The Omics Dashboard for Interactive Exploration of Metabolomics and Multi-Omics Data

The Omics Dashboard is a software tool for interactive exploration and analysis of metabolomics, transcriptomics, proteomics, and multi-omics datasets. Organized as a hierarchy of cellular systems, the Dashboard at its highest level contains graphical panels for the full range of cellular systems, including biosynthesis, energy metabolism, and response to stimulus. Thus, the Dashboard top level surveys the state of the cell across a broad range of key systems in a single screen. Each Dashboard panel contains a series of X-Y plots depicting the aggregated omics data values relevant to different subsystems of that panel, e.g., subsystems within the biosynthesis panel include amino acid biosynthesis, carbohydrate biosynthesis and cofactor biosynthesis. Users can interactively drill down to focus in on successively lower-level subsystems of interest. In this article, we present for the first time the metabolomics analysis capabilities of the Omics Dashboard, along with significant new extensions to better accommodate metabolomics datasets, enable analysis and visualization of multi-omics datasets, and provide new data-filtering options.

The EcoCyc Database (2023)

EcoCyc is a bioinformatics database available online at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on the regulation of gene expression, E. coli gene essentiality, and nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for the analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed online. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. Data generated from a whole-cell model that is parameterized from the latest data on EcoCyc are also available. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function

Animals colonized with a defined microbiota represent useful experimental systems to investigate microbiome function. The altered Schaedler flora (ASF) represents a consortium of eight murine bacterial species that have been used for more than 4 decades where the study of mice with a reduced microbiota is desired. In contrast to germ-free mice, or mice colonized with only one or two species, ASF mice show the normal gut structure and immune system development. To further expand the utility of the ASF, we have developed technical and bioinformatic resources to enable a systems-based analysis of microbiome function using this model. Here, we highlighted four distinct applications of these resources that enable and improve (i) measurements of the abundance of each ASF member by quantitative PCR; (ii) exploration and comparative analysis of ASF genomes and the metabolic pathways they encode that comprise the entire gut microbiome; (iii) global transcriptional profiling to identify genes whose expression responds to environmental changes within the gut; and (iv) discovery of genetic changes resulting from the evolutionary adaptation of the microbiota. These resources were designed to be accessible to a broad community of researchers that, in combination with conventionally-reared mice (i.e., with complex microbiome), should contribute to our understanding of microbiome structure and function. IMPORTANCE Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology. The altered Schaedler flora (ASF) consortium is a well-established defined microbiota model, where mice are stably colonized with 8 distinct murine bacterial species. To take better advantage of the ASF, we established new experimental and bioinformatics resources for researchers to make better use of this model as an experimental system to study microbiome function.

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.

Plant Metabolic Network 15: A resource of genome-wide metabolism databases for 126 plants and algae

To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org). Of these, 104 have not been reported before. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell type-specific metabolic pathways. This work shows the quality and quantity of our resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology.

The EcoCyc Database in 2021

The EcoCyc model-organism database collects and summarizes experimental data for Escherichia coli K-12. EcoCyc is regularly updated by the manual curation of individual database entries, such as genes, proteins, and metabolic pathways, and by the programmatic addition of results from select high-throughput analyses. Updates to the Pathway Tools software that supports EcoCyc and to the web interface that enables user access have continuously improved its usability and expanded its functionality. This article highlights recent improvements to the curated data in the areas of metabolism, transport, DNA repair, and regulation of gene expression. New and revised data analysis and visualization tools include an interactive metabolic network explorer, a circular genome viewer, and various improvements to the speed and usability of existing tools.

The BioCyc Metabolic Network Explorer

Background

The Metabolic Network Explorer is a new addition to the BioCyc.org website and the Pathway Tools software suite that supports the interactive exploration of metabolic networks. Any metabolic network visualization tool must by necessity show only a subset of all possible metabolite connections, or the results will be visually overwhelming. Existing tools, even those that purport to show an organism’s full metabolic network, limit the set of displayed connections based on predefined pathways or other preselected criteria. We sought instead to provide a tool that would give the user dynamic control over which connections to follow.

Results

The Metabolic Network Explorer is an easy-to-use, web-based software tool that allows the user to specify a starting metabolite of interest and interactively explore its immediate metabolic neighborhood in either or both directions to any desired depth, letting the user select from the full set of connected reactions. Although, as for other tools, only a small portion of the metabolic network is visible at a time, that portion is selected by the user, based on the full reaction complement, and it is easy to switch among alternate paths of interest. The display is intuitive, customizable, and provides copious links to more detailed information pages.

Conclusions

The Metabolic Network Explorer fills a gap in the set of metabolic network visualization tools and complements other modes of exploration. Its primary strengths are its ease of use, diagrams that are intuitive to biologists, and its integration with the broader corpus of data provided by a BioCyc Pathway/Genome Database.

Leveraging Curation Among Escherichia coli Pathway/Genome Databases Using Ortholog-Based Annotation Propagation

Updating genome databases to reflect newly published molecular findings for an organism was hard enough when only a single strain of a given organism had been sequenced. With multiple sequenced strains now available for many organisms, the challenge has grown significantly because of the still-limited resources available for the manual curation that corrects errors and captures new knowledge. We have developed a method to automatically propagate multiple types of curated knowledge from genes and proteins in one genome database to their orthologs in uncurated databases for related strains, imposing several quality-control filters to reduce the chances of introducing errors. We have applied this method to propagate information from the highly curated EcoCyc database for Escherichia coli K-12 to databases for 480 other Escherichia coli strains in the BioCyc database collection. The increase in value and utility of the target databases after propagation is considerable. Target databases received updates for an average of 2,535 proteins each. In addition to widespread addition and regularization of gene and protein names, 97% of the target databases were improved by the addition of at least 200 new protein complexes, at least 800 new or updated reaction assignments, and at least 2,400 sets of GO annotations.

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.

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.

The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database

Background

High-throughput experiments can bring to light associations between genes, proteins and/or metabolites, many of which will be explainable by existing knowledge. Our aim is to speed elucidation of such explanations and, in some cases, find explanations that scientists might otherwise overlook.

Results

We describe the MultiOmics Explainer, a new tool within the Pathway Tools software suite that leverages what is known about an organism’s metabolic and regulatory network to suggest explanations for the results of omics experiments. Querying a database such as EcoCyc, the MultiOmics Explainer searches the organism’s network of metabolic reactions, transporters, cofactors, enzyme substrate-level activation and inhibition relationships, and transcriptional and translational regulation relationships to identify paths of influence among input genes, proteins and metabolites. Results are presented in a combined metabolic and regulatory diagram. We present several examples of explanations generated for associations found in the Escherichia coli literature.

Conclusions

The MultiOmics Explainer is a valuable tool that helps researchers understand and interpret the results of their omics experiments in the context of what is known about an organism’s metabolic and regulatory network. It showcases the rich set of computational inferences that can be drawn from a database such as EcoCyc that encodes a diverse range of biological interactions.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2971-6) contains supplementary material, which is available to authorized users.

A Comparison of Microbial Genome Web Portals

Microbial genome web portals have a broad range of capabilities that address a number of information-finding and analysis needs for scientists. This article compares the capabilities of the major microbial genome web portals to aid researchers in determining which portal(s) are best suited to their needs. We assessed both the bioinformatics tools and the data content of BioCyc, KEGG, Ensembl Bacteria, KBase, IMG, and PATRIC. For each portal, our assessment compared and tallied the available capabilities. The strengths of BioCyc include its genomic and metabolic tools, multi-search capabilities, table-based analysis tools, regulatory network tools and data, omics data analysis tools, breadth of data content, and large amount of curated data. The strengths of KEGG include its genomic and metabolic tools. The strengths of Ensembl Bacteria include its genomic tools and large number of genomes. The strengths of KBase include its genomic tools and metabolic models. The strengths of IMG include its genomic tools, multi-search capabilities, large number of genomes, table-based analysis tools, and breadth of data content. The strengths of PATRIC include its large number of genomes, table-based analysis tools, metabolic models, and breadth of data content.

The EcoCyc Database

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed via EcoCyc.org. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

The Omics Dashboard for interactive exploration of gene-expression data

The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X–Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli.

Update notifications for the BioCyc collection of databases

We describe the BioCyc update notifications service, a new mechanism to keep researchers informed of the latest developments in their areas of interest. BioCyc.org combines databases for 9,300 sequenced organisms that integrate genome, metabolic pathway, and regulatory information with extensive bioinformatics tools. Users of the BioCyc website can register their specific areas of interest online by specifying a set of genes, pathways and/or Gene Ontology terms. Then, when significant new information becomes available in a BioCyc database in a user’s interest areas (usually due to curation), an email notification is sent to the user. The BioCyc ontology is leveraged to identify changes that are both relevant to a user’s specified interests and worthy of notification. Every effort is made to ensure that the resulting email text is both concise and informative, with links to relevant BioCyc pages.

Database URL:https://BioCyc.org, https://EcoCyc.org, https://MetaCyc.org

Pathway collages: personalized multi-pathway diagrams

Background

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?

Results

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.

Conclusions

Pathway collages enable facile construction of personalized multi-pathway diagrams.

The EcoCyc database: reflecting new knowledge about Escherichia coli K-12

EcoCyc (EcoCyc.org) is a freely accessible, comprehensive database that collects and summarizes experimental data for Escherichia coli K-12, the best-studied bacterial model organism. New experimental discoveries about gene products, their function and regulation, new metabolic pathways, enzymes and cofactors are regularly added to EcoCyc. New SmartTable tools allow users to browse collections of related EcoCyc content. SmartTables can also serve as repositories for user- or curator-generated lists. EcoCyc now supports running and modifying E. coli metabolic models directly on the EcoCyc website.

Representation and inference of cellular architecture for metabolic reconstruction and modeling

MOTIVATION

Metabolic modeling depends on accurately representing the cellular locations of enzyme-catalyzed and transport reactions. We sought to develop a representation of cellular compartmentation that would accurately capture cellular location information. We further sought a representation that would support automated inference of the cellular compartments present in newly sequenced organisms to speed model development, and that would enable representing the cellular compartments present in multiple cell types within a multicellular organism.

RESULTS

We define the cellular architecture of a unicellular organism, or of a cell type from a multicellular organism, as the collection of cellular components it contains plus the topological relationships among those components. We developed a tool for inferring cellular architectures across many domains of life and extended our Cell Component Ontology to enable representation of the inferred architectures. We provide software for visualizing cellular architectures to verify their correctness and software for editing cellular architectures to modify or correct them. We also developed a representation that records the cellular compartment assignments of reactions with minimal duplication of information.

AVAILABILITY AND IMPLEMENTATION

The Cell Component Ontology is freely available. The Pathway Tools software is freely available for academic research and is available for a fee for commercial use.

CONTACT

pkarp@ai.sri.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Computational Metabolomics Operations at BioCyc.org

BioCyc.org is a genome and metabolic pathway web portal covering 5500 organisms, including Homo sapiens, Arabidopsis thaliana, Saccharomyces cerevisiae and Escherichia coli. These organism-specific databases have undergone variable degrees of curation. The EcoCyc (Escherichia coli Encyclopedia) database is the most highly curated; its contents have been derived from 27,000 publications. The MetaCyc (Metabolic Encyclopedia) database within BioCyc is a "universal" metabolic database that describes pathways, reactions, enzymes and metabolites from all domains of life. Metabolic pathways provide an organizing framework for analyzing metabolomics data, and the BioCyc website provides computational operations for metabolomics data that include metabolite search and translation of metabolite identifiers across multiple metabolite databases. The site allows researchers to store and manipulate metabolite lists using a facility called SmartTables, which supports metabolite enrichment analysis. That analysis operation identifies metabolite sets that are statistically over-represented for the substrates of specific metabolic pathways. BioCyc also enables visualization of metabolomics data on individual pathway diagrams and on the organism-specific metabolic map diagrams that are available for every BioCyc organism. Most of these operations are available both interactively and as programmatic web services.

The EcoCyc Database

EcoCyc is a bioinformatics database available at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene, metabolite, reaction, operon, and metabolic pathway. The database also includes information on E. coli gene essentiality and on nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. This review provides a detailed description of the data content of EcoCyc and of the procedures by which this content is generated.

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.

EcoCyc: fusing model organism databases with systems biology

EcoCyc (http://EcoCyc.org) is a model organism database built on the genome sequence of Escherichia coli K-12 MG1655. Expert manual curation of the functions of individual E. coli gene products in EcoCyc has been based on information found in the experimental literature for E. coli K-12-derived strains. Updates to EcoCyc content continue to improve the comprehensive picture of E. coli biology. The utility of EcoCyc is enhanced by new tools available on the EcoCyc web site, and the development of EcoCyc as a teaching tool is increasing the impact of the knowledge collected in EcoCyc.

Browsing metabolic and regulatory networks with BioCyc

The BioCyc database collection at BioCyc.org integrates genome and cellular network information for more than 1,100 organisms. This method chapter describes Web-based tools for browsing metabolic and regulatory networks within BioCyc. These tools allow visualization of complete metabolic and regulatory networks, and allow the user to zoom-in on regions of the network of interest. The user can find objects of interest such as genes and metabolites within the networks, and can selectively examine the connectivity of the network. The EcoCyc database within the BioCyc collection has been extensively curated. The descriptions within EcoCyc of the Escherichia coli metabolic network and regulatory network were derived from thousands of publications. Other BioCyc databases received moderate levels of curation, or no curation at all. Those databases receiving no curation contain metabolic networks that were computationally inferred from the annotated genome sequences of each organism.

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.

EcoCyc: a comprehensive database of Escherichia coli biology

EcoCyc (http://EcoCyc.org) is a comprehensive model organism database for Escherichia coli K-12 MG1655. From the scientific literature, EcoCyc captures the functions of individual E. coli gene products; their regulation at the transcriptional, post-transcriptional and protein level; and their organization into operons, complexes and pathways. EcoCyc users can search and browse the information in multiple ways. Recent improvements to the EcoCyc Web interface include combined gene/protein pages and a Regulation Summary Diagram displaying a graphical overview of all known regulatory inputs to gene expression and protein activity. The graphical representation of signal transduction pathways has been updated, and the cellular and regulatory overviews were enhanced with new functionality. A specialized undergraduate teaching resource using EcoCyc is being developed.

The BioPAX community standard for pathway data sharing

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.

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 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.

EcoCyc: a comprehensive view of Escherichia coli biology

EcoCyc (http://EcoCyc.org) provides a comprehensive encyclopedia of Escherichia coli biology. EcoCyc integrates information about the genome, genes and gene products; the metabolic network; and the regulatory network of E. coli. Recent EcoCyc developments include a new initiative to represent and curate all types of E. coli regulatory processes such as attenuation and regulation by small RNAs. EcoCyc has started to curate Gene Ontology (GO) terms for E. coli and has made a dataset of E. coli GO terms available through the GO Web site. The curation and visualization of electron transfer processes has been significantly improved. Other software and Web site enhancements include the addition of tracks to the EcoCyc genome browser, in particular a type of track designed for the display of ChIP-chip datasets, and the development of a comparative genome browser. A new Genome Omics Viewer enables users to paint omics datasets onto the full E. coli genome for analysis. A new advanced query page guides users in interactively constructing complex database queries against EcoCyc. A Macintosh version of EcoCyc is now available. A series of Webinars is available to instruct users in the use of EcoCyc.

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

MetaCyc (MetaCyc.org) is a universal database of metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are curated from the primary scientific literature, and are experimentally determined small-molecule metabolic pathways. Each reaction in a MetaCyc pathway is annotated with one or more well-characterized enzymes. Because MetaCyc contains only experimentally elucidated knowledge, it provides a uniquely high-quality resource for metabolic pathways and enzymes. BioCyc (BioCyc.org) is a collection of more than 350 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the predicted metabolic network of one organism, including metabolic pathways, enzymes, metabolites and reactions predicted by the Pathway Tools software using MetaCyc as a reference database. BioCyc PGDBs also contain predicted operons and predicted pathway hole fillers—predictions of which enzymes may catalyze pathway reactions that have not been assigned to an enzyme. The BioCyc website offers many tools for computational analysis of PGDBs, including comparative analysis and analysis of omics data in a pathway context. The BioCyc PGDBs generated by SRI are offered for adoption by any interested party for the ongoing integration of metabolic and genome-related information about an organism.

MetaCyc: a multiorganism database of metabolic pathways and enzymes

MetaCyc is a database of metabolic pathways and enzymes located at http://MetaCyc.org/. Its goal is to serve as a metabolic encyclopedia, containing a collection of non-redundant pathways central to small molecule metabolism, which have been reported in the experimental literature. Most of the pathways in MetaCyc occur in microorganisms and plants, although animal pathways are also represented. MetaCyc contains metabolic pathways, enzymatic reactions, enzymes, chemical compounds, genes and review-level comments. Enzyme information includes substrate specificity, kinetic properties, activators, inhibitors, cofactor requirements and links to sequence and structure databases. Data are curated from the primary literature by curators with expertise in biochemistry and molecular biology. MetaCyc serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. Querying, visualization and curation of the database is supported by SRI's Pathway Tools software. The PathoLogic component of Pathway Tools is used in conjunction with MetaCyc to predict the metabolic network of an organism from its annotated genome. SRI and the European Bioinformatics Institute employed this tool to create pathway/genome databases (PGDBs) for 165 organisms, available at the BioCyc.org website. These PGDBs also include predicted operons and pathway hole fillers.

Querying and computing with BioCyc databases

We describe multiple methods for accessing and querying the complex and integrated cellular data in the BioCyc family of databases: access through multiple file formats, access through Application Program Interfaces (APIs) for LISP, Perl and Java, and SQL access through the BioWarehouse relational database.

MetaCyc and AraCyc. Metabolic pathway databases for plant research

MetaCyc (http://metacyc.org) contains experimentally determined biochemical pathways to be used as a reference database for metabolism. In conjunction with the Pathway Tools software, MetaCyc can be used to computationally predict the metabolic pathway complement of an annotated genome. To increase the breadth of pathways and enzymes, more than 60 plant-specific pathways have been added or updated in MetaCyc recently. In contrast to MetaCyc, which contains metabolic data for a wide range of organisms, AraCyc is a species-specific database containing only enzymes and pathways found in the model plant Arabidopsis (Arabidopsis thaliana). AraCyc (http://arabidopsis.org/tools/aracyc/) was the first computationally predicted plant metabolism database derived from MetaCyc. Since its initial computational build, AraCyc has been under continued curation to enhance data quality and to increase breadth of pathway coverage. Twenty-eight pathways have been manually curated from the literature recently. Pathway predictions in AraCyc have also been recently updated with the latest functional annotations of Arabidopsis genes that use controlled vocabulary and literature evidence. AraCyc currently features 1,418 unique genes mapped onto 204 pathways with 1,156 literature citations. The Omics Viewer, a user data visualization and analysis tool, allows a list of genes, enzymes, or metabolites with experimental values to be painted on a diagram of the full pathway map of AraCyc. Other recent enhancements to both MetaCyc and AraCyc include implementation of an evidence ontology, which has been used to provide information on data quality, expansion of the secondary metabolism node of the pathway ontology to accommodate curation of secondary metabolic pathways, and enhancement of the cellular component ontology for storing and displaying enzyme and pathway locations within subcellular compartments.

EcoCyc: a comprehensive database resource for Escherichia coli

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.

The Pathway Tools software

MOTIVATION

Bioinformatics requires reusable software tools for creating model-organism databases (MODs).

RESULTS

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.

An evidence ontology for use in pathway/genome databases

An important emerging need in Model Organism Databases (MODs) and other bioinformatics databases (DBs) is that of capturing the scientific evidence that supports the information within a DB. This need has become particularly acute as more DB content consists of computationally predicted information, such as predicted gene functions, operons, metabolic pathways, and protein properties. This paper presents an ontology for encoding the type of support and the degree of support for DB assertions, and for encoding the literature source in which that support is reported. The ontology includes a hierarchy of 35 evidence codes for modeling different types of wet-lab and computational evidence for the existence of operons and metabolic pathways, and for gene functions. We also describe an implementation of the ontology within the Pathway Tools software environment, which is used to query and update Pathway/Genome DBs such as EcoCyc, MetaCyc, and HumanCyc.

MetaCyc: a multiorganism database of metabolic pathways and enzymes

The MetaCyc database (see URL http://MetaCyc.org) is a collection of metabolic pathways and enzymes from a wide variety of organisms, primarily microorganisms and plants. The goal of MetaCyc is to contain a representative sample of each experimentally elucidated pathway, and thereby to catalog the universe of metabolism. MetaCyc also describes reactions, chemical compounds and genes. Many of the pathways and enzymes in MetaCyc contain extensive information, including comments and literature citations. SRI's Pathway Tools software supports querying, visualization and curation of MetaCyc. With its wide breadth and depth of metabolic information, MetaCyc is a valuable resource for a variety of applications. MetaCyc is the reference database of pathways and enzymes that is used in conjunction with SRI's metabolic pathway prediction program to create Pathway/Genome Databases that can be augmented with curation from the scientific literature and published on the world wide web. MetaCyc also serves as a readily accessible comprehensive resource on microbial and plant pathways for genome analysis, basic research, education, metabolic engineering and systems biology. In the past 2 years the data content and the Pathway Tools software used to query, visualize and edit MetaCyc have been expanded significantly. These enhancements are described in this paper.

The Pathway Tools software

MOTIVATION

Bioinformatics requires reusable software tools for creating model-organism databases (MODs).

RESULTS

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.

Database verification studies of SWISS-PROT and GenBank

PROBLEM STATEMENT

We have studied the relationships among SWISS-PROT, TrEMBL, and GenBank with two goals. First is to determine whether users can reliably identify those proteins in SWISS-PROT whose functions were determined experimentally, as opposed to proteins whose functions were predicted computationally. If this information was present in reasonable quantities, it would allow researchers to decrease the propagation of incorrect function predictions during sequence annotation, and to assemble training sets for developing the next generation of sequence-analysis algorithms. Second is to assess the consistency between translated GenBank sequences and sequences in SWISS-PROT and TrEMBL.

RESULTS

(1) Contrary to claims by the SWISS-PROT authors, we conclude that SWISS-PROT does not identify a significant number of experimentally characterized proteins. (2) SWISS-PROT is more incomplete than we expected in that version 38.0 from July 1999 lacks many proteins from the full genomes of important organisms that were sequenced years earlier. (3) Even if we combine SWISS-PROT and TrEMBL, some sequences from the full genomes are missing from the combined dataset. (4) In many cases, translated GenBank genes do not exactly match the corresponding SWISS-PROT sequences, for reasons that include missing or removed methionines, differing translation start positions, individual amino-acid differences, and inclusion of sequence data from multiple sequencing projects. For example, results show that for Escherichia coli, 80.6% of the proteins in the GenBank entry for the complete genome have identical sequence matches with SWISS-PROT/TrEMBL sequences, 13.4% have exact substring matches, and matches for 4.1% can be found using BLAST search; the remaining 2.0% of E.coli protein sequences (most of which are ORFs) have no clear matches to SWISS-PROT/TrEMBL. Although many of these differences can be explained by the complexity of the DB, and by the curation processes used to create it, the scale of the differences is notable.

Integrated pathway-genome databases and their role in drug discovery

Integrated pathway-genome databases describe the genes and genome of an organism, as well as its predicted pathways, reactions, enzymes and metabolites. In conjunction with visualization and analysis software, these databases provide a framework for improved understanding of microbial physiology and for antimicrobial drug discovery. We describe pathway-based analyses of the genomes of a number of medically relevant microorganisms and a novel software tool that visualizes gene-expression data on a diagram showing the whole metabolic network of the microorganism.

Integrated access to metabolic and genomic data

The EcoCyc system consists of a knowledge base (KB) that describes the genes and intermediary metabolism of Escherichia coli, and a graphical user interface (GUI) for accessing that knowledge. This paper addresses two problems: How can we create a GUI that provides integrated access to metabolic and genomic data? We describe the design and implementation of visual presentations that closely mimic those found in the biology literature, and that offer hypertext navigation among related entities, and multiple views of the same entity. We employ a frame knowledge representation system (FRS) called HyperTHEO to manage the EcoCyc knowledge base. Among the advantages of FRSs are an expressive data model for capturing the complexities of biological information, and schema-evolution capabilities that facilitate the constant schema changes that biological databases tend to undergo. HyperTHEO also includes rule-based inference facilities that are the foundation of expert systems, a constraint language for maintaining data integrity, and a declarative query language. A graphic KB editor and browser allow the EcoCyc developers to interactively inspect and modify this evolving KB.