Pathway/Genome Databases Research Articles

Bioinformatics Approach for Metabolism Pathways Curation: Carbohydrate Metabolism and TCA Cycle in the Archaeon Sulfolobus solfataricus P2

Background: Metabolic and genomic informatics integrations in organism-specific databases require comprehensive and intensive efforts. PathoLogic, a component of the Pathway Tools software package can create complete Pathway/Genome Databases (PGDBs) from genomic sequence and annotation files for any organism. This tool can predict the metabolic pathways using MetaCyc as a reference knowledge base. This work aimed to apply a bioinformatics approach to curate a PGDB created for the Crenarchaeon Sulfolobus solfataricus P2. This archaeon grows optimally at 80o C and pH 2-4. The complete genome of S. solfataricus P2 was released in 2001. Created PGDBs often need manual curations to fill in the metabolic gaps that the software failed to detect.
 Methods: We used Pathway Tools to create the PGDB for the Sulfolobus solfataricus P2. Bioinformatics curation for carbohydrate metabolism pathway (Entner-Doudoroff “ED”) and TCA cycle was carried out. Literature search as well as homology-, orthology- and context-based protein function prediction methods were followed for this curation using the Editors component of the Pathway Tools program.
 Results: Curation modified the number of the pathways in the database by adding extra pathways that have not been detected by the PathoLogic. New pathways such as semi-phosphorylated ED and a new variation of the TCA cycle were added to the PGDB of S. solfataricus P2. Filling in the metabolic holes (missing enzymes) in the pathways under study was also involved in the curation process.
 Conclusion: The bioinformatics curation of the PGDB of S. solfataricus P2 improved the database that can serve as a reference knowledge base for genomic annotations and metabolic pathway reconstructions of other organisms especially the closely related Archaea.

BuDb: A Curated Drug Discovery Database for Buruli Ulcer

Buruli ulcer (BU), a severe skin disease is caused by Mycobacterium ulcerans. There are concerns of therapeutic inefficacy of existing drugs coupled with chemoresistance. Databases have been shown to augment data mining and integrative systems pharmacology approaches towards the search for novel therapeutic moieties. So far, there is no known integrated database solely dedicated to BU drug discovery. In this work, Buruli ulcer database (BuDb) is a “one-stop-shop” knowledgebase for supporting BU drug discovery. It contains both manually verified literature and database-curated data on BU. The BuDb provides comprehensive information on the various drug targets, tested compounds, existing drugs, ethnopharmacological plants and information on the genome of M. ulcerans. It also contains cross-referenced links to databases including PubMed, PubChem, DrugBank, NCBI, Gene Ontology (GO), UniProt, Prota4u, String database, KEGG Pathway and KEGG genome database. The BuDb has been implemented with accessibility features such as keyword and specific searches as well as browsing. BuDb is the first useful online repository of its kind integrated with enriched datasets that can aid in the discovery of new biotherapeutic entities for BU. BuDb can be freely accessed at http://197.255.126.13:3000/ .

Pathway Tools Management of Pathway/Genome Data for Microbial Communities.

The Pathway Tools (PTools) software provides a suite of capabilities for storing and analyzing integrated collections of genomic and metabolic information in the form of organism-specific Pathway/Genome Databases (PGDBs). A microbial community is represented in PTools by generating a PGDB from each metagenome-assembled genome (MAG). PTools computes a metabolic reconstruction for each organism, and predicts its operons. The properties of individual MAGs can be investigated using the many search and visualization operations within PTools. PTools also enables the user to investigate the properties of the microbial community by issuing searches across the full community, and by performing comparative operations across genome and pathway information. The software can generate a metabolic network diagram for the community, and it can overlay community omics datasets on that network diagram. PTools also provides a tool for searching for metabolic transformation routes across an organism community.

Metabolic Reconstruction and Modeling From Sequenced Genomes

We present new developments in the bioinformatics algorithms that reconstruct the metabolic network of an organism from its sequenced genome, and that convert that metabolic network into a quantitative metabolic model. These algorithms are implemented in the Pathway Tools software. The Pathway Tools metabolic reconstruction process begins with an annotated genome; its first step infers the subset of metabolic reactions in the MetaCyc database that are catalyzed by enzymes within the genome. Reactome inference is based on the enzyme name and/or EC numbers within the genome annotation. The second step uses the inferred reactome to infer the subset of MetaCyc metabolic pathways present in the organism using a pathway scoring algorithm. Recent improvements to these algorithms are based on a large increase in the number of EC numbers in recent years, growth in the reaction (+30%) and pathway (+22%) content of the MetaCyc database, and development of a new pathway scoring algorithm that makes use of key reactions that must be either present or absent, and pathway taxonomic range information. The resulting metabolic reconstruction is available in the form of a Pathway/Genome Database (PGDB) that can be queried and visualized via an extensive set of online tools. The BioCyc.org website contains such PGDBs for 14,700 organisms.The MetaFlux component of Pathway Tools enables creation and execution of quantitative steady‐state metabolic flux models. Several steps are used to refine a PGDB to a quantitative steady‐state metabolic flux model. First, we must identify a set of nutrients that support growth of the organism, and we must identify a set of biomass metabolites that form the molecular building blocks of the organism. Next we ensure that the reactome within the PGDB can synthesize each of the biomass metabolites from the provided nutrients. Often the reactome contains gaps due to incompleteness in the genome annotation. We present a new taxonomic gap‐filling algorithm with significantly improved accuracy: when evaluated on randomly degraded variants of the Escherichia coli metabolic model, it shows an average F1 score of 99.0, compared to 91.0 for the previous Pathway Tools gap filler, and compared to 80.3 for a basic gap filler. Once gaps have been filled in the reaction network, MetaFlux can execute the model, using flux‐balance analysis to compute flux rates for all reactions in the model. Those fluxes can be interpreted by visualizing them on a whole‐organism metabolic network diagram. MetaFlux can also simulate the effects of single and double‐gene knock‐out mutants on the model. And MetaFlux can execute groups of models that simulate the growth of organism communities.Support or Funding InformationThis work was supported by the National Institutes of Health under grants GM080746 and GM075742. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The MetaCyc database of metabolic pathways and enzymes - a 2019 update.

MetaCyc (MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains 2749 pathways derived from more than 60 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc are evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in BioCyc.org and other genomic portals. This article provides an update on the developments in MetaCyc during September 2017 to August 2019, up to version 23.1. Some of the topics that received intensive curation during this period include cobamides biosynthesis, sterol metabolism, fatty acid biosynthesis, lipid metabolism, carotenoid metabolism, protein glycosylation, antibiotics and cytotoxins biosynthesis, siderophore biosynthesis, bioluminescence, vitamin K metabolism, brominated compound metabolism, plant secondary metabolism and human metabolism. Other additions include modifications to the GlycanBuilder software that enable displaying glycans using symbolic representation, improved graphics and fonts for web displays, improvements in the PathoLogic component of Pathway Tools, and the optional addition of regulatory information to pathway diagrams.

Automated Reconstruction and Manual Curation of Amino Acid Biosynthesis Pathways in Sulfolobus solfataricus P2

The efficient sequencing techniques have significantly increased the number of genomes that are now available, including the Crenarchaeon Sulfolobus solfataricus P2 genome. The genome-scale metabolic pathways in Sulfolobus solfataricus P2 were predicted by implementing the “Pathway Tools” software using MetaCyc database as reference knowledge base. A Pathway/Genome Data Base (PGDB) specific for Sulfolobus solfataricus P2 was created. A curation approach was carried out regarding all the amino acids biosynthetic pathways. Experimental literatures as well as homology-, orthology- and context-based protein function prediction methods were followed for the curation process. The “PathoLogic” component of the “Pathway Tools” programme was able to predict many amino acid biosynthetic metabolic pathways. The total number of the metabolic pathways was modified to 168 pathways by adding extra pathways that have not been detected by the “PathoLogic”. Amino acid biosynthetic pathways such as alpha-aminoadipic acid (AAA) pathway of Lysine biosynthesis and Alanine biosynthesis as well as the super-pathway of Phenylalanine, Tyrosine and Tryptophan biosynthesis variation II were added to the Pathway/Genome data base of Sulfolobus solfataricus P2. Discovery of the missing enzymes that have to fill in the metabolic holes in the pathways under study was the main curation task. This approach and the curated amino acid biosynthetic pathways in the PGDB of Sulfolobus solfataricus P2 can be used for genomic annotations and metabolic pathway reconstructions of closely related Bacteria and Archaea.

The MACADAM database: a MetAboliC pAthways DAtabase for Microbial taxonomic groups for mining potential metabolic capacities of archaeal and bacterial taxonomic groups.

Progress in genome sequencing and bioinformatics opens up new possibilities, including that of correlating genome annotations with functional information such as metabolic pathways. Thanks to the development of functional annotation databases, scientists are able to link genome annotations with functional annotations. We present MetAboliC pAthways DAtabase for Microbial taxonomic groups (MACADAM) here, a user-friendly database that makes it possible to find presence/absence/completeness statistics for metabolic pathways at a given microbial taxonomic position. For each prokaryotic ‘RefSeq complete genome’, MACADAM builds a pathway genome database (PGDB) using Pathway Tools software based on MetaCyc data that includes metabolic pathways as well as associated metabolites, reactions and enzymes. To ensure the highest quality of the genome functional annotation data, MACADAM also contains MicroCyc, a manually curated collection of PGDBs; Functional Annotation of Prokaryotic Taxa (FAPROTAX), a manually curated functional annotation database; and the IJSEM phenotypic database. The MACADAM database contains 13 509 PGDBs (13 195 bacterial and 314 archaeal), 1260 unique metabolic pathways, completed with 82 functional annotations from FAPROTAX and 16 from the IJSEM phenotypic database. MACADAM contains a total of 7921 metabolites, 592 enzymatic reactions, 2134 EC numbers and 7440 enzymes. MACADAM can be queried at any rank of the NCBI taxonomy (from phyla to species). It provides the possibility to explore functional information completed with metabolites, enzymes, enzymatic reactions and EC numbers. MACADAM returns a tabulated file containing a list of pathways with two scores (pathway score and pathway frequency score) that are present in the queried taxa. The file also contains the names of the organisms in which the pathways are found and the metabolic hierarchy associated with the pathways. Finally, MACADAM can be downloaded as a single file and queried with SQLite or python command lines or explored through a web interface.

Computational analysis of the Plasmodiophora brassicae genome: mitochondrial sequence description and metabolic pathway database design

Plasmodiophora brassicae is an obligate biotrophic pathogenic protist responsible for clubroot, a root gall disease of Brassicaceae species. In addition to the reference genome of the P. brassicae European e3 isolate and the draft genomes of Canadian or Chinese isolates, we present the genome of eH, a second European isolate. Refinement of the annotation of the eH genome led to the identification of the mitochondrial genome sequence, which was found to be bigger than that of Spongospora subterranea, another plant parasitic Plasmodiophorid phylogenetically related to P. brassicae. New pathways were also predicted, such as those for the synthesis of spermidine, a polyamine up-regulated in clubbed regions of roots. A P. brassicae pathway genome database was created to facilitate the functional study of metabolic pathways in transcriptomics approaches. These available tools can help in our understanding of the regulation of P. brassicae metabolism during infection and in response to diverse constraints.

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases.

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/

The MetaCyc database of metabolic pathways and enzymes.

MetaCyc (https://MetaCyc.org) is a comprehensive reference database of metabolic pathways and enzymes from all domains of life. It contains more than 2570 pathways derived from >54 000 publications, making it the largest curated collection of metabolic pathways. The data in MetaCyc is strictly evidence-based and richly curated, resulting in an encyclopedic reference tool for metabolism. MetaCyc is also used as a knowledge base for generating thousands of organism-specific Pathway/Genome Databases (PGDBs), which are available in the BioCyc (https://BioCyc.org) and other PGDB collections. This article provides an update on the developments in MetaCyc during the past two years, including the expansion of data and addition of new features.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

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.

Pathway Analysis and Omics Data Visualization Using Pathway Genome Databases: FragariaCyc, a Case Study.

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.

What's My Substrate? Computational Function Assignment of Candida parapsilosis ADH5 by Genome Database Search, Virtual Screening, and QM/MM Calculations.

Zinc-dependent medium chain reductase from Candida parapsilosis can be used in the reduction of carbonyl compounds to pharmacologically important chiral secondary alcohols. To date, the nomenclature of cpADH5 is differing (CPCR2/RCR/SADH) in the literature, and its natural substrate is not known. In this study, we utilized a substrate docking based virtual screening method combined with KEGG, MetaCyc pathway, and Candida genome databases search for the discovery of natural substrates of cpADH5. The virtual screening of 7834 carbonyl compounds from the ZINC database provided 94 aldehydes or methyl/ethyl ketones as putative carbonyl substrates. Out of which, 52 carbonyl substrates of cpADH5 with catalytically active docking pose were identified by employing mechanism based substrate docking protocol. Comparison of the virtual screening results with KEGG, MetaCyc database search, and Candida genome pathway analysis suggest that cpADH5 might be involved in the Ehrlich pathway (reduction of fusel aldehydes in leucine, isoleucine, and valine degradation). Our QM/MM calculations and experimental activity measurements affirmed that butyraldehyde substrates are the potential natural substrates of cpADH5, suggesting a carbonyl reductase role for this enzyme in butyraldehyde reduction in aliphatic amino acid degradation pathways. Phylogenetic tree analysis of known ADHs from Candida albicans shows that cpADH5 is close to caADH5. We therefore propose, according to the experimental substrate identification and sequence similarity, the common name butyraldehyde dehydrogenase cpADH5 for Candida parapsilosis CPCR2/RCR/SADH.

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome.

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.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

The MetaCyc database (MetaCyc.org) is a freely accessible comprehensive database describing metabolic pathways and enzymes from all domains of life. The majority of MetaCyc pathways are small-molecule metabolic pathways that have been experimentally determined. MetaCyc contains more than 2400 pathways derived from >46 000 publications, and is the largest curated collection of metabolic pathways. BioCyc (BioCyc.org) is a collection of 5700 organism-specific Pathway/Genome Databases (PGDBs), each containing the full genome and predicted metabolic network of one organism, including metabolites, enzymes, reactions, metabolic pathways, predicted operons, transport systems, and pathway-hole fillers. The BioCyc website offers a variety of tools for querying and analyzing PGDBs, including Omics Viewers and tools for comparative analysis. This article provides an update of new developments in MetaCyc and BioCyc during the last two years, including addition of Gibbs free energy values for compounds and reactions; redesign of the primary gene/protein page; addition of a tool for creating diagrams containing multiple linked pathways; several new search capabilities, including searching for genes based on sequence patterns, searching for databases based on an organism's phenotypes, and a cross-organism search; and a metabolite identifier translation service.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases

The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible database describing metabolic pathways and enzymes from all domains of life. MetaCyc pathways are experimentally determined, mostly small-molecule metabolic pathways and are curated from the primary scientific literature. MetaCyc contains >2100 pathways derived from >37 000 publications, and is the largest curated collection of metabolic pathways currently available. BioCyc (BioCyc.org) is a collection of >3000 organism-specific Pathway/Genome Databases (PGDBs), each containing the full genome and predicted metabolic network of one organism, including metabolites, enzymes, reactions, metabolic pathways, predicted operons, transport systems and pathway-hole fillers. Additions to BioCyc over the past 2 years include YeastCyc, a PGDB for Saccharomyces cerevisiae, and 891 new genomes from the Human Microbiome Project. The BioCyc Web site offers a variety of tools for querying and analysis of PGDBs, including Omics Viewers and tools for comparative analysis. New developments include atom mappings in reactions, a new representation of glycan degradation pathways, improved compound structure display, better coverage of enzyme kinetic data, enhancements of the Web Groups functionality, improvements to the Omics viewers, a new representation of the Enzyme Commission system and, for the desktop version of the software, the ability to save display states.

Data mining in the MetaCyc family of pathway databases.

Pathway databases collect the bioreactions and molecular interactions that define the processes of life. The MetaCyc family of pathway databases consists of thousands of databases that were derived through computational inference of metabolic pathways from the MetaCyc pathway/genome database (PGDB). In some cases, these DBs underwent subsequent manual curation. Curated pathway DBs are now available for most of the major model organisms. Databases in the MetaCyc family are managed using the Pathway Tools software. This chapter presents methods for performing data mining on the MetaCyc family of pathway DBs. We discuss the major data access mechanisms for the family, which include data files in multiple formats; application programming interfaces (APIs) for the Lisp, Java, and Perl languages; and web services. We present an overview of the Pathway Tools schema, an understanding of which is needed to query the DBs. The chapter also presents several interactive data mining tools within Pathway Tools for performing omics data analysis.

Enhancing a Pathway-Genome Database (PGDB) to capture subcellular localization of metabolites and enzymes: the nucleotide-sugar biosynthetic pathways of Populus trichocarpa

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.

The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

The MetaCyc database (http://metacyc.org/) provides 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. MetaCyc contains more than 1800 pathways derived from more than 30 000 publications, and is the largest curated collection of metabolic pathways currently available. Most reactions in MetaCyc pathways are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes and literature citations. BioCyc (http://biocyc.org/) is a collection of more than 1700 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 database, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs contain additional features, including predicted operons, transport systems and pathway-hole fillers. The BioCyc website and Pathway Tools software offer many tools for querying and analysis of PGDBs, including Omics Viewers and comparative analysis. New developments include a zoomable web interface for diagrams; flux-balance analysis model generation from PGDBs; web services; and a new tool called Web Groups.

닭 특이 대사 경로 재확립

닭의 대사 생리에 대한 연구는 산업적 가치 및 생물학, 의학적으로도 매우 중요하다. 닭의 유전체 염기서열 분석 결과는 2004년에 처음 발표되었고, 이러한 유전체 정보를 바탕으로 유전형과 표현형의 상관관계를 분석하는 연구가 필요하다. 따라서 본 연구는 닭 유전체 정보를 바탕으로 대사 경로를 재확립하고, 닭 특이 대사 경로 유전체 데이터베이스를 구축하였다. 이를 위해 Perl 언어를 기반으로 개발된 자동 파이프라인(pipeline)을 이용하여 여러 생물정보 데이터베이스에 산재해 있는 닭 유전체에 관한 정보를 통합한 닭 특이 통합 데이터베이스를 구축하였다. 또한, 구축된 닭 특이 통합 데이터베이스를기반으로PathoLogic 알고리즘을구현한Pathway Tools 소프트웨어를 이용하여 닭 특이 대사 경로를 재확립하였다. 결과적으로, 닭 유전체 Gallus_gallus-2.1에서 2,709개의 효소, 71개의 운반체(transporter)와 1,698개의 효소 반응, 8개의 운반 반응(transport reaction)이 도출되었다. 이를 통해 총 212개의 대사 경로가 재확립되었고, 1,360개의 화합물(compound)이 닭 특이 대사 데이터베이스에 포함되었다. 다른 종(사람, 생쥐, 소)과의 비교 분석을 통해 중요한 대사 경로가 닭 유전체에 보존되어 있음을 보였다. 또한, 닭 유전체의 assembly와 annotation의 질을 높이는 노력과 닭 및 조류에서 유전자 기능 및 대사 경로에 대한 연구가 필요한 것으로 나타났다. 결론적으로, 본 연구에서 재확립된 닭의 대사 경로 및 데이터베이스는 닭 및 조류의 대사 연구뿐만 아니라 포유동물 및 미생물과의 비교 생물학적 접근을 통한 의학 및 생물학적 연구에 활용될 것으로 기대된다. Chicken is an important livestock as a valuable biomedical model as well as food for human, and there is a strong rationale for improving our understanding on metabolism and physiology of this organism. The first draft of chicken genome assembly was released in 2004, which enables elaboration on the linkage between genetic and metabolic traits of chicken. The objectives of this study were thus to reconstruct metabolic pathway of the chicken genome and to construct a chicken specific pathway genome database (PGDB). We developed a comprehensive genome database for chicken by integrating all the known annotations for chicken genes and proteins using a pipeline written in Perl. Based on the comprehensive genome annotations, metabolic pathways of the chicken genome were reconstructed using the PathoLogic algorithm in Pathway Tools software. We identified a total of 212 metabolic pathways, 2,709 enzymes, 71 transporters, 1,698 enzymatic reactions, 8 transport reactions, and 1,360 compounds in the current chicken genome build, Gallus_gallus-2.1. Comparative metabolic analysis with the human, mouse and cattle genomes revealed that core metabolic pathways are highly conserved in the chicken genome. It was indicated the quality of assembly and annotations of the chicken genome need to be improved and more researches are required for improving our understanding on function of genes and metabolic pathways of avian species. We conclude that the chicken PGDB is useful for studies on avian and chicken metabolism and provides a platform for comparative genomic and metabolic analysis of animal biology and biomedicine.