Biomedical subjects

Minoru Kanehisa

Publications and source records attributed to Minoru Kanehisa.

At least 55 records · Page 3Linked to original sources

PubMed2004

Using protein motif combinations to update KEGG pathway maps and orthologue tables.

We have studied the projection of protein family data onto single bacterial translated genome as a solution to visualise relationships between families restricted to bacterial sequences. Any member of any type of family as defined in the Pfam database (domains, signatures, etc.) is considered as a protein module. Our first goal is to discover rules correlating the occurrence of modules with biochemical properties. To achieve this goal we have developed a platform to quantify information found in protein databases and to support the analysis of the nature of modules, their position and corresponding frequencies of occurrence (in isolation or in combination) in association with pathway knowledge as found in KEGG. This paper focuses on two pathways: the two-component system and the aminophosphonate metabolism, that are partially but not completely documented. Proteins involved in those pathways were listed separately in each organism to analyse module composition and rules constraining pathway interactions were identified. It is shown how these results can be used to update KEGG pathways and orthologue tables.

Animals↗

PubMed2004

Extraction of species-specific glycan substructures.

Glycans, which are carbohydrate sugar chains attached to some lipids or proteins, have a huge variety of structures and play a key role in cell communication, protein interaction and immunity. The availability of a number of glycan structures stored in the KEGG/GLYCAN database makes it possible for us to conduct a large-scale comparative research of glycans. In this paper, we present a novel approach to compare glycan structures and extract characteristic glycan substructures of certain organisms. In the algorithm we developed a new similarity measure of glycan structures taking into account of several biological aspects of glycan synthesis and glycosyltransferases, and we confirmed the validity of our similarity measure by conducting experiments on its ability to classify glycans between organisms in the framework of a support vector machine. Finally, our method successfully extracted a set of candidates of substructrues which are characteristic to human, rat, mouse, bovine, pig, chicken, yeast, wheat and sycamore, respectively. We confirmed that the characteristic substructures extracted by our method correspond to the substructures which are known as the species-specific sugar chain of gamma-glutamyltranspeptidases in the kidney.

Animals↗

PubMed2004

Clustering of database sequences for fast homology search using upper bounds on alignment score.

Homology data are among the most important information used to predict the functions of unknown proteins and thus fast and accurate methods are needed. In this paper, we propose a new approach for fast and accurate homology search using pre-computed all-against-all similarity scores in a target database. We previously developed a method for derivation of an upper bound of the Smith-Waterman score (SW-score) between a query and a homolog candidate sequence using the SW-score between the candidate and a sequence similar to the query. In this paper, by using this upper bound, we first cluster the sequences in the target database so that upper bounds of SW-scores for all the members in the clusters are less than a given value and select representative sequences for respective clusters. Then, the query sequence is searched against the representative sequences and the upper bounds of SW-scores for respective clusters are estimated. Only if the upper bound is higher than a given threshold, SW-alignments are computed for all the sequences in the cluster. We performed computational experiments to test efficiency of the proposed method for the KEGG/GENES database using the KEGG/SSDB. The results suggest that our method is efficient for redundant databases that include multiple closely related species.

Algorithms↗

PubMed2004

Extraction of phylogenetic network modules from prokayrote metabolic pathways.

In the post-genomic era, it is important to analyze interaction networks that include genes, proteins, enzymes and compounds such as a metabolic pathway. Every organism has such networks individually. However, several parts of them are conserved in different organisms. The purpose of this analysis is to extract sub-networks composed of these common elements through the phylogenetic analysis. We extracted network modules from metabolic pathways using phylogenetic profile and cluster analysis. The enzymes of these modules are related by evolutionary and functional correlation. Our results give a valuable insight into the evolution of metabolic pathways.

Bacteria↗

PubMed2003

Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways.

Cellular functions result from intricate networks of molecular interactions, which involve not only proteins and nucleic acids but also small chemical compounds. Here we present an efficient algorithm for comparing two chemical structures of compounds, where the chemical structure is treated as a graph consisting of atoms as nodes and covalent bonds as edges. On the basis of the concept of functional groups, 68 atom types (node types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection of biochemically meaningful features. Maximal common subgraphs of two graphs can be found by searching for maximal cliques in the association graph, and we have introduced heuristics to accelerate the clique finding and to detect optimal local matches (simply connected common subgraphs). Our procedure was applied to the comparison and clustering of 9383 compounds, mostly metabolic compounds, in the KEGG/LIGAND database. The largest clusters of similar compounds were related to carbohydrates, and the clusters corresponded well to the categorization of pathways as represented by the KEGG pathway map numbers. When each pathway map was examined in more detail, finer clusters could be identified corresponding to subpathways or pathway modules containing continuous sets of reaction steps. Furthermore, it was found that the pathway modules identified by similar compound structures sometimes overlap with the pathway modules identified by genomic contexts, namely, by operon structures of enzyme genes.

Algorithms↗

PubMed2003

Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs.

MOTIVATION: The subcellular location of a protein is closely correlated to its function. Thus, computational prediction of subcellular locations from the amino acid sequence information would help annotation and functional prediction of protein coding genes in complete genomes. We have developed a method based on support vector machines (SVMs). RESULTS: We considered 12 subcellular locations in eukaryotic cells: chloroplast, cytoplasm, cytoskeleton, endoplasmic reticulum, extracellular medium, Golgi apparatus, lysosome, mitochondrion, nucleus, peroxisome, plasma membrane, and vacuole. We constructed a data set of proteins with known locations from the SWISS-PROT database. A set of SVMs was trained to predict the subcellular location of a given protein based on its amino acid, amino acid pair, and gapped amino acid pair compositions. The predictors based on these different compositions were then combined using a voting scheme. Results obtained through 5-fold cross-validation tests showed an improvement in prediction accuracy over the algorithm based on the amino acid composition only. This prediction method is available via the Internet.

Algorithms↗

PubMed2003

Identification of a new cryptochrome class. Structure, function, and evolution.

Cryptochrome flavoproteins, which share sequence homology with light-dependent DNA repair photolyases, function as photoreceptors in plants and circadian clock components in animals. Here, we coupled sequencing of an Arabidopsis cryptochrome gene with phylogenetic, structural, and functional analyses to identify a new cryptochrome class (cryptochrome DASH) in bacteria and plants, suggesting that cryptochromes evolved before the divergence of eukaryotes and prokaryotes. The cryptochrome crystallographic structure, reported here for Synechocystis cryptochrome DASH, reveals commonalities with photolyases in DNA binding and redox-dependent function, despite distinct active-site and interaction surface features. Whole genome transcriptional profiling together with experimental confirmation of DNA binding indicated that Synechocystis cryptochrome DASH functions as a transcriptional repressor.

Amino Acid Sequence↗

PubMed2003

Bioinformatics in the post-sequence era.

In the past decade, bioinformatics has become an integral part of research and development in the biomedical sciences. Bioinformatics now has an essential role both in deciphering genomic, transcriptomic and proteomic data generated by high-throughput experimental technologies and in organizing information gathered from traditional biology. Sequence-based methods of analyzing individual genes or proteins have been elaborated and expanded, and methods have been developed for analyzing large numbers of genes or proteins simultaneously, such as in the identification of clusters of related genes and networks of interacting proteins. With the complete genome sequences for an increasing number of organisms at hand, bioinformatics is beginning to provide both conceptual bases and practical methods for detecting systemic functional behaviors of the cell and the organism.

Computational Biology↗

PubMed2003

Extracting active pathways from gene expression data.

MOTIVATION: A promising way to make sense out of gene expression profiles is to relate them to the activity of metabolic and signalling pathways. Each pathway usually involves many genes, such as enzymes, which can themselves participate in many pathways. The set of all known pathways can therefore be represented by a complex network of genes. Searching for regularities in the set of gene expression profiles with respect to the topology of this gene network is a way to automatically extract active pathways and their associated patterns of activity. METHOD: We present a method to perform this task, which consists in encoding both the gene network and the set of profiles into two kernel functions, and performing a regularized form of canonical correlation analysis between the two kernels. RESULTS: When applied to publicly available expression data the method is able to extract biologically relevant expression patterns, as well as pathways with related activity.

Algorithms↗

PubMed2003

DNA microarray analysis of redox-responsive genes in the genome of the cyanobacterium Synechocystis sp. strain PCC 6803.

Whole-genome DNA microarrays were used to evaluate the effect of the redox state of the photosynthetic electron transport chain on gene expression in Synechocystis sp. strain PCC 6803. Two specific inhibitors of electron transport, 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) and 2,5-dibromo-3-methyl-6-isopropyl-p-benzoquinone (DBMIB), were added to the cultures, and changes in accumulation of transcripts were examined. About 140 genes were highlighted as reproducibly affected by the change in the redox state of the photosynthetic electron transport chain. It was shown that some stress-responsive genes but not photosynthetic genes were under the control of the redox state of the plastoquinone pool in Synechocystis sp. strain PCC 6803.

Bacterial Proteins↗

PubMed2003

Efficient tree-matching methods for accurate carbohydrate database queries.

One aspect of glycome informatics is the analysis of carbohydrate sugar chains, or glycans, whose basic structure is not a sequence, but a tree structure. Although there has been much work in the development of sequence databases and matching algorithms for sequences (for performing queries and analyzing similarity), the more complicated tree structure of glycans does not allow a direct implementation of such a database for glycans, and further, does not allow for the direct application of sequence alignment algorithms for performing searches or analyzing similarity. Therefore, we have utilized a polynomial-time dynamic programming algorithm for solving the maximum common subtree of two trees to implement an accurate and efficient tool for finding and aligning maximally matching glycan trees. The KEGG Glycan database for glycan structures released recently incorporates our tree-structure alignment algorithm with various parameters to adapt to the needs of a variety of users. Because we use similarity scores as opposed to a distance metric, our methods are more readily used to display trees of higher similarity. We present the two methods developed for this purpose and illustrate its validity.

Algorithms↗

PubMed2003

Heuristics for chemical compound matching.

We have developed an efficient algorithm for comparing two chemical compounds, where the chemical structure is treated as a 2D graph consisting of atoms as vertices and covalent bonds as edges. Based on the concept of functional groups in chemistry, 68 atom types (vertex types) are defined for carbon, nitrogen, oxygen, and other atomic species with different environments, which has enabled detection of biochemically meaningful features. Maximal common subgraphs of two graphs can be found by searching for maximal cliques in the association graph, and we have introduced heuristics to accelerate the clique finding. Our heuristic procedure is controlled by some adjustable parameters. Here we applied our procedure to the latest KEGG/LIGAND database with different sets of parameters, and demonstrated the correlation of parameters in our algorithm with the distribution of similarity scores and/or the execution time. Finally, we showed the effectiveness of our heuristics for compound pairs along metabolic pathways.

Algorithms↗

PubMed2002

Update of MAGEST: Maboya Gene Expression patterns and Sequence Tags.

MAGEST is a database for maternal gene expression information for an ascidian, Halocynthia roretzi. The ascidian has become an animal model in developmental biological research because it shows a simple developmental process, and belongs to one of the chordate groups. Various data are deposited into the MAGEST database, e.g. the 3'- and 5'-tag sequences from the fertilized egg cDNA library, the results of similarity searches against GenBank and the expression data from whole mount in situ hybridization. Over the last 2 years, the data retrieval systems have been improved in several aspects, and the tag sequence entries have increased to over 20 000 clones. Additionally, we constructed a database, translated MAGEST, for the amino acid fragment sequences predicted from the EST data sets. Using this information comprehensively, we should obtain new information on gene functions. The MAGEST database is accessible via the Internet at http://www.genome.ad.jp/magest/.

Amino Acid Sequence↗

PubMed2002

LIGAND: database of chemical compounds and reactions in biological pathways.

LIGAND is a composite database comprising three sections: COMPOUND for the information about metabolites and other chemical compounds, REACTION for the collection of substrate-product relations representing metabolic and other reactions, and ENZYME for the information about enzyme molecules. The current release (as of September 7, 2001) includes 7298 compounds, 5166 reactions and 3829 enzymes. In addition to the keyword search provided by the DBGET/LinkDB system, a substructure search to the COMPOUND and REACTION sections is now available through the World Wide Web (http://www.genome.ad.jp/ligand/). LIGAND may be also downloaded by anonymous FTP (ftp://ftp.genome.ad.jp/pub/kegg/ligand/).

Animals↗

PubMed2002

The KEGG databases at GenomeNet.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).

Animals↗

PubMed2002

Screening for the target gene of cyanobacterial cAMP receptor protein SYCRP1.

The target genes for SYCRP1, a cyanobacterial cAMP receptor protein, were surveyed using a DNA microarray method. Total RNAs were extracted from a wild-type strain and a sycrp1 disruptant of Synechocystis sp. PCC 6803, and the respective gene expression levels were compared. The expression levels of six genes (slr1667, slr1168, slr2015, slr2016, slr2017 and slr2018) were clearly decreased by the disruption of the sycrp1 gene. The data suggest that slr1667 and slr1668 constitute one operon and the other four genes constitute another operon. Transcription start points for the first genes of these putative operons, which are slr1667 and slr2015, were determined by primer extension experiments. Gel mobility shift assays and DNase 1 footprint analyses were carried out to explore the binding of SYCRP1 to the putative promoter regions of slr1667 and slr2015. SYCRP1 bound to the specific site in the 5' upstream region of slr1667 from positions -170 to -155 relative to the transcription start point, while it did not bind to the 5' upstream region of slr2015. It was concluded that SYCRP1 regulates the expression of the slr1667 gene directly by binding to a specific site in its promoter.

Bacterial Proteins↗

PubMed2002

A two-component Mn2+-sensing system negatively regulates expression of the mntCAB operon in Synechocystis.

Mn is an essential component of the oxygen-evolving machinery of photosynthesis and is an essential cofactor of several important enzymes, such as Mn-superoxide dismutase and Mn-catalase. The availability of Mn in the environment varies, and little is known about the mechanisms for maintaining cytoplasmic Mn(2+) ion homeostasis. Using a DNA microarray, we screened knockout libraries of His kinases and response regulators of Synechocystis sp PCC 6803 to identify possible participants in this process. We identified a His kinase, ManS, which might sense the extracellular concentration of Mn(2+) ions, and a response regulator, ManR, which might regulate the expression of the mntCAB operon for the ABC-type transporter of Mn(2+) ions. Furthermore, analysis with the DNA microarray and by reverse transcription PCR suggested that ManS produces a signal that activates ManR, which represses the expression of the mntCAB operon. At low concentrations of Mn(2+) ions, ManS does not generate a signal, with resulting inactivation of ManR and subsequent expression of the mntCAB operon.

ATP-Binding Cassette Transporters↗

PubMed2002

The KEGG database.

KEGG (http://www.genome.ad.jp/kegg/) is a suite of databases and associated software for understanding and simulating higher-order functional behaviours of the cell or the organism from its genome information. First, KEGG computerizes data and knowledge on protein interaction networks (PATHWAY database) and chemical reactions (LIGAND database) that are responsible for various cellular processes. Second, KEGG attempts to reconstruct protein interaction networks for all organisms whose genomes are completely sequenced (GENES and SSDB databases). Third, KEGG can be utilized as reference knowledge for functional genomics (EXPRESSION database) and proteomics (BRITE database) experiments. I will review the current status of KEGG and report on new developments in graph representation and graph computations.

Amino Acid Sequence↗