Transcriptional modulation induced by ionizing radiation: p53 remains a central player.

The cellular response to DNA damage is vital for maintaining genomic stability and preventing undue cell death or cancer formation. The DNA damage response (DDR), most robustly mobilized by double-strand breaks (DSBs), rapidly activates an extensive signaling network that affects numerous cellular systems, leading to cell survival or programmed cell death. A major component of the DDR is the widespread modulation of gene expression. We analyzed together six datasets that probed transcriptional responses to ionizing radiation (IR) - our novel experimental data and 5 published datasets - to elucidate the scope of this response and identify its gene targets. According to the mRNA expression profiles we recorded from 5 cancerous and non-cancerous human cell lines after exposure to 5 Gy of IR, most of the responses were cell line-specific. Computational analysis identified significant enrichment for p53 target genes and cell cycle-related pathways among groups of up-regulated and down-regulated genes, respectively. Computational promoter analysis of the six datasets disclosed that a statistically significant number of the induced genes contained p53 binding site signatures. p53-mediated regulation had previously been documented for subsets of these gene groups, making our lists a source of novel potential p53 targets. Real-time qPCR and chromatin immunoprecipitation (ChIP) assays validated the IR-induced p53-dependent induction and p53 binding to the respective promoters of 11 selected genes. Our results demonstrate the power of a combined computational and experimental approach to identify new transcriptional targets in the DNA damage response network.

Expander: from expression microarrays to networks and functions.

A major challenge in the analysis of gene expression microarray data is to extract meaningful biological knowledge out of the huge volume of raw data. Expander (EXPression ANalyzer and DisplayER) is an integrated software platform for the analysis of gene expression data, which is freely available for academic use. It is designed to support all the stages of microarray data analysis, from raw data normalization to inference of transcriptional regulatory networks. The microarray analysis described in this protocol starts with importing the data into Expander 5.0 and is followed by normalization and filtering. Then, clustering and network-based analyses are performed. The gene groups identified are tested for enrichment in function (based on Gene Ontology), co-regulation (using transcription factor and microRNA target predictions) or co-location. The results of each analysis step can be visualized in a number of ways. The complete protocol can be executed in approximately 1 h.

A comprehensive library of fluorescent transcriptional reporters for Escherichia coli.

E. coli is widely used for systems biology research; there exists a need, however, for tools that can be used to accurately and comprehensively measure expression dynamics in individual living cells. To address this we present a library of transcriptional fusions of gfp to each of about 2,000 different promoters in E. coli K12, covering the great majority of the promoters in the organism. Each promoter fusion is expressed from a low-copy plasmid. We demonstrate that this library can be used to obtain highly accurate dynamic measurements of promoter activity on a genomic scale, in a glucose-lactose diauxic shift experiment. The library allowed detection of about 80 previously uncharacterized transcription units in E. coli, including putative internal promoters within previously known operons, such as the lac operon. This library can serve as a tool for accurate, high-resolution analysis of transcription networks in living E. coli cells.

Plasticity of the cis-regulatory input function of a gene.

The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.