Araceli M. Huerta

RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation

RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database offering curated knowledge of the transcriptional regulatory network of Escherichia coli K12, currently the best-known electronically encoded database of the genetic regulatory network of any free-living organism. This paper summarizes the improvements, new biology and new features available in version 6.0. Curation of original literature is, from now on, up to date for every new release. All the objects are supported by their corresponding evidences, now classified as strong or weak. Transcription factors are classified by origin of their effectors and by gene ontology class. We have now computational predictions for σ54 and five different promoter types of the σ70 family, as well as their corresponding −10 and −35 boxes. In addition to those curated from the literature, we added about 300 experimentally mapped promoters coming from our own high-throughput mapping efforts. RegulonDB v.6.0 now expands beyond transcription initiation, including RNA regulatory elements, specifically riboswitches, attenuators and small RNAs, with their known associated targets. The data can be accessed through overviews of correlations about gene regulation. RegulonDB associated original literature, together with more than 4000 curation notes, can now be searched with the Textpresso text mining engine.

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.

RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more

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.

RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units)

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.

Genome-Wide Identification of Transcription Start Sites, Promoters and Transcription Factor Binding Sites in E. coli

Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5′ RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of σ factors that control the expression of about 80% of these genes. As expected, the housekeeping σ70 was the most common type of promoter, followed by σ38. The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.

REGULONDB : A DATABASE ON TRANSCRIPTIONAL REGULATION IN ESCHERICHIA COLI

RegulonDB is a DataBase that integrates biological knowledge of the mechanisms that regulate the transcription initiation in Escherichia coli , as well as knowledge on the organization of the genes and regulatory signals into operons in the chromosome. The operon is the basic structure used in RegulonDB to describe the elements and properties of transcriptional regulation. The current version contains information around some 500 regulation mechanisms, essentially for sigma 70 promoters.

Prediction of transcriptional regulatory sites in the complete genome sequence of Escherichia coli K-12.

MOTIVATION As one of the best-characterized free-living organisms, Escherichia coli and its recently completed genomic sequence offer a special opportunity to exploit systematically the variety of regulatory data available in the literature in order to make a comprehensive set of regulatory predictions in the whole genome. RESULTS The complete genome sequence of E.coli was analyzed for the binding of transcriptional regulators upstream of coding sequences. The biological information contained in RegulonDB (Huerta, A.M. et al., Nucleic Acids Res.,26,55-60, 1998) for 56 different transcriptional proteins was the support to implement a stringent strategy combining string search and weight matrices. We estimate that our search included representatives of 15-25% of the total number of regulatory binding proteins in E.coli. This search was performed on the set of 4288 putative regulatory regions, each 450 bp long. Within the regions with predicted sites, 89% are regulated by one protein and 81% involve only one site. These numbers are reasonably consistent with the distribution of experimental regulatory sites. Regulatory sites are found in 603 regions corresponding to 16% of operon regions and 10% of intra-operonic regions. Additional evidence gives stronger support to some of these predictions, including the position of the site, biological consistency with the function of the downstream gene, as well as genetic evidence for the regulatory interaction. The predictions described here were incorporated into the map presented in the paper describing the complete E.coli genome (Blattner,F.R. et al., Science, 277, 1453-1461, 1997). AVAILABILITY The complete set of predictions in GenBank format is available at the url: http://www. cifn.unam.mx/Computational_Biology/E.coli-predictions CONTACT ecoli-reg@cifn.unam.mx, collado@cifn.unam.mx

Syntactic recognition of regulatory regions in Escherichia coli

MOTIVATION One of the most common methodologies to identify cis-regulatory sites in regulatory regions in the DNA is that of weight matrices, as testified by several articles in this issue. An alternative to strengthen the computational predictions in regulatory regions is to develop methods that incorporate more biological properties present in such DNA regions. The grammatical implementation presented in this paper provides a concrete example in this direction. RESULTS On the basis of the analysis of an exhaustive collection of regulatory regions in Escherichia coli, a grammatical model for the regulatory regions of sigma 70 promoters has been developed. The terminal symbols of the grammar represent individual sites for the binding of activator and repressor proteins, and include the precise position of sites in relation to transcription initiation. Combining these symbols, the grammar generates a large number of different sentences, each of which can be searched for matching against a collection of regulatory regions by means of weight matrices specific for each set of sites for individual proteins. On the basis of this grammatical model, a Prolog syntactic recognizer is presented here. Specific subgrammars for ArgR, LexA and TyrR were implemented. When parsing a collection of 128 sigma 70 promoter regions, the syntactic recognizer produces a much lower number of false-positive sites than the standard search using weight matrices.

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.

GETools: gene expression tool for analysis of transcriptome experiments in E. coli

Microarray methods provide global evaluation of changes in gene expression that the cell uses to adapt to different conditions. Given the rich legacy of biological knowledge available for Escherichia coli, the analysis of microarray data poses the challenge of comparing them against the knowledge available in the literature and against computational predictions. Here we present Gene Expression Tools (GETools), a computational environment to analyze expression profiles in Escherichia coli K-12, evaluating their congruence with characterized transcription units, upstream regulatory signals and putative transcriptional factors.