PathwayAccess: CellDesigner plugins for pathway databases.
Van Hemert, John L; Dickerson, Julie A
2010-09-15
CellDesigner provides a user-friendly interface for graphical biochemical pathway description. Many pathway databases are not directly exportable to CellDesigner models. PathwayAccess is an extensible suite of CellDesigner plugins, which connect CellDesigner directly to pathway databases using respective Java application programming interfaces. The process is streamlined for creating new PathwayAccess plugins for specific pathway databases. Three PathwayAccess plugins, MetNetAccess, BioCycAccess and ReactomeAccess, directly connect CellDesigner to the pathway databases MetNetDB, BioCyc and Reactome. PathwayAccess plugins enable CellDesigner users to expose pathway data to analytical CellDesigner functions, curate their pathway databases and visually integrate pathway data from different databases using standard Systems Biology Markup Language and Systems Biology Graphical Notation. Implemented in Java, PathwayAccess plugins run with CellDesigner version 4.0.1 and were tested on Ubuntu Linux, Windows XP and 7, and MacOSX. Source code, binaries, documentation and video walkthroughs are freely available at http://vrac.iastate.edu/~jlv.
BioWarehouse: a bioinformatics database warehouse toolkit
Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David WJ; Tenenbaum, Jessica D; Karp, Peter D
2006-01-01
Background This article addresses the problem of interoperation of heterogeneous bioinformatics databases. Results We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. Conclusion BioWarehouse embodies significant progress on the database integration problem for bioinformatics. PMID:16556315
BioWarehouse: a bioinformatics database warehouse toolkit.
Lee, Thomas J; Pouliot, Yannick; Wagner, Valerie; Gupta, Priyanka; Stringer-Calvert, David W J; Tenenbaum, Jessica D; Karp, Peter D
2006-03-23
This article addresses the problem of interoperation of heterogeneous bioinformatics databases. We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. BioWarehouse embodies significant progress on the database integration problem for bioinformatics.
Hadadi, Noushin; Hafner, Jasmin; Shajkofci, Adrian; Zisaki, Aikaterini; Hatzimanikatis, Vassily
2016-10-21
Because the complexity of metabolism cannot be intuitively understood or analyzed, computational methods are indispensable for studying biochemistry and deepening our understanding of cellular metabolism to promote new discoveries. We used the computational framework BNICE.ch along with cheminformatic tools to assemble the whole theoretical reactome from the known metabolome through expansion of the known biochemistry presented in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. We constructed the ATLAS of Biochemistry, a database of all theoretical biochemical reactions based on known biochemical principles and compounds. ATLAS includes more than 130 000 hypothetical enzymatic reactions that connect two or more KEGG metabolites through novel enzymatic reactions that have never been reported to occur in living organisms. Moreover, ATLAS reactions integrate 42% of KEGG metabolites that are not currently present in any KEGG reaction into one or more novel enzymatic reactions. The generated repository of information is organized in a Web-based database ( http://lcsb-databases.epfl.ch/atlas/ ) that allows the user to search for all possible routes from any substrate compound to any product. The resulting pathways involve known and novel enzymatic steps that may indicate unidentified enzymatic activities and provide potential targets for protein engineering. Our approach of introducing novel biochemistry into pathway design and associated databases will be important for synthetic biology and metabolic engineering.
Nag, Ambarish; Karpinets, Tatiana V; Chang, Christopher H; Bar-Peled, Maor
2012-01-01
Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES.
Nag, Ambarish; Karpinets, Tatiana V.; Chang, Christopher H.; Bar-Peled, Maor
2012-01-01
Understanding how cellular metabolism works and is regulated requires that the underlying biochemical pathways be adequately represented and integrated with large metabolomic data sets to establish a robust network model. Genetically engineering energy crops to be less recalcitrant to saccharification requires detailed knowledge of plant polysaccharide structures and a thorough understanding of the metabolic pathways involved in forming and regulating cell-wall synthesis. Nucleotide-sugars are building blocks for synthesis of cell wall polysaccharides. The biosynthesis of nucleotide-sugars is catalyzed by a multitude of enzymes that reside in different subcellular organelles, and precise representation of these pathways requires accurate capture of this biological compartmentalization. The lack of simple localization cues in genomic sequence data and annotations however leads to missing compartmentalization information for eukaryotes in automatically generated databases, such as the Pathway-Genome Databases (PGDBs) of the SRI Pathway Tools software that drives much biochemical knowledge representation on the internet. In this report, we provide an informal mechanism using the existing Pathway Tools framework to integrate protein and metabolite sub-cellular localization data with the existing representation of the nucleotide-sugar metabolic pathways in a prototype PGDB for Populus trichocarpa. The enhanced pathway representations have been successfully used to map SNP abundance data to individual nucleotide-sugar biosynthetic genes in the PGDB. The manually curated pathway representations are more conducive to the construction of a computational platform that will allow the simulation of natural and engineered nucleotide-sugar precursor fluxes into specific recalcitrant polysaccharide(s). Database URL: The curated Populus PGDB is available in the BESC public portal at http://cricket.ornl.gov/cgi-bin/beocyc_home.cgi and the nucleotide-sugar biosynthetic pathways can be directly accessed at http://cricket.ornl.gov:1555/PTR/new-image?object=SUGAR-NUCLEOTIDES. PMID:22465851
Classification of Chemical Compounds to Support Complex Queries in a Pathway Database
Weidemann, Andreas; Kania, Renate; Peiss, Christian; Rojas, Isabel
2004-01-01
Data quality in biological databases has become a topic of great discussion. To provide high quality data and to deal with the vast amount of biochemical data, annotators and curators need to be supported by software that carries out part of their work in an (semi-) automatic manner. The detection of errors and inconsistencies is a part that requires the knowledge of domain experts, thus in most cases it is done manually, making it very expensive and time-consuming. This paper presents two tools to partially support the curation of data on biochemical pathways. The tool enables the automatic classification of chemical compounds based on their respective SMILES strings. Such classification allows the querying and visualization of biochemical reactions at different levels of abstraction, according to the level of detail at which the reaction participants are described. Chemical compounds can be classified in a flexible manner based on different criteria. The support of the process of data curation is provided by facilitating the detection of compounds that are identified as different but that are actually the same. This is also used to identify similar reactions and, in turn, pathways. PMID:18629066
Accurate atom-mapping computation for biochemical reactions.
Latendresse, Mario; Malerich, Jeremiah P; Travers, Mike; Karp, Peter D
2012-11-26
The complete atom mapping of a chemical reaction is a bijection of the reactant atoms to the product atoms that specifies the terminus of each reactant atom. Atom mapping of biochemical reactions is useful for many applications of systems biology, in particular for metabolic engineering where synthesizing new biochemical pathways has to take into account for the number of carbon atoms from a source compound that are conserved in the synthesis of a target compound. Rapid, accurate computation of the atom mapping(s) of a biochemical reaction remains elusive despite significant work on this topic. In particular, past researchers did not validate the accuracy of mapping algorithms. We introduce a new method for computing atom mappings called the minimum weighted edit-distance (MWED) metric. The metric is based on bond propensity to react and computes biochemically valid atom mappings for a large percentage of biochemical reactions. MWED models can be formulated efficiently as Mixed-Integer Linear Programs (MILPs). We have demonstrated this approach on 7501 reactions of the MetaCyc database for which 87% of the models could be solved in less than 10 s. For 2.1% of the reactions, we found multiple optimal atom mappings. We show that the error rate is 0.9% (22 reactions) by comparing these atom mappings to 2446 atom mappings of the manually curated Kyoto Encyclopedia of Genes and Genomes (KEGG) RPAIR database. To our knowledge, our computational atom-mapping approach is the most accurate and among the fastest published to date. The atom-mapping data will be available in the MetaCyc database later in 2012; the atom-mapping software will be available within the Pathway Tools software later in 2012.
PathFinder: reconstruction and dynamic visualization of metabolic pathways.
Goesmann, Alexander; Haubrock, Martin; Meyer, Folker; Kalinowski, Jörn; Giegerich, Robert
2002-01-01
Beyond methods for a gene-wise annotation and analysis of sequenced genomes new automated methods for functional analysis on a higher level are needed. The identification of realized metabolic pathways provides valuable information on gene expression and regulation. Detection of incomplete pathways helps to improve a constantly evolving genome annotation or discover alternative biochemical pathways. To utilize automated genome analysis on the level of metabolic pathways new methods for the dynamic representation and visualization of pathways are needed. PathFinder is a tool for the dynamic visualization of metabolic pathways based on annotation data. Pathways are represented as directed acyclic graphs, graph layout algorithms accomplish the dynamic drawing and visualization of the metabolic maps. A more detailed analysis of the input data on the level of biochemical pathways helps to identify genes and detect improper parts of annotations. As an Relational Database Management System (RDBMS) based internet application PathFinder reads a list of EC-numbers or a given annotation in EMBL- or Genbank-format and dynamically generates pathway graphs.
Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A
2018-01-01
Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this strategy will significantly advance the curation status of all organism-specific databases in SolCyc resulting in the improvement on database accuracy, data analysis and visualization of biochemical networks in those species. Database URL https://solgenomics.net/tools/solcyc/ PMID:29762652
Pathway collages: personalized multi-pathway diagrams.
Paley, Suzanne; O'Maille, Paul E; Weaver, Daniel; Karp, Peter D
2016-12-13
Metabolic pathway diagrams are a classical way of visualizing a linked cascade of biochemical reactions. However, to understand some biochemical situations, viewing a single pathway is insufficient, whereas viewing the entire metabolic network results in information overload. How do we enable scientists to rapidly construct personalized multi-pathway diagrams that depict a desired collection of interacting pathways that emphasize particular pathway interactions? We define software for constructing personalized multi-pathway diagrams called pathway-collages using a combination of manual and automatic layouts. The user specifies a set of pathways of interest for the collage from a Pathway/Genome Database. Layouts for the individual pathways are generated by the Pathway Tools software, and are sent to a Javascript Pathway Collage application implemented using Cytoscape.js. That application allows the user to re-position pathways; define connections between pathways; change visual style parameters; and paint metabolomics, gene expression, and reaction flux data onto the collage to obtain a desired multi-pathway diagram. We demonstrate the use of pathway collages in two application areas: a metabolomics study of pathogen drug response, and an Escherichia coli metabolic model. Pathway collages enable facile construction of personalized multi-pathway diagrams.
Multi-membership gene regulation in pathway based microarray analysis
2011-01-01
Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531
Multi-membership gene regulation in pathway based microarray analysis.
Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M
2011-09-22
Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.
Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.
2018-01-01
The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400
Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A
2018-02-22
The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.
Corcoran, Callan C.; Grady, Cameron R.; Pisitkun, Trairak; Parulekar, Jaya
2017-01-01
The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database (https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database (Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. PMID:27974320
MetaMapR: pathway independent metabolomic network analysis incorporating unknowns.
Grapov, Dmitry; Wanichthanarak, Kwanjeera; Fiehn, Oliver
2015-08-15
Metabolic network mapping is a widely used approach for integration of metabolomic experimental results with biological domain knowledge. However, current approaches can be limited by biochemical domain or pathway knowledge which results in sparse disconnected graphs for real world metabolomic experiments. MetaMapR integrates enzymatic transformations with metabolite structural similarity, mass spectral similarity and empirical associations to generate richly connected metabolic networks. This open source, web-based or desktop software, written in the R programming language, leverages KEGG and PubChem databases to derive associations between metabolites even in cases where biochemical domain or molecular annotations are unknown. Network calculation is enhanced through an interface to the Chemical Translation System, which allows metabolite identifier translation between >200 common biochemical databases. Analysis results are presented as interactive visualizations or can be exported as high-quality graphics and numerical tables which can be imported into common network analysis and visualization tools. Freely available at http://dgrapov.github.io/MetaMapR/. Requires R and a modern web browser. Installation instructions, tutorials and application examples are available at http://dgrapov.github.io/MetaMapR/. ofiehn@ucdavis.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Kaluarachchi, Manuja R; Boulangé, Claire L; Garcia-Perez, Isabel; Lindon, John C; Minet, Emmanuel F
2016-10-01
Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events. A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC-MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed. Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.
miRPathDB: a new dictionary on microRNAs and target pathways.
Backes, Christina; Kehl, Tim; Stöckel, Daniel; Fehlmann, Tobias; Schneider, Lara; Meese, Eckart; Lenhof, Hans-Peter; Keller, Andreas
2017-01-04
In the last decade, miRNAs and their regulatory mechanisms have been intensively studied and many tools for the analysis of miRNAs and their targets have been developed. We previously presented a dictionary on single miRNAs and their putative target pathways. Since then, the number of miRNAs has tripled and the knowledge on miRNAs and targets has grown substantially. This, along with changes in pathway resources such as KEGG, leads to an improved understanding of miRNAs, their target genes and related pathways. Here, we introduce the miRNA Pathway Dictionary Database (miRPathDB), freely accessible at https://mpd.bioinf.uni-sb.de/ With the database we aim to complement available target pathway web-servers by providing researchers easy access to the information which pathways are regulated by a miRNA, which miRNAs target a pathway and how specific these regulations are. The database contains a large number of miRNAs (2595 human miRNAs), different miRNA target sets (14 773 experimentally validated target genes as well as 19 281 predicted targets genes) and a broad selection of functional biochemical categories (KEGG-, WikiPathways-, BioCarta-, SMPDB-, PID-, Reactome pathways, functional categories from gene ontology (GO), protein families from Pfam and chromosomal locations totaling 12 875 categories). In addition to Homo sapiens, also Mus musculus data are stored and can be compared to human target pathways. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Corcoran, Callan C; Grady, Cameron R; Pisitkun, Trairak; Parulekar, Jaya; Knepper, Mark A
2017-03-01
The organization of the mammalian genome into gene subsets corresponding to specific functional classes has provided key tools for systems biology research. Here, we have created a web-accessible resource called the Mammalian Metabolic Enzyme Database ( https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/MetabolicEnzymeDatabase.html) keyed to the biochemical reactions represented on iconic metabolic pathway wall charts created in the previous century. Overall, we have mapped 1,647 genes to these pathways, representing ~7 percent of the protein-coding genome. To illustrate the use of the database, we apply it to the area of kidney physiology. In so doing, we have created an additional database ( Database of Metabolic Enzymes in Kidney Tubule Segments: https://hpcwebapps.cit.nih.gov/ESBL/Database/MetabolicEnzymes/), mapping mRNA abundance measurements (mined from RNA-Seq studies) for all metabolic enzymes to each of 14 renal tubule segments. We carry out bioinformatics analysis of the enzyme expression pattern among renal tubule segments and mine various data sources to identify vasopressin-regulated metabolic enzymes in the renal collecting duct. Copyright © 2017 the American Physiological Society.
Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka
2018-05-08
Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on docking calculations with biochemical pathways and enables users to easily and quickly assess PPI feasibilities by archiving PPI predictions. MEGADOCK-Web also promotes the discovery of new PPIs and protein functions and is freely available for use at http://www.bi.cs.titech.ac.jp/megadock-web/ .
Using Bioinformatic Approaches to Identify Pathways Targeted by Human Leukemogens
Thomas, Reuben; Phuong, Jimmy; McHale, Cliona M.; Zhang, Luoping
2012-01-01
We have applied bioinformatic approaches to identify pathways common to chemical leukemogens and to determine whether leukemogens could be distinguished from non-leukemogenic carcinogens. From all known and probable carcinogens classified by IARC and NTP, we identified 35 carcinogens that were associated with leukemia risk in human studies and 16 non-leukemogenic carcinogens. Using data on gene/protein targets available in the Comparative Toxicogenomics Database (CTD) for 29 of the leukemogens and 11 of the non-leukemogenic carcinogens, we analyzed for enrichment of all 250 human biochemical pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The top pathways targeted by the leukemogens included metabolism of xenobiotics by cytochrome P450, glutathione metabolism, neurotrophin signaling pathway, apoptosis, MAPK signaling, Toll-like receptor signaling and various cancer pathways. The 29 leukemogens formed 18 distinct clusters comprising 1 to 3 chemicals that did not correlate with known mechanism of action or with structural similarity as determined by 2D Tanimoto coefficients in the PubChem database. Unsupervised clustering and one-class support vector machines, based on the pathway data, were unable to distinguish the 29 leukemogens from 11 non-leukemogenic known and probable IARC carcinogens. However, using two-class random forests to estimate leukemogen and non-leukemogen patterns, we estimated a 76% chance of distinguishing a random leukemogen/non-leukemogen pair from each other. PMID:22851955
Explorations into Chemical Reactions and Biochemical Pathways.
Gasteiger, Johann
2016-12-01
A brief overview of the work in the research group of the present author on extracting knowledge from chemical reaction data is presented. Methods have been developed to calculate physicochemical effects at the reaction site. It is shown that these physicochemical effects can quite favourably be used to derive equations for the calculation of data on gas phase reactions and on reactions in solution such as aqueous acidity of alcohols or carboxylic acids or the hydrolysis of amides. Furthermore, it is shown that these physicochemical effects are quite effective for assigning reactions into reaction classes that correspond to chemical knowledge. Biochemical reactions constitute a particularly interesting and challenging task for increasing our understanding of living species. The BioPath.Database is a rich source of information on biochemical reactions and has been used for a variety of applications of chemical, biological, or medicinal interests. Thus, it was shown that biochemical reactions can be assigned by the physicochemical effects into classes that correspond to the classification of enzymes by the EC numbers. Furthermore, 3D models of reaction intermediates can be used for searching for novel enzyme inhibitors. It was shown in a combined application of chemoinformatics and bioinformatics that essential pathways of diseases can be uncovered. Furthermore, a study showed that bacterial flavor-forming pathways can be discovered. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
2012-01-01
Background Exposure to environmental tobacco smoke (ETS) leads to higher rates of pulmonary diseases and infections in children. To study the biochemical changes that may precede lung diseases, metabolomic effects on fetal and maternal lungs and plasma from rats exposed to ETS were compared to filtered air control animals. Genome- reconstructed metabolic pathways may be used to map and interpret dysregulation in metabolic networks. However, mass spectrometry-based non-targeted metabolomics datasets often comprise many metabolites for which links to enzymatic reactions have not yet been reported. Hence, network visualizations that rely on current biochemical databases are incomplete and also fail to visualize novel, structurally unidentified metabolites. Results We present a novel approach to integrate biochemical pathway and chemical relationships to map all detected metabolites in network graphs (MetaMapp) using KEGG reactant pair database, Tanimoto chemical and NIST mass spectral similarity scores. In fetal and maternal lungs, and in maternal blood plasma from pregnant rats exposed to environmental tobacco smoke (ETS), 459 unique metabolites comprising 179 structurally identified compounds were detected by gas chromatography time of flight mass spectrometry (GC-TOF MS) and BinBase data processing. MetaMapp graphs in Cytoscape showed much clearer metabolic modularity and complete content visualization compared to conventional biochemical mapping approaches. Cytoscape visualization of differential statistics results using these graphs showed that overall, fetal lung metabolism was more impaired than lungs and blood metabolism in dams. Fetuses from ETS-exposed dams expressed lower lipid and nucleotide levels and higher amounts of energy metabolism intermediates than control animals, indicating lower biosynthetic rates of metabolites for cell division, structural proteins and lipids that are critical for in lung development. Conclusions MetaMapp graphs efficiently visualizes mass spectrometry based metabolomics datasets as network graphs in Cytoscape, and highlights metabolic alterations that can be associated with higher rate of pulmonary diseases and infections in children prenatally exposed to ETS. The MetaMapp scripts can be accessed at http://metamapp.fiehnlab.ucdavis.edu. PMID:22591066
Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.
2011-01-01
Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212
Recent Progress in the Development of Metabolome Databases for Plant Systems Biology
Fukushima, Atsushi; Kusano, Miyako
2013-01-01
Metabolomics has grown greatly as a functional genomics tool, and has become an invaluable diagnostic tool for biochemical phenotyping of biological systems. Over the past decades, a number of databases involving information related to mass spectra, compound names and structures, statistical/mathematical models and metabolic pathways, and metabolite profile data have been developed. Such databases complement each other and support efficient growth in this area, although the data resources remain scattered across the World Wide Web. Here, we review available metabolome databases and summarize the present status of development of related tools, particularly focusing on the plant metabolome. Data sharing discussed here will pave way for the robust interpretation of metabolomic data and advances in plant systems biology. PMID:23577015
Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming
2017-04-07
Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.
BiKEGG: a COBRA toolbox extension for bridging the BiGG and KEGG databases.
Jamialahmadi, Oveis; Motamedian, Ehsan; Hashemi-Najafabadi, Sameereh
2016-10-18
Development of an interface tool between the Biochemical, Genetic and Genomic (BiGG) and KEGG databases is necessary for simultaneous access to the features of both databases. For this purpose, we present the BiKEGG toolbox, an open source COBRA toolbox extension providing a set of functions to infer the reaction correspondences between the KEGG reaction identifiers and those in the BiGG knowledgebase using a combination of manual verification and computational methods. Inferred reaction correspondences using this approach are supported by evidence from the literature, which provides a higher number of reconciled reactions between these two databases compared to the MetaNetX and MetRxn databases. This set of equivalent reactions is then used to automatically superimpose the predicted fluxes using COBRA methods on classical KEGG pathway maps or to create a customized metabolic map based on the KEGG global metabolic pathway, and to find the corresponding reactions in BiGG based on the genome annotation of an organism in the KEGG database. Customized metabolic maps can be created for a set of pathways of interest, for the whole KEGG global map or exclusively for all pathways for which there exists at least one flux carrying reaction. This flexibility in visualization enables BiKEGG to indicate reaction directionality as well as to visualize the reaction fluxes for different static or dynamic conditions in an animated manner. BiKEGG allows the user to export (1) the output visualized metabolic maps to various standard image formats or save them as a video or animated GIF file, and (2) the equivalent reactions for an organism as an Excel spreadsheet.
DESHARKY: automatic design of metabolic pathways for optimal cell growth.
Rodrigo, Guillermo; Carrera, Javier; Prather, Kristala Jones; Jaramillo, Alfonso
2008-11-01
The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context. We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size. Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html
Fahrmann, Johannes F.; Grapov, Dmitry; Wanichthanarak, Kwanjeera; DeFelice, Brian C.; Salemi, Michelle R.; Rom, William N.; Gandara, David R.; Phinney, Brett S.; Fiehn, Oliver; Pass, Harvey
2017-01-01
Abstract Lung cancer is the leading cause of cancer mortality in the United States with non-small cell lung cancer adenocarcinoma being the most common histological type. Early perturbations in cellular metabolism are a hallmark of cancer, but the extent of these changes in early stage lung adenocarcinoma remains largely unknown. In the current study, an integrated metabolomics and proteomics approach was utilized to characterize the biochemical and molecular alterations between malignant and matched control tissue from 27 subjects diagnosed with early stage lung adenocarcinoma. Differential analysis identified 71 metabolites and 1102 proteins that delineated tumor from control tissue. Integrated results indicated four major metabolic changes in early stage adenocarcinoma (1): increased glycosylation and glutaminolysis (2); elevated Nrf2 activation (3); increase in nicotinic and nicotinamide salvaging pathways and (4) elevated polyamine biosynthesis linked to differential regulation of the s-adenosylmethionine/nicotinamide methyl-donor pathway. Genomic data from publicly available databases were included to strengthen proteomic findings. Our findings provide insight into the biochemical and molecular biological reprogramming that may accompany early stage lung tumorigenesis and highlight potential therapeutic targets. PMID:28049629
Kinetic Modeling using BioPAX ontology
Ruebenacker, Oliver; Moraru, Ion. I.; Schaff, James C.; Blinov, Michael L.
2010-01-01
Thousands of biochemical interactions are available for download from curated databases such as Reactome, Pathway Interaction Database and other sources in the Biological Pathways Exchange (BioPAX) format. However, the BioPAX ontology does not encode the necessary information for kinetic modeling and simulation. The current standard for kinetic modeling is the System Biology Markup Language (SBML), but only a small number of models are available in SBML format in public repositories. Additionally, reusing and merging SBML models presents a significant challenge, because often each element has a value only in the context of the given model, and information encoding biological meaning is absent. We describe a software system that enables a variety of operations facilitating the use of BioPAX data to create kinetic models that can be visualized, edited, and simulated using the Virtual Cell (VCell), including improved conversion to SBML (for use with other simulation tools that support this format). PMID:20862270
The underlying pathway structure of biochemical reaction networks
Schilling, Christophe H.; Palsson, Bernhard O.
1998-01-01
Bioinformatics is yielding extensive, and in some cases complete, genetic and biochemical information about individual cell types and cellular processes, providing the composition of living cells and the molecular structure of its components. These components together perform integrated cellular functions that now need to be analyzed. In particular, the functional definition of biochemical pathways and their role in the context of the whole cell is lacking. In this study, we show how the mass balance constraints that govern the function of biochemical reaction networks lead to the translation of this problem into the realm of linear algebra. The functional capabilities of biochemical reaction networks, and thus the choices that cells can make, are reflected in the null space of their stoichiometric matrix. The null space is spanned by a finite number of basis vectors. We present an algorithm for the synthesis of a set of basis vectors for spanning the null space of the stoichiometric matrix, in which these basis vectors represent the underlying biochemical pathways that are fundamental to the corresponding biochemical reaction network. In other words, all possible flux distributions achievable by a defined set of biochemical reactions are represented by a linear combination of these basis pathways. These basis pathways thus represent the underlying pathway structure of the defined biochemical reaction network. This development is significant from a fundamental and conceptual standpoint because it yields a holistic definition of biochemical pathways in contrast to definitions that have arisen from the historical development of our knowledge about biochemical processes. Additionally, this new conceptual framework will be important in defining, characterizing, and studying biochemical pathways from the rapidly growing information on cellular function. PMID:9539712
Sig2BioPAX: Java tool for converting flat files to BioPAX Level 3 format.
Webb, Ryan L; Ma'ayan, Avi
2011-03-21
The World Wide Web plays a critical role in enabling molecular, cell, systems and computational biologists to exchange, search, visualize, integrate, and analyze experimental data. Such efforts can be further enhanced through the development of semantic web concepts. The semantic web idea is to enable machines to understand data through the development of protocol free data exchange formats such as Resource Description Framework (RDF) and the Web Ontology Language (OWL). These standards provide formal descriptors of objects, object properties and their relationships within a specific knowledge domain. However, the overhead of converting datasets typically stored in data tables such as Excel, text or PDF into RDF or OWL formats is not trivial for non-specialists and as such produces a barrier to seamless data exchange between researchers, databases and analysis tools. This problem is particularly of importance in the field of network systems biology where biochemical interactions between genes and their protein products are abstracted to networks. For the purpose of converting biochemical interactions into the BioPAX format, which is the leading standard developed by the computational systems biology community, we developed an open-source command line tool that takes as input tabular data describing different types of molecular biochemical interactions. The tool converts such interactions into the BioPAX level 3 OWL format. We used the tool to convert several existing and new mammalian networks of protein interactions, signalling pathways, and transcriptional regulatory networks into BioPAX. Some of these networks were deposited into PathwayCommons, a repository for consolidating and organizing biochemical networks. The software tool Sig2BioPAX is a resource that enables experimental and computational systems biologists to contribute their identified networks and pathways of molecular interactions for integration and reuse with the rest of the research community.
Meta-All: a system for managing metabolic pathway information.
Weise, Stephan; Grosse, Ivo; Klukas, Christian; Koschützki, Dirk; Scholz, Uwe; Schreiber, Falk; Junker, Björn H
2006-10-23
Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at http://bic-gh.de/meta-all and can be downloaded free of charge and installed locally.
Meta-All: a system for managing metabolic pathway information
Weise, Stephan; Grosse, Ivo; Klukas, Christian; Koschützki, Dirk; Scholz, Uwe; Schreiber, Falk; Junker, Björn H
2006-01-01
Background Many attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed. Results We have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed. Conclusion META-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at and can be downloaded free of charge and installed locally. PMID:17059592
Santos, André S; Ramos, Rommel T; Silva, Artur; Hirata, Raphael; Mattos-Guaraldi, Ana L; Meyer, Roberto; Azevedo, Vasco; Felicori, Liza; Pacheco, Luis G C
2018-05-11
Biochemical tests are traditionally used for bacterial identification at the species level in clinical microbiology laboratories. While biochemical profiles are generally efficient for the identification of the most important corynebacterial pathogen Corynebacterium diphtheriae, their ability to differentiate between biovars of this bacterium is still controversial. Besides, the unambiguous identification of emerging human pathogenic species of the genus Corynebacterium may be hampered by highly variable biochemical profiles commonly reported for these species, including Corynebacterium striatum, Corynebacterium amycolatum, Corynebacterium minutissimum, and Corynebacterium xerosis. In order to identify the genomic basis contributing for the biochemical variabilities observed in phenotypic identification methods of these bacteria, we combined a comprehensive literature review with a bioinformatics approach based on reconstruction of six specific biochemical reactions/pathways in 33 recently released whole genome sequences. We used data retrieved from curated databases (MetaCyc, PathoSystems Resource Integration Center (PATRIC), The SEED, TransportDB, UniProtKB) associated with homology searches by BLAST and profile Hidden Markov Models (HMMs) to detect enzymes participating in the various pathways and performed ab initio protein structure modeling and molecular docking to confirm specific results. We found a differential distribution among the various strains of genes that code for some important enzymes, such as beta-phosphoglucomutase and fructokinase, and also for individual components of carbohydrate transport systems, including the fructose-specific phosphoenolpyruvate-dependent sugar phosphotransferase (PTS) and the ribose-specific ATP-binging cassette (ABC) transporter. Horizontal gene transfer plays a role in the biochemical variability of the isolates, as some genes needed for sucrose fermentation were seen to be present in genomic islands. Noteworthy, using profile HMMs, we identified an enzyme with putative alpha-1,6-glycosidase activity only in some specific strains of C. diphtheriae and this may aid to understanding of the differential abilities to utilize glycogen and starch between the biovars.
A Web Tool for Generating High Quality Machine-readable Biological Pathways.
Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Grant, Jason; Wu, Anthony; Wishart, David S
2017-02-08
PathWhiz is a web server built to facilitate the creation of colorful, interactive, visually pleasing pathway diagrams that are rich in biological information. The pathways generated by this online application are machine-readable and fully compatible with essentially all web-browsers and computer operating systems. It uses a specially developed, web-enabled pathway drawing interface that permits the selection and placement of different combinations of pre-drawn biological or biochemical entities to depict reactions, interactions, transport processes and binding events. This palette of entities consists of chemical compounds, proteins, nucleic acids, cellular membranes, subcellular structures, tissues, and organs. All of the visual elements in it can be interactively adjusted and customized. Furthermore, because this tool is a web server, all pathways and pathway elements are publicly accessible. This kind of pathway "crowd sourcing" means that PathWhiz already contains a large and rapidly growing collection of previously drawn pathways and pathway elements. Here we describe a protocol for the quick and easy creation of new pathways and the alteration of existing pathways. To further facilitate pathway editing and creation, the tool contains replication and propagation functions. The replication function allows existing pathways to be used as templates to create or edit new pathways. The propagation function allows one to take an existing pathway and automatically propagate it across different species. Pathways created with this tool can be "re-styled" into different formats (KEGG-like or text-book like), colored with different backgrounds, exported to BioPAX, SBGN-ML, SBML, or PWML data exchange formats, and downloaded as PNG or SVG images. The pathways can easily be incorporated into online databases, integrated into presentations, posters or publications, or used exclusively for online visualization and exploration. This protocol has been successfully applied to generate over 2,000 pathway diagrams, which are now found in many online databases including HMDB, DrugBank, SMPDB, and ECMDB.
Griffith, Rachel M; Li, Hu; Zhang, Nan; Favazza, Tara L; Fulton, Anne B; Hansen, Ronald M; Akula, James D
2013-08-01
The purpose of this study was to identify the genes, biochemical signaling pathways, and biological themes involved in the pathogenesis of retinopathy of prematurity (ROP). Next-generation sequencing (NGS) was performed on the RNA transcriptome of rats with the Penn et al. (Pediatr Res 36:724-731, 1994) oxygen-induced retinopathy model of ROP at the height of vascular abnormality, postnatal day (P) 19, and normalized to age-matched, room-air-reared littermate controls. Eight custom-developed pathways with potential relevance to known ROP sequelae were evaluated for significant regulation in ROP: The three major Wnt signaling pathways, canonical, planar cell polarity (PCP), and Wnt/Ca(2+); two signaling pathways mediated by the Rho GTPases RhoA and Cdc42, which are, respectively, thought to intersect with canonical and non-canonical Wnt signaling; nitric oxide signaling pathways mediated by two nitric oxide synthase (NOS) enzymes, neuronal (nNOS) and endothelial (eNOS); and the retinoic acid (RA) signaling pathway. Regulation of other biological pathways and themes was detected by gene ontology using the Kyoto Encyclopedia of Genes and Genomes and the NIH's Database for Annotation, Visualization, and Integrated Discovery's GO terms databases. Canonical Wnt signaling was found to be regulated, but the non-canonical PCP and Wnt/Ca(2+) pathways were not. Nitric oxide signaling, as measured by the activation of nNOS and eNOS, was also regulated, as was RA signaling. Biological themes related to protein translation (ribosomes), neural signaling, inflammation and immunity, cell cycle, and cell death were (among others) highly regulated in ROP rats. These several genes and pathways identified by NGS might provide novel targets for intervention in ROP.
Griffith, Rachel M.; Li, Hu; Zhang, Nan; Favazza, Tara L.; Fulton, Anne B.; Hansen, Ronald M.; Akula, James D.
2013-01-01
Purpose To identify the genes, biochemical signaling pathways and biological themes involved in the pathogenesis of retinopathy of prematurity (ROP). Methods Next-generation sequencing (NGS) was performed on the RNA transcriptome of rats with the Penn et al. (1994) oxygen-induced retinopathy (OIR) model of ROP at the height of vascular abnormality, postnatal day (P) 19, and normalized to age-matched, room-air-reared littermate controls. Eight custom developed pathways with potential relevance to known ROP sequelae were evaluated for significant regulation in ROP: The three major Wnt signaling pathways, canonical, planar cell polarity (PCP), and Wnt/Ca2+, two signaling pathways mediated by the Rho GTPases RhoA and Cdc42, which are respectively thought to intersect with canonical and noncanonical Wnt signaling, nitric oxide signaling pathways mediated by two nitrox oxide synthase (NOS) enzymes, neuronal (nNOS) and endothelial (eNOS), and the retinoic acid (RA) signaling pathway. Regulation of other biological pathways and themes were detected by gene ontology using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the NIH's Database for Annotation, Visualization and Integrated Discovery (DAVID)'s GO terms databases. Results Canonical Wnt signaling was found to be regulated, but the non-canonical PCP and Wnt/Ca2+ pathways were not. Nitric oxide (NO) signaling, as measured by the activation of nNOS eNOS, was also regulated, as was RA signaling. Biological themes related to protein translation (ribosomes), neural signaling, inflammation and immunity, cell cycle and cell death, were (among others) highly regulated in ROP rats. Conclusions These several genes and pathways identified by NGS might provide novel targets for intervention in ROP. PMID:23775346
DNA assembler, an in vivo genetic method for rapid construction of biochemical pathways
Shao, Zengyi; Zhao, Hua; Zhao, Huimin
2009-01-01
The assembly of large recombinant DNA encoding a whole biochemical pathway or genome represents a significant challenge. Here, we report a new method, DNA assembler, which allows the assembly of an entire biochemical pathway in a single step via in vivo homologous recombination in Saccharomyces cerevisiae. We show that DNA assembler can rapidly assemble a functional d-xylose utilization pathway (∼9 kb DNA consisting of three genes), a functional zeaxanthin biosynthesis pathway (∼11 kb DNA consisting of five genes) and a functional combined d-xylose utilization and zeaxanthin biosynthesis pathway (∼19 kb consisting of eight genes) with high efficiencies (70–100%) either on a plasmid or on a yeast chromosome. As this new method only requires simple DNA preparation and one-step yeast transformation, it represents a powerful tool in the construction of biochemical pathways for synthetic biology, metabolic engineering and functional genomics studies. PMID:19074487
Simulation studies in biochemical signaling and enzyme reactions
NASA Astrophysics Data System (ADS)
Nelatury, Sudarshan R.; Vagula, Mary C.
2014-06-01
Biochemical pathways characterize various biochemical reaction schemes that involve a set of species and the manner in which they are connected. Determination of schematics that represent these pathways is an important task in understanding metabolism and signal transduction. Examples of these Pathways are: DNA and protein synthesis, and production of several macro-molecules essential for cell survival. A sustained feedback mechanism arises in gene expression and production of mRNA that lead to protein synthesis if the protein so synthesized serves as a transcription factor and becomes a repressor of the gene expression. The cellular regulations are carried out through biochemical networks consisting of reactions and regulatory proteins. Systems biology is a relatively new area that attempts to describe the biochemical pathways analytically and develop reliable mathematical models for the pathways. A complete understanding of chemical reaction kinetics is prohibitively hard thanks to the nonlinear and highly complex mechanisms that regulate protein formation, but attempting to numerically solve some of the governing differential equations seems to offer significant insight about their biochemical picture. To validate these models, one can perform simple experiments in the lab. This paper introduces fundamental ideas in biochemical signaling and attempts to take first steps into the understanding of biochemical oscillations. Initially, the two-pool model of calcium is used to describe the dynamics behind the oscillations. Later we present some elementary results showing biochemical oscillations arising from solving differential equations of Elowitz and Leibler using MATLAB software.
BioNetSim: a Petri net-based modeling tool for simulations of biochemical processes.
Gao, Junhui; Li, Li; Wu, Xiaolin; Wei, Dong-Qing
2012-03-01
BioNetSim, a Petri net-based software for modeling and simulating biochemistry processes, is developed, whose design and implement are presented in this paper, including logic construction, real-time access to KEGG (Kyoto Encyclopedia of Genes and Genomes), and BioModel database. Furthermore, glycolysis is simulated as an example of its application. BioNetSim is a helpful tool for researchers to download data, model biological network, and simulate complicated biochemistry processes. Gene regulatory networks, metabolic pathways, signaling pathways, and kinetics of cell interaction are all available in BioNetSim, which makes modeling more efficient and effective. Similar to other Petri net-based softwares, BioNetSim does well in graphic application and mathematic construction. Moreover, it shows several powerful predominances. (1) It creates models in database. (2) It realizes the real-time access to KEGG and BioModel and transfers data to Petri net. (3) It provides qualitative analysis, such as computation of constants. (4) It generates graphs for tracing the concentration of every molecule during the simulation processes.
Song, Huwei; Zhao, Xiangxiang; Hu, Weicheng; Wang, Xinfeng; Shen, Ting; Yang, Liming
2016-11-04
Loquat ( Eriobotrya japonica Lindl.) is an important non-climacteric fruit and rich in essential nutrients such as minerals and carotenoids. During fruit development and ripening, thousands of the differentially expressed genes (DEGs) from various metabolic pathways cause a series of physiological and biochemical changes. To better understand the underlying mechanism of fruit development, the Solexa/Illumina RNA-seq high-throughput sequencing was used to evaluate the global changes of gene transcription levels. More than 51,610,234 high quality reads from ten runs of fruit development were sequenced and assembled into 48,838 unigenes. Among 3256 DEGs, 2304 unigenes could be annotated to the Gene Ontology database. These DEGs were distributed into 119 pathways described in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. A large number of DEGs were involved in carbohydrate metabolism, hormone signaling, and cell-wall degradation. The real-time reverse transcription (qRT)-PCR analyses revealed that several genes related to cell expansion, auxin signaling and ethylene response were differentially expressed during fruit development. Other members of transcription factor families were also identified. There were 952 DEGs considered as novel genes with no annotation in any databases. These unigenes will serve as an invaluable genetic resource for loquat molecular breeding and postharvest storage.
Application of bioinformatics tools and databases in microbial dehalogenation research (a review).
Satpathy, R; Konkimalla, V B; Ratha, J
2015-01-01
Microbial dehalogenation is a biochemical process in which the halogenated substances are catalyzed enzymatically in to their non-halogenated form. The microorganisms have a wide range of organohalogen degradation ability both explicit and non-specific in nature. Most of these halogenated organic compounds being pollutants need to be remediated; therefore, the current approaches are to explore the potential of microbes at a molecular level for effective biodegradation of these substances. Several microorganisms with dehalogenation activity have been identified and characterized. In this aspect, the bioinformatics plays a key role to gain deeper knowledge in this field of dehalogenation. To facilitate the data mining, many tools have been developed to annotate these data from databases. Therefore, with the discovery of a microorganism one can predict a gene/protein, sequence analysis, can perform structural modelling, metabolic pathway analysis, biodegradation study and so on. This review highlights various methods of bioinformatics approach that describes the application of various databases and specific tools in the microbial dehalogenation fields with special focus on dehalogenase enzymes. Attempts have also been made to decipher some recent applications of in silico modeling methods that comprise of gene finding, protein modelling, Quantitative Structure Biodegradibility Relationship (QSBR) study and reconstruction of metabolic pathways employed in dehalogenation research area.
"Which Pathway Am I?" Using a Game Approach to Teach Students about Biochemical Pathways
ERIC Educational Resources Information Center
Ooi, Beng Guat; Sanger, Michael J.
2009-01-01
This game was designed to provide students with an alternative way to learn biochemical pathways through an interactive approach. In this game, students worked in pairs to help each other identify pathways taped to each other's backs by asking simple "yes or no" questions related to these pathways. This exercise was conducted after the traditional…
Correcting ligands, metabolites, and pathways
Ott, Martin A; Vriend, Gert
2006-01-01
Background A wide range of research areas in bioinformatics, molecular biology and medicinal chemistry require precise chemical structure information about molecules and reactions, e.g. drug design, ligand docking, metabolic network reconstruction, and systems biology. Most available databases, however, treat chemical structures more as illustrations than as a datafield in its own right. Lack of chemical accuracy impedes progress in the areas mentioned above. We present a database of metabolites called BioMeta that augments the existing pathway databases by explicitly assessing the validity, correctness, and completeness of chemical structure and reaction information. Description The main bulk of the data in BioMeta were obtained from the KEGG Ligand database. We developed a tool for chemical structure validation which assesses the chemical validity and stereochemical completeness of a molecule description. The validation tool was used to examine the compounds in BioMeta, showing that a relatively small number of compounds had an incorrect constitution (connectivity only, not considering stereochemistry) and that a considerable number (about one third) had incomplete or even incorrect stereochemistry. We made a large effort to correct the errors and to complete the structural descriptions. A total of 1468 structures were corrected and/or completed. We also established the reaction balance of the reactions in BioMeta and corrected 55% of the unbalanced (stoichiometrically incorrect) reactions in an automatic procedure. The BioMeta database was implemented in PostgreSQL and provided with a web-based interface. Conclusion We demonstrate that the validation of metabolite structures and reactions is a feasible and worthwhile undertaking, and that the validation results can be used to trigger corrections and improvements to BioMeta, our metabolite database. BioMeta provides some tools for rational drug design, reaction searches, and visualization. It is freely available at provided that the copyright notice of all original data is cited. The database will be useful for querying and browsing biochemical pathways, and to obtain reference information for identifying compounds. However, these applications require that the underlying data be correct, and that is the focus of BioMeta. PMID:17132165
Wang, Huan; Tang, Lei; Wei, Hongling; Lu, Junkai; Mu, Changkao; Wang, Chunlin
2018-05-31
Scylla paramamosain (Crustacea: Decapoda: Portunidae: Syclla De Hann) is a commercially important mud crab distributed along the coast of southern China and other Indo-Pacific countries (Lin Z, Hao M, Zhu D, et al, Comp Biochem Physiol B Biochem Mol Biol 208-209:29-37, 2017; Walton ME, Vay LL, Lebata JH, et al, Estuar Coast Shelf Sci 66(3-4):493-500, 2006; Wang Z, Sun B, Zhu F, Fish Shellfish Immunol 67:612-9, 2017). While S. paramamosain is a euryhaline species, a sudden drop in salinity induces a negative impact on growth, molting, and reproduction, and may even cause death. The mechanism of osmotic regulation of marine crustaceans has been recently under investigation. However, the mechanism of adapting to a sudden drop in salinity has not been reported. In this study, transcriptomics analysis was conducted on the gills of S. paramamosain to test its adaptive capabilities over 120 h with a sudden drop in salinity from 23 ‰ to 3 ‰. At the level of transcription, 135 DEGs (108 up-regulated and 27 down-regulated) annotated by NCBI non-redundant (nr) protein database were screened. GO analysis showed that the catalytic activity category showed the most participating genes in the 24 s-tier GO terms, indicating that intracellular metabolic activities in S. paramamosain were enhanced. Of the 164 mapped KEGG pathways, seven of the top 20 pathways were closely related to regulation of the Na + / K + -ATPase. Seven additional amino acid metabolism-related pathways were also found, along with other important signaling pathways. Ion transport and amino acid metabolism were key factors in regulating the salinity adaptation of S. paramamosain in addition to several important signaling pathways.
HMDB 3.0--The Human Metabolome Database in 2013.
Wishart, David S; Jewison, Timothy; Guo, An Chi; Wilson, Michael; Knox, Craig; Liu, Yifeng; Djoumbou, Yannick; Mandal, Rupasri; Aziat, Farid; Dong, Edison; Bouatra, Souhaila; Sinelnikov, Igor; Arndt, David; Xia, Jianguo; Liu, Philip; Yallou, Faizath; Bjorndahl, Trent; Perez-Pineiro, Rolando; Eisner, Roman; Allen, Felicity; Neveu, Vanessa; Greiner, Russ; Scalbert, Augustin
2013-01-01
The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40,000 (a 600% increase). This enormous expansion is a result of the inclusion of both 'detected' metabolites (those with measured concentrations or experimental confirmation of their existence) and 'expected' metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
Construction and completion of flux balance models from pathway databases.
Latendresse, Mario; Krummenacker, Markus; Trupp, Miles; Karp, Peter D
2012-02-01
Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. mario.latendresse@sri.com Supplementary data are available at Bioinformatics online.
Fridman, Eyal; Wang, Jihong; Iijima, Yoko; Froehlich, John E.; Gang, David R.; Ohlrogge, John; Pichersky, Eran
2005-01-01
Medium-length methylketones (C7-C15) are highly effective in protecting plants from numerous pests. We used a biochemical genomics approach to elucidate the pathway leading to synthesis of methylketones in the glandular trichomes of the wild tomato Lycopersicon hirsutum f glabratum (accession PI126449). A comparison of gland EST databases from accession PI126449 and a second L. hirsutum accession, LA1777, whose glands do not contain methylketones, showed that the expression of genes for fatty acid biosynthesis is elevated in PI126449 glands, suggesting de novo biosynthesis of methylketones. A cDNA abundant in the PI126449 gland EST database but rare in the LA1777 database was similar in sequence to plant esterases. This cDNA, designated Methylketone Synthase 1 (MKS1), was expressed in Escherichia coli and the purified protein used to catalyze in vitro reactions in which C12, C14, and C16 β-ketoacyl–acyl-carrier-proteins (intermediates in fatty acid biosynthesis) were hydrolyzed and decarboxylated to give C11, C13, and C15 methylketones, respectively. Although MKS1 does not contain a classical transit peptide, in vitro import assays showed that it was targeted to the stroma of plastids, where fatty acid biosynthesis occurs. Levels of MKS1 transcript, protein, and enzymatic activity were correlated with levels of methylketones and gland density in a variety of tomato accessions and in different plant organs. PMID:15772286
Abaka, Gamze; Bıyıkoğlu, Türker; Erten, Cesim
2013-07-01
Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Supplementary data are available at Bioinformatics online.
Biochemical-Pathway Diversity in Archaebacteria
1990-08-30
Classification) (U) Biochemical-pathway diversity in Archaebacteria 12 PERSONAL AUTHOR(S) I Jensen, Roy-A. i3o. TYPE OF REN" RT 12b. Tki~ 0’E D-30-9 4...by block numtb.sj FIEL I ROU I SIGRLJP Archaebacteria , biochemical diversity, prephenate 06 03. 1 dehydratase, aromatic amino acid biosynthesis t...1988 RE10SE: lo assess the extent to which the archaebacteria possess unique biochemical features of aromatic amino acid biosynthesis and regulation and
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hay, J.; Schwender, J.
Computational simulation of large-scale biochemical networks can be used to analyze and predict the metabolic behavior of an organism, such as a developing seed. Based on the biochemical literature, pathways databases and decision rules defining reaction directionality we reconstructed bna572, a stoichiometric metabolic network model representing Brassica napus seed storage metabolism. In the highly compartmentalized network about 25% of the 572 reactions are transport reactions interconnecting nine subcellular compartments and the environment. According to known physiological capabilities of developing B. napus embryos, four nutritional conditions were defined to simulate heterotrophy or photoheterotrophy, each in combination with the availability of inorganicmore » nitrogen (ammonia, nitrate) or amino acids as nitrogen sources. Based on mathematical linear optimization the optimal solution space was comprehensively explored by flux variability analysis, thereby identifying for each reaction the range of flux values allowable under optimality. The range and variability of flux values was then categorized into flux variability types. Across the four nutritional conditions, approximately 13% of the reactions have variable flux values and 10-11% are substitutable (can be inactive), both indicating metabolic redundancy given, for example, by isoenzymes, subcellular compartmentalization or the presence of alternative pathways. About one-third of the reactions are never used and are associated with pathways that are suboptimal for storage synthesis. Fifty-seven reactions change flux variability type among the different nutritional conditions, indicating their function in metabolic adjustments. This predictive modeling framework allows analysis and quantitative exploration of storage metabolism of a developing B. napus oilseed.« less
biochem4j: Integrated and extensible biochemical knowledge through graph databases.
Swainston, Neil; Batista-Navarro, Riza; Carbonell, Pablo; Dobson, Paul D; Dunstan, Mark; Jervis, Adrian J; Vinaixa, Maria; Williams, Alan R; Ananiadou, Sophia; Faulon, Jean-Loup; Mendes, Pedro; Kell, Douglas B; Scrutton, Nigel S; Breitling, Rainer
2017-01-01
Biologists and biochemists have at their disposal a number of excellent, publicly available data resources such as UniProt, KEGG, and NCBI Taxonomy, which catalogue biological entities. Despite the usefulness of these resources, they remain fundamentally unconnected. While links may appear between entries across these databases, users are typically only able to follow such links by manual browsing or through specialised workflows. Although many of the resources provide web-service interfaces for computational access, performing federated queries across databases remains a non-trivial but essential activity in interdisciplinary systems and synthetic biology programmes. What is needed are integrated repositories to catalogue both biological entities and-crucially-the relationships between them. Such a resource should be extensible, such that newly discovered relationships-for example, those between novel, synthetic enzymes and non-natural products-can be added over time. With the introduction of graph databases, the barrier to the rapid generation, extension and querying of such a resource has been lowered considerably. With a particular focus on metabolic engineering as an illustrative application domain, biochem4j, freely available at http://biochem4j.org, is introduced to provide an integrated, queryable database that warehouses chemical, reaction, enzyme and taxonomic data from a range of reliable resources. The biochem4j framework establishes a starting point for the flexible integration and exploitation of an ever-wider range of biological data sources, from public databases to laboratory-specific experimental datasets, for the benefit of systems biologists, biosystems engineers and the wider community of molecular biologists and biological chemists.
biochem4j: Integrated and extensible biochemical knowledge through graph databases
Batista-Navarro, Riza; Dunstan, Mark; Jervis, Adrian J.; Vinaixa, Maria; Ananiadou, Sophia; Faulon, Jean-Loup; Kell, Douglas B.
2017-01-01
Biologists and biochemists have at their disposal a number of excellent, publicly available data resources such as UniProt, KEGG, and NCBI Taxonomy, which catalogue biological entities. Despite the usefulness of these resources, they remain fundamentally unconnected. While links may appear between entries across these databases, users are typically only able to follow such links by manual browsing or through specialised workflows. Although many of the resources provide web-service interfaces for computational access, performing federated queries across databases remains a non-trivial but essential activity in interdisciplinary systems and synthetic biology programmes. What is needed are integrated repositories to catalogue both biological entities and–crucially–the relationships between them. Such a resource should be extensible, such that newly discovered relationships–for example, those between novel, synthetic enzymes and non-natural products–can be added over time. With the introduction of graph databases, the barrier to the rapid generation, extension and querying of such a resource has been lowered considerably. With a particular focus on metabolic engineering as an illustrative application domain, biochem4j, freely available at http://biochem4j.org, is introduced to provide an integrated, queryable database that warehouses chemical, reaction, enzyme and taxonomic data from a range of reliable resources. The biochem4j framework establishes a starting point for the flexible integration and exploitation of an ever-wider range of biological data sources, from public databases to laboratory-specific experimental datasets, for the benefit of systems biologists, biosystems engineers and the wider community of molecular biologists and biological chemists. PMID:28708831
Cellular compartmentalization of secondary metabolism
Kistler, H. Corby; Broz, Karen
2015-01-01
Fungal secondary metabolism is often considered apart from the essential housekeeping functions of the cell. However, there are clear links between fundamental cellular metabolism and the biochemical pathways leading to secondary metabolite synthesis. Besides utilizing key biochemical precursors shared with the most essential processes of the cell (e.g., amino acids, acetyl CoA, NADPH), enzymes for secondary metabolite synthesis are compartmentalized at conserved subcellular sites that position pathway enzymes to use these common biochemical precursors. Co-compartmentalization of secondary metabolism pathway enzymes also may function to channel precursors, promote pathway efficiency and sequester pathway intermediates and products from the rest of the cell. In this review we discuss the compartmentalization of three well-studied fungal secondary metabolite biosynthetic pathways for penicillin G, aflatoxin and deoxynivalenol, and summarize evidence used to infer subcellular localization. We also discuss how these metabolites potentially are trafficked within the cell and may be exported. PMID:25709603
Singh, Satendra; Singh, Dev Bukhsh; Singh, Anamika; Gautam, Budhayash; Ram, Gurudayal; Dwivedi, Seema; Ramteke, Pramod W
2016-12-01
Streptococcus pyogenes is one of the most important pathogens as it is involved in various infections affecting upper respiratory tract and skin. Due to the emergence of multidrug resistance and cross-resistance, S. Pyogenes is becoming more pathogenic and dangerous. In the present study, an in silico comparative analysis of total 65 metabolic pathways of the host (Homo sapiens) and the pathogen was performed. Initially, 486 paralogous enzymes were identified so that they can be removed from possible drug target list. The 105 enzymes of the biochemical pathways of S. pyogenes from the KEGG metabolic pathway database were compared with the proteins from the Homo sapiens by performing a BLASTP search against the non-redundant database restricted to the Homo sapiens subset. Out of these, 83 enzymes were identified as non-human homologous while 30 enzymes of inadequate amino acid length were removed for further processing. Essential enzymes were finally mined from remaining 53 enzymes. Finally, 28 essential enzymes were identified in S. pyogenes SF370 (serotype M1). In subcellular localization study, 18 enzymes were predicted with cytoplasmic localization and ten enzymes with the membrane localization. These ten enzymes with putative membrane localization should be of particular interest. Acyl-carrier-protein S-malonyltransferase, DNA polymerase III subunit beta and dihydropteroate synthase are novel drug targets and thus can be used to design potential inhibitors against S. pyogenes infection. 3D structure of dihydropteroate synthase was modeled and validated that can be used for virtual screening and interaction study of potential inhibitors with the target enzyme.
The chemokine receptor CCR1 is identified in mast cell-derived exosomes.
Liang, Yuting; Qiao, Longwei; Peng, Xia; Cui, Zelin; Yin, Yue; Liao, Huanjin; Jiang, Min; Li, Li
2018-01-01
Mast cells are important effector cells of the immune system, and mast cell-derived exosomes carrying RNAs play a role in immune regulation. However, the molecular function of mast cell-derived exosomes is currently unknown, and here, we identify differentially expressed genes (DEGs) in mast cells and exosomes. We isolated mast cells derived exosomes through differential centrifugation and screened the DEGs from mast cell-derived exosomes, using the GSE25330 array dataset downloaded from the Gene Expression Omnibus database. Biochemical pathways were analyzed by Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the online tool DAVID. DEGs-associated protein-protein interaction networks (PPIs) were constructed using the STRING database and Cytoscape software. The genes identified from these bioinformatics analyses were verified by qRT-PCR and Western blot in mast cells and exosomes. We identified 2121 DEGs (843 up and 1278 down-regulated genes) in HMC-1 cell-derived exosomes and HMC-1 cells. The up-regulated DEGs were classified into two significant modules. The chemokine receptor CCR1 was screened as a hub gene and enriched in cytokine-mediated signaling pathway in module one. Seven genes, including CCR1, CD9, KIT, TGFBR1, TLR9, TPSAB1 and TPSB2 were screened and validated through qRT-PCR analysis. We have achieved a comprehensive view of the pivotal genes and pathways in mast cells and exosomes and identified CCR1 as a hub gene in mast cell-derived exosomes. Our results provide novel clues with respect to the biological processes through which mast cell-derived exosomes modulate immune responses.
BNDB - the Biochemical Network Database.
Küntzer, Jan; Backes, Christina; Blum, Torsten; Gerasch, Andreas; Kaufmann, Michael; Kohlbacher, Oliver; Lenhof, Hans-Peter
2007-10-02
Technological advances in high-throughput techniques and efficient data acquisition methods have resulted in a massive amount of life science data. The data is stored in numerous databases that have been established over the last decades and are essential resources for scientists nowadays. However, the diversity of the databases and the underlying data models make it difficult to combine this information for solving complex problems in systems biology. Currently, researchers typically have to browse several, often highly focused, databases to obtain the required information. Hence, there is a pressing need for more efficient systems for integrating, analyzing, and interpreting these data. The standardization and virtual consolidation of the databases is a major challenge resulting in a unified access to a variety of data sources. We present the Biochemical Network Database (BNDB), a powerful relational database platform, allowing a complete semantic integration of an extensive collection of external databases. BNDB is built upon a comprehensive and extensible object model called BioCore, which is powerful enough to model most known biochemical processes and at the same time easily extensible to be adapted to new biological concepts. Besides a web interface for the search and curation of the data, a Java-based viewer (BiNA) provides a powerful platform-independent visualization and navigation of the data. BiNA uses sophisticated graph layout algorithms for an interactive visualization and navigation of BNDB. BNDB allows a simple, unified access to a variety of external data sources. Its tight integration with the biochemical network library BN++ offers the possibility for import, integration, analysis, and visualization of the data. BNDB is freely accessible at http://www.bndb.org.
Comprehensive, comprehensible, distributed and intelligent databases: current status.
Frishman, D; Heumann, K; Lesk, A; Mewes, H W
1998-01-01
It is only a matter of time until a user will see not many but one integrated database of information for molecular biology. Is this true? Is it a good thing? Why will it happen? Where are we now? What developments are fostering and what developments are impeding progress towards this end? A list of WWW resources devoted to database issues in molecular biology is available at http://www.mips.biochem.mpg.de frishman@mips.biochem.mpg.de
AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide
2015-11-19
Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database in which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. This database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.
Childs, Kevin L; Konganti, Kranti; Buell, C Robin
2012-01-01
Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: http://bfgr.plantbiology.msu.edu.
design TEA LCA Biochemical conversion process pathways Algal biomass production and conversion pathways Production," Green Chemistry (2015) Process Design and Economics for the Conversion of Lignocellulosic Production," Applied Energy (2011) Process Design and Economics for Biochemical Conversion of
Vongsangnak, Wanwipa; Chumnanpuen, Pramote
2016-01-01
Bioluminescence, which living organisms such as fireflies emit light, has been studied extensively for over half a century. This intriguing reaction, having its origins in nature where glowing insects can signal things such as attraction or defense, is now widely used in biotechnology with applications of bioluminescence and chemiluminescence. Luciferase, a key enzyme in this reaction, has been well characterized; however, the enzymes involved in the biosynthetic pathway of its substrate, luciferin, remains unsolved at present. To elucidate the luciferin metabolism, we performed a de novo transcriptome analysis using larvae of the firefly species, Luciola aquatilis. Here, a comparative analysis is performed with the model coleopteran insect Tribolium casteneum to elucidate the metabolic pathways in L. aquatilis. Based on a template luciferin biosynthetic pathway, combined with a range of protein and pathway databases, and various prediction tools for functional annotation, the candidate genes, enzymes, and biochemical reactions involved in luciferin metabolism are proposed for L. aquatilis. The candidate gene expression is validated in the adult L. aquatilis using reverse transcription PCR (RT-PCR). This study provides useful information on the bio-production of luciferin in the firefly and will benefit to future applications of the valuable firefly bioluminescence system. PMID:27761329
Early lignin pathway enzymes and routes to chlorogenic acid in switchgrass (Panicum virgatum L.).
Escamilla-Treviño, Luis L; Shen, Hui; Hernandez, Timothy; Yin, Yanbin; Xu, Ying; Dixon, Richard A
2014-03-01
Studying lignin biosynthesis in Panicum virgatum (switchgrass) has provided a basis for generating plants with reduced lignin content and increased saccharification efficiency. Chlorogenic acid (CGA, caffeoyl quinate) is the major soluble phenolic compound in switchgrass, and the lignin and CGA biosynthetic pathways potentially share intermediates and enzymes. The enzyme hydroxycinnamoyl-CoA: quinate hydroxycinnamoyltransferase (HQT) is responsible for CGA biosynthesis in tobacco, tomato and globe artichoke, but there are no close orthologs of HQT in switchgrass or in other monocotyledonous plants with complete genome sequences. We examined available transcriptomic databases for genes encoding enzymes potentially involved in CGA biosynthesis in switchgrass. The protein products of two hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyltransferase (HCT) genes (PvHCT1a and PvHCT2a), closely related to lignin pathway HCTs from other species, were characterized biochemically and exhibited the expected HCT activity, preferring shikimic acid as acyl acceptor. We also characterized two switchgrass coumaroyl shikimate 3'-hydroxylase (C3'H) enzymes (PvC3'H1 and PvC3'H2); both of these cytochrome P450s had the capacity to hydroxylate 4-coumaroyl shikimate or 4-coumaroyl quinate to generate caffeoyl shikimate or CGA. Another switchgrass hydroxycinnamoyl transferase, PvHCT-Like1, is phylogenetically distant from HCTs or HQTs, but exhibits HQT activity, preferring quinic acid as acyl acceptor, and could therefore function in CGA biosynthesis. The biochemical features of the recombinant enzymes, the presence of the corresponding activities in plant protein extracts, and the expression patterns of the corresponding genes, suggest preferred routes to CGA in switchgrass.
Srivastava, Anubhav; Evans, Krystal J; Sexton, Anna E; Schofield, Louis; Creek, Darren J
2017-04-07
A detailed analysis of the metabolic state of human-stem-cell-derived erythrocytes allowed us to characterize the existence of active metabolic pathways in younger reticulocytes and compare them to mature erythrocytes. Using high-resolution LC-MS-based untargeted metabolomics, we found that reticulocytes had a comparatively much richer repertoire of metabolites, which spanned a range of metabolite classes. An untargeted metabolomics analysis using stable-isotope-labeled glucose showed that only glycolysis and the pentose phosphate pathway actively contributed to the biosynthesis of metabolites in erythrocytes, and these pathways were upregulated in reticulocytes. Most metabolite species found to be enriched in reticulocytes were residual pools of metabolites produced by earlier erythropoietic processes, and their systematic depletion in mature erythrocytes aligns with the simplification process, which is also seen at the cellular and the structural level. Our work shows that high-resolution LC-MS-based untargeted metabolomics provides a global coverage of the biochemical species that are present in erythrocytes. However, the incorporation of stable isotope labeling provides a more accurate description of the active metabolic processes that occur in each developmental stage. To our knowledge, this is the first detailed characterization of the active metabolic pathways of the erythroid lineage, and it provides a rich database for understanding the physiology of the maturation of reticulocytes into mature erythrocytes.
Reconstructing biochemical pathways from time course data.
Srividhya, Jeyaraman; Crampin, Edmund J; McSharry, Patrick E; Schnell, Santiago
2007-03-01
Time series data on biochemical reactions reveal transient behavior, away from chemical equilibrium, and contain information on the dynamic interactions among reacting components. However, this information can be difficult to extract using conventional analysis techniques. We present a new method to infer biochemical pathway mechanisms from time course data using a global nonlinear modeling technique to identify the elementary reaction steps which constitute the pathway. The method involves the generation of a complete dictionary of polynomial basis functions based on the law of mass action. Using these basis functions, there are two approaches to model construction, namely the general to specific and the specific to general approach. We demonstrate that our new methodology reconstructs the chemical reaction steps and connectivity of the glycolytic pathway of Lactococcus lactis from time course experimental data.
2014-04-01
the Fanconi Anemia Pathway- Regulated Nucleases in Genome Maintenance for Preventing Bone Marrow Failure and Cancer PRINCIPAL INVESTIGATOR...GRANT NUMBER 4. TITLE AND SUBTITLE A Biochemical Approach to Understanding the Fanconi Anemia Pathway-Regulated Nucleases in Genome Maintenance for...Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Fanconi anemia is the most prevalent inherited BMF syndromes, caused by mutations in
Construction and engineering of large biochemical pathways via DNA assembler
Shao, Zengyi; Zhao, Huimin
2015-01-01
Summary DNA assembler enables rapid construction and engineering of biochemical pathways in a one-step fashion by exploitation of the in vivo homologous recombination mechanism in Saccharomyces cerevisiae. It has many applications in pathway engineering, metabolic engineering, combinatorial biology, and synthetic biology. Here we use two examples including the zeaxanthin biosynthetic pathway and the aureothin biosynthetic gene cluster to describe the key steps in the construction of pathways containing multiple genes using the DNA assembler approach. Methods for construct design, pathway assembly, pathway confirmation, and functional analysis are shown. The protocol for fine genetic modifications such as site-directed mutagenesis for engineering the aureothin gene cluster is also illustrated. PMID:23996442
Hackmann, Timothy J; Ngugi, David Kamanda; Firkins, Jeffrey L; Tao, Junyi
2017-11-01
Bacteria have been thought to follow only a few well-recognized biochemical pathways when fermenting glucose or other hexoses. These pathways have been chiseled in the stone of textbooks for decades, with most sources rendering them as they appear in the classic 1986 text by Gottschalk. Still, it is unclear how broadly these pathways apply, given that they were established and delineated biochemically with only a few model organisms. Here, we show that well-recognized pathways often cannot explain fermentation products formed by bacteria. In the most extensive analysis of its kind, we reconstructed pathways for glucose fermentation from genomes of 48 species and subspecies of bacteria from one environment (the rumen). In total, 44% of these bacteria had atypical pathways, including several that are completely unprecedented for bacteria or any organism. In detail, 8% of bacteria had an atypical pathway for acetate formation; 21% of bacteria had an atypical pathway for propionate or succinate formation; 6% of bacteria had an atypical pathway for butyrate formation and 33% of bacteria had an atypical or incomplete Embden-Meyerhof-Parnas pathway. This study shows that reconstruction of metabolic pathways - a common goal of omics studies - could be incorrect if well-recognized pathways are used for reference. Furthermore, it calls for renewed efforts to delineate fermentation pathways biochemically. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.
Calculation of biochemical net reactions and pathways by using matrix operations.
Alberty, R A
1996-01-01
Pathways for net biochemical reactions can be calculated by using a computer program that solves systems of linear equations. The coefficients in the linear equations are the stoichiometric numbers in the biochemical equations for the system. The solution of the system of linear equations is a vector of the stoichiometric numbers of the reactions in the pathway for the net reaction; this is referred to as the pathway vector. The pathway vector gives the number of times the various reactions have to occur to produce the desired net reaction. Net reactions may involve unknown numbers of ATP, ADP, and Pi molecules. The numbers of ATP, ADP, and Pi in a desired net reaction can be calculated in a two-step process. In the first step, the pathway is calculated by solving the system of linear equations for an abbreviated stoichiometric number matrix without ATP, ADP, Pi, NADred, and NADox. In the second step, the stoichiometric numbers in the desired net reaction, which includes ATP, ADP, Pi, NADred, and NADox, are obtained by multiplying the full stoichiometric number matrix by the calculated pathway vector. PMID:8804633
Crowhurst, Ross N; Gleave, Andrew P; MacRae, Elspeth A; Ampomah-Dwamena, Charles; Atkinson, Ross G; Beuning, Lesley L; Bulley, Sean M; Chagne, David; Marsh, Ken B; Matich, Adam J; Montefiori, Mirco; Newcomb, Richard D; Schaffer, Robert J; Usadel, Björn; Allan, Andrew C; Boldingh, Helen L; Bowen, Judith H; Davy, Marcus W; Eckloff, Rheinhart; Ferguson, A Ross; Fraser, Lena G; Gera, Emma; Hellens, Roger P; Janssen, Bart J; Klages, Karin; Lo, Kim R; MacDiarmid, Robin M; Nain, Bhawana; McNeilage, Mark A; Rassam, Maysoon; Richardson, Annette C; Rikkerink, Erik HA; Ross, Gavin S; Schröder, Roswitha; Snowden, Kimberley C; Souleyre, Edwige JF; Templeton, Matt D; Walton, Eric F; Wang, Daisy; Wang, Mindy Y; Wang, Yanming Y; Wood, Marion; Wu, Rongmei; Yauk, Yar-Khing; Laing, William A
2008-01-01
Background Kiwifruit (Actinidia spp.) are a relatively new, but economically important crop grown in many different parts of the world. Commercial success is driven by the development of new cultivars with novel consumer traits including flavor, appearance, healthful components and convenience. To increase our understanding of the genetic diversity and gene-based control of these key traits in Actinidia, we have produced a collection of 132,577 expressed sequence tags (ESTs). Results The ESTs were derived mainly from four Actinidia species (A. chinensis, A. deliciosa, A. arguta and A. eriantha) and fell into 41,858 non redundant clusters (18,070 tentative consensus sequences and 23,788 EST singletons). Analysis of flavor and fragrance-related gene families (acyltransferases and carboxylesterases) and pathways (terpenoid biosynthesis) is presented in comparison with a chemical analysis of the compounds present in Actinidia including esters, acids, alcohols and terpenes. ESTs are identified for most genes in color pathways controlling chlorophyll degradation and carotenoid biosynthesis. In the health area, data are presented on the ESTs involved in ascorbic acid and quinic acid biosynthesis showing not only that genes for many of the steps in these pathways are represented in the database, but that genes encoding some critical steps are absent. In the convenience area, genes related to different stages of fruit softening are identified. Conclusion This large EST resource will allow researchers to undertake the tremendous challenge of understanding the molecular basis of genetic diversity in the Actinidia genus as well as provide an EST resource for comparative fruit genomics. The various bioinformatics analyses we have undertaken demonstrates the extent of coverage of ESTs for genes encoding different biochemical pathways in Actinidia. PMID:18655731
The chemokine receptor CCR1 is identified in mast cell-derived exosomes
Liang, Yuting; Qiao, Longwei; Peng, Xia; Cui, Zelin; Yin, Yue; Liao, Huanjin; Jiang, Min; Li, Li
2018-01-01
Mast cells are important effector cells of the immune system, and mast cell-derived exosomes carrying RNAs play a role in immune regulation. However, the molecular function of mast cell-derived exosomes is currently unknown, and here, we identify differentially expressed genes (DEGs) in mast cells and exosomes. We isolated mast cells derived exosomes through differential centrifugation and screened the DEGs from mast cell-derived exosomes, using the GSE25330 array dataset downloaded from the Gene Expression Omnibus database. Biochemical pathways were analyzed by Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the online tool DAVID. DEGs-associated protein-protein interaction networks (PPIs) were constructed using the STRING database and Cytoscape software. The genes identified from these bioinformatics analyses were verified by qRT-PCR and Western blot in mast cells and exosomes. We identified 2121 DEGs (843 up and 1278 down-regulated genes) in HMC-1 cell-derived exosomes and HMC-1 cells. The up-regulated DEGs were classified into two significant modules. The chemokine receptor CCR1 was screened as a hub gene and enriched in cytokine-mediated signaling pathway in module one. Seven genes, including CCR1, CD9, KIT, TGFBR1, TLR9, TPSAB1 and TPSB2 were screened and validated through qRT-PCR analysis. We have achieved a comprehensive view of the pivotal genes and pathways in mast cells and exosomes and identified CCR1 as a hub gene in mast cell-derived exosomes. Our results provide novel clues with respect to the biological processes through which mast cell-derived exosomes modulate immune responses. PMID:29511430
A Method for Finding Metabolic Pathways Using Atomic Group Tracking.
Huang, Yiran; Zhong, Cheng; Lin, Hai Xiang; Wang, Jianyi
2017-01-01
A fundamental computational problem in metabolic engineering is to find pathways between compounds. Pathfinding methods using atom tracking have been widely used to find biochemically relevant pathways. However, these methods require the user to define the atoms to be tracked. This may lead to failing to predict the pathways that do not conserve the user-defined atoms. In this work, we propose a pathfinding method called AGPathFinder to find biochemically relevant metabolic pathways between two given compounds. In AGPathFinder, we find alternative pathways by tracking the movement of atomic groups through metabolic networks and use combined information of reaction thermodynamics and compound similarity to guide the search towards more feasible pathways and better performance. The experimental results show that atomic group tracking enables our method to find pathways without the need of defining the atoms to be tracked, avoid hub metabolites, and obtain biochemically meaningful pathways. Our results also demonstrate that atomic group tracking, when incorporated with combined information of reaction thermodynamics and compound similarity, improves the quality of the found pathways. In most cases, the average compound inclusion accuracy and reaction inclusion accuracy for the top resulting pathways of our method are around 0.90 and 0.70, respectively, which are better than those of the existing methods. Additionally, AGPathFinder provides the information of thermodynamic feasibility and compound similarity for the resulting pathways.
A Method for Finding Metabolic Pathways Using Atomic Group Tracking
Zhong, Cheng; Lin, Hai Xiang; Wang, Jianyi
2017-01-01
A fundamental computational problem in metabolic engineering is to find pathways between compounds. Pathfinding methods using atom tracking have been widely used to find biochemically relevant pathways. However, these methods require the user to define the atoms to be tracked. This may lead to failing to predict the pathways that do not conserve the user-defined atoms. In this work, we propose a pathfinding method called AGPathFinder to find biochemically relevant metabolic pathways between two given compounds. In AGPathFinder, we find alternative pathways by tracking the movement of atomic groups through metabolic networks and use combined information of reaction thermodynamics and compound similarity to guide the search towards more feasible pathways and better performance. The experimental results show that atomic group tracking enables our method to find pathways without the need of defining the atoms to be tracked, avoid hub metabolites, and obtain biochemically meaningful pathways. Our results also demonstrate that atomic group tracking, when incorporated with combined information of reaction thermodynamics and compound similarity, improves the quality of the found pathways. In most cases, the average compound inclusion accuracy and reaction inclusion accuracy for the top resulting pathways of our method are around 0.90 and 0.70, respectively, which are better than those of the existing methods. Additionally, AGPathFinder provides the information of thermodynamic feasibility and compound similarity for the resulting pathways. PMID:28068354
ReactPRED: a tool to predict and analyze biochemical reactions.
Sivakumar, Tadi Venkata; Giri, Varun; Park, Jin Hwan; Kim, Tae Yong; Bhaduri, Anirban
2016-11-15
Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same. ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application. ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system
DOE Office of Scientific and Technical Information (OSTI.GOV)
AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide
Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database inmore » which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.« less
An affinity-structure database of helix-turn-helix: DNA complexes with a universal coordinate system
AlQuraishi, Mohammed; Tang, Shengdong; Xia, Xide
2015-11-19
Molecular interactions between proteins and DNA molecules underlie many cellular processes, including transcriptional regulation, chromosome replication, and nucleosome positioning. Computational analyses of protein-DNA interactions rely on experimental data characterizing known protein-DNA interactions structurally and biochemically. While many databases exist that contain either structural or biochemical data, few integrate these two data sources in a unified fashion. Such integration is becoming increasingly critical with the rapid growth of structural and biochemical data, and the emergence of algorithms that rely on the synthesis of multiple data types to derive computational models of molecular interactions. We have developed an integrated affinity-structure database inmore » which the experimental and quantitative DNA binding affinities of helix-turn-helix proteins are mapped onto the crystal structures of the corresponding protein-DNA complexes. This database provides access to: (i) protein-DNA structures, (ii) quantitative summaries of protein-DNA binding affinities using position weight matrices, and (iii) raw experimental data of protein-DNA binding instances. Critically, this database establishes a correspondence between experimental structural data and quantitative binding affinity data at the single basepair level. Furthermore, we present a novel alignment algorithm that structurally aligns the protein-DNA complexes in the database and creates a unified residue-level coordinate system for comparing the physico-chemical environments at the interface between complexes. Using this unified coordinate system, we compute the statistics of atomic interactions at the protein-DNA interface of helix-turn-helix proteins. We provide an interactive website for visualization, querying, and analyzing this database, and a downloadable version to facilitate programmatic analysis. Lastly, this database will facilitate the analysis of protein-DNA interactions and the development of programmatic computational methods that capitalize on integration of structural and biochemical datasets. The database can be accessed at http://ProteinDNA.hms.harvard.edu.« less
ORENZA: a web resource for studying ORphan ENZyme activities
Lespinet, Olivier; Labedan, Bernard
2006-01-01
Background Despite the current availability of several hundreds of thousands of amino acid sequences, more than 36% of the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB) are not associated with any amino acid sequence in major public databases. This wide gap separating knowledge of biochemical function and sequence information is found for nearly all classes of enzymes. Thus, there is an urgent need to explore these sequence-less EC numbers, in order to progressively close this gap. Description We designed ORENZA, a PostgreSQL database of ORphan ENZyme Activities, to collate information about the EC numbers defined by the NC-IUBMB with specific emphasis on orphan enzyme activities. Complete lists of all EC numbers and of orphan EC numbers are available and will be periodically updated. ORENZA allows one to browse the complete list of EC numbers or the subset associated with orphan enzymes or to query a specific EC number, an enzyme name or a species name for those interested in particular organisms. It is possible to search ORENZA for the different biochemical properties of the defined enzymes, the metabolic pathways in which they participate, the taxonomic data of the organisms whose genomes encode them, and many other features. The association of an enzyme activity with an amino acid sequence is clearly underlined, making it easy to identify at once the orphan enzyme activities. Interactive publishing of suggestions by the community would provide expert evidence for re-annotation of orphan EC numbers in public databases. Conclusion ORENZA is a Web resource designed to progressively bridge the unwanted gap between function (enzyme activities) and sequence (dataset present in public databases). ORENZA should increase interactions between communities of biochemists and of genomicists. This is expected to reduce the number of orphan enzyme activities by allocating gene sequences to the relevant enzymes. PMID:17026747
METscout: a pathfinder exploring the landscape of metabolites, enzymes and transporters.
Geffers, Lars; Tetzlaff, Benjamin; Cui, Xiao; Yan, Jun; Eichele, Gregor
2013-01-01
METscout (http://metscout.mpg.de) brings together metabolism and gene expression landscapes. It is a MySQL relational database linking biochemical pathway information with 3D patterns of gene expression determined by robotic in situ hybridization in the E14.5 mouse embryo. The sites of expression of ∼1500 metabolic enzymes and of ∼350 solute carriers (SLCs) were included and are accessible as single cell resolution images and in the form of semi-quantitative image abstractions. METscout provides several graphical web-interfaces allowing navigation through complex anatomical and metabolic information. Specifically, the database shows where in the organism each of the many metabolic reactions take place and where SLCs transport metabolites. To link enzymatic reactions and transport, the KEGG metabolic reaction network was extended to include metabolite transport. This network in conjunction with spatial expression pattern of the network genes allows for a tracing of metabolic reactions and transport processes across the entire body of the embryo.
Exercise-induced biochemical changes and their potential influence on cancer: a scientific review
Thomas, Robert James; Kenfield, Stacey A; Jimenez, Alfonso
2017-01-01
Aim To review and discuss the available international literature regarding the indirect and direct biochemical mechanisms that occur after exercise, which could positively, or negatively, influence oncogenic pathways. Methods The PubMed, MEDLINE, Embase and Cochrane libraries were searched for papers up to July 2016 addressing biochemical changes after exercise with a particular reference to cancer. The three authors independently assessed their appropriateness for inclusion in this review based on their scientific quality and relevance. Results 168 papers were selected and categorised into indirect and direct biochemical pathways. The indirect effects included changes in vitamin D, weight reduction, sunlight exposure and improved mood. The direct effects included insulin-like growth factor, epigenetic effects on gene expression and DNA repair, vasoactive intestinal peptide, oxidative stress and antioxidant pathways, heat shock proteins, testosterone, irisin, immunity, chronic inflammation and prostaglandins, energy metabolism and insulin resistance. Summary Exercise is one of several lifestyle factors known to lower the risk of developing cancer and is associated with lower relapse rates and better survival. This review highlights the numerous biochemical processes, which explain these potential anticancer benefits. PMID:27993842
Vinnakota, Kalyan C.; Wu, Fan; Kushmerick, Martin J.; Beard, Daniel A.
2009-01-01
The operation of biochemical systems in vivo and in vitro is strongly influenced by complex interactions between biochemical reactants and ions such as H+, Mg2+, K+, and Ca2+. These are important second messengers in metabolic and signaling pathways that directly influence the kinetics and thermodynamics of biochemical systems. Herein we describe the biophysical theory and computational methods to account for multiple ion binding to biochemical reactants and demonstrate the crucial effects of ion binding on biochemical reaction kinetics and thermodynamics. In simulations of realistic systems, the concentrations of these ions change with time due to dynamic buffering and competitive binding. In turn, the effective thermodynamic properties vary as functions of cation concentrations and important environmental variables such as temperature and overall ionic strength. Physically realistic simulations of biochemical systems require incorporating all of these phenomena into a coherent mathematical description. Several applications to physiological systems are demonstrated based on this coherent simulation framework. PMID:19216922
Drug-Path: a database for drug-induced pathways
Zeng, Hui; Cui, Qinghua
2015-01-01
Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. Database URL: http://www.cuilab.cn/drugpath PMID:26130661
Biochemical Characterization of β-Amino Acid Incorporation in Fluvirucin B 2 Biosynthesis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barajas, Jesus F.; Zargar, Amin; Pang, Bo
Naturally occurring lactams, such as the polyketide-derived macrolactams, provide a diverse class of natural products that could enhance existing chemically produced lactams. While β-amino acid loading in the fluvirucin B 2 polyketide pathway has been proposed by a previously identified putative biosynthetic gene cluster, biochemical characterization of the complete loading enzymes has not been described. In this paper, we elucidate the complete biosynthetic pathway of the β-amino acid loading pathway in fluvirucin B 2 biosynthesis. We demonstrate the promiscuity of the loading pathway to utilize a range of amino acids and further illustrate the ability to introduce non-native acyl transferasesmore » to selectively transfer β-amino acids onto a PKS loading platform. The results presented here provide a detailed biochemical description of β-amino acid selection and will further aid in future efforts to develop engineered lactam-producing PKS platforms.« less
Biochemical Characterization of β-Amino Acid Incorporation in Fluvirucin B 2 Biosynthesis
Barajas, Jesus F.; Zargar, Amin; Pang, Bo; ...
2018-03-30
Naturally occurring lactams, such as the polyketide-derived macrolactams, provide a diverse class of natural products that could enhance existing chemically produced lactams. While β-amino acid loading in the fluvirucin B 2 polyketide pathway has been proposed by a previously identified putative biosynthetic gene cluster, biochemical characterization of the complete loading enzymes has not been described. In this paper, we elucidate the complete biosynthetic pathway of the β-amino acid loading pathway in fluvirucin B 2 biosynthesis. We demonstrate the promiscuity of the loading pathway to utilize a range of amino acids and further illustrate the ability to introduce non-native acyl transferasesmore » to selectively transfer β-amino acids onto a PKS loading platform. The results presented here provide a detailed biochemical description of β-amino acid selection and will further aid in future efforts to develop engineered lactam-producing PKS platforms.« less
Quantitative trait loci and metabolic pathways
McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.
1998-01-01
The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823
Gene Polymorphism Studies in a Teaching Laboratory
NASA Astrophysics Data System (ADS)
Shultz, Jeffry
2009-02-01
I present a laboratory procedure for illustrating transcription, post-transcriptional modification, gene conservation, and comparative genetics for use in undergraduate biology education. Students are individually assigned genes in a targeted biochemical pathway, for which they design and test polymerase chain reaction (PCR) primers. In this example, students used genes annotated for the steroid biosynthesis pathway in soybean. The authoritative Kyoto encyclopedia of genes and genomes (KEGG) interactive database and other online resources were used to design primers based first on soybean expressed sequence tags (ESTs), then on ESTs from an alternate organism if soybean sequence was unavailable. Students designed a total of 50 gene-based primer pairs (37 soybean, 13 alternative) and tested these for polymorphism state and similarity between two soybean and two pea lines. Student assessment was based on acquisition of laboratory skills and successful project completion. This simple procedure illustrates conservation of genes and is not limited to soybean or pea. Cost per student estimates are included, along with a detailed protocol and flow diagram of the procedure.
Zhu, Baojie; Cao, Huiting; Sun, Limin; Li, Bo; Guo, Liwei; Duan, Jinao; Zhu, Huaxu; Zhang, Qichun
2018-04-24
Huang-Lian Jie-Du decoction (HLJDD), a traditional formula of Chinese medicine constituted with Rhizoma Coptidis, RadixScutellariae, CortexPhellodendri amurensis and Fructus Gardeniae, exhibits unambiguous therapeutic effect on cerebral ischemia via multi-targets action. Further investigation, however, is still required to explore the relationship between those mechanisms and targets through system approaches. Rats of cerebral ischemia were completed by middle cerebral artery occlusion (MCAO) with reperfusion. Following evaluation of pharmacological actions of HLJDD on MCAO rats, the plasma samples from rats of control, MCAO and HLJDD-treated MCAO groups were prepared strictly and subjected to ultra-performance liquid chromatography quadrupole time of flight mass spectrometry for metabolites analysis. The raw mass data were imported to MassLynx software for peak detection and alignment, and further introduced to EZinfo 2.0 software for orthogonal projection to latent structures analysis, principal component analysis and partial least-squares-discriminant analysis. The metabolic pathways assay of those potential biomarkers were performed with MetaboAnalyst through the online database, HMDB, Metlin, KEGG and SMPD. Those intriguing metabolic pathways were further investigated via biochemical assay. HLJDD ameliorated the MCAO-induce cerebral damage and blocked the severe inflammation response. There were nineteen different biomarkers identified among control, MCAO and HLJDD-treated MCAO groups. Ten metabolic pathways were proposed from these significant metabolites. Incorporation with the biochemical assay of cerebral tissue, modulation of metabolic stress, regulation glutamate/GABA-glutamine cycle and enhancement of cholinergic neurons function were explored that involved in the actions of HLJDD on cerebral ischemia. HLJDD achieves therapeutic action on cerebral ischemia via coordinating the basic pathophysiological network of metabolic stress, glutamate metabolism, and acetylcholine levels and function. Copyright © 2018 Elsevier B.V. All rights reserved.
A genome-scale metabolic reconstruction of Pseudomonas putida KT2440: iJN746 as a cell factory.
Nogales, Juan; Palsson, Bernhard Ø; Thiele, Ines
2008-09-16
Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in bioremediation and bioplastic production.
Targeted metabolomics and medication classification data from participants in the ADNI1 cohort.
St John-Williams, Lisa; Blach, Colette; Toledo, Jon B; Rotroff, Daniel M; Kim, Sungeun; Klavins, Kristaps; Baillie, Rebecca; Han, Xianlin; Mahmoudiandehkordi, Siamak; Jack, John; Massaro, Tyler J; Lucas, Joseph E; Louie, Gregory; Motsinger-Reif, Alison A; Risacher, Shannon L; Saykin, Andrew J; Kastenmüller, Gabi; Arnold, Matthias; Koal, Therese; Moseley, M Arthur; Mangravite, Lara M; Peters, Mette A; Tenenbaum, Jessica D; Thompson, J Will; Kaddurah-Daouk, Rima
2017-10-17
Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions
2010-01-01
Background Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. Description We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. Conclusions BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu. PMID:20426874
Targeted metabolomics and medication classification data from participants in the ADNI1 cohort
St John-Williams, Lisa; Blach, Colette; Toledo, Jon B.; Rotroff, Daniel M.; Kim, Sungeun; Klavins, Kristaps; Baillie, Rebecca; Han, Xianlin; Mahmoudiandehkordi, Siamak; Jack, John; Massaro, Tyler J.; Lucas, Joseph E.; Louie, Gregory; Motsinger-Reif, Alison A.; Risacher, Shannon L.; Saykin, Andrew J.; Kastenmüller, Gabi; Arnold, Matthias; Koal, Therese; Moseley, M. Arthur; Mangravite, Lara M.; Peters, Mette A.; Tenenbaum, Jessica D.; Thompson, J. Will; Kaddurah-Daouk, Rima
2017-01-01
Alzheimer’s disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes. PMID:29039849
Seaver, Samuel M. D.; Gerdes, Svetlana; Frelin, Océane; Lerma-Ortiz, Claudia; Bradbury, Louis M. T.; Zallot, Rémi; Hasnain, Ghulam; Niehaus, Thomas D.; El Yacoubi, Basma; Pasternak, Shiran; Olson, Robert; Pusch, Gordon; Overbeek, Ross; Stevens, Rick; de Crécy-Lagard, Valérie; Ware, Doreen; Hanson, Andrew D.; Henry, Christopher S.
2014-01-01
The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today’s annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed. PMID:24927599
Seaver, Samuel M D; Gerdes, Svetlana; Frelin, Océane; Lerma-Ortiz, Claudia; Bradbury, Louis M T; Zallot, Rémi; Hasnain, Ghulam; Niehaus, Thomas D; El Yacoubi, Basma; Pasternak, Shiran; Olson, Robert; Pusch, Gordon; Overbeek, Ross; Stevens, Rick; de Crécy-Lagard, Valérie; Ware, Doreen; Hanson, Andrew D; Henry, Christopher S
2014-07-01
The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. To overcome these problems, we have developed the PlantSEED, an integrated, metabolism-centric database to support subsystems-based annotation and metabolic model reconstruction for plant genomes. PlantSEED combines SEED subsystems technology, first developed for microbial genomes, with refined protein families and biochemical data to assign fully consistent functional annotations to orthologous genes, particularly those encoding primary metabolic pathways. Seamless integration with its parent, the prokaryotic SEED database, makes PlantSEED a unique environment for cross-kingdom comparative analysis of plant and bacterial genomes. The consistent annotations imposed by PlantSEED permit rapid reconstruction and modeling of primary metabolism for all plant genomes in the database. This feature opens the unique possibility of model-based assessment of the completeness and accuracy of gene annotation and thus allows computational identification of genes and pathways that are restricted to certain genomes or need better curation. We demonstrate the PlantSEED system by producing consistent annotations for 10 reference genomes. We also produce a functioning metabolic model for each genome, gapfilling to identify missing annotations and proposing gene candidates for missing annotations. Models are built around an extended biomass composition representing the most comprehensive published to date. To our knowledge, our models are the first to be published for seven of the genomes analyzed.
Hsiao, Yu-Yun; Tsai, Wen-Chieh; Kuoh, Chang-Sheng; Huang, Tian-Hsiang; Wang, Hei-Chia; Wu, Tian-Shung; Leu, Yann-Lii; Chen, Wen-Huei; Chen, Hong-Hwa
2006-07-13
Floral scent is one of the important strategies for ensuring fertilization and for determining seed or fruit set. Research on plant scents has hampered mainly by the invisibility of this character, its dynamic nature, and complex mixtures of components that are present in very small quantities. Most progress in scent research, as in other areas of plant biology, has come from the use of molecular and biochemical techniques. Although volatile components have been identified in several orchid species, the biosynthetic pathways of orchid flower fragrance are far from understood. We investigated how flower fragrance was generated in certain Phalaenopsis orchids by determining the chemical components of the floral scent, identifying floral expressed-sequence-tags (ESTs), and deducing the pathways of floral scent biosynthesis in Phalaneopsis bellina by bioinformatics analysis. The main chemical components in the P. bellina flower were shown by gas chromatography-mass spectrometry to be monoterpenoids, benzenoids and phenylpropanoids. The set of floral scent producing enzymes in the biosynthetic pathway from glyceraldehyde-3-phosphate (G3P) to geraniol and linalool were recognized through data mining of the P. bellina floral EST database (dbEST). Transcripts preferentially expressed in P. bellina were distinguished by comparing the scent floral dbEST to that of a scentless species, P. equestris, and included those encoding lipoxygenase, epimerase, diacylglycerol kinase and geranyl diphosphate synthase. In addition, EST filtering results showed that transcripts encoding signal transduction and Myb transcription factors and methyltransferase, in addition to those for scent biosynthesis, were detected by in silico hybridization of the P. bellina unigene database against those of the scentless species, rice and Arabidopsis. Altogether, we pinpointed 66% of the biosynthetic steps from G3P to geraniol, linalool and their derivatives. This systems biology program combined chemical analysis, genomics and bioinformatics to elucidate the scent biosynthesis pathway and identify the relevant genes. It integrates the forward and reverse genetic approaches to knowledge discovery by which researchers can study non-model plants.
Lamba, Sanjay; Bera, Soumen; Rashid, Mubasher; Medvinsky, Alexander B.; Acquisti, Claudia; Li, Bai-Lian
2017-01-01
Nitrogen is cycled throughout ecosystems by a suite of biogeochemical processes. The high complexity of the nitrogen cycle resides in an intricate interplay between reversible biochemical pathways alternatively and specifically activated in response to diverse environmental cues. Despite aggressive research, how the fundamental nitrogen biochemical processes are assembled and maintained in fluctuating soil redox conditions remains elusive. Here, we address this question using a kinetic modelling approach coupled with dynamical systems theory and microbial genomics. We show that alternative biochemical pathways play a key role in keeping nitrogen conversion and conservation properties invariant in fluctuating environments. Our results indicate that the biochemical network holds inherent adaptive capacity to stabilize ammonium and nitrate availability, and that the bistability in the formation of ammonium is linked to the transient upregulation of the amo-hao mediated nitrification pathway. The bistability is maintained by a pair of complementary subsystems acting as either source or sink type systems in response to soil redox fluctuations. It is further shown how elevated anthropogenic pressure has the potential to break down the stability of the system, altering substantially ammonium and nitrate availability in the soil, with dramatic effects on biodiversity. PMID:28280580
Computational multiscale modeling in protein--ligand docking.
Taufer, Michela; Armen, Roger; Chen, Jianhan; Teller, Patricia; Brooks, Charles
2009-01-01
In biological systems, the binding of small molecule ligands to proteins is a crucial process for almost every aspect of biochemistry and molecular biology. Enzymes are proteins that function by catalyzing specific biochemical reactions that convert reactants into products. Complex organisms are typically composed of cells in which thousands of enzymes participate in complex and interconnected biochemical pathways. Some enzymes serve as sequential steps in specific pathways (such as energy metabolism), while others function to regulate entire pathways and cellular functions [1]. Small molecule ligands can be designed to bind to a specific enzyme and inhibit the biochemical reaction. Inhibiting the activity of key enzymes may result in the entire biochemical pathways being turned on or off [2], [3]. Many small molecule drugs marketed today function in this generic way as enzyme inhibitors. If research identifies a specific enzyme as being crucial to the progress of disease, then this enzyme may be targeted with an inhibitor, which may slow down or reverse the progress of disease. In this way, enzymes are targeted from specific pathogens (e.g., virus, bacteria, fungi) for infectious diseases [4], [5], and human enzymes are targeted for noninfectious diseases such as cardiovascular disease, cancer, diabetes, and neurodegenerative diseases [6].
Tracing the Repertoire of Promiscuous Enzymes along the Metabolic Pathways in Archaeal Organisms.
Martínez-Núñez, Mario Alberto; Rodríguez-Escamilla, Zuemy; Rodríguez-Vázquez, Katya; Pérez-Rueda, Ernesto
2017-07-13
The metabolic pathways that carry out the biochemical transformations sustaining life depend on the efficiency of their associated enzymes. In recent years, it has become clear that promiscuous enzymes have played an important role in the function and evolution of metabolism. In this work we analyze the repertoire of promiscuous enzymes in 89 non-redundant genomes of the Archaea cellular domain. Promiscuous enzymes are defined as those proteins with two or more different Enzyme Commission (E.C.) numbers, according the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. From this analysis, it was found that the fraction of promiscuous enzymes is lower in Archaea than in Bacteria. A greater diversity of superfamily domains is associated with promiscuous enzymes compared to specialized enzymes, both in Archaea and Bacteria, and there is an enrichment of substrate promiscuity rather than catalytic promiscuity in the archaeal enzymes. Finally, the presence of promiscuous enzymes in the metabolic pathways was found to be heterogeneously distributed at the domain level and in the phyla that make up the Archaea. These analyses increase our understanding of promiscuous enzymes and provide additional clues to the evolution of metabolism in Archaea.
Wei, Jiankai; Zhang, Xiaojun; Yu, Yang; Huang, Hao; Li, Fuhua; Xiang, Jianhai
2014-01-01
Penaeid shrimp has a distinctive metamorphosis stage during early development. Although morphological and biochemical studies about this ontogeny have been developed for decades, researches on gene expression level are still scarce. In this study, we have investigated the transcriptomes of five continuous developmental stages in Pacific white shrimp (Litopenaeus vannamei) with high throughput Illumina sequencing technology. The reads were assembled and clustered into 66,815 unigenes, of which 32,398 have putative homologues in nr database, 14,981 have been classified into diverse functional categories by Gene Ontology (GO) annotation and 26,257 have been associated with 255 pathways by KEGG pathway mapping. Meanwhile, the differentially expressed genes (DEGs) between adjacent developmental stages were identified and gene expression patterns were clustered. By GO term enrichment analysis, KEGG pathway enrichment analysis and functional gene profiling, the physiological changes during shrimp metamorphosis could be better understood, especially histogenesis, diet transition, muscle development and exoskeleton reconstruction. In conclusion, this is the first study that characterized the integrated transcriptomic profiles during early development of penaeid shrimp, and these findings will serve as significant references for shrimp developmental biology and aquaculture research. PMID:25197823
acetaldehyde from bacteria. The idea was to short-sheet the ethanol fermentation pathway to produce ; Biochem. (1995) "Fermentation strategies: Acetaldehyde or ethanol?," Process Biochem. (1987
Identification of Enzyme Genes Using Chemical Structure Alignments of Substrate-Product Pairs.
Moriya, Yuki; Yamada, Takuji; Okuda, Shujiro; Nakagawa, Zenichi; Kotera, Masaaki; Tokimatsu, Toshiaki; Kanehisa, Minoru; Goto, Susumu
2016-03-28
Although there are several databases that contain data on many metabolites and reactions in biochemical pathways, there is still a big gap in the numbers between experimentally identified enzymes and metabolites. It is supposed that many catalytic enzyme genes are still unknown. Although there are previous studies that estimate the number of candidate enzyme genes, these studies required some additional information aside from the structures of metabolites such as gene expression and order in the genome. In this study, we developed a novel method to identify a candidate enzyme gene of a reaction using the chemical structures of the substrate-product pair (reactant pair). The proposed method is based on a search for similar reactant pairs in a reference database and offers ortholog groups that possibly mediate the given reaction. We applied the proposed method to two experimentally validated reactions. As a result, we confirmed that the histidine transaminase was correctly identified. Although our method could not directly identify the asparagine oxo-acid transaminase, we successfully found the paralog gene most similar to the correct enzyme gene. We also applied our method to infer candidate enzyme genes in the mesaconate pathway. The advantage of our method lies in the prediction of possible genes for orphan enzyme reactions where any associated gene sequences are not determined yet. We believe that this approach will facilitate experimental identification of genes for orphan enzymes.
Drug-Path: a database for drug-induced pathways.
Zeng, Hui; Qiu, Chengxiang; Cui, Qinghua
2015-01-01
Some databases for drug-associated pathways have been built and are publicly available. However, the pathways curated in most of these databases are drug-action or drug-metabolism pathways. In recent years, high-throughput technologies such as microarray and RNA-sequencing have produced lots of drug-induced gene expression profiles. Interestingly, drug-induced gene expression profile frequently show distinct patterns, indicating that drugs normally induce the activation or repression of distinct pathways. Therefore, these pathways contribute to study the mechanisms of drugs and drug-repurposing. Here, we present Drug-Path, a database of drug-induced pathways, which was generated by KEGG pathway enrichment analysis for drug-induced upregulated genes and downregulated genes based on drug-induced gene expression datasets in Connectivity Map. Drug-Path provides user-friendly interfaces to retrieve, visualize and download the drug-induced pathway data in the database. In addition, the genes deregulated by a given drug are highlighted in the pathways. All data were organized using SQLite. The web site was implemented using Django, a Python web framework. Finally, we believe that this database will be useful for related researches. © The Author(s) 2015. Published by Oxford University Press.
Atkinson, Joshua T; Campbell, Ian; Bennett, George N; Silberg, Jonathan J
2016-12-27
The ferredoxin (Fd) protein family is a structurally diverse group of iron-sulfur proteins that function as electron carriers, linking biochemical pathways important for energy transduction, nutrient assimilation, and primary metabolism. While considerable biochemical information about individual Fd protein electron carriers and their reactions has been acquired, we cannot yet anticipate the proportion of electrons shuttled between different Fd-partner proteins within cells using biochemical parameters that govern electron flow, such as holo-Fd concentration, midpoint potential (driving force), molecular interactions (affinity and kinetics), conformational changes (allostery), and off-pathway electron leakage (chemical oxidation). Herein, we describe functional and structural gaps in our Fd knowledge within the context of a sequence similarity network and phylogenetic tree, and we propose a strategy for improving our understanding of Fd sequence-function relationships. We suggest comparing the functions of divergent Fds within cells whose growth, or other measurable output, requires electron transfer between defined electron donor and acceptor proteins. By comparing Fd-mediated electron transfer with biochemical parameters that govern electron flow, we posit that models that anticipate energy flow across Fd interactomes can be built. This approach is expected to transform our ability to anticipate Fd control over electron flow in cellular settings, an obstacle to the construction of synthetic electron transfer pathways and rational optimization of existing energy-conserving pathways.
Toward the automated generation of genome-scale metabolic networks in the SEED.
DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron
2007-04-26
Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.
WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.
Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L
2018-01-04
WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Zhang, Peifen; Dreher, Kate; Karthikeyan, A.; Chi, Anjo; Pujar, Anuradha; Caspi, Ron; Karp, Peter; Kirkup, Vanessa; Latendresse, Mario; Lee, Cynthia; Mueller, Lukas A.; Muller, Robert; Rhee, Seung Yon
2010-01-01
Metabolic networks reconstructed from sequenced genomes or transcriptomes can help visualize and analyze large-scale experimental data, predict metabolic phenotypes, discover enzymes, engineer metabolic pathways, and study metabolic pathway evolution. We developed a general approach for reconstructing metabolic pathway complements of plant genomes. Two new reference databases were created and added to the core of the infrastructure: a comprehensive, all-plant reference pathway database, PlantCyc, and a reference enzyme sequence database, RESD, for annotating metabolic functions of protein sequences. PlantCyc (version 3.0) includes 714 metabolic pathways and 2,619 reactions from over 300 species. RESD (version 1.0) contains 14,187 literature-supported enzyme sequences from across all kingdoms. We used RESD, PlantCyc, and MetaCyc (an all-species reference metabolic pathway database), in conjunction with the pathway prediction software Pathway Tools, to reconstruct a metabolic pathway database, PoplarCyc, from the recently sequenced genome of Populus trichocarpa. PoplarCyc (version 1.0) contains 321 pathways with 1,807 assigned enzymes. Comparing PoplarCyc (version 1.0) with AraCyc (version 6.0, Arabidopsis [Arabidopsis thaliana]) showed comparable numbers of pathways distributed across all domains of metabolism in both databases, except for a higher number of AraCyc pathways in secondary metabolism and a 1.5-fold increase in carbohydrate metabolic enzymes in PoplarCyc. Here, we introduce these new resources and demonstrate the feasibility of using them to identify candidate enzymes for specific pathways and to analyze metabolite profiling data through concrete examples. These resources can be searched by text or BLAST, browsed, and downloaded from our project Web site (http://plantcyc.org). PMID:20522724
Roy Choudhury, Swarup; Wang, Yuqi; Pandey, Sona
2014-07-01
Signalling pathways mediated by heterotrimeric G-proteins are common to all eukaryotes. Plants have a limited number of each of the G-protein subunits, with the most elaborate G-protein network discovered so far in soya bean (Glycine max, also known as soybean) which has four Gα, four Gβ and ten Gγ proteins. Biochemical characterization of Gα proteins from plants suggests significant variation in their properties compared with the well-characterized non-plant proteins. Furthermore, the four soya bean Gα (GmGα) proteins exhibit distinct biochemical activities among themselves, but the extent to which such biochemical differences contribute to their in vivo function is also not known. We used the yeast gpa1 mutant which displays constitutive signalling and growth arrest in the pheromone-response pathway as an in vivo model to evaluate the effect of distinct biochemical activities of GmGα proteins. We showed that specific GmGα proteins can be activated during pheromone-dependent receptor-mediated signalling in yeast and they display different strengths towards complementation of yeast gpa1 phenotypes. We also identified amino acids that are responsible for differential complementation abilities of specific Gα proteins. These data establish that specific plant Gα proteins are functional in the receptor-mediated pheromone-response pathway in yeast and that the subtle biochemical differences in their activity are physiologically relevant.
Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome.
Bowman, John L; Kohchi, Takayuki; Yamato, Katsuyuki T; Jenkins, Jerry; Shu, Shengqiang; Ishizaki, Kimitsune; Yamaoka, Shohei; Nishihama, Ryuichi; Nakamura, Yasukazu; Berger, Frédéric; Adam, Catherine; Aki, Shiori Sugamata; Althoff, Felix; Araki, Takashi; Arteaga-Vazquez, Mario A; Balasubrmanian, Sureshkumar; Barry, Kerrie; Bauer, Diane; Boehm, Christian R; Briginshaw, Liam; Caballero-Perez, Juan; Catarino, Bruno; Chen, Feng; Chiyoda, Shota; Chovatia, Mansi; Davies, Kevin M; Delmans, Mihails; Demura, Taku; Dierschke, Tom; Dolan, Liam; Dorantes-Acosta, Ana E; Eklund, D Magnus; Florent, Stevie N; Flores-Sandoval, Eduardo; Fujiyama, Asao; Fukuzawa, Hideya; Galik, Bence; Grimanelli, Daniel; Grimwood, Jane; Grossniklaus, Ueli; Hamada, Takahiro; Haseloff, Jim; Hetherington, Alexander J; Higo, Asuka; Hirakawa, Yuki; Hundley, Hope N; Ikeda, Yoko; Inoue, Keisuke; Inoue, Shin-Ichiro; Ishida, Sakiko; Jia, Qidong; Kakita, Mitsuru; Kanazawa, Takehiko; Kawai, Yosuke; Kawashima, Tomokazu; Kennedy, Megan; Kinose, Keita; Kinoshita, Toshinori; Kohara, Yuji; Koide, Eri; Komatsu, Kenji; Kopischke, Sarah; Kubo, Minoru; Kyozuka, Junko; Lagercrantz, Ulf; Lin, Shih-Shun; Lindquist, Erika; Lipzen, Anna M; Lu, Chia-Wei; De Luna, Efraín; Martienssen, Robert A; Minamino, Naoki; Mizutani, Masaharu; Mizutani, Miya; Mochizuki, Nobuyoshi; Monte, Isabel; Mosher, Rebecca; Nagasaki, Hideki; Nakagami, Hirofumi; Naramoto, Satoshi; Nishitani, Kazuhiko; Ohtani, Misato; Okamoto, Takashi; Okumura, Masaki; Phillips, Jeremy; Pollak, Bernardo; Reinders, Anke; Rövekamp, Moritz; Sano, Ryosuke; Sawa, Shinichiro; Schmid, Marc W; Shirakawa, Makoto; Solano, Roberto; Spunde, Alexander; Suetsugu, Noriyuki; Sugano, Sumio; Sugiyama, Akifumi; Sun, Rui; Suzuki, Yutaka; Takenaka, Mizuki; Takezawa, Daisuke; Tomogane, Hirokazu; Tsuzuki, Masayuki; Ueda, Takashi; Umeda, Masaaki; Ward, John M; Watanabe, Yuichiro; Yazaki, Kazufumi; Yokoyama, Ryusuke; Yoshitake, Yoshihiro; Yotsui, Izumi; Zachgo, Sabine; Schmutz, Jeremy
2017-10-05
The evolution of land flora transformed the terrestrial environment. Land plants evolved from an ancestral charophycean alga from which they inherited developmental, biochemical, and cell biological attributes. Additional biochemical and physiological adaptations to land, and a life cycle with an alternation between multicellular haploid and diploid generations that facilitated efficient dispersal of desiccation tolerant spores, evolved in the ancestral land plant. We analyzed the genome of the liverwort Marchantia polymorpha, a member of a basal land plant lineage. Relative to charophycean algae, land plant genomes are characterized by genes encoding novel biochemical pathways, new phytohormone signaling pathways (notably auxin), expanded repertoires of signaling pathways, and increased diversity in some transcription factor families. Compared with other sequenced land plants, M. polymorpha exhibits low genetic redundancy in most regulatory pathways, with this portion of its genome resembling that predicted for the ancestral land plant. PAPERCLIP. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
Walking the C4 pathway: past, present, and future.
Furbank, Robert T
2017-01-01
The year 2016 marks 50 years since the publication of the seminal paper by Hatch and Slack describing the biochemical pathway we now know as C 4 photosynthesis. This review provides insight into the initial discovery of this pathway, the clues which led Hatch and Slack and others to these definitive experiments, some of the intrigue which surrounds the international activities which led up to the discovery, and personal insights into the future of this research field. While the biochemical understanding of the basic pathways came quickly, the role of the bundle sheath intermediate CO 2 pool was not understood for a number of years, and the nature of C 4 as a biochemical CO 2 pump then linked the unique Kranz anatomy of C 4 plants to their biochemical specialization. Decades of "grind and find biochemistry" and leaf physiology fleshed out the regulation of the pathway and the differences in physiological response to the environment between C 3 and C 4 plants. The more recent advent of plant transformation then high-throughput RNA and DNA sequencing and synthetic biology has allowed us both to carry out biochemical experiments and test hypotheses in planta and to better understand the evolution-driven molecular and genetic changes which occurred in the genomes of plants in the transition from C 3 to C 4 Now we are using this knowledge in attempts to engineer C 4 rice and improve the C 4 engine itself for enhanced food security and to provide novel biofuel feedstocks. The next 50 years of photosynthesis will no doubt be challenging, stimulating, and a drawcard for the best young minds in plant biology. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Walking the C4 pathway: past, present, and future.
Furbank, Robert T
2016-07-01
The year 2016 marks 50 years since the publication of the seminal paper by Hatch and Slack describing the biochemical pathway we now know as C4 photosynthesis. This review provides insight into the initial discovery of this pathway, the clues which led Hatch and Slack and others to these definitive experiments, some of the intrigue which surrounds the international activities which led up to the discovery, and personal insights into the future of this research field. While the biochemical understanding of the basic pathways came quickly, the role of the bundle sheath intermediate CO2 pool was not understood for a number of years, and the nature of C4 as a biochemical CO2 pump then linked the unique Kranz anatomy of C4 plants to their biochemical specialization. Decades of "grind and find biochemistry" and leaf physiology fleshed out the regulation of the pathway and the differences in physiological response to the environment between C3 and C4 plants. The more recent advent of plant transformation then high-throughput RNA and DNA sequencing and synthetic biology has allowed us both to carry out biochemical experiments and test hypotheses in planta and to better understand the evolution-driven molecular and genetic changes which occurred in the genomes of plants in the transition from C3 to C4 Now we are using this knowledge in attempts to engineer C4 rice and improve the C4 engine itself for enhanced food security and to provide novel biofuel feedstocks. The next 50 years of photosynthesis will no doubt be challenging, stimulating, and a drawcard for the best young minds in plant biology. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Application of the ToxMiner Database: Network Analysis of ...
The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that tar
Application of the ToxMiner Database: Network Analysis ...
The US EPA ToxCast program is using in vitro HTS (High-Throughput Screening) methods to profile and model bioactivity of environmental chemicals. The main goals of the ToxCast program are to generate predictive signatures of toxicity, and ultimately provide rapid and cost-effective alternatives to animal testing. The chemicals selected for Phase I are composed largely by a diverse set of pesticide active ingredients, which had sufficient supporting in vivo data included as part of their registration process with the EPA. Other miscellaneous chemicals of environmental concern were also included. Application of HTS to environmental toxicants is a novel approach to predictive toxicology and health risk assessment, and differs from what is required for drug efficacy screening in that biochemical interaction of environmental chemicals are sometimes weaker than that seen with drugs and their intended targets. Additionally, the chemical space covered by environmental chemicals is much broader compared to that of pharmaceuticals. The ToxMiner database has been created and added to the EPA’s ACToR (Aggregated Computational Toxicology Resource) chemical database. One purpose of the ToxMiner database is to link biological, metabolic, and cellular pathway data to genes and in vitro assay data for the initial subset of chemicals screened in the ToxCast Phase I HTS assays. Also included in ToxMiner is human disease information, which correlates with ToxCast assays that ta
Seasonal induction of alternative principal pathway for rose flower scent
Hirata, Hiroshi; Ohnishi, Toshiyuki; Tomida, Kensuke; Ishida, Haruka; Kanda, Momoyo; Sakai, Miwa; Yoshimura, Jin; Suzuki, Hideyuki; Ishikawa, Takamasa; Dohra, Hideo; Watanabe, Naoharu
2016-01-01
Ecological adaptations to seasonal changes are often observed in the phenotypic traits of plants and animals, and these adaptations are usually expressed through the production of different biochemical end products. In this study, ecological adaptations are observed in a biochemical pathway without alteration of the end products. We present an alternative principal pathway to the characteristic floral scent compound 2-phenylethanol (2PE) in roses. The new pathway is seasonally induced in summer as a heat adaptation that uses rose phenylpyruvate decarboxylase (RyPPDC) as a novel enzyme. RyPPDC transcript levels and the resulting production of 2PE are increased time-dependently under high temperatures. The novel summer pathway produces levels of 2PE that are several orders of magnitude higher than those produced by the previously known pathway. Our results indicate that the alternative principal pathway identified here is a seasonal adaptation for managing the weakened volatility of summer roses. PMID:26831950
eQuilibrator--the biochemical thermodynamics calculator.
Flamholz, Avi; Noor, Elad; Bar-Even, Arren; Milo, Ron
2012-01-01
The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like 'how much Gibbs energy is released by ATP hydrolysis at pH 5?' are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use.
eQuilibrator—the biochemical thermodynamics calculator
Flamholz, Avi; Noor, Elad; Bar-Even, Arren; Milo, Ron
2012-01-01
The laws of thermodynamics constrain the action of biochemical systems. However, thermodynamic data on biochemical compounds can be difficult to find and is cumbersome to perform calculations with manually. Even simple thermodynamic questions like ‘how much Gibbs energy is released by ATP hydrolysis at pH 5?’ are complicated excessively by the search for accurate data. To address this problem, eQuilibrator couples a comprehensive and accurate database of thermodynamic properties of biochemical compounds and reactions with a simple and powerful online search and calculation interface. The web interface to eQuilibrator (http://equilibrator.weizmann.ac.il) enables easy calculation of Gibbs energies of compounds and reactions given arbitrary pH, ionic strength and metabolite concentrations. The eQuilibrator code is open-source and all thermodynamic source data are freely downloadable in standard formats. Here we describe the database characteristics and implementation and demonstrate its use. PMID:22064852
Exploitation of Nontraditional Corp, Yacon, in Breast Cancer Prevention Using Preclinical Rat Model
2011-07-01
liver glucose disposal evident along sorbitol, PPP, and hexosamine pathways. • Gut microbiome : A significant impact of diet on levels of...biochemicals reflecting metabolism of the gut microbiome was evident in plasma and liver and observed for several classes of metabolites. Biochemicals...acid metabolites reflecting activity of the gut microbiome contribute to host metabolic pathways and/or must be metabolized further by the liver
Vivar, Juan C; Pemu, Priscilla; McPherson, Ruth; Ghosh, Sujoy
2013-08-01
Abstract Unparalleled technological advances have fueled an explosive growth in the scope and scale of biological data and have propelled life sciences into the realm of "Big Data" that cannot be managed or analyzed by conventional approaches. Big Data in the life sciences are driven primarily via a diverse collection of 'omics'-based technologies, including genomics, proteomics, metabolomics, transcriptomics, metagenomics, and lipidomics. Gene-set enrichment analysis is a powerful approach for interrogating large 'omics' datasets, leading to the identification of biological mechanisms associated with observed outcomes. While several factors influence the results from such analysis, the impact from the contents of pathway databases is often under-appreciated. Pathway databases often contain variously named pathways that overlap with one another to varying degrees. Ignoring such redundancies during pathway analysis can lead to the designation of several pathways as being significant due to high content-similarity, rather than truly independent biological mechanisms. Statistically, such dependencies also result in correlated p values and overdispersion, leading to biased results. We investigated the level of redundancies in multiple pathway databases and observed large discrepancies in the nature and extent of pathway overlap. This prompted us to develop the application, ReCiPa (Redundancy Control in Pathway Databases), to control redundancies in pathway databases based on user-defined thresholds. Analysis of genomic and genetic datasets, using ReCiPa-generated overlap-controlled versions of KEGG and Reactome pathways, led to a reduction in redundancy among the top-scoring gene-sets and allowed for the inclusion of additional gene-sets representing possibly novel biological mechanisms. Using obesity as an example, bioinformatic analysis further demonstrated that gene-sets identified from overlap-controlled pathway databases show stronger evidence of prior association to obesity compared to pathways identified from the original databases.
Liu, Jingjing; Yin, Tongming; Ye, Ning; Chen, Yingnan; Yin, Tingting; Liu, Min; Hassani, Danial
2013-01-01
Background The dioecious system is relatively rare in plants. Shrub willow is an annual flowering dioecious woody plant, and possesses many characteristics that lend it as a great model for tracking the missing pieces of sex determination evolution. To gain a global view of the genes differentially expressed in the male and female shrub willows and to develop a database for further studies, we performed a large-scale transcriptome sequencing of flower buds which were separately collected from two types of sexes. Results Totally, 1,201,931 high quality reads were obtained, with an average length of 389 bp and a total length of 467.96 Mb. The ESTs were assembled into 29,048 contigs, and 132,709 singletons. These unigenes were further functionally annotated by comparing their sequences to different proteins and functional domain databases and assigned with Gene Ontology (GO) terms. A biochemical pathway database containing 291 predicted pathways was also created based on the annotations of the unigenes. Digital expression analysis identified 806 differentially expressed genes between the male and female flower buds. And 33 of them located on the incipient sex chromosome of Salicaceae, among which, 12 genes might involve in plant sex determination empirically. These genes were worthy of special notification in future studies. Conclusions In this study, a large number of EST sequences were generated from the flower buds of a male and a female shrub willow. We also reported the differentially expressed genes between the two sex-type flowers. This work provides valuable information and sequence resources for uncovering the sex determining genes and for future functional genomics analysis of Salicaceae spp. PMID:23560075
Doss, C George Priya; Chakrabarty, Chiranjib; Debajyoti, C; Debottam, S
2014-11-01
Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.
AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database.
The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful AOP-DB user interface in...
AOP-DB Frontend: A user interface for the Adverse Outcome Pathways Database
The EPA Adverse Outcome Pathway Database (AOP-DB) is a database resource that aggregates association relationships between AOPs, genes, chemicals, diseases, pathways, species orthology information, ontologies. The AOP-DB frontend is a simple yet powerful user interface in the for...
Góngora-Castillo, Elsa; Childs, Kevin L.; Fedewa, Greg; Hamilton, John P.; Liscombe, David K.; Magallanes-Lundback, Maria; Mandadi, Kranthi K.; Nims, Ezekiel; Runguphan, Weerawat; Vaillancourt, Brieanne; Varbanova-Herde, Marina; DellaPenna, Dean; McKnight, Thomas D.; O’Connor, Sarah; Buell, C. Robin
2012-01-01
The natural diversity of plant metabolism has long been a source for human medicines. One group of plant-derived compounds, the monoterpene indole alkaloids (MIAs), includes well-documented therapeutic agents used in the treatment of cancer (vinblastine, vincristine, camptothecin), hypertension (reserpine, ajmalicine), malaria (quinine), and as analgesics (7-hydroxymitragynine). Our understanding of the biochemical pathways that synthesize these commercially relevant compounds is incomplete due in part to a lack of molecular, genetic, and genomic resources for the identification of the genes involved in these specialized metabolic pathways. To address these limitations, we generated large-scale transcriptome sequence and expression profiles for three species of Asterids that produce medicinally important MIAs: Camptotheca acuminata, Catharanthus roseus, and Rauvolfia serpentina. Using next generation sequencing technology, we sampled the transcriptomes of these species across a diverse set of developmental tissues, and in the case of C. roseus, in cultured cells and roots following elicitor treatment. Through an iterative assembly process, we generated robust transcriptome assemblies for all three species with a substantial number of the assembled transcripts being full or near-full length. The majority of transcripts had a related sequence in either UniRef100, the Arabidopsis thaliana predicted proteome, or the Pfam protein domain database; however, we also identified transcripts that lacked similarity with entries in either database and thereby lack a known function. Representation of known genes within the MIA biosynthetic pathway was robust. As a diverse set of tissues and treatments were surveyed, expression abundances of transcripts in the three species could be estimated to reveal transcripts associated with development and response to elicitor treatment. Together, these transcriptomes and expression abundance matrices provide a rich resource for understanding plant specialized metabolism, and promotes realization of innovative production systems for plant-derived pharmaceuticals. PMID:23300689
The usefulness of ozone treatment in spinal pain
Bocci, Velio; Borrelli, Emma; Zanardi, Iacopo; Travagli, Valter
2015-01-01
Objective The aim of this review is to elucidate the biochemical, molecular, immunological, and pharmaceutical mechanisms of action of ozone dissolved in biological fluids. Studies performed during the last two decades allow the drawing of a comprehensive framework for understanding and recommending the integration of ozone therapy for spinal pain. Methods An in-depth screening of primary sources of information online – via SciFinder Scholar, Google Scholar, and Scopus databases as well as Embase, PubMed, and the Cochrane Database of Systemic Reviews – was performed. In this review, the most significant papers of the last 25 years are presented and their proposals critically evaluated, regardless of the bibliometric impact of the journals. Results The efficacy of standard treatments combined with the unique capacity of ozone therapy to reactivate the innate antioxidant system is the key to correcting the oxidative stress typical of chronic inflammatory diseases. Pain pathways and control systems of algesic signals after ozone administration are described. Conclusion This paper finds favors the full insertion of ozone therapy into pharmaceutical sciences, rather than as either an alternative or an esoteric approach. PMID:26028964
Validation of RetroPath, a computer-aided design tool for metabolic pathway engineering.
Fehér, Tamás; Planson, Anne-Gaëlle; Carbonell, Pablo; Fernández-Castané, Alfred; Grigoras, Ioana; Dariy, Ekaterina; Perret, Alain; Faulon, Jean-Loup
2014-11-01
Metabolic engineering has succeeded in biosynthesis of numerous commodity or high value compounds. However, the choice of pathways and enzymes used for production was many times made ad hoc, or required expert knowledge of the specific biochemical reactions. In order to rationalize the process of engineering producer strains, we developed the computer-aided design (CAD) tool RetroPath that explores and enumerates metabolic pathways connecting the endogenous metabolites of a chassis cell to the target compound. To experimentally validate our tool, we constructed 12 top-ranked enzyme combinations producing the flavonoid pinocembrin, four of which displayed significant yields. Namely, our tool queried the enzymes found in metabolic databases based on their annotated and predicted activities. Next, it ranked pathways based on the predicted efficiency of the available enzymes, the toxicity of the intermediate metabolites and the calculated maximum product flux. To implement the top-ranking pathway, our procedure narrowed down a list of nine million possible enzyme combinations to 12, a number easily assembled and tested. One round of metabolic network optimization based on RetroPath output further increased pinocembrin titers 17-fold. In total, 12 out of the 13 enzymes tested in this work displayed a relative performance that was in accordance with its predicted score. These results validate the ranking function of our CAD tool, and open the way to its utilization in the biosynthesis of novel compounds. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
SABIO-RK: an updated resource for manually curated biochemical reaction kinetics
Rey, Maja; Weidemann, Andreas; Kania, Renate; Müller, Wolfgang
2018-01-01
Abstract SABIO-RK (http://sabiork.h-its.org/) is a manually curated database containing data about biochemical reactions and their reaction kinetics. The data are primarily extracted from scientific literature and stored in a relational database. The content comprises both naturally occurring and alternatively measured biochemical reactions and is not restricted to any organism class. The data are made available to the public by a web-based search interface and by web services for programmatic access. In this update we describe major improvements and extensions of SABIO-RK since our last publication in the database issue of Nucleic Acid Research (2012). (i) The website has been completely revised and (ii) allows now also free text search for kinetics data. (iii) Additional interlinkages with other databases in our field have been established; this enables users to gain directly comprehensive knowledge about the properties of enzymes and kinetics beyond SABIO-RK. (iv) Vice versa, direct access to SABIO-RK data has been implemented in several systems biology tools and workflows. (v) On request of our experimental users, the data can be exported now additionally in spreadsheet formats. (vi) The newly established SABIO-RK Curation Service allows to respond to specific data requirements. PMID:29092055
Simulation of a Petri net-based model of the terpenoid biosynthesis pathway.
Hawari, Aliah Hazmah; Mohamed-Hussein, Zeti-Azura
2010-02-09
The development and simulation of dynamic models of terpenoid biosynthesis has yielded a systems perspective that provides new insights into how the structure of this biochemical pathway affects compound synthesis. These insights may eventually help identify reactions that could be experimentally manipulated to amplify terpenoid production. In this study, a dynamic model of the terpenoid biosynthesis pathway was constructed based on the Hybrid Functional Petri Net (HFPN) technique. This technique is a fusion of three other extended Petri net techniques, namely Hybrid Petri Net (HPN), Dynamic Petri Net (HDN) and Functional Petri Net (FPN). The biological data needed to construct the terpenoid metabolic model were gathered from the literature and from biological databases. These data were used as building blocks to create an HFPNe model and to generate parameters that govern the global behaviour of the model. The dynamic model was simulated and validated against known experimental data obtained from extensive literature searches. The model successfully simulated metabolite concentration changes over time (pt) and the observations correlated with known data. Interactions between the intermediates that affect the production of terpenes could be observed through the introduction of inhibitors that established feedback loops within and crosstalk between the pathways. Although this metabolic model is only preliminary, it will provide a platform for analysing various high-throughput data, and it should lead to a more holistic understanding of terpenoid biosynthesis.
Genetic basis of congenital erythrocytosis: mutation update and online databases.
Bento, Celeste; Percy, Melanie J; Gardie, Betty; Maia, Tabita Magalhães; van Wijk, Richard; Perrotta, Silverio; Della Ragione, Fulvio; Almeida, Helena; Rossi, Cedric; Girodon, François; Aström, Maria; Neumann, Drorit; Schnittger, Susanne; Landin, Britta; Minkov, Milen; Randi, Maria Luigia; Richard, Stéphane; Casadevall, Nicole; Vainchenker, William; Rives, Susana; Hermouet, Sylvie; Ribeiro, M Leticia; McMullin, Mary Frances; Cario, Holger; Chauveau, Aurelie; Gimenez-Roqueplo, Anne-Paule; Bressac-de-Paillerets, Brigitte; Altindirek, Didem; Lorenzo, Felipe; Lambert, Frederic; Dan, Harlev; Gad-Lapiteau, Sophie; Catarina Oliveira, Ana; Rossi, Cédric; Fraga, Cristina; Taradin, Gennadiy; Martin-Nuñez, Guillermo; Vitória, Helena; Diaz Aguado, Herrera; Palmblad, Jan; Vidán, Julia; Relvas, Luis; Ribeiro, Maria Leticia; Luigi Larocca, Maria; Luigia Randi, Maria; Pedro Silveira, Maria; Percy, Melanie; Gross, Mor; Marques da Costa, Ricardo; Beshara, Soheir; Ben-Ami, Tal; Ugo, Valérie
2014-01-01
Congenital erythrocytosis (CE), or congenital polycythemia, represents a rare and heterogeneous clinical entity. It is caused by deregulated red blood cell production where erythrocyte overproduction results in elevated hemoglobin and hematocrit levels. Primary congenital familial erythrocytosis is associated with low erythropoietin (Epo) levels and results from mutations in the Epo receptor gene (EPOR). Secondary CE arises from conditions causing tissue hypoxia and results in increased Epo production. These include hemoglobin variants with increased affinity for oxygen (HBB, HBA mutations), decreased production of 2,3-bisphosphoglycerate due to BPGM mutations, or mutations in the genes involved in the hypoxia sensing pathway (VHL, EPAS1, and EGLN1). Depending on the affected gene, CE can be inherited either in an autosomal dominant or recessive mode, with sporadic cases arising de novo. Despite recent important discoveries in the molecular pathogenesis of CE, the molecular causes remain to be identified in about 70% of the patients. With the objective of collecting all the published and unpublished cases of CE the COST action MPN&MPNr-Euronet developed a comprehensive Internet-based database focusing on the registration of clinical history, hematological, biochemical, and molecular data (http://www.erythrocytosis.org/). In addition, unreported mutations are also curated in the corresponding Leiden Open Variation Database. © 2013 WILEY PERIODICALS, INC.
DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions
Arjunan, Selvam; Sastri, Narayan P.; Chandra, Nagasuma
2016-01-01
Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue–human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue–human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/). PMID:27618709
DenHunt - A Comprehensive Database of the Intricate Network of Dengue-Human Interactions.
Karyala, Prashanthi; Metri, Rahul; Bathula, Christopher; Yelamanchi, Syam K; Sahoo, Lipika; Arjunan, Selvam; Sastri, Narayan P; Chandra, Nagasuma
2016-09-01
Dengue virus (DENV) is a human pathogen and its etiology has been widely established. There are many interactions between DENV and human proteins that have been reported in literature. However, no publicly accessible resource for efficiently retrieving the information is yet available. In this study, we mined all publicly available dengue-human interactions that have been reported in the literature into a database called DenHunt. We retrieved 682 direct interactions of human proteins with dengue viral components, 382 indirect interactions and 4120 differentially expressed human genes in dengue infected cell lines and patients. We have illustrated the importance of DenHunt by mapping the dengue-human interactions on to the host interactome and observed that the virus targets multiple host functional complexes of important cellular processes such as metabolism, immune system and signaling pathways suggesting a potential role of these interactions in viral pathogenesis. We also observed that 7 percent of the dengue virus interacting human proteins are also associated with other infectious and non-infectious diseases. Finally, the understanding that comes from such analyses could be used to design better strategies to counteract the diseases caused by dengue virus. The whole dataset has been catalogued in a searchable database, called DenHunt (http://proline.biochem.iisc.ernet.in/DenHunt/).
Zhou, Hufeng; Jin, Jingjing; Zhang, Haojun; Yi, Bo; Wozniak, Michal; Wong, Limsoon
2012-01-01
Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath.
Plant Reactome: a resource for plant pathways and comparative analysis
Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D.; Wu, Guanming; Fabregat, Antonio; Elser, Justin L.; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D.; Ware, Doreen; Jaiswal, Pankaj
2017-01-01
Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. PMID:27799469
Kamitsuji, Shigeo; Matsuda, Takashi; Nishimura, Koichi; Endo, Seiko; Wada, Chisa; Watanabe, Kenji; Hasegawa, Koichi; Hishigaki, Haretsugu; Masuda, Masatoshi; Kuwahara, Yusuke; Tsuritani, Katsuki; Sugiura, Kenkichi; Kubota, Tomoko; Miyoshi, Shinji; Okada, Kinya; Nakazono, Kazuyuki; Sugaya, Yuki; Yang, Woosung; Sawamoto, Taiji; Uchida, Wataru; Shinagawa, Akira; Fujiwara, Tsutomu; Yamada, Hisaharu; Suematsu, Koji; Tsutsui, Naohisa; Kamatani, Naoyuki; Liou, Shyh-Yuh
2015-06-01
Japan Pharmacogenomics Data Science Consortium (JPDSC) has assembled a database for conducting pharmacogenomics (PGx) studies in Japanese subjects. The database contains the genotypes of 2.5 million single-nucleotide polymorphisms (SNPs) and 5 human leukocyte antigen loci from 2994 Japanese healthy volunteers, as well as 121 kinds of clinical information, including self-reports, physiological data, hematological data and biochemical data. In this article, the reliability of our data was evaluated by principal component analysis (PCA) and association analysis for hematological and biochemical traits by using genome-wide SNP data. PCA of the SNPs showed that all the samples were collected from the Japanese population and that the samples were separated into two major clusters by birthplace, Okinawa and other than Okinawa, as had been previously reported. Among 87 SNPs that have been reported to be associated with 18 hematological and biochemical traits in genome-wide association studies (GWAS), the associations of 56 SNPs were replicated using our data base. Statistical power simulations showed that the sample size of the JPDSC control database is large enough to detect genetic markers having a relatively strong association even when the case sample size is small. The JPDSC database will be useful as control data for conducting PGx studies to explore genetic markers to improve the safety and efficacy of drugs either during clinical development or in post-marketing.
Caromile, Leslie Ann; Dortche, Kristina; Rahman, M. Mamunur; Grant, Christina L.; Stoddard, Christopher; Ferrer, Fernando A.; Shapiro, Linda H.
2017-01-01
Increased abundance of the prostate-specific membrane antigen (PSMA) on prostate epithelium is a hallmark of advanced metastatic prostate cancer (PCa) and correlates negatively with prognosis. However, direct evidence that PSMA functionally contributes to PCa progression remains elusive. We generated mice bearing PSMA-positive or PSMA-negative PCa by crossing PSMA-deficient mice with transgenic PCa (TRAMP) models, enabling direct assessment of PCa incidence and progression in the presence or absence of PSMA. Compared with PSMA-positive tumors, PSMA-negative tumors were smaller, lower-grade, and more apoptotic with fewer blood vessels, consistent with the recognized proangiogenic function of PSMA. Relative to PSMA-positive tumors, tumors lacking PSMA had less than half the abundance of type 1 insulin-like growth factor receptor (IGF-1R), less activity in the survival pathway mediated by PI3K-AKT signaling, and more activity in the proliferative pathway mediated by MAPK-ERK1/2 signaling. Biochemically, PSMA interacted with the scaffolding protein RACK1, disrupting signaling between the β1 integrin and IGF-1R complex to the MAPK pathway, enabling activation of the AKT pathway instead. Manipulation of PSMA abundance in PCa cell lines recapitulated this signaling pathway switch. Analysis of published databases indicated that IGF-1R abundance, cell proliferation, and expression of transcripts for antiapoptotic markers positively correlated with PSMA abundance in patients, suggesting that this switch may be relevant to human PCa. Our findings suggest that increase in PSMA in prostate tumors contributes to progression by altering normal signal transduction pathways to drive PCa progression and that enhanced signaling through the IGF-1R/β1 integrin axis may occur in other tumors. PMID:28292957
Li, Fengmei; Liu, Wuyi
2017-06-01
The basic helix-loop-helix (bHLH) transcription factors (TFs) form a huge superfamily and play crucial roles in many essential developmental, genetic, and physiological-biochemical processes of eukaryotes. In total, 109 putative bHLH TFs were identified and categorized successfully in the genomic databases of cattle, Bos Taurus, after removing redundant sequences and merging genetic isoforms. Through phylogenetic analyses, 105 proteins among these bHLH TFs were classified into 44 families with 46, 25, 14, 3, 13, and 4 members in the high-order groups A, B, C, D, E, and F, respectively. The remaining 4 bHLH proteins were sorted out as 'orphans.' Next, these 109 putative bHLH proteins identified were further characterized as significantly enriched in 524 significant Gene Ontology (GO) annotations (corrected P value ≤ 0.05) and 21 significantly enriched pathways (corrected P value ≤ 0.05) that had been mapped by the web server KOBAS 2.0. Furthermore, 95 bHLH proteins were further screened and analyzed together with two uncharacterized proteins in the STRING online database to reconstruct the protein-protein interaction network of cattle bHLH TFs. Ultimately, 89 bHLH proteins were fully mapped in a network with 67 biological process, 13 molecular functions, 5 KEGG pathways, 12 PFAM protein domains, and 25 INTERPRO classified protein domains and features. These results provide much useful information and a good reference for further functional investigations and updated researches on cattle bHLH TFs.
Activity-based protein profiling for biochemical pathway discovery in cancer
Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.
2011-01-01
Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252
Cellular compartmentalization of secondary metabolism
USDA-ARS?s Scientific Manuscript database
Fungal secondary metabolism is often considered apart from the essential housekeeping functions of the cell. However, there are clear links between fundamental cellular metabolism and the biochemical pathways leading to secondary metabolite synthesis. Besides utilizing key biochemical precursors sh...
2012-01-01
Background Pathway data are important for understanding the relationship between genes, proteins and many other molecules in living organisms. Pathway gene relationships are crucial information for guidance, prediction, reference and assessment in biochemistry, computational biology, and medicine. Many well-established databases--e.g., KEGG, WikiPathways, and BioCyc--are dedicated to collecting pathway data for public access. However, the effectiveness of these databases is hindered by issues such as incompatible data formats, inconsistent molecular representations, inconsistent molecular relationship representations, inconsistent referrals to pathway names, and incomprehensive data from different databases. Results In this paper, we overcome these issues through extraction, normalization and integration of pathway data from several major public databases (KEGG, WikiPathways, BioCyc, etc). We build a database that not only hosts our integrated pathway gene relationship data for public access but also maintains the necessary updates in the long run. This public repository is named IntPath (Integrated Pathway gene relationship database for model organisms and important pathogens). Four organisms--S. cerevisiae, M. tuberculosis H37Rv, H. Sapiens and M. musculus--are included in this version (V2.0) of IntPath. IntPath uses the "full unification" approach to ensure no deletion and no introduced noise in this process. Therefore, IntPath contains much richer pathway-gene and pathway-gene pair relationships and much larger number of non-redundant genes and gene pairs than any of the single-source databases. The gene relationships of each gene (measured by average node degree) per pathway are significantly richer. The gene relationships in each pathway (measured by average number of gene pairs per pathway) are also considerably richer in the integrated pathways. Moderate manual curation are involved to get rid of errors and noises from source data (e.g., the gene ID errors in WikiPathways and relationship errors in KEGG). We turn complicated and incompatible xml data formats and inconsistent gene and gene relationship representations from different source databases into normalized and unified pathway-gene and pathway-gene pair relationships neatly recorded in simple tab-delimited text format and MySQL tables, which facilitates convenient automatic computation and large-scale referencing in many related studies. IntPath data can be downloaded in text format or MySQL dump. IntPath data can also be retrieved and analyzed conveniently through web service by local programs or through web interface by mouse clicks. Several useful analysis tools are also provided in IntPath. Conclusions We have overcome in IntPath the issues of compatibility, consistency, and comprehensiveness that often hamper effective use of pathway databases. We have included four organisms in the current release of IntPath. Our methodology and programs described in this work can be easily applied to other organisms; and we will include more model organisms and important pathogens in future releases of IntPath. IntPath maintains regular updates and is freely available at http://compbio.ddns.comp.nus.edu.sg:8080/IntPath. PMID:23282057
Alterations in metabolic pathways and networks in Alzheimer's disease
Kaddurah-Daouk, R; Zhu, H; Sharma, S; Bogdanov, M; Rozen, S G; Matson, W; Oki, N O; Motsinger-Reif, A A; Churchill, E; Lei, Z; Appleby, D; Kling, M A; Trojanowski, J Q; Doraiswamy, P M; Arnold, S E
2013-01-01
The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure. PMID:23571809
Alterations in metabolic pathways and networks in Alzheimer's disease.
Kaddurah-Daouk, R; Zhu, H; Sharma, S; Bogdanov, M; Rozen, S G; Matson, W; Oki, N O; Motsinger-Reif, A A; Churchill, E; Lei, Z; Appleby, D; Kling, M A; Trojanowski, J Q; Doraiswamy, P M; Arnold, S E
2013-04-09
The pathogenic mechanisms of Alzheimer's disease (AD) remain largely unknown and clinical trials have not demonstrated significant benefit. Biochemical characterization of AD and its prodromal phase may provide new diagnostic and therapeutic insights. We used targeted metabolomics platform to profile cerebrospinal fluid (CSF) from AD (n=40), mild cognitive impairment (MCI, n=36) and control (n=38) subjects; univariate and multivariate analyses to define between-group differences; and partial least square-discriminant analysis models to classify diagnostic groups using CSF metabolomic profiles. A partial correlation network was built to link metabolic markers, protein markers and disease severity. AD subjects had elevated methionine (MET), 5-hydroxyindoleacetic acid (5-HIAA), vanillylmandelic acid, xanthosine and glutathione versus controls. MCI subjects had elevated 5-HIAA, MET, hypoxanthine and other metabolites versus controls. Metabolite ratios revealed changes within tryptophan, MET and purine pathways. Initial pathway analyses identified steps in several pathways that appear altered in AD and MCI. A partial correlation network showed total tau most directly related to norepinephrine and purine pathways; amyloid-β (Ab42) was related directly to an unidentified metabolite and indirectly to 5-HIAA and MET. These findings indicate that MCI and AD are associated with an overlapping pattern of perturbations in tryptophan, tyrosine, MET and purine pathways, and suggest that profound biochemical alterations are linked to abnormal Ab42 and tau metabolism. Metabolomics provides powerful tools to map interlinked biochemical pathway perturbations and study AD as a disease of network failure.
Hsiao, Yu-Yun; Tsai, Wen-Chieh; Kuoh, Chang-Sheng; Huang, Tian-Hsiang; Wang, Hei-Chia; Wu, Tian-Shung; Leu, Yann-Lii; Chen, Wen-Huei; Chen, Hong-Hwa
2006-01-01
Background Floral scent is one of the important strategies for ensuring fertilization and for determining seed or fruit set. Research on plant scents has hampered mainly by the invisibility of this character, its dynamic nature, and complex mixtures of components that are present in very small quantities. Most progress in scent research, as in other areas of plant biology, has come from the use of molecular and biochemical techniques. Although volatile components have been identified in several orchid species, the biosynthetic pathways of orchid flower fragrance are far from understood. We investigated how flower fragrance was generated in certain Phalaenopsis orchids by determining the chemical components of the floral scent, identifying floral expressed-sequence-tags (ESTs), and deducing the pathways of floral scent biosynthesis in Phalaneopsis bellina by bioinformatics analysis. Results The main chemical components in the P. bellina flower were shown by gas chromatography-mass spectrometry to be monoterpenoids, benzenoids and phenylpropanoids. The set of floral scent producing enzymes in the biosynthetic pathway from glyceraldehyde-3-phosphate (G3P) to geraniol and linalool were recognized through data mining of the P. bellina floral EST database (dbEST). Transcripts preferentially expressed in P. bellina were distinguished by comparing the scent floral dbEST to that of a scentless species, P. equestris, and included those encoding lipoxygenase, epimerase, diacylglycerol kinase and geranyl diphosphate synthase. In addition, EST filtering results showed that transcripts encoding signal transduction and Myb transcription factors and methyltransferase, in addition to those for scent biosynthesis, were detected by in silico hybridization of the P. bellina unigene database against those of the scentless species, rice and Arabidopsis. Altogether, we pinpointed 66% of the biosynthetic steps from G3P to geraniol, linalool and their derivatives. Conclusion This systems biology program combined chemical analysis, genomics and bioinformatics to elucidate the scent biosynthesis pathway and identify the relevant genes. It integrates the forward and reverse genetic approaches to knowledge discovery by which researchers can study non-model plants. PMID:16836766
Das, Sankha Subhra; Saha, Pritam
2018-01-01
Abstract MicroRNAs (miRNAs) are well-known as key regulators of diverse biological pathways. A series of experimental evidences have shown that abnormal miRNA expression profiles are responsible for various pathophysiological conditions by modulating genes in disease associated pathways. In spite of the rapid increase in research data confirming such associations, scientists still do not have access to a consolidated database offering these miRNA-pathway association details for critical diseases. We have developed miRwayDB, a database providing comprehensive information of experimentally validated miRNA-pathway associations in various pathophysiological conditions utilizing data collected from published literature. To the best of our knowledge, it is the first database that provides information about experimentally validated miRNA mediated pathway dysregulation as seen specifically in critical human diseases and hence indicative of a cause-and-effect relationship in most cases. The current version of miRwayDB collects an exhaustive list of miRNA-pathway association entries for 76 critical disease conditions by reviewing 663 published articles. Each database entry contains complete information on the name of the pathophysiological condition, associated miRNA(s), experimental sample type(s), regulation pattern (up/down) of miRNA, pathway association(s), targeted member of dysregulated pathway(s) and a brief description. In addition, miRwayDB provides miRNA, gene and pathway score to evaluate the role of a miRNA regulated pathways in various pathophysiological conditions. The database can also be used for other biomedical approaches such as validation of computational analysis, integrated analysis and prediction of computational model. It also offers a submission page to submit novel data from recently published studies. We believe that miRwayDB will be a useful tool for miRNA research community. Database URL: http://www.mirway.iitkgp.ac.in PMID:29688364
Xue, Yunping; Lv, Juan; Xu, Pengfei; Gu, Lin; Cao, Jian; Xu, Lingling; Xue, Kai; Li, Qian
2018-05-01
Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disease, which is characterized by hyperandrogenism (HA), chronic anovulation, polycystic ovaries, insulin resistance, and obesity. At present, the mechanism by which PCOS/HA occurs has not been fully elucidated, thus, the mechanisms behind and interventions for HA in PCOS are current hot topics in research. MiRNAs have recently been shown to serve as diagnostic or prognostic biomarkers in patients with cancer. Thus, we are currently focused on studying the altered expression of miRNAs in follicular fluid and their correlation with HA in PCOS. Illumina deep sequencing technology was used to explore different miRNAs in the follicular fluid of women with PCOS/HA and in the follicular fluid of women in a control group. Target prediction databases were then used to analyse the target genes of different expressed miRNAs, and GO analysis and the KEGG pathway database were used to identify the functions and the main biochemical and signalling pathways of differentially expressed target genes. The expression levels of 263 miRNAs were significantly different (>2-fold up-regulated or <0.5-fold down-regulated, P < 0.05) between the two groups of women. For example, the expression levels of miRNA (200a-3p, 10b-3p, 200b-3p, 29c-3p, 99a-3p, and 125a-5p) were significantly increased, while there was a decreased expression of miR-105-3p in PCOS patients with respect to the control. Literature has shown that the above seven miRNAs were associated with HA in PCOS. Furthermore, 31 770 genes were predicted to be targets of the 263 differentially expressed microRNAs. GO analysis and the KEGG pathway database showed involvement of these target genes in HA in PCOS. These results suggest the presence of differentially expressed miRNAs in the follicular fluid of women with PCOS/HA versus women in the control group. The potential role of these microRNAs was elucidated using bioinformatics tools and was found to be involved in the regulation of different pathways, biological functions, and cellular components underlying PCOS. The results of this research may reveal new mechanisms of PCOS/HA and suggest potential treatment targets. © 2017 Wiley Periodicals, Inc.
Ismail, Ahmad Muhaimin; Mohamad, Mohd Saberi; Abdul Majid, Hairudin; Abas, Khairul Hamimah; Deris, Safaai; Zaki, Nazar; Mohd Hashim, Siti Zaiton; Ibrahim, Zuwairie; Remli, Muhammad Akmal
2017-12-01
Mathematical modelling is fundamental to understand the dynamic behavior and regulation of the biochemical metabolisms and pathways that are found in biological systems. Pathways are used to describe complex processes that involve many parameters. It is important to have an accurate and complete set of parameters that describe the characteristics of a given model. However, measuring these parameters is typically difficult and even impossible in some cases. Furthermore, the experimental data are often incomplete and also suffer from experimental noise. These shortcomings make it challenging to identify the best-fit parameters that can represent the actual biological processes involved in biological systems. Computational approaches are required to estimate these parameters. The estimation is converted into multimodal optimization problems that require a global optimization algorithm that can avoid local solutions. These local solutions can lead to a bad fit when calibrating with a model. Although the model itself can potentially match a set of experimental data, a high-performance estimation algorithm is required to improve the quality of the solutions. This paper describes an improved hybrid of particle swarm optimization and the gravitational search algorithm (IPSOGSA) to improve the efficiency of a global optimum (the best set of kinetic parameter values) search. The findings suggest that the proposed algorithm is capable of narrowing down the search space by exploiting the feasible solution areas. Hence, the proposed algorithm is able to achieve a near-optimal set of parameters at a fast convergence speed. The proposed algorithm was tested and evaluated based on two aspartate pathways that were obtained from the BioModels Database. The results show that the proposed algorithm outperformed other standard optimization algorithms in terms of accuracy and near-optimal kinetic parameter estimation. Nevertheless, the proposed algorithm is only expected to work well in small scale systems. In addition, the results of this study can be used to estimate kinetic parameter values in the stage of model selection for different experimental conditions. Copyright © 2017 Elsevier B.V. All rights reserved.
Metabolomic strategies to map functions of metabolic pathways
Mulvihill, Melinda M.
2014-01-01
Genome sequencing efforts have revealed a strikingly large number of unannotated and uncharacterized genes that fall into metabolic enzymes classes, likely indicating that our current knowledge of biochemical pathways in normal physiology, let alone in disease states, remains largely incomplete. This realization presents a daunting challenge for post-genomic-era scientists in deciphering the biochemical and (patho)physiological roles of these enzymes and their metabolites and metabolic networks. This is further complicated by many recent studies showing a rewiring of normal metabolic networks in disease states to give rise to unique pathophysiological functions of enzymes, metabolites, and metabolic pathways. This review focuses on recent discoveries made using metabolic mapping technologies to uncover novel pathways and metabolite-mediated posttranslational modifications and epigenetic alterations and their impact on physiology and disease. PMID:24918200
Schomburg, Ida; Chang, Antje; Placzek, Sandra; Söhngen, Carola; Rother, Michael; Lang, Maren; Munaretto, Cornelia; Ulas, Susanne; Stelzer, Michael; Grote, Andreas; Scheer, Maurice; Schomburg, Dietmar
2013-01-01
The BRENDA (BRaunschweig ENzyme DAtabase) enzyme portal (http://www.brenda-enzymes.org) is the main information system of functional biochemical and molecular enzyme data and provides access to seven interconnected databases. BRENDA contains 2.7 million manually annotated data on enzyme occurrence, function, kinetics and molecular properties. Each entry is connected to a reference and the source organism. Enzyme ligands are stored with their structures and can be accessed via their names, synonyms or via a structure search. FRENDA (Full Reference ENzyme DAta) and AMENDA (Automatic Mining of ENzyme DAta) are based on text mining methods and represent a complete survey of PubMed abstracts with information on enzymes in different organisms, tissues or organelles. The supplemental database DRENDA provides more than 910 000 new EC number-disease relations in more than 510 000 references from automatic search and a classification of enzyme-disease-related information. KENDA (Kinetic ENzyme DAta), a new amendment extracts and displays kinetic values from PubMed abstracts. The integration of the EnzymeDetector offers an automatic comparison, evaluation and prediction of enzyme function annotations for prokaryotic genomes. The biochemical reaction database BKM-react contains non-redundant enzyme-catalysed and spontaneous reactions and was developed to facilitate and accelerate the construction of biochemical models.
Song, Hun-Suk; Jeon, Jong-Min; Kim, Hyun-Joong; Bhatia, Shashi Kant; Sathiyanarayanan, Ganesan; Kim, Junyoung; Won Hong, Ju; Gi Hong, Yoon; Young Choi, Kwon; Kim, Yun-Gon; Kim, Wooseong; Yang, Yung-Hun
2017-12-01
To reduce the furfural toxicity for biochemical production in E. coli, a new strategy was successfully applied by supplying NAD(P)H through the nicotine amide salvage pathway. To alleviate the toxicity, nicotinamide salvage pathway genes were overexpressed in recombinant, isobutanol-producing E. coli. Gene expression of pncB and nadE respectively showed increased tolerance to furfural among these pathways. The combined expression of pncB and nadE was the most effective in increasing the tolerance of the cells to toxic aldehydes. By comparing noxE- and fdh-harbouring strains, the form of NADH, rather than NAD + , was the major effector of furfural tolerance. Overall, this study is the application of the salvage pathway to isobutanol production in the presence of furfural, and this system seems to be applicable to alleviate furfural toxicity in the production of other biochemical. Copyright © 2017 Elsevier Ltd. All rights reserved.
Plant Reactome: a resource for plant pathways and comparative analysis.
Naithani, Sushma; Preece, Justin; D'Eustachio, Peter; Gupta, Parul; Amarasinghe, Vindhya; Dharmawardhana, Palitha D; Wu, Guanming; Fabregat, Antonio; Elser, Justin L; Weiser, Joel; Keays, Maria; Fuentes, Alfonso Munoz-Pomer; Petryszak, Robert; Stein, Lincoln D; Ware, Doreen; Jaiswal, Pankaj
2017-01-04
Plant Reactome (http://plantreactome.gramene.org/) is a free, open-source, curated plant pathway database portal, provided as part of the Gramene project. The database provides intuitive bioinformatics tools for the visualization, analysis and interpretation of pathway knowledge to support genome annotation, genome analysis, modeling, systems biology, basic research and education. Plant Reactome employs the structural framework of a plant cell to show metabolic, transport, genetic, developmental and signaling pathways. We manually curate molecular details of pathways in these domains for reference species Oryza sativa (rice) supported by published literature and annotation of well-characterized genes. Two hundred twenty-two rice pathways, 1025 reactions associated with 1173 proteins, 907 small molecules and 256 literature references have been curated to date. These reference annotations were used to project pathways for 62 model, crop and evolutionarily significant plant species based on gene homology. Database users can search and browse various components of the database, visualize curated baseline expression of pathway-associated genes provided by the Expression Atlas and upload and analyze their Omics datasets. The database also offers data access via Application Programming Interfaces (APIs) and in various standardized pathway formats, such as SBML and BioPAX. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Hu, Qian-Nan; Deng, Zhe; Hu, Huanan; Cao, Dong-Sheng; Liang, Yi-Zeng
2011-09-01
Biochemical reactions play a key role to help sustain life and allow cells to grow. RxnFinder was developed to search biochemical reactions from KEGG reaction database using three search criteria: molecular structures, molecular fragments and reaction similarity. RxnFinder is helpful to get reference reactions for biosynthesis and xenobiotics metabolism. RxnFinder is freely available via: http://sdd.whu.edu.cn/rxnfinder. qnhu@whu.edu.cn.
Tan, Kevin; Goldstein, David; Crowe, Philip; Yang, Jia-Lin
2013-11-01
Anoikis ('homelessness' in Greek) is a form of apoptosis following the detachment of cells from the appropriate extracellular matrix (Chiarugi and Giannoni in Biochem Pharmacol 76:1352-1364, 2008). Resistance to anoikis is a critical mediator of metastasis in cancer by enabling cancer cells to survive during invasion and transport in the blood and lymph. Numerous regulators and mechanisms of anoikis in human cancer have been proposed to date. Consequently, the identification of key regulators of anoikis that can be targeted to at least partially restore anoikis sensitivity in cancer cells is important in the development of therapies to treat metastatic cancer. A literature search focusing on the regulators of anoikis in human cancer was performed on the Medline, Embase and Scopus databases. Mcl-1, Cav-1, Bcl-(xL), cFLIP, 14-3-3ζ and Bit1 appear to regulate anoikis in human cancer by participating in the intrinsic apoptotic pathway, extrinsic apoptotic pathway or caspase-independent pathways. Mcl-1, Cav-1, Bcl-(xL), cFLIP and 14-3-3ζ are suppressors of anoikis, and their upregulation confers anoikis resistance to cancer cells. Bit1 is a promoter of anoikis and is downregulated to confer anoikis resistance in metastatic cancer. Anoikis is a complex process involving the crosstalk between different signalling pathways. The dysregulated expression of key regulators of anoikis that participate in these signalling pathways promotes anoikis resistance in human cancer. These regulators of anoikis might therefore be the targets for developing therapies to overcome anoikis resistance in metastatic cancer.
The mevalonate pathway in neurons: It's not just about cholesterol.
Moutinho, Miguel; Nunes, Maria João; Rodrigues, Elsa
2017-11-01
Cholesterol homeostasis greatly impacts neuronal function due to the essential role of this sterol in the brain. The mevalonate (MVA) pathway leads to the synthesis of cholesterol, but also supplies cells with many other intermediary molecules crucial for neuronal function. Compelling evidence point to a model in which neurons shutdown cholesterol synthesis, and rely on a shuttle derived from astrocytes to meet their cholesterol needs. Nevertheless, several reports suggest that neurons maintain the MVA pathway active, even with sustained cholesterol supply by astrocytes. Hence, in this review we focus not on cholesterol production, but rather on the role of the MVA pathway in the synthesis of particular intermediaries, namely isoprenoids, and on their role on neuronal function. Isoprenoids act as anchors for membrane association, after being covalently bound to proteins, such as most of the small guanosine triphosphate-binding proteins, which are critical to neuronal cell function. Based on literature, on our own results, and on the analysis of public transcriptomics databases, we raise the idea that in neurons there is a shift of the MVA pathway towards the non-sterol branch, responsible for isoprenoid synthesis, in detriment to post-squalene branch, and that this is ultimately essential for synaptic activity. Nevertheless new tools that facilitate imaging and the biochemical characterization and quantification of the prenylome in neurons and astrocytes are needed to understand the regulation of isoprenoid production and protein prenylation in the brain, and to analyze its differences on diverse physiological or pathological conditions, such as aging and neurodegenerative states. Copyright © 2017 Elsevier Inc. All rights reserved.
Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D
2016-02-01
Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.
Recovering metabolic pathways via optimization.
Beasley, John E; Planes, Francisco J
2007-01-01
A metabolic pathway is a coherent set of enzyme catalysed biochemical reactions by which a living organism transforms an initial (source) compound into a final (target) compound. Some of the different metabolic pathways adopted within organisms have been experimentally determined. In this paper, we show that a number of experimentally determined metabolic pathways can be recovered by a mathematical optimization model.
Plant MetGenMAP: an integrative analysis system for plant systems biology
USDA-ARS?s Scientific Manuscript database
We have developed a web-based system, Plant MetGenMAP, which can identify significantly altered biochemical pathways and highly affected biological processes, predict functional roles of pathway genes, and potential pathway-related regulatory motifs from transcript and metabolite profile datasets. P...
Reconstruction of metabolic pathways for the cattle genome
Seo, Seongwon; Lewin, Harris A
2009-01-01
Background Metabolic reconstruction of microbial, plant and animal genomes is a necessary step toward understanding the evolutionary origins of metabolism and species-specific adaptive traits. The aims of this study were to reconstruct conserved metabolic pathways in the cattle genome and to identify metabolic pathways with missing genes and proteins. The MetaCyc database and PathwayTools software suite were chosen for this work because they are widely used and easy to implement. Results An amalgamated cattle genome database was created using the NCBI and Ensembl cattle genome databases (based on build 3.1) as data sources. PathwayTools was used to create a cattle-specific pathway genome database, which was followed by comprehensive manual curation for the reconstruction of metabolic pathways. The curated database, CattleCyc 1.0, consists of 217 metabolic pathways. A total of 64 mammalian-specific metabolic pathways were modified from the reference pathways in MetaCyc, and two pathways previously identified but missing from MetaCyc were added. Comparative analysis of metabolic pathways revealed the absence of mammalian genes for 22 metabolic enzymes whose activity was reported in the literature. We also identified six human metabolic protein-coding genes for which the cattle ortholog is missing from the sequence assembly. Conclusion CattleCyc is a powerful tool for understanding the biology of ruminants and other cetartiodactyl species. In addition, the approach used to develop CattleCyc provides a framework for the metabolic reconstruction of other newly sequenced mammalian genomes. It is clear that metabolic pathway analysis strongly reflects the quality of the underlying genome annotations. Thus, having well-annotated genomes from many mammalian species hosted in BioCyc will facilitate the comparative analysis of metabolic pathways among different species and a systems approach to comparative physiology. PMID:19284618
Dong, Wei-Ren; Sun, Cen-Cen; Zhu, Guan; Hu, Shi-Hua; Xiang, Li-Xin; Shao, Jian-Zhong
2014-02-08
In an effort to reconstitute the NAD(+) synthetic pathway in Escherichia coli (E. coli), we produced a set of gene knockout mutants with deficiencies in previously well-defined NAD(+)de novo and salvage pathways. Unexpectedly, the mutant deficient in NAD(+) de novo and salvage pathway I could grow in M9/nicotinamide medium, which was contradictory to the proposed classic NAD(+) metabolism of E. coli. Such E. coli mutagenesis assay suggested the presence of an undefined machinery to feed nicotinamide into the NAD(+) biosynthesis. We wanted to verify whether xanthosine phophorylase (xapA) contributed to a new NAD(+) salvage pathway from nicotinamide. Additional knockout of xapA further slowed down the bacterial growth in M9/nicotinamide medium, whereas the complementation of xapA restored the growth phenotype. To further validate the new function of xapA, we cloned and expressed E. coli xapA as a recombinant soluble protein. Biochemical assay confirmed that xapA was capable of using nicotinamide as a substrate for nicotinamide riboside formation. Both the genetic and biochemical evidences indicated that xapA could convert nicotinamide to nicotinamide riboside in E. coli, albeit with relatively weak activity, indicating that xapA may contribute to a second NAD(+) salvage pathway from nicotinamide. We speculate that this xapA-mediated NAD(+) salvage pathway might be significant in some bacteria lacking NAD(+) de novo and NAD(+) salvage pathway I or II, to not only use nicotinamide riboside, but also nicotinamide as precursors to synthesize NAD(+). However, this speculation needs to be experimentally tested.
Diversity of bile salts in fish and amphibians: evolution of a complex biochemical pathway.
Hagey, Lee R; Møller, Peter R; Hofmann, Alan F; Krasowski, Matthew D
2010-01-01
Bile salts are the major end metabolites of cholesterol and are also important in lipid and protein digestion, as well as shaping of the gut microflora. Previous studies had demonstrated variation of bile salt structures across vertebrate species. We greatly extend prior surveys of bile salt variation in fish and amphibians, particularly in analysis of the biliary bile salts of Agnatha and Chondrichthyes. While there is significant structural variation of bile salts across all fish orders, bile salt profiles are generally stable within orders of fish and do not correlate with differences in diet. This large data set allowed us to infer evolutionary changes in the bile salt synthetic pathway. The hypothesized ancestral bile salt synthetic pathway, likely exemplified in extant hagfish, is simpler and much shorter than the pathway of most teleost fish and terrestrial vertebrates. Thus, the bile salt synthetic pathway has become longer and more complex throughout vertebrate evolution. Analysis of the evolution of bile salt synthetic pathways provides a rich model system for the molecular evolution of a complex biochemical pathway in vertebrates.
An editor for pathway drawing and data visualization in the Biopathways Workbench.
Byrnes, Robert W; Cotter, Dawn; Maer, Andreia; Li, Joshua; Nadeau, David; Subramaniam, Shankar
2009-10-02
Pathway models serve as the basis for much of systems biology. They are often built using programs designed for the purpose. Constructing new models generally requires simultaneous access to experimental data of diverse types, to databases of well-characterized biological compounds and molecular intermediates, and to reference model pathways. However, few if any software applications provide all such capabilities within a single user interface. The Pathway Editor is a program written in the Java programming language that allows de-novo pathway creation and downloading of LIPID MAPS (Lipid Metabolites and Pathways Strategy) and KEGG lipid metabolic pathways, and of measured time-dependent changes to lipid components of metabolism. Accessed through Java Web Start, the program downloads pathways from the LIPID MAPS Pathway database (Pathway) as well as from the LIPID MAPS web server http://www.lipidmaps.org. Data arises from metabolomic (lipidomic), microarray, and protein array experiments performed by the LIPID MAPS consortium of laboratories and is arranged by experiment. Facility is provided to create, connect, and annotate nodes and processes on a drawing panel with reference to database objects and time course data. Node and interaction layout as well as data display may be configured in pathway diagrams as desired. Users may extend diagrams, and may also read and write data and non-lipidomic KEGG pathways to and from files. Pathway diagrams in XML format, containing database identifiers referencing specific compounds and experiments, can be saved to a local file for subsequent use. The program is built upon a library of classes, referred to as the Biopathways Workbench, that convert between different file formats and database objects. An example of this feature is provided in the form of read/construct/write access to models in SBML (Systems Biology Markup Language) contained in the local file system. Inclusion of access to multiple experimental data types and of pathway diagrams within a single interface, automatic updating through connectivity to an online database, and a focus on annotation, including reference to standardized lipid nomenclature as well as common lipid names, supports the view that the Pathway Editor represents a significant, practicable contribution to current pathway modeling tools.
Metabolomic strategies to map functions of metabolic pathways.
Mulvihill, Melinda M; Nomura, Daniel K
2014-08-01
Genome sequencing efforts have revealed a strikingly large number of unannotated and uncharacterized genes that fall into metabolic enzymes classes, likely indicating that our current knowledge of biochemical pathways in normal physiology, let alone in disease states, remains largely incomplete. This realization presents a daunting challenge for post-genomic-era scientists in deciphering the biochemical and (patho)physiological roles of these enzymes and their metabolites and metabolic networks. This is further complicated by many recent studies showing a rewiring of normal metabolic networks in disease states to give rise to unique pathophysiological functions of enzymes, metabolites, and metabolic pathways. This review focuses on recent discoveries made using metabolic mapping technologies to uncover novel pathways and metabolite-mediated posttranslational modifications and epigenetic alterations and their impact on physiology and disease. Copyright © 2014 the American Physiological Society.
NASA Astrophysics Data System (ADS)
Frank, T. D.
2013-08-01
We derive a nonlinear limit cycle model for oscillatory mood variations as observed in patients with cycling bipolar disorder. To this end, we consider two signaling pathways leading to the activation of two enzymes that play a key role for cellular and neural processes. We model pathway cross-talk in terms of an inhibitory impact of the first pathway on the second and an excitatory impact of the second on the first. The model also involves a negative feedback loop (inhibitory self-regulation) for the first pathway and a positive feedback loop (excitatory self-regulation) for the second pathway. We demonstrate that due to the cross-talk the biochemical dynamics is described by an oscillator equation. Under disease-free conditions the oscillatory system exhibits a stable fixed point. The breakdown of the self-inhibition of the first pathway at higher concentration levels is studied by means of a scalar control parameter ξ, where ξ equal to zero refers to intact self-inhibition at all concentration levels. Under certain conditions, stable limit cycle solutions emerge at critical parameter values of ξ larger than zero. These oscillations mimic pathological cycling mood variations that emerge due to a disease-induced bifurcation. Consequently, our modeling analysis supports the notion of bipolar disorder as a dynamical disease. In addition, our study establishes a connection between mechanistic biochemical modeling of bipolar disorder and phenomenological nonlinear oscillator approaches to bipolar disorder suggested in the literature.
Pierce, Arand; Miller, Geoffrey; Arden, Rosalind; Gottfredson, Linda S
2009-09-01
We recently found positive correlations between human general intelligence and three key indices of semen quality, and hypothesized that these correlations arise through a phenotype-wide 'general fitness factor' reflecting overall mutation load. In this addendum we consider some of the biochemical pathways that may act as targets for pleiotropic mutations that disrupt both neuron function and sperm function in parallel. We focus especially on the inter-related roles of polyunsaturated fatty acids, exocytosis and receptor signaling.
Karp, Peter D; Paley, Suzanne; Romero, Pedro
2002-01-01
Bioinformatics requires reusable software tools for creating model-organism databases (MODs). The Pathway Tools is a reusable, production-quality software environment for creating a type of MOD called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc (see http://ecocyc.org) integrates our evolving understanding of the genes, proteins, metabolic network, and genetic network of an organism. This paper provides an overview of the four main components of the Pathway Tools: The PathoLogic component supports creation of new PGDBs from the annotated genome of an organism. The Pathway/Genome Navigator provides query, visualization, and Web-publishing services for PGDBs. The Pathway/Genome Editors support interactive updating of PGDBs. The Pathway Tools ontology defines the schema of PGDBs. The Pathway Tools makes use of the Ocelot object database system for data management services for PGDBs. The Pathway Tools has been used to build PGDBs for 13 organisms within SRI and by external users.
Kinase Pathway Database: An Integrated Protein-Kinase and NLP-Based Protein-Interaction Resource
Koike, Asako; Kobayashi, Yoshiyuki; Takagi, Toshihisa
2003-01-01
Protein kinases play a crucial role in the regulation of cellular functions. Various kinds of information about these molecules are important for understanding signaling pathways and organism characteristics. We have developed the Kinase Pathway Database, an integrated database involving major completely sequenced eukaryotes. It contains the classification of protein kinases and their functional conservation, ortholog tables among species, protein–protein, protein–gene, and protein–compound interaction data, domain information, and structural information. It also provides an automatic pathway graphic image interface. The protein, gene, and compound interactions are automatically extracted from abstracts for all genes and proteins by natural-language processing (NLP).The method of automatic extraction uses phrase patterns and the GENA protein, gene, and compound name dictionary, which was developed by our group. With this database, pathways are easily compared among species using data with more than 47,000 protein interactions and protein kinase ortholog tables. The database is available for querying and browsing at http://kinasedb.ontology.ims.u-tokyo.ac.jp/. PMID:12799355
Caspi, Ron; Altman, Tomer; Dale, Joseph M.; Dreher, Kate; Fulcher, Carol A.; Gilham, Fred; Kaipa, Pallavi; Karthikeyan, Athikkattuvalasu S.; Kothari, Anamika; Krummenacker, Markus; Latendresse, Mario; Mueller, Lukas A.; Paley, Suzanne; Popescu, Liviu; Pujar, Anuradha; Shearer, Alexander G.; Zhang, Peifen; Karp, Peter D.
2010-01-01
The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism. PMID:19850718
2013-01-01
Background Chrysanthemum is one of the most important ornamental crops in the world and drought stress seriously limits its production and distribution. In order to generate a functional genomics resource and obtain a deeper understanding of the molecular mechanisms regarding chrysanthemum responses to dehydration stress, we performed large-scale transcriptome sequencing of chrysanthemum plants under dehydration stress using the Illumina sequencing technology. Results Two cDNA libraries constructed from mRNAs of control and dehydration-treated seedlings were sequenced by Illumina technology. A total of more than 100 million reads were generated and de novo assembled into 98,180 unique transcripts which were further extensively annotated by comparing their sequencing to different protein databases. Biochemical pathways were predicted from these transcript sequences. Furthermore, we performed gene expression profiling analysis upon dehydration treatment in chrysanthemum and identified 8,558 dehydration-responsive unique transcripts, including 307 transcription factors and 229 protein kinases and many well-known stress responsive genes. Gene ontology (GO) term enrichment and biochemical pathway analyses showed that dehydration stress caused changes in hormone response, secondary and amino acid metabolism, and light and photoperiod response. These findings suggest that drought tolerance of chrysanthemum plants may be related to the regulation of hormone biosynthesis and signaling, reduction of oxidative damage, stabilization of cell proteins and structures, and maintenance of energy and carbon supply. Conclusions Our transcriptome sequences can provide a valuable resource for chrysanthemum breeding and research and novel insights into chrysanthemum responses to dehydration stress and offer candidate genes or markers that can be used to guide future studies attempting to breed drought tolerant chrysanthemum cultivars. PMID:24074255
Reactome graph database: Efficient access to complex pathway data
Korninger, Florian; Viteri, Guilherme; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D’Eustachio, Peter
2018-01-01
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types. PMID:29377902
Reactome graph database: Efficient access to complex pathway data.
Fabregat, Antonio; Korninger, Florian; Viteri, Guilherme; Sidiropoulos, Konstantinos; Marin-Garcia, Pablo; Ping, Peipei; Wu, Guanming; Stein, Lincoln; D'Eustachio, Peter; Hermjakob, Henning
2018-01-01
Reactome is a free, open-source, open-data, curated and peer-reviewed knowledgebase of biomolecular pathways. One of its main priorities is to provide easy and efficient access to its high quality curated data. At present, biological pathway databases typically store their contents in relational databases. This limits access efficiency because there are performance issues associated with queries traversing highly interconnected data. The same data in a graph database can be queried more efficiently. Here we present the rationale behind the adoption of a graph database (Neo4j) as well as the new ContentService (REST API) that provides access to these data. The Neo4j graph database and its query language, Cypher, provide efficient access to the complex Reactome data model, facilitating easy traversal and knowledge discovery. The adoption of this technology greatly improved query efficiency, reducing the average query time by 93%. The web service built on top of the graph database provides programmatic access to Reactome data by object oriented queries, but also supports more complex queries that take advantage of the new underlying graph-based data storage. By adopting graph database technology we are providing a high performance pathway data resource to the community. The Reactome graph database use case shows the power of NoSQL database engines for complex biological data types.
De novo transcriptomic analysis and development of EST-SSRs for Sorbus pohuashanensis (Hance) Hedl.
Guan, Xuelian; Fu, Qiang; Zhang, Ze; Hu, Zenghui; Zheng, Jian; Lu, Yizeng; Li, Wei
2017-01-01
Sorbus pohuashanensis is a native tree species of northern China that is used for a variety of ecological purposes. The species is often grown as an ornamental landscape tree because of its beautiful form, silver flowers in early summer, attractive pinnate leaves in summer, and red leaves and fruits in autumn. However, development and further utilization of the species are hindered by the lack of comprehensive genetic information, which impedes research into its genetics and molecular biology. Recent advances in de novo transcriptome sequencing (RNA-seq) technology have provided an effective means to obtain genomic information from non-model species. Here, we applied RNA-seq for sequencing S. pohuashanensis leaves and obtained a total of 137,506 clean reads. After assembly, 96,213 unigenes with an average length of 770 bp were obtained. We found that 64.5% of the unigenes could be annotated using bioinformatics tools to analyze gene function and alignment with the NCBI database. Overall, 59,089 unigenes were annotated using the Nr database(non-redundant protein database), 35,225 unigenes were annotated using the GO (Gene Ontology categories) database, and 33,168 unigenes were annotated using COG (Cluster of Orthologous Groups). Analysis of the unigenes using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database indicated that 13,953 unigenes were involved in 322 metabolic pathways. Finally, simple sequence repeat (SSR) site detection identified 6,604 unigenes that included EST-SSRs and a total of 7,473 EST-SSRs in the unigene sequences. Fifteen polymorphic SSRs were screened and found to be of use for future genetic research. These unigene sequences will provide important genetic resources for genetic improvement and investigation of biochemical processes in S. pohuashanensis. PMID:28614366
Emerging evidence on the role of the Hippo/YAP pathway in liver physiology and cancer.
Yimlamai, Dean; Fowl, Brendan H; Camargo, Fernando D
2015-12-01
The Hippo pathway and its regulatory target, YAP, has recently emerged as an important biochemical signaling pathway that tightly governs epithelial tissue growth. Initially defined in Drosophilia, this pathway has shown remarkable conservation in vertebrate systems with many components of the Hippo/YAP pathway showing biochemical and functional conservation. The liver is particularly sensitive to changes in Hippo/YAP signaling with rapid increases in liver size becoming manifest on the order of days to weeks after perturbation. The first identified direct targets of Hippo/YAP signaling were pro-proliferative and anti-apoptotic gene programs, but recent work has now implicated this pathway in cell fate choice, stem cell maintenance/renewal, epithelial to mesenchymal transition, and oncogenesis. The mechanisms by which Hippo/YAP signaling is changed endogenously are beginning to come to light as well as how this pathway interacts with other signaling pathways, and important details for designing new therapeutic interventions. This review focuses on the known roles for Hippo/YAP signaling in the liver and promising avenues for future study. Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.
Levac, Dylan; Cázares, Paulo; Yu, Fang
2016-01-01
Members of the Apocynaceae plant family produce a large number of monoterpenoid indole alkaloids (MIAs) with different substitution patterns that are responsible for their various biological activities. A novel N-methyltransferase involved in the vindoline pathway in Catharanthus roseus showing distinct similarity to γ-tocopherol C-methyltransferases was used in a bioinformatic screen of transcriptomes from Vinca minor, Rauvolfia serpentina, and C. roseus to identify 10 γ-tocopherol-like N-methyltransferases from a large annotated transcriptome database of different MIA-producing plant species (www.phytometasyn.ca). The biochemical function of two members of this group cloned from V. minor (VmPiNMT) and R. serpentina (RsPiNMT) have been characterized by screening their biochemical activities against potential MIA substrates harvested from the leaf surfaces of MIA-accumulating plants. The approach was validated by identifying the MIA picrinine from leaf surfaces of Amsonia hubrichtii as a substrate of VmPiNMT and RsPiNMT. Recombinant proteins were shown to have high substrate specificity and affinity for picrinine, converting it to N-methylpicrinine (ervincine). Developmental studies with V. minor and R. serpentina showed that RsPiNMT and VmPiNMT gene expression and biochemical activities were highest in younger leaf tissues. The assembly of at least 150 known N-methylated MIAs within members of the Apocynaceae family may have occurred as a result of the evolution of the γ-tocopherol-like N-methyltransferase family from γ-tocopherol methyltransferases. PMID:26848097
Groves, Ryan A.; Hagel, Jillian M.; Zhang, Ye; Kilpatrick, Korey; Levy, Asaf; Marsolais, Frédéric; Lewinsohn, Efraim; Sensen, Christoph W.; Facchini, Peter J.
2015-01-01
Amphetamine analogues are produced by plants in the genus Ephedra and by khat (Catha edulis), and include the widely used decongestants and appetite suppressants (1S,2S)-pseudoephedrine and (1R,2S)-ephedrine. The production of these metabolites, which derive from L-phenylalanine, involves a multi-step pathway partially mapped out at the biochemical level using knowledge of benzoic acid metabolism established in other plants, and direct evidence using khat and Ephedra species as model systems. Despite the commercial importance of amphetamine-type alkaloids, only a single step in their biosynthesis has been elucidated at the molecular level. We have employed Illumina next-generation sequencing technology, paired with Trinity and Velvet-Oases assembly platforms, to establish data-mining frameworks for Ephedra sinica and khat plants. Sequence libraries representing a combined 200,000 unigenes were subjected to an annotation pipeline involving direct searches against public databases. Annotations included the assignment of Gene Ontology (GO) terms used to allocate unigenes to functional categories. As part of our functional genomics program aimed at novel gene discovery, the databases were mined for enzyme candidates putatively involved in alkaloid biosynthesis. Queries used for mining included enzymes with established roles in benzoic acid metabolism, as well as enzymes catalyzing reactions similar to those predicted for amphetamine alkaloid metabolism. Gene candidates were evaluated based on phylogenetic relationships, FPKM-based expression data, and mechanistic considerations. Establishment of expansive sequence resources is a critical step toward pathway characterization, a goal with both academic and industrial implications. PMID:25806807
Zimmermann, Katrin; Engeser, Marianne; Blunt, John W; Munro, Murray H G; Piel, Jörn
2009-03-04
The complex polyketide pederin is a potent antitumor agent isolated from Paederus spp. rove beetles. We have previously isolated a set of genes from a bacterial endosymbiont that are good candidates for pederin biosynthesis. To biochemically study this pathway, we expressed three methyltransferases from the putative pederin pathway and used the partially unmethylated analogue mycalamide A from the marine sponge Mycale hentscheli as test substrate. Analysis by high-resolution MS/MS and NMR revealed that PedO regiospecifically methylates the marine compound to generate the nonnatural hybrid compound 18-O-methylmycalamide A with increased cytotoxicity. To our knowledge, this is the first biochemical evidence that invertebrates can obtain defensive complex polyketides from bacterial symbionts.
Berim, Anna; Hyatt, David C.; Gang, David R.
2012-01-01
Polymethoxylated flavonoids occur in a number of plant families, including the Lamiaceae. To date, the metabolic pathways giving rise to the diversity of these compounds have not been studied. Analysis of our expressed sequence tag database for four sweet basil (Ocimum basilicum) lines afforded identification of candidate flavonoid O-methyltransferase genes. Recombinant proteins displayed distinct substrate preferences and product specificities that can account for all detected 7-/6-/4′-methylated, 8-unsubstituted flavones. Their biochemical specialization revealed only certain metabolic routes to be highly favorable and therefore likely in vivo. Flavonoid O-methyltransferases catalyzing 4′- and 6-O-methylations shared high identity (approximately 90%), indicating that subtle sequence changes led to functional differentiation. Structure homology modeling suggested the involvement of several amino acid residues in defining the proteins’ stringent regioselectivities. The roles of these individual residues were confirmed by site-directed mutagenesis, revealing two discrete mechanisms as a basis for the switch between 6- and 4′-O-methylation of two different substrates. These findings delineate major pathways in a large segment of the flavone metabolic network and provide a foundation for its further elucidation. PMID:22923679
Clinical and Biochemical Manifestations of Depression: Relation to the Neurobiology of Stress
Gold, Phillip W.; Machado-Vieira, Rodrigo; Pavlatou, Maria G.
2015-01-01
Major depressive disorder (MDD) is a chronic, recurrent, and severe psychiatric disorder with high mortality and medical comorbidities. Stress-related pathways have been directly involved in the pathophysiology and treatment of MDD. The present paper provides an overview on the stress system as a model to understand key pathophysiological paradigms in MDD. These mechanisms involve behavioral, cognitive, and systemic manifestations and are also associated with the mechanisms of action of effective antidepressants. Aspects such as depression subtypes, inflammation, insulin resistance, oxidative stress, and prothrombotic states in critical brain circuits and periphery are critically appraised. Finally, new strategies for approaching treatment-resistant major depression and potential adverse effects associated with this complex and intricate network are highlighted. The authors used PubMed as the database for this review. Each author extracted relevant data and assessed the methodological quality of each study. PMID:25878903
Integrating mass spectrometry and genomics for cyanobacterial metabolite discovery
Bertin, Matthew J.; Kleigrewe, Karin; Leão, Tiago F.; Gerwick, Lena
2016-01-01
Filamentous marine cyanobacteria produce bioactive natural products with both potential therapeutic value and capacity to be harmful to human health. Genome sequencing has revealed that cyanobacteria have the capacity to produce many more secondary metabolites than have been characterized. The biosynthetic pathways that encode cyanobacterial natural products are mostly uncharacterized, and lack of cyanobacterial genetic tools has largely prevented their heterologous expression. Hence, a combination of cutting edge and traditional techniques has been required to elucidate their secondary metabolite biosynthetic pathways. Here, we review the discovery and refined biochemical understanding of the olefin synthase and fatty acid ACP reductase/aldehyde deformylating oxygenase pathways to hydrocarbons, and the curacin A, jamaicamide A, lyngbyabellin, columbamide, and a trans-acyltransferase macrolactone pathway encoding phormidolide. We integrate into this discussion the use of genomics, mass spectrometric networking, biochemical characterization, and isolation and structure elucidation techniques. PMID:26578313
Comparison of human cell signaling pathway databases—evolution, drawbacks and challenges
Chowdhury, Saikat; Sarkar, Ram Rup
2015-01-01
Elucidating the complexities of cell signaling pathways is of immense importance to gain understanding about various biological phenomenon, such as dynamics of gene/protein expression regulation, cell fate determination, embryogenesis and disease progression. The successful completion of human genome project has also helped experimental and theoretical biologists to analyze various important pathways. To advance this study, during the past two decades, systematic collections of pathway data from experimental studies have been compiled and distributed freely by several databases, which also integrate various computational tools for further analysis. Despite significant advancements, there exist several drawbacks and challenges, such as pathway data heterogeneity, annotation, regular update and automated image reconstructions, which motivated us to perform a thorough review on popular and actively functioning 24 cell signaling databases. Based on two major characteristics, pathway information and technical details, freely accessible data from commercial and academic databases are examined to understand their evolution and enrichment. This review not only helps to identify some novel and useful features, which are not yet included in any of the databases but also highlights their current limitations and subsequently propose the reasonable solutions for future database development, which could be useful to the whole scientific community. PMID:25632107
2014-01-01
Background In an effort to reconstitute the NAD+ synthetic pathway in Escherichia coli (E. coli), we produced a set of gene knockout mutants with deficiencies in previously well-defined NAD+de novo and salvage pathways. Unexpectedly, the mutant deficient in NAD+de novo and salvage pathway I could grow in M9/nicotinamide medium, which was contradictory to the proposed classic NAD+ metabolism of E. coli. Such E. coli mutagenesis assay suggested the presence of an undefined machinery to feed nicotinamide into the NAD+ biosynthesis. We wanted to verify whether xanthosine phophorylase (xapA) contributed to a new NAD+ salvage pathway from nicotinamide. Results Additional knockout of xapA further slowed down the bacterial growth in M9/nicotinamide medium, whereas the complementation of xapA restored the growth phenotype. To further validate the new function of xapA, we cloned and expressed E. coli xapA as a recombinant soluble protein. Biochemical assay confirmed that xapA was capable of using nicotinamide as a substrate for nicotinamide riboside formation. Conclusions Both the genetic and biochemical evidences indicated that xapA could convert nicotinamide to nicotinamide riboside in E. coli, albeit with relatively weak activity, indicating that xapA may contribute to a second NAD+ salvage pathway from nicotinamide. We speculate that this xapA-mediated NAD+ salvage pathway might be significant in some bacteria lacking NAD+de novo and NAD+ salvage pathway I or II, to not only use nicotinamide riboside, but also nicotinamide as precursors to synthesize NAD+. However, this speculation needs to be experimentally tested. PMID:24506841
Dogrusoz, U; Erson, E Z; Giral, E; Demir, E; Babur, O; Cetintas, A; Colak, R
2006-02-01
Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.
Chao, Yu-Hsin; Giagtzoglou, Nikolaos; Putluri, Nagireddy; Coarfa, Cristian; Donti, Taraka; Faust, Joseph E.; McNew, James A.; Sardiello, Marco; Baes, Myriam; Bellen, Hugo J.
2017-01-01
Peroxisome biogenesis disorders (PBD) are a group of multi-system human diseases due to mutations in the PEX genes that are responsible for peroxisome assembly and function. These disorders lead to global defects in peroxisomal function and result in severe brain, liver, bone and kidney disease. In order to study their pathogenesis we undertook a systematic genetic and biochemical study of Drosophila pex16 and pex2 mutants. These mutants are short-lived with defects in locomotion and activity. Moreover these mutants exhibit severe morphologic and functional peroxisomal defects. Using metabolomics we uncovered defects in multiple biochemical pathways including defects outside the canonical specialized lipid pathways performed by peroxisomal enzymes. These included unanticipated changes in metabolites in glycolysis, glycogen metabolism, and the pentose phosphate pathway, carbohydrate metabolic pathways that do not utilize known peroxisomal enzymes. In addition, mutant flies are starvation sensitive and are very sensitive to glucose deprivation exhibiting dramatic shortening of lifespan and hyperactivity on low-sugar food. We use bioinformatic transcriptional profiling to examine gene co-regulation between peroxisomal genes and other metabolic pathways and we observe that the expression of peroxisomal and carbohydrate pathway genes in flies and mouse are tightly correlated. Indeed key steps in carbohydrate metabolism were found to be strongly co-regulated with peroxisomal genes in flies and mice. Moreover mice lacking peroxisomes exhibit defective carbohydrate metabolism at the same key steps in carbohydrate breakdown. Our data indicate an unexpected link between these two metabolic processes and suggest metabolism of carbohydrates could be a new therapeutic target for patients with PBD. PMID:28640802
Shirdel, Elize A.; Xie, Wing; Mak, Tak W.; Jurisica, Igor
2011-01-01
Background MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome – referred to as the micronome – to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal — mirDIP (http://ophid.utoronto.ca/mirDIP). Results mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05), suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001), to be more studied (p<0.0002), and to have higher degree in the KEGG cancer pathway (p<0.0001), compared to intra-pathway microRNAs. Conclusions Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level. PMID:21364759
Environmental Impact on Vascular Development Predicted by High-Throughput Screening
Judson, Richard S.; Reif, David M.; Sipes, Nisha S.; Singh, Amar V.; Chandler, Kelly J.; DeWoskin, Rob; Dix, David J.; Kavlock, Robert J.; Knudsen, Thomas B.
2011-01-01
Background: Understanding health risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. High-throughput screening (HTS) in the U.S. Environmental Protection Agency (EPA) ToxCast™ project provides vast data on an expanding chemical library currently consisting of > 1,000 unique compounds across > 500 in vitro assays in phase I (complete) and Phase II (under way). This public data set can be used to evaluate concentration-dependent effects on many diverse biological targets and build predictive models of prototypical toxicity pathways that can aid decision making for assessments of human developmental health and disease. Objective: We mined the ToxCast phase I data set to identify signatures for potential chemical disruption of blood vessel formation and remodeling. Methods: ToxCast phase I screened 309 chemicals using 467 HTS assays across nine assay technology platforms. The assays measured direct interactions between chemicals and molecular targets (receptors, enzymes), as well as downstream effects on reporter gene activity or cellular consequences. We ranked the chemicals according to individual vascular bioactivity score and visualized the ranking using ToxPi (Toxicological Priority Index) profiles. Results: Targets in inflammatory chemokine signaling, the vascular endothelial growth factor pathway, and the plasminogen-activating system were strongly perturbed by some chemicals, and we found positive correlations with developmental effects from the U.S. EPA ToxRefDB (Toxicological Reference Database) in vivo database containing prenatal rat and rabbit guideline studies. We observed distinctly different correlative patterns for chemicals with effects in rabbits versus rats, despite derivation of in vitro signatures based on human cells and cell-free biochemical targets, implying conservation but potentially differential contributions of developmental pathways among species. Follow-up analysis with antiangiogenic thalidomide analogs and additional in vitro vascular targets showed in vitro activity consistent with the most active environmental chemicals tested here. Conclusions: We predicted that blood vessel development is a target for environmental chemicals acting as putative vascular disruptor compounds (pVDCs) and identified potential species differences in sensitive vascular developmental pathways. PMID:21788198
Argout, Xavier; Fouet, Olivier; Wincker, Patrick; Gramacho, Karina; Legavre, Thierry; Sabau, Xavier; Risterucci, Ange Marie; Da Silva, Corinne; Cascardo, Julio; Allegre, Mathilde; Kuhn, David; Verica, Joseph; Courtois, Brigitte; Loor, Gaston; Babin, Regis; Sounigo, Olivier; Ducamp, Michel; Guiltinan, Mark J; Ruiz, Manuel; Alemanno, Laurence; Machado, Regina; Phillips, Wilberth; Schnell, Ray; Gilmour, Martin; Rosenquist, Eric; Butler, David; Maximova, Siela; Lanaud, Claire
2008-01-01
Background Theobroma cacao L., is a tree originated from the tropical rainforest of South America. It is one of the major cash crops for many tropical countries. T. cacao is mainly produced on smallholdings, providing resources for 14 million farmers. Disease resistance and T. cacao quality improvement are two important challenges for all actors of cocoa and chocolate production. T. cacao is seriously affected by pests and fungal diseases, responsible for more than 40% yield losses and quality improvement, nutritional and organoleptic, is also important for consumers. An international collaboration was formed to develop an EST genomic resource database for cacao. Results Fifty-six cDNA libraries were constructed from different organs, different genotypes and different environmental conditions. A total of 149,650 valid EST sequences were generated corresponding to 48,594 unigenes, 12,692 contigs and 35,902 singletons. A total of 29,849 unigenes shared significant homology with public sequences from other species. Gene Ontology (GO) annotation was applied to distribute the ESTs among the main GO categories. A specific information system (ESTtik) was constructed to process, store and manage this EST collection allowing the user to query a database. To check the representativeness of our EST collection, we looked for the genes known to be involved in two different metabolic pathways extensively studied in other plant species and important for T. cacao qualities: the flavonoid and the terpene pathways. Most of the enzymes described in other crops for these two metabolic pathways were found in our EST collection. A large collection of new genetic markers was provided by this ESTs collection. Conclusion This EST collection displays a good representation of the T. cacao transcriptome, suitable for analysis of biochemical pathways based on oligonucleotide microarrays derived from these ESTs. It will provide numerous genetic markers that will allow the construction of a high density gene map of T. cacao. This EST collection represents a unique and important molecular resource for T. cacao study and improvement, facilitating the discovery of candidate genes for important T. cacao trait variation. PMID:18973681
Argout, Xavier; Fouet, Olivier; Wincker, Patrick; Gramacho, Karina; Legavre, Thierry; Sabau, Xavier; Risterucci, Ange Marie; Da Silva, Corinne; Cascardo, Julio; Allegre, Mathilde; Kuhn, David; Verica, Joseph; Courtois, Brigitte; Loor, Gaston; Babin, Regis; Sounigo, Olivier; Ducamp, Michel; Guiltinan, Mark J; Ruiz, Manuel; Alemanno, Laurence; Machado, Regina; Phillips, Wilberth; Schnell, Ray; Gilmour, Martin; Rosenquist, Eric; Butler, David; Maximova, Siela; Lanaud, Claire
2008-10-30
Theobroma cacao L., is a tree originated from the tropical rainforest of South America. It is one of the major cash crops for many tropical countries. T. cacao is mainly produced on smallholdings, providing resources for 14 million farmers. Disease resistance and T. cacao quality improvement are two important challenges for all actors of cocoa and chocolate production. T. cacao is seriously affected by pests and fungal diseases, responsible for more than 40% yield losses and quality improvement, nutritional and organoleptic, is also important for consumers. An international collaboration was formed to develop an EST genomic resource database for cacao. Fifty-six cDNA libraries were constructed from different organs, different genotypes and different environmental conditions. A total of 149,650 valid EST sequences were generated corresponding to 48,594 unigenes, 12,692 contigs and 35,902 singletons. A total of 29,849 unigenes shared significant homology with public sequences from other species.Gene Ontology (GO) annotation was applied to distribute the ESTs among the main GO categories.A specific information system (ESTtik) was constructed to process, store and manage this EST collection allowing the user to query a database.To check the representativeness of our EST collection, we looked for the genes known to be involved in two different metabolic pathways extensively studied in other plant species and important for T. cacao qualities: the flavonoid and the terpene pathways. Most of the enzymes described in other crops for these two metabolic pathways were found in our EST collection.A large collection of new genetic markers was provided by this ESTs collection. This EST collection displays a good representation of the T. cacao transcriptome, suitable for analysis of biochemical pathways based on oligonucleotide microarrays derived from these ESTs. It will provide numerous genetic markers that will allow the construction of a high density gene map of T. cacao. This EST collection represents a unique and important molecular resource for T. cacao study and improvement, facilitating the discovery of candidate genes for important T. cacao trait variation.
Adverse Outcome Pathways: From Definition to Application
A challenge for both human health and ecological toxicologists is the transparent application of mechanistic (e.g., molecular, biochemical, histological) data to risk assessments. The adverse outcome pathway (AOP) is a conceptual framework designed to meet this need. Specifical...
B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis
Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar
2012-01-01
The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187
Diabetic Neuropathy: Mechanisms to Management
Edwards, James L.; Vincent, Andrea; Cheng, Thomas; Feldman, Eva L.
2014-01-01
Neuropathy is the most common and debilitating complication of diabetes and results in pain, decreased motility, and amputation. Diabetic neuropathy encompasses a variety of forms whose impact ranges from discomfort to death. Hyperglycemia induces oxidative stress in diabetic neurons and results in activation of multiple biochemical pathways. These activated pathways are a major source of damage and are potential therapeutic targets in diabetic neuropathy. Though therapies are available to alleviate the symptoms of diabetic neuropathy, few options are available to eliminate the root causes. The immense physical, psychological, and economic cost of diabetic neuropathy underscores the need for causally targeted therapies. This review covers the pathology, epidemiology, biochemical pathways, and prevention of diabetic neuropathy, as well as discusses current symptomatic and causal therapies and novel approaches to identify therapeutic targets. PMID:18616962
Naithani, Sushma; Jaiswal, Pankaj
2017-01-01
The species-specific plant Pathway Genome Databases (PGDBs) based on the BioCyc platform provide a conceptual model of the cellular metabolic network of an organism. Such frameworks allow analysis of the genome-scale expression data to understand changes in the overall metabolisms of an organism (or organs, tissues, and cells) in response to various extrinsic (e.g. developmental and differentiation) and/or extrinsic signals (e.g. pathogens and abiotic stresses) from the surrounding environment. Using FragariaCyc, a pathway database for the diploid strawberry Fragaria vesca, we show (1) the basic navigation across a PGDB; (2) a case study of pathway comparison across plant species; and (3) an example of RNA-Seq data analysis using Omics Viewer tool. The protocols described here generally apply to other Pathway Tools-based PGDBs.
Cellular and molecular mechanisms for the bone response to mechanical loading
NASA Technical Reports Server (NTRS)
Bloomfield, S. A.
2001-01-01
To define the cellular and molecular mechanisms for the osteogenic response of bone to increased loading, several key steps must be defined: sensing of the mechanical signal by cells in bone, transduction of the mechanical signal to a biochemical one, and transmission of that biochemical signal to effector cells. Osteocytes are likely to serve as sensors of loading, probably via interstitial fluid flow produced during loading. Evidence is presented for the role of integrins, the cell's actin cytoskeleton, G proteins, and various intracellular signaling pathways in transducing that mechanical signal to a biochemical one. Nitric oxide, prostaglandins, and insulin-like growth factors all play important roles in these pathways. There is growing evidence for modulation of these mechanotransduction steps by endocrine factors, particularly parathyroid hormone and estrogen. The efficiency of this process is also impaired in the aged animal, yet what remains undefined is at what step mechanotransduction is affected.
Magnetic resonance microscopy: concepts, challenges, and state-of-the-art.
Gimi, Barjor
2006-01-01
Recent strides in targeted therapy and regenerative medicine have created a need to identify molecules and metabolic pathways implicated in a disease and its treatment. These molecules and pathways must be discerned at the cellular level to meaningfully reveal the biochemical underpinnings of the disease and to identify key molecular targets for therapy. Magnetic resonance (MR) techniques are well suited for molecular and functional imaging because of their noninvasive nature and their versatility in extracting physiological, biochemical, and functional information over time. However, MR is an insensitive technique; MR microscopy seeks to increase detection sensitivity, thereby localizing biochemical and functional information at the level of single cells or small cellular clusters. Here, we discuss some of the challenges facing MR microscopy and the technical and phenomenological strategies used to overcome these challenges. Some of the applications of MR microscopy are highlighted in this chapter.
Geer, Lewis Y; Marchler-Bauer, Aron; Geer, Renata C; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H
2010-01-01
The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI's Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets.
VitisCyc: a metabolic pathway knowledgebase for grapevine (Vitis vinifera)
Naithani, Sushma; Raja, Rajani; Waddell, Elijah N.; Elser, Justin; Gouthu, Satyanarayana; Deluc, Laurent G.; Jaiswal, Pankaj
2014-01-01
We have developed VitisCyc, a grapevine-specific metabolic pathway database that allows researchers to (i) search and browse the database for its various components such as metabolic pathways, reactions, compounds, genes and proteins, (ii) compare grapevine metabolic networks with other publicly available plant metabolic networks, and (iii) upload, visualize and analyze high-throughput data such as transcriptomes, proteomes, metabolomes etc. using OMICs-Viewer tool. VitisCyc is based on the genome sequence of the nearly homozygous genotype PN40024 of Vitis vinifera “Pinot Noir” cultivar with 12X v1 annotations and was built on BioCyc platform using Pathway Tools software and MetaCyc reference database. Furthermore, VitisCyc was enriched for plant-specific pathways and grape-specific metabolites, reactions and pathways. Currently VitisCyc harbors 68 super pathways, 362 biosynthesis pathways, 118 catabolic pathways, 5 detoxification pathways, 36 energy related pathways and 6 transport pathways, 10,908 enzymes, 2912 enzymatic reactions, 31 transport reactions and 2024 compounds. VitisCyc, as a community resource, can aid in the discovery of candidate genes and pathways that are regulated during plant growth and development, and in response to biotic and abiotic stress signals generated from a plant's immediate environment. VitisCyc version 3.18 is available online at http://pathways.cgrb.oregonstate.edu. PMID:25538713
Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae.
Li, Mingji; Borodina, Irina
2015-02-01
Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae We describe computational tools for the prediction of biochemical pathways, molecular biology methods for assembly of DNA parts into pathways, and for introducing the pathways into the host, and finally approaches for optimizing performance of the introduced pathways. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.
Murine models of atrophy, cachexia, and sarcopenia in skeletal muscle
Romanick, Mark; Brown-Borg, Holly M.
2013-01-01
With the extension of life span over the past several decades, the age-related loss of muscle mass and strength that characterizes sarcopenia is becoming more evident and thus, has a more significant impact on society. To determine ways to intervene and delay, or even arrest the physical frailty and dependence that accompany sarcopenia, it is necessary to identify those biochemical pathways that define this process. Animal models that mimic one or more of the physiological pathways involved with this phenomenon are very beneficial in providing an understanding of the cellular processes at work in sarcopenia. The ability to influence pathways through genetic manipulation gives insight into cellular responses and their impact on the physical expression of sarcopenia. This review evaluates several murine models that have the potential to elucidate biochemical processes integral to sarcopenia. Identifying animal models that reflect sarcopenia or its component pathways will enable researchers to better understand those pathways that contribute to age-related skeletal muscle mass loss, and in turn, develop interventions that will prevent, retard, arrest, or reverse this phenomenon. PMID:23523469
Parisi, Federica; Riccardo, Sara; Daniel, Margaret; Saqcena, Mahesh; Kundu, Nandini; Pession, Annalisa; Grifoni, Daniela; Stocker, Hugo; Tabak, Esteban; Bellosta, Paola
2011-09-27
Genetic studies in Drosophila melanogaster reveal an important role for Myc in controlling growth. Similar studies have also shown how components of the insulin and target of rapamycin (TOR) pathways are key regulators of growth. Despite a few suggestions that Myc transcriptional activity lies downstream of these pathways, a molecular mechanism linking these signaling pathways to Myc has not been clearly described. Using biochemical and genetic approaches we tried to identify novel mechanisms that control Myc activity upon activation of insulin and TOR signaling pathways. Our biochemical studies show that insulin induces Myc protein accumulation in Drosophila S2 cells, which correlates with a decrease in the activity of glycogen synthase kinase 3-beta (GSK3β ) a kinase that is responsible for Myc protein degradation. Induction of Myc by insulin is inhibited by the presence of the TOR inhibitor rapamycin, suggesting that insulin-induced Myc protein accumulation depends on the activation of TOR complex 1. Treatment with amino acids that directly activate the TOR pathway results in Myc protein accumulation, which also depends on the ability of S6K kinase to inhibit GSK3β activity. Myc upregulation by insulin and TOR pathways is a mechanism conserved in cells from the wing imaginal disc, where expression of Dp110 and Rheb also induces Myc protein accumulation, while inhibition of insulin and TOR pathways result in the opposite effect. Our functional analysis, aimed at quantifying the relative contribution of Myc to ommatidial growth downstream of insulin and TOR pathways, revealed that Myc activity is necessary to sustain the proliferation of cells from the ommatidia upon Dp110 expression, while its contribution downstream of TOR is significant to control the size of the ommatidia. Our study presents novel evidence that Myc activity acts downstream of insulin and TOR pathways to control growth in Drosophila. At the biochemical level we found that both these pathways converge at GSK3β to control Myc protein stability, while our genetic analysis shows that insulin and TOR pathways have different requirements for Myc activity during development of the eye, suggesting that Myc might be differentially induced by these pathways during growth or proliferation of cells that make up the ommatidia.
Castada, Hardy Z; Wick, Cheryl; Taylor, Kaitlyn; Harper, W James
2014-04-01
Splits/cracks are recurring product defects that negatively affect the Swiss cheese industry. Investigations to understand the biophysicochemical aspects of these defects, and thus determine preventive measures against their occurrence, are underway. In this study, selected-ion, flow tube mass spectrometry was employed to determine the volatile organic compound (VOC) profiles present in the headspace of split compared with nonsplit cheeses. Two sampling methodologies were employed: split compared with nonsplit cheese vat pair blocks; and comparison of blind, eye, and split segments within cheese blocks. The variability in VOC profiles was examined to evaluate the potential biochemical pathway chemistry differences within and between cheese samples. VOC profile inhomogeneity was most evident in cheeses between factories. Evaluation of biochemical pathways leading to the formation of key VOCs differentiating the split from the blind and eye segments within factories indicated release of additional carbon dioxide by-product. These results suggest a factory-dependent cause of split formation that could develop from varied fermentation pathways in the blind, eye, and split areas within a cheese block. The variability of VOC profiles within and between factories exhibit varied biochemical fermentation pathways that could conceivably be traced back in the making process to identify parameters responsible for split defect. © 2014 Institute of Food Technologists®
HBVPathDB: a database of HBV infection-related molecular interaction network.
Zhang, Yi; Bo, Xiao-Chen; Yang, Jing; Wang, Sheng-Qi
2005-03-21
To describe molecules or genes interaction between hepatitis B viruses (HBV) and host, for understanding how virus' and host's genes and molecules are networked to form a biological system and for perceiving mechanism of HBV infection. The knowledge of HBV infection-related reactions was organized into various kinds of pathways with carefully drawn graphs in HBVPathDB. Pathway information is stored with relational database management system (DBMS), which is currently the most efficient way to manage large amounts of data and query is implemented with powerful Structured Query Language (SQL). The search engine is written using Personal Home Page (PHP) with SQL embedded and web retrieval interface is developed for searching with Hypertext Markup Language (HTML). We present the first version of HBVPathDB, which is a HBV infection-related molecular interaction network database composed of 306 pathways with 1 050 molecules involved. With carefully drawn graphs, pathway information stored in HBVPathDB can be browsed in an intuitive way. We develop an easy-to-use interface for flexible accesses to the details of database. Convenient software is implemented to query and browse the pathway information of HBVPathDB. Four search page layout options-category search, gene search, description search, unitized search-are supported by the search engine of the database. The database is freely available at http://www.bio-inf.net/HBVPathDB/HBV/. The conventional perspective HBVPathDB have already contained a considerable amount of pathway information with HBV infection related, which is suitable for in-depth analysis of molecular interaction network of virus and host. HBVPathDB integrates pathway data-sets with convenient software for query, browsing, visualization, that provides users more opportunity to identify regulatory key molecules as potential drug targets and to explore the possible mechanism of HBV infection based on gene expression datasets.
Selenium uptake, translocation, assimilation and metabolic fate in plants.
Sors, T G; Ellis, D R; Salt, D E
2005-12-01
The chemical and physical resemblance between selenium (Se) and sulfur (S) establishes that both these elements share common metabolic pathways in plants. The presence of isologous Se and S compounds indicates that these elements compete in biochemical processes that affect uptake, translocation and assimilation throughout plant development. Yet, minor but crucial differences in reactivity and other metabolic interactions infer that some biochemical processes involving Se may be excluded from those relating to S. This review examines the current understanding of physiological and biochemical relationships between S and Se metabolism by highlighting their similarities and differences in relation to uptake, transport and assimilation pathways as observed in Se hyperaccumulator and non-accumulator plant species. The exploitation of genetic resources used in bioengineering strategies of plants is illuminating the function of sulfate transporters and key enzymes of the S assimilatory pathway in relation to Se accumulation and final metabolic fate. These strategies are providing the basic framework by which to resolve questions relating to the essentiality of Se in plants and the mechanisms utilized by Se hyperaccumulators to circumvent toxicity. In addition, such approaches may assist in the future application of genetically engineered Se accumulating plants for environmental renewal and human health objectives.
Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise
NASA Astrophysics Data System (ADS)
Hinczewski, Michael; Thirumalai, D.
2014-10-01
Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.
Convergent evolution of caffeine in plants by co-option of exapted ancestral enzymes.
Huang, Ruiqi; O'Donnell, Andrew J; Barboline, Jessica J; Barkman, Todd J
2016-09-20
Convergent evolution is a process that has occurred throughout the tree of life, but the historical genetic and biochemical context promoting the repeated independent origins of a trait is rarely understood. The well-known stimulant caffeine, and its xanthine alkaloid precursors, has evolved multiple times in flowering plant history for various roles in plant defense and pollination. We have shown that convergent caffeine production, surprisingly, has evolved by two previously unknown biochemical pathways in chocolate, citrus, and guaraná plants using either caffeine synthase- or xanthine methyltransferase-like enzymes. However, the pathway and enzyme lineage used by any given plant species is not predictable from phylogenetic relatedness alone. Ancestral sequence resurrection reveals that this convergence was facilitated by co-option of genes maintained over 100 million y for alternative biochemical roles. The ancient enzymes of the Citrus lineage were exapted for reactions currently used for various steps of caffeine biosynthesis and required very few mutations to acquire modern-day enzymatic characteristics, allowing for the evolution of a complete pathway. Future studies aimed at manipulating caffeine content of plants will require the use of different approaches given the metabolic and genetic diversity revealed by this study.
Anaerobic Degradation of Benzene and Polycyclic Aromatic Hydrocarbons.
Meckenstock, Rainer U; Boll, Matthias; Mouttaki, Housna; Koelschbach, Janina S; Cunha Tarouco, Paola; Weyrauch, Philip; Dong, Xiyang; Himmelberg, Anne M
2016-01-01
Aromatic hydrocarbons such as benzene and polycyclic aromatic hydrocarbons (PAHs) are very slowly degraded without molecular oxygen. Here, we review the recent advances in the elucidation of the first known degradation pathways of these environmental hazards. Anaerobic degradation of benzene and PAHs has been successfully documented in the environment by metabolite analysis, compound-specific isotope analysis and microcosm studies. Subsequently, also enrichments and pure cultures were obtained that anaerobically degrade benzene, naphthalene or methylnaphthalene, and even phenanthrene, the largest PAH currently known to be degradable under anoxic conditions. Although such cultures grow very slowly, with doubling times of around 2 weeks, and produce only very little biomass in batch cultures, successful proteogenomic, transcriptomic and biochemical studies revealed novel degradation pathways with exciting biochemical reactions such as for example the carboxylation of naphthalene or the ATP-independent reduction of naphthoyl-coenzyme A. The elucidation of the first anaerobic degradation pathways of naphthalene and methylnaphthalene at the genetic and biochemical level now opens the door to studying the anaerobic metabolism and ecology of anaerobic PAH degraders. This will contribute to assessing the fate of one of the most important contaminant classes in anoxic sediments and aquifers. © 2016 S. Karger AG, Basel.
Convergent evolution of caffeine in plants by co-option of exapted ancestral enzymes
Huang, Ruiqi; O’Donnell, Andrew J.; Barboline, Jessica J.; Barkman, Todd J.
2016-01-01
Convergent evolution is a process that has occurred throughout the tree of life, but the historical genetic and biochemical context promoting the repeated independent origins of a trait is rarely understood. The well-known stimulant caffeine, and its xanthine alkaloid precursors, has evolved multiple times in flowering plant history for various roles in plant defense and pollination. We have shown that convergent caffeine production, surprisingly, has evolved by two previously unknown biochemical pathways in chocolate, citrus, and guaraná plants using either caffeine synthase- or xanthine methyltransferase-like enzymes. However, the pathway and enzyme lineage used by any given plant species is not predictable from phylogenetic relatedness alone. Ancestral sequence resurrection reveals that this convergence was facilitated by co-option of genes maintained over 100 million y for alternative biochemical roles. The ancient enzymes of the Citrus lineage were exapted for reactions currently used for various steps of caffeine biosynthesis and required very few mutations to acquire modern-day enzymatic characteristics, allowing for the evolution of a complete pathway. Future studies aimed at manipulating caffeine content of plants will require the use of different approaches given the metabolic and genetic diversity revealed by this study. PMID:27638206
2015-01-01
Ergothioneine is a histidine thiol derivative. Its mycobacterial biosynthetic pathway has five steps (EgtA-E catalysis) with two novel reactions: a mononuclear nonheme iron enzyme (EgtB) catalyzed oxidative C–S bond formation and a PLP-mediated C–S lyase (EgtE) reaction. Our bioinformatic and biochemical analyses indicate that the fungus Neurospora crassa has a more concise ergothioneine biosynthetic pathway because its nonheme iron enzyme, Egt1, makes use of cysteine instead of γ-Glu-Cys as the substrate. Such a change of substrate preference eliminates the competition between ergothioneine and glutathione biosyntheses. In addition, we have identified the N. crassa C–S lyase (NCU11365) and reconstituted its activity in vitro, which makes the future ergothioneine production through metabolic engineering feasible. PMID:25275953
Thoughts on the Teaching of Metabolism
ERIC Educational Resources Information Center
Metzger, Robert P.
2006-01-01
Systems biology, metabolomics, metabolic engineering, and other recent developments in biochemistry suggest that future biochemists will require a detailed familiarity with the compounds and pathways of intermediary metabolism and their biochemical control. The challenge to the biochemistry instructor is the presentation of metabolic pathways in a…
The Molecular Basis of Communication within the Cell.
ERIC Educational Resources Information Center
Berridge, Michael J.
1985-01-01
Only a few substances serve as signals within cells; this indicates that internal signal pathways are remarkably universal. The variety of physiological and biochemical processes regulated by known messengers is discussed along with chemical structures, pathways, inositol-lipid cycles, and cell growth regulation. (DH)
Biochemical-Pathway Diversity in Archabacteria
1988-06-28
8a NAME OF_ FUNDINGISFF0N Gr ... FFICE SYMBOL 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ORGANIZATION (If applicable) Office of Naval Researh ONR... BIOLOGY AND EVOLUTION OF MICROORGANISMS (July 24-28. 1989) in a talk entitled "Evolution of Metabolic Pathways". TRAINING ACTIVITIES: Dr. Raj Bhatnagar, a
Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow
Brunk, Elizabeth; George, Kevin W.; Alonso-Gutierrez, Jorge; ...
2016-05-19
Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proofmore » of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.« less
The fractional diffusion limit of a kinetic model with biochemical pathway
NASA Astrophysics Data System (ADS)
Perthame, Benoît; Sun, Weiran; Tang, Min
2018-06-01
Kinetic-transport equations that take into account the intracellular pathways are now considered as the correct description of bacterial chemotaxis by run and tumble. Recent mathematical studies have shown their interest and their relations to more standard models. Macroscopic equations of Keller-Segel type have been derived using parabolic scaling. Due to the randomness of receptor methylation or intracellular chemical reactions, noise occurs in the signaling pathways and affects the tumbling rate. Then comes the question to understand the role of an internal noise on the behavior of the full population. In this paper we consider a kinetic model for chemotaxis which includes biochemical pathway with noises. We show that under proper scaling and conditions on the tumbling frequency as well as the form of noise, fractional diffusion can arise in the macroscopic limits of the kinetic equation. This gives a new mathematical theory about how long jumps can be due to the internal noise of the bacteria.
Fei, Chenyi; Cao, Yuansheng; Ouyang, Qi; Tu, Yuhai
2018-04-12
Biological systems need to function accurately in the presence of strong noise and at the same time respond sensitively to subtle external cues. Here we study design principles in biochemical oscillatory circuits to achieve these two seemingly incompatible goals. We show that energy dissipation can enhance phase sensitivity linearly by driving the phase-amplitude coupling and increase timing accuracy by suppressing phase diffusion. Two general design principles in the key underlying reaction loop formed by two antiparallel pathways are found to optimize oscillation performance with a given energy budget: balancing the forward-to-backward flux ratio between the two pathways to reduce phase diffusion and maximizing the net flux of the phase-advancing pathway relative to that of the phase-retreating pathway to enhance phase sensitivity. Experimental evidences consistent with these design principles are found in the circadian clock of cyanobacteria. Future experiments to test the predicted dependence of phase sensitivity on energy dissipation are proposed.
An update on the Enzyme Portal: an integrative approach for exploring enzyme knowledge
Onwubiko, J.; Zaru, R.; Rosanoff, S.; Antunes, R.; Bingley, M.; Watkins, X.; O'Donovan, C.; Martin, M. J.
2017-01-01
Abstract Enzymes are a key part of life processes and are increasingly important for various areas of research such as medicine, biotechnology, bioprocessing and drug research. The goal of the Enzyme Portal is to provide an interface to all European Bioinformatics Institute (EMBL-EBI) data about enzymes (de Matos, P., et al., (2013), BMC Bioinformatics, 14 (1), 103). These data include enzyme function, sequence features and family classification, protein structure, reactions, pathways, small molecules, diseases and the associated literature. The sources of enzyme data are: the UniProt Knowledgebase (UniProtKB) (UniProt Consortium, 2015), the Protein Data Bank in Europe (PDBe), (Valenkar, S., et al., Nucleic Acids Res.2016; 44, D385–D395) Rhea—a database of enzyme-catalysed reactions (Morgat, A., et al., Nucleic Acids Res. 2015; 43, D459-D464), Reactome—a database of biochemical pathways (Fabregat, A., et al., Nucleic Acids Res. 2016; 44, D481–D487), IntEnz—a resource with enzyme nomenclature information (Fleischmann, A., et al., Nucleic Acids Res. 2004 32, D434–D437) and ChEBI (Hastings, J., et al., Nucleic Acids Res. 2013) and ChEMBL (Bento, A. P., et al., Nucleic Acids Res. 201442, 1083–1090)—resources which contain information about small-molecule chemistry and bioactivity. This article describes the redesign of Enzyme Portal and the increased functionality added to maximise integration and interpretation of these data. Use case examples of the Enzyme Portal and the versatile workflows its supports are illustrated. We welcome the suggestion of new resources for integration. PMID:28158609
An update on the Enzyme Portal: an integrative approach for exploring enzyme knowledge.
Pundir, S; Onwubiko, J; Zaru, R; Rosanoff, S; Antunes, R; Bingley, M; Watkins, X; O'Donovan, C; Martin, M J
2017-03-01
Enzymes are a key part of life processes and are increasingly important for various areas of research such as medicine, biotechnology, bioprocessing and drug research. The goal of the Enzyme Portal is to provide an interface to all European Bioinformatics Institute (EMBL-EBI) data about enzymes (de Matos, P., et al. , (2013), BMC Bioinformatics , (1), 103). These data include enzyme function, sequence features and family classification, protein structure, reactions, pathways, small molecules, diseases and the associated literature. The sources of enzyme data are: the UniProt Knowledgebase (UniProtKB) (UniProt Consortium, 2015), the Protein Data Bank in Europe (PDBe), (Valenkar, S., et al ., Nucleic Acids Res. 2016; , D385-D395) Rhea-a database of enzyme-catalysed reactions (Morgat, A., et al ., Nucleic Acids Res. 2015; , D459-D464), Reactome-a database of biochemical pathways (Fabregat, A., et al ., Nucleic Acids Res. 2016; , D481-D487), IntEnz-a resource with enzyme nomenclature information (Fleischmann, A., et al ., Nucleic Acids Res. 2004 , D434-D437) and ChEBI (Hastings, J., et al ., Nucleic Acids Res. 2013) and ChEMBL (Bento, A. P., et al ., Nucleic Acids Res. 2014 , 1083-1090)-resources which contain information about small-molecule chemistry and bioactivity. This article describes the redesign of Enzyme Portal and the increased functionality added to maximise integration and interpretation of these data. Use case examples of the Enzyme Portal and the versatile workflows its supports are illustrated. We welcome the suggestion of new resources for integration. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Geer, Lewis Y.; Marchler-Bauer, Aron; Geer, Renata C.; Han, Lianyi; He, Jane; He, Siqian; Liu, Chunlei; Shi, Wenyao; Bryant, Stephen H.
2010-01-01
The NCBI BioSystems database, found at http://www.ncbi.nlm.nih.gov/biosystems/, centralizes and cross-links existing biological systems databases, increasing their utility and target audience by integrating their pathways and systems into NCBI resources. This integration allows users of NCBI’s Entrez databases to quickly categorize proteins, genes and small molecules by metabolic pathway, disease state or other BioSystem type, without requiring time-consuming inference of biological relationships from the literature or multiple experimental datasets. PMID:19854944
PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.
Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela
2018-01-04
The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
1-CMDb: A Curated Database of Genomic Variations of the One-Carbon Metabolism Pathway.
Bhat, Manoj K; Gadekar, Veerendra P; Jain, Aditya; Paul, Bobby; Rai, Padmalatha S; Satyamoorthy, Kapaettu
2017-01-01
The one-carbon metabolism pathway is vital in maintaining tissue homeostasis by driving the critical reactions of folate and methionine cycles. A myriad of genetic and epigenetic events mark the rate of reactions in a tissue-specific manner. Integration of these to predict and provide personalized health management requires robust computational tools that can process multiomics data. The DNA sequences that may determine the chain of biological events and the endpoint reactions within one-carbon metabolism genes remain to be comprehensively recorded. Hence, we designed the one-carbon metabolism database (1-CMDb) as a platform to interrogate its association with a host of human disorders. DNA sequence and network information of a total of 48 genes were extracted from a literature survey and KEGG pathway that are involved in the one-carbon folate-mediated pathway. The information generated, collected, and compiled for all these genes from the UCSC genome browser included the single nucleotide polymorphisms (SNPs), CpGs, copy number variations (CNVs), and miRNAs, and a comprehensive database was created. Furthermore, a significant correlation analysis was performed for SNPs in the pathway genes. Detailed data of SNPs, CNVs, CpG islands, and miRNAs for 48 folate pathway genes were compiled. The SNPs in CNVs (9670), CpGs (984), and miRNAs (14) were also compiled for all pathway genes. The SIFT score, the prediction and PolyPhen score, as well as the prediction for each of the SNPs were tabulated and represented for folate pathway genes. Also included in the database for folate pathway genes were the links to 124 various phenotypes and disease associations as reported in the literature and from publicly available information. A comprehensive database was generated consisting of genomic elements within and among SNPs, CNVs, CpGs, and miRNAs of one-carbon metabolism pathways to facilitate (a) single source of information and (b) integration into large-genome scale network analysis to be developed in the future by the scientific community. The database can be accessed at http://slsdb.manipal.edu/ocm/. © 2017 S. Karger AG, Basel.
Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote
2016-01-01
Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Zachary A.; Lu, Justin; Drager, Andreas; ...
2015-10-17
In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.
2016-01-01
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456
VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.
Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles
2007-07-01
With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.
Giridharan, Nappan Veettil
2012-01-01
Purpose Obesity is a major public health problem worldwide, and of late, epidemiological studies indicate a preponderance of cataracts under obesity conditions. Although cataract is a multifactorial disorder and various biochemical mechanisms have been proposed, the influence of obesity on cataractogenesis has yet to be investigated. In such a scenario, a suitable animal model that develops cataract following the onset of obesity will be a welcome tool for biomedical research. Therefore, we investigated the molecular and biochemical basis for predisposition to cataract in the obese mutant rat models established in our institute because 15%–20% of these rats develop cataracts spontaneously as they reach 12–15 months of age. Methods We analyzed the major biochemical pathways in the normal lenses of different age groups of our obese mutant rat strains, Wistar/Obese (WNIN/Ob) and WNIN/GR-Ob, the former with euglycemia and the latter with an additional impaired glucose tolerance trait. In addition, sorbitol levels were estimated in the cataractous lenses of the obese rats. Results Except for the polyol pathway, all the principal pathways of the lens remained unaltered. Therefore, sorbitol levels were found to be high in the normal eye lenses of obese rats (WNIN/Ob and WNIN/GR-Ob) compared to their lean controls from three months of age onwards. Between WNIN/Ob and WNIN/GR-Ob, the levels of sorbitol were higher in the latter, suggesting a synergistic effect of impaired glucose tolerance along with obesity in the activation of the sorbitol pathway. Either way, an elevated sorbitol pathway seemed to be the predisposing factor responsible for cataract formation in these mutant rats. Conclusions Activation of the sorbitol pathway indeed enhances the risk of cataract development in conditions such as metabolic syndrome. These rat models thus may be valuable tools for investigating obesity-associated cataract and for developing intervention strategies, based on these findings. PMID:22393276
Reddy, Paduru Yadagiri; Giridharan, Nappan Veettil; Reddy, Geereddy Bhanuprakash
2012-01-01
Obesity is a major public health problem worldwide, and of late, epidemiological studies indicate a preponderance of cataracts under obesity conditions. Although cataract is a multifactorial disorder and various biochemical mechanisms have been proposed, the influence of obesity on cataractogenesis has yet to be investigated. In such a scenario, a suitable animal model that develops cataract following the onset of obesity will be a welcome tool for biomedical research. Therefore, we investigated the molecular and biochemical basis for predisposition to cataract in the obese mutant rat models established in our institute because 15%-20% of these rats develop cataracts spontaneously as they reach 12-15 months of age. We analyzed the major biochemical pathways in the normal lenses of different age groups of our obese mutant rat strains, Wistar/Obese (WNIN/Ob) and WNIN/GR-Ob, the former with euglycemia and the latter with an additional impaired glucose tolerance trait. In addition, sorbitol levels were estimated in the cataractous lenses of the obese rats. Except for the polyol pathway, all the principal pathways of the lens remained unaltered. Therefore, sorbitol levels were found to be high in the normal eye lenses of obese rats (WNIN/Ob and WNIN/GR-Ob) compared to their lean controls from three months of age onwards. Between WNIN/Ob and WNIN/GR-Ob, the levels of sorbitol were higher in the latter, suggesting a synergistic effect of impaired glucose tolerance along with obesity in the activation of the sorbitol pathway. Either way, an elevated sorbitol pathway seemed to be the predisposing factor responsible for cataract formation in these mutant rats. Activation of the sorbitol pathway indeed enhances the risk of cataract development in conditions such as metabolic syndrome. These rat models thus may be valuable tools for investigating obesity-associated cataract and for developing intervention strategies, based on these findings.
Bland, Cassidy L; Byrne-Hoffman, Christina N; Fernandez, Audry; Rellick, Stephanie L; Deng, Wentao; Klinke, David J
2018-03-01
While recent clinical studies demonstrate the promise of cancer immunotherapy, a barrier for broadening the clinical benefit is identifying how tumors locally suppress cytotoxic immunity. As an emerging mode of intercellular communication, exosomes secreted by malignant cells can deliver a complex payload of coding and noncoding RNA to cells within the tumor microenvironment. Here, we quantified the RNA payload within tumor-derived exosomes and the resulting dynamic transcriptomic response to cytotoxic T cells upon exosome delivery to better understand how tumor-derived exosomes can alter immune cell function. Exosomes derived from B16F0 melanoma cells were enriched for a subset of coding and noncoding RNAs that did not reflect the abundance in the parental cell. Upon exosome delivery, RNAseq revealed the dynamic changes in the transcriptome of CTLL2 cytotoxic T cells. In analyzing transiently coexpressed gene clusters, pathway enrichment suggested that the B16F0 exosomal payload altered mitochondrial respiration, which was confirmed independently, and upregulated genes associated with the Notch signaling pathway. Interestingly, exosomal miRNA appeared to have no systematic effect on downregulating target mRNA levels. Gene expression data are available in the GEO database under the accession SuperSeries number GSE102951. © 2018 Federation of European Biochemical Societies.
USDA-ARS?s Scientific Manuscript database
Cotton (Gossypium hirsutum L.) provides a major source of oil for food and feed industries, but little was known about the oil biosynthesis pathway in cottonseed. Towards understanding the biochemical pathway of oil accumulation in cottonseed, this study focused on phosphatidic acid phosphatase (PAP...
Meetei, Potshangbam Angamba; Singh, Pankaj; Nongdam, Potshangbam; Prabhu, N Prakash; Rathore, RS; Vindal, Vaibhav
2012-01-01
The North-East region of India is one of the twelve mega biodiversity region, containing many rare and endangered species. A curated database of medicinal and aromatic plants from the regions called NeMedPlant is developed. The database contains traditional, scientific and medicinal information about plants and their active constituents, obtained from scholarly literature and local sources. The database is cross-linked with major biochemical databases and analytical tools. The integrated database provides resource for investigations into hitherto unexplored medicinal plants and serves to speed up the discovery of natural productsbased drugs. Availability The database is available for free at http://bif.uohyd.ac.in/nemedplant/orhttp://202.41.85.11/nemedplant/ PMID:22419844
Gluconeogenesis: An ancient biochemical pathway with a new twist
Miyamoto, Tetsuya; Amrein, Hubert
2017-01-01
ABSTRACT Synthesis of sugars from simple carbon sources is critical for survival of animals under limited nutrient availability. Thus, sugar-synthesizing enzymes should be present across the entire metazoan spectrum. Here, we explore the evolution of glucose and trehalose synthesis using a phylogenetic analysis of enzymes specific for the two pathways. Our analysis reveals that the production of trehalose is the more ancestral biochemical process, found in single cell organisms and primitive metazoans, but also in insects. The gluconeogenic-specific enzyme glucose-6-phosphatase (G6Pase) first appears in Cnidaria, but is also present in Echinodermata, Mollusca and Vertebrata. Intriguingly, some species of nematodes and arthropods possess the genes for both pathways. Moreover, expression data from Drosophila suggests that G6Pase and, hence, gluconeogenesis, initially had a neuronal function. We speculate that in insects—and possibly in some vertebrates—gluconeogenesis may be used as a means of neuronal signaling. PMID:28121487
Gluconeogenesis: An ancient biochemical pathway with a new twist.
Miyamoto, Tetsuya; Amrein, Hubert
2017-07-03
Synthesis of sugars from simple carbon sources is critical for survival of animals under limited nutrient availability. Thus, sugar-synthesizing enzymes should be present across the entire metazoan spectrum. Here, we explore the evolution of glucose and trehalose synthesis using a phylogenetic analysis of enzymes specific for the two pathways. Our analysis reveals that the production of trehalose is the more ancestral biochemical process, found in single cell organisms and primitive metazoans, but also in insects. The gluconeogenic-specific enzyme glucose-6-phosphatase (G6Pase) first appears in Cnidaria, but is also present in Echinodermata, Mollusca and Vertebrata. Intriguingly, some species of nematodes and arthropods possess the genes for both pathways. Moreover, expression data from Drosophila suggests that G6Pase and, hence, gluconeogenesis, initially had a neuronal function. We speculate that in insects-and possibly in some vertebrates-gluconeogenesis may be used as a means of neuronal signaling.
Biochemical Basis of Sestrin Physiological Activities
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ho, Allison; Cho, Chun-Seok; Namkoong, Sim
Excessive accumulation of reactive oxygen species (ROS) and chronic activation of mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) are well-characterized promoters of aging and age-associated degenerative pathologies. Sestrins, a family of highly conserved stress-inducible proteins, are important negative regulators of both ROS and mTORC1 signaling pathways; however, the mechanistic basis of how Sestrins suppress these pathways remains elusive. In the past couple of years, breakthrough discoveries about Sestrin signaling and its molecular nature have markedly increased our biochemical understanding of Sestrin function. These discoveries have also uncovered new potential therapeutic strategies that may eventually enable us to attenuate agingmore » and age-associated diseases.« less
SASD: the Synthetic Alternative Splicing Database for identifying novel isoform from proteomics
2013-01-01
Background Alternative splicing is an important and widespread mechanism for generating protein diversity and regulating protein expression. High-throughput identification and analysis of alternative splicing in the protein level has more advantages than in the mRNA level. The combination of alternative splicing database and tandem mass spectrometry provides a powerful technique for identification, analysis and characterization of potential novel alternative splicing protein isoforms from proteomics. Therefore, based on the peptidomic database of human protein isoforms for proteomics experiments, our objective is to design a new alternative splicing database to 1) provide more coverage of genes, transcripts and alternative splicing, 2) exclusively focus on the alternative splicing, and 3) perform context-specific alternative splicing analysis. Results We used a three-step pipeline to create a synthetic alternative splicing database (SASD) to identify novel alternative splicing isoforms and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. First, we extracted information on gene structures of all genes in the Ensembl Genes 71 database and incorporated the Integrated Pathway Analysis Database. Then, we compiled artificial splicing transcripts. Lastly, we translated the artificial transcripts into alternative splicing peptides. The SASD is a comprehensive database containing 56,630 genes (Ensembl gene IDs), 95,260 transcripts (Ensembl transcript IDs), and 11,919,779 Alternative Splicing peptides, and also covering about 1,956 pathways, 6,704 diseases, 5,615 drugs, and 52 organs. The database has a web-based user interface that allows users to search, display and download a single gene/transcript/protein, custom gene set, pathway, disease, drug, organ related alternative splicing. Moreover, the quality of the database was validated with comparison to other known databases and two case studies: 1) in liver cancer and 2) in breast cancer. Conclusions The SASD provides the scientific community with an efficient means to identify, analyze, and characterize novel Exon Skipping and Intron Retention protein isoforms from mass spectrometry and interpret them at the context of pathway, disease, drug and organ specificity or custom gene set with maximum coverage and exclusive focus on alternative splicing. PMID:24267658
Abdelrahman, Mostafa; El-Sayed, Magdi; Sato, Shusei; Hirakawa, Hideki; Ito, Shin-ichi; Tanaka, Keisuke; Mine, Yoko; Sugiyama, Nobuo; Suzuki, Minoru; Yamauchi, Naoki
2017-01-01
The genus Allium is a rich source of steroidal saponins, and its medicinal properties have been attributed to these bioactive compounds. The saponin compounds with diverse structures play a pivotal role in Allium’s defense mechanism. Despite numerous studies on the occurrence and chemical structure of steroidal saponins, their biosynthetic pathway in Allium species is poorly understood. The monosomic addition lines (MALs) of the Japanese bunching onion (A. fistulosum, FF) with an extra chromosome from the shallot (A. cepa Aggregatum group, AA) are powerful genetic resources that enable us to understand many physiological traits of Allium. In the present study, we were able to isolate and identify Alliospiroside A saponin compound in A. fistulosum with extra chromosome 2A from shallot (FF2A) and its role in the defense mechanism against Fusarium pathogens. Furthermore, to gain molecular insight into the Allium saponin biosynthesis pathway, high-throughput RNA-Seq of the root, bulb, and leaf of AA, MALs, and FF was carried out using Illumina's HiSeq 2500 platform. An open access Allium Transcript Database (Allium TDB, http://alliumtdb.kazusa.or.jp) was generated based on RNA-Seq data. The resulting assembled transcripts were functionally annotated, revealing 50 unigenes involved in saponin biosynthesis. Differential gene expression (DGE) analyses of AA and MALs as compared with FF (as a control) revealed a strong up-regulation of the saponin downstream pathway, including cytochrome P450, glycosyltransferase, and beta-glucosidase in chromosome 2A. An understanding of the saponin compounds and biosynthesis-related genes would facilitate the development of plants with unique saponin content and, subsequently, improved disease resistance. PMID:28800607
Abdelrahman, Mostafa; El-Sayed, Magdi; Sato, Shusei; Hirakawa, Hideki; Ito, Shin-Ichi; Tanaka, Keisuke; Mine, Yoko; Sugiyama, Nobuo; Suzuki, Yutaka; Yamauchi, Naoki; Shigyo, Masayoshi
2017-01-01
The genus Allium is a rich source of steroidal saponins, and its medicinal properties have been attributed to these bioactive compounds. The saponin compounds with diverse structures play a pivotal role in Allium's defense mechanism. Despite numerous studies on the occurrence and chemical structure of steroidal saponins, their biosynthetic pathway in Allium species is poorly understood. The monosomic addition lines (MALs) of the Japanese bunching onion (A. fistulosum, FF) with an extra chromosome from the shallot (A. cepa Aggregatum group, AA) are powerful genetic resources that enable us to understand many physiological traits of Allium. In the present study, we were able to isolate and identify Alliospiroside A saponin compound in A. fistulosum with extra chromosome 2A from shallot (FF2A) and its role in the defense mechanism against Fusarium pathogens. Furthermore, to gain molecular insight into the Allium saponin biosynthesis pathway, high-throughput RNA-Seq of the root, bulb, and leaf of AA, MALs, and FF was carried out using Illumina's HiSeq 2500 platform. An open access Allium Transcript Database (Allium TDB, http://alliumtdb.kazusa.or.jp) was generated based on RNA-Seq data. The resulting assembled transcripts were functionally annotated, revealing 50 unigenes involved in saponin biosynthesis. Differential gene expression (DGE) analyses of AA and MALs as compared with FF (as a control) revealed a strong up-regulation of the saponin downstream pathway, including cytochrome P450, glycosyltransferase, and beta-glucosidase in chromosome 2A. An understanding of the saponin compounds and biosynthesis-related genes would facilitate the development of plants with unique saponin content and, subsequently, improved disease resistance.
Reconstruction of biological pathways and metabolic networks from in silico labeled metabolites.
Hadadi, Noushin; Hafner, Jasmin; Soh, Keng Cher; Hatzimanikatis, Vassily
2017-01-01
Reaction atom mappings track the positional changes of all of the atoms between the substrates and the products as they undergo the biochemical transformation. However, information on atom transitions in the context of metabolic pathways is not widely available in the literature. The understanding of metabolic pathways at the atomic level is of great importance as it can deconvolute the overlapping catabolic/anabolic pathways resulting in the observed metabolic phenotype. The automated identification of atom transitions within a metabolic network is a very challenging task since the degree of complexity of metabolic networks dramatically increases when we transit from metabolite-level studies to atom-level studies. Despite being studied extensively in various approaches, the field of atom mapping of metabolic networks is lacking an automated approach, which (i) accounts for the information of reaction mechanism for atom mapping and (ii) is extendable from individual atom-mapped reactions to atom-mapped reaction networks. Hereby, we introduce a computational framework, iAM.NICE (in silico Atom Mapped Network Integrated Computational Explorer), for the systematic atom-level reconstruction of metabolic networks from in silico labelled substrates. iAM.NICE is to our knowledge the first automated atom-mapping algorithm that is based on the underlying enzymatic biotransformation mechanisms, and its application goes beyond individual reactions and it can be used for the reconstruction of atom-mapped metabolic networks. We illustrate the applicability of our method through the reconstruction of atom-mapped reactions of the KEGG database and we provide an example of an atom-level representation of the core metabolic network of E. coli. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Zain, Maryam; Awan, Fazli Rabbi
2014-09-01
Diabetes mellitus is a multifactorial disorder of hyperglycemia caused by a combination of biochemical, molecular and genetic factors, which leads to the dysfunction of various organs including kidneys. Diabetic nephropathy (DN) is one of the microvascular complications of diabetes that results due to poor glycemic control. Several molecular and biochemical pathways have been implicated in the pathogenesis of DN. Of these, the Renin Angiotensin Aldosterone System (RAAS) is considered as a key pathway. RAAS involves various subsystems which contribute to the development of DN. Mutations in several genes of the RAAS pathway have been associated with the development of DN. These genes or their products present them as therapeutic targets for potent drugs to control or prevent DN, and development of new drugs for targeting the RAAS. Drugs in use for DN are mainly the Angiotensin Converting Enzyme (ACE) inhibitors, Angiotensin Receptors Blockers (ARB) and renin inhibitors which play important roles in reducing DN. Hence, the present review is focused on the pathophysiology and genetic factors for DN by exploring the RAAS pathway and emphasizing the benefits of blocking this pathway to control and prevent DN.
Rouigari, Maedeh; Dehbashi, Moein; Ghaedi, Kamran; Pourhossein, Meraj
2018-07-01
For the first time, we used molecular signaling pathway enrichment analysis to determine possible involvement of miR-126 and IRS-1 in neurotrophin pathway. In this prospective study, Validated and predicted targets (targetome) of miR-126 were collected following searching miRtarbase (http://mirtarbase.mbc.nctu.edu.tw/) and miRWalk 2.0 databases, respectively. Then, approximate expression of miR-126 targeting in Glioma tissue was examined using UniGene database (http://www.ncbi. nlm.nih.gov/unigene). In silico molecular pathway enrichment analysis was carried out by DAVID 6.7 database (http://david. abcc.ncifcrf.gov/) to explore which signaling pathway is related to miR-126 targeting and how miR-126 attributes to glioma development. MiR-126 exerts a variety of functions in cancer pathogenesis via suppression of expression of target gene including PI3K, KRAS, EGFL7, IRS-1 and VEGF. Our bioinformatic studies implementing DAVID database, showed the involvement of miR-126 target genes in several signaling pathways including cancer pathogenesis, neurotrophin functions, Glioma formation, insulin function, focal adhesion production, chemokine synthesis and secretion and regulation of the actin cytoskeleton. Taken together, we concluded that miR-126 enhances the formation of glioma cancer stem cell probably via down regulation of IRS-1 in neurotrophin signaling pathway. Copyright© by Royan Institute. All rights reserved.
Amelogenin test: From forensics to quality control in clinical and biochemical genomics.
Francès, F; Portolés, O; González, J I; Coltell, O; Verdú, F; Castelló, A; Corella, D
2007-01-01
The increasing number of samples from the biomedical genetic studies and the number of centers participating in the same involves increasing risk of mistakes in the different sample handling stages. We have evaluated the usefulness of the amelogenin test for quality control in sample identification. Amelogenin test (frequently used in forensics) was undertaken on 1224 individuals participating in a biomedical study. Concordance between referred sex in the database and amelogenin test was estimated. Additional sex-error genetic detecting systems were developed. The overall concordance rate was 99.84% (1222/1224). Two samples showed a female amelogenin test outcome, being codified as males in the database. The first, after checking sex-specific biochemical and clinical profile data was found to be due to a codification error in the database. In the second, after checking the database, no apparent error was discovered because a correct male profile was found. False negatives in amelogenin male sex determination were discarded by additional tests, and feminine sex was confirmed. A sample labeling error was revealed after a new DNA extraction. The amelogenin test is a useful quality control tool for detecting sex-identification errors in large genomic studies, and can contribute to increase its validity.
Chatonnet, A; Hotelier, T; Cousin, X
1999-05-14
Cholinesterases are targets for organophosphorus compounds which are used as insecticides, chemical warfare agents and drugs for the treatment of disease such as glaucoma, or parasitic infections. The widespread use of these chemicals explains the growing of this area of research and the ever increasing number of sequences, structures, or biochemical data available. Future advances will depend upon effective management of existing information as well as upon creation of new knowledge. The ESTHER database goal is to facilitate retrieval and comparison of data about structure and function of proteins presenting the alpha/beta hydrolase fold. Protein engineering and in vitro production of enzymes allow direct comparison of biochemical parameters. Kinetic parameters of enzymatic reactions are now included in the database. These parameters can be searched and compared with a table construction tool. ESTHER can be reached through internet (http://www.ensam.inra.fr/cholinesterase). The full database or the specialised X-window Client-server system can be downloaded from our ftp server (ftp://ftp.toulouse.inra.fr./pub/esther). Forms can be used to send updates or corrections directly from the web.
Xu, Jie; Hu, Feng-Lin; Wang, Wei; Wan, Xiao-Chun; Bao, Guan-Hu
2015-11-01
Fu brick tea (FBT) is a unique post-fermented tea product which is fermented with fungi during the manufacturing process. In this study, we investigated the biochemical compositional changes occurring during the microbial fermentation process (MFP) of FBT based on non-targeted LC-MS, which was a comprehensive and unbiased methodology. Our data analysis took a two-phase approach: (1) comparison of FBT with other tea products using PCA analysis to exhibit the characteristic effect of MFP on the formation of Fu brick tea and (2) comparison of tea samples throughout the MFP of FBT to elucidate the possible key metabolic pathways produced by the fungi. Non-targeted LC-MS analysis clearly distinguished FBT with other tea samples and highlighted some interesting metabolic pathways during the MFP including B ring fission catechin. Our study demonstrated that those fungi had a significant influence on the biochemical profiles in the FBT and consequently contributed to its unique quality. Copyright © 2014 Elsevier Ltd. All rights reserved.
GOBASE—a database of mitochondrial and chloroplast information
O'Brien, Emmet A.; Badidi, Elarbi; Barbasiewicz, Ania; deSousa, Cristina; Lang, B. Franz; Burger, Gertraud
2003-01-01
GOBASE is a relational database containing integrated sequence, RNA secondary structure and biochemical and taxonomic information about organelles. GOBASE release 6 (summer 2002) contains over 130 000 mitochondrial sequences, an increase of 37% over the previous release, and more than 30 000 chloroplast sequences in a new auxiliary database. To handle this flood of new data, we have designed and implemented GOpop, a Java system for population and verification of the database. We have also implemented a more powerful and flexible user interface using the PHP programming language. http://megasun.bch.umontreal.ca/gobase/gobase.html. PMID:12519975
The Listeria monocytogenes strain 10403S BioCyc database
Orsi, Renato H.; Bergholz, Teresa M.; Wiedmann, Martin; Boor, Kathryn J.
2015-01-01
Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database. Database URL: http://biocyc.org/organism-summary?object=10403S_RAST PMID:25819074
Virtual Interactomics of Proteins from Biochemical Standpoint
Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel
2012-01-01
Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109
Proteomics Unveils Fibroblast-Cardiomyocyte Lactate Shuttle and Hexokinase Paradox in Mouse Muscles.
Rakus, Dariusz; Gizak, Agnieszka; Wiśniewski, Jacek R
2016-08-05
Quantitative mapping, given in biochemically interpretable units such as mol per mg of total protein, of tissue-specific proteomes is prerequisite for the analysis of any process in cells. We applied label- and standard-free proteomics to characterize three types of striated muscles: white, red, and cardiac muscle. The analysis presented here uncovers several unexpected and novel features of striated muscles. In addition to differences in protein expression levels, the three muscle types substantially differ in their patterns of basic metabolic pathways and isoforms of regulatory proteins. Importantly, some of the conclusions drawn on the basis of our results, such as the potential existence of a "fibroblast-cardiomyocyte lactate shuttle" and the "hexokinase paradox" point to the necessity of reinterpretation of some basic aspects of striated muscle metabolism. The data presented here constitute a powerful database and a resource for future studies of muscle physiology and for the design of pharmaceutics for the treatment of muscular disorders.
cPath: open source software for collecting, storing, and querying biological pathways.
Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris
2006-11-13
Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.
Casás-Selves, Matias; Zhang, Andrew X; Dowling, James E; Hallén, Stefan; Kawatkar, Aarti; Pace, Nicholas J; Denz, Christopher R; Pontz, Timothy; Garahdaghi, Farzin; Cao, Qing; Sabirsh, Alan; Thakur, Kumar; O'Connell, Nichole; Hu, Jun; Cornella-Taracido, Iván; Weerapana, Eranthie; Zinda, Michael; Goodnow, Robert A; Castaldi, M Paola
2017-06-21
Wnt signaling is critical for development, cell proliferation and differentiation, and mutations in this pathway resulting in constitutive signaling have been implicated in various cancers. A pathway screen using a Wnt-dependent reporter identified a chemical series based on a 1,2,3-thiadiazole-5-carboxamide (TDZ) core with sub-micromolar potency. Herein we report a comprehensive mechanism-of-action deconvolution study toward identifying the efficacy target(s) and biological implication of this chemical series involving bottom-up quantitative chemoproteomics, cell biology, and biochemical methods. Through observing the effects of our probes on metabolism and performing confirmatory cellular and biochemical assays, we found that this chemical series inhibits ATP synthesis by uncoupling the mitochondrial potential. Affinity chemoproteomics experiments identified sarco(endo)plasmic reticulum Ca 2+ -dependent ATPase (SERCA2) as a binding partner of the TDZ series, and subsequent validation studies suggest that the TDZ series can act as ionophores through SERCA2 toward Wnt pathway inhibition. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Exploring consumer exposure pathways and patterns of use for chemicals in the environment through the Chemical/Product Categories Database (CPCat) (Presented by: Kathie Dionisio, Sc.D., NERL, US EPA, Research Triangle Park, NC (1/23/2014).
Dhanasekaran, A Ranjitha; Pearson, Jon L; Ganesan, Balasubramanian; Weimer, Bart C
2015-02-25
Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism's genome as a database restricts metabolite identification to only those compounds that the organism can produce. To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment's MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis. Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.
Java Web Simulation (JWS); a web based database of kinetic models.
Snoep, J L; Olivier, B G
2002-01-01
Software to make a database of kinetic models accessible via the internet has been developed and a core database has been set up at http://jjj.biochem.sun.ac.za/. This repository of models, available to everyone with internet access, opens a whole new way in which we can make our models public. Via the database, a user can change enzyme parameters and run time simulations or steady state analyses. The interface is user friendly and no additional software is necessary. The database currently contains 10 models, but since the generation of the program code to include new models has largely been automated the addition of new models is straightforward and people are invited to submit their models to be included in the database.
Elucidation of metabolic pathways from enzyme classification data.
McDonald, Andrew G; Tipton, Keith F
2014-01-01
The IUBMB Enzyme List is widely used by other databases as a source for avoiding ambiguity in the recognition of enzymes as catalytic entities. However, it was not designed for metabolic pathway tracing, which has become increasingly important in systems biology. A Reactions Database has been created from the material in the Enzyme List to allow reactions to be searched by substrate/product, and pathways to be traced from any selected starting/seed substrate. An extensive synonym glossary allows searches by many of the alternative names, including accepted abbreviations, by which a chemical compound may be known. This database was necessary for the development of the application Reaction Explorer ( http://www.reaction-explorer.org ), which was written in Real Studio ( http://www.realsoftware.com/realstudio/ ) to search the Reactions Database and draw metabolic pathways from reactions selected by the user. Having input the name of the starting compound (the "seed"), the user is presented with a list of all reactions containing that compound and then selects the product of interest as the next point on the ensuing graph. The pathway diagram is then generated as the process iterates. A contextual menu is provided, which allows the user: (1) to remove a compound from the graph, along with all associated links; (2) to search the reactions database again for additional reactions involving the compound; (3) to search for the compound within the Enzyme List.
Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii.
Boyle, Nanette R; Morgan, John A
2009-01-07
Photosynthetic organisms convert atmospheric carbon dioxide into numerous metabolites along the pathways to make new biomass. Aquatic photosynthetic organisms, which fix almost half of global inorganic carbon, have great potential: as a carbon dioxide fixation method, for the economical production of chemicals, or as a source for lipids and starch which can then be converted to biofuels. To harness this potential through metabolic engineering and to maximize production, a more thorough understanding of photosynthetic metabolism must first be achieved. A model algal species, C. reinhardtii, was chosen and the metabolic network reconstructed. Intracellular fluxes were then calculated using flux balance analysis (FBA). The metabolic network of primary metabolism for a green alga, C. reinhardtii, was reconstructed using genomic and biochemical information. The reconstructed network accounts for the intracellular localization of enzymes to three compartments and includes 484 metabolic reactions and 458 intracellular metabolites. Based on BLAST searches, one newly annotated enzyme (fructose-1,6-bisphosphatase) was added to the Chlamydomonas reinhardtii database. FBA was used to predict metabolic fluxes under three growth conditions, autotrophic, heterotrophic and mixotrophic growth. Biomass yields ranged from 28.9 g per mole C for autotrophic growth to 15 g per mole C for heterotrophic growth. The flux balance analysis model of central and intermediary metabolism in C. reinhardtii is the first such model for algae and the first model to include three metabolically active compartments. In addition to providing estimates of intracellular fluxes, metabolic reconstruction and modelling efforts also provide a comprehensive method for annotation of genome databases. As a result of our reconstruction, one new enzyme was annotated in the database and several others were found to be missing; implying new pathways or non-conserved enzymes. The use of FBA to estimate intracellular fluxes also provides flux values that can be used as a starting point for rational engineering of C. reinhardtii. From these initial estimates, it is clear that aerobic heterotrophic growth on acetate has a low yield on carbon, while mixotrophically and autotrophically grown cells are significantly more carbon efficient.
Zhao, Daqiu; Jiang, Yao; Ning, Chuanlong; Meng, Jiasong; Lin, Shasha; Ding, Wen; Tao, Jun
2014-08-19
Herbaceous peony (Paeonia lactiflora Pall.) is a traditional flower in China and a wedding attractive flower in worldwide. In its flower colour, yellow is the rarest which is ten times the price of the other colours. However, the breeding of new yellow P. lactiflora varieties using genetic engineering is severely limited due to the little-known biochemical and molecular mechanisms underlying its characteristic formation. In this study, two cDNA libraries generated from P. lactiflora chimaera with red outer-petal and yellow inner-petal were sequenced using an Illumina HiSeq™ 2000 platform. 66,179,398 and 65,481,444 total raw reads from red outer-petal and yellow inner-petal cDNA libraries were generated, which were assembled into 61,431 and 70,359 Unigenes with an average length of 628 and 617 nt, respectively. Moreover, 61,408 non-redundant All-unigenes were obtained, with 37,511 All-unigenes (61.08%) annotated in public databases. In addition, 6,345 All-unigenes were differentially expressed between the red outer-petal and yellow inner-petal, with 3,899 up-regulated and 2,446 down-regulated All-unigenes, and the flavonoid metabolic pathway related to colour development was identified using the Kyoto encyclopedia of genes and genomes database (KEGG). Subsequently, the expression patterns of 10 candidate differentially expressed genes (DEGs) involved in the flavonoid metabolic pathway were examined, and flavonoids were qualitatively and quantitatively analysed. Numerous anthoxanthins (flavone and flavonol) and a few anthocyanins were detected in the yellow inner-petal, which were all lower than those in the red outer-petal due to the low expression levels of the phenylalanine ammonialyase gene (PlPAL), flavonol synthase gene (PlFLS), dihydroflavonol 4-reductase gene (PlDFR), anthocyanidin synthase gene (PlANS), anthocyanidin 3-O-glucosyltransferase gene (Pl3GT) and anthocyanidin 5-O-glucosyltransferase gene (Pl5GT). Transcriptome sequencing (RNA-Seq) analysis based on the high throughput sequencing technology was an efficient approach to identify critical genes in P. lactiflora and other non-model plants. The flavonoid metabolic pathway and glucide metabolic pathway were identified as relatived yellow formation in P. lactiflora, PlPAL, PlFLS, PlDFR, PlANS, Pl3GT and Pl5GT were selected as potential candidates involved in flavonoid metabolic pathway, which inducing inhibition of anthocyanin biosynthesis mediated yellow formation in P. lactiflora. This study could lay a theoretical foundation for breeding new yellow P. lactiflora varieties.
NASA Technical Reports Server (NTRS)
Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)
2001-01-01
Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.
The Birmingham pituitary database: auditing the outcome of the treatment of acromegaly.
Jenkins, D; O'Brien, I; Johnson, A; Shakespear, R; Sheppard, M C; Stewart, P M
1995-11-01
Reduction of GH concentrations in acromegalic subjects may improve the increased mortality associated with the condition. Audit of the biochemical outcome of the management of acromegaly is, therefore, important. (1) To audit the biochemical 'cure' rate of acromegalic patients treated by surgery and/or radiotherapy under the care of the South Birmingham Endocrine Clinic. (2) To assess the correlation between random or basal GH with IGF-I and nadir GH during an oral glucose tolerance test. Ascertainment of acromegalic patients from a pituitary database. Mode of therapy, pretreatment GH, pretreatment tumour size, post-treatment GH, post-treatment IGF-I and post-treatment nadir GH were recorded. Biochemical cure was defined as a most recent random or basal GH < 5 mU/l. Cure rates were determined. Eighty-nine acromegalic patients were identified as having received surgery and/or radiotherapy. In 35/89 (39%) the most recent GH was < 5 mU/l. The cure rate following surgery was 26/78 (33%). This was not significantly associated with tumour size, but was associated with pretreatment GH concentration (chi 2 = 7.1, 2d.f., P < 0.05). Random/basal GH showed a log-linear association with IGF-I, r = 0.72, and a linear association with nadir GH, r = 0.93. Biochemical cure of acromegaly was more strongly associated with pretreatment GH than with tumour size. Random/basal GH measurements are useful and convenient for the audit of treatment outcome in acromegaly. Ways of improving the biochemical outcome of acromegaly should be sought.
SSER: Species specific essential reactions database.
Labena, Abraham A; Ye, Yuan-Nong; Dong, Chuan; Zhang, Fa-Z; Guo, Feng-Biao
2017-04-19
Essential reactions are vital components of cellular networks. They are the foundations of synthetic biology and are potential candidate targets for antimetabolic drug design. Especially if a single reaction is catalyzed by multiple enzymes, then inhibiting the reaction would be a better option than targeting the enzymes or the corresponding enzyme-encoding gene. The existing databases such as BRENDA, BiGG, KEGG, Bio-models, Biosilico, and many others offer useful and comprehensive information on biochemical reactions. But none of these databases especially focus on essential reactions. Therefore, building a centralized repository for this class of reactions would be of great value. Here, we present a species-specific essential reactions database (SSER). The current version comprises essential biochemical and transport reactions of twenty-six organisms which are identified via flux balance analysis (FBA) combined with manual curation on experimentally validated metabolic network models. Quantitative data on the number of essential reactions, number of the essential reactions associated with their respective enzyme-encoding genes and shared essential reactions across organisms are the main contents of the database. SSER would be a prime source to obtain essential reactions data and related gene and metabolite information and it can significantly facilitate the metabolic network models reconstruction and analysis, and drug target discovery studies. Users can browse, search, compare and download the essential reactions of organisms of their interest through the website http://cefg.uestc.edu.cn/sser .
Identifying pathways affected by cancer mutations.
Iengar, Prathima
2017-12-16
Mutations in 15 cancers, sourced from the COSMIC Whole Genomes database, and 297 human pathways, arranged into pathway groups based on the processes they orchestrate, and sourced from the KEGG pathway database, have together been used to identify pathways affected by cancer mutations. Genes studied in ≥15, and mutated in ≥10 samples of a cancer have been considered recurrently mutated, and pathways with recurrently mutated genes have been considered affected in the cancer. Novel doughnut plots have been presented which enable visualization of the extent to which pathways and genes, in each pathway group, are targeted, in each cancer. The 'organismal systems' pathway group (including organism-level pathways; e.g., nervous system) is the most targeted, more than even the well-recognized signal transduction, cell-cycle and apoptosis, and DNA repair pathway groups. The important, yet poorly-recognized, role played by the group merits attention. Pathways affected in ≥7 cancers yielded insights into processes affected. Copyright © 2017 Elsevier Inc. All rights reserved.
Identification of novel loci for the generation of reporter mice
Rebecchi, Monica; Levandis, Giovanna
2017-01-01
Abstract Deciphering the etiology of complex pathologies at molecular level requires longitudinal studies encompassing multiple biochemical pathways (apoptosis, proliferation, inflammation, oxidative stress). In vivo imaging of current reporter animals enabled the spatio-temporal analysis of specific molecular events, however, the lack of a multiplicity of loci for the generalized and regulated expression of the integrated transgenes hampers the creation of systems for the simultaneous analysis of more than a biochemical pathways at the time. We here developed and tested an in vivo-based methodology for the identification of multiple insertional loci suitable for the generation of reliable reporter mice. The validity of the methodology was tested with the generation of novel mice useful to report on inflammation and oxidative stress. PMID:27899606
Lin, Henry J; Lehoang, Jennifer; Kwan, Isabel; Baghaee, Anita; Prasad, Priya; Ha-Chen, Stephanie J; Moss, Tanesha; Woods, Jeremy D
2018-01-01
The 8 studs on a 2 × 4 Lego brick conveniently represent the outer shell of electrons for carbon, nitrogen, and oxygen atoms. We used Lego bricks to model these atoms, which are then joined together to form molecules by following the Lewis octet rule. A variety of small biological molecules can be modeled in this way, such as most amino acids, fatty acids, glucose, and various intermediate metabolites. Model building with these familiar toys can be a helpful, hands-on exercise for learning-or re-learning-biochemical pathways. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):54-57, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.
Current Status on Biochemistry and Molecular Biology of Microbial Degradation of Nicotine
Gurusamy, Raman; Natarajan, Sakthivel
2013-01-01
Bioremediation is one of the most promising methods to clean up polluted environments using highly efficient potent microbes. Microbes with specific enzymes and biochemical pathways are capable of degrading the tobacco alkaloids including highly toxic heterocyclic compound, nicotine. After the metabolic conversion, these nicotinophilic microbes use nicotine as the sole carbon, nitrogen, and energy source for their growth. Various nicotine degradation pathways such as demethylation pathway in fungi, pyridine pathway in Gram-positive bacteria, pyrrolidine pathway, and variant of pyridine and pyrrolidine pathways in Gram-negative bacteria have been reported. In this review, we discussed the nicotine-degrading pathways of microbes and their enzymes and biotechnological applications of nicotine intermediate metabolites. PMID:24470788
Garver, William S.; Jelinek, David; Meaney, F. John; Flynn, James; Pettit, Kathleen M.; Shepherd, Glen; Heidenreich, Randall A.; Vockley, Cate M. Walsh; Castro, Graciela; Francis, Gordon A.
2010-01-01
Niemann-Pick type C1 disease (NPC1) is an autosomal recessive lysosomal storage disorder characterized by neonatal jaundice, hepatosplenomegaly, and progressive neurodegeneration. The present study provides the lipid profiles, mutations, and corresponding associations with the biochemical phenotype obtained from NPC1 patients who participated in the National NPC1 Disease Database. Lipid profiles were obtained from 34 patients (39%) in the survey and demonstrated significantly reduced plasma LDL cholesterol (LDL-C) and increased plasma triglycerides in the majority of patients. Reduced plasma HDL cholesterol (HDL-C) was the most consistent lipoprotein abnormality found in male and female NPC1 patients across age groups and occurred independent of changes in plasma triglycerides. A subset of 19 patients for whom the biochemical severity of known NPC1 mutations could be correlated with their lipid profile showed a strong inverse correlation between plasma HDL-C and severity of the biochemical phenotype. Gene mutations were available for 52 patients (59%) in the survey, including 52 different mutations and five novel mutations (Y628C, P887L, I923V, A1151T, and 3741_3744delACTC). Together, these findings provide novel information regarding the plasma lipoprotein changes and mutations in NPC1 disease, and suggest plasma HDL-C represents a potential biomarker of NPC1 disease severity. PMID:19744920
Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome
Kim, Woonsu; Park, Hyesun; Seo, Seongwon
2016-01-01
The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle. PMID:26992093
cPath: open source software for collecting, storing, and querying biological pathways
Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris
2006-01-01
Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041
SIMULTANEOUS PRODUCTION OF TWO CAPSULAR POLYSACCHARIDES BY PNEUMOCOCCUS
Austrian, Robert; Bernheimer, Harriet P.; Smith, Evelyn E. B.; Mills, George T.
1959-01-01
Study of the capsular genome of pneumococcus has shown that it controls a multiplicity of biochemical reactions essential to the synthesis of capsular polysaccharide. Mutation affecting any one of several biochemical reactions concerned with capsular synthesis may result in loss of capsulation without alteration of other biochemical functions similarly concerned. Mutations affecting the synthesis of uronic acids are an important cause of loss of capsulation and of virulence by strains of pneumococcus Type I and Type III. The capsular genome appears to have a specific location in the total genome of the cell, this locus being occupied by the capsular genome of whatever capsular type is expressed by the cell. Transformation of capsulated or of non-capsulated pneumococci to heterologous capsular type results probably from a genetic exchange followed by the development of a new biosynthetic pathway in the transformed cell. The new capsular genome is transferred to the transformed cell as a single particle of DNA. Binary capsulation results from the simultaneous presence within the pneumococcal cell of two capsular genomes, one mutated, the other normal. Interaction between the biochemical pathways controlled by the two capsular genomes leads to augmentation of the phenotypic expression of the product controlled by one and to partial suppression of the product determined by the other. Knowledge of the biochemical basis of binary capsulation can be used to indicate the presence of uronic acid in the capsular polysaccharide of a pneurnococcal type the composition of the capsule of which is unknown. PMID:13795197
Mallik, Mrinmay Kumar
2018-02-07
Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that is indicative of their strong influence in the protein protein interaction network. Similarly the newly proposed GEADCA helped identify the transcription factors with high centrality values indicative of their key roles in transcriptional regulation. The enrichment studies provided a list of molecular functions, biological processes and biochemical pathways associated with the constructed network. The study shows how pathway based databases may be used to create and analyze a relevant protein interaction network in glioma cancer stem cells and identify the essential elements within it to gather insights into the molecular interactions that regulate the properties of glioma stem cells. How these insights may be utilized to help the development of future research towards formulation of new management strategies have been discussed from a theoretical standpoint. Copyright © 2017 Elsevier Ltd. All rights reserved.
Modeling Neisseria meningitidis metabolism: from genome to metabolic fluxes
Baart, Gino JE; Zomer, Bert; de Haan, Alex; van der Pol, Leo A; Beuvery, E Coen; Tramper, Johannes; Martens, Dirk E
2007-01-01
Background Neisseria meningitidis is a human pathogen that can infect diverse sites within the human host. The major diseases caused by N. meningitidis are responsible for death and disability, especially in young infants. In general, most of the recent work on N. meningitidis focuses on potential antigens and their functions, immunogenicity, and pathogenicity mechanisms. Very little work has been carried out on Neisseria primary metabolism over the past 25 years. Results Using the genomic database of N. meningitidis serogroup B together with biochemical and physiological information in the literature we constructed a genome-scale flux model for the primary metabolism of N. meningitidis. The validity of a simplified metabolic network derived from the genome-scale metabolic network was checked using flux-balance analysis in chemostat cultures. Several useful predictions were obtained from in silico experiments, including substrate preference. A minimal medium for growth of N. meningitidis was designed and tested succesfully in batch and chemostat cultures. Conclusion The verified metabolic model describes the primary metabolism of N. meningitidis in a chemostat in steady state. The genome-scale model is valuable because it offers a framework to study N. meningitidis metabolism as a whole, or certain aspects of it, and it can also be used for the purpose of vaccine process development (for example, the design of growth media). The flux distribution of the main metabolic pathways (that is, the pentose phosphate pathway and the Entner-Douderoff pathway) indicates that the major part of pyruvate (69%) is synthesized through the ED-cleavage, a finding that is in good agreement with literature. PMID:17617894
Shahbaaz, Mohd; Ahmad, Faizan; Imtaiyaz Hassan, Md
2015-06-01
Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure-function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.
Charan, Manish; Choudhary, Hadi Hasan; Singh, Nidhi; Sadik, Mohammad; Siddiqi, Mohammad Imran; Mishra, Satish; Habib, Saman
2017-08-01
The relict plastid (apicoplast) of the malaria parasite is the site for important biochemical pathways and is essential for parasite survival. The sulfur mobilization (SUF) pathway of iron-sulfur [Fe-S] cluster assembly in the apicoplast of Plasmodium spp. is of interest due to its absence in the human host suggesting the possibility of antimalarial intervention through apicoplast [Fe-S] biogenesis. We report biochemical characterization of components of the Plasmodium falciparum apicoplast SUF pathway after the first step of SUF. In vitro interaction experiments and in vivo cross-linking showed that apicoplast-encoded PfSufB and apicoplast-targeted PfSufC and PfSufD formed a complex. The PfSufB-C 2 -D complex could function as a scaffold to assemble [4Fe-4S] clusters in vitro and activity of the PfSufC ATPase was enhanced by PfSufD. Two carrier proteins, the NifU-like protein PfNfu and the A-type carrier PfSufA are homodimers, the former mediating transfer of [4Fe-4S] from the scaffold to a model [4Fe-4S] target protein with higher efficiency. Conditional knockout of SufS, the enzyme catalyzing the first step of SUF, by selective excision in the mosquito stages of Plasmodium berghei severely impaired development of sporozoites in oocysts establishing essentiality of the SUF machinery in the vector. Our results delineate steps of the complete apicoplast SUF pathway and demonstrate its critical role in the parasite life cycle. © 2017 Federation of European Biochemical Societies.
Evidence from Biochemical Pathways in Favor of Unfinished Evolution Rather than Intelligent Design
ERIC Educational Resources Information Center
Behrman, Edward J.; Marzluf, George A.
2004-01-01
An argument is made in favor of imperfect or unfinished evolution based on some metabolic pathways in which it seems that intelligent design would have done better. The case studies noted indicate the absence of highly intelligent design and are not intended as comprehensive collection but as a limited sample of inefficient situations in…
genome-wide association and metabolic pathway analysis of corn earworm resistance in maize
Marilyn L. Warburton; Erika D. Womack; Juliet D. Tang; Adam Thrash; J. Spencer Smith; Wenwei Xu; Seth C. Murray; W. Paul Williams
2018-01-01
Maize (Zea mays mays L.) is a staple crop of economic, industrial, and food security importance. Damage to the growing ears by corn earworm [Helicoverpa zea (Boddie)] is a major economic burden and increases secondary fungal infections and mycotoxin levels. To identify biochemical pathways associated with native resistance mechanisms, a genome-wide...
Bottcher, Alexandra; Cesarino, Igor; Brombini dos Santos, Adriana; Vicentini, Renato; Mayer, Juliana Lischka Sampaio; Vanholme, Ruben; Morreel, Kris; Goeminne, Geert; Moura, Jullyana Cristina Magalhães Silva; Nobile, Paula Macedo; Carmello-Guerreiro, Sandra Maria; Antonio dos Anjos, Ivan; Creste, Silvana; Boerjan, Wout; Landell, Marcos Guimarães de Andrade; Mazzafera, Paulo
2013-01-01
Sugarcane (Saccharum spp.) is currently one of the most efficient crops in the production of first-generation biofuels. However, the bagasse represents an additional abundant lignocellulosic resource that has the potential to increase the ethanol production per plant. To achieve a more efficient conversion of bagasse into ethanol, a better understanding of the main factors affecting biomass recalcitrance is needed. Because several studies have shown a negative effect of lignin on saccharification yield, the characterization of lignin biosynthesis, structure, and deposition in sugarcane is an important goal. Here, we present, to our knowledge, the first systematic study of lignin deposition during sugarcane stem development, using histological, biochemical, and transcriptional data derived from two sugarcane genotypes with contrasting lignin contents. Lignin amount and composition were determined in rind (outer) and pith (inner) tissues throughout stem development. In addition, the phenolic metabolome was analyzed by ultra-high-performance liquid chromatography-mass spectrometry, which allowed the identification of 35 compounds related to the phenylpropanoid pathway and monolignol biosynthesis. Furthermore, the Sugarcane EST Database was extensively surveyed to identify lignin biosynthetic gene homologs, and the expression of all identified genes during stem development was determined by quantitative reverse transcription-polymerase chain reaction. Our data provide, to our knowledge, the first in-depth characterization of lignin biosynthesis in sugarcane and form the baseline for the rational metabolic engineering of sugarcane feedstock for bioenergy purposes. PMID:24144790
Fimognari, Nicholas; Hollings, Ashley; Lam, Virginie; Tidy, Rebecca J; Kewish, Cameron M; Albrecht, Matthew A; Takechi, Ryu; Mamo, John C L; Hackett, Mark J
2018-06-14
Western society is facing a health epidemic due to the increasing incidence of dementia in ageing populations, and there are still few effective diagnostic methods, minimal treatment options, and no cure. Ageing is the greatest risk factor for memory loss that occurs during the natural ageing process, as well as being the greatest risk factor for neurodegenerative disease such as Alzheimer's disease. Therefore, greater understanding of the biochemical pathways that drive a healthy ageing brain towards dementia (pathological ageing or Alzheimer's disease), is required to accelerate the development of improved diagnostics and therapies. Unfortunately, many animal models of dementia model chronic amyloid precursor protein over-expression, which although highly relevant to mechanisms of amyloidosis and familial Alzheimer's disease, does not model well dementia during the natural ageing process. A promising animal model reported to model mechanisms of accelerated natural ageing and memory impairments, is the senescence accelerated murine prone strain 8 (SAMP8), which has been adopted by many research group to study the biochemical transitions that occur during brain ageing. A limitation to traditional methods of biochemical characterisation is that many important biochemical and elemental markers (lipid saturation, lactate, transition metals) cannot be imaged at meso- or micro-spatial resolution. Therefore, in this investigation we report the first multi-modal biospectroscopic characterisation of the SAMP8 model, and have identified important biochemical and elemental alterations, and co-localisations, between 4 month old SAMP8 mice and the relevant control (SAMR1) mice. Specifically, we demonstrate direct evidence of altered metabolism and disturbed lipid homeostasis within corpus callosum white matter, in addition to localised hippocampal metal deficiencies, in the accelerated ageing phenotype. Such findings have important implication for future research aimed at elucidating specific biochemical pathways for therapeutic intervention.
Cai, Yu-Dong; Chou, Kuo-Chen
2011-01-01
Given a regulatory pathway system consisting of a set of proteins, can we predict which pathway class it belongs to? Such a problem is closely related to the biological function of the pathway in cells and hence is quite fundamental and essential in systems biology and proteomics. This is also an extremely difficult and challenging problem due to its complexity. To address this problem, a novel approach was developed that can be used to predict query pathways among the following six functional categories: (i) “Metabolism”, (ii) “Genetic Information Processing”, (iii) “Environmental Information Processing”, (iv) “Cellular Processes”, (v) “Organismal Systems”, and (vi) “Human Diseases”. The prediction method was established trough the following procedures: (i) according to the general form of pseudo amino acid composition (PseAAC), each of the pathways concerned is formulated as a 5570-D (dimensional) vector; (ii) each of components in the 5570-D vector was derived by a series of feature extractions from the pathway system according to its graphic property, biochemical and physicochemical property, as well as functional property; (iii) the minimum redundancy maximum relevance (mRMR) method was adopted to operate the prediction. A cross-validation by the jackknife test on a benchmark dataset consisting of 146 regulatory pathways indicated that an overall success rate of 78.8% was achieved by our method in identifying query pathways among the above six classes, indicating the outcome is quite promising and encouraging. To the best of our knowledge, the current study represents the first effort in attempting to identity the type of a pathway system or its biological function. It is anticipated that our report may stimulate a series of follow-up investigations in this new and challenging area. PMID:21980418
Varela, Anna Lidia N; Komatsu, Setsuko; Wang, Xin; Silva, Rodolpho G G; Souza, Pedro Filho N; Lobo, Ana Karla M; Vasconcelos, Ilka M; Silveira, Joaquim A G; Oliveira, Jose T A
2017-06-23
Cowpea severe mosaic virus (CPSMV) causes significant losses in cowpea (Vigna unguiculata) production. In this present study biochemical, physiological, and proteomic analysis were done to identify pathways and defense proteins that are altered during the incompatible interaction between the cowpea genotype BRS-Marataoã and CPSMV. The leaf protein extracts from mock- (MI) and CPSMV-inoculated plantlets (V) were evaluated at 2 and 6days post-inoculation (DPI). Data support the assumptions that increases in biochemical (high hydrogen peroxide, antioxidant enzymes, and secondary compounds) and physiological responses (high photosynthesis index and chlorophyll content), confirmed by label-free comparative proteomic approach, in which quantitative changes in proteasome proteins, proteins related to photosynthesis, redox homeostasis, regulation factors/RNA processing proteins were observed may be implicated in the resistance of BRS-Marataoã to CPSMV. This pioneering study provides information for the selection of specific pathways and proteins, altered in this incompatible relationship, which could be chosen as targets for detailed studies to advance our understanding of the molecular, physiological, and biochemistry basis of the resistance mechanism of cowpea and design approachs to engineer plants that are more productive. This is a pioneering study in which an incompatible relationship between a resistant cowpea and Cowpea severe mosaic virus (CPSMV) was conducted to comparatively evaluate proteomic profiles by Gel-free/label-free methodology and some physiological and biochemical parameters to shed light on how a resistant cowpea cultivar deals with the virus attack. Specific proteins and associated pathways were altered in the cowpea plants challenged with CPSMV and will contribute to our knowledge on the biological process tailored by cowpea in response to CPSMV. Copyright © 2017 Elsevier B.V. All rights reserved.
El-Haggar, Sahar Mohamed; Mostafa, Tarek Mohamed
2015-07-01
Non-alcoholic fatty liver disease is a common health problem associated with increased liver and vascular specific complications. The purpose of this study was to assess and compare the effect of fenofibrate alone or in combination with pentoxifylline on the measured biochemical parameters, inflammatory pathway and liver stiffness in patients with non-alcoholic fatty liver disease. The study design was randomized controlled trial. From July 2013 to June 2014, we recruited 90 non-alcoholic fatty liver patients from the Internal Medicine Department at Tanta University Hospital, Egypt. They were classified randomly into two groups to receive fenofibrate 300 mg daily or fenofibrate 300 mg daily plus pentoxifylline 1200 mg/day in three divided doses for 24 weeks. Fasting blood sample was obtained before and 24 weeks after treatment for biochemical analysis of liver and lipid panels, tumor necrosis factor-alpha, hyaluronic acid, transforming growth factor beta 1, fasting plasma insulin and fasting glucose. Liver stiffness measurement was carried out using fibro-scan. Data were statistically analyzed by paired and unpaired Student's t test. The data obtained suggests that adding pentoxifylline to fenofibrate does not provide a beneficial effect on lipid panel, but has a beneficial effect on indirect biochemical markers of hepatic fibrosis, a direct marker linked to matrix deposition (hyaluronic acid), a cytokine/growth factor linked to liver fibrosis (transforming growth factor beta 1), the inflammatory pathway, insulin resistance and liver stiffness as compared to fenofibrate alone. The combination pentoxifylline plus fenofibrate may represent a new therapeutic strategy for non-alcoholic fatty liver disease as it resulted in more beneficial effects on direct and indirect markers of liver fibrosis, liver stiffness, insulin resistance and inflammatory pathway implicated in NAFLD.
In Vitro Reconstitution of Metabolic Pathways: Insights into Nature’s Chemical Logic
Lowry, Brian; Walsh, Christopher T.
2015-01-01
In vitro analysis of metabolic pathways is becoming a powerful method to gain a deeper understanding of Nature’s core biochemical transformations. With astounding advancements in biotechnology, purification of a metabolic pathway’s constitutive enzymatic components is becoming a tractable problem, and such in vitro studies allow scientists to capture the finer details of enzymatic reaction mechanisms, kinetics, and the identity of organic product molecules. In this review, we present eleven metabolic pathways that have been the subject of in vitro reconstitution studies in the literature in recent years. In addition, we have selected and analyzed subset of four case studies within these eleven examples that exemplify remarkable organic chemistry occurring within biology. These examples serves as tangible reminders that Nature’s biochemical routes obey the fundamental principles of organic chemistry, and the chemical mechanisms are reminiscent of those featured in traditional synthetic organic routes. The illustrations of biosynthetic chemistry depicted in this review may inspire the development of biomimetic chemistries via abiotic chemical techniques. PMID:26207083
Shen, Yanwen; Jarboe, Laura; Brown, Robert; Wen, Zhiyou
2015-12-01
Thermochemical-biological hybrid processing uses thermochemical decomposition of lignocellulosic biomass to produce a variety of intermediate compounds that can be converted into fuels and chemicals through microbial fermentation. It represents a unique opportunity for biomass conversion as it mitigates some of the deficiencies of conventional biochemical (pretreatment-hydrolysis-fermentation) and thermochemical (pyrolysis or gasification) processing. Thermochemical-biological hybrid processing includes two pathways: (i) pyrolysis/pyrolytic substrate fermentation, and (ii) gasification/syngas fermentation. This paper provides a comprehensive review of these two hybrid processing pathways, including the characteristics of fermentative substrates produced in the thermochemical stage and microbial utilization of these compounds in the fermentation stage. The current challenges of these two biomass conversion pathways include toxicity of the crude pyrolytic substrates, the inhibition of raw syngas contaminants, and the mass-transfer limitations in syngas fermentation. Possible approaches for mitigating substrate toxicities are discussed. The review also provides a summary of the current efforts to commercialize hybrid processing. Copyright © 2015 Elsevier Inc. All rights reserved.
libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.
Ji, Xinglai; Xu, Ying
2006-01-01
Estimation of kinetic parameters in a biochemical pathway or network represents a common problem in systems studies of biological processes. We have implemented a C library, named libSRES, to facilitate a fast implementation of computer software for study of non-linear biochemical pathways. This library implements a (mu, lambda)-ES evolutionary optimization algorithm that uses stochastic ranking as the constraint handling technique. Considering the amount of computing time it might require to solve a parameter-estimation problem, an MPI version of libSRES is provided for parallel implementation, as well as a simple user interface. libSRES is freely available and could be used directly in any C program as a library function. We have extensively tested the performance of libSRES on various pathway parameter-estimation problems and found its performance to be satisfactory. The source code (in C) is free for academic users at http://csbl.bmb.uga.edu/~jix/science/libSRES/
The Listeria monocytogenes strain 10403S BioCyc database.
Orsi, Renato H; Bergholz, Teresa M; Wiedmann, Martin; Boor, Kathryn J
2015-01-01
Listeria monocytogenes is a food-borne pathogen of humans and other animals. The striking ability to survive several stresses usually used for food preservation makes L. monocytogenes one of the biggest concerns to the food industry, while the high mortality of listeriosis in specific groups of humans makes it a great concern for public health. Previous studies have shown that a regulatory network involving alternative sigma (σ) factors and transcription factors is pivotal to stress survival. However, few studies have evaluated at the metabolic networks controlled by these regulatory mechanisms. The L. monocytogenes BioCyc database uses the strain 10403S as a model. Computer-generated initial annotation for all genes also allowed for identification, annotation and display of predicted reactions and pathways carried out by a single cell. Further ongoing manual curation based on published data as well as database mining for selected genes allowed the more refined annotation of functions, which, in turn, allowed for annotation of new pathways and fine-tuning of previously defined pathways to more L. monocytogenes-specific pathways. Using RNA-Seq data, several transcription start sites and promoter regions were mapped to the 10403S genome and annotated within the database. Additionally, the identification of promoter regions and a comprehensive review of available literature allowed the annotation of several regulatory interactions involving σ factors and transcription factors. The L. monocytogenes 10403S BioCyc database is a new resource for researchers studying Listeria and related organisms. It allows users to (i) have a comprehensive view of all reactions and pathways predicted to take place within the cell in the cellular overview, as well as to (ii) upload their own data, such as differential expression data, to visualize the data in the scope of predicted pathways and regulatory networks and to carry on enrichment analyses using several different annotations available within the database. © The Author(s) 2015. Published by Oxford University Press.
Riise Stensland, Hilde Monica Frostad; Frantzen, Gabrio; Kuokkanen, Elina; Buvang, Elisabeth Kjeldsen; Klenow, Helle Bagterp; Heikinheimo, Pirkko; Malm, Dag; Nilssen, Øivind
2015-06-01
α-Mannosidosis is an autosomal recessive lysosomal storage disorder caused by mutations in the MAN2B1 gene, encoding lysosomal α-mannosidase. The disorder is characterized by a range of clinical phenotypes of which the major manifestations are mental impairment, hearing impairment, skeletal changes, and immunodeficiency. Here, we report an α-mannosidosis mutation database, amamutdb.no, which has been constructed as a publicly accessible online resource for recording and analyzing MAN2B1 variants (http://amamutdb.no). Our aim has been to offer structured and relational information on MAN2B1 mutations and genotypes along with associated clinical phenotypes. Classifying missense mutations, as pathogenic or benign, is a challenge. Therefore, they have been given special attention as we have compiled all available data that relate to their biochemical, functional, and structural properties. The α-mannosidosis mutation database is comprehensive and relational in the sense that information can be retrieved and compiled across datasets; hence, it will facilitate diagnostics and increase our understanding of the clinical and molecular aspects of α-mannosidosis. We believe that the amamutdb.no structure and architecture will be applicable for the development of databases for any monogenic disorder. © 2015 WILEY PERIODICALS, INC.
Bioinformatics analysis on molecular mechanism of rheum officinale in treatment of jaundice
NASA Astrophysics Data System (ADS)
Shan, Si; Tu, Jun; Nie, Peng; Yan, Xiaojun
2017-01-01
Objective: To study the molecular mechanism of Rheum officinale in the treatment of Jaundice by building molecular networks and comparing canonical pathways. Methods: Target proteins of Rheum officinale and related genes of Jaundice were searched from Pubchem and Gene databases online respectively. Molecular networks and canonical pathways comparison analyses were performed by Ingenuity Pathway Analysis (IPA). Results: The molecular networks of Rheum officinale and Jaundice were complex and multifunctional. The 40 target proteins of Rheum officinale and 33 Homo sapiens genes of Jaundice were found in databases. There were 19 common pathways both related networks. Rheum officinale could regulate endothelial differentiation, Interleukin-1B (IL-1B) and Tumor Necrosis Factor (TNF) in these pathways. Conclusions: Rheum officinale treat Jaundice by regulating many effective nodes of Apoptotic pathway and cellular immunity related pathways.
BioPAX – A community standard for pathway data sharing
Demir, Emek; Cary, Michael P.; Paley, Suzanne; Fukuda, Ken; Lemer, Christian; Vastrik, Imre; Wu, Guanming; D’Eustachio, Peter; Schaefer, Carl; Luciano, Joanne; Schacherer, Frank; Martinez-Flores, Irma; Hu, Zhenjun; Jimenez-Jacinto, Veronica; Joshi-Tope, Geeta; Kandasamy, Kumaran; Lopez-Fuentes, Alejandra C.; Mi, Huaiyu; Pichler, Elgar; Rodchenkov, Igor; Splendiani, Andrea; Tkachev, Sasha; Zucker, Jeremy; Gopinath, Gopal; Rajasimha, Harsha; Ramakrishnan, Ranjani; Shah, Imran; Syed, Mustafa; Anwar, Nadia; Babur, Ozgun; Blinov, Michael; Brauner, Erik; Corwin, Dan; Donaldson, Sylva; Gibbons, Frank; Goldberg, Robert; Hornbeck, Peter; Luna, Augustin; Murray-Rust, Peter; Neumann, Eric; Reubenacker, Oliver; Samwald, Matthias; van Iersel, Martijn; Wimalaratne, Sarala; Allen, Keith; Braun, Burk; Whirl-Carrillo, Michelle; Dahlquist, Kam; Finney, Andrew; Gillespie, Marc; Glass, Elizabeth; Gong, Li; Haw, Robin; Honig, Michael; Hubaut, Olivier; Kane, David; Krupa, Shiva; Kutmon, Martina; Leonard, Julie; Marks, Debbie; Merberg, David; Petri, Victoria; Pico, Alex; Ravenscroft, Dean; Ren, Liya; Shah, Nigam; Sunshine, Margot; Tang, Rebecca; Whaley, Ryan; Letovksy, Stan; Buetow, Kenneth H.; Rzhetsky, Andrey; Schachter, Vincent; Sobral, Bruno S.; Dogrusoz, Ugur; McWeeney, Shannon; Aladjem, Mirit; Birney, Ewan; Collado-Vides, Julio; Goto, Susumu; Hucka, Michael; Le Novère, Nicolas; Maltsev, Natalia; Pandey, Akhilesh; Thomas, Paul; Wingender, Edgar; Karp, Peter D.; Sander, Chris; Bader, Gary D.
2010-01-01
BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery. PMID:20829833
miR-31 Regulates Spermatogonial Stem Cells Meiosis via Targeting Stra8.
Wang, Yingjie; Zuo, Qisheng; Bi, Yulin; Zhang, Wenhui; Jin, Jing; Zhang, Liangliang; Zhang, Ya-Ni; Li, Bichun
2017-12-01
Stra8 (stimulated by retinoic acid gene 8) is a specific gene that is expressed in mammalian germ cells during transition from mitosis to meiosis and plays a key role in the initiation of meiosis in mammals and birds. So, the evaluation of the Stra8 pathway in cSSCs may provide a deeper insight into mammalian spermatogenesis. miRNA was also an important regulating factor for meiosis of SSCs. However, there is currently no data indicating that miRNA regulate the meiosis of SSCs via Stra8. Here, we predicted the prospective miRNA targeting to Stra8 using the online Bioinformatics database-Targetscan, and performed an analysis of the dual-luciferase recombinant vector, pGL3-CMV-LUC-MCS-Stra8-3'UTR. miR-31 mimics (miR-31m), miR-31 inhibitors (miR-31i), Control (NC, scrambled oligonucleotides transfection) were transfected into cSSCs; Stra8 and miRNA were analyzed by RT-qPCR, immunofluorescence, and Western blot. The detection of haploid was conducted by flow cytometry. The results showed that miR-31 regulates meiosis of cSSCs via targeting Stra8 in vitro and in vivo. Our study identifies a new regulatory pathway that miR-31 targets Stra8 and inhibits spermatogenesis. J. Cell. Biochem. 118: 4844-4853, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Pheochromocytoma-paraganglioma: Biochemical and genetic diagnosis.
Cano Megías, Marta; Rodriguez Puyol, Diego; Fernández Rodríguez, Loreto; Sención Martinez, Gloria Lisette; Martínez Miguel, Patricia
Pheochromocytomas and paragangliomas are tumours derived from neural crest cells, which can be diagnosed by biochemical measurement of metanephrine and methoxytyramine. Advances in genetic research have identified many genes involved in the pathogenesis of these tumours, suggesting that up to 35-45% may have an underlying germline mutation. These genes have a singular transcriptional signature and can be grouped into 2 clusters (or groups): cluster 1 (VHL and SHDx), involved in angiogenesis and hypoxia pathways; and cluster 2 (MEN2 and NF1), linked to the kinase signalling pathway. In turn, these genes are associated with a characteristic biochemical phenotype (noradrenergic and adrenergic), and clinical features (location, biological behaviour, age of presentation, etc.) in a large number of cases. Early diagnosis of these tumours, accompanied by a correct genetic diagnosis, should eventually become a priority to enable better treatment, early detection of complications, proper screening of family members and related tumours, as well as an improvement in the overall prognosis of these patients. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.
Pan, Yan; Kislinger, Thomas; Gramolini, Anthony O; Zvaritch, Elena; Kranias, Evangelia G; MacLennan, David H; Emili, Andrew
2004-02-24
Phospholamban (PLN) is a critical regulator of cardiac contractility through its binding to and regulation of the activity of the sarco(endo)plasmic reticulum Ca2+ ATPase. To uncover biochemical adaptations associated with extremes of cardiac muscle contractility, we used high-throughput gel-free tandem MS to monitor differences in the relative abundance of membrane proteins in standard microsomal fractions isolated from the hearts of PLN-null mice (PLN-KO) with high contractility and from transgenic mice overexpressing a superinhibitory PLN mutant in a PLN-null background (I40A-KO) with diminished contractility. Significant differential expression was detected for a subset of the 782 proteins identified, including known membrane-associated biomarkers, components of signaling pathways, and previously uninvestigated proteins. Proteins involved in fat and carbohydrate metabolism and proteins linked to G protein-signaling pathways activating protein kinase C were enriched in I40A-KO cardiac muscle, whereas proteins linked to enhanced contractile function were enriched in PLN-KO mutant hearts. These data demonstrate that Ca2+ dysregulation, leading to elevated or depressed cardiac contractility, induces compensatory biochemical responses.
USDA-ARS?s Scientific Manuscript database
C4 photosynthesis is an elaborate set of metabolic pathways that utilize specialized anatomical and biochemical adaptations to concentrate CO2 around RuBisCO. The activities of the C4 pathways are coordinated between two specialized leaf cell types, mesophyll (M) and bundle sheath (BS), and rely hea...
Methanococcus maripaludis is a strictly anaerobic, methane-producing archaeon and facultative autotroph capable of biosynthesizing all the amino acids and vitamins required for growth. In this work, the novel 6-deoxy-5-ketofructose-1-phosphate (DKFP) pathway for the biosynthesis ...
Chemical modulation of glycerolipid signaling and metabolic pathways
Scott, Sarah A.; Mathews, Thomas P.; Ivanova, Pavlina T.; Lindsley, Craig W.; Brown, H. Alex
2014-01-01
Thirty years ago, glycerolipids captured the attention of biochemical researchers as novel cellular signaling entities. We now recognize that these biomolecules occupy signaling nodes critical to a number of physiological and pathological processes. Thus, glycerolipid-metabolizing enzymes present attractive targets for new therapies. A number of fields—ranging from neuroscience and cancer to diabetes and obesity—have elucidated the signaling properties of glycerolipids. The biochemical literature teems with newly emerging small molecule inhibitors capable of manipulating glycerolipid metabolism and signaling. This ever-expanding pool of chemical modulators appears daunting to those interested in exploiting glycerolipid-signaling pathways in their model system of choice. This review distills the current body of literature surrounding glycerolipid metabolism into a more approachable format, facilitating the application of small molecule inhibitors to novel systems. PMID:24440821
Thomas, Reuben; Hubbard, Alan E.; McHale, Cliona M.; Zhang, Luoping; Rappaport, Stephen M.; Lan, Qing; Rothman, Nathaniel; Vermeulen, Roel; Guyton, Kathryn Z.; Jinot, Jennifer; Sonawane, Babasaheb R.; Smith, Martyn T.
2014-01-01
Benzene, a ubiquitous environmental pollutant, causes acute myeloid leukemia (AML). Recently, through transcriptome profiling of peripheral blood mononuclear cells (PBMC), we reported dose-dependent effects of benzene exposure on gene expression and biochemical pathways in 83 workers exposed across four airborne concentration ranges (from <1 ppm to >10 ppm) compared with 42 subjects with non-workplace ambient exposure levels. Here, we further characterize these dose-dependent effects with continuous benzene exposure in all 125 study subjects. We estimated air benzene exposure levels in the 42 environmentally-exposed subjects from their unmetabolized urinary benzene levels. We used a novel non-parametric, data-adaptive model selection method to estimate the change with dose in the expression of each gene. We describe non-parametric approaches to model pathway responses and used these to estimate the dose responses of the AML pathway and 4 other pathways of interest. The response patterns of majority of genes as captured by mean estimates of the first and second principal components of the dose-response for the five pathways and the profiles of 6 AML pathway response-representative genes (identified by clustering) exhibited similar apparent supra-linear responses. Responses at or below 0.1 ppm benzene were observed for altered expression of AML pathway genes and CYP2E1. Together, these data show that benzene alters disease-relevant pathways and genes in a dose-dependent manner, with effects apparent at doses as low as 100 ppb in air. Studies with extensive exposure assessment of subjects exposed in the low-dose range between 10 ppb and 1 ppm are needed to confirm these findings. PMID:24786086
Garrocho-Villegas, Verónica; Aguilar C, Raúl; Sánchez de Jiménez, Estela
2013-12-23
The primordial TOR pathway, known to control growth and cell proliferation, has still not been fully described for plants. Nevertheless, in maize, an insulin-like growth factor (ZmIGF) peptide has been reported to stimulate this pathway. This research provides further insight into the TOR pathway in maize, using a biochemical approach in cultures of fast-growing (FG) and slow-growing (SG) calli, as a model system. Our results revealed that addition of either ZmIGF or insulin to SG calli stimulated DNA synthesis and increased the growth rate through cell proliferation and increased the rate of ribosomal protein (RP) synthesis by the selective mobilization of RP mRNAs into polysomes. Furthermore, analysis of the phosphorylation status of the main TOR and S6K kinases from the TOR pathway revealed stimulation by ZmIGF or insulin, whereas rapamycin inhibited its activation. Remarkably, a putative maize insulin-like receptor was recognized by a human insulin receptor antibody, as demonstrated by immunoprecipitation from membrane protein extracts of maize callus. Furthermore, competition experiments between ZmIGF and insulin for the receptor site on maize protoplasts suggested structural recognition of the putative receptor by either effector. These data were confirmed by confocal immunolocalization within the cell membrane of callus cells. Taken together, these data indicate that cell growth and cell proliferation in maize depend on the activation of the TOR-S6K pathway through the interaction of an insulin-like growth factor and its receptor. This evidence suggests that higher plants as well as metazoans have conserved this biochemical pathway to regulate their growth, supporting the conclusion that it is a highly evolved conserved pathway.
Harnessing Intracellular Biochemical Pathways for In Vitro Synthesis of Designer Tellurium Nanorods.
Xiong, Ling-Hong; Cui, Ran; Zhang, Zhi-Ling; Tu, Jia-Wei; Shi, Yun-Bo; Pang, Dai-Wen
2015-10-28
Synthesizing nanomaterials of desired properties is a big challenge, which requires extremely harsh conditions and/or use of toxic materials. More recently developed in vivo methods have brought a different set of problems such as separation and purification of nanomaterials made in vivo. Here, a novel approach that harnesses cellular pathways for in vitro synthesis of high-quality tellurium nanorods with tunable lengths and optical properties is reported. It is first demonstrated that in vivo biochemical pathways could be used to synthesize Te nanorods via the intracellular reduction of TeO3(2-) in living Staphylococcus aureus cells. The pathways to set up a quasi-biological system for Te precursor formation are then utilized, which could further synthesize Te nanorods in vitro. This allows to successfully synthesize in vitro, under routine laboratory conditions, Te nanorods with uniform and tunable lengths, ranging from about 10 to 200 nm, and controllable optical properties with high molar extinction coefficients. The approach here should open new avenues for controllable, facile, and efficient synthesis of designer nanomaterials for diverse industrial and biomedical applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Gagescu, Raluca; Demaurex, Nicolas; Parton, Robert G.; Hunziker, Walter; Huber, Lukas A.; Gruenberg, Jean
2000-01-01
We present a biochemical and morphological characterization of recycling endosomes containing the transferrin receptor in the epithelial Madin-Darby canine kidney cell line. We find that recycling endosomes are enriched in molecules known to regulate transferrin recycling but lack proteins involved in early endosome membrane dynamics, indicating that recycling endosomes are distinct from conventional early endosomes. We also find that recycling endosomes are less acidic than early endosomes because they lack a functional vacuolar ATPase. Furthermore, we show that recycling endosomes can be reached by apically internalized tracers, confirming that the apical endocytic pathway intersects the transferrin pathway. Strikingly, recycling endosomes are enriched in the raft lipids sphingomyelin and cholesterol as well as in the raft-associated proteins caveolin-1 and flotillin-1. These observations may suggest that a lipid-based sorting mechanism operates along the Madin-Darby canine kidney recycling pathway, contributing to the maintenance of cell polarity. Altogether, our data indicate that recycling endosomes and early endosomes differ functionally and biochemically and thus that different molecular mechanisms regulate protein sorting and membrane traffic at each step of the receptor recycling pathway. PMID:10930469
Lok, Benjamin H.; Powell, Simon N.
2012-01-01
The Rad52 protein was largely ignored in humans and other mammals when the mouse knockout revealed a largely “no-effect” phenotype. However, using synthetic lethal approaches to investigate context dependent function, new studies have shown that Rad52 plays a key survival role in cells lacking the function of the BRCA1-BRCA2 pathway of homologous recombination. Biochemical studies also showed significant differences between yeast and human Rad52, in which yeast Rad52 can promote strand invasion of RPA-coated single-stranded DNA in the presence of Rad51, but human Rad52 cannot. This results in the paradox of how is human Rad52 providing Rad51 function: presumably there is something missing in the biochemical assays that exists in-vivo, but the nature of this missing factor is currently unknown. Recent studies have suggested that Rad52 provides back-up Rad51 function for all members of the BRCA1-BRCA2 pathway, suggesting that Rad52 may be a target for therapy in BRCA pathway deficient cancers. Screening for ways to inhibit Rad52 would potentially provide a complementary strategy for targeting BRCA-deficient cancers in addition to PARP inhibitors. PMID:23071261
Higgins, Victoria; Chan, Man Khun; Nieuwesteeg, Michelle; Hoffman, Barry R; Bromberg, Irvin L; Gornall, Doug; Randell, Edward; Adeli, Khosrow
2016-01-01
The Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) has recently established pediatric age- and sex-specific reference intervals for over 85 biochemical markers on the Abbott Architect system. Previously, CALIPER reference intervals for several biochemical markers were successfully transferred from Abbott assays to Roche, Beckman, Ortho, and Siemens assays. This study further broadens the CALIPER database by performing transference and verification for 52 biochemical assays on the Roche cobas 6000 and the Roche Modular P. Using CLSI C28-A3 and EP9-A2 guidelines, transference of the CALIPER reference intervals was attempted for 16 assays on the Roche cobas 6000 and 36 on the Modular P. Calculated reference intervals were further verified using 100 healthy CALIPER samples. Most assays showed strong correlation between assay systems and were transferable from Abbott to the Roche cobas 6000 (81%) and the Modular P (86%). Bicarbonate and magnesium were not transferable on either system and calcium and prealbumin were not transferable to the Modular P. Of the transferable analytes, 62% and 61% were verified on the cobas 6000 and the Modular P, respectively. This study extends the utility of the CALIPER database to two additional analytical systems, which facilitates the broad application of CALIPER reference intervals at pediatric centers utilizing Roche biochemical assays. Transference studies across different analytical platforms can later be collectively analyzed in an attempt to develop common reference intervals across all clinical chemistry instruments to harmonize laboratory test interpretation in diagnosis and monitoring of pediatric disease. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Lin, Yi-Chun; Hsu, Ju-Yu; Shu, Jui-Hsu; Chi, Yi; Chiang, Su-Chi; Lee, Sho Tone
2008-11-01
Genome-wide search for the genes involved in arsenite resistance in two distinct variants A and A' of Leishmania amazonensis revealed that the two variants used two different mechanisms to achieve resistance, even though these two variants were derived from the same clone and selected against arsenite under the same conditions. In variant A, the variant with DNA amplification, the biochemical pathways for detoxification of oxidative stress, the energy generation system to support the biochemical and physiological needs of the variant for DNA and protein synthesis and the arsenite translocating system to dispose arsenite are among the primary biochemical events that are upregulated under the arsenite stress to gain resistance. In variant A', the variant without DNA amplification, the upregulation of aquaglyceroporin (AQP) gene and the high level of resistance to arsenate point to the direction that the resistance gained by the variant is due to arsenate which is probably oxidized from arsenite in the arsenite solution used for selection and the maintenance of the cell culture. As a result of the AQP upregulation for arsenite disposal, a different set of biochemical pathways for detoxification of oxidative stress, energy generation and cellular signaling are upregulated to sustain the growth of the variant to gain resistance to arsenate. From current evidences, reactive oxygen species (ROS) overproduced by the parasite soon after exposure to arsenite appear to play an instrumental role in both variants to initiate the subsequent biochemical events that allow the same clone of L. amazonensis to take two totally different routes to diverge into two different variants.
Mortensen, Ninell P; Mercier, Kelly A; McRitchie, Susan; Cavallo, Tammy B; Pathmasiri, Wimal; Stewart, Delisha; Sumner, Susan J
2016-06-01
Microfluidic devices that are currently being used in pharmaceutical research also have a significant potential for utilization in investigating exposure to infectious agents. We have established a microfluidic device cultured with Caco-2 cells, and utilized metabolomics to investigate the biochemical responses to the bacterial pathogen Campylobacter jejuni. In the microfluidic devices, Caco-2 cells polarize at day 5, are uniform, have defined brush borders and tight junctions, and form a mucus layer. Metabolomics analysis of cell culture media collected from both Caco-2 cell culture systems demonstrated a more metabolic homogenous biochemical profile in the media collected from microfluidic devices, compared with media collected from transwells. GeneGo pathway mapping indicated that aminoacyl-tRNA biosynthesis was perturbed by fluid flow, suggesting that fluid dynamics and shear stress impacts the cells translational quality control. Both microfluidic device and transwell culturing systems were used to investigate the impact of Campylobacter jejuni infection on biochemical processes. Caco-2 cells cultured in either system were infected at day 5 with C. jejuni 81-176 for 48 h. Metabolomics analysis clearly differentiated C. jejuni 81-176 infected and non-infected medias collected from the microfluidic devices, and demonstrated that C. jejuni 81-176 infection in microfluidic devices impacts branched-chain amino acid metabolism, glycolysis, and gluconeogenesis. In contrast, no distinction was seen in the biochemical profiles of infected versus non-infected media collected from cells cultured in transwells. Microfluidic culturing conditions demonstrated a more metabolically homogenous cell population, and present the opportunity for studying host-pathogen interactions for extended periods of time.
Mortensen, Ninell P.; Mercier, Kelly A.; McRitchie, Susan; Cavallo, Tammy B.; Pathmasiri, Wimal; Stewart, Delisha; Sumner, Susan J.
2016-01-01
Microfluidic devices that are currently being used in pharmaceutical research also have a significant potential for utilization in investigating exposure to infectious agents. We have established a microfluidic device cultured with Caco-2 cells, and utilized metabolomics to investigate the biochemical responses to the bacterial pathogen Campylobacter jejuni. In the microfluidic devices, Caco-2 cells polarize at day 5, are uniform, have defined brush borders and tight junctions, and form a mucus layer. Metabolomics analysis of cell culture media collected from both Caco-2 cell culture systems demonstrated a more metabolic homogenous biochemical profile in the media collected from microfluidic devices, compared with media collected from transwells. GeneGo pathway mapping indicated that aminoacyl-tRNA biosynthesis was perturbed by fluid flow, suggesting that fluid dynamics and shear stress impacts the cells translational quality control. Both microfluidic device and transwell culturing systems were used to investigate the impact of Campylobacter jejuni infection on biochemical processes. Caco-2 cells cultured in either system were infected at day 5 with C. jejuni 81-176 for 48 hours. Metabolomics analysis clearly differentiated C. jejuni 81-176 infected and non-infected medias collected from the microfluidic devices, and demonstrated that C. jejuni 81-176 infection in microfluidic devices impacts branched-chain amino acid metabolism, glycolysis, and gluconeogenesis. In contrast, no distinction was seen in the biochemical profiles of infected versus non-infected media collected from cells cultured in transwells. Microfluidic culturing conditions demonstrated a more metabolically homogenous cell population, and present the opportunity for studying host-pathogen interactions for extended periods of time. PMID:27231016
Eisenhofer, Graeme; Klink, Barbara; Richter, Susan; Lenders, Jacques WM; Robledo, Mercedes
2017-01-01
The tremendous advances over the past two decades in both clinical genetics and biochemical testing of chromaffin cell tumours have led to new considerations about how these aspects of laboratory medicine can be integrated to improve diagnosis and management of affected patients. With germline mutations in 15 genes now identified to be responsible for over a third of all cases of phaeochromocytomas and paragangliomas, these tumours are recognised to have one of the richest hereditary backgrounds among all neoplasms. Depending on the mutation, tumours show distinct differences in metabolic pathways that relate to or even directly impact clinical presentation. At the same time, there has been improved understanding about how catecholamines are synthesised, stored, secreted and metabolised by chromaffin cell tumours. Although the tumours may not always secrete catecholamines it has become clear that almost all continuously produce and metabolise catecholamines. This has not only fuelled changes in laboratory medicine, but has also assisted in recognition of genotype-biochemical phenotype relationships important for diagnostics and clinical care. In particular, differences in catecholamine and energy pathway metabolomes can guide genetic testing, assist with test interpretation and provide predictions about the nature, behaviour and imaging characteristics of the tumours. Conversely, results of genetic testing are important for guiding how routine biochemical testing should be employed and interpreted in surveillance programmes for at-risk patients. In these ways there are emerging needs for modern laboratory medicine to seamlessly integrate biochemical and genetic testing into the diagnosis and management of patients with chromaffin cell tumours. PMID:29332973
Application of cloud database in the management of clinical data of patients with skin diseases.
Mao, Xiao-fei; Liu, Rui; DU, Wei; Fan, Xue; Chen, Dian; Zuo, Ya-gang; Sun, Qiu-ning
2015-04-01
To evaluate the needs and applications of using cloud database in the daily practice of dermatology department. The cloud database was established for systemic scleroderma and localized scleroderma. Paper forms were used to record the original data including personal information, pictures, specimens, blood biochemical indicators, skin lesions,and scores of self-rating scales. The results were input into the cloud database. The applications of the cloud database in the dermatology department were summarized and analyzed. The personal and clinical information of 215 systemic scleroderma patients and 522 localized scleroderma patients were included and analyzed using the cloud database. The disease status,quality of life, and prognosis were obtained by statistical calculations. The cloud database can efficiently and rapidly store and manage the data of patients with skin diseases. As a simple, prompt, safe, and convenient tool, it can be used in patients information management, clinical decision-making, and scientific research.
Jeffryes, James G; Colastani, Ricardo L; Elbadawi-Sidhu, Mona; Kind, Tobias; Niehaus, Thomas D; Broadbelt, Linda J; Hanson, Andrew D; Fiehn, Oliver; Tyo, Keith E J; Henry, Christopher S
2015-01-01
In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography-mass spectrometry (LC-MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC-MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. Graphical abstractMINE database construction and access methods. The process of constructing a MINE database from the curated source databases is depicted on the left. The methods for accessing the database are shown on the right.
Meereis, Florian; Kaufmann, Michael
2004-10-15
The rapidly increasing number of completely sequenced genomes led to the establishment of the COG-database which, based on sequence homologies, assigns similar proteins from different organisms to clusters of orthologous groups (COGs). There are several bioinformatic studies that made use of this database to determine (hyper)thermophile-specific proteins by searching for COGs containing (almost) exclusively proteins from (hyper)thermophilic genomes. However, public software to perform individually definable group-specific searches is not available. The tool described here exactly fills this gap. The software is accessible at http://www.uni-wh.de/pcogr and is linked to the COG-database. The user can freely define two groups of organisms by selecting for each of the (current) 66 organisms to belong either to groupA, to the reference groupB or to be ignored by the algorithm. Then, for all COGs a specificity index is calculated with respect to the specificity to groupA, i. e. high scoring COGs contain proteins from the most of groupA organisms while proteins from the most organisms assigned to groupB are absent. In addition to ranking all COGs according to the user defined specificity criteria, a graphical visualization shows the distribution of all COGs by displaying their abundance as a function of their specificity indexes. This software allows detecting COGs specific to a predefined group of organisms. All COGs are ranked in the order of their specificity and a graphical visualization allows recognizing (i) the presence and abundance of such COGs and (ii) the phylogenetic relationship between groupA- and groupB-organisms. The software also allows detecting putative protein-protein interactions, novel enzymes involved in only partially known biochemical pathways, and alternate enzymes originated by convergent evolution.
Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A.; Pacheco-Sanchez, Magda A.; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N.; Islas-Osuna, Maria A.
2015-01-01
Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. “Kent” was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like “cell wall,” “carbohydrate catabolic process” and “starch and sucrose metabolic process” among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening. PMID:25741352
Dautt-Castro, Mitzuko; Ochoa-Leyva, Adrian; Contreras-Vergara, Carmen A; Pacheco-Sanchez, Magda A; Casas-Flores, Sergio; Sanchez-Flores, Alejandro; Kuhn, David N; Islas-Osuna, Maria A
2015-01-01
Fruit ripening is a physiological and biochemical process genetically programmed to regulate fruit quality parameters like firmness, flavor, odor and color, as well as production of ethylene in climacteric fruit. In this study, a transcriptomic analysis of mango (Mangifera indica L.) mesocarp cv. "Kent" was done to identify key genes associated with fruit ripening. Using the Illumina sequencing platform, 67,682,269 clean reads were obtained and a transcriptome of 4.8 Gb. A total of 33,142 coding sequences were predicted and after functional annotation, 25,154 protein sequences were assigned with a product according to Swiss-Prot database and 32,560 according to non-redundant database. Differential expression analysis identified 2,306 genes with significant differences in expression between mature-green and ripe mango [1,178 up-regulated and 1,128 down-regulated (FDR ≤ 0.05)]. The expression of 10 genes evaluated by both qRT-PCR and RNA-seq data was highly correlated (R = 0.97), validating the differential expression data from RNA-seq alone. Gene Ontology enrichment analysis, showed significantly represented terms associated to fruit ripening like "cell wall," "carbohydrate catabolic process" and "starch and sucrose metabolic process" among others. Mango genes were assigned to 327 metabolic pathways according to Kyoto Encyclopedia of Genes and Genomes database, among them those involved in fruit ripening such as plant hormone signal transduction, starch and sucrose metabolism, galactose metabolism, terpenoid backbone, and carotenoid biosynthesis. This study provides a mango transcriptome that will be very helpful to identify genes for expression studies in early and late flowering mangos during fruit ripening.
Hoffman, Jessica M.; Tran, ViLinh; Wachtman, Lynn M.; Green, Cara L.; Jones, Dean P.; Promislow, Daniel E.L.
2016-01-01
Primates tend to be long-lived for their size with humans being the longest lived of all primates. There are compelling reasons to understand the underlying age-related processes that shape human lifespan. But the very fact of our long lifespan that makes it so compelling, also makes it especially difficult to study. Thus, in studies of aging, researchers have turned to non-human primate models, including chimpanzees, baboons, and rhesus macaques. More recently, the common marmoset, Callithrix jacchus, has been recognized as a particularly valuable model in studies of aging, given its small size, ease of housing in captivity, and relatively short lifespan. However, little is known about the physiological changes that occur as marmosets age. To begin to fill in this gap, we utilized high sensitivity metabolomics to define the longitudinal biochemical changes associated with age in the common marmoset. We measured 2104 metabolites from blood plasma at three separate time points over a 17-month period, and we completed both a cross-sectional and longitudinal analysis of the metabolome. We discovered hundreds of metabolites associated with age and body weight in both male and female animals. Our longitudinal analysis identified age-associated metabolic pathways that were not found in our cross-sectional analysis. Pathways enriched for age-associated metabolites included tryptophan, nucleotide, and xenobiotic metabolism, suggesting these biochemical pathways might play an important role in the basic mechanisms of aging in primates. Moreover, we found that many metabolic pathways associated with age were sex specific. Our work illustrates the power of longitudinal approaches, even in a short time frame, to discover novel biochemical changes that occur with age. PMID:26805607
Challenges of the information age: the impact of false discovery on pathway identification.
Rog, Colin J; Chekuri, Srinivasa C; Edgerton, Mary E
2012-11-21
Pathways with members that have known relevance to a disease are used to support hypotheses generated from analyses of gene expression and proteomic studies. Using cancer as an example, the pitfalls of searching pathways databases as support for genes and proteins that could represent false discoveries are explored. The frequency with which networks could be generated from 100 instances each of randomly selected five and ten genes sets as input to MetaCore, a commercial pathways database, was measured. A PubMed search enumerated cancer-related literature published for any gene in the networks. Using three, two, and one maximum intervening step between input genes to populate the network, networks were generated with frequencies of 97%, 77%, and 7% using ten gene sets and 73%, 27%, and 1% using five gene sets. PubMed reported an average of 4225 cancer-related articles per network gene. This can be attributed to the richly populated pathways databases and the interest in the molecular basis of cancer. As information sources become enriched, they are more likely to generate plausible mechanisms for false discoveries.
Genetic and Environmental Pathways in Type 1 Diabetes Complication
2008-06-01
obese diabetic mice. Biochem Biophys Res Commun 2002. 294:592-596. 4. Beyan H, Goodier MR, Nawroly NS, Hawa MI, Bustin SA, Ogunkolade WB, Londei M...peroxidation in patients with hyperglycemic crisis . Diabetes 2004. 53:2079-2086. 14 In our second quarterly scientific progress report (09/01/07 – 11...cells induced to differentiate into insulin-positive cells. Biochem Biophys Res Commun . 2007;357(2):414-20. 44. Takahashi K, Tanabe K, Ohnuki M, Narita
Biochemical analysis of force-sensitive responses using a large-scale cell stretch device.
Renner, Derrick J; Ewald, Makena L; Kim, Timothy; Yamada, Soichiro
2017-09-03
Physical force has emerged as a key regulator of tissue homeostasis, and plays an important role in embryogenesis, tissue regeneration, and disease progression. Currently, the details of protein interactions under elevated physical stress are largely missing, therefore, preventing the fundamental, molecular understanding of mechano-transduction. This is in part due to the difficulty isolating large quantities of cell lysates exposed to force-bearing conditions for biochemical analysis. We designed a simple, easy-to-fabricate, large-scale cell stretch device for the analysis of force-sensitive cell responses. Using proximal biotinylation (BioID) analysis or phospho-specific antibodies, we detected force-sensitive biochemical changes in cells exposed to prolonged cyclic substrate stretch. For example, using promiscuous biotin ligase BirA* tagged α-catenin, the biotinylation of myosin IIA increased with stretch, suggesting the close proximity of myosin IIA to α-catenin under a force bearing condition. Furthermore, using phospho-specific antibodies, Akt phosphorylation was reduced upon stretch while Src phosphorylation was unchanged. Interestingly, phosphorylation of GSK3β, a downstream effector of Akt pathway, was also reduced with stretch, while the phosphorylation of other Akt effectors was unchanged. These data suggest that the Akt-GSK3β pathway is force-sensitive. This simple cell stretch device enables biochemical analysis of force-sensitive responses and has potential to uncover molecules underlying mechano-transduction.
Jeffryes, James G.; Colastani, Ricardo L.; Elbadawi-Sidhu, Mona; ...
2015-08-28
Metabolomics have proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likelymore » to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.« less
Hsa-miR-146a-5p modulates androgen-independent prostate cancer cells apoptosis by targeting ROCK1.
Xu, Bin; Huang, Yeqing; Niu, Xiaobing; Tao, Tao; Jiang, Liang; Tong, Na; Chen, Shuqiu; Liu, Ning; Zhu, Weidong; Chen, Ming
2015-12-01
MicroRNAs (miRNAs) have been demonstrated playing important roles in the procession of prostate cancer cells transformation from androgen-dependence to androgen-independence. We conducted the miRNA microarray and realtime PCR analyses in both androgen-dependent (ADPC) and androgen-independent prostate cancer (AIPC) tissues. We also explored the role of hsa-miR-146a-5p (miR-146a) in MSKCC prostate cancer clinical database. Moreover, the impact of miR-146a on prostate cancer cells apoptosis were detected by Hoechst staining and fluorescence-activated cell sorter (FACS). Its target is predicted by DIANA LAB online database and the result was assumed by western blotting and luciferase assay. We demonstrated that miR-146a was down-regulated in AIPC tissues and cell lines compared to that in the ADPC tissues. In MSKCC data re-analyses, we found that miR-146a was underexpressed in metastatic prostate cancer tissues and those with Gleason score >8, moreover, low level of miR-146a represented a high biochemical relapse rate after radical prostatectomy. In the functional analyses, we transfected miR-146a mimics into CPRC cell lines and found miR-146a induced cells apoptosis. In mechanic analyses, we found that miR-146a inhibited the basal level of Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) expression by targeting its 3'UTR and an inverse correlation of expression between miR-146a and ROCK1 was observed. Moreover, caspase 3 activity was stimulated by miR-146a overexpression. miR-146a has a critical role in the process of AIPC prostate cancer cells apoptosis through regulation of ROCK/Caspase 3 pathway. Targeting this pathway may be a promising therapeutic strategy for future personalized anti-cancer treatment. © 2015 Wiley Periodicals, Inc.
Pathway Distiller - multisource biological pathway consolidation
2012-01-01
Background One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. Methods After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. Results We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. Conclusions By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments. PMID:23134636
Pathway Distiller - multisource biological pathway consolidation.
Doderer, Mark S; Anguiano, Zachry; Suresh, Uthra; Dashnamoorthy, Ravi; Bishop, Alexander J R; Chen, Yidong
2012-01-01
One method to understand and evaluate an experiment that produces a large set of genes, such as a gene expression microarray analysis, is to identify overrepresentation or enrichment for biological pathways. Because pathways are able to functionally describe the set of genes, much effort has been made to collect curated biological pathways into publicly accessible databases. When combining disparate databases, highly related or redundant pathways exist, making their consolidation into pathway concepts essential. This will facilitate unbiased, comprehensive yet streamlined analysis of experiments that result in large gene sets. After gene set enrichment finds representative pathways for large gene sets, pathways are consolidated into representative pathway concepts. Three complementary, but different methods of pathway consolidation are explored. Enrichment Consolidation combines the set of the pathways enriched for the signature gene list through iterative combining of enriched pathways with other pathways with similar signature gene sets; Weighted Consolidation utilizes a Protein-Protein Interaction network based gene-weighting approach that finds clusters of both enriched and non-enriched pathways limited to the experiments' resultant gene list; and finally the de novo Consolidation method uses several measurements of pathway similarity, that finds static pathway clusters independent of any given experiment. We demonstrate that the three consolidation methods provide unified yet different functional insights of a resultant gene set derived from a genome-wide profiling experiment. Results from the methods are presented, demonstrating their applications in biological studies and comparing with a pathway web-based framework that also combines several pathway databases. Additionally a web-based consolidation framework that encompasses all three methods discussed in this paper, Pathway Distiller (http://cbbiweb.uthscsa.edu/PathwayDistiller), is established to allow researchers access to the methods and example microarray data described in this manuscript, and the ability to analyze their own gene list by using our unique consolidation methods. By combining several pathway systems, implementing different, but complementary pathway consolidation methods, and providing a user-friendly web-accessible tool, we have enabled users the ability to extract functional explanations of their genome wide experiments.
Akinpelu, Enoch A; Adetunji, Adewole T; Ntwampe, Seteno K O; Nchu, Felix; Mekuto, Lukhanyo
2017-10-01
Sustainability of nutrient requirements for microbial proliferation on a large scale is a challenge in bioremediation processes. This article presents data on biochemical properties of a free cyanide resistant and total nitrogen assimilating fungal isolate from the rhizosphere of Zea mays (maize) growing in soil contaminated with a cyanide-based pesticide. DNA extracted from this isolate were PCR amplified using universal primers; TEF1-α and ITS. The raw sequence files are available on the NCBI database. Characterisation using biochemical data was obtained using colorimetric reagents analysed with VITEK ® 2 software version 7.01. The data will be informative in selection of biocatalyst for environmental engineering application.
Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu
2003-11-07
To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s).
Pan, Deyun; Sun, Ning; Cheung, Kei-Hoi; Guan, Zhong; Ma, Ligeng; Holford, Matthew; Deng, Xingwang; Zhao, Hongyu
2003-01-01
Background To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis. Results We have developed PathMAPA, a web-based application written in Java that can be easily accessed over the Internet. An Oracle database is used to store, query, and manipulate the large amounts of data that are involved. PathMAPA allows its users to (i) upload and populate microarray data into a database; (ii) integrate gene expression with enzymes of the pathways; (iii) generate pathway diagrams without building image files manually; (iv) visualize gene expressions for each pathway at enzyme, locus, and probe levels; and (v) perform statistical tests at pathway, enzyme and gene levels. PathMAPA can be used to examine Arabidopsis thaliana gene expression patterns associated with metabolic pathways. Conclusion PathMAPA provides two unique features for the gene expression analysis of Arabidopsis thaliana: (i) automatic generation of pathways associated with gene expression and (ii) statistical tests at pathway level. The first feature allows for the periodical updating of genomic data for pathways, while the second feature can provide insight into how treatments affect relevant pathways for the selected experiment(s). PMID:14604444
A computational platform to maintain and migrate manual functional annotations for BioCyc databases.
Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A
2014-10-12
BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.
EcoCyc: a comprehensive database resource for Escherichia coli
Keseler, Ingrid M.; Collado-Vides, Julio; Gama-Castro, Socorro; Ingraham, John; Paley, Suzanne; Paulsen, Ian T.; Peralta-Gil, Martín; Karp, Peter D.
2005-01-01
The EcoCyc database (http://EcoCyc.org/) is a comprehensive source of information on the biology of the prototypical model organism Escherichia coli K12. The mission for EcoCyc is to contain both computable descriptions of, and detailed comments describing, all genes, proteins, pathways and molecular interactions in E.coli. Through ongoing manual curation, extensive information such as summary comments, regulatory information, literature citations and evidence types has been extracted from 8862 publications and added to Version 8.5 of the EcoCyc database. The EcoCyc database can be accessed through a World Wide Web interface, while the downloadable Pathway Tools software and data files enable computational exploration of the data and provide enhanced querying capabilities that web interfaces cannot support. For example, EcoCyc contains carefully curated information that can be used as training sets for bioinformatics prediction of entities such as promoters, operons, genetic networks, transcription factor binding sites, metabolic pathways, functionally related genes, protein complexes and protein–ligand interactions. PMID:15608210
Hierarchical modularization of biochemical pathways using fuzzy-c means clustering.
de Luis Balaguer, Maria A; Williams, Cranos M
2014-08-01
Biological systems that are representative of regulatory, metabolic, or signaling pathways can be highly complex. Mathematical models that describe such systems inherit this complexity. As a result, these models can often fail to provide a path toward the intuitive comprehension of these systems. More coarse information that allows a perceptive insight of the system is sometimes needed in combination with the model to understand control hierarchies or lower level functional relationships. In this paper, we present a method to identify relationships between components of dynamic models of biochemical pathways that reside in different functional groups. We find primary relationships and secondary relationships. The secondary relationships reveal connections that are present in the system, which current techniques that only identify primary relationships are unable to show. We also identify how relationships between components dynamically change over time. This results in a method that provides the hierarchy of the relationships among components, which can help us to understand the low level functional structure of the system and to elucidate potential hierarchical control. As a proof of concept, we apply the algorithm to the epidermal growth factor signal transduction pathway, and to the C3 photosynthesis pathway. We identify primary relationships among components that are in agreement with previous computational decomposition studies, and identify secondary relationships that uncover connections among components that current computational approaches were unable to reveal.
Exploring the combinatorial space of complete pathways to chemicals.
Wang, Lin; Ng, Chiam Yu; Dash, Satyakam; Maranas, Costas D
2018-04-06
Computational pathway design tools often face the challenges of balancing the stoichiometry of co-metabolites and cofactors, and dealing with reaction rule utilization in a single workflow. To this end, we provide an overview of two complementary stoichiometry-based pathway design tools optStoic and novoStoic developed in our group to tackle these challenges. optStoic is designed to determine the stoichiometry of overall conversion first which optimizes a performance criterion (e.g. high carbon/energy efficiency) and ensures a comprehensive search of co-metabolites and cofactors. The procedure then identifies the minimum number of intervening reactions to connect the source and sink metabolites. We also further the pathway design procedure by expanding the search space to include both known and hypothetical reactions, represented by reaction rules, in a new tool termed novoStoic. Reaction rules are derived based on a mixed-integer linear programming (MILP) compatible reaction operator, which allow us to explore natural promiscuous enzymes, engineer candidate enzymes that are not already promiscuous as well as design de novo enzymes. The identified biochemical reaction rules then guide novoStoic to design routes that expand the currently known biotransformation space using a single MILP modeling procedure. We demonstrate the use of the two computational tools in pathway elucidation by designing novel synthetic routes for isobutanol. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
Xu, Jun; Guo, Baohua; Zhang, Zengmin; Wu, Qiong; Zhou, Quan; Chen, Jinchun; Chen, Guoqiang; Li, Guodong
2005-06-30
A mathematical model is proposed for predicting the copolymer composition of the microbially synthesized polyhydroxyalkanoate (PHA) copolymers. Based on the biochemical reactions involved in the precursor formation and polymerization pathways, the model correlates the copolymer composition with the cultivation conditions, the enzyme levels and selectivity, and the metabolic pathways. It suggests the following points: (1) in the case of a sole carbon source, the copolymer composition depends mainly on the topology of the metabolic pathways and the selectivity of both the enzymes involved in the precursor formation and the polymerization route; (2) the copolymer composition can be varied in a wide range via alteration of the flux ratio of different types of monomers channeled from two or more independent and simultaneous pathways; (3) the enzymes which should be over-expressed or inhibited to obtain the desired copolymer composition can be predicted. For example, inhibition of the beta-oxidation pathway will increase the content of the monomer units with longer chain length. To test the model, various experiments were envisaged by varying cultivation time, concentration and chain length of the sole carbon source, and molar ratio of the cosubstrates. The predictions from the model agree well with the experimental results. Therefore, the proposed model will be useful in predicting the PHA copolymer composition under different biochemical reaction conditions. In other words, it can provide a guide for the synthesis of desired PHA copolymers.
Kumar, Ritesh; Zhao, Suwen; Vetting, Matthew W.; Wood, B. McKay; Sakai, Ayano; Cho, Kyuil; Solbiati, José; Almo, Steven C.; Sweedler, Jonathan V.; Jacobson, Matthew P.; Gerlt, John A.; Cronan, John E.
2014-01-01
ABSTRACT Through the use of genetic, enzymatic, metabolomic, and structural analyses, we have discovered the catabolic pathway for proline betaine, an osmoprotectant, in Paracoccus denitrificans and Rhodobacter sphaeroides. Genetic and enzymatic analyses showed that several of the key enzymes of the hydroxyproline betaine degradation pathway also function in proline betaine degradation. Metabolomic analyses detected each of the metabolic intermediates of the pathway. The proline betaine catabolic pathway was repressed by osmotic stress and cold stress, and a regulatory transcription factor was identified. We also report crystal structure complexes of the P. denitrificans HpbD hydroxyproline betaine epimerase/proline betaine racemase with l-proline betaine and cis-hydroxyproline betaine. PMID:24520058
Pathway Design, Engineering, and Optimization.
Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin
The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.
Serum Biochemical Phenotypes in the Domestic Dog
Chang, Yu-Mei; Hadox, Erin; Szladovits, Balazs; Garden, Oliver A.
2016-01-01
The serum or plasma biochemical profile is essential in the diagnosis and monitoring of systemic disease in veterinary medicine, but current reference intervals typically take no account of breed-specific differences. Breed-specific hematological phenotypes have been documented in the domestic dog, but little has been published on serum biochemical phenotypes in this species. Serum biochemical profiles of dogs in which all measurements fell within the existing reference intervals were retrieved from a large veterinary database. Serum biochemical profiles from 3045 dogs were retrieved, of which 1495 had an accompanying normal glucose concentration. Sixty pure breeds plus a mixed breed control group were represented by at least 10 individuals. All analytes, except for sodium, chloride and glucose, showed variation with age. Total protein, globulin, potassium, chloride, creatinine, cholesterol, total bilirubin, ALT, CK, amylase, and lipase varied between sexes. Neutering status significantly impacted all analytes except albumin, sodium, calcium, urea, and glucose. Principal component analysis of serum biochemical data revealed 36 pure breeds with distinctive phenotypes. Furthermore, comparative analysis identified 23 breeds with significant differences from the mixed breed group in all biochemical analytes except urea and glucose. Eighteen breeds were identified by both principal component and comparative analysis. Tentative reference intervals were generated for breeds with a distinctive phenotype identified by comparative analysis and represented by at least 120 individuals. This is the first large-scale analysis of breed-specific serum biochemical phenotypes in the domestic dog and highlights potential genetic components of biochemical traits in this species. PMID:26919479
MIPS: a database for genomes and protein sequences.
Mewes, H W; Heumann, K; Kaps, A; Mayer, K; Pfeiffer, F; Stocker, S; Frishman, D
1999-01-01
The Munich Information Center for Protein Sequences (MIPS-GSF), Martinsried near Munich, Germany, develops and maintains genome oriented databases. It is commonplace that the amount of sequence data available increases rapidly, but not the capacity of qualified manual annotation at the sequence databases. Therefore, our strategy aims to cope with the data stream by the comprehensive application of analysis tools to sequences of complete genomes, the systematic classification of protein sequences and the active support of sequence analysis and functional genomics projects. This report describes the systematic and up-to-date analysis of genomes (PEDANT), a comprehensive database of the yeast genome (MYGD), a database reflecting the progress in sequencing the Arabidopsis thaliana genome (MATD), the database of assembled, annotated human EST clusters (MEST), and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). MIPS provides access through its WWW server (http://www.mips.biochem.mpg.de) to a spectrum of generic databases, including the above mentioned as well as a database of protein families (PROTFAM), the MITOP database, and the all-against-all FASTA database. PMID:9847138
dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock.
Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta
2016-01-01
Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf.
dEMBF: A Comprehensive Database of Enzymes of Microalgal Biofuel Feedstock
Misra, Namrata; Panda, Prasanna Kumar; Parida, Bikram Kumar; Mishra, Barada Kanta
2016-01-01
Microalgae have attracted wide attention as one of the most versatile renewable feedstocks for production of biofuel. To develop genetically engineered high lipid yielding algal strains, a thorough understanding of the lipid biosynthetic pathway and the underpinning enzymes is essential. In this work, we have systematically mined the genomes of fifteen diverse algal species belonging to Chlorophyta, Heterokontophyta, Rhodophyta, and Haptophyta, to identify and annotate the putative enzymes of lipid metabolic pathway. Consequently, we have also developed a database, dEMBF (Database of Enzymes of Microalgal Biofuel Feedstock), which catalogues the complete list of identified enzymes along with their computed annotation details including length, hydrophobicity, amino acid composition, subcellular location, gene ontology, KEGG pathway, orthologous group, Pfam domain, intron-exon organization, transmembrane topology, and secondary/tertiary structural data. Furthermore, to facilitate functional and evolutionary study of these enzymes, a collection of built-in applications for BLAST search, motif identification, sequence and phylogenetic analysis have been seamlessly integrated into the database. dEMBF is the first database that brings together all enzymes responsible for lipid synthesis from available algal genomes, and provides an integrative platform for enzyme inquiry and analysis. This database will be extremely useful for algal biofuel research. It can be accessed at http://bbprof.immt.res.in/embf. PMID:26727469
Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection.
Yoon, Jeongah; Si, Yaguang; Nolan, Ryan; Lee, Kyongbum
2007-09-15
The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top-down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. Supplementary data are available at Bioinformatics online.
The pomegranate (Punica granatum L.) genome and the genomics of punicalagin biosynthesis.
Qin, Gaihua; Xu, Chunyan; Ming, Ray; Tang, Haibao; Guyot, Romain; Kramer, Elena M; Hu, Yudong; Yi, Xingkai; Qi, Yongjie; Xu, Xiangyang; Gao, Zhenghui; Pan, Haifa; Jian, Jianbo; Tian, Yinping; Yue, Zhen; Xu, Yiliu
2017-09-01
Pomegranate (Punica granatum L.) is a perennial fruit crop grown since ancient times that has been planted worldwide and is known for its functional metabolites, particularly punicalagins. We have sequenced and assembled the pomegranate genome with 328 Mb anchored into nine pseudo-chromosomes and annotated 29 229 gene models. A Myrtales lineage-specific whole-genome duplication event was detected that occurred in the common ancestor before the divergence of pomegranate and Eucalyptus. Repetitive sequences accounted for 46.1% of the assembled genome. We found that the integument development gene INNER NO OUTER (INO) was under positive selection and potentially contributed to the development of the fleshy outer layer of the seed coat, an edible part of pomegranate fruit. The genes encoding the enzymes for synthesis and degradation of lignin, hemicelluloses and cellulose were also differentially expressed between soft- and hard-seeded varieties, reflecting differences in their accumulation in cultivars differing in seed hardness. Candidate genes for punicalagin biosynthesis were identified and their expression patterns indicated that gallic acid synthesis in tissues could follow different biochemical pathways. The genome sequence of pomegranate provides a valuable resource for the dissection of many biological and biochemical traits and also provides important insights for the acceleration of breeding. Elucidation of the biochemical pathway(s) involved in punicalagin biosynthesis could assist breeding efforts to increase production of this bioactive compound. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.
Zhang, Bo; Yuan, Jiaqi; Brüschweiler, Rafael
2017-07-12
A primary goal of metabolomics is the characterization of a potentially very large number of metabolites that are part of complex mixtures. Application to biofluids and tissue samples offers insights into biochemical metabolic pathways and their role in health and disease. 1D 1 H and 2D 13 C- 1 H HSQC NMR spectra are most commonly used for this purpose. They yield quantitative information about each proton of the mixture, but do not tell which protons belong to the same molecule. Interpretation requires the use of NMR spectral databases, which naturally limits these investigations to known metabolites. Here, a new method is presented that uses complementary ion exchange resin beads to differentially attenuate 2D NMR cross-peaks that belong to different metabolites. Based on their characteristic attenuation patterns, cross-peaks could be clustered and assigned to individual molecules, including unknown metabolites with multiple spin systems, as demonstrated for a metabolite model mixture and E. coli cell lysate. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Steffensen, Jon Lund; Dufault-Thompson, Keith; Zhang, Ying
2018-01-01
The metabolism of individual organisms and biological communities can be viewed as a network of metabolites connected to each other through chemical reactions. In metabolic networks, chemical reactions transform reactants into products, thereby transferring elements between these metabolites. Knowledge of how elements are transferred through reactant/product pairs allows for the identification of primary compound connections through a metabolic network. However, such information is not readily available and is often challenging to obtain for large reaction databases or genome-scale metabolic models. In this study, a new algorithm was developed for automatically predicting the element-transferring reactant/product pairs using the limited information available in the standard representation of metabolic networks. The algorithm demonstrated high efficiency in analyzing large datasets and provided accurate predictions when benchmarked with manually curated data. Applying the algorithm to the visualization of metabolic networks highlighted pathways of primary reactant/product connections and provided an organized view of element-transferring biochemical transformations. The algorithm was implemented as a new function in the open source software package PSAMM in the release v0.30 (https://zhanglab.github.io/psamm/).
Estey, Mathew P; Cohen, Ashley H; Colantonio, David A; Chan, Man Khun; Marvasti, Tina Binesh; Randell, Edward; Delvin, Edgard; Cousineau, Jocelyne; Grey, Vijaylaxmi; Greenway, Donald; Meng, Qing H; Jung, Benjamin; Bhuiyan, Jalaluddin; Seccombe, David; Adeli, Khosrow
2013-09-01
The CALIPER program recently established a comprehensive database of age- and sex-stratified pediatric reference intervals for 40 biochemical markers. However, this database was only directly applicable for Abbott ARCHITECT assays. We therefore sought to expand the scope of this database to biochemical assays from other major manufacturers, allowing for a much wider application of the CALIPER database. Based on CLSI C28-A3 and EP9-A2 guidelines, CALIPER reference intervals were transferred (using specific statistical criteria) to assays performed on four other commonly used clinical chemistry platforms including Beckman Coulter DxC800, Ortho Vitros 5600, Roche Cobas 6000, and Siemens Vista 1500. The resulting reference intervals were subjected to a thorough validation using 100 reference specimens (healthy community children and adolescents) from the CALIPER bio-bank, and all testing centers participated in an external quality assessment (EQA) evaluation. In general, the transferred pediatric reference intervals were similar to those established in our previous study. However, assay-specific differences in reference limits were observed for many analytes, and in some instances were considerable. The results of the EQA evaluation generally mimicked the similarities and differences in reference limits among the five manufacturers' assays. In addition, the majority of transferred reference intervals were validated through the analysis of CALIPER reference samples. This study greatly extends the utility of the CALIPER reference interval database which is now directly applicable for assays performed on five major analytical platforms in clinical use, and should permit the worldwide application of CALIPER pediatric reference intervals. Copyright © 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Characterization of mango (Mangifera indica L.) transcriptome and chloroplast genome.
Azim, M Kamran; Khan, Ishtaiq A; Zhang, Yong
2014-05-01
We characterized mango leaf transcriptome and chloroplast genome using next generation DNA sequencing. The RNA-seq output of mango transcriptome generated >12 million reads (total nucleotides sequenced >1 Gb). De novo transcriptome assembly generated 30,509 unigenes with lengths in the range of 300 to ≥3,000 nt and 67× depth of coverage. Blast searching against nonredundant nucleotide databases and several Viridiplantae genomic datasets annotated 24,593 mango unigenes (80% of total) and identified Citrus sinensis as closest neighbor of mango with 9,141 (37%) matched sequences. The annotation with gene ontology and Clusters of Orthologous Group terms categorized unigene sequences into 57 and 25 classes, respectively. More than 13,500 unigenes were assigned to 293 KEGG pathways. Besides major plant biology related pathways, KEGG based gene annotation pointed out active presence of an array of biochemical pathways involved in (a) biosynthesis of bioactive flavonoids, flavones and flavonols, (b) biosynthesis of terpenoids and lignins and (c) plant hormone signal transduction. The mango transcriptome sequences revealed 235 proteases belonging to five catalytic classes of proteolytic enzymes. The draft genome of mango chloroplast (cp) was obtained by a combination of Sanger and next generation sequencing. The draft mango cp genome size is 151,173 bp with a pair of inverted repeats of 27,093 bp separated by small and large single copy regions, respectively. Out of 139 genes in mango cp genome, 91 found to be protein coding. Sequence analysis revealed cp genome of C. sinensis as closest neighbor of mango. We found 51 short repeats in mango cp genome supposed to be associated with extensive rearrangements. This is the first report of transcriptome and chloroplast genome analysis of any Anacardiaceae family member.
Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.
Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.
Ding, Yan; Xiong, Xiao-Li; Zhou, Li-Shan; Yan, Su-Qi; Qin, Huan; Li, Hua-Rong; Zhang, Ling-Ling; Chen, Peng; Yao, Cong; Jiang, Zhi-Xia; Zhao, Lei
2016-12-01
The aim of this study is to investigate Emodin on alleviating intrahepatic cholestasis by regulation of liver farnesoid X receptor (FXR) pathway. Cell and animal models of intrahepatic cholestatis were established. Biochemical tests and histomorphology were performed. The messenger RNA (mRNA) and protein expression of FXR, small heterodimer partner (SHP), uridine diphosphate glucuronosyltransferase 2 family polypeptide B4 (UGT2B4), and bile salt export pump (BSEP) was detected. As a result, compared with the model group, the serum levels of biochemical test were significantly lower in the Emodin group (P <0.01). The histopathological changes were remitted significantly by Emodin treatment. In the model group, the mRNA and protein expression of FXR, SHP, UGT2B4, and BSEP was significantly lower than in the normal group in cell models (P <0.05). With Emodin intervention, the expression of FXR, SHP, UGT2B4, and BSEP was notably increased (P <0.05). In conclusion, Emodin plays a protective role in intrahepatic cholestasis by promoting FXR signal pathways. © The Author(s) 2016.
Martinez-Urtaza, Jaime; Lozano-Leon, Antonio; Viña-Feas, Alejandro; de Novoa, Jacobo; Garcia-Martin, Oscar
2006-02-01
Genetic differences in clinical and environmental strains of Vibrio parahaemolyticus have been widely used as criteria in identifying pathogenic isolates. However, few studies have been carried out to assess the differences in biochemical characteristics of V. parahaemolyticus isolates from human and environmental sources. We compared the biochemical profiles obtained by the characterization of V. parahaemolyticus isolates from human infections and the marine environment using the API 20E system. Environmental and clinical isolates showed significant differences in the gelatin and arabinose tests. Additionally, clinical isolates were correctly identified according to the API 20E profile using 0.85% NaCl diluent, but they presented nonspecific profiles with 2% NaCl diluent. In contrast, use of 2% NaCl diluent facilitated correct identification of the environmental isolates. Clinical isolates showed significant differences in up to five biochemical tests with respect to the API 20E database. The API 20E system is widely used in routine identification of bacteria in clinical laboratories, and this discrepancy in an important number of biochemical tests may lead to misidentification of V. parahaemolyticus infection.
Xu, Hui; Chakrabarty, Yindrila; Philmus, Benjamin; Mehta, Angad P.; Bhandari, Dhananjay; Hohmann, Hans-Peter; Begley, Tadhg P.
2016-01-01
Riboflavin is a common cofactor, and its biosynthetic pathway is well characterized. However, its catabolic pathway, despite intriguing hints in a few distinct organisms, has never been established. This article describes the isolation of a Microbacterium maritypicum riboflavin catabolic strain, and the cloning of the riboflavin catabolic genes. RcaA, RcaB, RcaD, and RcaE were overexpressed and biochemically characterized as riboflavin kinase, riboflavin reductase, ribokinase, and riboflavin hydrolase, respectively. Based on these activities, a pathway for riboflavin catabolism is proposed. PMID:27590337
The JAK/STAT pathway in obesity and diabetes.
Gurzov, Esteban N; Stanley, William J; Pappas, Evan G; Thomas, Helen E; Gough, Daniel J
2016-08-01
Diabetes mellitus are complex, multi-organ metabolic pathologies characterized by hyperglycemia. Emerging evidence shows that the highly conserved and potent JAK/STAT signaling pathway is required for normal homeostasis, and, when dysregulated, contributes to the development of obesity and diabetes. In this review, we analyze the role of JAK/STAT activation in the brain, liver, muscle, fat and pancreas, and how this affects the course of the disease. We also consider the therapeutic implications of targeting the JAK/STAT pathway in treatment of obesity and diabetes. © 2016 Federation of European Biochemical Societies.
Viroid Pathogenicity: One Process, Many Faces
Owens, Robert A.; Hammond, Rosemarie W.
2009-01-01
Despite the non-coding nature of their small RNA genomes, the visible symptoms of viroid infection resemble those associated with many plant virus diseases. Recent evidence indicates that viroid-derived small RNAs acting through host RNA silencing pathways play a key role in viroid pathogenicity. Host responses to viroid infection are complex, involving signaling cascades containing host-encoded protein kinases and crosstalk between hormonal and defense-signaling pathways. Studies of viroid-host interaction in the context of entire biochemical or developmental pathways are just beginning, and many working hypotheses have yet to be critically tested. PMID:21994551
Detecting breakdown points in metabolic networks.
Tagore, Somnath; De, Rajat K
2011-12-14
A complex network of biochemical reactions present in an organism generates various biological moieties necessary for its survival. It is seen that biological systems are robust to genetic and environmental changes at all levels of organization. Functions of various organisms are sustained against mutational changes by using alternative pathways. It is also seen that if any one of the paths for production of the same metabolite is hampered, an alternate path tries to overcome this defect and helps in combating the damage. Certain physical, chemical or genetic change in any of the precursor substrate of a biochemical reaction may damage the production of the ultimate product. We employ a quantitative approach for simulating this phenomena of causing a physical change in the biochemical reactions by performing external perturbations to 12 metabolic pathways under carbohydrate metabolism in Saccharomyces cerevisae as well as 14 metabolic pathways under carbohydrate metabolism in Homo sapiens. Here, we investigate the relationship between structure and degree of compatibility of metabolites against external perturbations, i.e., robustness. Robustness can also be further used to identify the extent to which a metabolic pathway can resist a mutation event. Biological networks with a certain connectivity distribution may be very resilient to a particular attack but not to another. The goal of this work is to determine the exact boundary of network breakdown due to both random and targeted attack, thereby analyzing its robustness. We also find that compared to various non-standard models, metabolic networks are exceptionally robust. Here, we report the use of a 'Resilience-based' score for enumerating the concept of 'network-breakdown'. We also use this approach for analyzing metabolite essentiality providing insight into cellular robustness that can be further used for future drug development. We have investigated the behavior of metabolic pathways under carbohydrate metabolism in S. cerevisae and H. sapiens against random and targeted attack. Both random as well as targeted resilience were calculated by formulating a measure, that we termed as 'Resilience score'. Datasets of metabolites were collected for 12 metabolic pathways belonging to carbohydrate metabolism in S. cerevisae and 14 metabolic pathways belonging to carbohydrate metabolism in H. sapiens from Kyoto Encyclopedia for Genes and Genomes (KEGG). Copyright © 2011 Elsevier Ltd. All rights reserved.
Metformin effects on biochemical recurrence and metabolic signaling in the prostate.
Winters, Brian; Plymate, Stephen; Zeliadt, Steven B; Holt, Sarah; Zhang, Xiaotun; Hu, Elaine; Lin, Daniel W; Morrissey, Colm; Wooldridge, Bryan; Gore, John L; Porter, Michael P; Wright, Jonathan L
2015-11-01
Metformin has received considerable attention as a potential anti-cancer agent. Animal and in-vitro prostate cancer (PCa) models have demonstrated decreased tumor growth with metformin, however the precise mechanisms are unknown. We examine the effects of metformin on PCa biochemical recurrence (BCR) in a large clinical database followed by evaluating metabolic signaling changes in a cohort of men undergoing prostate needle biopsy (PNB). Men treated for localized PCa were identified in a comprehensive clinical database between 2001 and 2010. Cox regression was performed to determine association with BCR relative to metformin use. We next identified a separate case-control cohort of men undergoing prostate needle biopsy (PNB) stratified by metformin use. Differences in mean IHC scores were compared with linear regression for phosphorylated IR, IGF-IR, AKT, and AMPK. One thousand seven hundred and thirty four men were evaluated for BCR with mean follow up of 41 months (range 1-121 months). "Ever" metformin use was not associated with BCR (HR 1.12, 0.77-1.65), however men reporting both pre/post-treatment metformin use had a 45% reduction in BCR (HR = 0.55 (0.31-0.96)). For the tissue-based study, 48 metformin users and 42 controls underwent PNB. Significantly greater staining in phosphorylated nuclear (p-IR, p-AKT) and cytoplasmic (p-IR, p-IGF-1R) insulin signaling proteins were seen in patients with PCa detected compared to those with negative PNB (P-values all <0.006). When stratified by metformin use, IGF-1R remained significantly elevated (P = 0.01) in men with PCa detected whereas p-AMPK (P = 0.05) was elevated only in those without PCa. Metformin use is associated with reduced BCR after treatment of localized PCa when considering pre-diagnostic and cumulative dosing. In men with cancer detected on PNB, insulin signaling markers were significantly elevated compared to negative PNB patients. The finding of IGF-1R elevation in positive PNBs versus p-AMPK elevation in negative PNBs suggests altered metabolic pathway activation precipitated by metformin use. © 2015 Wiley Periodicals, Inc.
Metformin Effects on Biochemical Recurrence and Metabolic Signaling in the Prostate
Winters, Brian; Plymate, Stephen; Zeliadt, Steven B; Holt, Sarah; Zhang, Xiaotun; Hu, Elaine; Lin, Daniel W.; Morrissey, Colm; Wooldridge, Bryan; Gore, John L; Porter, Michael P; Wright, Jonathan L
2015-01-01
Background Metformin has received considerable attention as a potential anti-cancer agent. Animal and in-vitro prostate cancer (PCa) models have demonstrated decreased tumor growth with metformin, however the precise mechanisms are unknown. We examine the effects of metformin on PCa biochemical recurrence (BCR) in a large clinical database followed by evaluating metabolic signaling changes in a cohort of men undergoing prostate needle biopsy (PNB). Methods Men treated for localized PCa were identified in a comprehensive clinical database between 2001 and 2010. Cox regression was performed to determine association with BCR relative to metformin use. We next identified a separate case-control cohort of men undergoing prostate needle biopsy (PNB) stratified by metformin use. Differences in mean IHC scores were compared with linear regression for phosphorylated IR, IGF-IR, AKT, and AMPK. Results 1,734 men were evaluated for BCR with mean follow up of 41 months (range 1-121 months). ‘Ever’ metformin use was not associated with BCR (HR 1.12, 0.77-1.65), however men reporting both pre/post-treatment metformin use had a 45% reduction in BCR (HR=0.55 (0.31-0.96)). For the tissue-based study, 48 metformin users and 42 controls underwent PNB. Significantly greater staining in phosphorylated nuclear (p-IR, p-AKT) and cytoplasmic (p-IR, p-IGF-1R) insulin signaling proteins were seen in patients with PCa detected compared to those with negative PNB (p-values all < 0.006). When stratified by metformin use, IGF-1R remained significantly elevated (p=0.01) in men with PCa detected whereas p-AMPK (p=0.05) was elevated only in those without PCa. Conclusion Metformin use is associated with reduced BCR after treatment of localized PCa when considering pre-diagnostic and cumulative dosing. In men with cancer detected on PNB, insulin signaling markers were significantly elevated compared to negative PNB patients. The finding of IGF-1R elevation in positive PNBs versus p-AMPK elevation in negative PNBs suggests altered metabolic pathway activation precipitated by metformin use. PMID:26201966
MIPS: a database for protein sequences and complete genomes.
Mewes, H W; Hani, J; Pfeiffer, F; Frishman, D
1998-01-01
The MIPS group [Munich Information Center for Protein Sequences of the German National Center for Environment and Health (GSF)] at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, is involved in a number of data collection activities, including a comprehensive database of the yeast genome, a database reflecting the progress in sequencing the Arabidopsis thaliana genome, the systematic analysis of other small genomes and the collection of protein sequence data within the framework of the PIR-International Protein Sequence Database (described elsewhere in this volume). Through its WWW server (http://www.mips.biochem.mpg.de ) MIPS provides access to a variety of generic databases, including a database of protein families as well as automatically generated data by the systematic application of sequence analysis algorithms. The yeast genome sequence and its related information was also compiled on CD-ROM to provide dynamic interactive access to the 16 chromosomes of the first eukaryotic genome unraveled. PMID:9399795
Zhang, Shuyi; Bryant, Donald A
2015-05-29
Cyanobacteria are important photoautotrophic bacteria with extensive but variable metabolic capacities. The existence of the glyoxylate cycle, a variant of the TCA cycle, is still poorly documented in cyanobacteria. Previous studies reported the activities of isocitrate lyase and malate synthase, the key enzymes of the glyoxylate cycle in some cyanobacteria, but other studies concluded that these enzymes are missing. In this study the genes encoding isocitrate lyase and malate synthase from Chlorogloeopsis fritschii PCC 9212 were identified, and the recombinant enzymes were biochemically characterized. Consistent with the presence of the enzymes of the glyoxylate cycle, C. fritschii could assimilate acetate under both light and dark growth conditions. Transcript abundances for isocitrate lyase and malate synthase increased, and C. fritschii grew faster, when the growth medium was supplemented with acetate. Adding acetate to the growth medium also increased the yield of poly-3-hydroxybutyrate. When the genes encoding isocitrate lyase and malate synthase were expressed in Synechococcus sp. PCC 7002, the acetate assimilation capacity of the resulting strain was greater than that of wild type. Database searches showed that the genes for the glyoxylate cycle exist in only a few other cyanobacteria, all of which are able to fix nitrogen. This study demonstrates that the glyoxylate cycle exists in a few cyanobacteria, and that this pathway plays an important role in the assimilation of acetate for growth in one of those organisms. The glyoxylate cycle might play a role in coordinating carbon and nitrogen metabolism under conditions of nitrogen fixation. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Targeting the Hippo signalling pathway for cancer treatment.
Nakatani, Keisuke; Maehama, Tomohiko; Nishio, Miki; Goto, Hiroki; Kato, Wakako; Omori, Hirofumi; Miyachi, Yosuke; Togashi, Hideru; Shimono, Yohei; Suzuki, Akira
2017-03-01
The Hippo signalling pathway monitors cell-cell contact and external factors that shape tissue structure. In mice, tumourigenesis and developmental abnormalities are common consequences of dysregulated Hippo signalling. Expression of Hippo pathway components is also frequently altered in human tumours and correlates with poor prognosis and reduced patient survival. Thus, the Hippo pathway is an attractive anti-cancer target. Here, we provide an overview of the function and regulation of Hippo signalling components and summarize progress to date on the development of agents able to regulate Hippo signalling for cancer therapy. © The Authors 2016. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.
Mangalam, AK; Poisson, LM; Nemutlu, E; Datta, I; Denic, A; Dzeja, P; Rodriguez, M; Rattan, R; Giri, S
2013-01-01
Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the CNS. Although, MS is well characterized in terms of the role played by immune cells, cytokines and CNS pathology, nothing is known about the metabolic alterations that occur during the disease process in circulation. Recently, metabolic aberrations have been defined in various disease processes either as contributing to the disease, as potential biomarkers, or as therapeutic targets. Thus in an attempt to define the metabolic alterations that may be associated with MS disease progression, we profiled the plasma metabolites at the chronic phase of disease utilizing relapsing remitting-experimental autoimmune encephalomyelitis (RR-EAE) model in SJL mice. At the chronic phase of the disease (day 45), untargeted global metabolomic profiling of plasma collected from EAE diseased SJL and healthy mice was performed, using a combination of high-throughput liquid-and-gas chromatography with mass spectrometry. A total of 282 metabolites were identified, with significant changes observed in 44 metabolites (32 up-regulated and 12 down-regulated), that mapped to lipid, amino acid, nucleotide and xenobiotic metabolism and distinguished EAE from healthy group (p<0.05, false discovery rate (FDR)<0.23). Mapping the differential metabolite signature to their respective biochemical pathways using the Kyoto Encyclopedia of Genes and Genomics (KEGG) database, we found six major pathways that were significantly altered (containing concerted alterations) or impacted (containing alteration in key junctions). These included bile acid biosynthesis, taurine metabolism, tryptophan and histidine metabolism, linoleic acid and D-arginine metabolism pathways. Overall, this study identified a 44 metabolite signature drawn from various metabolic pathways which correlated well with severity of the EAE disease, suggesting that these metabolic changes could be exploited as (1) biomarkers for EAE/MS progression and (2) to design new treatment paradigms where metabolic interventions could be combined with present and experimental therapeutics to achieve better treatment of MS. PMID:24273690
Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology
Latendresse, Mario; Paley, Suzanne M.; Krummenacker, Markus; Ong, Quang D.; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M.; Caspi, Ron
2016-01-01
Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. PMID:26454094
LeishCyc: a guide to building a metabolic pathway database and visualization of metabolomic data.
Saunders, Eleanor C; MacRae, James I; Naderer, Thomas; Ng, Milica; McConville, Malcolm J; Likić, Vladimir A
2012-01-01
The complexity of the metabolic networks in even the simplest organisms has raised new challenges in organizing metabolic information. To address this, specialized computer frameworks have been developed to capture, manage, and visualize metabolic knowledge. The leading databases of metabolic information are those organized under the umbrella of the BioCyc project, which consists of the reference database MetaCyc, and a number of pathway/genome databases (PGDBs) each focussed on a specific organism. A number of PGDBs have been developed for bacterial, fungal, and protozoan pathogens, greatly facilitating dissection of the metabolic potential of these organisms and the identification of new drug targets. Leishmania are protozoan parasites belonging to the family Trypanosomatidae that cause a broad spectrum of diseases in humans. In this work we use the LeishCyc database, the BioCyc database for Leishmania major, to describe how to build a BioCyc database from genomic sequences and associated annotations. By using metabolomic data generated in our group, we show how such databases can be utilized to elucidate specific changes in parasite metabolism.
Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB.
Ullah, M; Schmidt, H; Cho, K H; Wolkenhauer, O
2006-03-01
The analysis of complex biochemical networks is conducted in two popular conceptual frameworks for modelling. The deterministic approach requires the solution of ordinary differential equations (ODEs, reaction rate equations) with concentrations as continuous state variables. The stochastic approach involves the simulation of differential-difference equations (chemical master equations, CMEs) with probabilities as variables. This is to generate counts of molecules for chemical species as realisations of random variables drawn from the probability distribution described by the CMEs. Although there are numerous tools available, many of them free, the modelling and simulation environment MATLAB is widely used in the physical and engineering sciences. We describe a collection of MATLAB functions to construct and solve ODEs for deterministic simulation and to implement realisations of CMEs for stochastic simulation using advanced MATLAB coding (Release 14). The program was successfully applied to pathway models from the literature for both cases. The results were compared to implementations using alternative tools for dynamic modelling and simulation of biochemical networks. The aim is to provide a concise set of MATLAB functions that encourage the experimentation with systems biology models. All the script files are available from www.sbi.uni-rostock.de/ publications_matlab-paper.html.
Nolz, Jeffrey C; Gomez, Timothy S; Zhu, Peimin; Li, Shuixing; Medeiros, Ricardo B; Shimizu, Yoji; Burkhardt, Janis K; Freedman, Bruce D; Billadeau, Daniel D
2006-01-10
The engagement of the T cell receptor results in actin cytoskeletal reorganization at the immune synapse (IS) and the triggering of biochemical signaling cascades leading to gene regulation and, ultimately, cellular activation. Recent studies have identified the WAVE family of proteins as critical mediators of Rac1-induced actin reorganization in other cell types. However, whether these proteins participate in actin reorganization at the IS or signaling pathways in T cells has not been investigated. By using a combination of biochemical, genetic, and cell biology approaches, we provide evidence that WAVE2 is recruited to the IS, is biochemically modified, and is required for actin reorganization and beta-integrin-mediated adhesion after TCR crosslinking. Moreover, we show that WAVE2 regulates calcium entry at a point distal to PLCgamma1 activation and IP(3)-mediated store release. These data reveal a role for WAVE2 in regulating multiple pathways leading to T cell activation. In particular, this work shows that WAVE2 is a key component of the actin regulatory machinery in T cells and that it also participates in linking intracellular calcium store depletion to calcium release-activated calcium (CRAC) channel activation.
Mu, Dongyan; Seager, Thomas; Rao, P Suresh; Zhao, Fu
2010-10-01
Lignocellulosic biomass can be converted into ethanol through either biochemical or thermochemical conversion processes. Biochemical conversion involves hydrolysis and fermentation while thermochemical conversion involves gasification and catalytic synthesis. Even though these routes produce comparable amounts of ethanol and have similar energy efficiency at the plant level, little is known about their relative environmental performance from a life cycle perspective. Especially, the indirect impacts, i.e. emissions and resource consumption associated with the production of various process inputs, are largely neglected in previous studies. This article compiles material and energy flow data from process simulation models to develop life cycle inventory and compares the fossil fuel consumption, greenhouse gas emissions, and water consumption of both biomass-to-ethanol production processes. The results are presented in terms of contributions from feedstock, direct, indirect, and co-product credits for four representative biomass feedstocks i.e., wood chips, corn stover, waste paper, and wheat straw. To explore the potentials of the two conversion pathways, different technological scenarios are modeled, including current, 2012 and 2020 technology targets, as well as different production/co-production configurations. The modeling results suggest that biochemical conversion has slightly better performance on greenhouse gas emission and fossil fuel consumption, but that thermochemical conversion has significantly less direct, indirect, and life cycle water consumption. Also, if the thermochemical plant operates as a biorefinery with mixed alcohol co-products separated for chemicals, it has the potential to achieve better performance than biochemical pathway across all environmental impact categories considered due to higher co-product credits associated with chemicals being displaced. The results from this work serve as a starting point for developing full life cycle assessment model that facilitates effective decision-making regarding lignocellulosic ethanol production.
NASA Astrophysics Data System (ADS)
Mu, Dongyan; Seager, Thomas; Rao, P. Suresh; Zhao, Fu
2010-10-01
Lignocellulosic biomass can be converted into ethanol through either biochemical or thermochemical conversion processes. Biochemical conversion involves hydrolysis and fermentation while thermochemical conversion involves gasification and catalytic synthesis. Even though these routes produce comparable amounts of ethanol and have similar energy efficiency at the plant level, little is known about their relative environmental performance from a life cycle perspective. Especially, the indirect impacts, i.e. emissions and resource consumption associated with the production of various process inputs, are largely neglected in previous studies. This article compiles material and energy flow data from process simulation models to develop life cycle inventory and compares the fossil fuel consumption, greenhouse gas emissions, and water consumption of both biomass-to-ethanol production processes. The results are presented in terms of contributions from feedstock, direct, indirect, and co-product credits for four representative biomass feedstocks i.e., wood chips, corn stover, waste paper, and wheat straw. To explore the potentials of the two conversion pathways, different technological scenarios are modeled, including current, 2012 and 2020 technology targets, as well as different production/co-production configurations. The modeling results suggest that biochemical conversion has slightly better performance on greenhouse gas emission and fossil fuel consumption, but that thermochemical conversion has significantly less direct, indirect, and life cycle water consumption. Also, if the thermochemical plant operates as a biorefinery with mixed alcohol co-products separated for chemicals, it has the potential to achieve better performance than biochemical pathway across all environmental impact categories considered due to higher co-product credits associated with chemicals being displaced. The results from this work serve as a starting point for developing full life cycle assessment model that facilitates effective decision-making regarding lignocellulosic ethanol production.
A Synthetic Alternative to Canonical One-Carbon Metabolism.
Bouzon, Madeleine; Perret, Alain; Loreau, Olivier; Delmas, Valérie; Perchat, Nadia; Weissenbach, Jean; Taran, Frédéric; Marlière, Philippe
2017-08-18
One-carbon metabolism is an ubiquitous metabolic pathway that encompasses the reactions transferring formyl-, hydroxymethyl- and methyl-groups bound to tetrahydrofolate for the synthesis of purine nucleotides, thymidylate, methionine and dehydropantoate, the precursor of coenzyme A. An alternative cyclic pathway was designed that substitutes 4-hydroxy-2-oxobutanoic acid (HOB), a compound absent from known metabolism, for the amino acids serine and glycine as one-carbon donors. It involves two novel reactions, the transamination of l-homoserine and the transfer of a one-carbon unit from HOB to tetrahydrofolate releasing pyruvate as coproduct. Since canonical reactions regenerate l-homoserine from pyruvate by carboxylation and subsequent reduction, every one-carbon moiety made available for anabolic reactions originates from CO 2 . The HOB-dependent pathway was established in an Escherichia coli auxotroph selected for prototrophy using long-term cultivation protocols. Genetic, metabolic and biochemical evidence support the emergence of a functional HOB-dependent one-carbon pathway achieved with the recruitment of the two enzymes l-homoserine transaminase and HOB-hydroxymethyltransferase and of HOB as an essential metabolic intermediate. Escherichia coli biochemical reprogramming was achieved by minimally altering canonical metabolism and leveraging on natural selection mechanisms, thereby launching the resulting strain on an evolutionary trajectory diverging from all known extant species.
The Molecular Ecophysiology of Programmed Cell Death in Marine Phytoplankton
NASA Astrophysics Data System (ADS)
Bidle, Kay D.
2015-01-01
Planktonic, prokaryotic, and eukaryotic photoautotrophs (phytoplankton) share a diverse and ancient evolutionary history, during which time they have played key roles in regulating marine food webs, biogeochemical cycles, and Earth's climate. Because phytoplankton represent the basis of marine ecosystems, the manner in which they die critically determines the flow and fate of photosynthetically fixed organic matter (and associated elements), ultimately constraining upper-ocean biogeochemistry. Programmed cell death (PCD) and associated pathway genes, which are triggered by a variety of nutrient stressors and are employed by parasitic viruses, play an integral role in determining the cell fate of diverse photoautotrophs in the modern ocean. Indeed, these multifaceted death pathways continue to shape the success and evolutionary trajectory of diverse phytoplankton lineages at sea. Research over the past two decades has employed physiological, biochemical, and genetic techniques to provide a novel, comprehensive, mechanistic understanding of the factors controlling this key process. Here, I discuss the current understanding of the genetics, activation, and regulation of PCD pathways in marine model systems; how PCD evolved in unicellular photoautotrophs; how it mechanistically interfaces with viral infection pathways; how stress signals are sensed and transduced into cellular responses; and how novel molecular and biochemical tools are revealing the impact of PCD genes on the fate of natural phytoplankton assemblages.
An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.
Nassif, Houssam; Al-Ali, Hassan; Khuri, Sawsan; Keirouz, Walid; Page, David
2010-01-01
Hexoses are simple sugars that play a key role in many cellular pathways, and in the regulation of development and disease mechanisms. Current protein-sugar computational models are based, at least partially, on prior biochemical findings and knowledge. They incorporate different parts of these findings in predictive black-box models. We investigate the empirical support for biochemical findings by comparing Inductive Logic Programming (ILP) induced rules to actual biochemical results. We mine the Protein Data Bank for a representative data set of hexose binding sites, non-hexose binding sites and surface grooves. We build an ILP model of hexose-binding sites and evaluate our results against several baseline machine learning classifiers. Our method achieves an accuracy similar to that of other black-box classifiers while providing insight into the discriminating process. In addition, it confirms wet-lab findings and reveals a previously unreported Trp-Glu amino acids dependency.
Islam, Mohammad Tawhidul; Mohamedali, Abidali; Ahn, Seong Beom; Nawar, Ishmam; Baker, Mark S; Ranganathan, Shoba
2017-01-01
In the past decade, proteomics and mass spectrometry have taken tremendous strides forward, particularly in the life sciences, spurred on by rapid advances in technology resulting in generation and conglomeration of vast amounts of data. Though this has led to tremendous advancements in biology, the interpretation of the data poses serious challenges for many practitioners due to the immense size and complexity of the data. Furthermore, the lack of annotation means that a potential gold mine of relevant biological information may be hiding within this data. We present here a simple and intuitive workflow for the research community to investigate and mine this data, not only to extract relevant data but also to segregate usable, quality data to develop hypotheses for investigation and validation. We apply an MS evidence workflow for verifying peptides of proteins from one's own data as well as publicly available databases. We then integrate a suite of freely available bioinformatics analysis and annotation software tools to identify homologues and map putative functional signatures, gene ontology and biochemical pathways. We also provide an example of the functional annotation of missing proteins in human chromosome 7 data from the NeXtProt database, where no evidence is available at the proteomic, antibody, or structural levels. We give examples of protocols, tools and detailed flowcharts that can be extended or tailored to interpret and annotate the proteome of any novel organism.
FragariaCyc: A Metabolic Pathway Database for Woodland Strawberry Fragaria vesca
Naithani, Sushma; Partipilo, Christina M.; Raja, Rajani; Elser, Justin L.; Jaiswal, Pankaj
2016-01-01
FragariaCyc is a strawberry-specific cellular metabolic network based on the annotated genome sequence of Fragaria vesca L. ssp. vesca, accession Hawaii 4. It was built on the Pathway-Tools platform using MetaCyc as the reference. The experimental evidences from published literature were used for supporting/editing existing entities and for the addition of new pathways, enzymes, reactions, compounds, and small molecules in the database. To date, FragariaCyc comprises 66 super-pathways, 488 unique pathways, 2348 metabolic reactions, 3507 enzymes, and 2134 compounds. In addition to searching and browsing FragariaCyc, researchers can compare pathways across various plant metabolic networks and analyze their data using Omics Viewer tool. We view FragariaCyc as a resource for the community of researchers working with strawberry and related fruit crops. It can help understanding the regulation of overall metabolism of strawberry plant during development and in response to diseases and abiotic stresses. FragariaCyc is available online at http://pathways.cgrb.oregonstate.edu. PMID:26973684
KEGGtranslator: visualizing and converting the KEGG PATHWAY database to various formats.
Wrzodek, Clemens; Dräger, Andreas; Zell, Andreas
2011-08-15
The KEGG PATHWAY database provides a widely used service for metabolic and nonmetabolic pathways. It contains manually drawn pathway maps with information about the genes, reactions and relations contained therein. To store these pathways, KEGG uses KGML, a proprietary XML-format. Parsers and translators are needed to process the pathway maps for usage in other applications and algorithms. We have developed KEGGtranslator, an easy-to-use stand-alone application that can visualize and convert KGML formatted XML-files into multiple output formats. Unlike other translators, KEGGtranslator supports a plethora of output formats, is able to augment the information in translated documents (e.g. MIRIAM annotations) beyond the scope of the KGML document, and amends missing components to fragmentary reactions within the pathway to allow simulations on those. KEGGtranslator is freely available as a Java(™) Web Start application and for download at http://www.cogsys.cs.uni-tuebingen.de/software/KEGGtranslator/. KGML files can be downloaded from within the application. clemens.wrzodek@uni-tuebingen.de Supplementary data are available at Bioinformatics online.
Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar
2015-04-01
The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.
Consensus and conflict cards for metabolic pathway databases
2013-01-01
Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. Conclusions C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. PMID:23803311
Consensus and conflict cards for metabolic pathway databases.
Stobbe, Miranda D; Swertz, Morris A; Thiele, Ines; Rengaw, Trebor; van Kampen, Antoine H C; Moerland, Perry D
2013-06-26
The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. We introduce the concept of Consensus and Conflict Cards (C₂Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C₂Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. C₂Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C₂Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.
RUAN, XIYUN; LI, HONGYUN; LIU, BO; CHEN, JIE; ZHANG, SHIBAO; SUN, ZEQIANG; LIU, SHUANGQING; SUN, FAHAI; LIU, QINGYONG
2015-01-01
The aim of the present study was to develop a novel method for identifying pathways associated with renal cell carcinoma (RCC) based on a gene co-expression network. A framework was established where a co-expression network was derived from the database as well as various co-expression approaches. First, the backbone of the network based on differentially expressed (DE) genes between RCC patients and normal controls was constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The differentially co-expressed links were detected by Pearson’s correlation, the empirical Bayesian (EB) approach and Weighted Gene Co-expression Network Analysis (WGCNA). The co-expressed gene pairs were merged by a rank-based algorithm. We obtained 842; 371; 2,883 and 1,595 co-expressed gene pairs from the co-expression networks of the STRING database, Pearson’s correlation EB method and WGCNA, respectively. Two hundred and eighty-one differentially co-expressed (DC) gene pairs were obtained from the merged network using this novel method. Pathway enrichment analysis based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the network enrichment analysis (NEA) method were performed to verify feasibility of the merged method. Results of the KEGG and NEA pathway analyses showed that the network was associated with RCC. The suggested method was computationally efficient to identify pathways associated with RCC and has been identified as a useful complement to traditional co-expression analysis. PMID:26058425
Evolution of amino acid metabolism inferred through cladistic analysis.
Cunchillos, Chomin; Lecointre, Guillaume
2003-11-28
Because free amino acids were most probably available in primitive abiotic environments, their metabolism is likely to have provided some of the very first metabolic pathways of life. What were the first enzymatic reactions to emerge? A cladistic analysis of metabolic pathways of the 16 aliphatic amino acids and 2 portions of the Krebs cycle was performed using four criteria of homology. The analysis is not based on sequence comparisons but, rather, on coding similarities in enzyme properties. The properties used are shared specific enzymatic activity, shared enzymatic function without substrate specificity, shared coenzymes, and shared functional family. The tree shows that the earliest pathways to emerge are not portions of the Krebs cycle but metabolisms of aspartate, asparagine, glutamate, and glutamine. The views of Horowitz (Horowitz, N. H. (1945) Proc. Natl. Acad. Sci. U. S. A. 31, 153-157) and Cordón (Cordón, F. (1990) Tratado Evolucionista de Biologia, Aguilar, Madrid, Spain), according to which the upstream reactions in the catabolic pathways and the downstream reactions in the anabolic pathways are the earliest in evolution, are globally corroborated; however, with some exceptions. These are due to later opportunistic connections of pathways (actually already suggested by these authors). Earliest enzymatic functions are mostly catabolic; they were deaminations, transaminations, and decarboxylations. From the consensus tree we extracted four time spans for amino acid metabolism development. For some amino acids catabolism and biosynthesis occurred at the same time (Asp, Glu, Lys, Leu, Ala, Val, Ile, Pro, Arg). For others ultimate reactions that use amino acids as a substrate or as a product are distinct in time, with catabolism preceding anabolism for Asn, Gln, and Cys and anabolism preceding catabolism for Ser, Met, and Thr. Cladistic analysis of the structure of biochemical pathways makes hypotheses in biochemical evolution explicit and parsimonious.
The care pathway: concepts and theories: an introduction.
Schrijvers, Guus; van Hoorn, Arjan; Huiskes, Nicolette
2012-01-01
This article addresses first the definition of a (care) pathway, and then follows a description of theories since the 1950s. It ends with a discussion of theoretical advantages and disadvantages of care pathways for patients and professionals. The objective of this paper is to provide a theoretical base for empirical studies on care pathways. The knowledge for this chapter is based on several books on pathways, which we found by searching in the digital encyclopedia Wikipedia. Although this is not usual in scientific publications, this method was used because books are not searchable by databases as Pubmed. From 2005, we performed a literature search on Pubmed and other literature databases, and with the keywords integrated care pathway, clinical pathway, critical pathway, theory, research, and evaluation. One of the inspirational sources was the website of the European Pathway Association (EPA) and its journal International Journal of Care Pathways. The authors visited several sites for this paper. These are mentioned as illustration of a concept or theory. Most of them have English websites with more information. The URLs of these websites are not mentioned in this paper as a reference, because the content of them changes fast, sometimes every day.
The care pathway: concepts and theories: an introduction
Schrijvers, Guus; van Hoorn, Arjan; Huiskes, Nicolette
2012-01-01
This article addresses first the definition of a (care) pathway, and then follows a description of theories since the 1950s. It ends with a discussion of theoretical advantages and disadvantages of care pathways for patients and professionals. The objective of this paper is to provide a theoretical base for empirical studies on care pathways. The knowledge for this chapter is based on several books on pathways, which we found by searching in the digital encyclopedia Wikipedia. Although this is not usual in scientific publications, this method was used because books are not searchable by databases as Pubmed. From 2005, we performed a literature search on Pubmed and other literature databases, and with the keywords integrated care pathway, clinical pathway, critical pathway, theory, research, and evaluation. One of the inspirational sources was the website of the European Pathway Association (EPA) and its journal International Journal of Care Pathways. The authors visited several sites for this paper. These are mentioned as illustration of a concept or theory. Most of them have English websites with more information. The URLs of these websites are not mentioned in this paper as a reference, because the content of them changes fast, sometimes every day. PMID:23593066
Abou El Hassan, Mohamed; Stoianov, Alexandra; Araújo, Petra A T; Sadeghieh, Tara; Chan, Man Khun; Chen, Yunqi; Randell, Edward; Nieuwesteeg, Michelle; Adeli, Khosrow
2015-11-01
The CALIPER program has established a comprehensive database of pediatric reference intervals using largely the Abbott ARCHITECT biochemical assays. To expand clinical application of CALIPER reference standards, the present study is aimed at transferring CALIPER reference intervals from the Abbott ARCHITECT to Beckman Coulter AU assays. Transference of CALIPER reference intervals was performed based on the CLSI guidelines C28-A3 and EP9-A2. The new reference intervals were directly verified using up to 100 reference samples from the healthy CALIPER cohort. We found a strong correlation between Abbott ARCHITECT and Beckman Coulter AU biochemical assays, allowing the transference of the vast majority (94%; 30 out of 32 assays) of CALIPER reference intervals previously established using Abbott assays. Transferred reference intervals were, in general, similar to previously published CALIPER reference intervals, with some exceptions. Most of the transferred reference intervals were sex-specific and were verified using healthy reference samples from the CALIPER biobank based on CLSI criteria. It is important to note that the comparisons performed between the Abbott and Beckman Coulter assays make no assumptions as to assay accuracy or which system is more correct/accurate. The majority of CALIPER reference intervals were transferrable to Beckman Coulter AU assays, allowing the establishment of a new database of pediatric reference intervals. This further expands the utility of the CALIPER database to clinical laboratories using the AU assays; however, each laboratory should validate these intervals for their analytical platform and local population as recommended by the CLSI. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology
Paley, Suzanne M.; Krummenacker, Markus; Latendresse, Mario; Dale, Joseph M.; Lee, Thomas J.; Kaipa, Pallavi; Gilham, Fred; Spaulding, Aaron; Popescu, Liviu; Altman, Tomer; Paulsen, Ian; Keseler, Ingrid M.; Caspi, Ron
2010-01-01
Pathway Tools is a production-quality software environment for creating a type of model-organism database called a Pathway/Genome Database (PGDB). A PGDB such as EcoCyc integrates the evolving understanding of the genes, proteins, metabolic network and regulatory network of an organism. This article provides an overview of Pathway Tools capabilities. The software performs multiple computational inferences including prediction of metabolic pathways, prediction of metabolic pathway hole fillers and prediction of operons. It enables interactive editing of PGDBs by DB curators. It supports web publishing of PGDBs, and provides a large number of query and visualization tools. The software also supports comparative analyses of PGDBs, and provides several systems biology analyses of PGDBs including reachability analysis of metabolic networks, and interactive tracing of metabolites through a metabolic network. More than 800 PGDBs have been created using Pathway Tools by scientists around the world, many of which are curated DBs for important model organisms. Those PGDBs can be exchanged using a peer-to-peer DB sharing system called the PGDB Registry. PMID:19955237
A geographically-diverse collection of 418 human gut microbiome pathway genome databases
Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.
2017-01-01
Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools. PMID:28398290
NASA Astrophysics Data System (ADS)
Hawcroft, David M.
1996-11-01
Courses of organic chemistry frequently include studies of biochemistry and hence of biochemical techniques. Radioisotopes have played a major role in the understanding of metabolic pathways, transport, enzyme activity and other processes. The experiment described in this paper uses simple techniques to illustrate the procedures involved in working with radioisotopes when following a simplified metabolic pathway. Safety considerations are discussed and a list of safety rules is provided, but the experiment itself uses very low levels of a weak beta-emitting isotope (tritium). Plant material is suggested to reduce legal, financial and emotive problems, but the techniques are applicable to all soft-tissued material. The problems involved in data interpretation in radioisotope experiments resulting from radiation quenching are resolved by simple correction calculations, and the merits of using radioisotopes shown by a calculation of the low mass of material being measured. Suggestions for further experiments are given.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hicks, Katherine A.; Ealick, Steven E.
HpxW from the ubiquitous pathogenKlebsiella pneumoniaeis involved in a novel uric acid degradation pathway downstream from the formation of oxalurate. Specifically, HpxW is an oxamate amidohydrolase which catalyzes the conversion of oxamate to oxalate and is a member of the Ntn-hydrolase superfamily. HpxW is autoprocessed from an inactive precursor to form a heterodimer, resulting in a 35.5 kDa α subunit and a 20 kDa β subunit. Here, the structure of HpxW is presented and the substrate complex is modeled. In addition, the steady-state kinetics of this enzyme and two active-site variants were characterized. These structural and biochemical studies provide furthermore » insight into this class of enzymes and allow a mechanism for catalysis consistent with other members of the Ntn-hydrolase superfamily to be proposed.« less
Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks
Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui
2017-01-01
The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways. PMID:29049295
Croft, Harry A
2017-12-01
The neurobiology of sexual response is driven in part by dopamine and serotonin-the former modulating excitatory pathways and the latter regulating inhibitory pathways. Neurobiological underpinnings of hypoactive sexual desire disorder (HSDD) are seemingly related to overactive serotonin activity that results in underactive dopamine activity. As such, pharmacologic agents that decrease serotonin, increase dopamine, or some combination thereof, have therapeutic potential for HSDD. To review the role of serotonin in female sexual function and the effects of pharmacologic interventions that target the serotonin system in the treatment of HSDD. Searches of the Medline database for articles on serotonin and female sexual function. Relevant articles from the peer-reviewed literature were included. Female sexual response is regulated not only by the sex hormones but also by several neurotransmitters. It is postulated that dopamine, norepinephrine, oxytocin, and melanocortins serve as key neuromodulators for the excitatory pathways, whereas serotonin, opioids, and endocannabinoids serve as key neuromodulators for the inhibitory pathways. Serotonin appears to be a key inhibitory modulator of sexual desire, because it decreases the ability of excitatory systems to be activated by sexual cues. Centrally acting drugs that modulate the excitatory and inhibitory pathways involved in sexual desire (eg, bremelanotide, bupropion, buspirone, flibanserin) have been investigated as treatment options for HSDD. However, only flibanserin, a multifunctional serotonin agonist and antagonist (5-hydroxytryptamine [5-HT] 1A receptor agonist and 5-HT 2A receptor antagonist), is currently approved for the treatment of HSDD. The central serotonin system is 1 biochemical target for medications intended to treat HSDD. This narrative review integrates findings from preclinical studies and clinical trials to elucidate neurobiological underpinnings of HSDD but is limited to 1 neurotransmitter system (serotonin). Serotonin overactivity is a putative cause of sexual dysfunction in patients with HSDD. The unique pharmacologic profile of flibanserin tones down inhibitory serotonergic function and restores dopaminergic and noradrenergic function. Croft HA. Understanding the Role of Serotonin in Female Hypoactive Sexual Desire Disorder and Treatment Options. J Sex Med 2017;14:1575-1584. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
Text mining for metabolic pathways, signaling cascades, and protein networks.
Hoffmann, Robert; Krallinger, Martin; Andres, Eduardo; Tamames, Javier; Blaschke, Christian; Valencia, Alfonso
2005-05-10
The complexity of the information stored in databases and publications on metabolic and signaling pathways, the high throughput of experimental data, and the growing number of publications make it imperative to provide systems to help the researcher navigate through these interrelated information resources. Text-mining methods have started to play a key role in the creation and maintenance of links between the information stored in biological databases and its original sources in the literature. These links will be extremely useful for database updating and curation, especially if a number of technical problems can be solved satisfactorily, including the identification of protein and gene names (entities in general) and the characterization of their types of interactions. The first generation of openly accessible text-mining systems, such as iHOP (Information Hyperlinked over Proteins), provides additional functions to facilitate the reconstruction of protein interaction networks, combine database and text information, and support the scientist in the formulation of novel hypotheses. The next challenge is the generation of comprehensive information regarding the general function of signaling pathways and protein interaction networks.
The Fanconi anemia DNA repair pathway: structural and functional insights into a complex disorder.
Walden, Helen; Deans, Andrew J
2014-01-01
Mutations in any of at least sixteen FANC genes (FANCA-Q) cause Fanconi anemia, a disorder characterized by sensitivity to DNA interstrand crosslinking agents. The clinical features of cytopenia, developmental defects, and tumor predisposition are similar in each group, suggesting that the gene products participate in a common pathway. The Fanconi anemia DNA repair pathway consists of an anchor complex that recognizes damage caused by interstrand crosslinks, a multisubunit ubiquitin ligase that monoubiquitinates two substrates, and several downstream repair proteins including nucleases and homologous recombination enzymes. We review progress in the use of structural and biochemical approaches to understanding how each FANC protein functions in this pathway.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Karp, Peter D.
Pathway Tools is a systems-biology software package written by SRI International (SRI) that produces Pathway/Genome Databases (PGDBs) for organisms with a sequenced genome. Pathway Tools also provides a wide range of capabilities for analyzing predicted metabolic networks and user-generated omics data. More than 5,000 academic, industrial, and government groups have licensed Pathway Tools. This user community includes researchers at all three DOE bioenergy centers, as well as academic and industrial metabolic engineering (ME) groups. An integral part of the Pathway Tools software is MetaCyc, a large, multiorganism database of metabolic pathways and enzymes that SRI and its academic collaborators manuallymore » curate. This project included two main goals: I. Enhance the MetaCyc content of bioenergy-related enzymes and pathways. II. Develop computational tools for engineering metabolic pathways that satisfy specified design goals, in particular for bioenergy-related pathways. In part I, SRI proposed to significantly expand the coverage of bioenergy-related metabolic information in MetaCyc, followed by the generation of organism-specific PGDBs for all energy-relevant organisms sequenced at the DOE Joint Genome Institute (JGI). Part I objectives included: 1: Expand the content of MetaCyc to include bioenergy-related enzymes and pathways. 2: Enhance the Pathway Tools software to enable display of complex polymer degradation processes. 3: Create new PGDBs for the energy-related organisms sequenced by JGI, update existing PGDBs with new MetaCyc content, and make these data available to JBEI via the BioCyc website. In part II, SRI proposed to develop an efficient computational tool for the engineering of metabolic pathways. Part II objectives included: 4: Develop computational tools for generating metabolic pathways that satisfy specified design goals, enabling users to specify parameters such as starting and ending compounds, and preferred or disallowed intermediate compounds. The pathways were to be generated using metabolic reactions from a reference database (DB). 5: Develop computational tools for ranking the pathways generated in objective (4) according to their optimality. The ranking criteria include stoichiometric yield, the number and cost of additional inputs and the cofactor compounds required by the pathway, pathway length, and pathway energetics. 6: Develop tools for visualizing generated pathways to facilitate the evaluation of a large space of generated pathways.« less
Chromophore absorbance change quantification in tissue during low-level light therapy
NASA Astrophysics Data System (ADS)
Huynh, Daniel; Chung, Christine; Qian, Li; Lilge, Lothar
2012-03-01
Low Level Light Therapy (LLLT) has been implicated to stimulate tissue, promoting healing and reducing pain. One of the potential pathways stimulated by LLLT relates to the electron transport chain, where photon quantum energy can induce a change in the biochemical reactions within the cell. The aim of this study is to assess the feasibility to exploit light additionally as a diagnostic tool to determine tissue physiological states, particularly in quantifying the changes in redox states of Cytochrome C as a result of induced LLLT biochemical reactions.
Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology.
Karp, Peter D; Latendresse, Mario; Paley, Suzanne M; Krummenacker, Markus; Ong, Quang D; Billington, Richard; Kothari, Anamika; Weaver, Daniel; Lee, Thomas; Subhraveti, Pallavi; Spaulding, Aaron; Fulcher, Carol; Keseler, Ingrid M; Caspi, Ron
2016-09-01
Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. This article outlines the advances in Pathway Tools in the past 5 years. Major additions include components for metabolic modeling, metabolic route search, computation of atom mappings and estimation of compound Gibbs free energies of formation; addition of editors for signaling pathways, for genome sequences and for cellular architecture; storage of gene essentiality data and phenotype data; display of multiple alignments, and of signaling and electron-transport pathways; and development of Python and web-services application programming interfaces. Scientists around the world have created more than 9800 Pathway/Genome Databases by using Pathway Tools, many of which are curated databases for important model organisms. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Metabolic pathway reconstruction of eugenol to vanillin bioconversion in Aspergillus niger
Srivastava, Suchita; Luqman, Suaib; Khan, Feroz; Chanotiya, Chandan S; Darokar, Mahendra P
2010-01-01
Identification of missing genes or proteins participating in the metabolic pathways as enzymes are of great interest. One such class of pathway is involved in the eugenol to vanillin bioconversion. Our goal is to develop an integral approach for identifying the topology of a reference or known pathway in other organism. We successfully identify the missing enzymes and then reconstruct the vanillin biosynthetic pathway in Aspergillus niger. The procedure combines enzyme sequence similarity searched through BLAST homology search and orthologs detection through COG & KEGG databases. Conservation of protein domains and motifs was searched through CDD, PFAM & PROSITE databases. Predictions regarding how proteins act in pathway were validated experimentally and also compared with reported data. The bioconversion of vanillin was screened on UV-TLC plates and later confirmed through GC and GC-MS techniques. We applied a procedure for identifying missing enzymes on the basis of conserved functional motifs and later reconstruct the metabolic pathway in target organism. Using the vanillin biosynthetic pathway of Pseudomonas fluorescens as a case study, we indicate how this approach can be used to reconstruct the reference pathway in A. niger and later results were experimentally validated through chromatography and spectroscopy techniques. PMID:20978605
NemaPath: online exploration of KEGG-based metabolic pathways for nematodes
Wylie, Todd; Martin, John; Abubucker, Sahar; Yin, Yong; Messina, David; Wang, Zhengyuan; McCarter, James P; Mitreva, Makedonka
2008-01-01
Background Nematode.net is a web-accessible resource for investigating gene sequences from parasitic and free-living nematode genomes. Beyond the well-characterized model nematode C. elegans, over 500,000 expressed sequence tags (ESTs) and nearly 600,000 genome survey sequences (GSSs) have been generated from 36 nematode species as part of the Parasitic Nematode Genomics Program undertaken by the Genome Center at Washington University School of Medicine. However, these sequencing data are not present in most publicly available protein databases, which only include sequences in Swiss-Prot. Swiss-Prot, in turn, relies on GenBank/Embl/DDJP for predicted proteins from complete genomes or full-length proteins. Description Here we present the NemaPath pathway server, a web-based pathway-level visualization tool for navigating putative metabolic pathways for over 30 nematode species, including 27 parasites. The NemaPath approach consists of two parts: 1) a backend tool to align and evaluate nematode genomic sequences (curated EST contigs) against the annotated Kyoto Encyclopedia of Genes and Genomes (KEGG) protein database; 2) a web viewing application that displays annotated KEGG pathway maps based on desired confidence levels of primary sequence similarity as defined by a user. NemaPath also provides cross-referenced access to nematode genome information provided by other tools available on Nematode.net, including: detailed NemaGene EST cluster information; putative translations; GBrowse EST cluster views; links from nematode data to external databases for corresponding synonymous C. elegans counterparts, subject matches in KEGG's gene database, and also KEGG Ontology (KO) identification. Conclusion The NemaPath server hosts metabolic pathway mappings for 30 nematode species and is available on the World Wide Web at . The nematode source sequences used for the metabolic pathway mappings are available via FTP , as provided by the Genome Center at Washington University School of Medicine. PMID:18983679
The Fanconi anaemia pathway: new players and new functions.
Ceccaldi, Raphael; Sarangi, Prabha; D'Andrea, Alan D
2016-06-01
The Fanconi anaemia pathway repairs DNA interstrand crosslinks (ICLs) in the genome. Our understanding of this complex pathway is still evolving, as new components continue to be identified and new biochemical systems are used to elucidate the molecular steps of repair. The Fanconi anaemia pathway uses components of other known DNA repair processes to achieve proper repair of ICLs. Moreover, Fanconi anaemia proteins have functions in genome maintenance beyond their canonical roles of repairing ICLs. Such functions include the stabilization of replication forks and the regulation of cytokinesis. Thus, Fanconi anaemia proteins are emerging as master regulators of genomic integrity that coordinate several repair processes. Here, we summarize our current understanding of the functions of the Fanconi anaemia pathway in ICL repair, together with an overview of its connections with other repair pathways and its emerging roles in genome maintenance.
Colonic Butyrate-Producing Communities in Humans: an Overview Using Omics Data
Pieper, Dietmar H.
2017-01-01
ABSTRACT Given the key role of butyrate for host health, understanding the ecology of intestinal butyrate-producing communities is a top priority for gut microbiota research. To this end, we performed a pooled analysis on 2,387 metagenomic/transcriptomic samples from 15 publicly available data sets that originated from three continents and encompassed eight diseases as well as specific interventions. For analyses, a gene catalogue was constructed from gene-targeted assemblies of all genes from butyrate synthesis pathways of all samples and from an updated reference database derived from genome screenings. We demonstrate that butyrate producers establish themselves within the first year of life and display high abundances (>20% of total bacterial community) in adults regardless of origin. Various bacteria form this functional group, exhibiting a biochemical diversity including different pathways and terminal enzymes, where one carbohydrate-fueled pathway was dominant with butyryl coenzyme A (CoA):acetate CoA transferase as the main terminal enzyme. Subjects displayed a high richness of butyrate producers, and 17 taxa, primarily members of the Lachnospiraceae and Ruminococcaceae along with some Bacteroidetes, were detected in >70% of individuals, encompassing ~85% of the total butyrate-producing potential. Most of these key taxa were also found to express genes for butyrate formation, indicating that butyrate producers occupy various niches in the gut ecosystem, concurrently synthesizing that compound. Furthermore, results from longitudinal analyses propose that diversity supports functional stability during ordinary life disturbances and during interventions such as antibiotic treatment. A reduction of the butyrate-producing potential along with community alterations was detected in various diseases, where patients suffering from cardiometabolic disorders were particularly affected. IMPORTANCE Studies focusing on taxonomic compositions of the gut microbiota are plentiful, whereas its functional capabilities are still poorly understood. Specific key functions deserve detailed investigations, as they regulate microbiota-host interactions and promote host health and disease. The production of butyrate is among the top targets since depletion of this microbe-derived metabolite is linked to several emerging noncommunicable diseases and was shown to facilitate establishment of enteric pathogens by disrupting colonization resistance. In this study, we established a workflow to investigate in detail the composition of the polyphyletic butyrate-producing community from omics data extracting its biochemical and taxonomic diversity. By combining information from various publicly available data sets, we identified universal ecological key features of this functional group and shed light on its role in health and disease. Our results will assist the development of precision medicine to combat functional dysbiosis. PMID:29238752
YMDB 2.0: a significantly expanded version of the yeast metabolome database.
Ramirez-Gaona, Miguel; Marcu, Ana; Pon, Allison; Guo, An Chi; Sajed, Tanvir; Wishart, Noah A; Karu, Naama; Djoumbou Feunang, Yannick; Arndt, David; Wishart, David S
2017-01-04
YMDB or the Yeast Metabolome Database (http://www.ymdb.ca/) is a comprehensive database containing extensive information on the genome and metabolome of Saccharomyces cerevisiae Initially released in 2012, the YMDB has gone through a significant expansion and a number of improvements over the past 4 years. This manuscript describes the most recent version of YMDB (YMDB 2.0). More specifically, it provides an updated description of the database that was previously described in the 2012 NAR Database Issue and it details many of the additions and improvements made to the YMDB over that time. Some of the most important changes include a 7-fold increase in the number of compounds in the database (from 2007 to 16 042), a 430-fold increase in the number of metabolic and signaling pathway diagrams (from 66 to 28 734), a 16-fold increase in the number of compounds linked to pathways (from 742 to 12 733), a 17-fold increase in the numbers of compounds with nuclear magnetic resonance or MS spectra (from 783 to 13 173) and an increase in both the number of data fields and the number of links to external databases. In addition to these database expansions, a number of improvements to YMDB's web interface and its data visualization tools have been made. These additions and improvements should greatly improve the ease, the speed and the quantity of data that can be extracted, searched or viewed within YMDB. Overall, we believe these improvements should not only improve the understanding of the metabolism of S. cerevisiae, but also allow more in-depth exploration of its extensive metabolic networks, signaling pathways and biochemistry. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Substrate biochemistry control on the pathways for the formation of soil organic matter
NASA Astrophysics Data System (ADS)
Almeida, L. F.; Hurtarte, L. C.; Souza, I. F.; Barros, E. M.; Vergutz, L.; Silva, I. R.
2017-12-01
Linking plant litter biochemistry, its decomposition and soil organic matter (SOM) formation is not straightforward. To address this issue, we evaluated the decomposition of four biochemical fractions operationally defined as i) hot-water extractable (HWE), ii) total solvent (acetone) extractable (TSE), iii) acid-base (HNO3-KOH) unhydrolyzable cellulosic fraction (CF), and iv) acid(H2SO4) unhydrolyzable (AUR) and the transfer of C from these fractions to SOM. Each biochemical fraction was Soxhlet-extracted from isotopically labeled (13C) leaves, twigs, bark and roots of eucalypt plants (120 days old). The molecular composition of each fraction was inferred from thermochemolysis with tertamethylammonium (TMAH), followed by gas chromatography coupled o mass spectrometry (GC-MS). For the incubation, we collected soil samples from the topsoil (0-20 cm) of a sandy-clay loam, kaolinitic Typic Hapludox (Haplic Ferralsol). Four plant organs and four biochemical fractions were arranged into a (4 4) + 1 factorial scheme, including one control treatment (soil only). The samples were incubated at 80% of their water-holding capacity and kept under controlled temperature (25 ºC). The decomposition of the biochemical fractions was monitored by determining the CO2 concentration into the headspace of the vials. Finished the incubation, soil samples were submitted to density followed by particle-size fractionation. HWE and CF was decomposed at faster rates than TSE and AUR throughout the incubation. The soil fraction <53 µm retained a significantly higher proportion of the initial input of HWE (32%) and AUR (31%) than TSE (19%) or CF (15%). Light fraction organic matter (LFOM) with density <1.8 g cm-3, retained a significant proportion of AUR (37%) and TSE (32%) while CF was mostly lost as CO2 (79%). Selective preservation of organic materials (e.g., long-chain lipids) within AUR and TSE fractions appears to be a significant pathway for SOM formation. A microbial-driven pathway cannot be ruled out for any biochemical fraction, but seems more relevant for HWE and CF. In short-term, substrate biochemistry exerts a strong influence on the conversion of eucalypt litter fractions into either CO2 or SOM. Such results warrant the relevance of field-based study to link plant litter biochemistry and SOM formation in long-term.
Neill, Meaghan Anne; Aschner, Judy; Barr, Frederick; Summar, Marshall L.
2009-01-01
The urea cycle and nitric oxide cycle play significant roles in complex biochemical and physiologic reactions. These cycles have distinct biochemical goals including the clearance of waste nitrogen; the production of the intermediates ornithine, citrulline, and arginine for the urea cycle; and the production of nitric oxide for the nitric oxide pathway. Despite their disparate functions, the two pathways share two enzymes, argininosuccinic acid synthase and argininosuccinic acid lyase, and a transporter, citrin. Studying the gene expression of these enzymes is paramount in understanding these complex biochemical pathways. Here, we examine the expression of genes involved in the urea cycle and the nitric oxide cycle in a panel of eleven different tissue samples obtained from individual adults without known inborn errors of metabolism. In this study, the pattern of co-expressed enzymes provides a global view of the metabolic activity of the urea and nitric oxide cycles in human tissues. Our results show that these transcripts are differentially expressed in different tissues. The pattern of co-expressed enzymes provides a global view of the metabolic activity of the urea and nitric oxide cycles in human tissues. Using the co-expression profiles, we discovered that the combination of expression of enzyme transcripts as detected in our study, might serve to fulfill specific physiologic function(s) in tissue including urea production/nitrogen removal, arginine/citrulline production, nitric oxide production, and ornithine production. Our study reveals the importance of studying not only the expression profile of an enzyme of interest, but also studying the expression profiles of the other enzymes involved in a particular pathway so as to better understand the context of expression. The tissue patterns we observed highlight the variety of important functions they conduct and provide insight into many of the clinical observations from their disruption. PMID:19345634
Nayak, Losiana; De, Rajat K
2007-12-01
Signaling pathways are large complex biochemical networks. It is difficult to analyze the underlying mechanism of such networks as a whole. In the present article, we have proposed an algorithm for modularization of signal transduction pathways. Unlike studying a signaling pathway as a whole, this enables one to study the individual modules (less complex smaller units) easily and hence to study the entire pathway better. A comparative study of modules belonging to different species (for the same signaling pathway) has been made, which gives an overall idea about development of the signaling pathways over the taken set of species of calcium and MAPK signaling pathways. The superior performance, in terms of biological significance, of the proposed algorithm over an existing community finding algorithm of Newman [Newman MEJ. Modularity and community structure in networks. Proc Natl Acad Sci USA 2006;103(23):8577-82] has been demonstrated using the aforesaid pathways of H. sapiens.
Modeling biochemical pathways in the gene ontology
Hill, David P.; D’Eustachio, Peter; Berardini, Tanya Z.; ...
2016-09-01
The concept of a biological pathway, an ordered sequence of molecular transformations, is used to collect and represent molecular knowledge for a broad span of organismal biology. Representations of biomedical pathways typically are rich but idiosyncratic presentations of organized knowledge about individual pathways. Meanwhile, biomedical ontologies and associated annotation files are powerful tools that organize molecular information in a logically rigorous form to support computational analysis. The Gene Ontology (GO), representing Molecular Functions, Biological Processes and Cellular Components, incorporates many aspects of biological pathways within its ontological representations. Here we present a methodology for extending and refining the classes inmore » the GO for more comprehensive, consistent and integrated representation of pathways, leveraging knowledge embedded in current pathway representations such as those in the Reactome Knowledgebase and MetaCyc. With carbohydrate metabolic pathways as a use case, we discuss how our representation supports the integration of variant pathway classes into a unified ontological structure that can be used for data comparison and analysis.« less
Sun, Xiaodian; Jin, Li; Xiong, Momiao
2008-01-01
It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks. PMID:19018286
Ruel, L; Stambolic, V; Ali, A; Manoukian, A S; Woodgett, J R
1999-07-30
The protein-serine kinase Shaggy(Zeste-white3) (Sgg(Zw3)) is the Drosophila homolog of mammalian glycogen synthase kinase-3 and has been genetically implicated in signal transduction pathways necessary for the establishment of patterning. Sgg(Zw3) is a putative component of the Wingless (Wg) pathway, and epistasis analyses suggest that Sgg(Zw3) function is repressed by Wg signaling. Here, we have investigated the biochemical consequences of Wg signaling with respect to the Sgg(Zw3) protein kinase in two types of Drosophila cell lines and in embryos. Our results demonstrate that Sgg(Zw3) activity is inhibited following exposure of cells to Wg protein and by expression of downstream components of Wg signaling, Drosophila frizzled 2 and dishevelled. Wg-dependent inactivation of Sgg(Zw3) is accompanied by serine phosphorylation. We also show that the level of Sgg(Zw3) activity regulates the stability of Armadillo protein and modulates the level of phosphorylation of D-Axin and Armadillo. Together, these results provide direct biochemical evidence in support of the genetic model of Wg signaling and provide a model for dissecting the molecular interactions between the signaling proteins.
2010-01-01
Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License. PMID:20587024
Wang, Ju; Yuan, Wenji; Li, Ming D
2011-12-01
Drug addiction is a chronic neuronal disease. In recent years, proteomics technology has been widely used to assess the protein expression in the brain tissues of both animals and humans exposed to addictive drugs. Through this approach, a large number of proteins potentially involved in the etiology of drug addictions have been identified, which provide a valuable resource to study protein function, biochemical pathways, and networks related to the molecular mechanisms underlying drug dependence. In this article, we summarize the recent application of proteomics to profiling protein expression patterns in animal or human brain tissues after the administration of alcohol, amphetamine/methamphetamine, cocaine, marijuana, morphine/heroin/butorphanol, or nicotine. From available reports, we compiled a list of 497 proteins associated with exposure to one or more addictive drugs, with 160 being related to exposure to at least two abused drugs. A number of biochemical pathways and biological processes appear to be enriched among these proteins, including synaptic transmission and signaling pathways related to neuronal functions. The data included in this work provide a summary and extension of the proteomics studies on drug addiction. Furthermore, the proteins and biological processes highlighted here may provide valuable insight into the cellular activities and biological processes in neurons in the development of drug addiction.
Wang, Yanjun; Liu, Xiangyang; Zhang, Chen; Wang, Zhengjun
2018-06-01
High salt induced renal disease is a condition resulting from the interactions of genetic and dietary factors causing multiple complications. To understand the metabolic alterations associated with renal disease, we comprehensively analyzed the metabonomic changes induced by high salt intake in Dahl salt-sensitive (SS) rats using GC-MS technology and biochemical analyses. Physiological features, serum chemistry, and histopathological data were obtained as complementary information. Our results showed that high salt (HS) intake for 16 weeks caused significant metabolic alterations in both the renal medulla and cortex involving a variety pathways involved in the metabolism of organic acids, amino acids, fatty acids, and purines. In addition, HS enhanced glycolysis (hexokinase, phosphofructokinase and pyruvate kinase) and amino acid metabolism and suppressed the TCA (citrate synthase and aconitase) cycle. Finally, HS intake caused up-regulation of the pentose phosphate pathway (glucose 6-phosphate dehydrogenase and 6-phosphogluconate dehydrogenase), the ratio of NADPH/NADP + , NADPH oxidase activity and ROS production, suggesting that increased oxidative stress was associated with an altered PPP pathway. The metabolic pathways identified may serve as potential targets for the treatment of renal damage. Our findings provide comprehensive biochemical details about the metabolic responses to a high salt diet, which may contribute to the understanding of renal disease and salt-induced hypertension in SS rats. Copyright © 2018. Published by Elsevier Inc.
Glycoprotein Ib activation by thrombin stimulates the energy metabolism in human platelets
Corona de la Peña, Norma; Gutiérrez-Aguilar, Manuel; Hernández-Reséndiz, Ileana; Marín-Hernández, Álvaro
2017-01-01
Thrombin-induced platelet activation requires substantial amounts of ATP. However, the specific contribution of each ATP-generating pathway i.e., oxidative phosphorylation (OxPhos) versus glycolysis and the biochemical mechanisms involved in the thrombin-induced activation of energy metabolism remain unclear. Here we report an integral analysis on the role of both energy pathways in human platelets activated by several agonists, and the signal transducing mechanisms associated with such activation. We found that thrombin, Trap-6, arachidonic acid, collagen, A23187, epinephrine and ADP significantly increased glycolytic flux (3–38 times vs. non-activated platelets) whereas ristocetin was ineffective. OxPhos (33 times) and mitochondrial transmembrane potential (88%) were increased only by thrombin. OxPhos was the main source of ATP in thrombin-activated platelets, whereas in platelets activated by any of the other agonists, glycolysis was the principal ATP supplier. In order to establish the biochemical mechanisms involved in the thrombin-induced OxPhos activation in platelets, several signaling pathways associated with mitochondrial activation were analyzed. Wortmannin and LY294002 (PI3K/Akt pathway inhibitors), ristocetin and heparin (GPIb inhibitors) as well as resveratrol, ATP (calcium-release inhibitors) and PP1 (Tyr-phosphorylation inhibitor) prevented the thrombin-induced platelet activation. These results suggest that thrombin activates OxPhos and glycolysis through GPIb-dependent signaling involving PI3K and Akt activation, calcium mobilization and protein phosphorylation. PMID:28817667
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bonner, C.A.; Fischer, R.S.; Ahmad, S.
The pathway construction for biosynthesis of aromatic amino acids in Escherichia coli is atypical of the phylogenetic subdivision of gram-negative bacteria to which it belongs. Related organisms possess second pathways to phenylalanine and tyrosine which depend upon the expression of a monofunctional chorismate mutase (CM-F) and cyclohexadienyl dehydratase (CDT). Some enteric bacteria, unlike E. coli, possess either CM-F or CDT. These essentially cryptic remnants of an ancestral pathway can be a latent source of biochemical potential under certain conditions. As one example of advantageous biochemical potential, the presence of CM-F in Salmonella typhimurium increases the capacity for prephenate accumulation inmore » a tyrA auxotroph. We report the finding that a significant fraction of the latter prephenate is transaminated to L-arogenate. The tyrA19 mutant is now the organism of choice for isolation of L-arogenate, uncomplicated by the presence of other cyclohexadienyl products coaccumulated by a Neurospora crassa mutant that had previously served as the prime biological source of L-arogenate. Prephenate aminotransferase activity was not conferred by a discrete enzyme, but rather was found to be synonymous with the combined activities of aspartate aminotransferase (aspC), aromatic aminotransferase (tyrB), and branched-chain aminotransferase (ilvE).« less
Yang, Daqian; Jiang, Huijie; Lu, Jingjing; Lv, Yueying; Baiyun, Ruiqi; Li, Siyu; Liu, Biying; Lv, Zhanjun; Zhang, Zhigang
2018-06-01
Lead, a pervasive environmental hazard worldwide, causes a wide range of physiological and biochemical destruction, including metabolic dysfunction. Grape seed proanthocyanidin extract (GSPE) is a natural production with potential metabolic regulation in liver. This study was performed to investigate the protective role of GSPE against lead-induced metabolic dysfunction in liver and elucidate the potential molecular mechanism of this event. Wistar rats received GSPE (200 mg/kg) daily with or without lead acetate (PbA, 0.5 g/L) exposure for 56 d. According to biochemical and histopathologic analysis, GSPE attenuated lead-induced metabolic dysfunction, oxidative stress, and liver dysfunction. Liver gene expression profiling was assessed by RNA sequencing and validated by qRT-PCR. Expression of some genes in peroxisome proliferator-activated receptor alpha (PPARα) signaling pathway was significantly suppressed in PbA group and revived in PbA + GSPE group, which was manifested by Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis and validated by western blot analysis. This study supports that dietary GSPE ameliorates lead-induced fatty acids metabolic disturbance in rat liver associated with PPARα signaling pathway, and suggests that dietary GSPE may be a protector against lead-induced metabolic dysfunction and liver injury, providing a novel therapy to protect liver against lead exposure. Copyright © 2018 Elsevier Ltd. All rights reserved.
Pathway of Glycine Betaine Biosynthesis in Aspergillus fumigatus
Lambou, Karine; Pennati, Andrea; Valsecchi, Isabel; Tada, Rui; Sherman, Stephen; Sato, Hajime; Beau, Remi
2013-01-01
The choline oxidase (CHOA) and betaine aldehyde dehydrogenase (BADH) genes identified in Aspergillus fumigatus are present as a cluster specific for fungal genomes. Biochemical and molecular analyses of this cluster showed that it has very specific biochemical and functional features that make it unique and different from its plant and bacterial homologs. A. fumigatus ChoAp catalyzed the oxidation of choline to glycine betaine with betaine aldehyde as an intermediate and reduced molecular oxygen to hydrogen peroxide using FAD as a cofactor. A. fumigatus Badhp oxidized betaine aldehyde to glycine betaine with reduction of NAD+ to NADH. Analysis of the AfchoAΔ::HPH and AfbadAΔ::HPH single mutants and the AfchoAΔAfbadAΔ::HPH double mutant showed that AfChoAp is essential for the use of choline as the sole nitrogen, carbon, or carbon and nitrogen source during the germination process. AfChoAp and AfBadAp were localized in the cytosol of germinating conidia and mycelia but were absent from resting conidia. Characterization of the mutant phenotypes showed that glycine betaine in A. fumigatus functions exclusively as a metabolic intermediate in the catabolism of choline and not as a stress protectant. This study in A. fumigatus is the first molecular, cellular, and biochemical characterization of the glycine betaine biosynthetic pathway in the fungal kingdom. PMID:23563483
Pathway of glycine betaine biosynthesis in Aspergillus fumigatus.
Lambou, Karine; Pennati, Andrea; Valsecchi, Isabel; Tada, Rui; Sherman, Stephen; Sato, Hajime; Beau, Remi; Gadda, Giovanni; Latgé, Jean-Paul
2013-06-01
The choline oxidase (CHOA) and betaine aldehyde dehydrogenase (BADH) genes identified in Aspergillus fumigatus are present as a cluster specific for fungal genomes. Biochemical and molecular analyses of this cluster showed that it has very specific biochemical and functional features that make it unique and different from its plant and bacterial homologs. A. fumigatus ChoAp catalyzed the oxidation of choline to glycine betaine with betaine aldehyde as an intermediate and reduced molecular oxygen to hydrogen peroxide using FAD as a cofactor. A. fumigatus Badhp oxidized betaine aldehyde to glycine betaine with reduction of NAD(+) to NADH. Analysis of the AfchoAΔ::HPH and AfbadAΔ::HPH single mutants and the AfchoAΔAfbadAΔ::HPH double mutant showed that AfChoAp is essential for the use of choline as the sole nitrogen, carbon, or carbon and nitrogen source during the germination process. AfChoAp and AfBadAp were localized in the cytosol of germinating conidia and mycelia but were absent from resting conidia. Characterization of the mutant phenotypes showed that glycine betaine in A. fumigatus functions exclusively as a metabolic intermediate in the catabolism of choline and not as a stress protectant. This study in A. fumigatus is the first molecular, cellular, and biochemical characterization of the glycine betaine biosynthetic pathway in the fungal kingdom.
Characterizing autism spectrum disorders by key biochemical pathways.
Subramanian, Megha; Timmerman, Christina K; Schwartz, Joshua L; Pham, Daniel L; Meffert, Mollie K
2015-01-01
The genetic and phenotypic heterogeneity of autism spectrum disorders (ASD) presents a substantial challenge for diagnosis, classification, research, and treatment. Investigations into the underlying molecular etiology of ASD have often yielded mixed and at times opposing findings. Defining the molecular and biochemical underpinnings of heterogeneity in ASD is crucial to our understanding of the pathophysiological development of the disorder, and has the potential to assist in diagnosis and the rational design of clinical trials. In this review, we propose that genetically diverse forms of ASD may be usefully parsed into entities resulting from converse patterns of growth regulation at the molecular level, which lead to the correlates of general synaptic and neural overgrowth or undergrowth. Abnormal brain growth during development is a characteristic feature that has been observed both in children with autism and in mouse models of autism. We review evidence from syndromic and non-syndromic ASD to suggest that entities currently classified as autism may fundamentally differ by underlying pro- or anti-growth abnormalities in key biochemical pathways, giving rise to either excessive or reduced synaptic connectivity in affected brain regions. We posit that this classification strategy has the potential not only to aid research efforts, but also to ultimately facilitate early diagnosis and direct appropriate therapeutic interventions.
Characterizing autism spectrum disorders by key biochemical pathways
Subramanian, Megha; Timmerman, Christina K.; Schwartz, Joshua L.; Pham, Daniel L.; Meffert, Mollie K.
2015-01-01
The genetic and phenotypic heterogeneity of autism spectrum disorders (ASD) presents a substantial challenge for diagnosis, classification, research, and treatment. Investigations into the underlying molecular etiology of ASD have often yielded mixed and at times opposing findings. Defining the molecular and biochemical underpinnings of heterogeneity in ASD is crucial to our understanding of the pathophysiological development of the disorder, and has the potential to assist in diagnosis and the rational design of clinical trials. In this review, we propose that genetically diverse forms of ASD may be usefully parsed into entities resulting from converse patterns of growth regulation at the molecular level, which lead to the correlates of general synaptic and neural overgrowth or undergrowth. Abnormal brain growth during development is a characteristic feature that has been observed both in children with autism and in mouse models of autism. We review evidence from syndromic and non-syndromic ASD to suggest that entities currently classified as autism may fundamentally differ by underlying pro- or anti-growth abnormalities in key biochemical pathways, giving rise to either excessive or reduced synaptic connectivity in affected brain regions. We posit that this classification strategy has the potential not only to aid research efforts, but also to ultimately facilitate early diagnosis and direct appropriate therapeutic interventions. PMID:26483618
Nolz, Jeffrey C.; Gomez, Timothy S.; Zhu, Peimin; Li, Shuixing; Medeiros, Ricardo B.; Shimizu, Yoji; Burkhardt, Janis K.; Freedman, Bruce D.; Billadeau, Daniel D.
2007-01-01
Summary Background The engagement of the T cell receptor results in actin cytoskeletal reorganization at the immune synapse (IS) and the triggering of biochemical signaling cascades leading to gene regulation and, ultimately, cellular activation. Recent studies have identified the WAVE family of proteins as critical mediators of Rac1-induced actin reorganization in other cell types. However, whether these proteins participate in actin reorganization at the IS or signaling pathways in T cells has not been investigated. Results By using a combination of biochemical, genetic, and cell biology approaches, we provide evidence that WAVE2 is recruited to the IS, is biochemically modified, and is required for actin reorganization and β-integrin-mediated adhesion after TCR crosslinking. Moreover, we show that WAVE2 regulates calcium entry at a point distal to PLCγ1 activation and IP3-mediated store release. Conclusions These data reveal a role for WAVE2 in regulating multiple pathways leading to T cell activation. In particular, this work shows that WAVE2 is a key component of the actin regulatory machinery in T cells and that it also participates in linking intracellular calcium store depletion to calcium release-activated calcium (CRAC) channel activation. PMID:16401421
Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays
High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...
Emanuele, Sonia; Lauricella, Marianna; Calvaruso, Giuseppe; D'Anneo, Antonella; Giuliano, Michela
2017-09-08
Litchi is a tasty fruit that is commercially grown for food consumption and nutritional benefits in various parts of the world. Due to its biological activities, the fruit is becoming increasingly known and deserves attention not only for its edible part, the pulp, but also for its peel and seed that contain beneficial substances with antioxidant, cancer preventive, antimicrobial, and anti-inflammatory functions. Although literature demonstrates the biological activity of Litchi components in reducing tumor cell viability in in vitro or in vivo models, data about the biochemical mechanisms responsible for these effects are quite fragmentary. This review specifically describes, in a comprehensive analysis, the antitumor properties of the different parts of Litchi and highlights the main biochemical mechanisms involved.
Heuett, William J; Beard, Daniel A; Qian, Hong
2008-05-15
Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA).
Hypothalamic digoxin, hemispheric chemical dominance and sarcoidosis.
Ravi Kumar, A; Kurup, Parameswara Achutha
2004-06-01
The isoprenoid pathway produces three key metabolites: endogenous digoxin (membrane sodium-potassium ATPase inhibitor, immunomodulator and regulator of neurotransmitter/amino acid transport), dolichol (regulates N-glycosylation of proteins) and ubiquinone (free radical scavenger). The role of the isoprenoid pathway in the pathogenesis of sarcoidosis in relation to hemispheric dominance was studied. The isoprenoid pathway-related cascade was assessed in patients with systemic sarcoidosis with pulmonary involvement. The pathway was also assessed in patients with right hemispheric, left hemispheric and bihemispheric dominance for comparison to find out the role of hemispheric dominance in the pathogenesis of sarcoidosis. In patients with sarcoidosis there was elevated digoxin synthesis, increased dolichol and glycoconjugate levels and low ubiquinone and elevated free radical levels. There was also an increase in tryptophan catabolites and a reduction in tyrosine catabolites. There was an increase in the cholesterol:phospholipid ratio and a reduction in the glycoconjugate level of red blood cell (RBC) membrane in this group of patients. The same biochemical patterns were obtained in individuals with right hemispheric dominance. In individuals with left hemispheric dominance the patterns were reversed. Endogenous digoxin, by activating the calcineurin signal transduction pathway of T cells, can contribute to immune activation in sarcoidosis. An altered glycoconjugate metabolism can lead to the generation of endogenous self-glycoprotein antigens in the lung as well as other tissues. Increased free radical generation can also lead to immune activation. The role of a dysfunctional isoprenoid pathway and endogenous digoxin in the pathogenesis of sarcoidosis in relation to right hemispheric chemical dominance is discussed. All the patients with sarcoidosis were right-handed/left hemispheric dominant according to the dichotic listening test, but their biochemical patterns were suggestive of right hemispheric chemical dominance. Hemispheric chemical dominance has no correlation with handedness or the dichotic listening test.
Identifying positive selection candidate loci for high-altitude adaptation in Andean populations
2009-01-01
High-altitude environments (>2,500 m) provide scientists with a natural laboratory to study the physiological and genetic effects of low ambient oxygen tension on human populations. One approach to understanding how life at high altitude has affected human metabolism is to survey genome-wide datasets for signatures of natural selection. In this work, we report on a study to identify selection-nominated candidate genes involved in adaptation to hypoxia in one highland group, Andeans from the South American Altiplano. We analysed dense microarray genotype data using four test statistics that detect departures from neutrality. Using a candidate gene, single nucleotide polymorphism-based approach, we identified genes exhibiting preliminary evidence of recent genetic adaptation in this population. These included genes that are part of the hypoxia-inducible transcription factor (HIF) pathway, a biochemical pathway involved in oxygen homeostasis, as well as three other genomic regions previously not known to be associated with high-altitude phenotypes. In addition to identifying selection-nominated candidate genes, we also tested whether the HIF pathway shows evidence of natural selection. Our results indicate that the genes of this biochemical pathway as a group show no evidence of having evolved in response to hypoxia in Andeans. Results from particular HIF-targeted genes, however, suggest that genes in this pathway could play a role in Andean adaptation to high altitude, even if the pathway as a whole does not show higher relative rates of evolution. These data suggest a genetic role in high-altitude adaptation and provide a basis for genotype/phenotype association studies that are necessary to confirm the role of putative natural selection candidate genes and gene regions in adaptation to altitude. PMID:20038496
A Graphical User Interface for a Method to Infer Kinetics and Network Architecture (MIKANA)
Mourão, Márcio A.; Srividhya, Jeyaraman; McSharry, Patrick E.; Crampin, Edmund J.; Schnell, Santiago
2011-01-01
One of the main challenges in the biomedical sciences is the determination of reaction mechanisms that constitute a biochemical pathway. During the last decades, advances have been made in building complex diagrams showing the static interactions of proteins. The challenge for systems biologists is to build realistic models of the dynamical behavior of reactants, intermediates and products. For this purpose, several methods have been recently proposed to deduce the reaction mechanisms or to estimate the kinetic parameters of the elementary reactions that constitute the pathway. One such method is MIKANA: Method to Infer Kinetics And Network Architecture. MIKANA is a computational method to infer both reaction mechanisms and estimate the kinetic parameters of biochemical pathways from time course data. To make it available to the scientific community, we developed a Graphical User Interface (GUI) for MIKANA. Among other features, the GUI validates and processes an input time course data, displays the inferred reactions, generates the differential equations for the chemical species in the pathway and plots the prediction curves on top of the input time course data. We also added a new feature to MIKANA that allows the user to exclude a priori known reactions from the inferred mechanism. This addition improves the performance of the method. In this article, we illustrate the GUI for MIKANA with three examples: an irreversible Michaelis–Menten reaction mechanism; the interaction map of chemical species of the muscle glycolytic pathway; and the glycolytic pathway of Lactococcus lactis. We also describe the code and methods in sufficient detail to allow researchers to further develop the code or reproduce the experiments described. The code for MIKANA is open source, free for academic and non-academic use and is available for download (Information S1). PMID:22096591
A graphical user interface for a method to infer kinetics and network architecture (MIKANA).
Mourão, Márcio A; Srividhya, Jeyaraman; McSharry, Patrick E; Crampin, Edmund J; Schnell, Santiago
2011-01-01
One of the main challenges in the biomedical sciences is the determination of reaction mechanisms that constitute a biochemical pathway. During the last decades, advances have been made in building complex diagrams showing the static interactions of proteins. The challenge for systems biologists is to build realistic models of the dynamical behavior of reactants, intermediates and products. For this purpose, several methods have been recently proposed to deduce the reaction mechanisms or to estimate the kinetic parameters of the elementary reactions that constitute the pathway. One such method is MIKANA: Method to Infer Kinetics And Network Architecture. MIKANA is a computational method to infer both reaction mechanisms and estimate the kinetic parameters of biochemical pathways from time course data. To make it available to the scientific community, we developed a Graphical User Interface (GUI) for MIKANA. Among other features, the GUI validates and processes an input time course data, displays the inferred reactions, generates the differential equations for the chemical species in the pathway and plots the prediction curves on top of the input time course data. We also added a new feature to MIKANA that allows the user to exclude a priori known reactions from the inferred mechanism. This addition improves the performance of the method. In this article, we illustrate the GUI for MIKANA with three examples: an irreversible Michaelis-Menten reaction mechanism; the interaction map of chemical species of the muscle glycolytic pathway; and the glycolytic pathway of Lactococcus lactis. We also describe the code and methods in sufficient detail to allow researchers to further develop the code or reproduce the experiments described. The code for MIKANA is open source, free for academic and non-academic use and is available for download (Information S1).
PathNER: a tool for systematic identification of biological pathway mentions in the literature
2013-01-01
Background Biological pathways are central to many biomedical studies and are frequently discussed in the literature. Several curated databases have been established to collate the knowledge of molecular processes constituting pathways. Yet, there has been little focus on enabling systematic detection of pathway mentions in the literature. Results We developed a tool, named PathNER (Pathway Named Entity Recognition), for the systematic identification of pathway mentions in the literature. PathNER is based on soft dictionary matching and rules, with the dictionary generated from public pathway databases. The rules utilise general pathway-specific keywords, syntactic information and gene/protein mentions. Detection results from both components are merged. On a gold-standard corpus, PathNER achieved an F1-score of 84%. To illustrate its potential, we applied PathNER on a collection of articles related to Alzheimer's disease to identify associated pathways, highlighting cases that can complement an existing manually curated knowledgebase. Conclusions In contrast to existing text-mining efforts that target the automatic reconstruction of pathway details from molecular interactions mentioned in the literature, PathNER focuses on identifying specific named pathway mentions. These mentions can be used to support large-scale curation and pathway-related systems biology applications, as demonstrated in the example of Alzheimer's disease. PathNER is implemented in Java and made freely available online at http://sourceforge.net/projects/pathner/. PMID:24555844
NASA Astrophysics Data System (ADS)
Dippold, Michaela; Kuzyakov, Yakov
2015-04-01
Understanding the soil organic matter (SOM) dynamics is one of the most important challenges in soil science. Transformation of low molecular weight organic substances (LMWOS) is a key step in biogeochemical cycles because 1) all high molecular substances pass this stage during their decomposition and 2) only LMWOS will be taken up by microorganisms. Previous studies on LMWOS were focused on determining net fluxes through the LMWOS pool, but they rarely identified transformations. As LMWOS are the preferred C and energy source for microorganisms, the transformations of LMWOS are dominated by biochemical pathways of the soil microorganisms. Thus, understanding fluxes and transformations in soils requires a detailed knowledge on the biochemical pathways and its controlling factors. Tracing C fate in soil by isotopes became on of the most applied and promising biogeochemistry tools. Up to now, studies on LMWOS were nearly exclusively based on uniformly labeled organic substances i.e. all C atoms in the molecules were labeled with 13C or 14C. However, this classical approach did not allow the differentiation between use of intact initial substances in any process, or whether they were transformed to metabolites. The novel tool of position-specific labeling enables to trace molecule atoms separately and thus to determine the cleavage of molecules - a prerequisite for metabolic tracing. Position-specific labeling of LMWOS and quantification of 13CO2 and 13C in bulk soil enabled following the basic metabolic pathways of soil microorganisms. However, only the combination of position-specific 13C labeling with compound-specific isotope analysis of microbial biomarkers and metabolites allowed 1) tracing specific anabolic pathways in diverse microbial communities in soils and 2) identification of specific pathways of individual functional microbial groups. So, these are the prerequisites for soil fluxomics. Our studies combining position-specific labeled glucose with amino sugar 13C analysis showed that oxidizing catabolic pathways and anabolic pathways, i.e. building-up new cellular compounds, occurred in soils simultaneously. This involved an intensive C recycling within the microorganisms that was observed not only for cytosolic compounds but also for cell wall polymers. Fungal metabolism and fluxes were slower than bacterial intracellular C recycling and turnover. Furthermore, position-specific labeling of glutamate and subsequent 13C analysis of microbial phospholipid fatty acids (PLFA) revealed starvation pathways, which were only active in specific microbial groups in soils. These studies revealed that position-specific labeling enables the reconstruction of metabolic pathways of LMWOS within diverse microbial communities in complex media such as soil. Processes occurring simultaneously in soil i.e. 1) within individual, reversible metabolic pathways and 2) in various microbial groups could be traced by position-specific labeling in soils in situ. Tracing these pathways and understanding their regulating factors are crucial for soil C fluxomics, the extremely complex network of transformations towards mineralization versus the formation of microbial biomass compounds. Quantitative models to assess microbial group specific metabolic networks can be generated and parameterized by this approach. The submolecular knowledge of transformation steps and biochemical pathways in soils and their regulating factors is essential for understanding C cycling and long-term C storage in soils.
García-Jiménez, Beatriz; Pons, Tirso; Sanchis, Araceli; Valencia, Alfonso
2014-01-01
Biological pathways are important elements of systems biology and in the past decade, an increasing number of pathway databases have been set up to document the growing understanding of complex cellular processes. Although more genome-sequence data are becoming available, a large fraction of it remains functionally uncharacterized. Thus, it is important to be able to predict the mapping of poorly annotated proteins to original pathway models. We have developed a Relational Learning-based Extension (RLE) system to investigate pathway membership through a function prediction approach that mainly relies on combinations of simple properties attributed to each protein. RLE searches for proteins with molecular similarities to specific pathway components. Using RLE, we associated 383 uncharacterized proteins to 28 pre-defined human Reactome pathways, demonstrating relative confidence after proper evaluation. Indeed, in specific cases manual inspection of the database annotations and the related literature supported the proposed classifications. Examples of possible additional components of the Electron transport system, Telomere maintenance and Integrin cell surface interactions pathways are discussed in detail. All the human predicted proteins in the 2009 and 2012 releases 30 and 40 of Reactome are available at http://rle.bioinfo.cnio.es.
From Databases to Modelling of Functional Pathways
2004-01-01
This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell. PMID:18629070
From databases to modelling of functional pathways.
Nasi, Sergio
2004-01-01
This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.
The Adverse Outcome Pathway (AOP) framework describes the progression of a toxicity pathway from molecular perturbation to population-level outcome in a series of measurable, mechanistic responses. The controlled, computer-readable vocabulary that defines an AOP has the ability t...
May, Brian H; Deng, Shiqiang; Zhang, Anthony L; Lu, Chuanjian; Xue, Charlie C L
2015-09-01
Reviews and meta-analyses of clinical trials identified plants used as traditional medicines (TMs) that show promise for psoriasis. These include Rehmannia glutinosa, Camptotheca acuminata, Indigo naturalis and Salvia miltiorrhiza. Compounds contained in these TMs have shown activities of relevance to psoriasis in experimental models. To further investigate the likely mechanisms of action of the multiple compounds in these TMs, we undertook a computer-based in silico investigation of the proteins known to be regulated by these compounds and their associated biological pathways. The proteins reportedly regulated by compounds in these four TMs were identified using the HIT (Herbal Ingredients' Targets) database. The resultant data were entered into the PANTHER (Protein ANnotation THrough Evolutionary Relationship) database to identify the pathways in which the proteins could be involved. The study identified 237 compounds in the TMs and these retrieved 287 proteins from HIT. These proteins identified 59 pathways in PANTHER with most proteins being located in the Apoptosis, Angiogenesis, Inflammation mediated by chemokine and cytokine, Gonadotropin releasing hormone receptor, and/or Interleukin signaling pathways. All four TMs contained compounds that had regulating effects on Apoptosis regulator BAX, Apoptosis regulator Bcl-2, Caspase-3, Tumor necrosis factor (TNF) or Prostaglandin G/H synthase 2 (COX2). The main proteins and pathways are primarily related to inflammation, proliferation and angiogenesis which are all processes involved in psoriasis. Experimental studies have reported that certain compounds from these TMs can regulate the expression of proteins involved in each of these pathways.
Metabolomics analysis: Finding out metabolic building blocks
2017-01-01
In this paper we propose a new methodology for the analysis of metabolic networks. We use the notion of strongly connected components of a graph, called in this context metabolic building blocks. Every strongly connected component is contracted to a single node in such a way that the resulting graph is a directed acyclic graph, called a metabolic DAG, with a considerably reduced number of nodes. The property of being a directed acyclic graph brings out a background graph topology that reveals the connectivity of the metabolic network, as well as bridges, isolated nodes and cut nodes. Altogether, it becomes a key information for the discovery of functional metabolic relations. Our methodology has been applied to the glycolysis and the purine metabolic pathways for all organisms in the KEGG database, although it is general enough to work on any database. As expected, using the metabolic DAGs formalism, a considerable reduction on the size of the metabolic networks has been obtained, specially in the case of the purine pathway due to its relative larger size. As a proof of concept, from the information captured by a metabolic DAG and its corresponding metabolic building blocks, we obtain the core of the glycolysis pathway and the core of the purine metabolism pathway and detect some essential metabolic building blocks that reveal the key reactions in both pathways. Finally, the application of our methodology to the glycolysis pathway and the purine metabolism pathway reproduce the tree of life for the whole set of the organisms represented in the KEGG database which supports the utility of this research. PMID:28493998
Biochemical characterization of a GH43 ß-xylosidase from Bacteroides ovatus
USDA-ARS?s Scientific Manuscript database
Divalent-metal-activated, glycoside hydrolase (GH43) ß-xylosidases have been found to have high kcat/Km for xylooligosaccharides and may demonstrate high efficacy in industrial reactors digesting hemicellulose. By searching an amino acid database, we found an enzyme that is 81% identical in amino ac...
Incorporation of Bioinformatics Exercises into the Undergraduate Biochemistry Curriculum
ERIC Educational Resources Information Center
Feig, Andrew L.; Jabri, Evelyn
2002-01-01
The field of bioinformatics is developing faster than most biochemistry textbooks can adapt. Supplementing the undergraduate biochemistry curriculum with data-mining exercises is an ideal way to expose the students to the common databases and tools that take advantage of this vast repository of biochemical information. An integrated collection of…
Tebani, Abdellah; Abily-Donval, Lenaig; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya
2016-01-01
Inborn errors of metabolism (IEM) represent a group of about 500 rare genetic diseases with an overall estimated incidence of 1/2500. The diversity of metabolic pathways involved explains the difficulties in establishing their diagnosis. However, early diagnosis is usually mandatory for successful treatment. Given the considerable clinical overlap between some inborn errors, biochemical and molecular tests are crucial in making a diagnosis. Conventional biological diagnosis procedures are based on a time-consuming series of sequential and segmented biochemical tests. The rise of “omic” technologies offers holistic views of the basic molecules that build a biological system at different levels. Metabolomics is the most recent “omic” technology based on biochemical characterization of metabolites and their changes related to genetic and environmental factors. This review addresses the principles underlying metabolomics technologies that allow them to comprehensively assess an individual biochemical profile and their reported applications for IEM investigations in the precision medicine era. PMID:27447622
Vaccari, Carolina; El Dib, Regina; de Camargo, João Lauro V
2017-05-15
Parkinson's disease (PD) is a progressive neurodegenerative condition that has genetic susceptibility, aging, and exposure to certain chemicals as risk factors. In recent decades, epidemiological and experimental studies have investigated the role of pesticides in the development of PD, in particular that of the herbicide paraquat. Here, we, therefore, aim to systematically review the association between paraquat exposure and PD. Observational studies (cohort, case-control, and cross-sectional) eligible for this systematic review will enroll any participant who was occupationally and/or environmentally exposed to paraquat. Experimental studies, including in vivo and in vitro assays designed to assess neurotoxicological endpoints or mechanisms of paraquat neurotoxicity, will also be eligible. Outcomes of interest include the following: PD diagnosis; neurobehavioral, biochemical, and/or morphological alterations; and cellular, biochemical, and/or molecular pathways to oxidative stress. Using terms to include all forms of paraquat combined with PD, the following electronic databases will be searched: PubMed, EMBASE, LILACS, Toxnet, and Web of Science, without restrictions as to language, year, or status of publication. A team of reviewers will independently select potential titles and abstracts, extract data, assess risk of bias, and determine the overall quality of evidence for each outcome using the Office of Health Assessment and Translation (OHAT) approach for systematic reviews and evidence integration. Dichotomous data will be summarized as odds ratios, and continuous data will be given as mean differences, both with their respective 95% confidence intervals. This is the first time that the OHAT systematic review protocol will be applied to investigate a possible causal association between exposure to paraquat and PD. Results from this study could serve as basis for regulatory agencies to define paraquat levels of concern, supporting its risk assessment process. PROSPERO CRD42016050861.
Protein Information Resource: a community resource for expert annotation of protein data
Barker, Winona C.; Garavelli, John S.; Hou, Zhenglin; Huang, Hongzhan; Ledley, Robert S.; McGarvey, Peter B.; Mewes, Hans-Werner; Orcutt, Bruce C.; Pfeiffer, Friedhelm; Tsugita, Akira; Vinayaka, C. R.; Xiao, Chunlin; Yeh, Lai-Su L.; Wu, Cathy
2001-01-01
The Protein Information Resource, in collaboration with the Munich Information Center for Protein Sequences (MIPS) and the Japan International Protein Information Database (JIPID), produces the most comprehensive and expertly annotated protein sequence database in the public domain, the PIR-International Protein Sequence Database. To provide timely and high quality annotation and promote database interoperability, the PIR-International employs rule-based and classification-driven procedures based on controlled vocabulary and standard nomenclature and includes status tags to distinguish experimentally determined from predicted protein features. The database contains about 200 000 non-redundant protein sequences, which are classified into families and superfamilies and their domains and motifs identified. Entries are extensively cross-referenced to other sequence, classification, genome, structure and activity databases. The PIR web site features search engines that use sequence similarity and database annotation to facilitate the analysis and functional identification of proteins. The PIR-International databases and search tools are accessible on the PIR web site at http://pir.georgetown.edu/ and at the MIPS web site at http://www.mips.biochem.mpg.de. The PIR-International Protein Sequence Database and other files are also available by FTP. PMID:11125041
Representing metabolic pathway information: an object-oriented approach.
Ellis, L B; Speedie, S M; McLeish, R
1998-01-01
The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD) is a website providing information and dynamic links for microbial metabolic pathways, enzyme reactions, and their substrates and products. The Compound, Organism, Reaction and Enzyme (CORE) object-oriented database management system was developed to contain and serve this information. CORE was developed using Java, an object-oriented programming language, and PSE persistent object classes from Object Design, Inc. CORE dynamically generates descriptive web pages for reactions, compounds and enzymes, and reconstructs ad hoc pathway maps starting from any UM-BBD reaction. CORE code is available from the authors upon request. CORE is accessible through the UM-BBD at: http://www. labmed.umn.edu/umbbd/index.html.
A two-step approach for mining patient treatment pathways in administrative healthcare databases.
Najjar, Ahmed; Reinharz, Daniel; Girouard, Catherine; Gagné, Christian
2018-05-01
Clustering electronic medical records allows the discovery of information on healthcare practices. Entries in such medical records are usually composed of a succession of diagnostics or therapeutic steps. The corresponding processes are complex and heterogeneous since they depend on medical knowledge integrating clinical guidelines, the physician's individual experience, and patient data and conditions. To analyze such data, we are first proposing to cluster medical visits, consultations, and hospital stays into homogeneous groups, and then to construct higher-level patient treatment pathways over these different groups. These pathways are then also clustered to distill typical pathways, enabling interpretation of clusters by experts. This approach is evaluated on a real-world administrative database of elderly people in Québec suffering from heart failures. Copyright © 2018 Elsevier B.V. All rights reserved.
Proteome reference map and regulation network of neonatal rat cardiomyocyte
Li, Zi-jian; Liu, Ning; Han, Qi-de; Zhang, You-yi
2011-01-01
Aim: To study and establish a proteome reference map and regulation network of neonatal rat cardiomyocyte. Methods: Cultured cardiomyocytes of neonatal rats were used. All proteins expressed in the cardiomyocytes were separated and identified by two-dimensional polyacrylamide gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). Biological networks and pathways of the neonatal rat cardiomyocytes were analyzed using the Ingenuity Pathway Analysis (IPA) program (www.ingenuity.com). A 2-DE database was made accessible on-line by Make2ddb package on a web server. Results: More than 1000 proteins were separated on 2D gels, and 148 proteins were identified. The identified proteins were used for the construction of an extensible markup language-based database. Biological networks and pathways were constructed to analyze the functions associate with cardiomyocyte proteins in the database. The 2-DE database of rat cardiomyocyte proteins can be accessed at http://2d.bjmu.edu.cn. Conclusion: A proteome reference map and regulation network of the neonatal rat cardiomyocytes have been established, which may serve as an international platform for storage, analysis and visualization of cardiomyocyte proteomic data. PMID:21841810
Realizing the promise of AOPs: A stakeholder-driven roadmap to the future
The adverse outcome pathway (AOP) framework was developed to serve as a knowledge assembly and communication tool to facilitate translation of mechanistic (e.g., molecular, biochemical, histological) data into adverse apical outcomes meaningful to chemical risk assessment. Althou...
Varbanova, Marina; Porter, Katie; Lu, Fachuang; Ralph, John; Hammerschmidt, Ray; Jones, A. Daniel; Day, Brad
2011-01-01
To elucidate the genetic and biochemical regulation of elicitor-induced p-coumaraldehyde accumulation in plants, we undertook a multifaceted approach to characterize the metabolic flux through the phenylpropanoid pathway via the characterization and chemical analysis of the metabolites in the p-coumaryl, coniferyl, and sinapyl alcohol branches of this pathway. Here, we report the identification and characterization of four cinnamyl alcohol dehydrogenases (CADs) from cucumber (Cucumis sativus) with low activity toward p-coumaraldehyde yet exhibiting significant activity toward other phenylpropanoid hydroxycinnamaldehydes. As part of this analysis, we identified and characterized the activity of a hydroxycinnamoyl-coenzyme A:shikimate hydroxycinnamoyl transferase (HCT) capable of utilizing shikimate and p-coumaroyl-coenzyme A to generate p-coumaroyl shikimate. Following pectinase treatment of cucumber, we observed the rapid accumulation of p-coumaraldehyde, likely the result of low aldehyde reductase activity (i.e. alcohol dehydrogenase in the reverse reaction) of CsCAD enzymes on p-coumaraldehyde. In parallel, we noted a concomitant reduction in the activity of CsHCT. Taken together, our findings support the hypothesis that the up-regulation of the phenylpropanoid pathway upon abiotic stress greatly enhances the overall p-coumaryl alcohol branch of the pathway. The data presented here point to a role for CsHCT (as well as, presumably, p-coumarate 3-hydroxylase) as a control point in the regulation of the coniferyl and sinapyl alcohol branches of this pathway. This mechanism represents a potentially evolutionarily conserved process to efficiently and quickly respond to biotic and abiotic stresses in cucurbit plants, resulting in the rapid lignification of affected tissues. PMID:21940999
The Halophile protein database.
Sharma, Naveen; Farooqi, Mohammad Samir; Chaturvedi, Krishna Kumar; Lal, Shashi Bhushan; Grover, Monendra; Rai, Anil; Pandey, Pankaj
2014-01-01
Halophilic archaea/bacteria adapt to different salt concentration, namely extreme, moderate and low. These type of adaptations may occur as a result of modification of protein structure and other changes in different cell organelles. Thus proteins may play an important role in the adaptation of halophilic archaea/bacteria to saline conditions. The Halophile protein database (HProtDB) is a systematic attempt to document the biochemical and biophysical properties of proteins from halophilic archaea/bacteria which may be involved in adaptation of these organisms to saline conditions. In this database, various physicochemical properties such as molecular weight, theoretical pI, amino acid composition, atomic composition, estimated half-life, instability index, aliphatic index and grand average of hydropathicity (Gravy) have been listed. These physicochemical properties play an important role in identifying the protein structure, bonding pattern and function of the specific proteins. This database is comprehensive, manually curated, non-redundant catalogue of proteins. The database currently contains 59 897 proteins properties extracted from 21 different strains of halophilic archaea/bacteria. The database can be accessed through link. Database URL: http://webapp.cabgrid.res.in/protein/ © The Author(s) 2014. Published by Oxford University Press.
Critical assessment of human metabolic pathway databases: a stepping stone for future integration
2011-01-01
Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison provides a stepping stone for such an endeavor. PMID:21999653
Examining the architecture of cellular computing through a comparative study with a computer
Wang, Degeng; Gribskov, Michael
2005-01-01
The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software–hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's ‘hardware’ equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the ‘bandwidth’ of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed. PMID:16849179
Belda-Palazón, Borja; Nohales, María A.; Rambla, José L.; Aceña, José L.; Delgado, Oscar; Fustero, Santos; Martínez, M. Carmen; Granell, Antonio; Carbonell, Juan; Ferrando, Alejandro
2014-01-01
The eukaryotic translation elongation factor eIF5A is the only protein known to contain the unusual amino acid hypusine which is essential for its biological activity. This post-translational modification is achieved by the sequential action of the enzymes deoxyhypusine synthase (DHS) and deoxyhypusine hydroxylase (DOHH). The crucial molecular function of eIF5A during translation has been recently elucidated in yeast and it is expected to be fully conserved in every eukaryotic cell, however the functional description of this pathway in plants is still sparse. The genetic approaches with transgenic plants for either eIF5A overexpression or antisense have revealed some activities related to the control of cell death processes but the molecular details remain to be characterized. One important aspect of fully understanding this pathway is the biochemical description of the hypusine modification system. Here we have used recombinant eIF5A proteins either modified by hypusination or non-modified to establish a bi-dimensional electrophoresis (2D-E) profile for the three eIF5A protein isoforms and their hypusinated or unmodified proteoforms present in Arabidopsis thaliana. The combined use of the recombinant 2D-E profile together with 2D-E/western blot analysis from whole plant extracts has provided a quantitative approach to measure the hypusination status of eIF5A. We have used this information to demonstrate that treatment with the hormone abscisic acid produces an alteration of the hypusine modification system in Arabidopsis thaliana. Overall this study presents the first biochemical description of the post-translational modification of eIF5A by hypusination which will be functionally relevant for future studies related to the characterization of this pathway in Arabidopsis thaliana. PMID:24904603
Examining the architecture of cellular computing through a comparative study with a computer.
Wang, Degeng; Gribskov, Michael
2005-06-22
The computer and the cell both use information embedded in simple coding, the binary software code and the quadruple genomic code, respectively, to support system operations. A comparative examination of their system architecture as well as their information storage and utilization schemes is performed. On top of the code, both systems display a modular, multi-layered architecture, which, in the case of a computer, arises from human engineering efforts through a combination of hardware implementation and software abstraction. Using the computer as a reference system, a simplistic mapping of the architectural components between the two is easily detected. This comparison also reveals that a cell abolishes the software-hardware barrier through genomic encoding for the constituents of the biochemical network, a cell's "hardware" equivalent to the computer central processing unit (CPU). The information loading (gene expression) process acts as a major determinant of the encoded constituent's abundance, which, in turn, often determines the "bandwidth" of a biochemical pathway. Cellular processes are implemented in biochemical pathways in parallel manners. In a computer, on the other hand, the software provides only instructions and data for the CPU. A process represents just sequentially ordered actions by the CPU and only virtual parallelism can be implemented through CPU time-sharing. Whereas process management in a computer may simply mean job scheduling, coordinating pathway bandwidth through the gene expression machinery represents a major process management scheme in a cell. In summary, a cell can be viewed as a super-parallel computer, which computes through controlled hardware composition. While we have, at best, a very fragmented understanding of cellular operation, we have a thorough understanding of the computer throughout the engineering process. The potential utilization of this knowledge to the benefit of systems biology is discussed.
2010-11-15
denitrosation of MNX by DN22 did not involve direct participation of either oxygen or water, but both played major roles in subsequent secondary chemical and... secondary reactions and products distributions would pro- vide new insights into the degradation pathway of RDX and thus help in the development of...not involve direct participation of either oxygen or water, but both played major roles in subsequent secondary chemical and biochemical reactions of
Clustering and optimal arrangement of enzymes in reaction-diffusion systems.
Buchner, Alexander; Tostevin, Filipe; Gerland, Ulrich
2013-05-17
Enzymes within biochemical pathways are often colocalized, yet the consequences of specific spatial enzyme arrangements remain poorly understood. We study the impact of enzyme arrangement on reaction efficiency within a reaction-diffusion model. The optimal arrangement transitions from a cluster to a distributed profile as a single parameter, which controls the probability of reaction versus diffusive loss of pathway intermediates, is varied. We introduce the concept of enzyme exposure to explain how this transition arises from the stochastic nature of molecular reactions and diffusion.
Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K
2015-01-01
Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Folate and epigenetic mechanisms in neural tube development and defects.
Meethal, Sivan Vadakkadath; Hogan, Kirk J; Mayanil, Chandra S; Iskandar, Bermans J
2013-09-01
Multiple genetic and epigenetic factors involved in central nervous system (CNS) development influence the incidence of neural tube defects (NTDs). The beneficial effect of periconceptional folic acid on NTD prevention denotes a vital role for the single-carbon biochemical pathway in NTD genesis. Indeed, NTDs are associated with polymorphisms in a diversity of genes that encode folate pathway enzymes. Recent evidence suggests that CNS development and function, and consequently NTDs, are also associated with epigenetic mechanisms, many of which participate in the folate cycle and its input and output pathways. We provide an overview with select examples drawn from the authors' research.
Genome sequence analysis of a flocculant-producing bacterium, Paenibacillus shenyangensis.
Fu, Lili; Jiang, Binhui; Liu, Jinliang; Zhao, Xin; Liu, Qian; Hu, Xiaomin
2016-03-01
To explore the metabolic process of Paenibacillus shenyangensis that is an efficient bioflocculant-producing bacterium. The biosynthesis mechanism of bioflocculation was used to enrich the genome of Paenibacillus shenyangensis and provide a basis for molecular genetics and functional genomics analyses. According to the analysis of de novo assembly, a total of 5,501,467 bp clean reads were generated, and were assembled into 92 contigs. 4800 unigenes were predicted of which 4393 were annotated showing a specific gene function in the NCBI-Nr database. 3423 genes were found in the database of cluster of orthologous groups. Among the 168 Kyoto Encyclopedia of Genes and Genomes database, cell growth and metabolism were the main biological processes, and a potential metabolic pathway was predicted from glucose to exopolysaccharide within the starch and sucrose metabolism pathway. By using the high-throughput sequencing technology, we provide a genome analysis of Paenibacillus shenyangensis that predicts the main metabolic processes and a potential pathway of exopolysaccharide biosynthesis.
Wang, Yali; Xu, Nan; Ye, Chao; Liu, Liming; Shi, Zhongping; Wu, Jing
2015-01-01
Actinoplanes sp. SE50/110 produces the α-glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites, and 1219 reactions. One hundred and twenty-two and eighty one genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78 and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110. PMID:26161077
Amendola, Giorgio; Di Maio, Danilo; La Pietra, Valeria; Cosconati, Sandro
2016-09-01
SMO receptor is one of the main components of the Hedgehog biochemical pathway. In the last decades compelling body of evidence demonstrated that this receptor is a pertinent target for the treatment of various types of solid tumors. Recently, the X-ray determination of the three-dimensional structure of SMO in complex with different antagonists opened up the way for the structure-based design of new antagonists for this receptor that could possibly overcome the limitations connected with the induction of acquired tumor resistance. Herein, taking advantage of three different docking software (namely Glide, PLANTS, and Vina) and of the available SMO structures we set up a retrospective virtual screening (VS) protocol. A database, made up by known SMO antagonists and compounds with no alleged activity against the receptor was created and screened against the different SMO structures. To evaluate the performance of the ranking in VS calculations different statistical metrics (EF, AUAC and BEDROC) were employed allowing to identify the best performing VS docking protocol. Results of these studies will serve as a platform for the application of structure-based VS against the pharmaceutically relevant SMO receptor. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Ennis, William J; Lee, Claudia; Plummer, Malgorzata; Meneses, Patricio
2011-01-01
Wound healing is a complex pathway that requires cells, an appropriate biochemical environment (i.e., cytokines, chemokines), an extracellular matrix, perfusion, and the application of both macrostrain and microstrain. The process is both biochemically complex and energy dependent. Healing can be assisted in difficult cases through the use of physical modalities. In the current literature, there is much debate over which treatment modality, dosage level, and timing is optimal. The mechanism of action for both electrical stimulation and ultrasound are reviewed along with possible clinical applications for the plastic surgeon.
MIMO: an efficient tool for molecular interaction maps overlap
2013-01-01
Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344
MetNetAPI: A flexible method to access and manipulate biological network data from MetNet
2010-01-01
Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api. PMID:21083943
Flavonoid engineering of flax potentiate its biotechnological application.
Zuk, Magdalena; Kulma, Anna; Dymińska, Lucyna; Szołtysek, Katarzyna; Prescha, Anna; Hanuza, Jerzy; Szopa, Jan
2011-01-28
Flavonoids are a group of secondary plant metabolites important for plant growth and development. They show also a protective effect against colon and breast cancer, diabetes, hypercholesterolemic atherosclerosis, lupus nephritis, and immune and inflammatory reactions. Thus, overproduction of these compounds in flax by genetic engineering method might potentiate biotechnological application of these plant products. Flax plants of third generation overexpressing key genes of flavonoid pathway cultivated in field were used as plant material throughout this study. The biochemical properties of seed, oil and seedcake extracts and fibre from natural and transgenic flax plants were compared. The data obtained suggests that the introduced genes were stably inherited and expressed through plant generations. Overproduction of flavonoid compounds resulted in increase of fatty acids accumulation in oil from transgenic seeds due to protection from oxidation offered during synthesis and seed maturation. The biochemical analysis of seedcake extracts from seeds of transgenic flax revealed significant increase in flavonoids (kaempferol), phenolic acids (coumaric, ferulic, synapic acids) and lignan content. Fibres, another product of flax plant showed increase in the level of catechine and acetylvanillone and decrease in phenolic acids upon flax modification.Biochemical analysis results were confirmed using IR spectroscopy. The integral intensities of IR bands have been used for identification of the component of phenylpropanoid pathway in oil, seedcake extract and fibre from control and transgenic flax. It was shown that levels of flavonoids, phenolic acids and lignans in oil and seedcake extract was higher in transgenic flax products compared to control. An FT-IR study of fibres confirmed the biochemical data and revealed that the arrangement of the cellulose polymer in the transgenic fibres differs from the control; in particular a significant decrease in the number of hydrogen bonds was detected. All analysed products from generated transgenic plants were enriched with antioxidant compounds derived from phenylopropanoid pathway Thus the products provide valuable source of flavonoids, phenolic acids and lignan for biomedical application. The compounds composition and quantity from transgenic plants was confirmed by IR spectroscopy. Thus the infrared spectroscopy appeared to be suitable method for characterization of flax products.
Flavonoid engineering of flax potentiate its biotechnological application
2011-01-01
Background Flavonoids are a group of secondary plant metabolites important for plant growth and development. They show also a protective effect against colon and breast cancer, diabetes, hypercholesterolemic atherosclerosis, lupus nephritis, and immune and inflammatory reactions. Thus, overproduction of these compounds in flax by genetic engineering method might potentiate biotechnological application of these plant products. Results Flax plants of third generation overexpressing key genes of flavonoid pathway cultivated in field were used as plant material throughout this study. The biochemical properties of seed, oil and seedcake extracts and fibre from natural and transgenic flax plants were compared. The data obtained suggests that the introduced genes were stably inherited and expressed through plant generations. Overproduction of flavonoid compounds resulted in increase of fatty acids accumulation in oil from transgenic seeds due to protection from oxidation offered during synthesis and seed maturation. The biochemical analysis of seedcake extracts from seeds of transgenic flax revealed significant increase in flavonoids (kaempferol), phenolic acids (coumaric, ferulic, synapic acids) and lignan content. Fibres, another product of flax plant showed increase in the level of catechine and acetylvanillone and decrease in phenolic acids upon flax modification. Biochemical analysis results were confirmed using IR spectroscopy. The integral intensities of IR bands have been used for identification of the component of phenylpropanoid pathway in oil, seedcake extract and fibre from control and transgenic flax. It was shown that levels of flavonoids, phenolic acids and lignans in oil and seedcake extract was higher in transgenic flax products compared to control. An FT-IR study of fibres confirmed the biochemical data and revealed that the arrangement of the cellulose polymer in the transgenic fibres differs from the control; in particular a significant decrease in the number of hydrogen bonds was detected. Conclusions All analysed products from generated transgenic plants were enriched with antioxidant compounds derived from phenylopropanoid pathway Thus the products provide valuable source of flavonoids, phenolic acids and lignan for biomedical application. The compounds composition and quantity from transgenic plants was confirmed by IR spectroscopy. Thus the infrared spectroscopy appeared to be suitable method for characterization of flax products. PMID:21276227
The art and design of genetic screens: maize
USDA-ARS?s Scientific Manuscript database
Maize (Zea mays) is an excellent model for basic research. Genetic screens have informed our understanding of developmental processes, meiosis, epigenetics and biochemical pathways--not only in maize but also in other cereal crops. We discuss the forward and reverse genetic screens that are possible...
How Living Things Obtain Energy: A Simpler Explanation.
ERIC Educational Resources Information Center
Igelsrud, Donald E.
1989-01-01
Examines five basic reactions which describe the biochemical pathways for living things obtaining energy. Shows the reactions that occur in respiration after glycolysis, the dehydrogenation reaction, decarboxylation, and two kinds of make-ready reactions which prepare molecules for further dehydrogenation and decarboxylation. Diagrams are…
Gene Polymorphism Studies in a Teaching Laboratory
ERIC Educational Resources Information Center
Shultz, Jeffry
2009-01-01
I present a laboratory procedure for illustrating transcription, post-transcriptional modification, gene conservation, and comparative genetics for use in undergraduate biology education. Students are individually assigned genes in a targeted biochemical pathway, for which they design and test polymerase chain reaction (PCR) primers. In this…
MODELS FOR LEACHING OF PESTICIDES IN SOILS AND GROUNDWATER
Models are developed which describe leaching of pesticides in the root zone and the intermediate vadose zone, and flushing of residual solute mass in the aquifer. Pollutants' loss pathways in the soil, such as volatilization, crop uptake, and biochemical decay, are emphasized, a...
Teaching Intermediary Metabolism Linearly Doesn't Work
ERIC Educational Resources Information Center
Glew, Robert H.; Brass, Eric
2005-01-01
Despite the fact that knowledge of the major biochemical metabolic pathways is essential to understanding the pathophysiology, clinical presentation, and management of many human diseases, there is disagreement among medical educators regarding the relevance of intermediary metabolism to the practicing physician and the expectations for medical…
Protein binding of isofluorophate in vivo after coexposure to multiple chemicals.
Vogel, John S; Keating, Garrett A; Buchholz, Bruce A
2002-01-01
Full toxicologic profiles of chemical mixtures, including dose-response extrapolations to realistic exposures, is a prohibitive analytical problem, even for a restricted class of chemicals. We present an approach to probing in vivo interactions of pesticide mixtures at relevant low doses using a monitor compound to report the response of biochemical pathways shared by mixture components. We use accelerator mass spectrometry (AMS) to quantify [14C]-diisopropylfluorophosphate as a tracer at attomole levels with 1-5% precision after coexposures to parathion (PTN), permethrin (PER), and pyridostigmine bromide separately and in conjunction. Pyridostigmine shows an overall protective effect against tracer binding in plasma, red blood cells, muscle, and brain that is not explained as competitive protein binding. PTN and PER induce a significant 25-30% increase in the amount of tracer reaching the brain with or without pyridostigmine. The sensitivity of AMS for isotope-labeled tracer compounds can be used to probe the physiologic responses of specific biochemical pathways to multiple compound exposures. PMID:12634135
A review of multi-threat medical countermeasures against chemical warfare and terrorism.
Cowan, Fred M; Broomfield, Clarence A; Stojiljkovic, Milos P; Smith, William J
2004-11-01
The Multi-Threat Medical Countermeasure (MTMC) hypothesis has been proposed with the aim of developing a single countermeasure drug with efficacy against different pathologies caused by multiple classes of chemical warfare agents. Although sites and mechanisms of action and the pathologies caused by different chemical insults vary, common biochemical signaling pathways, molecular mediators, and cellular processes provide targets for MTMC drugs. This article will review the MTMC hypothesis for blister and nerve agents and will expand the scope of the concept to include other chemicals as well as briefly consider biological agents. The article will also consider how common biochemical signaling pathways, molecular mediators, and cellular processes that contribute to clinical pathologies and syndromes may relate to the toxicity of threat agents. Discovery of MTMC provides the opportunity for the integration of diverse researchers and clinicians, and for the exploitation of cutting-edge technologies and drug discovery. The broad-spectrum nature of MTMC can augment military and civil defense to combat chemical warfare and chemical terrorism.
IR and Raman studies of oil and seedcake extracts from natural and genetically modified flax seeds
NASA Astrophysics Data System (ADS)
Żuk, M.; Dymińska, L.; Kulma, A.; Boba, A.; Prescha, A.; Szopa, J.; Mączka, M.; Zając, A.; Szołtysek, K.; Hanuza, J.
2011-03-01
Flax plant of the third generation (F3) overexpressing key genes of flavonoid pathway cultivated in field in 2008 season was used as the plant material throughout this study. The biochemical properties of seed, oil and seedcake extracts from natural and transgenic flax plants were compared. Overproduction of flavonoids (kaempferol), phenolic acids (coumaric, ferulic/synapic) and lignan-secoisolariciresinol diglucoside (SDG) in oil and extracts from transgenic seeds has been revealed providing a valuable source of these compounds for biotechnological application. The changes in fatty acids composition and increase in their stability against oxidation along three plant generations were also detected. The analysis of oil and seedcake extracts was performed using Raman and IR spectroscopy. The wavenumbers and integral intensities of Raman and IR bands were used to identify the components of phenylpropanoid pathway in oil and seedcake extracts from control and transgenic flax seeds. The spectroscopic data were compared to those obtained from biochemical analysis.
Lu, Xin; Liang, Weili; Wang, Yunduan; Xu, Jialiang
2014-01-01
Vibrio fluvialis is an important food-borne pathogen that causes diarrheal illness and sometimes extraintestinal infections in humans. In this study, we sequenced the genome of a clinical V. fluvialis strain and determined its phylogenetic relationships with other Vibrio species by comparative genomic analysis. We found that the closest relationship was between V. fluvialis and V. furnissii, followed by those with V. cholerae and V. mimicus. Moreover, based on genome comparisons and gene complementation experiments, we revealed genetic mechanisms of the biochemical tests that differentiate V. fluvialis from closely related species. Importantly, we identified a variety of genes encoding potential virulence factors, including multiple hemolysins, transcriptional regulators, and environmental survival and adaptation apparatuses, and the type VI secretion system, which is indicative of complex regulatory pathways modulating pathogenesis in this organism. The availability of V. fluvialis genome sequences may promote our understanding of pathogenic mechanisms for this emerging pathogen. PMID:24441165
The Pathway Coexpression Network: Revealing pathway relationships
Tanzi, Rudolph E.
2018-01-01
A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099
Heuett, William J; Beard, Daniel A; Qian, Hong
2008-01-01
Background Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RTBS and STBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA). PMID:18482450
The return of metabolism: biochemistry and physiology of the pentose phosphate pathway
Stincone, Anna; Prigione, Alessandro; Cramer, Thorsten; Wamelink, Mirjam M. C.; Campbell, Kate; Cheung, Eric; Olin-Sandoval, Viridiana; Grüning, Nana-Maria; Krüger, Antje; Alam, Mohammad Tauqeer; Keller, Markus A.; Breitenbach, Michael; Brindle, Kevin M.; Rabinowitz, Joshua D.; Ralser, Markus
2015-01-01
The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner–Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the ‘Warburg effect’ of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and parasite infections, neurons, stem cell potency and cancer metabolism. PMID:25243985
Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.
Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju
2017-04-27
Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By means of network and pathway-based methodology, we explored the pathogenetic mechanism underlying AD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular mechanism underlying AD. In addition, the framework proposed in this study could be used to investigate the pathological molecular network and genes relevant to other complex diseases or phenotypes.
Struck-Lewicka, Wiktoria; Kordalewska, Marta; Bujak, Renata; Yumba Mpanga, Arlette; Markuszewski, Marcin; Jacyna, Julia; Matuszewski, Marcin; Kaliszan, Roman; Markuszewski, Michał J
2015-01-01
Prostate cancer (CaP) is a leading cause of cancer deaths in men worldwide. The alarming statistics, the currently applied biomarkers are still not enough specific and selective. In addition, pathogenesis of CaP development is not totally understood. Therefore, in the present work, metabolomics study related to urinary metabolic fingerprinting analyses has been performed in order to scrutinize potential biomarkers that could help in explaining the pathomechanism of the disease and be potentially useful in its diagnosis and prognosis. Urine samples from CaP patients and healthy volunteers were analyzed with the use of high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) in positive and negative polarity as well as gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in a scan mode. The obtained data sets were statistically analyzed using univariate and multivariate statistical analyses. The Principal Component Analysis (PCA) was used to check systems' stability and possible outliers, whereas Partial Least Squares Discriminant Analysis (PLS-DA) was performed for evaluation of quality of the model as well as its predictive ability using statistically significant metabolites. The subsequent identification of selected metabolites using NIST library and commonly available databases allows for creation of a list of putative biomarkers and related biochemical pathways they are involved in. The selected pathways, like urea and tricarboxylic acid cycle, amino acid and purine metabolism, can play crucial role in pathogenesis of prostate cancer disease. Copyright © 2014 Elsevier B.V. All rights reserved.
Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves
2017-01-01
Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501
Tong, Jun; Dong, Yanfang; Xu, Dongyun; Mao, Jing; Zhou, Yuan
2017-01-01
Rhododendron spp. is an important ornamental species that is widely cultivated for landscape worldwide. Heat stress is a major obstacle for its cultivation in south China. Previous studies on rhododendron principally focused on its physiological and biochemical processes, which are involved in a series of stress tolerance. However, molecular or genetic properties of rhododendron’s response to heat stress are still poorly understood. The phenotype and chlorophyll fluorescence kinetics parameters of four rhododendron cultivars were compared under normal or heat stress conditions, and a cultivar with highest heat tolerance, “Yanzhimi” (R. obtusum) was selected for transcriptome sequencing. A total of 325,429,240 high quality reads were obtained and assembled into 395,561 transcripts and 92,463 unigenes. Functional annotation showed that 38,724 unigenes had sequence similarity to known genes in at least one of the proteins or nucleotide databases used in this study. These 38,724 unigenes were categorized into 51 functional groups based on Gene Ontology classification and were blasted to 24 known cluster of orthologous groups. A total of 973 identified unigenes belonged to 57 transcription factor families, including the stress-related HSF, DREB, ZNF, and NAC genes. Photosynthesis was significantly enriched in the Kyoto Encyclopedia of Genes and Genomes pathway, and the changed expression pattern was illustrated. The key pathways and signaling components that contribute to heat tolerance in rhododendron were revealed. These results provide a potentially valuable resource that can be used for heat-tolerance breeding. PMID:29059200
Zhang, Libin; Feng, Qiming; Sun, Lina; Ding, Kui; Huo, Da; Fang, Yan; Zhang, Tao; Yang, Hongsheng
2018-03-01
Sea cucumber, Apostichopus japonicus is an important species for aquaculture, and its behavior and physiology can change in response to changing salinity conditions. For this reason, it is important to understand the molecular responses of A. japonicus when exposed to ambient changes in salinity. In this study, RNA-Seq provided a general overview of the gene expression profiles in the intestine of A. japonicus exposed to high salinity (SD40), normal salinity (SD30) and low salinity (SD20) environments. Screening for differentially expressed genes (DEGs) using the NOISeq method identified 109, 100, and 89 DEGs based on a fold change of ≥2 and divergence probability ≥0.8 according to the comparisons of SD20 vs. SD30, SD20 vs.SD40, and SD30 vs. SD40, respectively. Gene ontology analysis showed that the terms "metabolic process" and "catalytic activity" comprised the most enriched DEGs. These fell into the categories of "biological process" and "molecular function". While "cell" and "cell part" had the most enriched DEGs in the category of "cellular component". With these DEGs mapping to 2119, 159, and 160 pathways in the Kyoto Encyclopedia of Genes and Genomes database. Of these 51, 2, and 57 pathways were significantly enriched, respectively. The osmosis-specific DEGs identified in this study of A. japonicus will be important targets for further studies to understand the biochemical mechanisms involved with the adaption of sea cucumbers to changes in salinity. Copyright © 2017. Published by Elsevier Inc.
Adeli, Khosrow; Higgins, Victoria; Nieuwesteeg, Michelle; Raizman, Joshua E; Chen, Yunqi; Wong, Suzy L; Blais, David
2015-08-01
Biological covariates such as age and sex can markedly influence biochemical marker reference values, but no comprehensive study has examined such changes across pediatric, adult, and geriatric ages. The Canadian Health Measures Survey (CHMS) collected comprehensive nationwide health information and blood samples from children and adults in the household population and, in collaboration with the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER), examined biological changes in biochemical markers from pediatric to geriatric age, establishing a comprehensive reference interval database for routine disease biomarkers. The CHMS collected health information, physical measurements, and biosamples (blood and urine) from approximately 12 000 Canadians aged 3-79 years and measured 24 biochemical markers with the Ortho Vitros 5600 FS analyzer or a manual microplate. By use of CLSI C28-A3 guidelines, we determined age- and sex-specific reference intervals, including corresponding 90% CIs, on the basis of specific exclusion criteria. Biochemical marker reference values exhibited dynamic changes from pediatric to geriatric age. Most biochemical markers required some combination of age and/or sex partitioning. Two or more age partitions were required for all analytes except bicarbonate, which remained constant throughout life. Additional sex partitioning was required for most biomarkers, except bicarbonate, total cholesterol, total protein, urine iodine, and potassium. Understanding the fluctuations in biochemical markers over a wide age range provides important insight into biological processes and facilitates clinical application of biochemical markers to monitor manifestation of various disease states. The CHMS-CALIPER collaboration addresses this important evidence gap and allows the establishment of robust pediatric and adult reference intervals. © 2015 American Association for Clinical Chemistry.
Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling
NASA Technical Reports Server (NTRS)
Cucinotta, Francis A.; O'Neill, Peter; Ponomarev, Artem; Carra, Claudio; Whalen, Mary; Pluth, Janice M.
2009-01-01
Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.
Chai, Hui; Yan, Zhaoyuan; Huang, Ke; Jiang, Yuanqing; Zhang, Lin
2018-02-01
This study aimed to systematically investigate the relationship between miRNA expression and the occurrence of ventricular septal defect (VSD), and characterize the miRNA target genes and pathways that can lead to VSD. The miRNAs that were differentially expressed in blood samples from VSD and normal infants were screened and validated by implementing miRNA microarrays and qRT-PCR. The target genes regulated by differentially expressed miRNAs were predicted using three target gene databases. The functions and signaling pathways of the target genes were enriched using the GO database and KEGG database, respectively. The transcription and protein expression of specific target genes in critical pathways were compared in the VSD and normal control groups using qRT-PCR and western blotting, respectively. Compared with the normal control group, the VSD group had 22 differentially expressed miRNAs; 19 were downregulated and three were upregulated. The 10,677 predicted target genes participated in many biological functions related to cardiac development and morphogenesis. Four target genes (mGLUR, Gq, PLC, and PKC) were involved in the PKC pathway and four (ECM, FAK, PI3 K, and PDK1) were involved in the PI3 K-Akt pathway. The transcription and protein expression of these eight target genes were significantly upregulated in the VSD group. The 22 miRNAs that were dysregulated in the VSD group were mainly downregulated, which may result in the dysregulation of several key genes and biological functions related to cardiac development. These effects could also be exerted via the upregulation of eight specific target genes, the subsequent over-activation of the PKC and PI3 K-Akt pathways, and the eventual abnormal cardiac development and VSD.
ERIC Educational Resources Information Center
Cedeno, David L.; Jones, Marjorie A.; Friesen, Jon A.; Wirtz, Mark W.; Rios, Luz Amalia; Ocampo, Gonzalo Taborda
2010-01-01
At the Universidad de Caldas, Manizales, Colombia, we used their new computer facilities to introduce chemistry graduate students to biochemical database mining and quantum chemistry calculations using freeware. These hands-on workshops allowed the students a strong introduction to easily accessible software and how to use this software to begin…
BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks
Rialle, Stéphanie; Felicori, Liza; Dias-Lopes, Camila; Pérès, Sabine; El Atia, Sanaâ; Thierry, Alain R.; Amar, Patrick; Molina, Franck
2010-01-01
Motivation: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. Results: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. Availability and implementation: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/ Contact: stephanie.rialle@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20628073
Chen, Xiao-Min; Feng, Ming-Jun; Shen, Cai-Jie; He, Bin; Du, Xian-Feng; Yu, Yi-Bo; Liu, Jing; Chu, Hui-Min
2017-07-01
The present study was designed to develop a novel method for identifying significant pathways associated with human hypertrophic cardiomyopathy (HCM), based on gene co‑expression analysis. The microarray dataset associated with HCM (E‑GEOD‑36961) was obtained from the European Molecular Biology Laboratory‑European Bioinformatics Institute database. Informative pathways were selected based on the Reactome pathway database and screening treatments. An empirical Bayes method was utilized to construct co‑expression networks for informative pathways, and a weight value was assigned to each pathway. Differential pathways were extracted based on weight threshold, which was calculated using a random model. In order to assess whether the co‑expression method was feasible, it was compared with traditional pathway enrichment analysis of differentially expressed genes, which were identified using the significance analysis of microarrays package. A total of 1,074 informative pathways were screened out for subsequent investigations and their weight values were also obtained. According to the threshold of weight value of 0.01057, 447 differential pathways, including folding of actin by chaperonin containing T‑complex protein 1 (CCT)/T‑complex protein 1 ring complex (TRiC), purine ribonucleoside monophosphate biosynthesis and ubiquinol biosynthesis, were obtained. Compared with traditional pathway enrichment analysis, the number of pathways obtained from the co‑expression approach was increased. The results of the present study demonstrated that this method may be useful to predict marker pathways for HCM. The pathways of folding of actin by CCT/TRiC and purine ribonucleoside monophosphate biosynthesis may provide evidence of the underlying molecular mechanisms of HCM, and offer novel therapeutic directions for HCM.
Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.
Wu, Xiya; Zhang, Wei; Hu, Yunhua; Yi, Xianghua
2015-01-01
The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it. Comprehensive bioinformatics methods were applied. Initially, significant differentially expressed genes (DEGs) were analyzed from the Affymetrix microarray data (GSE27262) deposited in the Gene Expression Omnibus (GEO). Subsequently, gene ontology (GO) analysis was performed using online Database for Annotation, Visualization and Integration Discovery (DAVID) software. Finally, significant pathway crosstalk was investigated based on the information derived from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. According to our results, the N-terminal globular domain of the type X collagen (COL10A1) gene and transmembrane protein 100 (TMEM100) gene were identified to be the most significant DEGs in tumor tissue compared with the adjacent normal tissues. The main GO categories were biological process, cellular component and molecular function. In addition, the crosstalk was significantly different between non-small cell lung cancer pathways and inositol phosphate metabolism pathway, focal adhesion signal pathway, vascular smooth muscle contraction signal pathway, peroxisome proliferator-activated receptor (PPAR) signaling pathway and calcium signaling pathway in tumor. Dysfunctional genes and pathways may play key roles in the progression and development of lung adenocarcinoma. Our data provide a systematic perspective for understanding this mechanism and may be helpful in discovering an effective treatment for lung adenocarcinoma.
Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.
Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E N; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa
2016-01-01
Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map. © 2015 The International Union of Biochemistry and Molecular Biology.
Rosic, Nedeljka N
2012-04-01
Mycosporine-like amino acids (MAAs) are multifunctional secondary metabolites involved in photoprotection in many marine organisms. As well as having broad ultraviolet (UV) absorption spectra (310-362 nm), these biological sunscreens are also involved in the prevention of oxidative stress. More than 20 different MAAs have been discovered so far, characterized by distinctive chemical structures and a broad ecological distribution. Additionally, UV-screening MAA metabolites have been investigated and used in biotechnology and cosmetics. The biosynthesis of MAAs has been suggested to occur via either the shikimate or pentose phosphate pathways. Despite their wide distribution in marine and freshwater species and also the commercial application in cosmetic products, there are still a number of uncertainties regarding the genetic, biochemical, and evolutionary origin of MAAs. Here, using a transcriptome-mining approach, we identify the gene counterparts from the shikimate or pentose phosphate pathway involved in MAA biosynthesis within the sequences of the reef-building coral symbiotic dinoflagellates (genus Symbiodinium). We also report the highly similar sequences of genes from the proposed MAA biosynthetic pathway involved in the metabolism of 4-deoxygadusol (direct MAA precursor) in various Symbiodinium strains confirming their algal origin and conserved nature. Finally, we reveal the separate identity of two O-methyltransferase genes, possibly involved in MAA biosynthesis, as well as nonribosomal peptide synthetase and adenosine triphosphate grasp homologs in symbiotic dinoflagellates. This study provides a biochemical and phylogenetic overview of the genes from the proposed MAA biosynthetic pathway with a focus on coral endosymbionts.
de Vries, Jan; de Vries, Sophie; Slamovits, Claudio H; Rose, Laura E; Archibald, John M
2017-05-01
The origin of land plants from algae is a long-standing question in evolutionary biology. It is becoming increasingly clear that many characters that were once assumed to be 'embryophyte specific' can in fact be found in their closest algal relatives, the streptophyte algae. One such case is the phenylpropanoid pathway. While biochemical data indicate that streptophyte algae harbor lignin-like components, the phenylpropanoid core pathway, which serves as the backbone of lignin biosynthesis, has been proposed to have arisen at the base of the land plants. Here we revisit this hypothesis using a wealth of new sequence data from streptophyte algae. Tracing the biochemical pathway towards lignin biogenesis, we show that most of the genes required for phenylpropanoid synthesis and the precursors for lignin production were already present in streptophyte algae. Nevertheless, phylogenetic analyses and protein structure predictions of one of the key enzyme classes in lignin production, cinnamyl alcohol dehydrogenase (CAD), suggest that CADs of streptophyte algae are more similar to sinapyl alcohol dehydrogenases (SADs). This suggests that the end-products of the pathway leading to lignin biosynthesis in streptophyte algae may facilitate the production of lignin-like compounds and defense molecules. We hypothesize that streptophyte algae already possessed the genetic toolkit from which the capacity to produce lignin later evolved in vascular plants. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Comprehensive analyses of genomes, transcriptomes and metabolites of neem tree
Rangiah, Kannan; Mahesh, HB; Rajamani, Anantharamanan; Shirke, Meghana D.; Russiachand, Heikham; Loganathan, Ramya Malarini; Shankara Lingu, Chandana; Siddappa, Shilpa; Ramamurthy, Aishwarya; Sathyanarayana, BN
2015-01-01
Neem (Azadirachta indica A. Juss) is one of the most versatile tropical evergreen tree species known in India since the Vedic period (1500 BC–600 BC). Neem tree is a rich source of limonoids, having a wide spectrum of activity against insect pests and microbial pathogens. Complex tetranortriterpenoids such as azadirachtin, salanin and nimbin are the major active principles isolated from neem seed. Absolutely nothing is known about the biochemical pathways of these metabolites in neem tree. To identify genes and pathways in neem, we sequenced neem genomes and transcriptomes using next generation sequencing technologies. Assembly of Illumina and 454 sequencing reads resulted in 267 Mb, which accounts for 70% of estimated size of neem genome. We predicted 44,495 genes in the neem genome, of which 32,278 genes were expressed in neem tissues. Neem genome consists about 32.5% (87 Mb) of repetitive DNA elements. Neem tree is phylogenetically related to citrus, Citrus sinensis. Comparative analysis anchored 62% (161 Mb) of assembled neem genomic contigs onto citrus chromomes. Ultrahigh performance liquid chromatography-mass spectrometry-selected reaction monitoring (UHPLC-MS/SRM) method was used to quantify azadirachtin, nimbin, and salanin from neem tissues. Weighted Correlation Network Analysis (WCGNA) of expressed genes and metabolites resulted in identification of possible candidate genes involved in azadirachtin biosynthesis pathway. This study provides genomic, transcriptomic and quantity of top three neem metabolites resource, which will accelerate basic research in neem to understand biochemical pathways. PMID:26290780
Selen Alpergin, Ebru S; Bolandnazar, Zeinab; Sabatini, Martina; Rogowski, Michael; Chiellini, Grazia; Zucchi, Riccardo; Assadi-Porter, Fariba M
2017-01-01
Complex diseases such as polycystic ovary syndrome (PCOS) are associated with intricate pathophysiological, hormonal, and metabolic feedbacks that make their early diagnosis challenging, thus increasing the prevalence risks for obesity, cardiovascular, and fatty liver diseases. To explore the crosstalk between endocrine and lipid metabolic pathways, we administered 3-iodothyronamine (T1AM), a natural analog of thyroid hormone, in a mouse model of PCOS and analyzed plasma and tissue extracts using multidisciplinary omics and biochemical approaches. T1AM administration induces a profound tissue-specific antilipogenic effect in liver and muscle by lowering gene expression of key regulators of lipid metabolism, PTP1B and PLIN2, significantly increasing metabolites (glucogenic, amino acids, carnitine, and citrate) levels, while enhancing protection against oxidative stress. In contrast, T1AM has an opposing effect on the regulation of estrogenic pathways in the ovary by upregulating STAR, CYP11A1, and CYP17A1. Biochemical measurements provide further evidence of significant reduction in liver cholesterol and triglycerides in post-T1AM treatment. Our results shed light onto tissue-specific metabolic vs. hormonal pathway interactions, thus illuminating the intricacies within the pathophysiology of PCOS This study opens up new avenues to design drugs for targeted therapeutics to improve quality of life in complex metabolic diseases. © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.
Tilki, Derya; Mandel, Philipp; Schlomm, Thorsten; Chun, Felix K-H; Tennstedt, Pierre; Pehrke, Dirk; Haese, Alexander; Huland, Hartwig; Graefen, Markus; Salomon, Georg
2015-06-01
The CAPRA-S score predicts prostate cancer recurrence based on pathological information from radical prostatectomy. To our knowledge CAPRA-S has never been externally validated in a European cohort. We independently validated CAPRA-S in a single institution European database. The study cohort comprised 14,532 patients treated with radical prostatectomy between January 1992 and August 2012. Prediction of biochemical recurrence, metastasis and cancer specific mortality by CAPRA-S was assessed by Kaplan-Meier analysis and the c-index. CAPRA-S performance to predict biochemical recurrence was evaluated by calibration plot and decision curve analysis. Median followup was 50.8 months (IQR 25.0-96.0). Biochemical recurrence developed in 20.3% of men at a median of 21.2 months (IQR 7.7-44.9). When stratifying patients by CAPRA-S risk group, estimated 5-year biochemical recurrence-free survival was 91.4%, 70.4% and 29.3% in the low, intermediate and high risk groups, respectively. The CAPRA-S c-index to predict biochemical recurrence, metastasis and cancer specific mortality was 0.80, 0.85 and 0.88, respectively. Metastasis developed in 417 men and 196 men died of prostate cancer. The CAPRA-S score was accurate when applied in a European study cohort. It predicted biochemical recurrence, metastasis and cancer specific mortality after radical prostatectomy with a c-index of greater than 0.80. The score can be valuable in regard to decision making for adjuvant therapy. Copyright © 2015. Published by Elsevier Inc.
In addressing the complexity and toxicity of chemical contaminants in Great Lakes ecosystems, we describe an approach to link chemically induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and populations. Analysis of population impac...
Saikrishna Mukkamala Saikrishna Mukkamala Researcher IV-Chemical Engineering Saikrishna.Mukkamala thermochemical, biochemical pathways Bio product and fuel characterization Education M.S. Chemical Engineering , University of Maine B.S. Chemical Engineering, JNTU-India Featured Publications S. Mukkamala, M.C. Wheeler
Ionomics: Genes and QTLs controlling heavy metal uptake in perennial grasses grown on phytoxic soil
USDA-ARS?s Scientific Manuscript database
Perennial grasses occupy diverse soils throughout the world, including many sites contaminated with heavy metals. Uncovering the genetic architecture of QTLs controlling mineral homoeostasis is critical for understanding the biochemical pathways that determine the elemental profiles of perennial pl...
Global gene expression profile analysis can be utilized to derive molecular footprints to understand biochemical
pathways implicated in the origin and progression of disease. Functional genomics efforts with tissue-specific focused
genearray appears to be the most...
Andretta, I; Kipper, M; Lehnen, C R; Lovatto, P A
2012-02-01
A meta-analysis was carried out to study the association of mycotoxins with hematological and biochemical profiles in broilers. Ninety-eight articles published between 1980 and 2009 were used in the database, totaling 37,371 broilers. The information was selected from the Materials and Methods and Results sections in the selected articles and then tabulated in a database. Meta-analysis followed 3 sequential analyses: graphic, correlation, and variance-covariance. Mycotoxins reduced (P < 0.05) the hematocrit (-5%), hemoglobin (-15%), leukocytes (-25%), heterophils (-2%), lymphocytes (-2%), uric acid (-31%), creatine kinase (-27%), creatinine (-23%), triglycerides (-39%), albumin (-17%), globulin (-1%), total cholesterol (-14%), calcium (-5%), and inorganic phosphorus (-12%). Mycotoxins also altered (P < 0.05) the concentrations of alkaline phosphatase, alanine aminotransferase, and aspartate aminotransferase. A quadratic effect was observed on the relationship between the concentration of aflatoxin in diets and the serum concentration of alkaline phosphatase, γ-glutamyl transferase, alanine aminotransferase, and aspartate aminotransferase. The total protein concentration in blood was 18% lower (P < 0.05) in broilers challenged by aflatoxins compared with that of the unchallenged ones. The inclusion of antimycotoxin additives in diets with aflatoxins altered (P < 0.05) some variables (uric acid, creatinine, alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transferase) in relation to the group that received diets with the mycotoxin and without the additive. The meta-analysis performed in this study allowed us to address and quantify systematically the relationship of mycotoxins with alterations in hematologic and biochemical profiles in broilers.
Photosynthetic strategies of two Mojave Desert shrubs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kleinkopf, G.E.; Hartsock, T.L.; Wallace, A.
1980-01-01
Photosynthetic production of two Mojave Desert shrubs was measured under natural growing conditions. Measurements of photosynthesis, transpiration, resistances to water vapor flux, soil moisture potential, and tissue water potential were made. Atriplex canescens (Pursh) Nutt., a member of the C/sub 4/ biochemical carbon dioxide fixation group was highly competitive in growth rate and production during conditions of adequate soil moisture. As soil moisture conditions declined to minus 40 bars, the net photosynthetic rate of Atriplex decreased to zero. However, the C/sub 3/ shrub species Larrea tridentata (Sesse and Moc. ex DC.) Cov. was able to maintain positive net photosynthetic productionmore » during conditions of high temperature and extreme low soil moisture through the major part of the season. The comparative advantages of the C/sub 4/ versus the C/sub 3/ pathway of carbon fixation was lost between these two species as the soil moisture potential declined to minus 40 bars. Desert plants have diffferent strategies for survival, one of the strategies being the C/sub 4/ biochemical carbon fixation pathway. However, many of the plants are members of the C/sub 3/ group. In this instance, the C/sub 4/ fixation pathway does not confer an added advantage to the productivity of the species in the Mojave Desert. Species distribution based on comparative photosynthetic production is discussed« less
Larkin, Paul B.; Sathyasaikumar, Korrapati V.; Notarangelo, Francesca M.; Funakoshi, Hiroshi; Nakamura, Toshikazu; Schwarcz, Robert; Muchowski, Paul J.
2018-01-01
In mammals, the majority of the essential amino acid tryptophan is degraded via the kynurenine pathway (KP). Several KP metabolites play distinct physiological roles, often linked to immune system functions, and may also be causally involved in human diseases including neurodegenerative disorders, schizophrenia and cancer. Pharmacological manipulation of the KP has therefore become an active area of drug development. To target the pathway effectively, it is important to understand how specific KP enzymes control levels of the bioactive metabolites in vivo. Here, we conducted a comprehensive biochemical characterization of mice with a targeted deletion of either tryptophan 2,3-dioxygenase (TDO) or indoleamine 2,3-dioxygenase (IDO), the two initial rate-limiting enzymes of the KP. These enzymes catalyze the same reaction, but differ in biochemical characteristics and expression patterns. We measured KP metabolite levels and enzyme activities and expression in several tissues in basal and immune-stimulated conditions. Although our study revealed several unexpected downstream effects on KP metabolism in both knockout mice, the results were essentially consistent with TDO-mediated control of basal KP metabolism and a role of IDO in phenomena involving stimulation of the immune system. PMID:27392942
Peng, Mengling; Han, Jing; Li, Longlong; Ma, Haitian
2016-01-01
(-)-Hydroxycitric acid (HCA) suppresses fatty acid synthesis in animals, but its biochemical mechanism in poultry is unclear. This study identified the key proteins associated with fat metabolism and elucidated the biochemical mechanism of (-)-HCA in broiler chickens. Four groups (n = 30 each) received a diet supplemented with 0, 1000, 2000 or 3000 mg/kg (-)-HCA for 4 weeks. Of the differentially expressed liver proteins, 40 and 26 were identified in the mitochondrial and cytoplasm respectively. Pyruvate dehydrogenase E1 components (PDHA1 and PDHB), dihydrolipoyl dehydrogenase (DLD), aconitase (ACO2), a-ketoglutarate dehydrogenase complex (DLST), enoyl-CoA hydratase (ECHS1) and phosphoglycerate kinase (PGK) were upregulated, while NADP-dependent malic enzyme (ME1) was downregulated. Biological network analysis showed that the identified proteins were involved in glycometabolism and lipid metabolism, whereas PDHA1, PDHB, ECHS1, and ME1 were identified in the canonical pathway by Ingenuity Pathway Analysis. The data indicated that (-)-HCA inhibited fatty acid synthesis by reducing the acetyl-CoA supply, via promotion of the tricarboxylic acid cycle (upregulation of PDHA1, PDHB, ACO2, and DLST expression) and inhibition of ME1 expression. Moreover, (-)-HCA promoted fatty acid beta-oxidation by upregulating ECHS1 expression. These results reflect a biochemically relevant mechanism of fat reduction by (-)-HCA in broiler chickens. PMID:27586962
2014-01-01
Automatic reconstruction of metabolic pathways for an organism from genomics and transcriptomics data has been a challenging and important problem in bioinformatics. Traditionally, known reference pathways can be mapped into an organism-specific ones based on its genome annotation and protein homology. However, this simple knowledge-based mapping method might produce incomplete pathways and generally cannot predict unknown new relations and reactions. In contrast, ab initio metabolic network construction methods can predict novel reactions and interactions, but its accuracy tends to be low leading to a lot of false positives. Here we combine existing pathway knowledge and a new ab initio Bayesian probabilistic graphical model together in a novel fashion to improve automatic reconstruction of metabolic networks. Specifically, we built a knowledge database containing known, individual gene / protein interactions and metabolic reactions extracted from existing reference pathways. Known reactions and interactions were then used as constraints for Bayesian network learning methods to predict metabolic pathways. Using individual reactions and interactions extracted from different pathways of many organisms to guide pathway construction is new and improves both the coverage and accuracy of metabolic pathway construction. We applied this probabilistic knowledge-based approach to construct the metabolic networks from yeast gene expression data and compared its results with 62 known metabolic networks in the KEGG database. The experiment showed that the method improved the coverage of metabolic network construction over the traditional reference pathway mapping method and was more accurate than pure ab initio methods. PMID:25374614
Phospholipid biosynthesis in Candida albicans: regulation by the precursors inositol and choline.
Klig, L S; Friedli, L; Schmid, E
1990-01-01
Phospholipid metabolism in the pathogenic fungus Candida albicans was examined. The phospholipid biosynthetic pathways of C. albicans were elucidated and were shown to be similar to those of Saccharomyces cerevisiae. However, marked differences were seen between these two fungi in the regulation of the pathways in response to exogenously provided precursors inositol and choline. In S. cerevisiae, the biosynthesis of phosphatidylcholine via methylation of phosphatidylethanolamine appears to be regulated in response to inositol and choline; provision of choline alone does not repress the activity of this pathway (G. M. Carman and S. A. Henry, Annu. Rev. Biochem. 58:636-669, 1989). The same pathway in C. albicans responds to the exogenous provision of choline. Possible explanations for the observed differences in regulation are discussed. Images PMID:2198258
Giersch, C; Cornish-Bowden, A
1996-10-07
The double modulation method for determining the elasticities of pathway enzymes, originally devised by Kacser & Burns (Biochem. Soc. Trans. 7, 1149-1160, 1979), is extended to pathways of complex topological structure, including branching and feedback loops. An explicit system of linear equations for the unknown elasticities is derived. The constraints imposed on this linear system imply that modulations of more than one enzyme are not necessarily independent. Simple combinatorial rules are described for identifying without using any algebra the set of independent modulations that allow the determination of the elasticities of any enzyme. By repeated application, the minimum numbers of modulations required to determine the elasticities of all enzymes of a given pathway can be determined. The procedure is illustrated with numerous examples.
Wang, Wenbo; Zhao, Linlin; He, Zhenyu; Wu, Ning; Li, Qiuxia; Qiu, Xinjian; Zhou, Lu; Wang, Dongsheng
2018-06-12
Ge-Gen-Jiao-Tai-Wan (GGJTW) formula, derived from traditional Chinese herbal medicine, is composed of Pueraria montana var. lobata (Willd.) Sanjappa & Pradeep (Ge-Gen in Chinese), Coptis chinensis Franch (Huang-Lian), and Cinnamomum cassia (L.) J. Presl (Rou-Gui). GGJTW is used for treatment of diabetes in China, reflecting the potent hypoglycemic effect of its ingredients. However, little is known of the hypoglycemic effect of GGJTW and the underlying metabolic mechanism. This study aimed to investigate the hypoglycemic effect of GGJTW in type 2 diabetic rats and the metabolic mechanism of action. Ultra high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF/MS)-based metabolomics approach was used for monitoring hyperglycaemia induced by high-sugar high-fat fodder and streptozotocin (STZ), and the protective effect of GGJTW. Dynamic fasting blood glucose (FBG) levels, body weight, and biochemical parameters, including lipid levels, hepatic-renal function, and hepatic histopathology were used to confirm the hyperglycaemic toxicity and attenuation effects. An orthogonal partial least squared-discriminant analysis (OPLS-DA) approach highlighted significant differences in the metabolome of the healthy control, diabetic, and drug-treated rats. The metabolomics pathway analysis (MetPA) and Kyoto encyclopedia of genes and genomes (KEGG) database were used to investigate the underlying metabolic pathways. Metabolic profiling revealed 37 metabolites as the most potential biomarker metabolites distinguishing GGJTW-treated rats from model rats. Most of the metabolites were primarily associated with bile acid metabolism and lipid metabolism. The most critical pathway was primary bile acid biosynthesis pathway involving the up-regulation of the levels of cholic acid (CA), chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), taurochenodesoxycholic acid (TCDCA), and taurine. The significantly-altered metabolite levels indicated the hypoglycemic effect of GGJTW on diabetic rats and the underlying metabolic mechanism. This study will be meaningful for the clinical application of GGJTW and valuable for further exploration of the mechanism. Copyright © 2018 Elsevier B.V. All rights reserved.
Knowledge representation in metabolic pathway databases.
Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C
2014-05-01
The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.
Entamoeba histolytica: construction and applications of subgenomic databases.
Hofer, Margit; Duchêne, Michael
2005-07-01
Knowledge about the influence of environmental stress such as the action of chemotherapeutic agents on gene expression in Entamoeba histolytica is limited. We plan to use oligonucleotide microarray hybridization to approach these questions. As the basis for our array, sequence data from the genome project carried out by the Institute for Genomic Research (TIGR) and the Sanger Institute were used to annotate parts of the parasite genome. Three subgenomic databases containing enzymes, cytoskeleton genes, and stress genes were compiled with the help of the ExPASy proteomics website and the BLAST servers at the two genome project sites. The known sequences from reference species, mostly human and Escherichia coli, were searched against TIGR and Sanger E. histolytica sequence contigs and the homologs were copied into a Microsoft Access database. In a similar way, two additional databases of cytoskeletal genes and stress genes were generated. Metabolic pathways could be assembled from our enzyme database, but sometimes they were incomplete as is the case for the sterol biosynthesis pathway. The raw databases contained a significant number of duplicate entries which were merged to obtain curated non-redundant databases. This procedure revealed that some E. histolytica genes may have several putative functions. Representative examples such as the case of the delta-aminolevulinate synthase/serine palmitoyltransferase are discussed.
Database on pharmacophore analysis of active principles, from medicinal plants
Pitchai, Daisy; Manikkam, Rajalakshmi; Rajendran, Sasikala R; Pitchai, Gnanamani
2010-01-01
Plants continue to be a major source of medicines, as they have been throughout human history. In the present days, drug discovery from plants involves a multidisciplinary approach combining ethnobotanical, phytochemical and biological techniques to provide us new chemical compounds (lead molecules) for the development of drugs against various pharmacological targets, including cancer, diabetes and its secondary complications. In view of this need in current drug discovery from medicinal plants, here we describe another web database containing the information of pharmacophore analysis of active principles possessing antidiabetic, antimicrobial, anticancerous and antioxidant properties from medicinal plants. The database provides the botanical, taxonomic classification, biochemical as well as pharmacological properties of medicinal plants. Data on antidiabetic, antimicrobial, anti oxidative, anti tumor and anti inflammatory compounds, and their physicochemical properties, SMILES Notation, Lipinski's properties are included in our database. One of the proposed features in the database is the predicted ADMET values and the interaction of bioactive compounds to the target protein. The database alphabetically lists the compound name and also provides tabs separating for anti microbial, antitumor, antidiabetic, and antioxidative compounds. Availability http://www.hccbif.info / PMID:21346859
Convergence of Hippocampal Pathophysiology in Syngap+/- and Fmr1-/y Mice.
Barnes, Stephanie A; Wijetunge, Lasani S; Jackson, Adam D; Katsanevaki, Danai; Osterweil, Emily K; Komiyama, Noboru H; Grant, Seth G N; Bear, Mark F; Nägerl, U Valentin; Kind, Peter C; Wyllie, David J A
2015-11-11
Previous studies have hypothesized that diverse genetic causes of intellectual disability (ID) and autism spectrum disorders (ASDs) converge on common cellular pathways. Testing this hypothesis requires detailed phenotypic analyses of animal models with genetic mutations that accurately reflect those seen in the human condition (i.e., have structural validity) and which produce phenotypes that mirror ID/ASDs (i.e., have face validity). We show that SynGAP haploinsufficiency, which causes ID with co-occurring ASD in humans, mimics and occludes the synaptic pathophysiology associated with deletion of the Fmr1 gene. Syngap(+/-) and Fmr1(-/y) mice show increases in basal protein synthesis and metabotropic glutamate receptor (mGluR)-dependent long-term depression that, unlike in their wild-type controls, is independent of new protein synthesis. Basal levels of phosphorylated ERK1/2 are also elevated in Syngap(+/-) hippocampal slices. Super-resolution microscopy reveals that Syngap(+/-) and Fmr1(-/y) mice show nanoscale alterations in dendritic spine morphology that predict an increase in biochemical compartmentalization. Finally, increased basal protein synthesis is rescued by negative regulators of the mGlu subtype 5 receptor and the Ras-ERK1/2 pathway, indicating that therapeutic interventions for fragile X syndrome may benefit patients with SYNGAP1 haploinsufficiency. As the genetics of intellectual disability (ID) and autism spectrum disorders (ASDs) are unraveled, a key issue is whether genetically divergent forms of these disorders converge on common biochemical/cellular pathways and hence may be amenable to common therapeutic interventions. This study compares the pathophysiology associated with the loss of fragile X mental retardation protein (FMRP) and haploinsufficiency of synaptic GTPase-activating protein (SynGAP), two prevalent monogenic forms of ID. We show that Syngap(+/-) mice phenocopy Fmr1(-/y) mice in the alterations in mGluR-dependent long-term depression, basal protein synthesis, and dendritic spine morphology. Deficits in basal protein synthesis can be rescued by pharmacological interventions that reduce the mGlu5 receptor-ERK1/2 signaling pathway, which also rescues the same deficit in Fmr1(-/y) mice. Our findings support the hypothesis that phenotypes associated with genetically diverse forms of ID/ASDs result from alterations in common cellular/biochemical pathways. Copyright © 2015 Barnes et al.
Ikeda, Shun; Abe, Takashi; Nakamura, Yukiko; Kibinge, Nelson; Hirai Morita, Aki; Nakatani, Atsushi; Ono, Naoaki; Ikemura, Toshimichi; Nakamura, Kensuke; Altaf-Ul-Amin, Md; Kanaya, Shigehiko
2013-05-01
Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.
Wang, Shur-Jen; Laulederkind, Stanley J F; Hayman, G Thomas; Petri, Victoria; Smith, Jennifer R; Tutaj, Marek; Nigam, Rajni; Dwinell, Melinda R; Shimoyama, Mary
2016-08-01
Cardiovascular diseases are complex diseases caused by a combination of genetic and environmental factors. To facilitate progress in complex disease research, the Rat Genome Database (RGD) provides the community with a disease portal where genome objects and biological data related to cardiovascular diseases are systematically organized. The purpose of this study is to present biocuration at RGD, including disease, genetic, and pathway data. The RGD curation team uses controlled vocabularies/ontologies to organize data curated from the published literature or imported from disease and pathway databases. These organized annotations are associated with genes, strains, and quantitative trait loci (QTLs), thus linking functional annotations to genome objects. Screen shots from the web pages are used to demonstrate the organization of annotations at RGD. The human cardiovascular disease genes identified by annotations were grouped according to data sources and their annotation profiles were compared by in-house tools and other enrichment tools available to the public. The analysis results show that the imported cardiovascular disease genes from ClinVar and OMIM are functionally different from the RGD manually curated genes in terms of pathway and Gene Ontology annotations. The inclusion of disease genes from other databases enriches the collection of disease genes not only in quantity but also in quality. Copyright © 2016 the American Physiological Society.
The systematic annotation of the three main GPCR families in Reactome.
Jassal, Bijay; Jupe, Steven; Caudy, Michael; Birney, Ewan; Stein, Lincoln; Hermjakob, Henning; D'Eustachio, Peter
2010-07-29
Reactome is an open-source, freely available database of human biological pathways and processes. A major goal of our work is to provide an integrated view of cellular signalling processes that spans from ligand-receptor interactions to molecular readouts at the level of metabolic and transcriptional events. To this end, we have built the first catalogue of all human G protein-coupled receptors (GPCRs) known to bind endogenous or natural ligands. The UniProt database has records for 797 proteins classified as GPCRs and sorted into families A/1, B/2 and C/3 on the basis of amino acid sequence. To these records we have added details from the IUPHAR database and our own manual curation of relevant literature to create reactions in which 563 GPCRs bind ligands and also interact with specific G-proteins to initiate signalling cascades. We believe the remaining 234 GPCRs are true orphans. The Reactome GPCR pathway can be viewed as a detailed interactive diagram and can be exported in many forms. It provides a template for the orthology-based inference of GPCR reactions for diverse model organism species, and can be overlaid with protein-protein interaction and gene expression datasets to facilitate overrepresentation studies and other forms of pathway analysis. Database URL: http://www.reactome.org.
Jakobson, Christopher M; Tullman-Ercek, Danielle; Mangan, Niall M
2018-05-29
Natural biochemical systems are ubiquitously organized both in space and time. Engineering the spatial organization of biochemistry has emerged as a key theme of synthetic biology, with numerous technologies promising improved biosynthetic pathway performance. One strategy, however, may produce disparate results for different biosynthetic pathways. We use a spatially resolved kinetic model to explore this fundamental design choice in systems and synthetic biology. We predict that two example biosynthetic pathways have distinct optimal organization strategies that vary based on pathway-dependent and cell-extrinsic factors. Moreover, we demonstrate that the optimal design varies as a function of kinetic and biophysical properties, as well as culture conditions. Our results suggest that organizing biosynthesis has the potential to substantially improve performance, but that choosing the appropriate strategy is key. The flexible design-space analysis we propose can be adapted to diverse biosynthetic pathways, and lays a foundation to rationally choose organization strategies for biosynthesis.
Phosphatidylcholine and the CDP-Choline Cycle
Fagone, Paolo; Jackowski, Suzanne
2012-01-01
The CDP-choline pathway of phosphatidylcholine (PtdCho) biosynthesis was first described more than 50 years ago. Investigation of the CDP-choline pathway in yeast provides a basis for understanding the CDP-choline pathway in mammals. PtdCho is considered as an intermediate in a cycle of synthesis and degradation, and the activity of a CDP-choline cycle is linked to subcellular membrane lipid movement. The components of the mammalian CDP-choline pathway include choline transport, choline kinase, phosphocholine cytidylyltransferase, and choline phosphotransferase activities. The protein isoforms and biochemical mechanisms of regulation of the pathway enzymes are related to their cell and tissue-specific functions. Regulated PtdCho turnover mediated by phospholipases or neuropathy target esterase participates in the mammalian CDP-choline cycle. Knockout mouse models define the biological functions of the CDP-choline cycle in mammalian cells and tissues. This article is part of a Special Issue entitled Phospholipids and Phospholipid Metabolism. PMID:23010477
Meyer, Thomas; Melin, Frédéric; Richter, Oliver-M H; Ludwig, Bernd; Kannt, Aimo; Müller, Hanne; Michel, Hartmut; Hellwig, Petra
2015-02-27
Two different pathways through which protons access cytochrome c oxidase operate during oxygen reduction from the mitochondrial matrix, or the bacterial cytoplasm. Here, we use electrocatalytic current measurements to follow oxygen reduction coupled to proton uptake in cytochrome c oxidase isolated from Paracoccus denitrificans. Wild type enzyme and site-specific variants with defects in both proton uptake pathways (K354M, D124N and K354M/D124N) were immobilized on gold nanoparticles, and oxygen reduction was probed electrochemically in the presence of varying concentrations of Zn(2+) ions, which are known to inhibit both the entry and the exit proton pathways in the enzyme. Our data suggest that under these conditions substrate protons gain access to the oxygen reduction site via the exit pathway. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Han, Rowland H.; Wang, Miao; Fang, Xiaoling; Han, Xianlin
2013-01-01
Although the synthesis pathways of intracellular triacylglycerol (TAG) species have been well elucidated, assessment of the contribution of an individual pathway to TAG pools in different mammalian organs, particularly under pathophysiological conditions, is difficult, although not impossible. Herein, we developed and validated a novel bioinformatic approach to assess the differential contributions of the known pathways to TAG pools through simulation of TAG ion profiles determined by shotgun lipidomics. This powerful approach was applied to determine such contributions in mouse heart, liver, and skeletal muscle and to examine the changes of these pathways in mouse liver induced after treatment with a high-fat diet. It was clearly demonstrated that assessment of the altered TAG biosynthesis pathways under pathophysiological conditions can be readily achieved through simulation of lipidomics data. Collectively, this new development should greatly facilitate our understanding of the biochemical mechanisms underpinning TAG accumulation at the states of obesity and lipotoxicity. PMID:23365150
Zhulin, Igor B.
2015-05-26
Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhulin, Igor B.
Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. Finally, the purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists.
2015-01-01
Databases play an increasingly important role in biology. They archive, store, maintain, and share information on genes, genomes, expression data, protein sequences and structures, metabolites and reactions, interactions, and pathways. All these data are critically important to microbiologists. Furthermore, microbiology has its own databases that deal with model microorganisms, microbial diversity, physiology, and pathogenesis. Thousands of biological databases are currently available, and it becomes increasingly difficult to keep up with their development. The purpose of this minireview is to provide a brief survey of current databases that are of interest to microbiologists. PMID:26013493
Aniline Is an Inducer, and Not a Precursor, for Indole Derivatives in Rubrivivax benzoatilyticus JA2
Mohammed, Mujahid; Ch, Sasikala; Ch, Ramana V.
2014-01-01
Rubrivivax benzoatilyticus JA2 and other anoxygenic photosynthetic bacteria produce indole derivatives when exposed to aniline, a xenobiotic compound. Though this phenomenon has been reported previously, the role of aniline in the production of indoles is still a biochemical riddle. The present study aims at understanding the specific role of aniline (as precursor or stimulator) in the production of indoles and elucidating the biochemical pathway of indoles in aniline-exposed cells by using stable isotope approaches. Metabolic profiling revealed tryptophan accumulation only in aniline exposed cells along with indole 3-acetic acid (IAA) and indole 3-aldehyde (IAld), the two major catabolites of tryptophan. Deuterium labelled aniline feeding studies revealed that aniline is not a precursor of indoles in strain JA2. Further, production of indoles only in aniline-exposed cells suggests that aniline is an indoles stimulator. In addition, production of indoles depended on the presence of a carbon source, and production enhanced when carbon sources were added to the culture. Isotope labelled fumarate feeding identified, fumarate as the precursor of indole, indicating de novo synthesis of indoles. Glyphosate (shikimate pathway inhibitor) inhibited the indoles production, accumulation of tryptophan, IAA and IAld indicating that indoles synthesis in strain JA2 occurs via the de novo shikimate pathway. The up-regulation of anthranilate synthase gene and induction of anthranilate synthase activity correlated well with tryptophan production in strain JA2. Induction of tryptophan aminotransferase and tryptophan 2-monooxygenase activities corroborated well with IAA levels, suggesting that tryptophan catabolism occurs simultaneously in aniline exposed cells. Our study demonstrates that aniline (stress) stimulates tryptophan/indoles synthesis via the shikimate pathway by possibly modulating the metabolic pathway. PMID:24533057
Mujahid, Mohammed; Sasikala, Ch; Ramana, Ch V
2014-01-01
Rubrivivax benzoatilyticus JA2 and other anoxygenic photosynthetic bacteria produce indole derivatives when exposed to aniline, a xenobiotic compound. Though this phenomenon has been reported previously, the role of aniline in the production of indoles is still a biochemical riddle. The present study aims at understanding the specific role of aniline (as precursor or stimulator) in the production of indoles and elucidating the biochemical pathway of indoles in aniline-exposed cells by using stable isotope approaches. Metabolic profiling revealed tryptophan accumulation only in aniline exposed cells along with indole 3-acetic acid (IAA) and indole 3-aldehyde (IAld), the two major catabolites of tryptophan. Deuterium labelled aniline feeding studies revealed that aniline is not a precursor of indoles in strain JA2. Further, production of indoles only in aniline-exposed cells suggests that aniline is an indoles stimulator. In addition, production of indoles depended on the presence of a carbon source, and production enhanced when carbon sources were added to the culture. Isotope labelled fumarate feeding identified, fumarate as the precursor of indole, indicating de novo synthesis of indoles. Glyphosate (shikimate pathway inhibitor) inhibited the indoles production, accumulation of tryptophan, IAA and IAld indicating that indoles synthesis in strain JA2 occurs via the de novo shikimate pathway. The up-regulation of anthranilate synthase gene and induction of anthranilate synthase activity correlated well with tryptophan production in strain JA2. Induction of tryptophan aminotransferase and tryptophan 2-monooxygenase activities corroborated well with IAA levels, suggesting that tryptophan catabolism occurs simultaneously in aniline exposed cells. Our study demonstrates that aniline (stress) stimulates tryptophan/indoles synthesis via the shikimate pathway by possibly modulating the metabolic pathway.
Yu, Yang; Park, Ji-Won; Kwon, Hyun-Mi; Hwang, Hyun-Ok; Jang, In-Hwan; Masuda, Akiko; Kurokawa, Kenji; Nakayama, Hiroshi; Lee, Won-Jae; Dohmae, Naoshi; Zhang, Jinghai; Lee, Bok Luel
2010-01-01
In Drosophila, the synthesis of antimicrobial peptides in response to microbial infections is under the control of the Toll and immune deficiency (Imd) signaling pathway. The Toll signaling pathway responds mainly to the lysine-type peptidoglycan of Gram-positive bacteria and fungal β-1,3-glucan, whereas the Imd pathway responds to the meso-diaminopimelic acid (DAP)-type peptidoglycan of Gram-negative bacteria and certain Gram-positive bacilli. Recently we determined the activation mechanism of a Toll signaling pathway biochemically using a large beetle, Tenebrio molitor. However, DAP-type peptidoglycan recognition mechanism and its signaling pathway are still unclear in the fly and beetle. Here, we show that polymeric DAP-type peptidoglycan, but not its monomeric form, formed a complex with Tenebrio peptidoglycan recognition protein-SA, and this complex activated the three-step proteolytic cascade to produce processed Spätzle, a Toll receptor ligand, and induced Drosophila defensin-like antimicrobial peptide in Tenebrio larvae similarly to polymeric lysine-type peptidoglycan. Monomeric DAP-type peptidoglycan induced Drosophila diptericin-like antimicrobial peptide in Tenebrio hemocytes. In addition, both polymeric and monomeric DAP-type peptidoglycans induced expression of Tenebrio peptidoglycan recognition protein-SC2, which is DAP-type peptidoglycan-selective N-acetylmuramyl-l-alanine amidase that functions as a DAP-type peptidoglycan scavenger, appearing to function as a negative regulator of the DAP-type peptidoglycan signaling by cleaving DAP-type peptidoglycan in Tenebrio larvae. Taken together, these results demonstrate that molecular recognition mechanism for polymeric DAP-type peptidoglycan is different between Tenebrio larvae and Drosophila adults, providing biochemical evidences of biological diversity of innate immune responses in insects. PMID:20702416
Ellis, L B; Hershberger, C D; Wackett, L P
1999-01-01
The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://www.labmed.umn.edu/umbbd/i nde x.html) first became available on the web in 1995 to provide information on microbial biocatalytic reactions of, and biodegradation pathways for, organic chemical compounds, especially those produced by man. Its goal is to become a representative database of biodegradation, spanning the diversity of known microbial metabolic routes, organic functional groups, and environmental conditions under which biodegradation occurs. The database can be used to enhance understanding of basic biochemistry, biocatalysis leading to speciality chemical manufacture, and biodegradation of environmental pollutants. It is also a resource for functional genomics, since it contains information on enzymes and genes involved in specialized metabolism not found in intermediary metabolism databases, and thus can assist in assigning functions to genes homologous to such less common genes. With information on >400 reactions and compounds, it is poised to become a resource for prediction of microbial biodegradation pathways for compounds it does not contain, a process complementary to predicting the functions of new classes of microbial genes. PMID:9847233
Gabriele, Domenico; Garibaldi, Monica; Girelli, Giuseppe; Taraglio, Stefano; Duregon, Eleonora; Gabriele, Pietro; Guiot, Caterina; Bollito, Enrico
2016-06-01
This work aims to definitely show the ability of percentage of positive biopsy cores (%PC) to independently predict biochemical outcome beyond traditional pretreatment risk-factors in prostate cancer (PCa) patients treated with radiotherapy. A cohort of 2493 men belonging to the EUREKA-2 retrospective multicentric database on (PCa) and treated with external-beam radiation therapy (EBRT) as primary treatment comprised the study population (median follow-up 50 months). A Cox regression time to prostate-specific antigen (PSA) failure analysis was performed to evaluate the predictive power of %PC, both in univariate and multivariate settings, with age, pretreatment PSA, clinical-radiological staging, bioptic Gleason Score (bGS), RT dose and RT +/- ADT as covariates. P statistics for %PC is lower than 0.001 both in univariate and multivariate models. %PC as a continuous variable yields an AUC of 69% in ROC curve analysis for biochemical relapse. Four classes of %PC (1-20%, 21-50%, 51-80% and 81-100%) distinctly split patients for risk of biochemical relapse (overall log-rank test P<0.0001), with biochemical progression free survival (bPFS) at 5-years ranging from 88% to 58% and 10-years bPFS ranging from 80% to 38%. We strongly affirm the usefulness of %PC information beyond main risk factors (PSA, staging and bGS) in predicting biochemical recurrence after EBRT for PCa. The stratification of patients according to %PC may be valuable to further discriminate cases with favourable or adverse prognosis.
An "EAR" on environmental surveillance and monitoring: A ...
Current environmental monitoring approaches focus primarily on chemical occurrence. However, based on chemical concentration alone, it can be difficult to identify which compounds may be of toxicological concern for prioritization for further monitoring or management. This can be problematic because toxicological characterization is lacking for many emerging contaminants. New sources of high throughput screening data like the ToxCast™ database, which contains data for over 9,000 compounds screened through up to 1,100 assays, are now available. Integrated analysis of chemical occurrence data with HTS data offers new opportunities to prioritize chemicals, sites, or biological effects for further investigation based on concentrations detected in the environment linked to relative potencies in pathway-based bioassays. As a case study, chemical occurrence data from a 2012 study in the Great Lakes Basin along with the ToxCast™ effects database were used to calculate exposure-activity ratios (EARs) as a prioritization tool. Technical considerations of data processing and use of the ToxCast™ database are presented and discussed. EAR prioritization identified multiple sites, biological pathways, and chemicals that warrant further investigation. Biological pathways were then linked to adverse outcome pathways to identify potential adverse outcomes and biomarkers for use in subsequent monitoring efforts. Anthropogenic contaminants are frequently reported in environm
USDA-ARS?s Scientific Manuscript database
Aspartate kinase (AK) and homoserine dehydrogenase (HSD) functions as key regulatory enzymes at branch points in the aspartate amino acid pathway and are feedback inhibited by threonine. In plants, the biochemical properties of AK and bifunctional AK-HSD enzymes have been characterized, but the mol...
USDA-ARS?s Scientific Manuscript database
Plant cells possess a number of membrane bound organelles that play important roles in compartmentalizing a large number of biochemical pathways and physiological functions that have potentially harmful intermediates or by-products. The plasma membrane is particularly important as it holds the enti...
USDA-ARS?s Scientific Manuscript database
Vegetation acclimation to changing climate, in particular elevated atmospheric concentrations of carbon dioxide (CO2), has been observed to include modifications to the biochemical and eco physiological functioning of leaves and the structural components of the canopy. These responses have the poten...
Metabolomics for Undergraduates: Identification and Pathway Assignment of Mitochondrial Metabolites
ERIC Educational Resources Information Center
Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E. N.; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa
2016-01-01
Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening…
THE USE OF GENE ARRAYS TO DETERMINE TEMPORAL GENE INDUCTION IN SHEEPSHEAD MINNOWS EXPOSED TO E2
Gene arrays provide a means to study differential gene expression in fish exposed to environmental estrogens by providing a "snapshot" of the genes expressed at a given time. Such array data may also uncover previously unknown biochemical pathways affected by estrogenic compounds...
Understanding the mechanisms underlying toxicity initiated by nickel, a ubiquitous environmental contaminant and known human carcinogen is necessary for proper assessment of its risks to human and environment. Among a variety of toxic mechanisms, disruption of protein responses a...
A Laboratory Exercise for Isolation and Characterizing Microbial Mutants with Metabolic Defects.
ERIC Educational Resources Information Center
Doe, Frank J.; Leslie, John F.
1993-01-01
Describes science experiments for undergraduate biology instruction on the concepts of mutation and characterization of the resulting mutant strains. The filamentous fungi "Fusarium moniliforme" is used to illustrate the induction of mutants (mutagenesis), identification of the mutated gene, construction of a biochemical pathway, and…