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The DNA damage response of Escherichia coli: differential gene expression after replication inhibition by azidothymidine

ABSTRACT: We examined the DNA damage response of bacterium E. coli using the replication inhibitor azidothyimdine (AZT), and RNA-Seq analysis. We confirm the induction of classic SOS loci by AZT and identify several genes, including many of the pyrimidine pathway, that are induced dependent on LexA cleavage, but have not been previously demonstrated to be DNA damage-inducible. Despite a strong dependence on LexA, these genes lack LexA boxes and their regulation by LexA is likely to be indirect via unknown factors. We show that stringent starvation protein, SspA, is as important as LexA in the regulation of AZT-induced genes. Our experiments identify a new set of LexA-independent DNA damage inducible genes, including 22 small RNA genes, some of which appear to activated by SspA. Motility and chemotaxis genes are strongly down-regulated by AZT, possibly as a result of one of more of the small RNAs or other transcription factors such as AppY and GadE, whose expression is elevated by AZT. Genes controlling the iron siderophore, enterobactin, and iron homeostasis are also strongly induced, independent of LexA. We confirm that IraD anti-adaptor protein and its upstream genes are induced, independent of LexA and that a second anti-adaptor, IraM is also strongly AZT-inducible, independent of LexA, suggesting that RpoS stabilization via these anti-adaptor proteins is an integral part of DNA damage tolerance.

ORGANISM(S): Escherichia coli K-12

PROVIDER: GSE263906 | GEO | 2024/06/26

REPOSITORIES: GEO

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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.

Project description:The SOS response is a conserved pathway that is activated under certain stress conditions and is regulated by the repressor LexA and the activator RecA. The food-borne pathogen Listeria monocytogenes contains RecA and LexA homologs, but their roles in Listeria have not been established. In this study, we identified the SOS regulon in L. monocytogenes by comparing the transcription profiles of the wild-type strain and the ÎrecA mutant strain after exposure to the DNA damaging agent mitomycinC (MMC). The SOS response is an inducible pathway involved in DNA repair, restart of stalled replication forks, and in induction of genetic variation in stressed and stationary phase cells. It is regulated by LexA and RecA. LexA is an autoregulatory repressor which binds to a consensus sequence in the promoter region of the SOS response genes, thereby repressing transcription. A consensus LexA binding motif for L. monocytogenes has not been identified thus far. Generally, the SOS response is induced under circumstances in which single stranded DNA accumulates in the cell. This results in activation of RecA, which in turn stimulates cleavage of LexA, and ultimately in the induction of the SOS response. Keywords: stress response, loop design, SOS response, mitomycin c, listeria monocytogenes, RecA, LexA Triple loop design of 3 independent experiments (series A, B, and C) using Wt strain and recA mutant (activator of the SOS response). Sampling was done before (t=0) and 1 hour after (t=60) exposure to mitomycin C (MMC) for both the wild-type strain and the recA mutant strain. One series therefore contains 4 samples and the complete experiments consists of 12 samples. Each of the 3 series was designed in a loop (wt, t=0 =>wt, t=60 => recA, t=60 => recA, t=0 => wt, t=0). These 3 loops were connected using series B as the central loop. Series B was connected to series A as follows: wt, t=0 (B) => recA, t=0 (A) and wt, t=60 (B) => recA, t=60 (A). Series B was connected to series C as follows: recA, t=0 (B) => wt, t=0 (C) and recA, t=60 (B) => wt, t=60 (C).