Bioinformatics Resources for the Study of Gene Regulation in Bacteria

Genomics, which has been identified as the science of the century, is dramatically changing the historically weak relationship between experimental and theoretical biology. The addition to the Journal of Bacteriology of a section for computational biology marks a turning point in the history of this dialogue. This minireview is focused on the computational biology of gene regulation in bacteria, defined as the extensive use of bioinformatics tools to increase our understanding of the regulation of gene expression. The study of gene regulation has been radically affected by the elucidation of full-genome DNA sequences and the subsequent development of high-throughput methodologies for deciphering their expression. Before the genomics era, most research was focused on individual biological systems. A large number of our colleagues, contributors to this journal, have devoted much of their academic careers to the understanding of individual regulatory units describing operons, regulators, and promoters and their roles in the physiology of the cell. These contributions have provided fundamental information to support the most recent efforts for the integrative knowledge of the cell that all the genomics sciences are achieving. Genomics offers for the microbiologist studying gene regulation the opportunity to understand individual systems in the context of the whole cell. These integrative sciences have also changed the landscape of data available for new discoveries in the evolution of gene regulation. The major challenge of the genomics era is dealing with large amounts of data at all molecular levels and being able to generate integrated biological knowledge from the data. Bioinformatics is essential to progress in this direction, as it provides what is necessary to deal with large amounts of data: databases, algorithms to generate genomic answers to standard questions, overviews, and navigation capabilities, as well as statistical methods to perform and validate analyses. Current knowledge of gene regulation in prokaryotes is quite diverse, from the constantly increasing number of full genome sequences for which very little experimental work has been performed, including the many genomes that cannot yet be grown in the laboratory or the little-studied archaea, to the few highly characterized bacterial genomes, such as those of Bacillus subtilis and Pseudomonas aeruginosa, with Escherichia coli K-12 being by far the best-known bacterium and free-living organism. Figure ​Figure11 shows this strongly unequal distribution of knowledge, with the number of publications on gene regulation, as an example, for the different microbial genomes. FIG. 1. Number of published particles per organism. We searched through PubMed by using a collection of keywords that we regularly use to gather information for RegulonDB across different bacteria. The profile requires the name of the organism to be in the title. ... The first exhaustive historical set of regulated promoters and their associated transcription factors (TFs) and TF DNA-binding sites (TFBSs) gathered around 120 σ70 and σ54 promoters of E. coli K-12 (16, 29). This information and the experience obtained were the seeds for what is now RegulonDB (http://regulondb.ccg.unam.mx/), the original source of expert curated knowledge on the regulation of transcription initiation and operon organization in E. coli K-12. It contains what is currently the major electronically encoded regulatory network for any free-living organism (25). This information is also contained in EcoCyc, the E. coli model organism database, with added curated knowledge on metabolism and transport (http://ecocyc.org/). We estimate that currently around 25% of the interactions of the full cellular regulatory network of transcription initiation have been assembled. RegulonDB should not be conceived of as a database, but as an environment for genomic regulatory investigations, linked to bioinformatics tools that facilitate analyses of upstream regions, together with data sets and tools for microarray analyses and, more recently, direct access to full papers supporting its knowledge. We are not only curating up-to-date original papers, but have also initiated “active annotation,” to use Jean-Michelle Claverie's terminology, to more precisely experimentally map promoters by using a high-throughput strategy. This minireview has been organized taking into account the fact that most of the readers of the Journal of Bacteriology are experimentalists. We start with a few examples of lessons on gene regulation from bioinformatics, focusing on promoters, their definition and regulation, and operon structure. The second section summarizes how RegulonDB has been useful to experimentalists, as well as its role as the “gold standard” for implementing bioinformatics predictive methods, topological analyses of the network, and models of the cell. The last section offers a compendium of links to bioinformatics resources on gene regulation in bacteria, illustrating their usage with flowcharts associated with questions on the regulation of gene expression that are entailed in the use of RegulonDB and associated bioinformatics resources. We illustrate the very efficient text analysis obtained using Textpresso to access more than 2,400 full papers that support the E. coli regulatory network. A cautionary note: the examples of the three sections are biased toward cases in E. coli and its RegulonDB regulatory database. This bias is natural, since first of all, our direct experience is with RegulonDB, and second, especially for bacterial-gene regulation (Fig. ​(Fig.1),1), we may well quote Fred Neidhardt (87): “Not everyone is mindful of it, but all cell biologists have two organisms of interest: the one they are studying and Escherichia coli!”