49 research outputs found

    Genetic networks of antibacterial responses of eukaryotic cells. Bioinformatics analysis and modeling

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    This work describes the development of new methods to construction of promoter models as one of necessary steps of regulatory networks construction. Identification of characteristic promoter features shows the role of specific transcription factors (TFs) in triggering the response, which in turn sheds light on the signaling pathways activating these TFs. Treating reported results of microarray analyses together with other available information about the genes expressed in different cellular systems under consideration, we search for distinguishing features of the promoters of coexpressed genes. The application of such promoter models enables to identify additional candidate genes belonging to the same regulatory network. Four novel approaches are presented in this work: (i) subtractive approach to matrix generation; (ii) distance distribution approach; (iii) "seed" sets approach; (iv) complementary pairs approach. These approaches help to solve serious problems in promoter model construction such as the doubtful reliability of positive training sets ("seed" sets approach) and lack of knowledge about the exact signaling pathways triggering the gene expression (complementary pairs approach); the subtractive approach to matrix generation allows to refine positional weight matrices (PWM) for heterogeneous sets of binding sites, thus to improve the PWM search for single TFBS. A significant improvement of the specificity of promoter analysis has been achieved by applying statistical methods for characterizing TFBS combinations at over-represented distances rather than the mere identification of single potential TFBS (distance distributions approach). The newly developed methods were applied to the description of four defensive eukaryotic systems in terms of transcription regulation. The obtained models enabled us to gain better insights into the pathways of the corresponding signaling networks.Diese Arbeit beschreibt die Entwicklung mehrerer neuer Methoden zur Konstruktion von Promotormodellen als einen der notwendigen Schritte zur Konstruktion regulatorischer Netzwerke. Die Identifizierung charakteristischer Eigenschaften von Promotoren zeigt die Rolle bestimmter Transkriptionsfaktoren (TF) beim Auslösen spezifischer Antworten auf, was wiederum Aufschluss über die Signalwege zur Aktivierung dieser TF gibt. Durch Verarbeitung von Ergebnissen aus Microarray-Analysen zusammen mit weiteren verfügbaren Informationen über die in den betrachteten zellulären Systemen exprimierten Gene suchen wir nach kennzeichnenden Eigenschaften koregulierter Promotoren. Die Applikation solcher Promotermodelle ermöglicht die Identifizierung zusätzlicher Kandidatengene, die demselben regulatorischen Netzwerk angehören. Vier neue Ansätze werden in dieser Arbeit präsentiert: (i) der subtraktive Ansatz zur Matrixerzeugung; (ii) der Distanzverteilungsansatz; (iii) der "seed"-Set-Ansatz; (iv) der Ansatz komplementärer Paare. Diese Ansätze helfen, beträchtliche Probleme der Promotormodellkonstruktion zu lösen, wie die zweifelhafte Zuverlässigkeit positiver Trainingsets ("seed"-Set-Ansatz) und der Mangel an Wissen über die präzisen Signalwege, die bestimmte Genexpressionsereignisse auslösen (Ansatz komplementärer Paare). Der subtraktive Ansatz zur Matrixerzeugung erlaubt, Positionsgewichtungsmatrizen (PWM) für heterogene Sets von Bindungsstellen zu verfeinern und dadurch die PWM-Suche für einzelne TFBSs zur verbessern. Eine signifikante Verbesserung der Spezifität der Promotoranalyse wurde durch die Anwendung statistischer Methoden zur Charakterisierung von TFBS-Kombinationen in überrepräsentierten Distanzen anstelle der bloßen Identifizierung einzelner potentieller TFBSs erreicht. Die neuentwickelten Methoden wurden zur Beschreibung von vier eukaryotischen Abwehrsystemen verwendet. Die erhaltenen Modelle eröffneten tiefergehende Einsichten in die Pfade der zugehörigen Signalnetzwerke

    Human genome program report. Part 2, 1996 research abstracts

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    Combinatorial motif analysis of regulatory gene expression in Mafb deficient macrophages

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    <p>Abstract</p> <p>Background</p> <p>Deficiency of the transcription factor MafB, which is normally expressed in macrophages, can underlie cellular dysfunction associated with a range of autoimmune diseases and arteriosclerosis. MafB has important roles in cell differentiation and regulation of target gene expression; however, the mechanisms of this regulation and the identities of other transcription factors with which MafB interacts remain uncertain. Bioinformatics methods provide a valuable approach for elucidating the nature of these interactions with transcriptional regulatory elements from a large number of DNA sequences. In particular, identification of patterns of co-occurrence of regulatory <it>cis</it>-elements (motifs) offers a robust approach.</p> <p>Results</p> <p>Here, the directional relationships among several functional motifs were evaluated using the Log-linear Graphical Model (LGM) after extraction and search for evolutionarily conserved motifs. This analysis highlighted GATA-1 motifs and 5’AT-rich half Maf recognition elements (MAREs) in promoter regions of 18 genes that were down-regulated in <it>Mafb</it> deficient macrophages. GATA-1 motifs and MafB motifs could regulate expression of these genes in both a negative and positive manner, respectively. The validity of this conclusion was tested with data from a luciferase assay that used a <it>C1qa</it> promoter construct carrying both the GATA-1 motifs and MAREs. GATA-1 was found to inhibit the activity of the <it>C1qa</it> promoter with the GATA-1 motifs and MafB motifs.</p> <p>Conclusions</p> <p>These observations suggest that both the GATA-1 motifs and MafB motifs are important for lineage specific expression of <it>C1qa</it>. In addition, these findings show that analysis of combinations of evolutionarily conserved motifs can be successfully used to identify patterns of gene regulation.</p

    Dissecting interferon-induced transcriptional programs in human peripheral blood cells

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    Interferons are key modulators of the immune system, and are central to the control of many diseases. The response of immune cells to stimuli in complex populations is the product of direct and indirect effects, and of homotypic and heterotypic cell interactions. Dissecting the global transcriptional profiles of immune cell populations may provide insights into this regulatory interplay. The host transcriptional response may also be useful in discriminating between disease states, and in understanding pathophysiology. The transcriptional programs of cell populations in health therefore provide a paradigm for deconvoluting disease-associated gene expression profiles.We used human cDNA microarrays to (1) compare the gene expression programs in human peripheral blood mononuclear cells (PBMCs) elicited by 6 major mediators of the immune response: interferons alpha, beta, omega and gamma, IL12 and TNFalpha; and (2) characterize the transcriptional responses of purified immune cell populations (CD4+ and CD8+ T cells, B cells, NK cells and monocytes) to IFNgamma stimulation. We defined a highly stereotyped response to type I interferons, while responses to IFNgamma and IL12 were largely restricted to a subset of type I interferon-inducible genes. TNFalpha stimulation resulted in a distinct pattern of gene expression. Cell type-specific transcriptional programs were identified, highlighting the pronounced response of monocytes to IFNgamma, and emergent properties associated with IFN-mediated activation of mixed cell populations. This information provides a detailed view of cellular activation by immune mediators, and contributes an interpretive framework for the definition of host immune responses in a variety of disease settings

    Stress-inducible protein 1: a bioinformatic analysis of the human, mouse and yeast STI1 gene structure

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    Stress-inducible protein 1 (Sti1) is a 60 kDa eukaryotic protein that is important under stress and non-stress conditions. Human Sti1 is also known as the Hsp70/Hsp90 organising protein (Hop) that coordinates the functional cooperation of heat shock protein 70 (Hsp70) and heat shock protein 90 (Hsp90) during the folding of various transcription factors and kinases, including certain oncogenic proteins and prion proteins. Limited studies have been conducted on the STI1 gene structure. Thus, the aim of this study was to develop a comprehensive description of human STI1 (hSTI1), mouse STI1 (mSTI1), and yeast STI1 (ySTI1) genes, using a bioinformatic approach. Genes encoded near the STI1 loci were identified for the three organisms using National Centre for Biotechnology Information (NCBI) MapViewer and the Saccharomyces Genome Database. Exon/intron boundaries were predicted using Hidden Markov model gene prediction software (HMMGene) and Genscan, and by alignment of the mRNA sequence with the genomic DNA sequence. Transcription factor binding sites (TFBS) were predicted by scanning the region 1000 base pairs (bp) upstream of the STI1 orthologues’ transcription start site (TSS) with Alibaba, Transcription element search software (TESS) and Transcription factor search (TFSearch). The promoter region was defined by comparing the number, type and position of TFBS across the orthologous STI1 genes. Additional putative TFBS were identified for ySTI1 by searching with software that aligns nucleic acid conserved elements (AlignACE) for over-represented motifs in the region upstream of the TSS of genes thought to be co-regulated with ySTI1. This study showed that hSTI1 and mSTI1 occur in a region of synteny with a number of genes of related function. Both hSTI1 and mSTI1 comprised 14 putative exons, while ySTI1 was encoded on a single exon. Human and mouse STI1 shared a perfectly conserved 55 bp region spanning their predicted TSS, although their TATA boxes were not conserved. A putative CpG island was identified in the region from -500 to +100 bp relative to the hSTI1 and mSTI1 TSS. This region overlapped with a region of high TFBS density, suggesting that the core promoter region was located in the region approximately 100 to 200 bp upstream of the TSS. Several conserved clusters of TFBS were also identified upstream of this promoter region, including binding sites for stimulatory protein 1 (Sp1), heat shock factor (HSF), nuclear factor kappa B (NF-kappaB), and the cAMP/enhancer binding protein (C/EBP). Microarray data suggested that ySTI1 was co-regulated with several heat shock proteins and substrates of the Hsp70/Hsp90 heterocomplex, and several putative regulatory elements were identified in the upstream region of these co-regulated genes, including a motif for HSF binding. The results of this research suggest several avenues of future experimental work, including the confirmation of the proposed core promoter, upstream regulatory elements, and CpG island, and the investigation into the co-regulation of mammalian STI1 with its surrounding genes. These results could also be used to inform STI1 gene knockout experiments in mice, to assess the biological importance of mammalian STI1

    Differences in APOBEC3G Expression in CD4+ T Helper Lymphocyte Subtypes Modulate HIV-1 Infectivity

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    The cytidine deaminases APOBEC3G and APOBEC3F exert anti–HIV-1 activity that is countered by the HIV-1 vif protein. Based on potential transcription factor binding sites in their putative promoters, we hypothesized that expression of APOBEC3G and APOBEC3F would vary with T helper lymphocyte differentiation. Naive CD4+ T lymphocytes were differentiated to T helper type 1 (Th1) and 2 (Th2) effector cells by expression of transcription factors Tbet and GATA3, respectively, as well as by cytokine polarization. APOBEC3G and APOBEC3F RNA levels, and APOBEC3G protein levels, were higher in Th1 than in Th2 cells. T cell receptor stimulation further increased APOBEC3G and APOBEC3F expression in Tbet- and control-transduced, but not in GATA3-transduced, cells. Neutralizing anti–interferon-γ antibodies reduced both basal and T cell receptor-stimulated APOBEC3G and APOBEC3F expression in Tbet- and control-transduced cells. HIV-1 produced from Th1 cells had more virion APOBEC3G, and decreased infectivity, compared to virions produced from Th2 cells. These differences between Th1- and Th2-produced virions were greater for viruses lacking functional vif, but also seen with vif-positive viruses. Over-expression of APOBEC3G in Th2 cells decreased the infectivity of virions produced from Th2 cells, and reduction of APOBEC3G in Th1 cells increased infectivity of virions produced from Th1 cells, consistent with a causal role for APOBEC3G in the infectivity difference. These results indicate that APOBEC3G and APOBEC3F levels vary physiologically during CD4+ T lymphocyte differentiation, that interferon-γ contributes to this modulation, and that this physiological regulation can cause changes in infectivity of progeny virions, even in the presence of HIV-1 vif

    Regulation of Cyclooxygenase-2 Expression by Heat: A Novel Aspect of Heat Shock Factor 1 Function in Human Cells

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    The heat-shock response, a fundamental defense mechanism against proteotoxic stress, is regulated by a family of heat-shock transcription factors (HSF). In humans HSF1 is considered the central regulator of heat-induced transcriptional responses. The main targets for HSF1 are specific promoter elements (HSE) located upstream of heat-shock genes encoding cytoprotective heat-shock proteins (HSP) with chaperone function. In addition to its cytoprotective function, HSF1 was recently hypothesized to play a more complex role, regulating the expression of non-HSP genes; however, the non-canonical role of HSF1 is still poorly understood. Herein we report that heat-stress promotes the expression of cyclooxygenase-2 (COX-2), a key regulator of inflammation controlling prostanoid and thromboxane synthesis, resulting in the production of high levels of prostaglandin-E2 in human cells. We show that heat-induced COX-2 expression is regulated at the transcriptional level via HSF1-mediated signaling and identify, by in-vitro reporter gene activity assay and deletion-mutant constructs analysis, the COX-2 heat-responsive promoter region and a new distal cis-acting HSE located at position −2495 from the transcription start site. As shown by ChIP analysis, HSF1 is recruited to the COX-2 promoter rapidly after heat treatment; by using shRNA-mediated HSF1 suppression and HSE-deletion from the COX-2 promoter, we demonstrate that HSF1 plays a central role in the transcriptional control of COX-2 by heat. Finally, COX-2 transcription is also induced at febrile temperatures in endothelial cells, suggesting that HSF1-dependent COX-2 expression could contribute to increasing blood prostaglandin levels during fever. The results identify COX-2 as a human non-classical heat-responsive gene, unveiling a new aspect of HSF1 function

    Understanding the transcriptional control of EIF4E and its dysregulation in acute myeloid leukemia: role of NF-κB

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    EIF4E, le facteur d’initiation de la traduction chez les eucaryotes est un oncogène puissant et qui se trouve induit dans plusieurs types de cancers, parmi lesquels les sous-types M4 et M5 de la leucémie aiguë myéloblastique (LAM). EIF4E est régulé à plusieurs niveaux cependant, la régulation transcriptionnelle de ce gène est peu connue. Mes résultats montrent que EIF4E est une cible transcriptionnelle directe du facteur nucléaire « kappa-light- chain- enhancer of activated B cells » (NF-κB).Dans les cellules hématopoïétiques primaires et les lignées cellulaires, les niveaux de EIF4E sont induits par des inducteurs de NF-κB. En effet, l’inactivation pharmaceutique ou génétique de NF-κB réprime l’activation de EIF4E. En effet, suite à l’activation de NF-κB chez l’humain, le promoteur endogène de EIF4E recrute p65 (RelA) et c-Rel aux sites évolutionnaires conservés κB in vitro et in vivo en même temps que p300 ainsi que la forme phosphorylée de Pol II. De plus, p65 est sélectivement associé au promoteur de EIF4E dans les sous-types LAM M4/M5 mais non pas dans les autres sous-types LAM ou dans les cellules hématopoïétiques primaires normales. Ceci indique que ce processus représente un facteur essentiel qui détermine l’expression différentielle de EIF4E dans la LAM. Les analyses de données d’expressions par séquençage de l’ARN provenant du « Cancer Genome Atlas » (TCGA) suggèrent que les niveaux d’ARNm de EIF4E et RELA se trouvent augmentés dans les cas LAM à pronostic intermédiaire ou faible mais non pas dans les groupes cytogénétiquement favorables. De plus, des niveaux élevés d’ARNm de EIF4E et RELA sont significativement associés avec un taux de survie relativement bas chez les patients. En effet, les sites uniques κB se trouvant dans le promoteur de EIF4E recrutent le régulateur de transcription NF-κB p65 dans 47 nouvelles cibles prévues. Finalement, 6 nouveaux facteurs de transcription potentiellement impliqués dans la régulation du gène EIF4E ont été prédits par des analyses de données ChIP-Seq provenant de l’encyclopédie des éléments d’ADN (ENCODE). Collectivement, ces résultats fournissent de nouveaux aperçus sur le control transcriptionnel de EIF4E et offrent une nouvelle base moléculaire pour sa dérégulation dans au moins un sous-groupe de spécimens de LAM. L’étude et la compréhension de ce niveau de régulation dans le contexte de spécimens de patients s’avère important pour le développement de nouvelles stratégies thérapeutiques ciblant l’expression du gène EIF4E moyennant des inhibiteurs de NF-κB en combinaison avec la ribavirine.The eukaryotic translation initiation factor EIF4E is a powerful oncogene that is overexpressed in cancers, including the M4 and M5 subtypes of acute myeloid leukemia (AML). EIF4E is regulated at multiple levels; however not much is known about the transcriptional regulation of this gene. My findings show that the nuclear factor kappa-light- chain-enhancer of activated B cells (NF-κB) is a direct transcriptional regulator of EIF4E. EIF4E levels are induced in primary hematopoietic cells and in cell lines in response to NF-κB activating stimuli. Pharmacological and genetic inhibition of NF-κB suppresses EIF4E levels. NF-κB factors RelA (p65) and c-Rel are recruited to evolutionarily conserved κB sites in the EIF4E promoter in vitro and in vivo following NF-κB activation concurrent with the recruitment of p300 and phosphorylated Pol II. Furthermore, p65 is selectively associated with the EIF4E promoter in M4/M5 AML subtypes but not in other AML subtypes or normal primary hematopoietic cells and thus represents an underlying factor in determining the differential expression of EIF4E in AML. Analysis of gene expression RNA-Seq data from The Cancer Genome Atlas (TCGA) suggests that EIF4E and RELA mRNA levels are upregulated in intermediate and poor prognosis AML but not in the cytogenetically favorable group. Additionally, elevated EIF4E and RELA mRNA levels are significantly associated with worst patient survival outcome. Furthermore, 8 new putative NF-κB target genes that may be regulated with a pattern similar to EIF4E in poor prognosis AML were in silico predicted from Chip-Seq data. Finally, 6 new transcription factors that may be implicated in EIF4E gene regulation were predicted from the analysis of ChIP-Seq data from the encyclopedia of DNA elements (ENCODE). Collectively, these findings could offer novel insights into the transcriptional regulation of EIF4E and a novel molecular basis for its dysregulation in AML. Understanding this level of regulation within the context of patient specimens is important for the development of novel therapeutic strategies to target EIF4E gene expression with specific NF-κB inhibitors combined with ribavirin
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