Pathway Tools version 23.0 update: software for pathway/genome informatics and systems biology

MOTIVATION

Biological systems function through dynamic interactions among genes and their products, regulatory circuits and metabolic networks. Our development of the Pathway Tools software was motivated by the need to construct biological knowledge resources that combine these many types of data, and that enable users to find and comprehend data of interest as quickly as possible through query and visualization tools. Further, we sought to support the development of metabolic flux models from pathway databases, and to use pathway information to leverage the interpretation of high-throughput data sets.

RESULTS

In the past 4 years we have enhanced the already extensive Pathway Tools software in several respects. It can now support metabolic-model execution through the Web, it provides a more accurate gap filler for metabolic models; it supports development of models for organism communities distributed across a spatial grid; and model results may be visualized graphically. Pathway Tools supports several new omics-data analysis tools including the Omics Dashboard, multi-pathway diagrams called pathway collages, a pathway-covering algorithm for metabolomics data analysis and an algorithm for generating mechanistic explanations of multi-omics data. We have also improved the core pathway/genome databases management capabilities of the software, providing new multi-organism search tools for organism communities, improved graphics rendering, faster performance and re-designed gene and metabolite pages.

AVAILABILITY

The software is free for academic use; a fee is required for commercial use. See http://pathwaytools.com.

CONTACT

pkarp@ai.sri.com.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Briefings in Bioinformatics online.

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 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.

Pathway Tools version 19.0 update: software for pathway/genome informatics and systems biology

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.

Curation accuracy of model organism databases

Manual extraction of information from the biomedical literature-or biocuration-is the central methodology used to construct many biological databases. For example, the UniProt protein database, the EcoCyc Escherichia coli database and the Candida Genome Database (CGD) are all based on biocuration. Biological databases are used extensively by life science researchers, as online encyclopedias, as aids in the interpretation of new experimental data and as golden standards for the development of new bioinformatics algorithms. Although manual curation has been assumed to be highly accurate, we are aware of only one previous study of biocuration accuracy. We assessed the accuracy of EcoCyc and CGD by manually selecting curated assertions within randomly chosen EcoCyc and CGD gene pages and by then validating that the data found in the referenced publications supported those assertions. A database assertion is considered to be in error if that assertion could not be found in the publication cited for that assertion. We identified 10 errors in the 633 facts that we validated across the two databases, for an overall error rate of 1.58%, and individual error rates of 1.82% for CGD and 1.40% for EcoCyc. These data suggest that manual curation of the experimental literature by Ph.D-level scientists is highly accurate. Database URL: http://ecocyc.org/, http://www.candidagenome.org//

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.

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.

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.

Inhibition of human natural cytotoxicity by macromolecular antiproteases

Human natural cell-mediated cytotoxicity is inhibited by macromolecular protease inhibitors. Human plasma alpha 1 antiproteases are more effective than the plant antiproteases lima bean trypsin inhibitor and soybean trypsin inhibitor for reduction of cytotoxicity to the "slow" targets T24 human bladder carcinoma and NKI-1 melanoma. This inhibition of natural cytotoxicity is more readily demonstrable in serum-free medium containing crystalline bovine serum albumin than in medium containing fetal calf serum. Although electrophoretically homogeneous plasma alpha 1 antitrypsin inhibits natural cytotoxicity, partially purified alpha 1 antitrypsin preparations that contain several apha 1 proteins are more inhibitory at equivalent trypsin inhibitory capacities. Partially purified alpha 1 antichymotrypsin with no antitrypsin activity is an extremely potent inhibitor. Thus, it seems likely that several of the plasma antiproteases, including alpha 1 antitrypsin and alpha 1 antichymotrypsin, are capable of influencing natural cytotoxicity. These data indicate that serine-dependent proteases hae a critical role in triggering and/or effecting cell-mediated cytolysis. Furthermore, since alpha 1 antichymotrypsin and alpha 1 antitrypsin are acute phase proteins, the increase in plasma concentration or turnover rates of the proteins could influence natural killer cell activity in vivo.

Inhibition of human natural cytotoxicity by macromolecular antiproteases

Human natural cell-mediated cytotoxicity is inhibited by macromolecular protease inhibitors. Human plasma alpha 1 antiproteases are more effective than the plant antiproteases lima bean trypsin inhibitor and soybean trypsin inhibitor for reduction of cytotoxicity to the "slow" targets T24 human bladder carcinoma and NKI-1 melanoma. This inhibition of natural cytotoxicity is more readily demonstrable in serum-free medium containing crystalline bovine serum albumin than in medium containing fetal calf serum. Although electrophoretically homogeneous plasma alpha 1 antitrypsin inhibits natural cytotoxicity, partially purified alpha 1 antitrypsin preparations that contain several apha 1 proteins are more inhibitory at equivalent trypsin inhibitory capacities. Partially purified alpha 1 antichymotrypsin with no antitrypsin activity is an extremely potent inhibitor. Thus, it seems likely that several of the plasma antiproteases, including alpha 1 antitrypsin and alpha 1 antichymotrypsin, are capable of influencing natural cytotoxicity. These data indicate that serine-dependent proteases hae a critical role in triggering and/or effecting cell-mediated cytolysis. Furthermore, since alpha 1 antichymotrypsin and alpha 1 antitrypsin are acute phase proteins, the increase in plasma concentration or turnover rates of the proteins could influence natural killer cell activity in vivo.