Doxycycline-mediated quantitative and tissue-specific control of gene expression in transgenic mice.

The tet regulatory system in which doxycycline (dox) acts as an inducer of specifically engineered RNA polymerase II promoters was transferred into transgenic mice. Tight control and a broad range of regulation spanning up to five orders of magnitude were monitored dependent on the dox concentration in the water supply of the animals. Administration of dox rapidly induces the synthesis of the indicator enzyme luciferase whose activity rises over several orders of magnitude within the first 4 h in some organs. Induction is complete after 24 h in most organs analyzed. A comparable regulatory potential was revealed with the tet regulatory system where dox prevents transcription activation. Directing the synthesis of the tetracycline-controlled transactivator (tTA) to the liver led to highly specific regulation in hepatocytes where, in presence of dox, less than one molecule of luciferase was detected per cell. By contrast, a more than 10(5)-fold activation of the luciferase gene was observed in the absence of the antibiotic. This regulation was homogeneous throughout but stringently restricted to hepatocytes. These results demonstrate that both tetracycline-controlled transcriptional activation systems provide genetic switches that permit the quantitative control of gene activities in transgenic mice in a tissue-specific manner and, thus, suggest possibilities for the generation of a novel type of conditional mutants.

The human lysozyme promoter directs reporter gene expression to activated myelomonocytic cells in transgenic mice.

The 5' region of the human lysozyme gene from -3500 to +25 was fused to a chloramphenicol acetyltransferase (CAT) reporter gene and three transgenic founder mice were obtained. All three transgenic lines showed the same pattern of CAT enzyme expression in adult mouse tissues that was consistent with the targeting of elicited, activated macrophages in tissues and developing and elicited granulocytes. In normal mice high CAT enzyme activity was found in the spleen, lung, and thymus, tissues rich in phagocytically active cells, but not in many other tissues, such as the gut and muscle, which contain resident macrophages. Cultured resident peritoneal macrophages and cells elicited 18 hr (granulocytes) and 4 days (macrophages) after injection of sterile thioglycollate broth expressed CAT activity. Bacillus Calmette-Guérin infection of transgenic mice resulted in CAT enzyme expression in the liver, which contained macrophage-rich granulomas, whereas the liver of uninfected mice did not have any detectable CAT enzyme activity. Although the Paneth cells of the small intestine in both human and mouse produce lysozyme, the CAT gene, under the control of the human lysozyme promoter, was not expressed in the mouse small intestine. These results indicate that the human lysozyme promoter region may be used to direct expression of genes to activated mouse myeloid cells.

Orchestration of gene expression across the seasons : Hypothalamic gene expression in natural photoperiod throughout the year in the Siberian hamster

Funding for work in the laboratory of PB was supported by Scottish Government Rural and Environment Science and Analytical Services Division, BBSRC (grant BB/M001504/1), British Society for Neuroendocrinology (research visit grant to IP). Work in the laboratory of SS was supported by a grant from the DFG (Ste 331/8-1). We thank Siegried Hilken, Marianne Brüning, Dr. Esther Lipokatic-Takacs and Dr. Frank Scherbarth at UVMH for technical assistance. We thank Graham Horgan of Bioinformatics, Statistics Scotland for assistance with some of statistical tests.

In vivo gene expression: DNA electrotransfer

The use of electric pulses to deliver therapeutic molecules to tissues and organs in vivo is a rapidly growing field of research. Electrotransfer can be used to deliver a wide range of potentially therapeutic agents, including drugs, proteins, oligonucleotides, RNA and DNA. Optimization of this approach depends upon a number of parameters such as target organ accessibility, cell turnover, microelectrode design, electric pulsing protocols and the physiological response to the therapeutic agent. Many organs have been successfully transfected by electroporation, including skin, liver, skeletal and cardiac muscle, male and female germ cells, artery, gut, kidney, retinal ganglion cells, cornea, spinal cord, joint synovium and brain. Electrotransfer technology is relevant in a variety of research and clinical settings including cancer therapy, modulation of pathogenic immune reactions, delivery of therapeutic proteins and drugs, and the identification of drug targets by the modulation of normal gene expression. This, together with the capacity to deliver very large DNA constructs, greatly expands the research and clinical applications of in vivo DNA electrotransfer.

Genes and gene expression in the brains of human alcoholics

Chronic alcohol misuse by human subjects leads to neuronal loss in regions such as the superior frontal cortex (SFC). Propensity to alcoholism is associated with several genes. γ-Aminobutyric acid (GABA)A receptor expression differs between alcoholics and controls, whereas glutamate receptor differences are muted. We determined whether genotype differentiated the regional presentation of GABAA and glutamate-NMDA (N-methyl-d-aspartate) receptors in SFC. Autopsy tissue was obtained from alcoholics without comorbid disease, alcoholics with liver cirrhosis, and matched controls. ADH1C, DRD2B, EAAT2, and APOE genotypes modulated GABAA-β subunit protein expression in SFC toward a less-effective form of the receptor. Most genotypes did not divide alcoholics and controls on glutamate-NMDA receptor pharmacology, although gender and cirrhosis did. Genotype may affect amino acid transmission locally to influence neuronal vulnerability.

Long Chain Saturated Fatty Acids Increase Haptoglobin Gene Expression in C57BL/6J Mice Adipose Tissue and 3T3-L1 Cells

Background Dietary lipids are directly related to the composition of adipose tissue, aetiology of obesity and arousal of obesity-related pathologies, like chronic inflammation states. Haptoglobin is an acute phase protein secreted by the liver and white adipose tissue, and its blood levels vary according to the volume of fat in the body. Aim of the study To investigate the effect of diets enriched with large amounts of dietary fats, which differ in their fatty acid composition, on the haptoglobin gene expression by visceral and subcutaneous adipose tissue of mice fed for 2 days or 8 weeks. 3T3-L1 cells were treated with fatty acids that are found in those types of dietary fats. Methods Mice were treated acutely (for 2 days) or chronically (for 8 weeks) with diets enriched with soybean oil, fish oil, coconut oil or lard. 3T3-L1 cells were treated with six different fatty acids. Haptoglobin gene expression was quantified by northern blotting. Results Both chronic and acute treatment with lard, which is rich in long chain saturated fatty acids, increased the haptoglobin mRNA expression in the retroperitoneal and epidydimal white adipose tissues. Chronic treatment with coconut oil, which is rich in medium chain saturated fatty acids, increased the haptoglobin expression in the epidydimal and subcutaneous depots. In 3T3-L1, palmitic acid increased the haptoglobin gene expression. Conclusion The type of lipids in the diet can differently modulate the white adipose tissue gene expression of haptoglobin, and saturated fatty acids play a major role in promoting a pro-inflammatory environment. This response is fat pad specific and dependant on the duration of treatment.

Whole Genome Analysis of Gene Expression Reveals Coordinated Activation of Signaling and Metabolic Pathways during Pollen-Pistil Interactions in Arabidopsis

Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.

Immune function, gene expression, blood indices and performance in transition dairy cows affected by diet and inflammation

The transition period is associated with the peak incidence of production problems, metabolic disorders and infectious diseases in dairy cows (Drackley, 1999). During this time the cow’s immune system seems to be weakened; it is apparent that metabolic challenges associated with the onset of lactation are factors capable of affecting immune function. However, the reasons for this state are not entirely clear (Goff, 2006). The negative energy balance associated with parturition leads to extensive mobilization of fatty acids stored in adipose tissue, thus, causing marked elevations in blood non-esterified fatty acids (NEFA) and B-hydroxybutyrate (BHBA) concentrations (Drackley et al., 2001). Prepartal level of dietary energy can potentially affect adipose tissue deposition and, thus, the amount of NEFA released into blood and available for metabolism in liver (Drackley et al., 2005). The current feeding practices for pregnant non-lactating cows has been called into question because increasing amounts of moderate-to-high energy diets (i.e. those more similar to lactation diets in the content of energy) during the last 3 wk postpartum have largely failed to overcome peripartal health problems, excessive body condition loss after calving, or declining fertility (Beever, 2006). Current prepartal feeding practices can lead to elevated intakes of energy, which can increase fat deposition in the viscera and upon parturition lead to compromised liver metabolism (Beever, 2006, Drackley et al., 2005). Our general hypothesis was that overfeeding dietary energy during the dry period, accompanied by the metabolic challenges associated with the onset of lactation would render the cow’s immune function less responsive early postpartum. The chapters in this dissertation evaluated neutrophil function, metabolic and inflammation indices and gene expression affected by the plane of dietary energy prepartum and an early post-partum inflammatory challenge in dairy cows. The diet effect in this experiment was transcendental during the transition period and potentially during the entire lactation. Changes in energy balance were observed and provided a good model to study the challenges associated with the onset of lactation. Overall the LPS model provided a consistent response representing an inflammation incident; however the changes in metabolic indices were sudden and hard to detect in most of the cases during the days following the challenge. In general overfeeding dietary energy during the dry period resulted in a less responsive immune function during the early postpartum. In other words, controlling the dietary energy prepartum has more benefits for the dairy cow during transition.

Identifying cancer-related microRNAs based on gene expression data

International audience

Identification Of Target Genes Using Gene Expression Profile Of Granulocytes From Patients With Chronic Myeloid Leukemia Treated With Tyrosine Kinase Inhibitors.

Differential gene expression analysis by suppression subtractive hybridization with correlation to the metabolic pathways involved in chronic myeloid leukemia (CML) may provide a new insight into the pathogenesis of CML. Among the overexpressed genes found in CML at diagnosis are SEPT5, RUNX1, MIER1, KPNA6 and FLT3, while PAN3, TOB1 and ITCH were decreased when compared to healthy volunteers. Some genes were identified and involved in CML for the first time, including TOB1, which showed a low expression in patients with CML during tyrosine kinase inhibitor treatment with no complete cytogenetic response. In agreement, reduced expression of TOB1 was also observed in resistant patients with CML compared to responsive patients. This might be related to the deregulation of apoptosis and the signaling pathway leading to resistance. Most of the identified genes were related to the regulation of nuclear factor κB (NF-κB), AKT, interferon and interleukin-4 (IL-4) in healthy cells. The results of this study combined with literature data show specific gene pathways that might be explored as markers to assess the evolution and prognosis of CML as well as identify new therapeutic targets.

Hypothyroidism decreases proinsulin gene expression and the attachment of its mRNA and eEF1A protein to the actin cytoskeleton of INS-1E cells

The actions of thyroid hormone (TH) on pancreatic beta cells have not been thoroughly explored, with current knowledge being limited to the modulation of insulin secretion in response to glucose, and beta cell viability by regulation of pro-mitotic and pro-apoptotic factors. Therefore, the effects of TH on proinsulin gene expression are not known. This led us to measure: a) proinsulin mRNA expression, b) proinsulin transcripts and eEF1A protein binding to the actin cytoskeleton, c) actin cytoskeleton arrangement, and d) proinsulin mRNA poly(A) tail length modulation in INS-1E cells cultured in different media containing: i) normal fetal bovine serum - FBS (control); ii) normal FBS plus 1 µM or 10 nM T3, for 12 h, and iii) FBS depleted of TH for 24 h (Tx). A decrease in proinsulin mRNA content and attachment to the cytoskeleton were observed in hypothyroid (Tx) beta cells. The amount of eEF1A protein anchored to the cytoskeleton was also reduced in hypothyroidism, and it is worth mentioning that eEF1A is essential to attach transcripts to the cytoskeleton, which might modulate their stability and rate of translation. Proinsulin poly(A) tail length and cytoskeleton arrangement remained unchanged in hypothyroidism. T3 treatment of control cells for 12 h did not induce any changes in the parameters studied. The data indicate that TH is important for proinsulin mRNA expression and translation, since its total amount and attachment to the cytoskeleton are decreased in hypothyroid beta cells, providing evidence that effects of TH on carbohydrate metabolism also include the control of proinsulin gene expression.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Xylella fastidiosa gene expression analysis by DNA microarrays

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Yerba Maté (Ilex paraguariensis) aqueous extract decreases intestinal SGLT1 gene expression but does not affect other biochemical parameters in alloxan-diabetic wistar rats

Yerba mate´ (Ilex paraguariensis) is rich in polyphenols, especially chlorogenic acids. Evidence suggests that dietary polyphenols could play a role in glucose absorption and metabolism. The aim of this study was to evaluate the antidiabetic properties of yerba mate´ extract in alloxan-induced diabetic Wistar rats. Animals (n ) 41) were divided in four groups: nondiabetic control (NDC, n=11), and diabetic yerba maté (DY, n = 10). The intervention consisted in the administration of yerba mate´ extract in a 1 g extract/ kg body weight dose for 28 days; controls received saline solution only. There were no significant differences in serum glucose, insulin, and hepatic glucose-6-phosphatase activity between the groups that ingested yerba maté extract (NDY and DY) and the controls (NDC and DC). However, the intestinal SGLT1 gene expression was significantly lower in animals that received yerba maté both in upper (p = 0.007) and middle (p < 0.001) small intestine. These results indicate that bioactive compounds present in yerba maté might be capable of interfering in glucose absorption, by decreasing SGLT1 expression

The full Bayesian significance test for mixture models: results in gene expression clustering

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method's sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results.