The Regulation of Rasd1 Expression by Glucocorticoids and Prolactin Controls Peripartum Maternal Insulin Secretion

The transition from gestation to lactation is characterized by a robust adaptation of maternal pancreatic beta-cells. Consistent with the loss of beta-cell mass, glucose-induced insulin secretion is down-regulated in the islets of early lactating dams. Extensive experimental evidence has demonstrated that the surge of prolactin is responsible for the morphofunctional remodeling of the maternal endocrine pancreas during pregnancy, but the precise molecular mechanisms by which this phenotype is rapidly reversed after delivery are not completely understood. This study investigated whether glucocorticoid-regulated expression of Rasd1/Dexras, a small inhibitoryGprotein, is involved in this physiological plasticity. Immunofluorescent staining demonstrated that Rasd1 is localized within pancreatic beta-cells. Rasd1 expression in insulin-secreting cells was increased by dexamethasone and decreased by prolactin. In vivo data confirmed that Rasd1 expression is decreased in islets from pregnant rats and increased in islets from lactating mothers. Knockdown of Rasd1 abolished the inhibitory effects of dexamethasone on insulin secretion and the protein kinase A, protein kinase C, and ERK1/2 pathways. Chromatin immunoprecipitation experiments revealed that glucocorticoid receptor (GR) and signal transducer and activator of transcription 5b (STAT5b) cooperatively mediate glucocorticoid-induced Rasd1 expression in islets. Prolactin inhibited the stimulatory effect of GR/STAT5b complex on Rasd1 transcription. Overall, our data indicate that the stimulation of Rasd1 expression by glucocorticoid at the end of pregnancy reverses the increased insulin secretion that occurs during pregnancy. Prolactin negatively regulates this pathway by inhibiting GR/STAT5b transcriptional activity on the Rasd1 gene. (Endocrinology 153: 3668-3678, 2012)

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.

Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays

Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Adjunct effect of the antimicrobial photodynamic therapy to an association of non-surgical and surgical periodontal treatment in modulation of gene expression

Background: This study has evaluated the effect of antimicrobial photodynamic therapy (aPDT) used in conjunction with non-surgical and surgical periodontal treatment (PT) in modulating gene expression during periodontal wound healing. Methods: Fifteen patients with chronic periodontitis, presenting bilaterally lower molars with class III furcation lesions and scheduled for extraction, were selected. In initial therapy, scaling and root planing (SRP) was performed in the Control Group (CG), while SRP + aPDT were performed in the Test Group (TG). 45 days later, flap surgery plus SRP, and flap surgery plus SRP + aPDT were performed in the CG and TG, respectively. At 21 days post-surgery, the newly formed granulation tissue was collected, and Real-time PCR evaluated the expression of the genes: tumor necrosis factor-?, interleukin-1?, interleukin-4, interleukin-10, matrix metalloproteinase-2 (MMP-2), tissue inhibitor of metalloproteinase-2 (TIMP-2), osteoprotegerin (OPG), receptor activator of nuclear factor- ?B ligand (RANKL), type I collagen, alkaline phosphatase, osteopontin, osteocalcin, and bone sialoprotein. Results: There were statistically significant differences between the groups in relation to mRNA levels for MMP-2 (TG = 3.26 ± 0.89; CG = 4.23 ± 0.97; p = 0.01), TIMP-2/MMP-2 ratio (TG = 0.91 ± 0.34; CG = 0.73 ± 0.32; p = 0.04), OPG (TG = 0.84 ± 0.45; CG = 0.30 ± 0.26; p = 0.001), and OPG/RANKL ratio (TG = 0.60 ± 0.86; CG = 0.23 ± 0.16; p = 0.04), favoring the TG. Conclusion: The present data suggest that the aPDT associated to nonsurgical and surgical periodontal therapy may modulate the extracellular matrix and bone remodeling by up regulating the TIMP- 2/MMP-2 and OPG/RANKL mRNA ratio, but the clinical relevance needs to be evaluated in further studies.

Regulation of TRAIL expression by PRAME and EZH2 as potential therapeutic target against solid tumors

We thank the Department of Pathologic Anatomy and the International Center for Research, from AC Camargo Hospital for the tissue microarray assays and for the donation of cancer cell lines, respectively. We thank Dr. René Bernards (Amsterdam, The Netherlands) for the gift of PRAME and EZH2 short hairpin RNA vectors.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Oral leucine supplementation is sensed by the brain but neither reduces food intake nor induces an anorectic pattern of gene expression in the hypothalamus

Leucine activates the intracellular mammalian target of the rapamycin (mTOR) pathway, and hypothalamic mTOR signaling regulates food intake. Although central infusion of leucine reduces food intake, it is still uncertain whether oral leucine supplementation is able to affect the hypothalamic circuits that control energy balance. We observed increased phosphorylation of p70s6k in the mouse hypothalamus after an acute oral gavage of leucine. We then assessed whether acute oral gavage of leucine induces the activation of neurons in several hypothalamic nuclei and in the brainstem. Leucine did not induce the expression of Fos in hypothalamic nuclei, but it increased the number of Fos-immunoreactive neurons in the area postrema. In addition, oral gavage of leucine acutely increased the 24 h food intake of mice. Nonetheless, chronic leucine supplementation in the drinking water did not change the food intake and the weight gain of ob/ob mice and of wild-type mice consuming a low- or a high-fat diet. We assessed the hypothalamic gene expression and observed that leucine supplementation increased the expression of enzymes (BCAT1, BCAT2 and BCKDK) that metabolize branched-chain amino acids. Despite these effects, leucine supplementation did not induce an anorectic pattern of gene expression in the hypothalamus. In conclusion, our data show that the brain is able to sense oral leucine intake. However, the food intake is not modified by chronic oral leucine supplementation. These results question the possible efficacy of leucine supplementation as an appetite suppressant to treat obesity

Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the σ54 regulon

Abstract Background Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a σ54-dependent manner. A more complete picture of the σ54 regulon was achieved by combining the transcriptome data with an in silico search for potential σ54-dependent promoters, using a position weight matrix approach. One of these σ54-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a σ54-dependent promoter. Conclusions Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the σ54 regulon.

Genome mapping and expression analyses of human intronic noncoding RNAs reveal tissue-specific patterns and enrichment in genes related to regulation of transcription

Abstract Background RNAs transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression. However, the complement of human genes in which introns are transcribed, and the number of intronic transcriptional units and their tissue expression patterns are not known. Results A survey of mRNA and EST public databases revealed more than 55,000 totally intronic noncoding (TIN) RNAs transcribed from the introns of 74% of all unique RefSeq genes. Guided by this information, we designed an oligoarray platform containing sense and antisense probes for each of 7,135 randomly selected TIN transcripts plus the corresponding protein-coding genes. We identified exonic and intronic tissue-specific expression signatures for human liver, prostate and kidney. The most highly expressed antisense TIN RNAs were transcribed from introns of protein-coding genes significantly enriched (p = 0.002 to 0.022) in the 'Regulation of transcription' Gene Ontology category. RNA polymerase II inhibition resulted in increased expression of a fraction of intronic RNAs in cell cultures, suggesting that other RNA polymerases may be involved in their biosynthesis. Members of a subset of intronic and protein-coding signatures transcribed from the same genomic loci have correlated expression patterns, suggesting that intronic RNAs regulate the abundance or the pattern of exon usage in protein-coding messages. Conclusion We have identified diverse intronic RNA expression patterns, pointing to distinct regulatory roles. This gene-oriented approach, using a combined intron-exon oligoarray, should permit further comparative analysis of intronic transcription under various physiological and pathological conditions, thus advancing current knowledge about the biological functions of these noncoding RNAs.

Amygdala gene expression of NMDA and GABAA receptors in patients with mesial temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is the most common form of partial epilepsy and affects 40% of the patients. Seizures arising from the mesial temporal lobe structures (i.e., amygdala and hippocampus) are common, whereas neocortical seizures are rare. In recent years, many studies aimed to identify the pattern of gene expression of neurotransmitters involved in molecular mechanisms of epilepsy. We used real-time PCR to quantify the expression of GABAA (subunits a1, beta 1, beta 2) and NMDA (subunits NR1, NR2A, and NR2B) receptor genes in amygdalae of 27 patients with TLE and 14 amygdalae from autopsy controls. The NR1 subunit was increased in patients with epilepsy when compared with controls. No differences were found in expression of NMDA subunits NR2A and NR2B or in a1, beta 1, and beta 2 subunits of GABAA receptors. Our results suggest that the NR1 subunit of NMDA receptors is involved in the amygdala hyperexcitability in some of the patients with TLE. (C) 2010 Wiley Periodicals, Inc., Inc.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

Pancreatic islets from dexamethasone-treated rats show alterations in global gene expression and mitochondrial pathways

Chronic administration of glucocorticoids (GC) leads to characteristic features of type 2 diabetes in mammals. The main action of dexamethasone in target cells occurs through modulation of gene expression, although the exact mechanisms are still unknown. We therefore investigated the gene expression profile of pancreatic islets from rats treated with dexamethasone using a cDNA array screening analysis. The expression of selected genes and proteins involved in mitochondria] apoptosis was further analyzed by PCR and immunoblotting. Insulin, triglyceride and free fatty acid plasma levels, as well as glucose-induced insulin secretion, were significantly higher in dexamethasone-treated rats compared with controls. Out of 1176 genes, 60 were up-regulated and 28 were down-regulated by dexamethasone treatment. Some of the modulated genes are involved in apoptosis, stress response, and proliferation pathways. RT-PCR confirmed the cDNA array results for 6 selected genes. Bax alpha protein expression was increased, while Bcl-2 was decreased. In vivo dexamethasone treatment decreased the mitochondrial production of NAD(P)H, and increased ROS production. Concluding, our data indicate that dexamethasone modulates the expression of genes and proteins involved in several pathways of pancreatic-islet cells, and mitochondria dysfunction might be involved in the deleterious effects after long-term GC treatment.

Changes in hippocampal gene expression by 7-nitroindazole in rats submitted to forced swimming stress

Nitric oxide (NO) is an atypical neurotransmitter that has been related to the pathophysiology of major depression disorder. Increased plasma NO levels have been reported in depressed and suicidal patients. Inhibition of neuronial nitric oxide synthase (nNOS), on the other hand, induces antidepressant effects in clinical and pre-clinical trials. The mechanisms responsible for the antidepressant-like effects of nNOS inhibitors, however, are not completely understood. In this study, genomic and proteomic analyses were used to investigate the effects of the preferential nNOS inhibitor 7-nitroindazole (7-NI) on changes in global gene and protein expression in the hippocampus of rats submitted to forced swimming test (FST). Chronic treatment (14 days, i.p.) with imipramine (15 mg/kg daily) or 7-NI (60 mg/kg daily) significantly reduced immobility in the FST. Saturation curves for Serial analysis of gene expression libraries showed that the hippocampus of animals submitted to FST presented a lower number of expressed genes compared to non-FST stressed groups. Imipramine, but not 7-NI, reverted this effect. GeneGo analyses revealed that genes related to oxidative phosphorylation, apoptosis and survival controlled by HTR1A signaling and cytoskeleton remodeling controlled by Rho GTPases were significantly changed by FST. 7-NI prevented this effect. In addition, 7-NI treatment changed the expression of genes related to transcription in the cAMP response element-binding pathway. Therefore, this study suggests that changes in oxidative stress and neuroplastic processes could be involved in the antidepressant-like effects induced by nNOS inhibition.

rpb2 is a reliable reference gene for quantitative gene expression analysis in the dermatophyte Trichophyton rubrum

The selection of reference genes used for data normalization to quantify gene expression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for gene expression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of gene expression under several experimental conditions, with improved accuracy and reliability.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.