967 resultados para Genetics - Expression
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Semliki Forest virus (SFV) vectors have been efficiently used for rapid high level expression of several G protein-coupled receptors. Here we describe the use of SFV vectors to express the alpha 1b-adrenergic receptor (AR) alone or in the presence of the G protein alpha q and/or beta 2 and gamma 2 subunits. Infection of baby hamster kidney (BHK) cells with recombinant SFV-alpha 1b-AR particles resulted in high specific binding activity of the alpha 1b-AR (24 pmol receptor/mg protein). Time-course studies indicated that the highest level of receptor expression was obtained 30 hours post-infection. The stimulation of BHK cells, with epinephrine led to a 5-fold increase in inositol phosphate (IP) accumulation, confirming the functional coupling of the receptor to G protein-mediated activation of phospholipase C. The SFV expression system represents a rapid and reproducible system to study the pharmacological properties and interactions of G protein coupled receptors and of G protein subunits.
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Staphylococcus aureus harbors redundant adhesins mediating tissue colonization and infection. To evaluate their intrinsic role outside of the staphylococcal background, a system was designed to express them in Lactococcus lactis subsp. cremoris 1363. This bacterium is devoid of virulence factors and has a known genetic background. A new Escherichia coli-L. lactis shuttle and expression vector was constructed for this purpose. First, the high-copy-number lactococcal plasmid pIL253 was equipped with the oriColE1 origin, generating pOri253 that could replicate in E. coli. Second, the lactococcal promoters P23 or P59 were inserted at one end of the pOri253 multicloning site. Gene expression was assessed by a luciferase reporter system. The plasmid carrying P23 (named pOri23) expressed luciferase constitutively at a level 10,000 times greater than did the P59-containing plasmid. Transcription was absent in E. coli. The staphylococcal clumping factor A (clfA) gene was cloned into pOri23 and used as a model system. Lactococci carrying pOri23-clfA produced an unaltered and functional 130-kDa ClfA protein attached to their cell walls. This was indicated both by the presence of the protein in Western blots of solubilized cell walls and by the ability of ClfA-positive lactococci to clump in the presence of plasma. ClfA-positive lactococci had clumping titers (titer of 4,112) similar to those of S. aureus Newman in soluble fibrinogen and bound equally well to solid-phase fibrinogen. These experiments provide a new way to study individual staphylococcal pathogenic factors and might complement both classical knockout mutagenesis and modern in vivo expression technology and signature tag mutagenesis.
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CYP4F (Cytochrome P4504F) enzymes metabolize endogenous molecules including leukotrienes, prostaglandins and arachidonic acid. The involvement of these endogenous compounds in inflammation has led to the hypothesis that changes in the inflamed tissue environment may affect the expression of CYP4Fs during the pro-inflammatory state, which in turn may modulate inflammatory conditions during the anti-inflammatory state. We demonstrated that inflamed tissues have different levels of CYP4F isoform expression profiles in a number of human samples when compared to the average population. The CYP4F isoform expression levels change with the degree of inflammation present in tissue. Further investigation in cell culture studies revealed that inflammatory cytokines, in particular TNF-α, play a role in regulating the expression of the CYP4F family. One of the isoforms, CYP4F11, had different characteristics than that of the other five CYP4F family members. CYP4F11 metabolizes xenobiotics while the other isoforms metabolize endogenous compounds with higher affinity. CYP4F11 also was expressed at high quantities in the brain, and was up-regulated by TNF-α, while the other isoforms were not expressed at high quantities in the brain and were down-regulated by TNF-α. We identified the AP-1 protein of the JNK pathway as the signaling protein that causes significant increase in CYP4F11 expression. Since TNF-α stimulation causes a simultaneous activation of both JNK pathway and NF-κB signaling, we investigated further the role that NF-κB plays on expression of the CYP4F11 gene. We concluded that although there is a significant increase in CYP4F11 expression in the presence of TNF-α, the activation of NF-κB signaling inhibits CYP4F11 expression in a time dependent manner. The expression of CYP4F11 is only significantly increased after 24 hours of treatment with TNF-α; at shorter time points NF-κB signaling overpowers the JNK pathway activation. We believe that these findings may in the future lead to improved drug design for modulating inflammation.
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Genetic analysis, both karyotyping and comparative genomic hybridization, of prostate cancer cell lines and specimens have revealed multiple areas of concordant increases in DNA content. An increase of DNA in specific regions of the genome in cancer is often associated with the amplification of oncogenes. Based on these observations we have hypothesized that oncogenes are involved in the initiation or progression of prostate cancer. An expression cloning approach was utilized to identify candidate oncogenes in prostate cancer. ^ A full-length, unidirectional cDNA expression library was constructed from DU145 prostate cancer cells. The cDNA library was screened using CP12, a rat prostate epithelial cell line. In soft agarose assays, CP12 (parental or vector transfected) do not form colonies. However, upon the introduction of a number of known oncogenes CP12 becomes anchorage independent in soft agarose. Based on this in-vitro phenotypic shift, a DU145 cDNA library was stably transfected into CP12, and selected for anchorage independence. Two hundred fifty nine anchorage independent clones were isolated. Some colonies contained more than one insert, bringing the candidate oncogene pool to approximately 400. Seven inserts were sequenced at random. Using the sequences obtained, GenBank was screened, and matches were found with p53, PARG1, a mitochondrial ATPase, RNF6, and three unknown genes that mapped to Unigene clusters. As the pool of cDNA inserts appeared promising, overexpressed genes were further selected. From 259 clones, 17 clones were overexpressed more than 6-fold in DU145 compared to Normal Prostate. From the 17 clones, 12 cDNA inserts were strongly expressed in DU145 and were isolated for sequencing. ^ Two of the sequences, 1G6 and 3E9, were identical. Expression of 1G6/2G9/3E9 was tested by RT-PCR. 1G6/2G9/3E9 was not expressed in normal prostate, but was expressed in all prostate cancer cell lines tested as well as six prostate cancer samples. When retransfected into CP12, 1G6/2G9/3E9 induced the formation of foci and anchorage independent colonies. Thus, functional and expression data suggest that 1G6/2G9/3E9 may be a prostate cancer oncogene. ^
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Atherosclerosis is a complex disease resulting from interactions of genetic and environmental risk factors leading to heart failure and stroke. Using an atherosclerotic mouse model (ldlr-/-, apobec1-/- designated as LDb), we performed microarray analysis to identify candidate genes and pathways, which are most perturbed in changes in the following risk factors: genetics (control C57BL/6 vs. LDb mice), shearstress (lesion-prone vs. lesion-resistant regions in LDb mice), diet (chow vs. high fat fed LDb mice) and age (2-month-old vs. 8-month old LDb mice). ^ Atherosclerotic lesion quantification and lipid profile studies were performed to assess the disease phenotype. A microarray study was performed on lesion-prone and lesion-resistant regions of each aorta. Briefly, 32 male C57BL/6 and LDb mice (n =16/each) were fed on either chow or high fat diet, sacrificed at 2- and 8-months old, and RNA isolated from the aortic lesion-prone and aortic lesion-resistant segments. Using 64 Affymetrix Murine 430 2.0 chips, we profiled differentially expressed genes with the cut off value of FDR ≤ 0.15 for t-test, and q <0.0001 for the ANOVA. The data were normalized using two normalization methods---invariant probe sets (Loess) and Quantile normalization, the statistical analysis was performed using t-tests and ANOVA, and pathway characterization was done using Pathway Express (Wayne State). The result identified the calcium signaling pathway as the most significant overrepresented pathway, followed by focal adhesion. In the calcium signaling pathway, 56 genes were found to be significantly differentially expressed out of 180 genes listed in the KEGG calcium signaling pathway. Nineteen of these genes were consistently identified by both statistical tests, 11 of which were unique to the test, and 26 were unique to the ANOVA test, using the cutoffs noted above. ^ In conclusion, this finding suggested that hypercholesterolemia drives the disease progression by altering the expression of calcium channels and regulators which subsequently results in cell differentiation, growth, adhesion, cytoskeletal change and death. Clinically, this pathway may serve as an important target for future therapeutic intervention, and thus the calcium signaling pathway may serve as an important target for future diagnostic and therapeutic intervention. ^
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Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.
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La néphropathie diabétique est une maladie rénale caractérisée par un syndrome néphrotique et de la glomérulosclérose. Celle-ci est reliée à l’angiopathie de capillaires suite au diabète. Il s’agit d’une importante cause d’insuffisance rénale en Amérique. Or, les anomalies tubulaires comme l’apoptose ou le détachement de tubules des glomérules sont reconnues comme étant de bons marqueurs de progression de cette maladie. Ainsi, il a été proposé au cours des travaux reliés à cette thèse d’étudier les différents mécanismes moléculaires reliés à l’apoptose des tubules proximaux, en particulier dans un thème de relation avec les dommages reliés aux espèces réactives oxygénées (ROS). Une des hypothèses développée au cours de précédents travaux faisait état que l’une des sources initiales qui entrainent le développement de dommages tubulaires soit régulée à travers la production de ROS dérivés des NADPH oxydases. Ainsi, une des premières séries d’expériences entreprises au cours de cette thèse a été effectuée sur un modèle animal de diabète de type 2, la souris db/db. Suite à la caractérisation des différentes pathologies rénales et leur réduction par la surexpression de l’enzyme antioxydante catalase dans les tubules proximaux, des expériences de micro-puces d’expression génétiques furent effectuées. À l’aide de cet outil et par des analyses bioinformatiques, il a été possible d’établir un profilage de gènes reliés à différentes voies de signalisation modulées par le diabète et la catalase. Ainsi, il a été possible d’effectuer de plus amples études sur des gènes reliés à l’apoptose surexprimé dans les tubules proximaux de souris diabétiques. Un des gènes pro-apoptotique mieux caractérisé durant cette thèse fut le gène Bmf, un membre de la famille des régulateurs de Bcl-2 impliqués dans l’apoptose via le relâchement de cytochrome c de la mitochondrie. Ainsi, il a été déterminé que ce gène est surexprimé dans les tubules proximaux de souris diabétiques, et que celui-ci était augmenté dans différents modèles in vitro de diabète. Cela a permis de conclure que Bmf joue sans doute un rôle important la régulation de l’apoptose et de l’atrophie des tubules proximaux. Une autre étude effectuée dans le cadre de cette thèse était reliée avec l’utilisation d’un modèle transgénique afin de mieux définir le rôle que jouent les dommages reliés au stress oxydatif dans la progression des pathologies rénales reliées à l’induction du système rénine-angiotensine. Les résultats obtenus ont permis de déterminer que la surexpression de l’enzyme antioxydante catalase a permis de réduire les différentes pathologies rénales observées dans les souris transgéniques, ce qui permet de conclure que les espèces réactives oxygénées jouen un rôle important dans le développement de l’hypertension et des dommages rénaux.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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We propose a model-based approach to unify clustering and network modeling using time-course gene expression data. Specifically, our approach uses a mixture model to cluster genes. Genes within the same cluster share a similar expression profile. The network is built over cluster-specific expression profiles using state-space models. We discuss the application of our model to simulated data as well as to time-course gene expression data arising from animal models on prostate cancer progression. The latter application shows that with a combined statistical/bioinformatics analyses, we are able to extract gene-to-gene relationships supported by the literature as well as new plausible relationships.
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Nuclear Factor Y (NF-Y) is a trimeric complex that binds to the CCAAT box, a ubiquitous eukaryotic promoter element. The three subunits NF-YA, NF-YB and NF-YC are represented by single genes in yeast and mammals. However, in model plant species (Arabidopsis and rice) multiple genes encode each subunit providing the impetus for the investigation of the NF-Y transcription factor family in wheat. A total of 37 NF-Y and Dr1 genes (10 NF-YA, 11 NF-YB, 14 NF-YC and 2 Dr1) in Triticum aestivum were identified in the global DNA databases by computational analysis in this study. Each of the wheat NF-Y subunit families could be further divided into 4-5 clades based on their conserved core region sequences. Several conserved motifs outside of the NF-Y core regions were also identified by comparison of NF-Y members from wheat, rice and Arabidopsis. Quantitative RT-PCR analysis revealed that some of the wheat NF-Y genes were expressed ubiquitously, while others were expressed in an organ-specific manner. In particular, each TaNF-Y subunit family had members that were expressed predominantly in the endosperm. The expression of nine NF-Y and two Dr1 genes in wheat leaves appeared to be responsive to drought stress. Three of these genes were up-regulated under drought conditions, indicating that these members of the NF-Y and Dr1 families are potentially involved in plant drought adaptation. The combined expression and phylogenetic analyses revealed that members within the same phylogenetic clade generally shared a similar expression profile. Organ-specific expression and differential response to drought indicate a plant-specific biological role for various members of this transcription factor family.
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Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.
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The most common human cancers are malignant neoplasms of the skin. Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease. Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm. Accordingly, though melanoma is thought to present with different 'taxonomic' forms, these are considered part of a continuous spectrum rather than discrete entities. Here we report the discovery of a subset of melanomas identified by mathematical analysis of gene expression in a series of samples. Remarkably, many genes underlying the classification of this subset are differentially regulated in invasive melanomas that form primitive tubular networks in vitro, a feature of some highly aggressive metastatic melanomas. Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression.
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We have used microarray gene expression profiling and machine learning to predict the presence of BRAF mutations in a panel of 61 melanoma cell lines. The BRAF gene was found to be mutated in 42 samples (69%) and intragenic mutations of the NRAS gene were detected in seven samples (11%). No cell line carried mutations of both genes. Using support vector machines, we have built a classifier that differentiates between melanoma cell lines based on BRAF mutation status. As few as 83 genes are able to discriminate between BRAF mutant and BRAF wild-type samples with clear separation observed using hierarchical clustering. Multidimensional scaling was used to visualize the relationship between a BRAF mutation signature and that of a generalized mitogen-activated protein kinase (MAPK) activation (either BRAF or NRAS mutation) in the context of the discriminating gene list. We observed that samples carrying NRAS mutations lie somewhere between those with or without BRAF mutations. These observations suggest that there are gene-specific mutation signals in addition to a common MAPK activation that result from the pleiotropic effects of either BRAF or NRAS on other signaling pathways, leading to measurably different transcriptional changes.