[Show abstract][Hide abstract] ABSTRACT: 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 web site and downloadable software contain tools for analysis of high-throughput datasets. 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 chapter provides a detailed description of the data content of EcoCyc, and of the procedures by which this content is generated.
[Show abstract][Hide abstract] ABSTRACT: RegulonDB provides curated information on the transcriptional regulatory network of Escherichia coli and contains both experimental data and computationally predicted objects. To account for the heterogeneity of these data, we introduced in version 6.0, a two-tier rating system for the strength of evidence, classifying evidence as either ‘weak’ or ‘strong’ (Gama-Castro,S., Jimenez-Jacinto,V., Peralta-Gil,M. et al. RegulonDB (Version 6.0): gene regulation model of Escherichia Coli K-12 beyond transcription, active (experimental) annotated promoters and textpresso navigation. Nucleic Acids Res., 2008;36:D120–D124.). We now add to our classification scheme the classification of high-throughput evidence, including chromatin immunoprecipitation (ChIP) and RNA-seq technologies. To integrate these data into RegulonDB, we present two strategies for the evaluation of confidence, statistical validation and independent cross-validation. Statistical validation involves verification of ChIP data for transcription factor-binding sites, using tools for motif discovery and quality assessment of the discovered matrices. Independent cross-validation combines independent evidence with the intention to mutually exclude false positives. Both statistical validation and cross-validation allow to upgrade subsets of data that are supported by weak evidence to a higher confidence level. Likewise, cross-validation of strong confidence data extends our two-tier rating system to a three-tier system by introducing a third confidence score ‘confirmed’.
Database The Journal of Biological Databases and Curation 01/2013; 2013:bas059. DOI:10.1093/database/bas059 · 3.37 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This article summarizes our progress with RegulonDB (http://regulondb.ccg.unam.mx/) during the past 2 years. We have kept up-to-date the knowledge from the published literature regarding transcriptional regulation in Escherichia coli K-12. We have maintained and expanded our curation efforts to improve the breadth and quality of the encoded experimental knowledge, and we have implemented criteria for the quality of our computational predictions. Regulatory phrases now provide high-level descriptions of regulatory regions. We expanded the assignment of quality to various sources of evidence, particularly for knowledge generated through high-throughput (HT) technology. Based on our analysis of most relevant methods, we defined rules for determining the quality of evidence when multiple independent sources support an entry. With this latest release of RegulonDB, we present a new highly reliable larger collection of transcription start sites, a result of our experimental HT genome-wide efforts. These improvements, together with several novel enhancements (the tracks display, uploading format and curational guidelines), address the challenges of incorporating HT-generated knowledge into RegulonDB. Information on the evolutionary conservation of regulatory elements is also available now. Altogether, RegulonDB version 8.0 is a much better home for integrating knowledge on gene regulation from the sources of information currently available.
[Show abstract][Hide abstract] ABSTRACT: 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.
Nucleic Acids Research 11/2012; 41(D1). DOI:10.1093/nar/gks1027 · 9.11 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Since its inception, RegulonDB ("http://regulondb.ccg.unam.mx/":http://regulondb.ccg.unam.mx/) has been a database that compiles information about the regulation of transcription initiation of _Escherichia coli_ K-12. However, we are aware that transcriptional regulation is not an isolated process; instead, it is the response to the different environmental conditions that trigger a series of concatenated reactions that end in transcriptional regulation, and it implies an adequate response in terms of induced and repressed gene products. We are working now to include all these new data in RegulonDB. As a consequence, transcriptional regulation in RegulonDB will be part of a unit that initiates with the signal, continues with the signal transduction to the core of regulation to modify expression of the affected set of target genes, and ends with an adequate response. We refer to these units as genetic sensory response units, or Gensor Units. The inclusion of Gensor Units will bring a dramatic change and expansion of RegulonDB, due to the fact that we will be adding several new types of reactions and interactions. We started to collect data about signal transduction of the sigma factors, the two-component systems, of some transcription factors involved in carbon source utilization, and of genes involved in the synthesis of amino acids. We plan a high-level curation with super-pathways summarizing concatenated sets of reactions linked to those other databases that curate such information, while enabling with RegulonDB a compilation of complete Gensor Units. In addition, the number of DNA binding sites for some transcription factors has grown considerably, and therefore we decided to review systematically those sites whose lengths ranging from 40 to 60 bp with orientation and consensus sequences that are not easy to identify. The current version of RegulonDB is the beginning of a higher-level curation of gene regulation information, and eventually our database will include all regulatory mechanisms and their regulated genes.
[Show abstract][Hide abstract] ABSTRACT: RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database of the best-known regulatory network of any free-living organism, that of Escherichia coli K-12. The major conceptual change since 3 years ago is an expanded biological context so that transcriptional regulation is now part of a unit that initiates with the signal and continues with the signal transduction to the core of regulation, modifying expression of the affected target genes responsible for the response. We call these genetic sensory response units, or Gensor Units. We have initiated their high-level curation, with graphic maps and superreactions with links to other databases. Additional connectivity uses expandable submaps. RegulonDB has summaries for every transcription factor (TF) and TF-binding sites with internal symmetry. Several DNA-binding motifs and their sizes have been redefined and relocated. In addition to data from the literature, we have incorporated our own information on transcription start sites (TSSs) and transcriptional units (TUs), obtained by using high-throughput whole-genome sequencing technologies. A new portable drawing tool for genomic features is also now available, as well as new ways to download the data, including web services, files for several relational database manager systems and text files including BioPAX format.