Identifying global regulators in transcriptional regulatory networks in bacteria

<p>The machinery for cells to take decisions, when environmental conditions change, includes protein–DNA interactions defined by transcriptional factors and their targets around promoters. Properties of global regulators are revised attempting to reach diagnostic explicit criteria for their definition and eventual future computational identification. These include among others, the number of regulated genes, the number and type of coregulators, the different s-classes of promoters and the number of transcriptional factors they regulate, the size of the evolutionary family they belong to, and the variety of conditions where they exert their control. As a consequence, global versus local regulation can be identified, as shown for Escherichia coli and eventually in other genomes.</p

Escherichia coli transcriptional regulatory network

<p>In this review are presented several structural and functional aspects of their transcriptional regulatory network constituted by transcription factors and target genes. The network discussed here represent to 1531 genes and 3421 regulatory interactions. This network shows a power-law distribution with a few global regulators and most of genes poorly connected. 176 of genes in the network correspond to transcription factors, which form a sub-network of seven hierarchical layers where global regulators tend to be set in superior layers while local regulators are located in the lower ones.</p

Operation of the Gene Regulatory Network in Escherichia coli

<p>In this chapter I present the advances of what we know about the mechanistic logic for the operation of the regulatory programme in E. coli. It is proposed that for a better understanding on the operation of the regulatory network it should be considered the globalism of transcription factors, the signal perceived by each, their co-regulating activity, the genome position of regulatory and target genes, and cellular concentration of the regulatory proteins, among others.</p

Mechanisms and Controls of DNA Replication in Bacteria

<p>In this chapter we will focus our discussion on the mechanisms and controls that conduct DNA replication in bacteria, including the components, functions and regulation of replication machinery. Most of our discourse will consider this biological process in Escherichia coli but when possible we will compare it to other bacterial models, mainly Bacillus subtilis and Caulobacter crescentus as examples of organisms with asymmetrical cell division.</p

Cadenas de ADN bajo representación de pseudocolores mediante imágenes digitales RGB

<p>Una molécula de ADN puede ser representada por una secuencia de letras, siendo posibles 4 letras diferentes A, C, G y T, estas representan las bases nitrogenadas que forman el ADN: Adenina. Citosina, Guanina y Timina. Aqui proponemos una representación visual y que facilite el análisis de información contenido en estas secuencias. La representación propuesta permite visualizar la distribución de las bases nitrogenadas en la cadena de ADN sin alterar su distribución y preservando toda la información que contiene. Para demostrar que de dicha representación es posible extraer información, a las imágenes de un conjunto de genes de bacterias, se les aplicó reconocimiento de patrones, en base a un proceso de clasificación, para reconstruir una taxonomía como lo hacen los algoritmos para hacer filogenia molecular.</p

COMPARATIVE MECHANISMS FOR TRANSCRIPTION AND REGULATORY SIGNALS IN ARCHAEA AND BACTERIA

<p>A review and comparisosn of genetic regulatory mechanisms in archaea and bacteria.</p

Characterization of the lipA gene encoding the major lipase from Pseudomonas aeruginosa strain IGB83

<p>The lipases produced by Pseudomonas have a wide range of potential biotechnological applications. Pseudomonas aeruginosa IGB83 was isolated as a highly lipolytic strain which produced a thermotolerant and alkaline lipase. In the present work, we have characterized the P. aeruginosa IGB83 gene (lipA) encoding this enzyme. We describe the construction of a lipA mutant and report the effect of two carbon sources on lipase expression.</p

Functional organisation of Escherichia coli transcriptional regulatory network

<p>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 controllingmetabolic 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.</p

Regulatory dynamics of standard two-component systems in bacteria

<p>Here, we study 14 two-component systems in Escherichia coli, which have been experimentally characterized with respect to their transcriptional regulation and their perceived signal. Given that the activity of these sensory units is connected to the rest of the transcriptional network, we first classify them as autonomous, semiautonomous or dependent, according to whether or not they use additional regulators to be transcribed. Next, we use discrete-time models to simulate their qualitative regulatory dynamics in response to their transcriptional regulation and to the activation of these systems by their cognate signals. Compared to more traditional ordinary differential equations method, ours has the advantage of being computationally simple and mathematically tractable, while keeping the ability to reproduce the phenomenology described by non-linear models. The aim of the present work is not the study of all possible behaviors of these two-component systems, but to exemplify those behaviors reported in the literature. On the other hand, most of these systems are auto-activating switches, a property that distinguishes them from the other transcription factors in the regulatory network, which are mostly auto-repressing. Based on the data, our models show dynamic behaviors that explain how most of these sensory systems convey abilities for multistationarity, and these dynamic properties could explain the phenotypic heterogeneity observed in bacterial populations. Our results are likely to have an impact in the design of synthetic signaling modules.</p

Conservation of transcriptional sensing systems in prokaryotes: A perspective from Escherichia coli

<p>Here, we introduce the notion of ‘‘triferog’’, which relates to the identification of orthologous transcription factors and effector genes across genomes and show that transcriptional sensing systems known in E. coli are poorly conserved beyond Salmonella. We also find that enzymes that act as effector genes for the production of endogenous effector metabolites are more conserved than their corresponding effector genes encoding for transport and two-component systems for sensing exogenous signals. Finally, we observe that on an evolutionary scale enzymes are more conserved than their respective TFs, suggesting a homogenous cellular metabolism across genomes and the conservation of transcriptional control of critical cellular processes like DNA replication by a common endogenous signal. We hypothesize that extensive variation in the domain architecture of TFs and changes in endogenous conditions at large phylogenetic distances could be the major contributing factors for the observed differential conservation of TFs and their corresponding effector genes encoding for enzymes, causing variations in transcriptional responses across organisms.</p