75 resultados para gene transcriptional regulatory network, stochastic differential equation, membership function
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An equation for mean first-passage times of non-Markovian processes driven by colored noise is derived through an appropriate backward integro-differential equation. The equation is solved in a Bourret-like approximation. In a weak-noise bistable situation, non-Markovian effects are taken into account by an effective diffusion coefficient. In this situation, our results compare satisfactorily with other approaches and experimental data.
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Background: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). Results: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. Conclusion: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models.
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Langevin Equations of Ginzburg-Landau form, with multiplicative noise, are proposed to study the effects of fluctuations in domain growth. These equations are derived from a coarse-grained methodology. The Cahn-Hiliard-Cook linear stability analysis predicts some effects in the transitory regime. We also derive numerical algorithms for the computer simulation of these equations. The numerical results corroborate the analytical predictions of the linear analysis. We also present simulation results for spinodal decomposition at large times.
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Recent reports point out the importance of the complex GK-GKRP in controlling glucose and lipid homeostasis. Several GK mutations affect GKRP binding, resulting in permanent activation of the enzyme. We hypothesize that hepatic overexpression of a mutated form of GK, GKA456V, described in a patient with persistent hyperinsulinemic hypoglycemia of infancy (PHHI) and could provide a model to study the consequences of GK-GKRP deregulation in vivo. GKA456V was overexpressed in the liver of streptozotocin diabetic mice. Metabolite profiling in serum and liver extracts, together with changes in key components of glucose and lipid homeostasis, were analyzed and compared to GK wild-type transfected livers. Cell compartmentalization of the mutant but not the wild-type GK was clearly affected in vivo, demonstrating impaired GKRP regulation. GKA456V overexpression markedly reduced blood glucose in the absence of dyslipidemia, in contrast to wild-type GK-overexpressing mice. Evidence in glucose utilization did not correlate with increased glycogen nor lactate levels in the liver. PEPCK mRNA was not affected, whereas the mRNA for the catalytic subunit of glucose-6-phosphatase was upregulated ~4 folds in the liver of GKA456V-treated animals, suggesting that glucose cycling was stimulated. Our results provide new insights into the complex GK regulatory network and validate liver-specific GK activation as a strategy for diabetes therapy.
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The known properties of diffusion on fractals are reviewed in order to give a general outlook of these dynamic processes. After that, we propose a description developed in the context of the intrinsic metric of fractals, which leads us to a differential equation able to describe diffusion in real fractals in the asymptotic regime. We show that our approach has a stronger physical justification than previous works on this field. The most important result we present is the introduction of a dependence on time and space for the conductivity in fractals, which is deduced by scaling arguments and supported by computer simulations. Finally, the diffusion equation is used to introduce the possibility of reaction-diffusion processes on fractals and analyze their properties. Specifically, an analytic expression for the speed of the corresponding travelling fronts, which can be of great interest for application purposes, is derived
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We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network covera.
Resumo:
We study a retail benchmarking approach to determine access prices for interconnected networks. Instead of considering fixed access charges as in the existing literature, we study access pricing rules that determine the access price that network i pays to network j as a linear function of the marginal costs and the retail prices set by both networks. In the case of competition in linear prices, we show that there is a unique linear rule that implements the Ramsey outcome as the unique equilibrium, independently of the underlying demand conditions. In the case of competition in two-part tariffs, we consider a class of access pricing rules, similar to the optimal one under linear prices but based on average retail prices. We show that firms choose the variable price equal to the marginal cost under this class of rules. Therefore, the regulator (or the competition authority) can choose one among the rules to pursue additional objectives such as consumer surplus, network coverage or investment: for instance, we show that both static and dynamic e±ciency can be achieved at the same time.
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A discussion on the expression proposed in [1]–[3]for deconvolving the wideband density function is presented. Weprove here that such an expression reduces to be proportionalto the wideband correlation receiver output, or continuous wavelettransform of the received signal with respect to the transmittedone. Moreover, we show that the same result has been implicitlyassumed in [1], when the deconvolution equation is derived. Westress the fact that the analyzed approach is just the orthogonalprojection of the density function onto the image of the wavelettransform with respect to the transmitted signal. Consequently,the approach can be considered a good representation of thedensity function only under the prior knowledge that the densityfunction belongs to such a subspace. The choice of the transmittedsignal is thus crucial to this approach.
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Background: The arrangement of regulatory motifs in gene promoters, or promoterarchitecture, is the result of mutation and selection processes that have operated over manymillions of years. In mammals, tissue-specific transcriptional regulation is related to the presence ofspecific protein-interacting DNA motifs in gene promoters. However, little is known about therelative location and spacing of these motifs. To fill this gap, we have performed a systematic searchfor motifs that show significant bias at specific promoter locations in a large collection ofhousekeeping and tissue-specific genes.Results: We observe that promoters driving housekeeping gene expression are enriched inparticular motifs with strong positional bias, such as YY1, which are of little relevance in promotersdriving tissue-specific expression. We also identify a large number of motifs that show positionalbias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specificmotifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis,as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictionsfor 559 tissue-specific motifs in mouse gene promoters.Conclusion: The study shows that motif positional bias is an important feature of mammalianproximal promoters and that it affects both general and tissue-specific motifs. Motif positionalconstraints define very distinct promoter architectures depending on breadth of expression andtype of tissue.
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Assessing the contribution of promoters and coding sequences to gene evolution is an important step toward discovering the major genetic determinants of human evolution. Many specific examples have revealed the evolutionary importance of cis-regulatory regions. However, the relative contribution of regulatory and coding regions to the evolutionary process and whether systemic factors differentially influence their evolution remains unclear. To address these questions, we carried out an analysis at the genome scale to identify signatures of positive selection in human proximal promoters. Next, we examined whether genes with positively selected promoters (Prom+ genes) show systemic differences with respect to a set of genes with positively selected protein-coding regions (Cod+ genes). We found that the number of genes in each set was not significantly different (8.1% and 8.5%, respectively). Furthermore, a functional analysis showed that, in both cases, positive selection affects almost all biological processes and only a few genes of each group are located in enriched categories, indicating that promoters and coding regions are not evolutionarily specialized with respect to gene function. On the other hand, we show that the topology of the human protein network has a different influence on the molecular evolution of proximal promoters and coding regions. Notably, Prom+ genes have an unexpectedly high centrality when compared with a reference distribution (P = 0.008, for Eigenvalue centrality). Moreover, the frequency of Prom+ genes increases from the periphery to the center of the protein network (P = 0.02, for the logistic regression coefficient). This means that gene centrality does not constrain the evolution of proximal promoters, unlike the case with coding regions, and further indicates that the evolution of proximal promoters is more efficient in the center of the protein network than in the periphery. These results show that proximal promoters have had a systemic contribution to human evolution by increasing the participation of central genes in the evolutionary process.
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Background: The G1-to-S transition of the cell cycle in the yeast Saccharomyces cerevisiae involves an extensive transcriptional program driven by transcription factors SBF (Swi4-Swi6) and MBF (Mbp1-Swi6). Activation of these factors ultimately depends on the G1 cyclin Cln3. Results: To determine the transcriptional targets of Cln3 and their dependence on SBF or MBF, we first have used DNA microarrays to interrogate gene expression upon Cln3 overexpression in synchronized cultures of strains lacking components of SBF and/or MBF. Secondly, we have integrated this expression dataset together with other heterogeneous data sources into a single probabilistic model based on Bayesian statistics. Our analysis has produced more than 200 transcription factor-target assignments, validated by ChIP assays and by functional enrichment. Our predictions show higher internal coherence and predictive power than previous classifications. Our results support a model whereby SBF and MBF may be differentially activated by Cln3. Conclusions: Integration of heterogeneous genome-wide datasets is key to building accurate transcriptional networks. By such integration, we provide here a reliable transcriptional network at the G1-to-S transition in the budding yeast cell cycle. Our results suggest that to improve the reliability of predictions we need to feed our models with more informative experimental data.
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6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFKFB)catalyzes the synthesis and degradation of fructose-2,6-bisphosphate, a key modulator of glycolysis-gluconeogenesis. To gain insight into the molecular mechanism behind hormonal and nutritional regulation of PFKFB expression, we have cloned and characterized the proximal promoter region of the liver isoform of PFKFB (PFKFB1) from gilthead sea bream (Sparus aurata). Transient transfection of HepG2 cells with deleted gene promoter constructs and electrophoretic mobility shift assays allowed us to identify a sterol regulatory element (SRE) to which SRE binding protein-1a (SREBP-1a)binds and transactivates PFKFB1 gene transcription. Mutating the SRE box abolished SREBP-1a binding and transactivation. The in vivo binding of SREBP-1a to the SRE box in the S. aurata PFKFB1 promoter was confirmed by chromatin immunoprecipitation assays. There is a great deal of evidence for a postprandial rise of PFKB1 mRNA levels in fish and rats. Consistently, starved-to-fed transition and treatment with glucose or insulin increased SREBP-1 immunodetectable levels, SREBP-1 association to PFKFB1 promoter, and PFKFB1 mRNA levels in the piscine liver. Our findings demonstrate involvement of SREBP-1a in the transcriptional activation of PFKFB1, and we conclude that SREBP-1a may exert a key role mediating postprandial activation of PFKFB1 transcription.
Resumo:
6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFKFB)catalyzes the synthesis and degradation of fructose-2,6-bisphosphate, a key modulator of glycolysis-gluconeogenesis. To gain insight into the molecular mechanism behind hormonal and nutritional regulation of PFKFB expression, we have cloned and characterized the proximal promoter region of the liver isoform of PFKFB (PFKFB1) from gilthead sea bream (Sparus aurata). Transient transfection of HepG2 cells with deleted gene promoter constructs and electrophoretic mobility shift assays allowed us to identify a sterol regulatory element (SRE) to which SRE binding protein-1a (SREBP-1a)binds and transactivates PFKFB1 gene transcription. Mutating the SRE box abolished SREBP-1a binding and transactivation. The in vivo binding of SREBP-1a to the SRE box in the S. aurata PFKFB1 promoter was confirmed by chromatin immunoprecipitation assays. There is a great deal of evidence for a postprandial rise of PFKB1 mRNA levels in fish and rats. Consistently, starved-to-fed transition and treatment with glucose or insulin increased SREBP-1 immunodetectable levels, SREBP-1 association to PFKFB1 promoter, and PFKFB1 mRNA levels in the piscine liver. Our findings demonstrate involvement of SREBP-1a in the transcriptional activation of PFKFB1, and we conclude that SREBP-1a may exert a key role mediating postprandial activation of PFKFB1 transcription.
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Growth experiments showed that adenine and hypoxanthine can be used as nitrogen sources by several strains of K. pneumoniae under aerobic conditions. The assimilation of all nitrogens from these purines indicates that the catabolic pathway is complete and proceeds past allantoin. Here we identify the genetic system responsible for the oxidation of hypoxanthine to allantoin in K. pneumoniae. The hpx cluster consists of seven genes, for which an organization in four transcriptional units, hpxDE, hpxR, hpxO and hpxPQT, is proposed. The proteins involved in the oxidation of hypoxanthine (HpxDE) or uric acid (HpxO) did not display any similarity to other reported enzymes known to catalyze these reactions, but instead are similar to oxygenases acting on aromatic compounds. Expression of the hpx system is activated by nitrogen limitation and by the presence of specific substrates, with hpxDE and hpxPQT controlled by both signals. Nitrogen control of hpxPQT transcription, which depends on 54, is mediated by the Ntr system. In contrast, neither NtrC nor NAC is involved in the nitrogen control of hpxDE, which is dependent on 70 for transcription. Activation of these operons by the specific substrates is also mediated by different effectors and regulatory proteins. Induction of hpxPQT requires uric acid formation, whereas expression of hpxDE is induced by the presence of hypoxanthine through the regulatory protein HpxR. This LysR-type regulator binds to a TCTGC-N4-GCAAA site in the intergenic hpxD-hpxR region. When bound to this site for hpxDE activation, HpxR negatively controls its own transcription.