Energetic and metabolic transient response of Saccharomyces cerevisiae to benzoic acid

Saccharomyces cerevisiae is known to be able to adapt to the presence of the commonly used food preservative benzoic acid with a large energy expenditure. Some mechanisms for the adaptation process have been suggested, but its quantitative energetic and metabolic aspects have rarely been discussed. This study discusses use of the stimulus response approach to quantitatively study the energetic and metabolic aspects of the transient adaptation of S. cerevisiae to a shift in benzoic acid concentration, from 0 to 0.8 mM. The information obtained also serves as the basis for further utilization of benzoic acid as a tool for targeted perturbation of the energy system, which is important in studying the kinetics and regulation of central carbon metabolism in S. cerevisiae. Using this experimental set-up, we found significant fast-transient (< 3000 s) increases in O(2) consumption and CO(2) production rates, of approximately 50%, which reflect a high energy requirement for the adaptation process. We also found that with a longer exposure time to benzoic acid, S. cerevisiae decreases the cell membrane permeability for this weak acid by a factor of 10 and decreases the cell size to approximately 80% of the initial value. The intracellular metabolite profile in the new steady-state indicates increases in the glycolytic and tricarboxylic acid cycle fluxes, which are in agreement with the observed increases in specific glucose and O(2) uptake rates.     

13C-Labeled metabolic flux analysis of a fed-batch culture of elutriated Saccharomyces cerevisiae

This study addresses the question of whether observable changes in fluxes in the primary carbon metabolism of Saccharomyces cerevisiae occur between the different phases of the cell division cycle. To detect such changes by metabolic flux analysis, a 13C-labeling experiment was performed with a fed-batch culture inoculated with a partially synchronized cell population obtained through centrifugal elutriation. Such a culture exhibits dynamic changes in the fractions of cells in different cell cycle phases over time. The mass isotopomer distributions of free intracellular metabolites in central carbon metabolism were measured by liquid chromatography-mass spectrometry. For four time points during the culture, these distributions were used to obtain the best estimates for the metabolic fluxes. The obtained flux fits suggested that the optimally fitted split ratio for the pentose phosphate pathway changed by almost a factor of 2 up and down around a value of 0.27 during the experiment. Statistical analysis revealed that some of the fitted flux distributions for different time points were significantly different from each other, indicating that cell cycle-dependent variations in cytosolic metabolic fluxes indeed occurred.     

Schemes of flux control in a model of Saccharomyces cerevisiae glycolysis.

We used parameter scanning to emulate changes to the limiting rate for steps in a fitted model of glucose-derepressed yeast glycolysis. Three flux-control regimes were observed, two of which were under the dominant control of hexose transport, in accordance with various experimental studies and other model predictions. A third control regime in which phosphofructokinase exerted dominant glycolytic flux control was also found, but it appeared to be physiologically unreachable by this model, and all realistically obtainable flux control regimes featured hexose transport as a step involving high flux control.     

Improve carbon metabolic flux in Saccharomyces cerevisiae at high temperature by overexpressed TSL1 gene

This study describes a novel strategy to improve the glycolysis flux of Saccharomyces cerevisiae at high temperature. The TSL1 gene-encoding regulatory subunit of the trehalose synthase complex was overexpressed in S. cerevisiae Z-06, which increased levels of trehalose synthase activity in extracts, enhanced stress tolerance and glucose consuming rate of the yeast cells. As a consequence, the final ethanol concentration of 185.5 g/L was obtained at 38 °C for 36 h (with productivity up to 5.2 g/L/h) in 7-L fermentor, and the ethanol productivity was 92.7 % higher than that of the parent strain. The results presented here provide a novel way to enhance the carbon metabolic flux at high temperature, which will be available for the purposes of producing other primary metabolites of commercial interest using S. cerevisiae as a host.     

A constraint-based model analysis of the metabolic consequences of increased NADPH oxidation in Saccharomyces cerevisiae

Controlling the amounts of redox cofactors to manipulate metabolic fluxes is emerging as a useful approach to optimizing byproduct yields in yeast biotechnological processes. Redox cofactors are extensively interconnected metabolites, so predicting metabolite patterns is challenging and requires in-depth knowledge of how the metabolic network responds to a redox perturbation. Our aim was to analyze comprehensively the metabolic consequences of increased cytosolic NADPH oxidation during yeast fermentation. Using a genetic device based on the overexpression of a modified 2,3-butanediol dehydrogenase catalyzing the NADPH-dependent reduction of acetoin into 2,3-butanediol, we increased the NADPH demand to between 8 and 40-fold the anabolic demand. We developed (i) a dedicated constraint-based model of yeast fermentation and (ii) a constraint-based modeling method based on the dynamical analysis of mass distribution to quantify the in vivo contribution of pathways producing NADPH to the maintenance of redox homeostasis. We report that yeast responds to NADPH oxidation through a gradual increase in the flux through the PP and acetate pathways, providing 80% and 20% of the NADPH demand, respectively. However, for the highest NADPH demand, the model reveals a saturation of the PP pathway and predicts an exchange between NADH and NADPH in the cytosol that may be mediated by the glycerol-DHA futile cycle. We also reveal the contribution of mitochondrial shuttles, resulting in a net production of NADH in the cytosol, to fine-tune the NADH/NAD(+) balance. This systems level study helps elucidate the physiological adaptation of yeast to NADPH perturbation. Our findings emphasize the robustness of yeast to alterations in NADPH metabolism and highlight the role of the glycerol-DHA cycle as a redox valve, providing additional NADPH from NADH under conditions of very high demand.     

Gel and gel-free proteomics to identify Saccharomyces cerevisiae cell surface proteins

The study of Saccharomyces cerevisiae cell surface proteins was performed because of their important role in cell wall biogenesis and in the physiology of the yeast. Two different proteomic approaches were carried out. First, proteins loosely associated or S–S linked to structural wall components were released by treatment of whole intact cells with dithiothreitol, separated by 2D-PAGE and identified by mass spectrometry. Second, cell surface-exposed proteins (surfome) were digested with trypsin and DTT from whole intact cells, and analyzed by LC–MS/MS. Ninety-nine different proteins were identified: 67 with DTT treatment and 52 with DTT and trypsin digestion. These proteins were classified in different cellular processes: control of cell wall organization, cell rescue, defence, and virulence, protein fate, protein synthesis and metabolism. Most of the proteins have already been reported as present on the cell surface showing that the yeast cell surface is composed not only by typical but also by atypical cell wall proteins. “Bona fide” cell wall proteins were identified by both protocols but a higher number with the non-gel strategy. However, only 20% of the proteins identified were common to both protocols, thus, for a complete knowledge of the cell surface proteome, several strategies have to be used.     

Use of a synthetic lethal screen to identify genes related to TIF51A in Saccharomyces cerevisiae

The putative eukaryotic translation initiation factor 5A (eIF5A) is an essential protein for cell viability and the only cellular protein known to contain the unusual amino acid residue hypusine. eIF5A has been implicated in translation initiation, cell proliferation, nucleocytoplasmic transport, mRNA decay, and actin polarization, but the precise biological function of this protein is not clear. However, eIF5A was recently shown to be directly involved with the translational machinery. A screen for synthetic lethal mutations was carried out with one of the temperature-sensitive alleles of TIF51A (tif51A-3) to identify factors that functionally interact with eIF5A and revealed the essential gene YPT1. This gene encodes a small GTPase, a member of the rab family involved with secretion, acting in the vesicular trafficking between endoplasmatic reticulum and the Golgi. Thus, the synthetic lethality between TIF51A and YPT1 may reveal the connection between translation and the polarized distribution of membrane components, suggesting that these proteins work together in the cell to guarantee proper protein synthesis and secretion necessary for correct bud formation during G1/S transition. Future studies will investigate the functional interaction between eIF5A and Ypt1 in order to clarify this involvement of eIF5A with vesicular trafficking.     

Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae

Background  

The yeast Saccharomyces cerevisiae is an important microorganism for both industrial processes and scientific research. Consequently, there have been extensive efforts to characterize its cellular processes. In order to fully understand the relationship between yeast's genome and its physiology, the stockpiles of diverse biological data sets that describe its cellular components and phenotypic behavior must be integrated at the genome-scale. Genome-scale metabolic networks have been reconstructed for several microorganisms, including S. cerevisiae, and the properties of these networks have been successfully analyzed using a variety of constraint-based methods. Phenotypic phase plane analysis is a constraint-based method which provides a global view of how optimal growth rates are affected by changes in two environmental variables such as a carbon and an oxygen uptake rate. Some applications of phenotypic phase plane analysis include the study of optimal growth rates and of network capaCity and function.     

The metabolic response of Saccharomyces cerevisiae to continuous heat stress

A study has been initiated to integrate molecular and physiological responses of Saccharomyces cerevisiae to heat stress conditions. We focus our research on a quantification of the energetics of the stress response. A series of continuous heat stresses was applied to exponentially growing cells of the strain X2180-1A at 28°C, by increasing the growth temperature to 37, 39, 40, 41, 42, or 43°C. Here, the results on cell growth and viability, as well as on anabolic and catabolic rates are presented. We observed a surprisingly thin line for the cells between growing, surviving, and dying, with regard to growth temperature. The heat stress showed a dual effect on catabolism: immediately after the temperature increase a strong peak was seen, after which a new, steady level was reached. In addition, the yield on glucose decreased with increasing temperature. Our results indicate that life at elevated temperatures is energetically unfavourable and a non-lethal heat stress invokes a redistribution of catabolic and anabolic fluxes.     

In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: II. Mathematical model

A mathematical model of glycolysis in Saccharomyces cerevisiae is presented. The model is based on rate equations for the individual reactions and aims to predict changes in the levels of intra- and extracellular metabolites after a glucose pulse, as described in part I of this study. Kinetic analysis focuses on a time scale of seconds, thereby neglecting biosynthesis of new enzymes. The model structure and experimental observations are related to the aerobic growth of the yeast. The model is based on material balance equations of the key metabolites in the extracellular environment, the cytoplasm and the mitochondria, and includes mechanistically based, experimentally matched rate equations for the individual enzymes. The model includes removal of metabolites from glycolysis and TCC for biosynthesis, and also compartmentation and translocation of adenine nucleotides. The model was verified by in vivo diagnosis of intracellular enzymes, which includes the decomposition of the network of reactions to reduce the number of parameters to be estimated simultaneously. Additionally, sensitivity analysis guarantees that only those parameters are estimated that contribute to systems trajectory with reasonable sensitivity. The model predictions and experimental observations agree reasonably well for most of the metabolites, except for pyruvate and adenine nucleotides. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 55: 592-608, 1997.     

A biochemically structured model for Saccharomyces cerevisiae.

A biochemically structured model for the aerobic growth of Saccharomyces cerevisiae on glucose and ethanol is presented. The model focuses on the pyruvate and acetaldehyde branch points where overflow metabolism occurs when the growth changes from oxidative to oxido-reductive. The model is designed to describe the onset of aerobic alcoholic fermentation during steady-state as well as under dynamical conditions, by triggering an increase in the glycolytic flux using a key signalling component which is assumed to be closely related to acetaldehyde. An investigation of the modelled process dynamics in a continuous cultivation revealed multiple steady states in a region of dilution rates around the transition between oxidative and oxido-reductive growth. A bifurcation analysis using the two external variables, the dilution rate, D, and the inlet concentration of glucose, S(f), as parameters, showed that a fold bifurcation occurs close to the critical dilution rate resulting in multiple steady-states. The region of dilution rates within which multiple steady states may occur depends strongly on the substrate feed concentration. Consequently a single steady state may prevail at low feed concentrations, whereas multiple steady states may occur over a relatively wide range of dilution rates at higher feed concentrations.     

FKBP12 controls aspartate pathway flux in Saccharomyces cerevisiae to prevent toxic intermediate accumulation

FKBP12 is a conserved member of the prolyl-isomerase enzyme family and serves as the intracellular receptor for FK506 that mediates immunosuppression in mammals and antimicrobial actions in fungi. To investigate the cellular functions of FKBP12 in Saccharomyces cerevisiae, we employed a high-throughput assay to identify mutations that are synthetically lethal with a mutation in the FPR1 gene, which encodes FKBP12. This screen identified a mutation in the HOM6 gene, which encodes homoserine dehydrogenase, the enzyme catalyzing the last step in conversion of aspartic acid into homoserine, the common precursor in threonine and methionine synthesis. Lethality of fpr1 hom6 double mutants was suppressed by null mutations in HOM3 or HOM2, encoding aspartokinase and aspartate beta-semialdehyde dehydrogenase, respectively, supporting the hypothesis that fpr1 hom6 double mutants are inviable because of toxic accumulation of aspartate beta-semialdehyde, the substrate of homoserine dehydrogenase. Our findings also indicate that mutation or inhibition of FKBP12 dysregulates the homoserine synthetic pathway by perturbing aspartokinase feedback inhibition by threonine. Because this pathway is conserved in fungi but not in mammals, our findings suggest a facile route to synergistic antifungal drug development via concomitant inhibition of FKBP12 and Hom6.     

Construction of robust dynamic genome-scale metabolic model structures of Saccharomyces cerevisiae through iterative re-parameterization

Dynamic flux balance analysis (dFBA) has been widely employed in metabolic engineering to predict the effect of genetic modifications and environmental conditions in the cell׳s metabolism during dynamic cultures. However, the importance of the model parameters used in these methodologies has not been properly addressed. Here, we present a novel and simple procedure to identify dFBA parameters that are relevant for model calibration. The procedure uses metaheuristic optimization and pre/post-regression diagnostics, fixing iteratively the model parameters that do not have a significant role. We evaluated this protocol in a Saccharomyces cerevisiae dFBA framework calibrated for aerobic fed-batch and anaerobic batch cultivations. The model structures achieved have only significant, sensitive and uncorrelated parameters and are able to calibrate different experimental data. We show that consumption, suboptimal growth and production rates are more useful for calibrating dynamic S. cerevisiae metabolic models than Boolean gene expression rules, biomass requirements and ATP maintenance.     

A transient proteasome activation is needed for acetic acid-induced programmed cell death to occur in Saccharomyces cerevisiae

To gain further insight into the mechanism by which yeast programmed cell death (PCD) occurs, we investigated whether and how proteasome activity changes in Saccharomyces cerevisiae cells undergoing PCD as a result of treatment with acetic acid (AA-PCD). We show that proteasome activation starts 60 min after AA-PCD induction, with a maximum at 90 min, and decreases at 150 min. Moreover, cell survival measurements carried out in the absence or presence of MG132, which inhibits proteasome function, show that the inhibition of proteasome activity partially prevents AA-PCD, thus indicating that a transient proteasome activation is needed for AA-PCD to occur.     

Using extreme gradient boosting to identify origin of replication in Saccharomyces cerevisiae via hybrid features

DNA replication is a fundamental task that plays a crucial role in the propagation of all living things on earth. Hence, the accurate identification of its origin could be the key to giving an insightful understanding of the regulatory mechanism of gene expression. Indeed, with the robust development of computational techniques and the abundant biological sequencing data, it has become possible for scientists to identify the origin of replication accurately and promptly. This growing concern has drawn a lot of attention among experts in this field. However, to gain better outcomes, more work is required. Therefore, this study is designed to explore the combination of state-of-the-art features and extreme gradient boosting learning system in classifying DNA sequences. Our hybrid approach is able to identify the origin of DNA replication with achieved sensitivity of 85.19%, specificity of 93.83%, accuracy of 89.51%, and MCC of 0.7931. Evidence is presented to show that our proposed method is superior to the state-of-the-art methods on the same benchmark dataset. Moreover, the research results represent a further step towards developing the prediction models for DNA replication in particular and DNA sequences in general.     

代谢改造酿酒酵母合成萜类化合物的研究进展

萜类化合物是一类种类繁多、功能多样的化合物,部分具有抗癌、增强免疫力等作用,具有良好的生物活性,在食品、保健品以及医疗等领域应用广泛.近年来,随着对萜类化合物生物合成途径研究的深入,研究人员采用代谢工程手段构建了多种萜类产物的高产酿酒酵母工程菌株,部分已经达到或者接近工业化生产水平.因此,采用合成生物学相关技术手段合成...