Transcription is an essential step in gene expression and its understanding has been one of the major interests in molecular and cellular biology. By

RegulonDB is the primary database of the major international maintained curation of original literature with experimental knowledge about the elements and interactions of the network of transcriptional regulation in Escherichia coli K-12. This includes mechanistic information about operon organization and their decomposition into transcription units (TUs), promoters and their sigma type, binding sites of specific transcriptional regulators (TRs), their organization into 'regulatory phrases', active and inactive conformations of TRs, as well as terminators and ribosome binding sites. The database is complemented with clearly marked computational predictions of TUs, promoters and binding sites of TRs. The current version has been expanded to include information beyond specific mechanisms aimed at gathering different growth conditions and the associated induced and/or repressed genes. RegulonDB is now linked with Swiss-Prot, with microarray databases, and with a suite of programs to analyze and visualize microarray experiments. We provide a summary of the biological knowledge contained in RegulonDB and describe the major changes in the design of the database. RegulonDB can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/regulondb/.

Taking advantage of available functional data associated with 115 transcription and 7 sigma factors, we have performed a structural analysis of the regulatory network of Escherichia coli. While the mode of regulatory interaction between transcription factors (TFs) is predominantly positive, TFs are frequently negatively autoregulated. Furthermore, feedback loops, regulatory motifs and regulatory pathways are unevenly distributed in this network. Short pathways, multiple feed-forward loops and negative autoregulatory interactions are particularly predominant in the subnetwork controlling metabolic functions such as the use of alternative carbon sources. In contrast, long hierarchical cascades and positive autoregulatory loops are overrepresented in the subnetworks controlling developmental processes for biofilm and chemotaxis. We propose that these long transcriptional cascades coupled with regulatory switches (positive loops) for external sensing enable the coexistence of multiple bacterial phenotypes. In contrast, short regulatory pathways and negative autoregulatory loops enable an efficient homeostatic control of crucial metabolites despite external variations. TFs at the core of the network coordinate the most basic endogenous processes by passing information onto multi-element circuits. Transcriptional expression data support broader and higher transcription of global TFs compared to specific ones. Global regulators are also more broadly conserved than specific regulators in bacteria, pointing to varying functional constraints.

Background: Pseudomonas aeruginosa is an important bacterial model due to its metabolic and pathogenic abilities, which allow it to interact and colonize a wide range of hosts, including plants and animals. In this work we compile and analyze the structure and organization of an experimentally supported regulatory network in this bacterium. Results: The regulatory network consists of 690 genes and 1020 regulatory interactions between their products (12% of total genes: 54% sigma and 16% of transcription factors). This complex interplay makes the third largest regulatory network of those reported in bacteria. The entire network is enriched for activating interactions and, peculiarly, self-activation seems to occur more prominent for transcription factors (TFs), which contrasts with other biological networks where self-repression is dominant. The network contains a giant component of 650 genes organized into 11 hierarchies, encompassing important biological processes, such as, biofilms formation, production of exopolysaccharide alginate and several virulence factors, and of the so-called quorum sensing regulons. Conclusions: The study of gene regulation in P. aeruginosa is biased towards pathogenesis and virulence processes, all of which are interconnected. The network shows power-law distribution -input degree -, and we identified the top ten global regulators, six two-element cycles, the longest paths have ten steps, six biological modules and the main motifs containing three and four elements. We think this work can provide insights for the design of further studies to cover the many gaps in knowledge of this important bacterial model, and for the design of systems strategies to combat this bacterium.