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Global LexA1 binding sites assessment in Leptospira interrogans serivar Copenhageni using ChIP-seq

ABSTRACT: The pathogen L. interrogans serovar Copenhageni can be shed in the urine of carrier mammals, and infect humans after weeks on water or mud. This wide range of possible niches implies the bacterium can be exposed to several different genotoxic stresses during its lifecycle. We assessed the impact of DNA damage in this leptospire, integrating high throughput data from ChIP-seq and DNA microarrays to determine the role of the SOS regulator LexA1. We observed 24 LexA1 binding sites located throughout the chromosome 1 and one in chromosome 2. Analyses of LexA1 ChIP-seq peak sequences revealed the SOS box is an imperfect asymmetric palindrome of 16bp, CTAA[A/T/G]CANNTG[T/A]TTAG. DNA damage caused significant changes of several aspects of bacterial physiology, decreasing expression of genes involved in energy metabolism and translation, in addition to genes related to virulence and motility. On the other hand, post replicative and recombination repair, but not the canonical DNA repair genes, were up regulated. The most striking feature of this response was the massive up-regulation of two prophages. Our findings point to an expression profile shift from cell growth and virulence to mutagenesis and recombination, emphasizing the fundamental role of DNA damage response as a highway for adaptation and evolution.

ORGANISM(S): Leptospira interrogans serovar Copenhageni

PROVIDER: GSE73688 | GEO | 2016/01/22

SECONDARY ACCESSION(S): PRJNA297669

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.

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Global LexA1 binding sites assessment in Leptospira interrogans serivar Copenhageni using ChIP-seq

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