995 resultados para YEAST TRANSFER RNAPHE


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The research of power-line communications has been concentrated on home automation, broadband indoor communications and broadband data transfer in a low voltage distribution network between home andtransformer station. There has not been carried out much research work that is focused on the high frequency characteristics of industrial low voltage distribution networks. The industrial low voltage distribution network may be utilised as a communication channel to data transfer required by the on-line condition monitoring of electric motors. The advantage of using power-line data transfer is that it does not require the installing of new cables. In the first part of this work, the characteristics of industrial low voltage distribution network components and the pilot distribution network are measured and modelled with respect topower-line communications frequencies up to 30 MHz. The distributed inductances, capacitances and attenuation of MCMK type low voltage power cables are measured in the frequency band 100 kHz - 30 MHz and an attenuation formula for the cables is formed based on the measurements. The input impedances of electric motors (15-250 kW) are measured using several signal couplings and measurement based input impedance model for electric motor with a slotted stator is formed. The model is designed for the frequency band 10 kHz - 30 MHz. Next, the effect of DC (direct current) voltage link inverter on power line data transfer is briefly analysed. Finally, a pilot distribution network is formed and signal attenuation in communication channels in the pilot environment is measured. The results are compared with the simulations that are carried out utilising the developed models and measured parameters for cables and motors. In the second part of this work, a narrowband power-line data transfer system is developed for the data transfer ofon-line condition monitoring of electric motors. It is developed using standardintegrated circuits. The system is tested in the pilot environment and the applicability of the system for the data transfer required by the on-line condition monitoring of electric motors is analysed.

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Gas-liquid mass transfer is an important issue in the design and operation of many chemical unit operations. Despite its importance, the evaluation of gas-liquid mass transfer is not straightforward due to the complex nature of the phenomena involved. In this thesis gas-liquid mass transfer was evaluated in three different gas-liquid reactors in a traditional way by measuring the volumetric mass transfer coefficient (kLa). The studied reactors were a bubble column with a T-junction two-phase nozzle for gas dispersion, an industrial scale bubble column reactor for the oxidation of tetrahydroanthrahydroquinone and a concurrent downflow structured bed.The main drawback of this approach is that the obtained correlations give only the average volumetric mass transfer coefficient, which is dependent on average conditions. Moreover, the obtained correlations are valid only for the studied geometry and for the chemical system used in the measurements. In principle, a more fundamental approach is to estimate the interfacial area available for mass transfer from bubble size distributions obtained by solution of population balance equations. This approach has been used in this thesis by developing a population balance model for a bubble column together with phenomenological models for bubble breakage and coalescence. The parameters of the bubble breakage rate and coalescence rate models were estimated by comparing the measured and calculated bubble sizes. The coalescence models always have at least one experimental parameter. This is because the bubble coalescence depends on liquid composition in a way which is difficult to evaluate using known physical properties. The coalescence properties of some model solutions were evaluated by measuring the time that a bubble rests at the free liquid-gas interface before coalescing (the so-calledpersistence time or rest time). The measured persistence times range from 10 msup to 15 s depending on the solution. The coalescence was never found to be instantaneous. The bubble oscillates up and down at the interface at least a coupleof times before coalescence takes place. The measured persistence times were compared to coalescence times obtained by parameter fitting using measured bubble size distributions in a bubble column and a bubble column population balance model. For short persistence times, the persistence and coalescence times are in good agreement. For longer persistence times, however, the persistence times are at least an order of magnitude longer than the corresponding coalescence times from parameter fitting. This discrepancy may be attributed to the uncertainties concerning the estimation of energy dissipation rates, collision rates and mechanisms and contact times of the bubbles.

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The purpose of this study was to investigate some important features of granular flows and suspension flows by computational simulation methods. Granular materials have been considered as an independent state ofmatter because of their complex behaviors. They sometimes behave like a solid, sometimes like a fluid, and sometimes can contain both phases in equilibrium. The computer simulation of dense shear granular flows of monodisperse, spherical particles shows that the collisional model of contacts yields the coexistence of solid and fluid phases while the frictional model represents a uniform flow of fluid phase. However, a comparison between the stress signals from the simulations and experiments revealed that the collisional model would result a proper match with the experimental evidences. Although the effect of gravity is found to beimportant in sedimentation of solid part, the stick-slip behavior associated with the collisional model looks more similar to that of experiments. The mathematical formulations based on the kinetic theory have been derived for the moderatesolid volume fractions with the assumption of the homogeneity of flow. In orderto make some simulations which can provide such an ideal flow, the simulation of unbounded granular shear flows was performed. Therefore, the homogeneous flow properties could be achieved in the moderate solid volume fractions. A new algorithm, namely the nonequilibrium approach was introduced to show the features of self-diffusion in the granular flows. Using this algorithm a one way flow can beextracted from the entire flow, which not only provides a straightforward calculation of self-diffusion coefficient but also can qualitatively determine the deviation of self-diffusion from the linear law at some regions nearby the wall inbounded flows. Anyhow, the average lateral self-diffusion coefficient, which was calculated by the aforementioned method, showed a desirable agreement with thepredictions of kinetic theory formulation. In the continuation of computer simulation of shear granular flows, some numerical and theoretical investigations were carried out on mass transfer and particle interactions in particulate flows. In this context, the boundary element method and its combination with the spectral method using the special capabilities of wavelets have been introduced as theefficient numerical methods to solve the governing equations of mass transfer in particulate flows. A theoretical formulation of fluid dispersivity in suspension flows revealed that the fluid dispersivity depends upon the fluid properties and particle parameters as well as the fluid-particle and particle-particle interactions.

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Neuronal dynamics are fundamentally constrained by the underlying structural network architecture, yet much of the details of this synaptic connectivity are still unknown even in neuronal cultures in vitro. Here we extend a previous approach based on information theory, the Generalized Transfer Entropy, to the reconstruction of connectivity of simulated neuronal networks of both excitatory and inhibitory neurons. We show that, due to the model-free nature of the developed measure, both kinds of connections can be reliably inferred if the average firing rate between synchronous burst events exceeds a small minimum frequency. Furthermore, we suggest, based on systematic simulations, that even lower spontaneous inter-burst rates could be raised to meet the requirements of our reconstruction algorithm by applying a weak spatially homogeneous stimulation to the entire network. By combining multiple recordings of the same in silico network before and after pharmacologically blocking inhibitory synaptic transmission, we show then how it becomes possible to infer with high confidence the excitatory or inhibitory nature of each individual neuron.

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Yeast successfully adapts to an environmental stress by altering physiology and fine-tuning metabolism. This fine-tuning is achieved through regulation of both gene expression and protein activity, and it is shaped by various physiological requirements. Such requirements impose a sustained evolutionary pressure that ultimately selects a specific gene expression profile, generating a suitable adaptive response to each environmental change. Although some of the requirements are stress specific, it is likely that others are common to various situations. We hypothesize that an evolutionary pressure for minimizing biosynthetic costs might have left signatures in the physicochemical properties of proteins whose gene expression is fine-tuned during adaptive responses. To test this hypothesis we analyze existing yeast transcriptomic data for such responses and investigate how several properties of proteins correlate to changes in gene expression. Our results reveal signatures that are consistent with a selective pressure for economy in protein synthesis during adaptive response of yeast to various types of stress. These signatures differentiate two groups of adaptive responses with respect to how cells manage expenditure in protein biosynthesis. In one group, significant trends towards downregulation of large proteins and upregulation of small ones are observed. In the other group we find no such trends. These results are consistent with resource limitation being important in the evolution of the first group of stress responses.

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Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.

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Background: Wine Saccharomyces cerevisiae strains, adapted to anaerobic must fermentations, suffer oxidative stress when they are grown under aerobic conditions for biomass propagation in the industrial process of active dry yeast production. Oxidative metabolism of sugars favors high biomass yields but also causes increased oxidation damage of cell components. The overexpression of the TRX2 gene, coding for a thioredoxin, enhances oxidative stress resistance in a wine yeast strain model. The thioredoxin and also the glutathione/glutaredoxin system constitute the most important defense against oxidation. Trx2p is also involved in the regulation of Yap1p-driven transcriptional response against some reactive oxygen species. Results: Laboratory scale simulations of the industrial active dry biomass production process demonstrate that TRX2 overexpression increases the wine yeast final biomass yield and also its fermentative capacity both after the batch and fed-batch phases. Microvinifications carried out with the modified strain show a fast start phenotype derived from its enhanced fermentative capacity and also increased content of beneficial aroma compounds. The modified strain displays an increased transcriptional response of Yap1p regulated genes and other oxidative stress related genes. Activities of antioxidant enzymes like Sod1p, Sod2p and catalase are also enhanced. Consequently, diminished oxidation of lipids and proteins is observed in the modified strain, which can explain the improved performance of the thioredoxin overexpressing strain. Conclusions: We report several beneficial effects of overexpressing the thioredoxin gene TRX2 in a wine yeast strain. We show that this strain presents an enhanced redox defense. Increased yield of biomass production process in TRX2 overexpressing strain can be of special interest for several industrial applications.

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Both the intermolecular interaction energies and the geometries for M ̄ thiophene, M ̄ pyrrole, M n+ ̄ thiophene, and M n+ ̄ pyrrole ͑with M = Li, Na, K, Ca, and Mg; and M n+ = Li+ , Na+ , K+ , Ca2+, and Mg2+͒ have been estimated using four commonly used density functional theory ͑DFT͒ methods: B3LYP, B3PW91, PBE, and MPW1PW91. Results have been compared to those provided by HF, MP2, and MP4 conventional ab initio methods. The PBE and MPW1PW91 are the only DFT methods able to provide a reasonable description of the M ̄ complexes. Regarding M n+ ̄ ␲ complexes, the four DFT methods have been proven to be adequate in the prediction of these electrostatically stabilized systems, even though they tend to overestimate the interaction energies.

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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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We have analyzed the heat stress response in the yeast Saccharomyces cerevisiae by determining mRNA levels and transcription rates for the whole transcriptome after a shift from 25uC to 37uC. Using an established mathematical algorithm, theoretical mRNA decay rates have also been calculated from the experimental data. We have verified the mathematical predictions for selected genes by determining their mRNA decay rates at different times during heat stress response using the regulatable tetO promoter. This study indicates that the yeast response to heat shock is not only due to changes in transcription rates, but also to changes in the mRNA stabilities. mRNA stability is affected in 62% of the yeast genes and it is particularly important in shaping the mRNA profile of the genes belonging to the environmental stress response. In most cases, changes in transcription rates and mRNA stabilities are homodirectional for both parameters, although some interesting cases of antagonist behavior are found. The statistical analysis of gene targets and sequence motifs within the clusters of genes with similar behaviors shows that both transcriptional and post-transcriptional regulons apparently contribute to the general heat stress response by means of transcriptional factors and RNA binding proteins.

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Cell-cell fusion is essential for fertilization. For fusion of walled cells, the cell wall must be degraded at a precise location but maintained in surrounding regions to protect against lysis. In fission yeast cells, the formin Fus1, which nucleates linear actin filaments, is essential for this process. In this paper, we show that this formin organizes a specific actin structure-the actin fusion focus. Structured illumination microscopy and live-cell imaging of Fus1, actin, and type V myosins revealed an aster of actin filaments whose barbed ends are focalized near the plasma membrane. Focalization requires Fus1 and type V myosins and happens asynchronously always in the M cell first. Type V myosins are essential for fusion and concentrate cell wall hydrolases, but not cell wall synthases, at the fusion focus. Thus, the fusion focus focalizes cell wall dissolution within a broader cell wall synthesis zone to shift from cell growth to cell fusion.

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Background: In the yeast biomass production process, protein carbonylation has severe adverse effects since it diminishes biomass yield and profitability of industrial production plants. However, this significant detriment of yeast performance can be alleviated by increasing thioredoxins levels. Thioredoxins are important antioxidant defenses implicated in many functions in cells, and their primordial functions include scavenging of reactive oxygen species that produce dramatic and irreversible alterations such as protein carbonylation. Results: In this work we have found several proteins specifically protected by yeast Thioredoxin 2 (Trx2p). Bidimensional electrophoresis and carbonylated protein identification from TRX-deficient and TRX-overexpressing cells revealed that glycolysis and fermentation-related proteins are specific targets of Trx2p protection. Indeed, the TRX2 overexpressing strain presented increased activity of the central carbon metabolism enzymes. Interestingly, Trx2p specifically preserved alcohol dehydrogenase I (Adh1p) from carbonylation, decreased oligomer aggregates and increased its enzymatic activity. Conclusions: The identified proteins suggest that the fermentative capacity detriment observed under industrial conditions in T73 wine commercial strain results from the oxidative carbonylation of specific glycolytic and fermentation enzymes. Indeed, increased thioredoxin levels enhance the performance of key fermentation enzymes such as Adh1p, which consequently increases fermentative capacity.

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Cell polarity is essential for various cellular functions during both proliferative and developmental stages, and it displays dynamic alterations in response to intracellular and extracellular cues. However, the molecular mechanisms underlying spatiotemporal control of polarity transition are poorly understood. Here, we show that fission yeast Cki3 (a casein kinase 1γ homolog) is a critical regulator to ensure persistent monopolar growth during S phase. Unlike the wild type, cki3 mutant cells undergo bipolar growth when S phase is blocked, a condition known to delay transition from monopolar to bipolar growth (termed NETO [new end takeoff]). Consistent with this role, Cki3 kinase activity is substantially increased, and cells lose their viability in the absence of Cki3 upon an S-phase block. Cki3 acts downstream of the checkpoint kinase Cds1/Chk2 and calcineurin, and the latter physically interacts with Cki3. Autophosphorylation in the C terminus is inhibitory toward Cki3 kinase activity, and calcineurin is responsible for its dephosphorylation. Cki3 localizes to the plasma membrane, and this localization requires the palmitoyltransferase complex Erf2-Erf4. Membrane localization is needed not only for proper NETO timing but also for Cki3 kinase activity. We propose that Cki3 acts as a critical inhibitor of cell polarity transition under S-phase arrest.

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We have developed an activator/repressor expression system for budding yeast in which tetracyclines control in opposite ways the ability of tetR-based activator and repressor molecules to bind tetO promoters. This combination allows tight expression of tetO-driven genes, both in a direct (tetracycline-repressible) and reverse (tetracycline-inducible) dual system. Ssn6 and Tup1, that are components of a general repressor complex in yeast, have been tested for their repressing properties in the dual system, using lacZ and CLN2 as reporter genes. Ssn6 gives better results and allows complete switching-off of the regulated genes, although increasing the levels of the Tup1-based repressor by expressing it from a stronger promoter improves repressing efficiency of the latter. Effector-mediated shifts between expression and non-expression conditions are rapid. The dual system here described may be useful for the functional analysis of essential genes whose conditional expression can be tightly controlled by tetracyclines.

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The genomes of two hemiascomycetous yeasts (Saccharomyces cerevisiae and Candida albicans) and one archiascomycete (Schizosaccharomyces pombe) have been completely sequenced and the genes have been annotated. In addition, the genomes of 13 more Hemiascomycetes have been partially sequenced. The amount of data thus obtained provides information on the evolutionary relationships between yeast species. In addition, the differential genetic characteristics of the microorganisms explain a number of distinctive biological traits. Gene order conservation is observed between phylogenetically close species and is lost in distantly related species, probably due to rearrangements of short regions of DNA. However, gene function is much more conserved along evolution. Compared to S. cerevisiae and S. pombe, C. albicans has a larger number of specific genes, i.e., genes not found in other organisms, a fact that can account for the biological characteristics of this pathogenic dimorphic yeast which is able to colonize a large variety of environments.