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

Salgado, Heladia; Peralta-Gil, Martín; Gama-Castro, Socorro; Santos-Zavaleta, Alberto; Muñiz-Rascado, Luis; García-Sotelo, Jair Santiago; Weiss, Verena; Solano-Lira, Hilda; Martínez-Flores, Irma; Medina-Rivera, Alejandra; Salgado-Osorio, Gerardo; Alquicira-Hernández, Shirley; Alquicira-Hernández, Kevin; López-Fuentes, Alejandra; Porrón-Sotelo, Liliana; Huerta, A.; Bonavides-Martínez, César; Balderas-Martínez, Yalbi I.; Pannier, Lucia; Olvera, Maricela; Labastida, Aurora; Jiménez-Jacinto, Verónica; Vega‐Alvarado, Leticia; Moral-Chávez, Víctor Del; Hernández-Alvarez, Alfredo; Morett, Enrique; Collado‐Vides, Julio

doi:10.1093/nar/gks1201

Cited by 413 publications

(581 citation statements)

References 47 publications

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“…However, as large, curated databases continue to develop for multiple organisms (e.g., for TFs and their binding sites; see refs. [54][55][56], it will become possible to test the various evolutionary hypotheses concerning the roles played by effective population size, numbers of molecules per cell, number of interacting partners, and so on.…”

Section: Discussionmentioning

confidence: 99%

Evolutionary meandering of intermolecular interactions along the drift barrier

Lynch¹,

Hagner

2014

Proc. Natl. Acad. Sci. U.S.A.

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Many cellular functions depend on highly specific intermolecular interactions, for example transcription factors and their DNA binding sites, microRNAs and their RNA binding sites, the interfaces between heterodimeric protein molecules, the stems in RNA molecules, and kinases and their response regulators in signaltransduction systems. Despite the need for complementarity between interacting partners, such pairwise systems seem to be capable of high levels of evolutionary divergence, even when subject to strong selection. Such behavior is a consequence of the diminishing advantages of increasing binding affinity between partners, the multiplicity of evolutionary pathways between selectively equivalent alternatives, and the stochastic nature of evolutionary processes. Because mutation pressure toward reduced affinity conflicts with selective pressure for greater interaction, situations can arise in which the expected distribution of the degree of matching between interacting partners is bimodal, even in the face of constant selection. Although biomolecules with larger numbers of interacting partners are subject to increased levels of evolutionary conservation, their more numerous partners need not converge on a single sequence motif or be increasingly constrained in more complex systems. These results suggest that most phylogenetic differences in the sequences of binding interfaces are not the result of adaptive fine tuning but a simple consequence of random genetic drift. cellular evolution | molecular interaction | transcription | random genetic drift | coevolution M uch of biology relies on the specificity of intermolecular interactions-the regulation of gene expression, the transmission of information via signal transduction, the assembly of monomeric subunits into multimers, vesicle sorting in eukaryotic cells, toxin-antitoxin systems in microbes, mating-type recognition, and many other cellular features. Although the basic structural features of such fitness-related traits would seem to be under strong purifying selection, molecular specificity often seems to be highly flexible in evolutionary time. For example, transcription-factor binding-site motifs often vary dramatically among orthologous genes in different species and even among similarly regulated genes within the same species (1-3). The binding interfaces of multimeric proteins can vary substantially among species, sometimes with no overlap at all (4, 5). The key amino acid sequences involved in intermolecular cross-talk in signal-transduction systems can evolve at high rates (6, 7), and growing evidence suggests that the locations of sites involved in posttranslational modification in individual proteins are under much weaker selective constraints than their absolute numbers (8). Although it is often argued that subtle differences in the motifs involved in intermolecular interactions are molded by the demands of natural selection, seldom has any direct evidence ever been provided in support of such arguments.The theory provided below makes the case...

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Section: Discussionmentioning

confidence: 99%

Evolutionary meandering of intermolecular interactions along the drift barrier

Lynch¹,

Hagner

2014

Proc. Natl. Acad. Sci. U.S.A.

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“…Genes with FDR-corrected P values ≤0.05 were deemed statistically significant. Regulation for genes in the OxyR and SoxRS regulons was identified as annotated in RegulonDB v8.2 (110). Microarray data collected in this study are available for download on the Gene Expression Omnibus (GEO), accession no.…”

Section: Methodsmentioning

confidence: 99%

Antibiotics induce redox-related physiological alterations as part of their lethality

Dwyer

Belenky

Yang

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

737

683

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Deeper understanding of antibiotic-induced physiological responses is critical to identifying means for enhancing our current antibiotic arsenal. Bactericidal antibiotics with diverse targets have been hypothesized to kill bacteria, in part by inducing production of damaging reactive species. This notion has been supported by many groups but has been challenged recently. Here we robustly test the hypothesis using biochemical, enzymatic, and biophysical assays along with genetic and phenotypic experiments. We first used a novel intracellular H 2 O 2 sensor, together with a chemically diverse panel of fluorescent dyes sensitive to an array of reactive species to demonstrate that antibiotics broadly induce redox stress. Subsequent gene-expression analyses reveal that complex antibiotic-induced oxidative stress responses are distinct from canonical responses generated by supraphysiological levels of H 2 O 2 . We next developed a method to quantify cellular respiration dynamically and found that bactericidal antibiotics elevate oxygen consumption, indicating significant alterations to bacterial redox physiology. We further show that overexpression of catalase or DNA mismatch repair enzyme, MutS, and antioxidant pretreatment limit antibiotic lethality, indicating that reactive oxygen species causatively contribute to antibiotic killing. Critically, the killing efficacy of antibiotics was diminished under strict anaerobic conditions but could be enhanced by exposure to molecular oxygen or by the addition of alternative electron acceptors, indicating that environmental factors play a role in killing cells physiologically primed for death. This work provides direct evidence that, downstream of their target-specific interactions, bactericidal antibiotics induce complex redox alterations that contribute to cellular damage and death, thus supporting an evolving, expanded model of antibiotic lethality.reactive oxygen species | DNA repair | mutagenesis T he increasing incidence of antibiotic-resistant infections coupled with a declining antibiotic pipeline has created a global public health threat (1-6). Therefore there is a pressing need to expand our conceptual understanding of how antibiotics act and to use insights gained from such efforts to enhance our antibiotic arsenal. It has been proposed that different classes of bactericidal antibiotics, regardless of their drug-target interactions, generate varying levels of deleterious reactive oxygen species (ROS) that contribute to cell killing (7,8). This unanticipated notion, built upon important prior work (9-11), has been extended and supported by multiple laboratories investigating wide-ranging drug classes (e.g., β-lactams, aminoglycosides, and fluoroquinolones) and bacterial species (e.g., Escherichia coli, Pseudomonas aeruginosa, Salmonella enterica, Mycobacterium tuberculosis, Bacillus subtilis, Staphylococcus aureus, Acinetobacter baumannii, Burkholderia cepecia, Streptococcus pneumonia, Enterococcus faecalis) using independent lines of evidence (12-39). Importantly,...

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“…In the case of E. coli, the number of known regulatory interactions in RegulonDB 24,27 has grown by more than tenfold in the last 15 years, leading to an increase in the density of edges and in the size of the LSCC. However, the size of the LSCC has consistently remained smaller than expected for a randomized network.…”

Section: Feedback Processes In Transcriptional Regulatory Networkmentioning

confidence: 99%

“…We considered the most recent reconstructions of the TRNs of B. subtilis 23 and E. coli 24 . By analysing a series of recently proposed graph-theoretic measures 25 we quantified the extent of hierarchical organization in the TRNs of the two organisms studied here.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the hierarchical structure of the B. subtilis transcriptional regulatory network

et al. 2015

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The transcriptional regulation of gene expression is orchestrated by complex networks of interacting genes. Increasing evidence indicates that these 'transcriptional regulatory networks' (TRNs) in bacteria have an inherently hierarchical architecture, although the design principles and the specific advantages offered by this type of organization have not yet been fully elucidated. In this study, we focussed on the hierarchical structure of the TRN of the gram-positive bacterium Bacillus subtilis and performed a comparative analysis with the TRN of the gram-negative bacterium Escherichia coli. Using a graph-theoretic approach, we organized the transcription factors (TFs) and σ-factors in the TRNs of B. subtilis and E. coli into three hierarchical levels (Top, Middle and Bottom) and studied several structural and functional properties across them. In addition to many similarities, we found also specific differences, explaining the majority of them with variations in the distribution of σ-factors across the hierarchical levels in the two organisms. We then investigated the control of target metabolic genes by transcriptional regulators to characterize the differential regulation of three distinct metabolic subsystems (catabolism, anabolism and central energy metabolism). These results suggest that the hierarchical architecture that we observed in B. subtilis represents an effective organization of its TRN to achieve flexibility in the response to diverse stimuli.

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

Cited by 413 publications

References 47 publications

Evolutionary meandering of intermolecular interactions along the drift barrier

Evolutionary meandering of intermolecular interactions along the drift barrier

Antibiotics induce redox-related physiological alterations as part of their lethality

Analysis of the hierarchical structure of the B. subtilis transcriptional regulatory network

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