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The genome-scale interplay amongst xenogene silencing, stress response and chromosome architecture in Escherichia coli.

Nucleic acids research | 2015

The gene expression state of exponentially growing Escherichia coli cells is manifested by high expression of essential and growth-associated genes and low levels of stress-related and horizontally acquired genes. An important player in maintaining this homeostasis is the H-NS-StpA gene silencing system. A Δhns-stpA deletion mutant results in high expression of otherwise-silent horizontally acquired genes, many located in the terminus-half of the chromosome, and an indirect downregulation of many highly expressed genes. The Δhns-stpA double mutant displays slow growth. Using laboratory evolution we address the evolutionary strategies that E. coli would adopt to redress this gene expression imbalance. We show that two global gene regulatory mutations-(i) point mutations inactivating the stress-responsive sigma factor RpoS or σ38 and (ii) an amplification of ∼40% of the chromosome centred around the origin of replication-converge in partially reversing the global gene expression imbalance caused by Δhns-stpA. Transcriptome data of these mutants further show a three-way link amongst the global gene regulatory networks of H-NS and σ38, as well as chromosome architecture. Increasing gene expression around the terminus of replication results in a decrease in the expression of genes around the origin and vice versa; this appears to be a persistent phenomenon observed as an association across ∼300 publicly-available gene expression data sets for E. coli. These global suppressor effects are transient and rapidly give way to more specific mutations, whose roles in reversing the growth defect of H-NS mutations remain to be understood.

Pubmed ID: 25429971 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


Bioconductor (tool)

RRID:SCR_006442

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

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RRID:SCR_007767

M3D is a resource for analyzing and retrieving gene expression data for microbes. The database currently contains Affymetrix expression compendia for Escherichia coli, Saccharomyces cerevisiae, and Shewanella oneidensis. M3D (Many Microbe Microarrays) was developed by the Gardner Lab at Boston University to facilitate the exchange and analysis of high quality, curated, microbial gene expression data. Currently, the database only includes data obtained using Affymetrix GeneChip technology, because the high quality of the platform facilitates cross-laboratory integration of data sets. The database allows downloading of raw data (CEL files) or preprocessed data that has been uniformly normalized with RMA. M3D also enables convenient web-based expression data exploration and visualization - accessable via the Analysis page.

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Gene Expression Omnibus (GEO) (tool)

RRID:SCR_005012

Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.

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RRID:SCR_006849

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edgeR (tool)

RRID:SCR_012802

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

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