Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

E. coli response to MMC

ABSTRACT: Changes in gene expression after treatment of E. coli cultures with mitomycin C were assessed using gene array technology. Unexpectedly, a large number of genes (nearly 30% of all genes) displayed significant changes in their expression level. Analysis and classification of expression profiles of the corresponding genes allowed us to assign this large number of genes into a dozen to two dozen small clusters of genes with similar expression profiles. This assignment allowed us to describe systematically the changes in the level of gene expression in response to DNA damage. Among the damage-induced genes more than a hundred are novel. From those genes involved in DNA metabolism that have not been previously shown to be induced by DNA damage, for example, the mutS gene involved in mismatch repair is especially noteworthy. In addition to the SOS response, we observed the induction of other stress response pathways such as those of oxidative stress and osmotic protection. Among the genes that are down-regulated in response to DNA damage are numerous protein biosynthesis genes. Analysis of the gene expression data highlighted the essential involvement of sigmaS regulated genes and the general stress response network in the response to DNA damage. Keywords = DNA damage, recA, SOS

ORGANISM(S): Escherichia coli

SUBMITTER: Natalya Smirnova

PROVIDER: E-GEOD-33 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Over 1000 genes are involved in the DNA damage response of Escherichia coli.

Khil Pavel P PP Camerini-Otero R Daniel RD

Molecular microbiology 20020401 1

Changes in gene expression after treatment of Escherichia coli cultures with mitomycin C were assessed using gene array technology. Unexpectedly, a large number of genes (nearly 30% of all genes) displayed significant changes in their expression level. Analysis and classification of expression profiles of the corresponding genes allowed us to assign this large number of genes into one or two dozen small clusters of genes with similar expression profiles. This assignment allowed us to describe sy ...[more]

PMID: 11967071

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Project description:Changes in human bladder epithelial cell gene expression associated with interstitial cystitis or antiproliferative factor treatment. Explanted bladder epithelial cells from patients with interstitial cystitis (IC) have been shown to differ from explanted control cells in several ways, including production of an antiproliferative factor (APF), altered production of certain epithelial growth factors, and rate of proliferation. To better understand the role of the APF in abnormal bladder epithelial cell proliferation in IC, we studied gene expression patterns in normal bladder epithelial cells treated with APF vs. mock APF and compared them to expression patterns in IC vs. normal cells using microarray analysis. Oligo-dT-primed total cellular RNA was labeled with [33P]dCTP and hybridized to GeneFilter GF211 microarray membranes (Research Genetics) containing cDNA for 3,964 human genes. Thirteen genes that function in epithelial cell proliferation or differentiation were consistently differentially expressed in both IC (compared with control) and APF-treated (compared with mock APF-treated) normal bladder epithelial cells. The general pattern of gene expression in IC and APF-treated cells suggested a less proliferative phenotype, with increased expression of E-cadherin, phosphoribosylpyrophosphate synthetase-associated protein 39, and SWI/SNF complex 170-kDa subunit, and decreased expression of vimentin, {alpha}2-integrin, {alpha}1-catenin, cyclin D1, and jun N-terminal kinase 1; these findings were confirmed for the structural gene products (E-cadherin, vimentin, {alpha}2-integrin, and {alpha}-catenin) by immunohistochemistry. These results are compatible with the previously noted decreased proliferation rate of IC and APF-treated normal cells, and indicate that the mechanism whereby APF inhibits cell proliferation may involve both downregulation of genes that stimulate cell proliferation along with upregulation of genes that inhibit cell growth.

Project description:Shimoni2009 - Escherichia Coli SOS Simple model, involving only the basic components of the circuit, sufficient to explain the peaks in the promoter activities of recA and lexA. This model is described in the article: Stochastic analysis of the SOS response in Escherichia coli. Shimoni Y, Altuvia S, Margalit H, Biham O PloS one. 2009; 4(5):e5363 Abstract: BACKGROUND: DNA damage in Escherichia coli evokes a response mechanism called the SOS response. The genetic circuit of this mechanism includes the genes recA and lexA, which regulate each other via a mixed feedback loop involving transcriptional regulation and protein-protein interaction. Under normal conditions, recA is transcriptionally repressed by LexA, which also functions as an auto-repressor. In presence of DNA damage, RecA proteins recognize stalled replication forks and participate in the DNA repair process. Under these conditions, RecA marks LexA for fast degradation. Generally, such mixed feedback loops are known to exhibit either bi-stability or a single steady state. However, when the dynamics of the SOS system following DNA damage was recently studied in single cells, ordered peaks were observed in the promoter activity of both genes (Friedman et al., 2005, PLoS Biol. 3(7):e238). This surprising phenomenon was masked in previous studies of cell populations. Previous attempts to explain these results harnessed additional genes to the system and deployed complex deterministic mathematical models that were only partially successful in explaining the results. PRINCIPAL FINDINGS: Here we apply stochastic methods, which are better suited for dynamic simulations of single cells. We show that a simple model, involving only the basic components of the circuit, is sufficient to explain the peaks in the promoter activities of recA and lexA. Notably, deterministic simulations of the same model do not produce peaks in the promoter activities. SIGNIFICANCE: We conclude that the double negative mixed feedback loop with auto-repression accounts for the experimentally observed peaks in the promoter activities. In addition to explaining the experimental results, this result shows that including additional regulations in a mixed feedback loop may dramatically change the dynamic functionality of this regulatory module. Furthermore, our results suggests that stochastic fluctuations strongly affect the qualitative behavior of important regulatory modules even under biologically relevant conditions, thus emphasizing the importance of stochastic analysis of regulatory circuits. This model is hosted on BioModels Database and identified by: MODEL2937159804. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

E. coli response to MMC

Publications

Over 1000 genes are involved in the DNA damage response of Escherichia coli.

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