Elucidation and validation of new targets of the global regulator PdhR in Escherichia coli
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ABSTRACT:
ORGANISM(S): Escherichia coli Escherichia coli O157:H7 str. EDL933 Escherichia coli O157:H7 str. Sakai Escherichia coli CFT073 Escherichia coli str. K-12 substr. MG1655
PROVIDER: GSE31333 | GEO | 2011/12/21
SECONDARY ACCESSION(S): PRJNA146005
REPOSITORIES: GEO
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Project description:The pyruvate dehydrogenase regulator protein (PdhR) of Escherichia coli acts as a transcriptional regulator in a pyruvate dependent manner to control central metabolic fluxes. However, the complete PdhR regulon has not yet been uncovered. To achieve an extended understanding of its gene regulation network, we combined large-scale network inference and experimental verification of results obtained by a systems biology approach. We determined the gene expression of four different strains of E. coli on three different media. The four strains corresponded to the wild-type E. coli (LJ110), a PdhR knockout mutant (LJ110deltapdhR), a strain carrying an empty plasmid (LJ110/pTM30) and a PdhR overexpression strain (LJ110/pTM30PdhRhis). These strains were cultivated on Luria-Bertani broth (LBo), standard phosphate minimal medium supplemented with acetate and standard phosphate minimal medium supplemented with pyruvate. We obtained an overall 24 microarray experiments from two replicates of each of these cultivations.
2011-12-21 | E-GEOD-31333 | biostudies-arrayexpress
Project description:Here we dissected a regulatory network directed by the conserved iron homeostasis regulator, Ferric Uptake Regulator (Fur), in uropathogenic E. coli strain CFT073. Comparing anaerobic genome-scale Fur DNA binding, with Fur dependent transcript expression and protein levels of the uropathogen to that of commensal E. coli K-12 strain MG1655, showed that the Fur regulon of the core genome is conserved but also includes genes within the pathogenicity/genetic islands. Unexpectedly, regulons indicative of amino acid limitation and the general stress response were also indirectly activated in the uropathogen fur mutant, suggesting that induction of the Fur regulon increases amino acid demand. Using RpoS levels as a proxy, addition of amino acids mitigated the stress. In addition, iron chelation increased RpoS to the same levels as in the fur mutant. The increased amino acid demand of the fur mutant or iron chelated cells was exacerbated by aerobic conditions, which could be partly explained by the O 2 -dependent synthesis of the siderophore aerobactin, encoded within a pathogenicity island. Taken together, this data suggest in the iron-poor environment of the urinary tract, amino acid availability could play a role in the proliferation of this uropathogen, particularly if there is sufficient O 2 to produce aerobactin.
2020-05-27 | PXD017582 | Pride
Project description:Although many methods have been developed for inference of biological networks, the validation of the resulting models has largely remained an unsolved problem. Here we present a framework for quantitative assessment of inferred gene interaction networks using knock-down data from cell line experiments. Using this framework we are able to show that network inference based on integration of prior knowledge derived from the biomedical literature with genomic data significantly improves the quality of inferred networks relative to other approaches. Our results also suggest that cell line experiments can be used to quantitatively assess the quality of networks inferred from tumor samples. Knock-down of eight genes were performed on colorectal cancer cell lines to identify the genes whose expression was significantly affected. These genes were subsequently used to validate the quality of our causal gene interaction network.
2013-12-23 | E-GEOD-53091 | biostudies-arrayexpress
Project description:We investigated the way global gene expression changed in E. coli correlated with the metabolism of seven carbon substrates chosen to trigger a large panel of metabolic pathways with features varying in: carbon influx flow rate; entry points in the metabolic network; modes of transport. Quantitative coarse-grained expression-pattern analysis demonstrated that the gene expression trend following immediately the reduction of carbon influx flow rate was determined by its initial expression level. Subsequent fine-grained expression-pattern analysis demonstrated that the Crp regulator, associated to a change in growth rate, governed the response of most carbon influx-dependent genes. By contrast, the Cra, Mlc and Fur regulators governed the expression of genes responding to non-glycolytic substrates, glycolytic substrates or PTS (phosphotransferase system) transported sugars following an idiosyncratic way, with the function of each of these regulators being titrated by the metabolism of the corresponding substrates. This work also allowed us to expand the extent of the gene complement regulated by each regulator with additional genes (27 genes in the Crp regulon, 49 genes in the Cra regulon, 1 gene in the Mlc regulon and 2 genes in Fur regulon) and to elucidate the regulatory functions of each regulator comprehensively. Strikingly, Crp and Cra worked in concert to coordinate central carbon metabolism with amino acids biosynthesis. Together, these results demonstrated the power of physiology-based interperation of global data in revealing regulatory networks of bacteria.
2021-03-02 | GSE156143 | GEO
Project description:Although many methods have been developed for inference of biological networks, the validation of the resulting models has largely remained an unsolved problem. Here we present a framework for quantitative assessment of inferred gene interaction networks using knock-down data from cell line experiments. Using this framework we are able to show that network inference based on integration of prior knowledge derived from the biomedical literature with genomic data significantly improves the quality of inferred networks relative to other approaches. Our results also suggest that cell line experiments can be used to quantitatively assess the quality of networks inferred from tumor samples.
2013-12-23 | GSE53091 | GEO
Project description:While global transcription factors (TFs) have been studied extensively in Escherichia coli model strains, conservation and diversity in TF regulation between strains is still unknown. Here we use a combination of ChIP-exo--to define ferric uptake regulator (Fur) binding sites--and differential gene expression--to define the Fur regulon in nine E. coli strains. We then define a pan-regulon consisting of 469 target genes that includes all Fur target genes in all nine strains. The pan-regulon is then divided into the core regulon (target genes found in all the strains, n=36), the accessory regulon (target found in two to eight strains, n=158) and the unique regulon (target genes found in one strain, n=275). Thus, there is a small set of Fur regulated genes common to all nine strains, but a large number of regulatory targets unique to a particular strain. Many of the unique regulatory targets are genes unique to that strain. This first-established pan-regulon reveals a common core of conserved regulatory targets and significant diversity in transcriptional regulation amongst E. coli strains, reflecting diverse niche specification and strain history.
2023-08-04 | GSE223483 | GEO
Project description:Pseudomonas aeruginosa displays tremendous metabolic diversity, controlled in part by the abundance of transcription regulators in the genome. We have been investigating P. aeruginosaM-bM-^@M-^Ys response to the host, particularly changes regulated by the host-derived quaternary amines choline and glycine betaine (GB). We previously identified GbdR as an AraC-family transcription factor that directly regulates choline acquisition from host phospholipids (via binding to plcH and pchP promoters), is required for catabolism of the choline metabolite GB, and is an activator that induces transcription in response to GB or dimethylglycine. Our goal was to characterize the GbdR regulon in P. aeruginosa using genetics and chemical biology in combination with transcriptomics and in vitro DNA-binding assays. Here we show that GbdR activation regulates transcription of 26 genes from 12 promoters; 11 of which have measureable binding to GbdR in vitro. The GbdR regulon includes the genes encoding GB, dimethylglycine, sarcosine, glycine, and serine catabolic enzymes, and the BetX and CbcXWV quaternary amine transport proteins. . Additionally, identification of two uncharacterized regulon members suggests roles for these proteins in response to choline metabolites. The conditions for inclusion in the gbdR regulon were: (i) called present in the array, (ii) changed more than 2.5-fold in signal in a statistically significant manner, (iii) altered in all three 'inducing' conditions (ethylcholine, choline+propargylcholine, and choline in the dgcA mutant), but (iv) not induced in the wild-type choline or diethylcholine treatments. Wild type and dgcA mutant cells were pre-grown in MOPS minimal media and then split and resuspended in MOPS pyruvate, MOPS pyruvate + choline, MOPS pyruvate + ethylcholine, MOPS pyruvate + diethylcholine, or MOPS pyruvate & choline + propargylcholine.
2013-10-23 | E-GEOD-49759 | biostudies-arrayexpress
Project description:Global transcriptional profiling of Bacillus subtilis cells comparing wild-type to a (ccpN-yqfL) double mutant. Abstract of the associated publication (article accepted): The transcriptional regulator CcpN of Bacillus subtilis has been recently characterized as a repressor of two gluconeogenic genes, gapB and pckA, and of a small non-coding regulatory RNA, sr1, involved in arginine catabolism. Deletion of ccpN impairs growth on glucose and strongly alters the distribution of intracellular fluxes, rerouting the main glucose catabolism from glycolysis to the pentose phosphate (PP) pathway. Using transcriptome analysis, we show that during growth on glucose, gapB and pckA are the only protein-coding genes directly repressed by CcpN. By quantifying intracellular fluxes in deletion mutants, we demonstrate that derepression of pckA under glycolytic condition causes the growth defect observed in the ccpN mutant due to extensive futile cycling through the pyruvate carboxylase, phosphoenolpyruvate carboxykinase, and pyruvate kinase. Beyond ATP dissipation via this cycle, PckA activity causes a drain on tricarboxylic acid cycle intermediates, which we show to be the main reason for the reduced growth of a ccpN mutant. The high flux through the PP pathway in the ccpN mutant is modulated by the flux through the alternative glyceraldehyde-3-phosphate dehydrogenases, GapA and GapB. Strongly increased concentrations of intermediates in upper glycolysis indicate that GapB overexpression causes a metabolic jamming of this pathway and, consequently, increases the relative flux through the PP pathway. In contrast, derepression of sr1, the third known target of CcpN, plays only a marginal role in ccpN mutant phenotypes. Two-condition experiment: wt vs. (ccpN-yqfL) double mutant. 2 totally independent comparisons were performed different days with 2 independent RNA preparations and 2 sets of macroarrays.
2008-07-01 | E-GEOD-11876 | biostudies-arrayexpress
Project description:BACKGROUND: The pyruvate dehydrogenase regulator protein (PdhR) of Escherichia coli acts as a transcriptional regulator in a pyruvate dependent manner to control central metabolic fluxes. However, the complete PdhR regulon has not yet been uncovered. To achieve an extended understanding of its gene regulatory network, we combined large-scale network inference and experimental verification of results obtained by a systems biology approach. RESULTS: 22 new genes contained in two operons controlled by PdhR (previously only 20 regulatory targets in eight operons were known) were identified by analysing a large-scale dataset of E. coli from the Many Microbes Microarray Database and novel expression data from a pdhR knockout strain, as well as a PdhR overproducing strain. We identified a regulation of the glycolate utilization operon glcDEFGBA using chromatin immunoprecipitation and gel shift assays. We show that this regulation could be part of a cross-induction between genes necessary for acetate and pyruvate utilisation controlled through PdhR. Moreover, a link of PdhR regulation to the replication machinery of the cell via control of the transcription of the dcw-cluster was verified in experiments. This augments our knowledge of the functions of the PdhR-regulon and demonstrates its central importance for further cellular processes in E. coli. CONCLUSIONS: We extended the PdhR regulon by 22 new genes contained in two operons and validated the regulation of the glcDEFGBA operon for glycolate utilisation and the dcw-cluster for cell division proteins experimentally. Our results provide, for the first time, a plausible regulatory link between the nutritional status of the cell and cell replication mediated by PdhR.
| S-EPMC3265435 | biostudies-literature
Project description:Machine learning approaches offer the potential to systematically identify transcriptional regulatory interactions from a compendium of microarray expression profiles. However, experimental validation of the performance of these methods at the genome scale has remained elusive. Here we assess the global performance of four existing classes of inference algorithms using 445 Escherichia coli Affymetrix arrays and 3,216 known E. coli regulatory interactions from RegulonDB. We also developed and applied the context likelihood of relatedness (CLR) algorithm, a novel extension of the relevance networks class of algorithms. CLR demonstrates an average precision gain of 36% relative to the next-best performing algorithm. At a 60% true positive rate, CLR identifies 1,079 regulatory interactions, of which 338 were in the previously known network and 741 were novel predictions. We tested the predicted interactions for three transcription factors with chromatin immunoprecipitation, confirming 21 novel interactions and verifying our RegulonDB-based performance estimates. CLR also identified a regulatory link providing central metabolic control of iron transport, which we confirmed with real-time quantitative PCR. The compendium of expression data compiled in this study, coupled with RegulonDB, provides a valuable model system for further improvement of network inference algorithms using experimental data. Keywords: mapping transcriptional regulation
2007-01-22 | GSE6836 | GEO