of 2,525 potential protein-coding genes, two sets of rRNA genes, 45 tRNA genes representing 42 tRNA species, and several genes for small stable RNAs were assigned to the chromosome by similarity searches and computer predictions. The translated products of 56% of the potential protein-coding genes showed sequence similarities to experimentally identified and predicted proteins of known function, and the products of 35% of the genes showed sequence similarities to the translated products of hypothetical genes. The remaining 9% of genes lacked significant similarities to genes for predicted proteins in the public DNA databases. Some 139 genes coding for photosynthesis-related components were identified. Thirty-seven genes for two-component signal transduction systems were also identified. This is the smallest number of such genes identified in cyanobacteria, except for marine cyanobacteria, suggesting that only simple signal transduction systems are found in this strain. The gene arrangement and nucleotide sequence of Synechococcus elongatus PCC 6301 were nearly identical to those of a closely related strain Synechococcus elongatus PCC 7942, except for the presence of a 188.6 kb inversion. The sequences as well as the gene information shown in this paper are available in the Web database, CYORF (http://www.cyano.genome.jp/).

Base Sequence↗

PubMed2006

MIMOX: a web tool for phage display based epitope mapping.

BACKGROUND: Phage display is widely used in basic research such as the exploration of protein-protein interaction sites and networks, and applied research such as the development of new drugs, vaccines, and diagnostics. It has also become a promising method for epitope mapping. Research on new algorithms that assist and automate phage display based epitope mapping has attracted many groups. Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them. RESULTS: We present MIMOX, a free web tool that helps to map the native epitope of an antibody based on one or more user supplied mimotopes and the antigen structure. MIMOX was coded in Perl using modules from the Bioperl project. It has two sections. In the first section, MIMOX provides a simple interface for ClustalW to align a set of mimotopes. It also provides a simple statistical method to derive the consensus sequence and embeds JalView as a Java applet to view and manage the alignment. In the second section, MIMOX can map a single mimotope or a consensus sequence of a set of mimotopes, on to the corresponding antigen structure and search for all of the clusters of residues that could represent the native epitope. NACCESS is used to evaluate the surface accessibility of the candidate clusters; and Jmol is embedded to view them interactively in their 3D context. Initial case studies show that MIMOX can reproduce mappings from existing tools such as FINDMAP and 3DEX, as well as providing novel, rational results. CONCLUSION: A web-based tool called MIMOX has been developed for phage display based epitope mapping. As a publicly available online service in this area, it is convenient for the community to access, utilize, and evaluate, complementing other existing programs. MIMOX is freely available at http://web.kuicr.kyoto-u.ac.jp/~hjian/mimox.

Bacteriophages↗

PubMed2006

Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions.

MOTIVATION: The computational prediction of protein-protein interactions is currently a major issue in bioinformatics. Recently, a variety of co-evolution-based methods have been investigated toward this goal. In this study, we introduced a partial correlation coefficient as a new measure for the degree of co-evolution between proteins, and proposed its use to predict protein-protein interactions. RESULTS: The accuracy of the prediction by the proposed method was compared with those of the original mirror tree method and the projection method previously developed by our group. We found that the partial correlation coefficient effectively reduces the number of false positives, as compared with other methods, although the number of false negatives increased in the prediction by the partial correlation coefficient. AVAILABILITY: The R script for the prediction of protein-protein interactions reported in this manuscript is available at http://timpani.genome.ad.jp/~parco/

Amino Acid Sequence↗

PubMed2006

Identification of metabolic units induced by environmental signals.

MOTIVATION: Biological cells continually need to adapt the activity levels of metabolic functions to changes in their living environment. Although genome-wide transcriptional data have been gathered in a large variety of environmental conditions, the connections between the expression response to external changes and the induction or repression of specific metabolic functions have not been investigated at the genome scale. RESULTS: We present here a correlation-based analysis for identifying the expression response of genes involved in metabolism to specific external signals, and apply it to analyze the transcriptional response of Saccharomyces cerevisiae to different stress conditions. We show that this approach leads to new insights about the specificity of the genomic response to given environmental changes, and allows us to identify genes that are particularly sensitive to a unique condition. We then integrate these signal-induced expression data with structural data of the yeast metabolic network and analyze the topological properties of the induced or repressed subnetworks. They reveal significant discrepancies from random networks, and in particular exhibit a high connectivity, allowing them to be mapped back to complete metabolic routes.

Adaptation, Physiological↗

PubMed2006

ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains.

MOTIVATION: Carbohydrate sugar chains, or glycans, are considered the third major class of biomolecules after DNA and proteins. They consist of branching monosaccharides, starting from a single monosaccharide. They are extremely vital to the development and functioning of multicellular organisms because they are recognized by various proteins to allow them to perform specific functions. Our motivation is to study this recognition mechanism using informatics techniques from the data available. Previously, we introduced a probabilistic sibling-dependent tree Markov model (PSTMM), which we showed could be efficiently trained on sibling-dependent tree structures and return the most likely state paths. However, it had some limitations in that the extra dependency between siblings caused overfitting problems. The retrieval of the patterns from the trained model also involved manually extracting the patterns from the most likely state paths. Thus we introduce a profilePSTMM model which avoids these problems, incorporating a novel concept of different types of state transitions to handle parent-child and sibling dependencies differently. RESULTS: Our new algorithms are more efficient and able to extract the patterns more easily. We tested the profilePSTMM model on both synthetic (controlled) data as well as glycan data from the KEGG GLYCAN database. Additionally, we tested it on glycans which are known to be recognized and bound to proteins at various binding affinities, and we show that our results correlate with results published in the literature.

Algorithms↗

PubMed2006

EGassembler: online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments.

Expressed sequence tag (EST) sequencing has proven to be an economically feasible alternative for gene discovery in species lacking a draft genome sequence. Ongoing large-scale EST sequencing projects feel the need for bioinformatics tools to facilitate uniform EST handling. This brings about a renewed importance for a universal tool for processing and functional annotation of large sets of ESTs. EGassembler (http://egassembler.hgc.jp/) is a web server, which provides an automated as well as a user-customized analysis tool for cleaning, repeat masking, vector trimming, organelle masking, clustering and assembling of ESTs and genomic fragments. The web server is publicly available and provides the community a unique all-in-one online application web service for large-scale ESTs and genomic DNA clustering and assembling. Running on a Sun Fire 15K supercomputer, a significantly large volume of data can be processed in a short period of time. The results can be used to functionally annotate genes, to facilitate splice alignment analysis, to link the transcripts to genetic and physical maps, design microarray chips, to perform transcriptome analysis and to map to KEGG metabolic pathways. The service provides an excellent bioinformatics tool to research groups in wet-lab as well as an all-in-one-tool for sequence handling to bioinformatics researchers.

Computational Biology↗

PubMed2006

Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis.

BACKGROUND: Elementary mode analysis of metabolic pathways has proven to be a valuable tool for assessing the properties and functions of biochemical systems. However, little comprehension of how individual elementary modes are used in real cellular states has been achieved so far. A quantitative measure of fluxes carried by individual elementary modes is of great help to identify dominant metabolic processes, and to understand how these processes are redistributed in biological cells in response to changes in environmental conditions, enzyme kinetics, or chemical concentrations. RESULTS: Selecting a valid decomposition of a flux distribution onto a set of elementary modes is not straightforward, since there is usually an infinite number of possible such decompositions. We first show that two recently introduced decompositions are very closely related and assign the same fluxes to reversible elementary modes. Then, we show how such decompositions can be used in combination with kinetic modelling to assess the effects of changes in enzyme kinetics on the usage of individual metabolic routes, and to analyse the range of attainable states in a metabolic system. This approach is illustrated by the example of yeast glycolysis. Our results indicate that only a small subset of the space of stoichiometrically feasible steady states is actually reached by the glycolysis system, even when large variation intervals are allowed for all kinetic parameters of the model. Among eight possible elementary modes, the standard glycolytic route remains dominant in all cases, and only one other elementary mode is able to gain significant flux values in steady state. CONCLUSION: These results indicate that a combination of structural and kinetic modelling significantly constrains the range of possible behaviours of a metabolic system. All elementary modes are not equal contributors to physiological cellular states, and this approach may open a direction toward a broader identification of physiologically relevant elementary modes among the very large number of stoichiometrically possible modes.

Algorithms↗

PubMed2006

Extraction of phylogenetic network modules from the metabolic network.

BACKGROUND: In bio-systems, genes, proteins and compounds are related to each other, thus forming complex networks. Although each organism has its individual network, some organisms contain common sub-networks based on function. Given a certain sub-network, the distribution of organisms common to it represents the diversity of its function. RESULTS: We extracted such "common" sub-networks, defined as "phylogenetic network modules," using phylogenetic profiles and cluster analysis. The enzymes in the same "phylogenetic network module" have similar phylogenetic profiles and related functions. These modules are shown to be phylogenetic building blocks. Furthermore, the network of the modules illustrated hierarchical feature as well as the network of enzymes involved in the metabolism. CONCLUSION: We conclude that phylogenetic network modules are evolutionary conserved functional units in the metabolic network. We claim that our concept of phylogenetic modules provides a more accurate understanding of the evolution of biological networks.

Animals↗

PubMed2006

ODB: a database of operons accumulating known operons across multiple genomes.

Operon structures play an important role in co-regulation in prokaryotes. Although over 200 complete genome sequences are now available, databases providing genome-wide operon information have been limited to certain specific genomes. Thus, we have developed an ODB (Operon DataBase), which provides a data retrieval system of known operons among the many complete genomes. Additionally, putative operons that are conserved in terms of known operons are also provided. The current version of our database contains about 2000 known operon information in more than 50 genomes and about 13 000 putative operons in more than 200 genomes. This system integrates four types of associations: genome context, gene co-expression obtained from microarray data, functional links in biological pathways and the conservation of gene order across the genomes. These associations are indicators of the genes that organize an operon, and the combination of these indicators allows us to predict more reliable operons. Furthermore, our system validates these predictions using known operon information obtained from the literature. This database integrates known literature-based information and genomic data. In addition, it provides an operon prediction tool, which make the system useful for both bioinformatics researchers and experimental biologists. Our database is accessible at http://odb.kuicr.kyoto-u.ac.jp/.

Databases, Nucleic Acid↗

PubMed2006

From genomics to chemical genomics: new developments in KEGG.

The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource (http://www.genome.jp/kegg/) provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES) and the chemical space (KEGG LIGAND), and wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY). A fourth component, KEGG BRITE, has been formally added to the KEGG suite of databases. This reflects our attempt to computerize functional interpretations as part of the pathway reconstruction process based on the hierarchically structured knowledge about the genomic, chemical and network spaces. In accordance with the new chemical genomics initiatives, the scope of KEGG LIGAND has been significantly expanded to cover both endogenous and exogenous molecules. Specifically, RPAIR contains curated chemical structure transformation patterns extracted from known enzymatic reactions, which would enable analysis of genome-environment interactions, such as the prediction of new reactions and new enzyme genes that would degrade new environmental compounds. Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps.

Biotransformation↗

PubMed2006

Extracting sequence motifs and the phylogenetic features of SNARE-dependent membrane traffic.

The SNARE proteins are required for membrane fusion during intracellular vesicular transport and for its specificity. Only the unique combination of SNARE proteins (cognates) can be bound and can lead to membrane fusion, although the characteristics of the possible specificity of the binding combinations encoded in the SNARE sequences have not yet been determined. We discovered by whole genome sequence analysis that sequence motifs (conserved sequences) in the SNARE motif domains for each protein group correspond to localization sites or transport pathways. We claim that these motifs reflect the specificity of the binding combinations of SNARE motif domains. Using these motifs, we could classify SNARE proteins from 48 organisms into their localization sites or transport pathways. The classification result shows that more than 10 SNARE subgroups are kingdom specific and that the SNARE paralogs involved in the plasma membrane-related transport pathways have developed greater variations in higher animals and higher plants than those involved in the endoplasmic reticulum-related transport pathways throughout eukaryotic evolution.

Amino Acid Motifs↗

PubMed2005

Extraction of leukemia specific glycan motifs in humans by computational glycomics.

There have been almost no standard methods for conducting computational analyses on glycan structures in comparison to DNA and proteins. In this paper, we present a novel method for extracting functional motifs from glycan structures using the KEGG/GLYCAN database. First, we developed a new similarity measure for comparing glycan structures taking into account the characteristic mechanisms of glycan biosynthesis, and we tested its ability to classify glycans of different blood components in the framework of support vector machines (SVMs). The results show that our method can successfully classify glycans from four types of human blood components: leukemic cells, erythrocyte, serum, and plasma. Next, we extracted characteristic functional motifs of glycans considered to be specific to each blood component. We predicted the substructure alpha-D-Neup5Ac-(2-->3)-beta-D-Galp-(1-->4)-D-GlcpNAc as a leukemia specific glycan motif. Based on the fact that the Agrocybe cylindracea galectin (ACG) specifically binds to the same substructure, we conducted an experiment using cell agglutination assay and confirmed that this fungal lectin specifically recognized human leukemic cells.

Biomarkers, Tumor↗

PubMed2005

MRP1 mutated in the L0 region transports SN-38 but not leukotriene C4 or estradiol-17 (beta-D-glucuronate).

Multidrug resistance protein 1 (MRP1) is an ATP-binding cassette transporter that confers multidrug resistance on tumor cells. Much convincing evidence has accumulated that MRP1 transports most substances in a GSH-dependent manner. On the other hand, several reports have revealed that MRP1 can transport some substrates independently of GSH; however, the importance of GSH-independent transport activity is not well established and the mechanistic differences between GSH-dependent and -independent transport by MRP1 are unclear. We previously demonstrated that the amino acids W261 and K267 in the L0 region of MRP1 were important for leukotriene C4 (LTC4) transport activity of MRP1 and for GSH-dependent photolabeling of MRP1 with azidophenyl agosterol-A (azidoAG-A). In this paper, we further tested the effect of W222L, W223L and R230A mutations in MRP1, designated dmL0MRP1, on MRP1 transport activity. SN-38 is an active metabolic form of CPT-11 that is one of the most promising anti-cancer drugs. Membrane vesicles prepared from cells expressing dmL0MRP1 could transport SN-38, but not LTC4 or estradiol-17 (beta-D-glucuronate), and could not be photolabeled with azidoAG-A. These data suggested that SN-38 was transported by a different mechanism than that of GSH-dependent transport. Understanding the GSH-independent transport mechanism of MRP1, and identification of drugs that are transported by this mechanism, will be critical for combating MRP1-mediated drug resistance. We performed a pairwise comparison of compounds that are transported by MRP1 in a GSH-dependent or -independent manner. These data indicated that it may be possible to predict compounds that are transported by MRP1 in a GSH-independent manner.

Base Sequence↗

PubMed2005

Prediction of glycan structures from gene expression data based on glycosyltransferase reactions.

MOTIVATION: Glycan chains are synthesized by a combination of several kinds of glycosyltransferases (GTs). Thus, once we know the repertoire of GTs in the genome, in the transcriptome or in the proteome, it should in principle be possible to predict the repertoire of possible glycan structures in an organism or at a specific stage of the cell. Here, we show that a repertoire of glycan structures can be predicted from the set of GTs in the transcriptome. That is, using knowledge about glycan structure characteristics, we can predict glycan structures from incomplete or noisy data such as DNA microarray data. RESULTS: First, we constructed a reaction pattern library consisting of bond-formation patterns of GT reactions and investigated the co-occurrence frequencies of all reaction patterns in the glycan database. This was followed by the prediction of glycan structures using this library and a co-occurrence score. A penalty score was also implemented in the prediction method. Then we examined the performance of prediction by the leave-one-out cross validation method using individual reaction pattern profiles in the KEGG GLYCAN database as virtual expression profiles. The accuracy of prediction was 81%. Finally, we applied the prediction method to real expression data. Using expression profiles from the human carcinoma cell, glycan structures with sialic acid and sialyl Lewis X epitope were predicted, which corresponded well with experimental results.

Algorithms↗

PubMed2005

A quadratic programming approach for decomposing steady-state metabolic flux distributions onto elementary modes.

MOTIVATION: It is known that steady-state flux distributions in metabolic networks can be expressed as non-negative combinations of elementary modes. However, little understanding has been achieved so far in how individual elementary modes contribute to the reconstruction of actual physiological flux distributions. RESULTS: We introduce an approach for decomposing steady-state flux distributions onto elementary modes based on quadratic programming. The decomposition is performed so as to favour modes that are closest to the actual state of the system, i.e. most relevant for biological interpretation. As an illustration, an application of this approach to a model of yeast glycolysis is presented. AVAILABILITY: Software is available upon request from the authors.

Algorithms↗

PubMed2005

Alteration of gene expression in human hepatocellular carcinoma with integrated hepatitis B virus DNA.

PURPOSE: Integration of hepatitis B virus (HBV) DNA into the human genome is one of the most important steps in HBV-related carcinogenesis. This study attempted to find the link between HBV DNA, the adjoining cellular sequence, and altered gene expression in hepatocellular carcinoma (HCC) with integrated HBV DNA. EXPERIMENTAL DESIGN: We examined 15 cases of HCC infected with HBV by cassette ligation-mediated PCR. The human DNA adjacent to the integrated HBV DNA was sequenced. Protein coding sequences were searched for in the human sequence. In five cases with HBV DNA integration, from which good quality RNA was extracted, gene expression was examined by cDNA microarray analysis. RESULTS: The human DNA sequence successive to integrated HBV DNA was determined in the 15 HCCs. Eight protein-coding regions were involved: ras-responsive element binding protein 1, calmodulin 1, mixed lineage leukemia 2 (MLL2), FLJ333655, LOC220272, LOC255345, LOC220220, and LOC168991. The MLL2 gene was expressed in three cases with HBV DNA integrated into exon 3 of MLL2 and in one case with HBV DNA integrated into intron 3 of MLL2. Gene expression analysis suggested that two HCCs with HBV integrated into MLL2 had similar patterns of gene expression compared with three HCCs with HBV integrated into other loci of human chromosomes. CONCLUSIONS: HBV DNA was integrated at random sites of human DNA, and the MLL2 gene was one of the targets for integration. Our results suggest that HBV DNA might modulate human genes near integration sites, followed by integration site-specific expression of such genes during hepatocarcinogenesis.

Adult↗

PubMed2005

KEGG as a glycome informatics resource.

Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field.

Carbohydrates↗

PubMed2005

The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships.

MOTIVATION: The prediction of protein-protein interactions is currently an important issue in bioinformatics. The mirror tree method uses evolutionary information to predict protein-protein interactions. However, it has been recognized that predictions by the mirror tree method lead to many false positives. The incentive of our study was to solve this problem by improving the method of extracting the co-evolutionary information regarding the protein pairs. RESULTS: We developed a novel method to predict protein-protein interactions from co-evolutionary information in the framework of the mirror tree method. The originality is the use of the projection operator to exclude the information about the phylogenetic relationships among the source organisms from the distance matrix. Each distance matrix was transformed into a vector for the operation. The vector is referred to as a 'phylogenetic vector'. We have proposed three ways to extract the phylogenetic information: (1) using the 16S rRNA from the same source organisms as the proteins under consideration, (2) averaging the phylogenetic vectors and (3) analyzing the principal components of the phylogenetic vectors. We examined the performance of the proposed methods to predict interacting protein pairs from Escherichia coli, using experimentally verified data. Our method was successful, and it drastically reduced the number of false positives in the prediction. AVAILABILITY: The R script for the prediction of protein-protein interactions reported in this manuscript is available at http://timpani.genome.ad.jp/~proj/ CONTACT: sato@kuicr.kyoto-u.ac.jp SUPPLEMENTARY INFORMATION: The information is also available at the same site as the R script.

Algorithms↗