139 resultados para genetic transcription


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ErbB3 binding protein Ebp1 has been shown to downregulate ErbB3 receptor-mediated signaling to inhibit cell proliferation. Rinderpest virus belongs to the family Paramyxoviridae and is characterized by the presence of a non-segmented negative-sense RNA genome. In this work, we show that rinderpest virus infection of Vero cells leads to the down-regulation of the host factor Ebp1, at both the mRNA and protein levels. Ebp1 protein has been shown to co-localize with viral inclusion bodies in infected cells, and it is packaged into virions, presumably through its interaction with the N protein or the N-RNA itself. Overexpression of Ebp1 inhibits viral transcription and multiplication in infected cells, suggesting that a mutual antagonism operates between host factor Ebp1 and the virus.

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This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

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This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

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In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

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The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

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Many optimal control problems are characterized by their multiple performance measures that are often noncommensurable and competing with each other. The presence of multiple objectives in a problem usually give rise to a set of optimal solutions, largely known as Pareto-optimal solutions. Evolutionary algorithms have been recognized to be well suited for multi-objective optimization because of their capability to evolve a set of nondominated solutions distributed along the Pareto front. This has led to the development of many evolutionary multi-objective optimization algorithms among which Nondominated Sorting Genetic Algorithm (NSGA and its enhanced version NSGA-II) has been found effective in solving a wide variety of problems. Recently, we reported a genetic algorithm based technique for solving dynamic single-objective optimization problems, with single as well as multiple control variables, that appear in fed-batch bioreactor applications. The purpose of this study is to extend this methodology for solution of multi-objective optimal control problems under the framework of NSGA-II. The applicability of the technique is illustrated by solving two optimal control problems, taken from literature, which have usually been solved by several methods as single-objective dynamic optimization problems. (C) 2004 Elsevier Ltd. All rights reserved.

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SLC22A18, a poly-specific organic cation transporter, is paternally imprinted in humans and mice. It shows loss-of-heterozygosity in childhood and adult tumors, and gain-of-imprinting in hepatocarcinomas and breast cancers. Despite the importance of this gene, its transcriptional regulation has not been studied, and the promoter has not yet been characterized. We therefore set out to identify the potential cis-regulatory elements including the promoter of this gene. The luciferase reporter assay in human cells indicated that a region from -120 by to +78 by is required for the core promoter activity. No consensus TATA or CHAT boxes were found in this region, but two Sp1 binding sites were conserved in human, chimpanzee, mouse and rat. Mutational analysis of the two Sp1 sites suggested their requirement for the promoter activity. Chromatin-immunoprecipitation showed binding of Sp1 to the promoter region in vivo. Overexpression of Sp1 in Drosophila Sp1-null SL2 cells suggested that Sp1 is the transactivator of the promoter. The human core promoter was functional in mouse 3T3 and monkey COS7 cells. We found a CpG island which spanned the core promoter and exon 1. COBRA technique did not reveal promoter methylation in 10 normal oral tissues, 14 oral tumors, and two human cell lines HuH7 and A549. This study provides the first insight into the mechanism that controls expression of this imprinted tumor suppressor gene. A COBRA-based assay has been developed to look for promoter methylation in different cancers. The present data will help to understand the regulation of this gene and its role in tumorigenesis. (C) 2008 Elsevier B.V. All rights reserved.

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SLC22A18, a poly-specific organic cation transporter, is paternally imprinted in humans and mice. It shows loss-of-heterozygosity in childhood and adult tumors, and gain-of-imprinting in hepatocarcinomas and breast cancers. Despite the importance of this gene, its transcriptional regulation has not been studied, and the promoter has not yet been characterized. We therefore set out to identify the potential cis-regulatory elements including the promoter of this gene. The luciferase reporter assay in human cells indicated that a region from -120 by to +78 by is required for the core promoter activity. No consensus TATA or CHAT boxes were found in this region, but two Sp1 binding sites were conserved in human, chimpanzee, mouse and rat. Mutational analysis of the two Sp1 sites suggested their requirement for the promoter activity. Chromatin-immunoprecipitation showed binding of Sp1 to the promoter region in vivo. Overexpression of Sp1 in Drosophila Sp1-null SL2 cells suggested that Sp1 is the transactivator of the promoter. The human core promoter was functional in mouse 3T3 and monkey COS7 cells. We found a CpG island which spanned the core promoter and exon 1. COBRA technique did not reveal promoter methylation in 10 normal oral tissues, 14 oral tumors, and two human cell lines HuH7 and A549. This study provides the first insight into the mechanism that controls expression of this imprinted tumor suppressor gene. A COBRA-based assay has been developed to look for promoter methylation in different cancers. The present data will help to understand the regulation of this gene and its role in tumorigenesis. (C) 2008 Elsevier B.V. All rights reserved.

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In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters of population size, the number of points of crossover and mutation rate for each population are fixed adaptively. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions, when compared with Island model GA(IGA) and Simple GA(SGA).

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The startling increase in the occurrence of rifampicin (Rif) resistance in the clinical isolates of Mycobacterium tuberculosis worldwide is posing a serious concern to tuberculosis management. The majority of Rif resistance in bacteria arises from mutations in the RpoB subunit of the RNA polymerase. We isolated M. smegmatis strains harbouring either an insertion (6 aa) or a deletion (10 aa) in their RpoB proteins. Although these strains showed a compromised fitness for growth in 7H9 Middlebrook medium, their resistance to Rif was remarkably high. The attenuated growth of the strains correlated with decreased specific activities of the RNA polymerases from the mutants. While the RNA polymerases from the parent or a mutant strain (harbouring a frequently occurring mutation, H442Y, in RpoB) were susceptible to Rif-mediated inhibition of transcription from calf thymus DNA, those from the insertion and deletion mutants were essentially refractory to such inhibition. Three-dimensional structure modelling revealed that the RpoB amino acids that interact with Rif are either deleted or unable to interact with Rif due to their unsuitable spatial positioning in these mutants. We discuss possible uses of the RpoB mutants in studying transcriptional regulation in mycobacteria and as potential targets for drug design.

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The TCP transcription factors control multiple developmental traits in diverse plant species. Members of this family share an similar to 60-residue-long TCP domain that binds to DNA. The TCP domain is predicted to form a basic helix-loop-helix ( bHLH) structure but shares little sequence similarity with canonical bHLH domain. This classifies the TCP domain as a novel class of DNA binding domain specific to the plant kingdom. Little is known about how the TCP domain interacts with its target DNA. We report biochemical characterization and DNA binding properties of a TCP member in Arabidopsis thaliana, TCP4. We have shown that the 58-residue domain of TCP4 is essential and sufficient for binding to DNA and possesses DNA binding parameters comparable to canonical bHLH proteins. Using a yeast-based random mutagenesis screen and site-directed mutants, we identified the residues important for DNA binding and dimer formation. Mutants defective in binding and dimerization failed to rescue the phenotype of an Arabidopsis line lacking the endogenous TCP4 activity. By combining structure prediction, functional characterization of the mutants, and molecular modeling, we suggest a possible DNA binding mechanism for this class of transcription factors.

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The PI3-kinase pathway is the target of inactivation in achieving better cancer chemotherapy. Here, we report that p53-mediated transcription is inhibited by pharmacological inhibitors and a dominant-negative mutant of PI3-kinase, and this inhibition was relieved by a constitutively active mutant of PI3-kinase. Akt/PKB and mTOR, the downstream effectors of PI3-kinase, were also found to be essential. LY294002 (PI3-kinase inhibitor) pre-treatment altered the post-translational modifications and the sub-cellular localization of p53. Although LY294002 increased the chemosensitivity of cells to low concentrations of adriamycin (adriamycin-low), it protected the cells from cytotoxicity induced by high concentrations of adriamycin (adriamycin-high) in a p53-dependent manner. Further, we found that LY294002 completely abolished the activation of p53 target genes (particularly pro-apoptotic) under adriamycin-high conditions, whereas it only marginally repressed the p53 target genes under adriamycin-low conditions; in fact, it further activated the transcription of NOXA, HRK, APAF1 and CASP5 genes. Thus, the differential effect of PI3-kinase on p53 functions seems to be responsible for the differential regulation of DNA damage-induced cytotoxicity and cell death by PI3-kinase. Our finding becomes relevant in the light of ongoing combination chemotherapy trials with the PI3-kinase pathway inhibitors and underscores the importance of p53 status in the careful formulation of combination chemotherapies. Oncogene (2010) 29, 3605-3618; doi: 10.1038/onc.2010.123; published online 26 April 2010

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The 3A region of foot-and-mouth disease virus has been implicated in host range and virulence. For example, amino acid deletions in the porcinophilic strain (O/TAW/97) at 93-102 aa of the 153 codons long 3A protein have been recognized as the determinant of species specificity. In the present study, 18 type 0 FMDV isolates from India were adapted in different cell culture systems and the 3A sequence was analyzed. These isolates had complete 3A coding sequence (153 aa) and did not exhibit growth restriction in cells based on species of origin. The 3A region was found to be highly conserved at N-terminal half (1-75 aa) but exhibited variability or substitutions towards C-terminal region (80-153). Moreover the amino acid substitutions were more frequent in recent Indian buffalo isolates but none of the Indian isolates showed deletion in 3A protein, which may be the reason for the absence of host specificity in vitro. Further inclusive analysis of 3A region will reveal interesting facts about the variability of FMD virus 3A region in an endemic environment. (C) 2010 Elsevier B.V. All rights reserved.

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The problem of assigning customers to satellite channels is considered. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of this approach with the standard optimization method is presented to show the advantages of this approach in terms of computation time

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DNA protein interactions that occur during transcription initiation play an important role in regulating gene expression. To initiate transcription, RNA polymerase (RNAP) binds to promoters in a sequence-specific fashion. This is followed by a series of steps governed by the equilibrium binding and kinetic rate constants, which in turn determine the overall efficiency of the transcription process. We present here the first detailed kinetic analysis of promoter RNAP interactions during transcription initiation in the sigma(A)-dependent promoters P-rrnAPCL1, P-rrnB and P-gyr of Mycobacterium smegmatis. The promoters show comparable equilibrium binding affinity but differ significantly in open complex formation, kinetics of isomerization and promoter clearance. Furthermore, the two rrn promoters exhibit varied kinetic properties during transcription initiation and appear to be subjected to different modes of regulation. In addition to distinct kinetic patterns, each one of the housekeeping promoters studied has its own rate-limiting step in the initiation pathway, indicating the differences in their regulation.