Regulatory proteins control a transcriptional network in response to antibiotic stress
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ABSTRACT:
PROVIDER: PRJNA659486 | ENA |
REPOSITORIES: ENA
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Project description:In a given bacterial population, antibiotic treatment kills a large portion of the population, while a small, tolerant subpopulation survives. Tolerant cells disrupt the efficacy of antibiotic treatment and increase the likelihood that a population gains antibiotic resistance. Antibiotic tolerance is different from resistance because tolerant cells cannot grow and replicate in the presence of the antibiotic, but when the antibiotic is removed, they begin to propagate. When a population becomes resistant, the antibiotic becomes ineffective, which is a major health concern. Since antibiotic tolerance often leads to antibiotic resistance, we have taken a systems biology approach to examine how regulatory networks respond to antibiotic stress so that cells can survive and recover after antibiotic treatment. We have compared gene expression with and without ampicillin in E. coli.
2020-12-04 | GSE156896 | GEO
Project description:ONAC127 and ONAC129 regulatory network
| PRJNA588457 | ENA
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin).
2014-09-11 | GSE55662 | GEO
Project description:Evolution of antibiotic resistance in microbes is frequently achieved by acquisition of spontaneous mutations during antimicrobial therapy. Here we demonstrate that inactivation of a central regulator of iron homeostasis (fur) facilitates laboratory evolution of ciprofloxacin resistance in Escherichia coli. To decipher the underlying molecular mechanisms, we first performed a global transcriptome analysis and demonstrated a substantial reorganization of the Fur regulon in response to antibiotic treatment. We hypothesized that the impact of Fur on evolvability under antibiotic pressure is due to the elevated intracellular concentration of free iron and the consequent enhancement of oxidative damage-induced mutagenesis. In agreement with expectations, over-expression of iron storage proteins, inhibition of iron transport, or anaerobic conditions drastically suppressed the evolution of resistance, while inhibition of the SOS response-mediated mutagenesis had no such effect in fur deficient population. In sum, our work revealed the central role of iron metabolism in de novo evolution of antibiotic resistance, a pattern that could influence the development of novel antimicrobial strategies. We used microarrays to identify genotype specific transcriptional changes under severe DNA damaging conditions (antibiotic ciprofloxacin). We treated Escherichia coli cells with a highly toxic level of ciprofloxacin (gyrase inhibitor) for RNA extraction and hybridization on Affymetrix microarrays. We planned to find genotype specific transcriptional responses using WT control (BW25113) and fur-knockout mutant (selected from the KEIO collection) strains during antibiotic treatments. For each treatment type we used two biological replicates.
2014-09-11 | E-GEOD-55662 | biostudies-arrayexpress
Project description:Pseudomonas syringae Virulence Regulatory Network construction
| PRJNA575032 | ENA
Project description:Regulatory network of SlDof1 in fruit ripening
| PRJNA489598 | ENA
Project description:Expression profiles of 22 reference Arabidopsis immunity mutants were collected using the Arabidopsis Pathoarray 464_001 (GPL3638) in order to build a network model predicting the Arabidopsis immune signaling network. Biological signaling processes may be mediated by complex networks in which network components and network sectors interact with each other in complex ways. Studies of complex networks benefit from approaches in which the roles of individual components are considered in the context of the network. The plant immune signaling network, which controls inducible responses to pathogen attack, is such a complex network. Here, we demonstrate that use of mRNA profiling to collect and analyze detailed descriptions of changes in the network state resulting from specific network perturbations is a powerful and economical strategy to elucidate regulatory relationships among the components of a complex signaling network. Specifically, we studied the Arabidopsis immune signaling network upon challenge with a strain of the bacterial pathogen Pseudomonas syringae expressing the effector protein AvrRpt2 (Pto DC3000 AvrRpt2). This bacterial strain feeds multiple inputs into the signaling network, allowing many parts of the network to be activated at once. mRNA profiles of 22 Arabidopsis immunity mutants and wild type were collected 6 hours after inoculation with the Pto DC3000 AvrRpt2 and used as detailed descriptions of the network states resulting from specific genetic perturbations. Regulatory relationships among the genes corresponding to the mutations were inferred by recursively applying a non-linear dimensionality reduction procedure to the mRNA profile data. The resulting network model accurately predicted 22 of 23 regulatory relationships reported in the literature, suggesting that predictions of novel regulatory relationships are also accurate. The network model revealed two striking features: (i) the components of the network are highly interconnected; (ii) negative regulatory relationships are common between signaling sectors. One case of a novel negative regulatory relationship, between the early microbe-associated molecular pattern (MAMP)-activated sector and the salicylic acid (SA)-mediated sector, was further validated. We propose that prevalent negative regulatory relationships among the signaling sectors make the plant immune signaling network a "sector-switching" network, which effectively balances two apparently conflicting demands, robustness against pathogenic perturbations and moderation of negative impacts of immune responses on plant fitness. Keywords: Responses of reference Arabidopsis immunity mutants to Pseudomonas syringae pv. tomato DC3000 carrying avrRpt2 This experiment consists of two (group00) or three (group01-04) biological replicates of each genotype (total 25 genotypes [3 are multiple mutants, which were removed for the network modeling, but were used for normalization]). For each genotype, two leaves per plant were pooled from three pots to prepare total RNA.
2010-07-22 | E-GEOD-19663 | biostudies-arrayexpress
Project description:Determining the gene regulatory network of an organism is fundamental to achieving a global understanding of cell behavior. In general, studies of transcription regulation are limited to the annotated transcription factors, not considering other non-canonical regulators. Here we describe the first systematic analysis of the DNA-interactome of a bacterium with a minimal proteome (Mycoplasma pneumoniae). We first determined by DNA affinity chromatography and intact chromatin isolation all potential DNA binding proteins. We then mapped the DNA binding of these factors by ChIP-seq, as well as their functionality by gain- and loss-of-function experiments, by transcriptomics and proteomics. This identified new DNA binding proteins and novel regulators with moonlighting properties like proteases and metabolic enzymes and allowed to reconstruct the gene regulatory network.
2019-11-11 | PXD007551 | Pride
Project description:Although global analyses of transcription factor binding provide one view of potential transcriptional regulatory networks, regulation also occurs at levels distinct from transcription factor binding. Here, we use a genetic approach to identify targets of transcription factors in yeast and reconstruct a functional regulatory network. First, we profiled transcriptional responses in S. cerevisiae strains with individual deletions of 263 transcription factors. Then we used directed-weighted graph modeling and regulatory epistasis analysis to identify indirect regulatory relationships between these transcription factors, and from this we reconstructed a functional transcriptional regulatory network. The enrichment of promoter motifs and Gene Ontology annotations provide insight into the biological functions of the transcription factors. Data values are X scores and corresponding p-values derived using an error model. We profiled transcriptional responses upon the individual deletion of more than 260 TFs. We used a directed-weighted graph modelling approach and regulatory epistasis analysis to identify indirect regulatory relationships, and thus constructed a refined, functional transcriptional regulatory network.
2010-07-02 | E-GEOD-4654 | biostudies-arrayexpress
Project description:Determining the gene regulatory network of an organism is fundamental to achieving a global understanding of cell behavior. In general, studies of transcription regulation are limited to the annotated transcription factors, not considering other non-canonical regulators. Here we describe the first systematic analysis of the DNA-interactome of a bacterium with a minimal proteome (Mycoplasma pneumoniae). We first determined by DNA affinity chromatography and intact chromatin isolation all potential DNA binding proteins. We then mapped the DNA binding of these factors by ChIP-seq, as well as their functionality by gain- and loss-of-function experiments, by transcriptomics and proteomics. This identified new DNA binding proteins and novel regulators with moonlighting properties like proteases and metabolic enzymes and allowed to reconstruct the gene regulatory network.
2019-11-12 | PXD007566 | Pride