Tracing the phylogenetic history of the Crl regulon through the Bacteria and Archaea genomes.

BACKGROUND: Crl, identified for curli production, is a small transcription factor that stimulates the association of the σS factor (RpoS) with the RNA polymerase core through direct and specific interactions, increasing the transcription rate of genes during the transition from exponential to stationary phase at low temperatures, using indole as an effector molecule. The lack of a comprehensive collection of information on the Crl regulon makes it difficult to identify a dominant function of Crl and to generate any hypotheses concerning its taxonomical distribution in archaeal and bacterial organisms. RESULTS: In this work, based on a systematic literature review, we identified the first comprehensive dataset of 86 genes under the control of Crl in the bacterium Escherichia coli K-12; those genes correspond to 40% of the σS regulon in this bacterium. Based on an analysis of orthologs in 18 archaeal and 69 bacterial taxonomical divisions and using E. coli K-12 as a framework, we suggest three main events that resulted in this regulon's actual form: (i) in a first step, rpoS, a gene widely distributed in bacteria and archaea cellular domains, was recruited to regulate genes involved in ancient metabolic processes, such as those associated with glycolysis and the tricarboxylic acid cycle; (ii) in a second step, the regulon recruited those genes involved in metabolic processes, which are mainly taxonomically constrained to Proteobacteria, with some secondary losses, such as those genes involved in responses to stress or starvation and cell adhesion, among others; and (iii) in a posterior step, Crl might have been recruited in Enterobacteriaceae; because its taxonomical pattern constrained to this bacterial order, however further analysis are necessary. CONCLUSIONS: Therefore, we suggest that the regulon Crl is highly flexible for phenotypic adaptation, probably as consequence of the diverse growth environments associated with all organisms in which members of this regulatory network are present.

MCO: towards an ontology and unified vocabulary for a framework-based annotation of microbial growth conditions.

MOTIVATION: A major component in increasing our understanding of the biology of an organism is the mapping of its genotypic potential into its phenotypic expression profiles. This mapping is executed by the machinery of gene regulation, which is essentially studied by changes in growth conditions. Although many efforts have been made to systematize the annotation of experimental conditions in microbiology, the available annotations are not based on a consistent and controlled vocabulary, making difficult the identification of biologically meaningful comparisons of knowledge derived from different experiments or laboratories. RESULTS: We curated terms related to experimental conditions that affect gene expression in Escherichia coli K-12. Since this is the best-studied microorganism, the collected terms are the seed for the Microbial Conditions Ontology (MCO), a controlled and structured vocabulary that can be expanded to annotate microbial conditions in general. Moreover, we developed an annotation framework to describe experimental conditions, providing the foundation to identify regulatory networks that operate under particular conditions. AVAILABILITY AND IMPLEMENTATION: As far as we know, MCO is the first ontology for growth conditions of any bacterial organism, and it is available at http://regulondb.ccg.unam.mx and https://github.com/microbial-conditions-ontology. Furthermore, we will disseminate MCO throughout the Open Biological and Biomedical Ontology (OBO) Foundry in order to set a standard for the annotation of gene expression data. This will enable comparison of data from diverse data sources. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Impact of Transcription Units rearrangement on the evolution of the regulatory network of gamma-proteobacteria

In the past years, several studies begun to unravel the structure, dynamical properties, and evolution of transcriptional regulatory networks. However, even those comparative studies that focus on a group of closely related organisms are limited by the rather scarce knowledge on regulatory interactions outside a few model organisms, such as E. coli among the prokaryotes. Results: In this paper we used the information annotated in Tractor_DB (a database of regulatory networks in gamma-proteobacteria) to calculate a normalized Site Orthology Score (SOS) that quantifies the conservation of a regulatory link across thirty genomes of this subclass. Then we used this SOS to assess how regulatory connections have evolved in this group, and how the variation of basic regulatory connection is reflected on the structure of the chromosome. We found that individual regulatory interactions shift between different organisms, a process that may be described as rewiring the network. At this evolutionary scale (the gamma-proteobacteria subclass) this rewiring process may be an important source of variation of regulatory incoming interactions for individual networks. We also noticed that the regulatory links that form feed forward motifs are conserved in a better correlated manner than triads of random regulatory interactions or pairs of co-regulated genes. Furthermore, the rewiring process that takes place at the most basic level of the regulatory network may be linked to rearrangements of genetic material within bacterial chromosomes, which change the structure of Transcription Units and therefore the regulatory connections between Transcription Factors and structural genes. Conclusion: The rearrangements that occur in bacterial chromosomes-mostly inversion or horizontal gene transfer events are important sources of variation of gene regulation at this evolutionary scale(AU)

En los últimos años, varios estudios han comenzado a desentrañar la estructura, la dinámica de las propiedades, y la evolución de las redes de regulación transcripcional. Sin embargo, incluso los estudios comparativos que se centran en un grupo de organismos estrechamente relacionados son limitados por la escasez de conocimientos en lugar de reglamentación sobre las interacciones fuera de unos pocos organismos modelo, como la E. coli entre los procariotas. Resultados En este trabajo se utilizó la información anotada en Tractor_DB (una base de datos de redes reguladoras en gamma proteobacteria) para calcular un sitio normalizado Orthology Puntuación (SOS) que cuantifica la conservación de un vínculo de reglamentación a través de treinta genomas de esta subclase. A continuación, hemos utilizado este SOS para evaluar cómo han evolucionado las conexiones de reglamentación en este grupo, y cómo la variación de la relación básica de regulación se refleja en la estructura del cromosoma. Se encontró que cada cambio de reglamentación interacciones entre los diferentes organismos, proceso que puede describirse como el cableado de la red. En esta escala evolutiva (la gamma-proteobacteria subclase) este proceso de cableado pueden ser una importante fuente de variación de la reglamentación de las interacciones individuales redes. Hemos observado también que la reglamentación que forman enlaces de alimentación hacia adelante motivos se conservan en una mejor correlación de las tríadas de manera aleatoria o reglamentario interacciones de pares de genes co-regulados. Además, el proceso de cableado que se lleva a cabo en el nivel más básico de regulación de la red pueden estar relacionados con reordenamientos del material genético de bacterias dentro de los cromosomas, que cambiar la estructura de las unidades de transcripción y, por tanto, el marco regulador conexiones entre factores de transcripción y genes estructurales......

Structure and evolution of gene regulatory networks in microbial genomes.

With the availability of genome sequences for hundreds of microbial genomes, it has become possible to address several questions from a comparative perspective to understand the structure and function of regulatory systems, at least in model organisms. Recent studies have focused on topological properties and the evolution of regulatory networks and their components. Our understanding of natural networks is paving the way to embedding synthetic regulatory systems into organisms, allowing us to expand the natural diversity of living systems to an extent we had never before anticipated.

Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors.

Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B. C. Goodwin, (Academic, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comput. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein and metabolite concentrations. Further, we present results for a three gene case in coregulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological system.

TRACTOR_DB: a database of regulatory networks in gamma-proteobacterial genomes

Experimental data on the Escherichia coli transcriptional regulatory system has been used in the past years to predict new regulatory elements (promoters, transcription factors (TFs), TFs' binding sites and operons) within its genome. As more genomes of gamma-proteobacteria are being sequenced, the prediction of these elements in a growing number of organisms has become more feasible, as a step towards the study of how different bacteria respond to environmental changes at the level of transcriptional regulation. In this work, we present TRACTOR_DB (TRAnscription FaCTORs' predicted binding sites in prokaryotic genomes), a relational database that contains computational predictions of new members of 74 regulons in 17 gamma-proteobacterial genomes. For these predictions we used a comparative genomics approach regarding which several proof-of-principle articles for large regulons have been published. TRACTOR_DB may be currently accessed at http://www.bioinfo.cu/Tractor_DB, http://www.tractor.lncc.br/ or at http://www.cifn.unam.mx/Computational_Genomics/tractorDB. Contact Email id is tractor@cifn.unam.mx(AU)

Common history at the origin of the position-function correlation in transcriptional regulators in archaea and bacteria.

Regulatory proteins in Escherichia coli with a helix-turn-helix (HTH) DNA binding motif show a position-function correlation such that repressors have this motif predominantly at the N terminus, whereas activators have the motif at the C-terminus extreme. Using this initial collection we identified by sequence comparison the exhaustive set of transcriptional regulators in 17 bacterial and 6 archaeal genomes. This enlarged set shows the same position-function correlation. The main question we address is whether this correlation is the result of common origin in evolution or the result of convergence. Evidence is presented supporting a common history at the origin of this correlation. We show the existence of a supergroup of eight repressor protein families sharing a conserved extended sequence comprising the classic HTH. Two of these repressor families (MarR and AsnC) originated before the divergence of Archaea and Bacteria. They are proposed at the origin of HTH-bearing transcriptional regulators currently present in Bacteria. The group of LysR proteins, with the HTH also at the N terminus, offers a control to the argument, since it shows clearly distinctive structural, functional, and evolutionary properties. This group of activator proteins, suggested to have originated within the Bacteria, has an advantageous gene organization to facilitate its horizontal transfer-used to conquer some Archaea-as well as negative autoregulation convenient for homeostasis, all of which agrees with this being the largest family in Bacteria. These results suggest that if shuffling of motifs occurred in Bacteria, it occurred only early in the history of these proteins, as opposed to what is observed in eukaryotic regulators.

A comparative genomics approach to prediction of new members of regulons.

Identifying the complete transcriptional regulatory network for an organism is a major challenge. For each regulatory protein, we want to know all the genes it regulates, that is, its regulon. Examples of known binding sites can be used to estimate the binding specificity of the protein and to predict other binding sites. However, binding site predictions can be unreliable because determining the true specificity of the protein is difficult because of the considerable variability of binding sites. Because regulatory systems tend to be conserved through evolution, we can use comparisons between species to increase the reliability of binding site predictions. In this article, an approach is presented to evaluate the computational predictions of regulatory sites. We combine the prediction of transcription units having orthologous genes with the prediction of transcription factor binding sites based on probabilistic models. We augment the sets of genes in Escherichia coli that are expected to be regulated by two transcription factors, the cAMP receptor protein and the fumarate and nitrate reduction regulatory protein, through a comparison with the Haemophilus influenzae genome. At the same time, we learned more about the regulatory networks of H. influenzae, a species with much less experimental knowledge than E. coli. By studying orthologous genes subject to regulation by the same transcription factor, we also gained understanding of the evolution of the entire regulatory systems.

Transcription unit conservation in the three domains of life: a perspective from Escherichia coli.

Here we address the question of the degree to which genes within experimentally characterized operons in one organism (Escherichia coli) are conserved in other genomes. We found that two genes adjacent within an operon are more likely both to have an ortholog in other organisms, regardless of relative position, than genes adjacent on the same strand but in two different transcription units. They are also more likely to occur next to, or fused to, one another in other genomes. Genes frequently conserved adjacent to each other, especially among evolutionarily distant species, must be part of the same transcription unit in most of them.

Conserved regulatory elements of the promoter sequence of the gene rpoH of enteric bacteria.

The rpoH regulatory region of different members of the enteric bacteria family was sequenced or downloaded from GenBank and compared. In addition, the transcriptional start sites of rpoH of Yersinia frederiksenii and Proteus mirabilis, two distant members of this family, were determined. Sequences similar to the sigma(70) promoters P1, P4 and P5, to the sigma(E) promoter P3 and to boxes DnaA1, DnaA2, cAMP receptor protein (CRP) boxes CRP1, CRP2 and box CytR present in Escherichia coli K12, were identified in sequences of closely related bacteria such as: E.coli, Shigella flexneri, Salmonella enterica serovar Typhimurium, Citrobacter freundii, Enterobacter cloacae and Klebsiella pneumoniae. In more distant bacteria, Y.frederiksenii and P.mirabilis, the rpoH regulatory region has a distal P1-like sigma(70) promoter and two proximal promoters: a heat-induced sigma(E)-like promoter and a sigma(70) promoter. Sequences similar to the regulatory boxes were not identified in these bacteria. This study suggests that the general pattern of transcription of the rpoH gene in enteric bacteria includes a distal sigma(70) promoter, >200 nt upstream of the initiation codon, and two proximal promoters: a heat-induced sigma(E)-like promoter and a sigma(70) promoter. A second proximal sigma(70) promoter under catabolite-regulation is probably present only in bacteria closely related to E.coli.

RegulonDB (version 3.2): transcriptional regulation and operon organization in Escherichia coli K-12.

RegulonDB is a database on mechanisms of transcription regulation and operon organization in Escherichia coli K-12. The current version has considerably increased numbers of regulatory elements such as promoters, binding sites and terminators. The complete repertoire of known and predicted DNA-binding transcriptional regulators can be considered to be included in this version. The database now distinguishes different allosteric conformations of regulatory proteins indicating the one active in binding and regulating the different promoters. A new set of operon predictions has been incorporated. The relational design has been modified accordingly. Furthermore, a major improvement is a graphic display enabling browsing of the database with a Java-based graphic user interface with three zoom-levels connected to properties of each chromosomal element. The purpose of these modifications is to make RegulonDB a useful tool and control set for transcriptome experiments. RegulonDB can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/++ +regulondb/

Operons in Escherichia coli: genomic analyses and predictions.

The rich knowledge of operon organization in Escherichia coli, together with the completed chromosomal sequence of this bacterium, enabled us to perform an analysis of distances between genes and of functional relationships of adjacent genes in the same operon, as opposed to adjacent genes in different transcription units. We measured and demonstrated the expected tendencies of genes within operons to have much shorter intergenic distances than genes at the borders of transcription units. A clear peak at short distances between genes in the same operon contrasts with a flat frequency distribution of genes at the borders of transcription units. Also, genes in the same operon tend to have the same physiological functional class. The results of these analyses were used to implement a method to predict the genomic organization of genes into transcription units. The method has a maximum accuracy of 88% correct identification of pairs of adjacent genes to be in an operon, or at the borders of transcription units, and correctly identifies around 75% of the known transcription units when used to predict the transcription unit organization of the E. coli genome. Based on the frequency distance distributions, we estimated a total of 630 to 700 operons in E. coli. This step opens the possibility of predicting operon organization in other bacteria whose genome sequences have been finished.

Discovering regulatory elements in non-coding sequences by analysis of spaced dyads.

The application of microarray and related technologies is currently generating a systematic catalog of the transcriptional response of any single gene to a multiplicity of experimental conditions. Clustering genes according to the similarity of their transcriptional response provides a direct hint to the regulons of the different transcription factors, many of which have still not been characterized. We have developed a new method for deciphering the mechanism underlying the common transcriptional response of a set of genes, i.e. discovering cis -acting regulatory elements from a set of unaligned upstream sequences. This method, called dyad analysis, is based on the observation that many regulatory sites consist of a pair of highly conserved trinucleotides, spaced by a non-conserved region of fixed width. The approach is to count the number of occurrences of each possible spaced pair of trinucleotides, and to assess its statistical significance. The method is highly efficient in the detection of sites bound by C(6)Zn(2)binuclear cluster proteins, as well as other transcription factors. In addition, we show that the dyad and single-word analyses are efficient for the detection of regulatory patterns in gene clusters from DNA chip experiments. In combination, these programs should provide a fast and efficient way to discover new regulatory sites for as yet unknown transcription factors.

The repertoire of DNA-binding transcriptional regulators in Escherichia coli K-12.

Using a combination of several approaches we estimated and characterized a total of 314 regulatory DNA-binding proteins in Escherichia coli, which might represent its minimal set of transcription factors. The collection is comprised of 35% activators, 43% repressors and 22% dual regulators. Within many regulatory protein families, the members are homogeneous in their regulatory roles, physiology of regulated genes, regulatory function, length and genome position, showing that these families have evolved homogeneously in prokaryotes, particularly in E.coli. This work describes a full characterization of the repertoire of regulatory interactions in a whole living cell. This repertoire should contribute to the interpretation of global gene expression profiles in both prokaryotes and eukaryotes.

A web site for the computational analysis of yeast regulatory sequences.

A series of computer programs were developed for the analysis of regulatory sequences, with a special focus on yeast. These tools are publicly available on the web (http://copan.cifn.unam. mx/Computational_Biology/yeast-tools or http://www.ucmb.ulb.ac. be/bioinformatics/rsa-tools/). Basically, three classical problems can be addressed: (a) search for known regulatory patterns in the upstream regions of known genes; (b) discovery of unknown regulatory patterns within a set of upstream regions known to be co-regulated; (c) search for unknown genes potentially regulated by a known transcription factor. Each of these tasks can be performed on basis of a simple (string) or more refined (matrix) description of the regulatory patterns. A feature-map program automatically generates visual representations of the positions at which patterns were found. The site also provides a series of general utilities, such as generation of random sequence, automatic drawing of XY graphs, interconversions between sequence formats, etc. Several tools are linked together to allow their sequential utilization (piping), but each one can also be used independently by filling the web form with external data. This widens the scope of the site to the analysis of non-regulatory and/or non-yeast sequences.

RegulonDB (version 3.0): transcriptional regulation and operon organization in Escherichia coli K-12.

RegulonDB is a database on transcription regulation and operon organization in Escherichia coli. The current version describes regulatory signals of transcription initiation, promoters, regulatory binding sites of specific regulators, ribosome binding sites and terminators, as well as information on genes clustered in operons. These specific annotations have been gathered from a constant search in the literature, as well as based on computational sequence predictions. The genomic coordinates of all these objects in the E.coli K-12 chromosome are clearly indicated. Every known object has a link to at least one MEDLINE reference. We have also added direct links to recent expression data of E.coli K-12. The version presented here has important modifications both in the structure of the database, as well as in the amount and type of information encoded in the database. RegulonDB can be accessed on the web at URL: http://www.cifn.unam. mx/Computational_Biology/regulondb/

Promoter interference in a bacteriophage lambda control region: effects of a range of interpromoter distances.

The p(R) and p(RM) promoters of bacteriophage lambda direct transcription in divergent directions from start sites separated by 83 phosphodiester bonds. We had previously shown that the presence of an RNA polymerase at p(R) interfered with open complex formation at p(RM) and that this effect was alleviated by the deletion of 10 bp between the two promoters. Here we present a detailed characterization of the dependence of the interference on the interpromoter distance. It was found that the reduced interference between the two promoters is unique to the 10-bp deletion. The relief of interference was demonstrated to be due to the facilitation of a step subsequent to RNA polymerase binding to the p(RM) promoter. A model to explain these observations is proposed. A search of known Escherichia coli promoters identified three pairs of divergent promoters with similar separations to those investigated here.

RegulonDB (version 2.0): a database on transcriptional regulation in Escherichia coli.

RegulonDB version 2.0, a database on transcriptional regulation and operon organization in Escherichia coli, is now available on the web at the following URL: http://www.cifn.unam. mx/Computational_Biology/regulondb/. In this paper we describe the main computational changes to the database, which include migrating the database to Sybase, providing graphical descriptions of the internal organization of operons and regulons, and direct links to MEDLINE references. The web interface offers searching either by mechanisms of regulation or by operon organization. The results of a search (operon organization, or site collection) are displayed as hypertext, and can also be displayed graphically. In terms of its contents, RegulonDB contains a large number of operons, as well as the absolute position in the completed genome sequence of sites, promoters, and individual genes of E.coli.

Networks of transcriptional regulation encoded in a grammatical model.

The work here presented enriches a previous grammatical model of the transcriptional regulation of gene expression. The previous model is centered on the representation of the regulatory regions upstream of genes, and their internal organization in the DNA. This paper is centered in discussing some alternatives related to the representation of the organization of operons and their alternative states of transcription, as active or inactive units of transcription. Transformational rules can be used to describe the binding and unbinding of regulatory proteins, and the associated representations of (ON/OFF) gene expression. The initial representation of a regulated promoter is linked to that of the operon encoding its regulatory protein. In this way the representation of a regulated operon depends on that of all others regulating its transcription, enabling in principle the encoding of regulatory networks within an expanded grammatical model of gene regulation.