81,950 research outputs found

    Temporal regulation of expression of immediate early and second phase transcripts by endothelin-1 in cardiomyocytes

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    Background: Endothelin-1 stimulates Gq protein-coupled receptors to promote proliferation in dividing cells or hypertrophy in terminally differentiated cardiomyocytes. In cardiomyocytes, endothelin-1 rapidly (within minutes) stimulates protein kinase signaling, including extracellular-signal regulated kinases 1/2 (ERK1/2; though not ERK5), with phenotypic/physiological changes developing from approximately 12 h. Hypertrophy is associated with changes in mRNA/protein expression, presumably consequent to protein kinase signaling, but the connections between early, transient signaling events and developed hypertrophy are unknown. Results: Using microarrays, we defined the early transcriptional responses of neonatal rat cardiomyocytes to endothelin-1 over 4 h, differentiating between immediate early gene (IEG) and second phase RNAs with cycloheximide. IEGs exhibited differential temporal and transient regulation, with expression of second phase RNAs within 1 h. Of transcripts upregulated at 30 minutes encoding established proteins, 28 were inhibited >50% by U0126 (which inhibits ERK1/2/5 signaling), with 9 inhibited 25-50%. Expression of only four transcripts was not inhibited. At 1 h, most RNAs (approximately 67%) were equally changed in total and polysomal RNA with approximately 17% of transcripts increased to a greater extent in polysomes. Thus, changes in expression of most protein-coding RNAs should be reflected in protein synthesis. However, approximately 16% of transcripts were essentially excluded from the polysomes, including some protein-coding mRNAs, presumably inefficiently translated. Conclusion: The phasic, temporal regulation of early transcriptional responses induced by endothelin-1 in cardiomyocytes indicates that, even in terminally differentiated cells, signals are propagated beyond the primary signaling pathways through transcriptional networks leading to phenotypic changes (that is, hypertrophy). Furthermore, ERK1/2 signaling plays a major role in this response

    Gill transcriptome response to changes in environmental calcium in the green spotted puffer fish

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    Abstract Background Calcium ion is tightly regulated in body fluids and for euryhaline fish, which are exposed to rapid changes in environmental [Ca2+], homeostasis is especially challenging. The gill is the main organ of active calcium uptake and therefore plays a crucial role in the maintenance of calcium ion homeostasis. To study the molecular basis of the short-term responses to changing calcium availability, the whole gill transcriptome obtained by Super Serial Analysis of Gene Expression (SuperSAGE) of the euryhaline teleost green spotted puffer fish, Tetraodon nigroviridis, exposed to water with altered [Ca2+] was analysed. Results Transfer of T. nigroviridis from 10 ppt water salinity containing 2.9 mM Ca2+ to high (10 mM Ca2+ ) and low (0.01 mM Ca2+) calcium water of similar salinity for 2-12 h resulted in 1,339 differentially expressed SuperSAGE tags (26-bp transcript identifiers) in gills. Of these 869 tags (65%) were mapped to T. nigroviridis cDNAs or genomic DNA and 497 (57%) were assigned to known proteins. Thirteen percent of the genes matched multiple tags indicating alternative RNA transcripts. The main enriched gene ontology groups belong to Ca2+ signaling/homeostasis but also muscle contraction, cytoskeleton, energy production/homeostasis and tissue remodeling. K-means clustering identified co-expressed transcripts with distinct patterns in response to water [Ca2+] and exposure time. Conclusions The generated transcript expression patterns provide a framework of novel water calcium-responsive genes in the gill during the initial response after transfer to different [Ca2+]. This molecular response entails initial perception of alterations, activation of signaling networks and effectors and suggests active remodeling of cytoskeletal proteins during the initial acclimation process. Genes related to energy production and energy homeostasis are also up-regulated, probably reflecting the increased energetic needs of the acclimation response. This study is the first genome-wide transcriptome analysis of fish gills and is an important resource for future research on the short-term mechanisms involved in the gill acclimation responses to environmental Ca2+ changes and osmoregulation.Peer Reviewe

    Probing host pathogen cross-talk by transcriptional profiling of both Mycobacterium tuberculosis and infected human dendritic cells and macrophages

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    This study provides the proof of principle that probing the host and the microbe transcriptomes simultaneously is a valuable means to accessing unique information on host pathogen interactions. Our results also underline the extraordinary plasticity of host cell and pathogen responses to infection, and provide a solid framework to further understand the complex mechanisms involved in immunity to M. tuberculosis and in mycobacterial adaptation to different intracellular environments

    Enteric helminths promote Salmonella co-infection by altering the intestinal metabolome

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    Intestinal helminth infections occur pre dominantly in regions where exposure to enteric bacterial pathogens is also common. Helminth infections inhibit host immunity against microbial pathogens, which has largely been attributed to the induction of regulatory or type 2 (Th2) immune responses. Here we demonstrate an additional three-way interaction in which helminth infection alters the metabolic environment of the host intestine to enhance bacterial pathogenicity. We show that an ongoing helminth infection increased colonization by Salmonella independently of T regulatory or Th2 cells. Instead, helminth infection altered the metabolic profile of the intestine, which directly enhanced bacterial expression of Salmonella pathogenicity island 1 (SPI-1) genes and increased intracellular invasion. These data reveal a novel mechanism by which a helminth-modified metabolome promotes susceptibility to bacterial co-infection

    Statistical modelling of transcript profiles of differentially regulated genes

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    Background: The vast quantities of gene expression profiling data produced in microarray studies, and the more precise quantitative PCR, are often not statistically analysed to their full potential. Previous studies have summarised gene expression profiles using simple descriptive statistics, basic analysis of variance (ANOVA) and the clustering of genes based on simple models fitted to their expression profiles over time. We report the novel application of statistical non-linear regression modelling techniques to describe the shapes of expression profiles for the fungus Agaricus bisporus, quantified by PCR, and for E. coli and Rattus norvegicus, using microarray technology. The use of parametric non-linear regression models provides a more precise description of expression profiles, reducing the "noise" of the raw data to produce a clear "signal" given by the fitted curve, and describing each profile with a small number of biologically interpretable parameters. This approach then allows the direct comparison and clustering of the shapes of response patterns between genes and potentially enables a greater exploration and interpretation of the biological processes driving gene expression. Results: Quantitative reverse transcriptase PCR-derived time-course data of genes were modelled. "Splitline" or "broken-stick" regression identified the initial time of gene up-regulation, enabling the classification of genes into those with primary and secondary responses. Five-day profiles were modelled using the biologically-oriented, critical exponential curve, y(t) = A + (B + Ct)Rt + ε. This non-linear regression approach allowed the expression patterns for different genes to be compared in terms of curve shape, time of maximal transcript level and the decline and asymptotic response levels. Three distinct regulatory patterns were identified for the five genes studied. Applying the regression modelling approach to microarray-derived time course data allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p < 0.05. Conclusion: The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes
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