Nuclear factor I-C links platelet-derived growth factor and transforming growth factor beta1 signaling to skin wound healing progression.

Transforming growth factor beta (TGF-beta) and platelet-derived growth factor A (PDGFAlpha) play a central role in tissue morphogenesis and repair, but their interplay remain poorly understood. The nuclear factor I C (NFI-C) transcription factor has been implicated in TGF-beta signaling, extracellular matrix deposition, and skin appendage pathologies, but a potential role in skin morphogenesis or healing had not been assessed. To evaluate this possibility, we performed a global gene expression analysis in NFI-C(-/-) and wild-type embryonic primary murine fibroblasts. This indicated that NFI-C acts mostly to repress gene expression in response to TGF-beta1. Misregulated genes were prominently overrepresented by regulators of connective tissue inflammation and repair. In vivo skin healing revealed a faster inflammatory stage and wound closure in NFI-C(-/-) mice. Expression of PDGFA and PDGF-receptor alpha were increased in wounds of NFI-C(-/-) mice, explaining the early recruitment of macrophages and fibroblasts. Differentiation of fibroblasts to contractile myofibroblasts was also elevated, providing a rationale for faster wound closure. Taken together with the role of TGF-beta in myofibroblast differentiation, our results imply a central role of NFI-C in the interplay of the two signaling pathways and in regulation of the progression of tissue regeneration.

Ecdysone triggered PGRP-LC expression controls Drosophila innate immunity.

Throughout the animal kingdom, steroid hormones have been implicated in the defense against microbial infection, but how these systemic signals control immunity is unclear. Here, we show that the steroid hormone ecdysone controls the expression of the pattern recognition receptor PGRP-LC in Drosophila, thereby tightly regulating innate immune recognition and defense against bacterial infection. We identify a group of steroid-regulated transcription factors as well as two GATA transcription factors that act as repressors and activators of the immune response and are required for the proper hormonal control of PGRP-LC expression. Together, our results demonstrate that Drosophila use complex mechanisms to modulate innate immune responses, and identify a transcriptional hierarchy that integrates steroid signalling and immunity in animals.

Sumoylated PPARalpha mediates sex-specific gene repression and protects the liver from estrogen-induced toxicity in mice.

As most metabolic studies are conducted in male animals, understanding the sex specificity of the underlying molecular pathways has been broadly neglected; for example, whether PPARs elicit sex-dependent responses has not been determined. Here we show that in mice, PPARalpha has broad female-dependent repressive actions on hepatic genes involved in steroid metabolism and immunity. In male mice, this effect was reproduced by the administration of a synthetic PPARalpha ligand. Using the steroid oxysterol 7alpha-hydroxylase cytochrome P4507b1 (Cyp7b1) gene as a model, we elucidated the molecular mechanism of this sex-specific PPARalpha-dependent repression. Initial sumoylation of the ligand-binding domain of PPARalpha triggered the interaction of PPARalpha with GA-binding protein alpha (GABPalpha) bound to the target Cyp7b1 promoter. Histone deacetylase and DNA and histone methylases were then recruited, and the adjacent Sp1-binding site and histones were methylated. These events resulted in loss of Sp1-stimulated expression and thus downregulation of Cyp7b1. Physiologically, this repression conferred on female mice protection against estrogen-induced intrahepatic cholestasis, the most common hepatic disease during pregnancy, suggesting a therapeutic target for prevention of this disease.

Control of the adaptive response of the heart to stress via the Notch1 receptor pathway.

In the damaged heart, cardiac adaptation relies primarily on cardiomyocyte hypertrophy. The recent discovery of cardiac stem cells in the postnatal heart, however, suggests that these cells could participate in the response to stress via their capacity to regenerate cardiac tissues. Using models of cardiac hypertrophy and failure, we demonstrate that components of the Notch pathway are up-regulated in the hypertrophic heart. The Notch pathway is an evolutionarily conserved cell-to-cell communication system, which is crucial in many developmental processes. Notch also plays key roles in the regenerative capacity of self-renewing organs. In the heart, Notch1 signaling takes place in cardiomyocytes and in mesenchymal cardiac precursors and is activated secondary to stimulated Jagged1 expression on the surface of cardiomyocytes. Using mice lacking Notch1 expression specifically in the heart, we show that the Notch1 pathway controls pathophysiological cardiac remodeling. In the absence of Notch1, cardiac hypertrophy is exacerbated, fibrosis develops, function is altered, and the mortality rate increases. Therefore, in cardiomyocytes, Notch controls maturation, limits the extent of the hypertrophic response, and may thereby contribute to cell survival. In cardiac precursors, Notch prevents cardiogenic differentiation, favors proliferation, and may facilitate the expansion of a transient amplifying cell compartment.

Development of Ewing's sarcoma from primary bone marrow-derived mesenchymal progenitor cells.

Ewing's sarcoma is a member of Ewing's family tumors (EFTs) and the second most common solid bone and soft tissue malignancy of children and young adults. It is associated in 85% of cases with the t(11;22)(q24:q12) chromosomal translocation that generates fusion of the 5' segment of the EWS gene with the 3' segment of the ETS family gene FLI-1. The EWS-FLI-1 fusion protein behaves as an aberrant transcriptional activator and is believed to contribute to EFT development. However, EWS-FLI-1 induces growth arrest and apoptosis in normal fibroblasts, and primary cells that are permissive for its putative oncogenic properties have not been discovered, hampering basic understanding of EFT biology. Here, we show that EWS-FLI-1 alone can transform primary bone marrow-derived mesenchymal progenitor cells and generate tumors that display hallmarks of Ewing's sarcoma, including a small round cell phenotype, expression of EFT-associated markers, insulin like growth factor-I dependence, and induction or repression of numerous EWS-FLI-1 target genes. These observations provide the first identification of candidate primary cells from which EFTs originate and suggest that EWS-FLI-1 expression may constitute the initiating event in EFT pathogenesis.

Cooperative expression of junctional adhesion molecule-C and -B supports growth and invasion of glioma.

Brain invasion is a biological hallmark of glioma that contributes to its aggressiveness and limits the potential of surgery and irradiation. Deregulated expression of adhesion molecules on glioma cells is thought to contribute to this process. Junctional adhesion molecules (JAMs) include several IgSF members involved in leukocyte trafficking, angiogenesis, and cell polarity. They are expressed mainly by endothelial cells, white blood cells, and platelets. Here, we report JAM-C expression by human gliomas, but not by their normal cellular counterpart. This expression correlates with the expression of genes involved in cytoskeleton remodeling and cell migration. These genes, identified by a transcriptomic approach, include poliovirus receptor and cystein-rich 61, both known to promote glioma invasion, as well as actin filament associated protein, a c-Src binding partner. Gliomas also aberrantly express JAM-B, a high affinity JAM-C ligand. Their interaction activates the c-Src proto-oncogene, a central upstream molecule in the pathways regulating cell migration and invasion. In the tumor microenvironment, this co-expression may thus promote glioma invasion through paracrine stimuli from both tumor cells and endothelial cells. Accordingly, JAM-C/B blocking antibodies impair in vivo glioma growth and invasion, highlighting the potential of JAM-C and JAM-B as new targets for the treatment of human gliomas.

Transcriptional profiling reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver.

Little is known about the role of the transcription factor peroxisome proliferator-activated receptor (PPAR) beta/delta in liver. Here we set out to better elucidate the function of PPARbeta/delta in liver by comparing the effect of PPARalpha and PPARbeta/delta deletion using whole genome transcriptional profiling and analysis of plasma and liver metabolites. In fed state, the number of genes altered by PPARalpha and PPARbeta/delta deletion was similar, whereas in fasted state the effect of PPARalpha deletion was much more pronounced, consistent with the pattern of gene expression of PPARalpha and PPARbeta/delta. Minor overlap was found between PPARalpha- and PPARbeta/delta-dependent gene regulation in liver. Pathways upregulated by PPARbeta/delta deletion were connected to innate immunity and inflammation. Pathways downregulated by PPARbeta/delta deletion included lipoprotein metabolism and various pathways related to glucose utilization, which correlated with elevated plasma glucose and triglycerides and reduced plasma cholesterol in PPARbeta/delta-/- mice. Downregulated genes that may underlie these metabolic alterations included Pklr, Fbp1, Apoa4, Vldlr, Lipg, and Pcsk9, which may represent novel PPARbeta/delta target genes. In contrast to PPARalpha-/- mice, no changes in plasma free fatty acid, plasma beta-hydroxybutyrate, liver triglycerides, and liver glycogen were observed in PPARbeta/delta-/- mice. Our data indicate that PPARbeta/delta governs glucose utilization and lipoprotein metabolism and has an important anti-inflammatory role in liver. Overall, our analysis reveals divergent roles of PPARalpha and PPARbeta/delta in regulation of gene expression in mouse liver.

Selective and powerful stress gene expression in Arabidopsis in response to malondialdehyde.

The provenance, half-life and biological activity of malondialdehyde (MDA) were investigated in Arabidopsis thaliana. We provide genetic confirmation of the hypothesis that MDA originates from fatty acids containing more than two methylene-linked double bonds, showing that tri-unsaturated fatty acids are the in vivo source of up to 75% of MDA. The abundance of the combined pool of free and reversibly bound MDA did not change dramatically in stress, although a significant increase in the free MDA pool under oxidative conditions was observed. The half-life of infiltrated MDA indicated rapid metabolic turnover/sequestration. Exposure of plants to low levels of MDA using a recently developed protocol powerfully upregulated many genes on a cDNA microarray with a bias towards those implicated in abiotic/environmental stress (e.g. ROF1 and XERO2). Remarkably, and in contrast to the activities of other reactive electrophile species (i.e. small vinyl ketones), none of the pathogenesis-related (PR) genes tested responded to MDA. The use of structural mimics of MDA isomers suggested that the propensity of the molecule to act as a cross-linking/modifying reagent might contribute to the activation of gene expression. Changes in the concentration/localisation of unbound MDA in vivo could strongly affect stress-related transcription.

MIMAS 3.0 is a Multiomics Information Management and Annotation System.

BACKGROUND: DNA sequence integrity, mRNA concentrations and protein-DNA interactions have been subject to genome-wide analyses based on microarrays with ever increasing efficiency and reliability over the past fifteen years. However, very recently novel technologies for Ultra High-Throughput DNA Sequencing (UHTS) have been harnessed to study these phenomena with unprecedented precision. As a consequence, the extensive bioinformatics environment available for array data management, analysis, interpretation and publication must be extended to include these novel sequencing data types. DESCRIPTION: MIMAS was originally conceived as a simple, convenient and local Microarray Information Management and Annotation System focused on GeneChips for expression profiling studies. MIMAS 3.0 enables users to manage data from high-density oligonucleotide SNP Chips, expression arrays (both 3'UTR and tiling) and promoter arrays, BeadArrays as well as UHTS data using MIAME-compliant standardized vocabulary. Importantly, researchers can export data in MAGE-TAB format and upload them to the EBI's ArrayExpress certified data repository using a one-step procedure. CONCLUSION: We have vastly extended the capability of the system such that it processes the data output of six types of GeneChips (Affymetrix), two different BeadArrays for mRNA and miRNA (Illumina) and the Genome Analyzer (a popular Ultra-High Throughput DNA Sequencer, Illumina), without compromising on its flexibility and user-friendliness. MIMAS, appropriately renamed into Multiomics Information Management and Annotation System, is currently used by scientists working in approximately 50 academic laboratories and genomics platforms in Switzerland and France. MIMAS 3.0 is freely available via http://multiomics.sourceforge.net/.

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.

Classification of human astrocytic gliomas on the basis of gene expression: a correlated group of genes with angiogenic activity emerges as a strong predictor of subtypes.

The development of targeted treatment strategies adapted to individual patients requires identification of the different tumor classes according to their biology and prognosis. We focus here on the molecular aspects underlying these differences, in terms of sets of genes that control pathogenesis of the different subtypes of astrocytic glioma. By performing cDNA-array analysis of 53 patient biopsies, comprising low-grade astrocytoma, secondary glioblastoma (respective recurrent high-grade tumors), and newly diagnosed primary glioblastoma, we demonstrate that human gliomas can be differentiated according to their gene expression. We found that low-grade astrocytoma have the most specific and similar expression profiles, whereas primary glioblastoma exhibit much larger variation between tumors. Secondary glioblastoma display features of both other groups. We identified several sets of genes with relatively highly correlated expression within groups that: (a). can be associated with specific biological functions; and (b). effectively differentiate tumor class. One prominent gene cluster discriminating primary versus nonprimary glioblastoma comprises mostly genes involved in angiogenesis, including VEGF fms-related tyrosine kinase 1 but also IGFBP2, that has not yet been directly linked to angiogenesis. In situ hybridization demonstrating coexpression of IGFBP2 and VEGF in pseudopalisading cells surrounding tumor necrosis provided further evidence for a possible involvement of IGFBP2 in angiogenesis. The separating groups of genes were found by the unsupervised coupled two-way clustering method, and their classification power was validated by a supervised construction of a nearly perfect glioma classifier.

MYC regulation of a "poor-prognosis" metastatic cancer cell state.

Gene expression signatures are used in the clinic as prognostic tools to determine the risk of individual patients with localized breast tumors developing distant metastasis. We lack a clear understanding, however, of whether these correlative biomarkers link to a common biological network that regulates metastasis. We find that the c-MYC oncoprotein coordinately regulates the expression of 13 different "poor-outcome" cancer signatures. In addition, functional inactivation of MYC in human breast cancer cells specifically inhibits distant metastasis in vivo and invasive behavior in vitro of these cells. These results suggest that MYC oncogene activity (as marked by "poor-prognosis" signature expression) may be necessary for the translocation of poor-outcome human breast tumors to distant sites.

Selecting control genes for RT-QPCR using public microarray data.

Background: Gene expression analysis has emerged as a major biological research area, with real-time quantitative reverse transcription PCR (RT-QPCR) being one of the most accurate and widely used techniques for expression profiling of selected genes. In order to obtain results that are comparable across assays, a stable normalization strategy is required. In general, the normalization of PCR measurements between different samples uses one to several control genes (e. g. housekeeping genes), from which a baseline reference level is constructed. Thus, the choice of the control genes is of utmost importance, yet there is not a generally accepted standard technique for screening a large number of candidates and identifying the best ones. Results: We propose a novel approach for scoring and ranking candidate genes for their suitability as control genes. Our approach relies on publicly available microarray data and allows the combination of multiple data sets originating from different platforms and/or representing different pathologies. The use of microarray data allows the screening of tens of thousands of genes, producing very comprehensive lists of candidates. We also provide two lists of candidate control genes: one which is breast cancer-specific and one with more general applicability. Two genes from the breast cancer list which had not been previously used as control genes are identified and validated by RT-QPCR. Open source R functions are available at http://www.isrec.isb-sib.ch/similar to vpopovic/research/ Conclusion: We proposed a new method for identifying candidate control genes for RT-QPCR which was able to rank thousands of genes according to some predefined suitability criteria and we applied it to the case of breast cancer. We also empirically showed that translating the results from microarray to PCR platform was achievable.

Comparative transcriptomics of rice reveals an ancient pattern of response to microbial colonization.

Glomalean fungi induce and colonize symbiotic tissue called arbuscular mycorrhiza on the roots of most land plants. Other fungi also colonize plants but cause disease not symbiosis. Whole-transcriptome analysis using a custom-designed Affymetrix Gene-Chip and confirmation with real-time RT-PCR revealed 224 genes affected during arbuscular mycorrhizal symbiosis. We compared these transcription profiles with those from rice roots that were colonized by pathogens (Magnaporthe grisea and Fusarium moniliforme). Over 40% of genes showed differential regulation caused by both the symbiotic and at least one of the pathogenic interactions. A set of genes was similarly expressed in all three associations, revealing a conserved response to fungal colonization. The responses that were shared between pathogen and symbiont infection may play a role in compatibility. Likewise, the responses that are different may cause disease. Some of the genes that respond to mycorrhizal colonization may be involved in the uptake of phosphate. Indeed, phosphate addition mimicked the effect of mycorrhiza on 8% of the tested genes. We found that 34% of the mycorrhiza-associated rice genes were also associated with mycorrhiza in dicots, revealing a conserved pattern of response between the two angiosperm classes.