EDISA: extracting biclusters from multiple time-series of gene expression profiles

Background  

Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consisting of co-regulated genes. A growing pool of publicly available microarray datasets allows the identification of modules by monitoring expression changes over time. These time-series datasets can be searched for gene expression modules by one of the many clustering methods published to date. For an integrative analysis, several time-series datasets can be joined into a three-dimensional gene-condition-time dataset, to which standard clustering or biclustering methods are, however, not applicable. We thus devise a probabilistic clustering algorithm for gene-condition-time datasets.     

Integrated olfactory receptor and microarray gene expression databases

Background  

Gene expression patterns of olfactory receptors (ORs) are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD) to house OR gene expression data. ORMD is integrated with the Olfactory Receptor Database (ORDB), which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction.     

Network analysis of skin tumor progression identifies a rewired genetic architecture affecting inflammation and tumor susceptibility

Background  

Germline polymorphisms can influence gene expression networks in normal mammalian tissues and can affect disease susceptibility. We and others have shown that analysis of this genetic architecture can identify single genes and whole pathways that influence complex traits, including inflammation and cancer susceptibility. Whether germline variants affect gene expression in tumors that have undergone somatic alterations, and the extent to which these variants influence tumor progression, is unknown.     

Expression profiling of human glial precursors

Background  

We have generated gene expression databases for human glial precursors, neuronal precursors, astrocyte precursors and neural stem cells and focused on comparing the profile of glial precursors with that of other populations.     

Effects of mRNA amplification on gene expression ratios in cDNA experiments estimated by analysis of variance

Background  

A limiting factor of cDNA microarray technology is the need for a substantial amount of RNA per labeling reaction. Thus, 20–200 micro-grams total RNA or 0.5–2 micro-grams poly (A) RNA is typically required for monitoring gene expression. In addition, gene expression profiles from large, heterogeneous cell populations provide complex patterns from which biological data for the target cells may be difficult to extract. In this study, we chose to investigate a widely used mRNA amplification protocol that allows gene expression studies to be performed on samples with limited starting material. We present a quantitative study of the variation and noise present in our data set obtained from experiments with either amplified or non-amplified material.     

Evaluation of methods for oligonucleotide array data via quantitative real-time PCR

Background  

There are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the "gold-standard" assay.     

Conditional gene expression in the mouse using a Sleeping Beauty gene-trap transposon

Background  

Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB) transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern.     

Manipulation of gene expression by an ecdysone-inducible gene switch in tumor xenografts

Background  

Rapid, robust and reversible induction of transgene expression would significantly facilitate cancer gene therapy as well as allow the in vivo functional study of newly discovered genes in tumor formation and progression. The popularity of the ecdysone inducible gene switch system has led us to investigate whether such a system can successfully regulate gene expression in a syngeneic tumor system in vivo.     

Gene expression analysis on small numbers of invasive cells collected by chemotaxis from primary mammary tumors of the mouse

Background  

cDNA microarrays have the potential to identify the genes involved in invasion and metastasis. However, when used with whole tumor tissue, the results average the expression patterns of different cell types. We have combined chemotaxis-based cell collection of the invasive subpopulation of cells within the primary tumor with array-based gene expression analysis to identify the genes necessary for the process of carcinoma cell invasion.     

Subinhibitory concentrations of antibiotics affect stress and virulence gene expression in Listeria monocytogenes and cause enhanced stress sensitivity but do not affect Caco‐2 cell invasion

Aims

Antibiotics can act as signal molecules and affect bacterial gene expression, physiology and virulence. The purpose of this study was to determine whether subinhibitory antibiotic concentrations alter gene expression and physiology of Listeria monocytogenes.

Methods and Results

Using an agar‐based screening assay with promoter fusions, 14 of 16 antibiotics induced or repressed expression of one or more stress and/or virulence genes. Despite ampicillin‐induced up‐regulation of PinlA‐lacZ expression, Caco‐2 cell invasion was not affected. Subinhibitory concentrations of ampicillin and tetracycline caused up‐ and down‐regulation of stress response genes, respectively, but both antibiotics caused increased sensitivity to acid stress. Six combinations of gene‐antibiotic were quantified in broth cultures and five of the six resulted in the same expression pattern as the agar‐based assay.

Conclusions

Antibiotics affect virulence and/or stress gene expression; however, altered expression could not predict changes in phenotypic behaviour. Subinhibitory concentrations of antibiotics led to increased acid sensitivity, and we speculate that this is attributed to changes in cell envelope or reduced σ^B‐dependent gene expression.

Significance and Impact of the Study

Although subinhibitory concentrations of antibiotics affect gene expression in L. monocytogenes, the changes did not increase virulence but did enhance the acid sensitivity.     

Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments

Background  

The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating variability of gene expression measurements in microarray experiments is essential for correctly identifying differentially expressed genes. Several recently developed methods for testing differential expression of genes utilize hierarchical Bayesian models to "pool" information from multiple genes. We have developed a statistical testing procedure that further improves upon current methods by incorporating the well-documented relationship between the absolute gene expression level and the variance of gene expression measurements into the general empirical Bayes framework.     

Using multiplexed regulation of luciferase activity and GFP translocation to screen for FOXO modulators

Background  

Independent luciferase reporter assays and fluorescent translocation assays have been successfully used in drug discovery for several molecular targets. We developed U2transLUC, an assay system in which luciferase and fluorescent read-outs can be multiplexed to provide a powerful cell-based high content screening method.     

Generation and characterization of a Tet-On (rtTA-M2) transgenic rat

Background  

The tetracycline-inducible gene regulation system is a powerful tool that allows temporal and dose-dependent regulation of target transgene expression in vitro and in vivo. Several tetracycline-inducible transgenic mouse models have been described with ubiquitous or tissue-specific expression of tetracycline-transactivator (tTA), reverse tetracycline-transactivator (rtTA) or Tet repressor (TetR). Here we describe a Tet-On transgenic rat that ubiquitously expresses rtTA-M2 driven by the murine ROSA 26 promoter.     

Alkane-induced expression,substrate binding profile,and immunolocalization of a cytochrome P450 encoded on the <Emphasis Type="Italic">nifD</Emphasis> excision element of <Emphasis Type="Italic">Anabaena</Emphasis> 7120

Background  

Alkanes have been hypothesized to act as universal inducers of bacterial cytochrome P450 gene expression. We tested this hypothesis on an unusual P450 gene (cyp110) found on a conserved 11 kilobase episomal DNA element of unknown function found in filamentous cyanobacteria. We also monitored the binding of potential substrates to the P450 protein and explored the distribution of P450 protein in vegetative cells and nitrogen-fixing heterocysts using immuno-electron microscopy.