32 research outputs found

    Effects of new polymorphisms in the bovine myocyte enhancer factor 2D (MEF2D) gene on the expression rates of the longissimus dorsi muscle

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    Myocyte enhancer factor 2D (MEF2D), a product of the MEF2D gene, belongs to the myocyte enhancer factor 2 (MEF2) protein family which is involved in vertebrate skeletal muscle development and differentiation during myogenesis. The aim of the present study was to search for polymorphisms in the bovine MEF2D gene and to analyze their effect on MEF2D mRNA and on protein expression levels in the longissimus dorsi muscle of Polish Holstein–Friesian cattle. Overall, three novel variations, namely, insertion/deletion g.−818_−814AGCCG and g.−211C<A transversion in the promoter region as well as g.7C<T transition in the 5′untranslated region (5′UTR), were identified by DNA sequencing. A total, 375 unrelated bulls belonging to six different cattle breeds were genotyped, and three combined genotypes (Ins-C-C/Ins-C-C, Del-A-T/Del-A-T and Ins-C-C/Del-A-T) were determined. The frequency of the combined genotype Ins-C-C/Ins-C-C and Del-A-T/Del-A-T was varied between the breeds and the average frequency was 0.521 and 0.037, respectively. Expression analysis showed that the MEF2D variants were highly correlated with MEF2D mRNA and protein levels in the longissimus dorsi muscle of Polish Holstein–Friesian bulls carrying the three different combined genotypes. The highest MEF2D mRNA and protein levels were estimated in the muscle of bulls with the Ins-C-C/Ins-C-C homozygous genotype as compared to the Del-A-T/Del-A-T homozygotes (P < 0.01) and Ins-C-C/Del-A-T heterozygotes (P < 0.05). A preliminary association study showed no significant differences in the carcass quality traits between bulls with various MEF2D combined genotypes in the investigated population of Polish Holstein–Friesian cattle

    Interference with Activator Protein-2 transcription factors leads to induction of apoptosis and an increase in chemo- and radiation-sensitivity in breast cancer cells

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    <p>Abstract</p> <p>Background</p> <p>Activator Protein-2 (AP-2) transcription factors are critically involved in a variety of fundamental cellular processes such as proliferation, differentiation and apoptosis and have also been implicated in carcinogenesis. Expression of the family members AP-2α and AP-2γ is particularly well documented in malignancies of the female breast. Despite increasing evaluation of single AP-2 isoforms in mammary tumors the functional role of concerted expression of multiple AP-2 isoforms in breast cancer remains to be elucidated. AP-2 proteins can form homo- or heterodimers, and there is growing evidence that the net effect whether a cell will proliferate, undergo apoptosis or differentiate is partly dependent on the balance between different AP-2 isoforms.</p> <p>Methods</p> <p>We simultaneously interfered with all AP-2 isoforms expressed in ErbB-2-positive murine N202.1A breast cancer cells by conditionally over-expressing a dominant-negative AP-2 mutant.</p> <p>Results</p> <p>We show that interference with AP-2 protein function lead to reduced cell number, induced apoptosis and increased chemo- and radiation-sensitivity. Analysis of global gene expression changes upon interference with AP-2 proteins identified 139 modulated genes (90 up-regulated, 49 down-regulated) compared with control cells. Gene Ontology (GO) investigations for these genes revealed <it>Cell Death </it>and <it>Cell Adhesion and Migration </it>as the main functional categories including 25 and 12 genes, respectively. By using information obtained from Ingenuity Pathway Analysis Systems we were able to present proven or potential connections between AP-2 regulated genes involved in cell death and response to chemo- and radiation therapy, (i.e. <it>Ctgf, Nrp1</it>, <it>Tnfaip3, Gsta3</it>) and AP-2 and other main apoptosis players and to create a unique network.</p> <p>Conclusions</p> <p>Expression of AP-2 transcription factors in breast cancer cells supports proliferation and contributes to chemo- and radiation-resistance of tumor cells by impairing the ability to induce apoptosis. Therefore, interference with AP-2 function could increase the sensitivity of tumor cells towards therapeutic intervention.</p

    Identification of target genes of transcription factor activator protein 2 gamma in breast cancer cells

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    <p>Abstract</p> <p>Background</p> <p>Activator protein 2 gamma (AP-2γ) is a member of the transcription factor activator protein-2 (AP-2) family, which is developmentally regulated and plays a role in human neoplasia. AP-2γ has been found to be overexpressed in most breast cancers, and have a dual role to inhibit tumor initiation and promote tumor progression afterwards during mammary tumorigensis.</p> <p>Methods</p> <p>To identify the gene targets that mediate its effects, we performed chromatin immunoprecipitation (ChIP) to isolate AP-2γ binding sites on genomic DNA from human breast cancer cell line MDA-MB-453.</p> <p>Results</p> <p>20 novel DNA fragments proximal to potential AP-2γ targets were obtained. They are categorized into functional groups of carcinogenesis, metabolism and others. A combination of sequence analysis, reporter gene assays, quantitative real-time PCR, electrophoretic gel mobility shift assays and immunoblot analysis further confirmed the four AP-2γ target genes in carcinogenesis group: ErbB2, CDH2, HPSE and IGSF11. Our results were consistent with the previous reports that ErbB2 was the target gene of AP-2γ. Decreased expression and overexpression of AP-2γ in human breast cancer cells significantly altered the expression of these four genes, indicating that AP-2γ directly regulates them.</p> <p>Conclusion</p> <p>This suggested that AP-2γ can coordinate the expression of a network of genes, involving in carcinogenesis, especially in breast cancer. They could serve as therapeutic targets against breast cancers in the future.</p

    Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

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    A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals

    ExCITED about HIF.

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    The structure of the CH1 domain of p300 in complex with the transactivation domain of CITED2 brings us one step closer toward understanding the molecular basis of the regulation of hypoxia response
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