Kutlu O. Ulgen

The stability of enzymes after sonication

Abstract The effects of operating conditions of sonication on the stability of some commercially purified enzyme preparations were investigated. Buffered solutions of six enzymes, alcohol dehydrogenase (ADH), malate dehydrogenase (MDH), glucose-6-phosphate dehydrogenase (G6PDH), l -lactic dehydrogenase (LDH), alkaline phosphatase (AP) and β-galactosidase (βG)were sonified over a range of power outputs up to 40 W. The enzymes had variable stabilities with complete stability for AP, and over 70% inactivation for G6PDH. Some inactivation models were tested for an understanding of the relation between sonification intensity and enzyme stability. Sonication processing times also affected the inactivation rate of ADH and MDH. The stability of sonified ADH was decreased with time when compared with unsonified controls. Increasing the viscosity of process fluid with glycerol gave 39% inactivation of ADH, while the control showed 15% inactivation for the operational conditions. The forces involved in the fluid must therefore have a significant role to play in the inactivation process.

Mathematical description of ethanol fermentation by immobilised Saccharomyces cerevisiae

Abstract Fermentation characteristics of Saccharomyces cerevisiae ATCC 9763 immobilised in Ca-alginate gel beads have been investigated in a stirred batch system at 2, 4, 8, 10% (w/v) initial glucose concentrations. The experimental results were tested using eleven different kinetic models relating biomass and ethanol production and glucose utilisation in different forms. The models proposed by Monod and Hinshelwood were found to be more appropriate for describing the batch growth and ethanol production of immobilised S. cerevisiae at low (2–4%) and high (8–10%) initial glucose concentrations, respectively. The validation of the models chosen was done using data obtained from experiments in an inclined reactor with nutrient recirculation.

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

BackgroundIt is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons.ModelThe constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle), lipid metabolism, reactive oxygen species (ROS) detoxification, amino acid metabolism (synthesis and catabolism), the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled.ResultsThe reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange) and 216 metabolites (183 internal, 33 external) distributed in and between astrocytes and neurons. Flux balance analysis (FBA) techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia) on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA). The results show the power of the constructed model to simulate disease behaviour on the flux level, and its potential to analyze cellular metabolic behaviour in silico.ConclusionThe predictive power of the constructed model for the key flux distributions, especially central carbon metabolism and glutamate-glutamine cycle fluxes, and its application to hypoxia is promising. The resultant acceptable predictions strengthen the power of such stoichiometric models in the analysis of mammalian cell metabolism.

PHISTO: pathogen–host interaction search tool

SUMMARY Knowledge of pathogen-host protein interactions is required to better understand infection mechanisms. The pathogen-host interaction search tool (PHISTO) is a web-accessible platform that provides relevant information about pathogen-host interactions (PHIs). It enables access to the most up-to-date PHI data for all pathogen types for which experimentally verified protein interactions with human are available. The platform also offers integrated tools for visualization of PHI networks, graph-theoretical analysis of targeted human proteins, BLAST search and text mining for detecting missing experimental methods. PHISTO will facilitate PHI studies that provide potential therapeutic targets for infectious diseases. AVAILABILITY http://www.phisto.org. CONTACT saliha.durmus@boun.edu.tr SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Improvement of ethanol production from starch by recombinant yeast through manipulation of environmental factors

The production of ethanol from starch has been investigated in a genetically modified Saccharomyces cerevisiae strain, YPB-G, which secretes a bifunctional fusion protein that contains both the Bacillus subtilis α-amylase and the Aspergillus awamori glucoamylase activities. The effects of a number of environmental factors on starch degradation, ethanol production, and plasmid stability have been assessed in batch culture. These include initial glucose supply, colony selection methodology prior to inoculation, and medium formulation. Cultures containing 40 g/l starch were observed to degrade starch effectively and produce higher amounts of ethanol in shorter periods. The provision of glucose in the growth medium during the early phases of fermentation resulted in faster growth and higher ethanol productivities. YE-Salts medium was found to support plasmid-containing cells throughout the whole fermentation; only 15% of the recombinant cells had lost the plasmid content by the end of the fermentation of 120 h. Fed-batch cultures produced high yields of ethanol on starch (0.46 g ethanol/g substrate) through the longer production period.

Infection Strategies of Bacterial and Viral Pathogens through Pathogen–Human Protein–Protein Interactions

Since ancient times, even in today’s modern world, infectious diseases cause lots of people to die. Infectious organisms, pathogens, cause diseases by physical interactions with human proteins. A thorough analysis of these interspecies interactions is required to provide insights about infection strategies of pathogens. Here we analyzed the most comprehensive available pathogen–human protein interaction data including 23,435 interactions, targeting 5,210 human proteins. The data were obtained from the newly developed pathogen–host interaction search tool, PHISTO. This is the first comprehensive attempt to get a comparison between bacterial and viral infections. We investigated human proteins that are targeted by bacteria and viruses to provide an overview of common and special infection strategies used by these pathogen types. We observed that in the human protein interaction network the proteins targeted by pathogens have higher connectivity and betweenness centrality values than those proteins not interacting with pathogens. The preference of interacting with hub and bottleneck proteins is found to be a common infection strategy of all types of pathogens to manipulate essential mechanisms in human. Compared to bacteria, viruses tend to interact with human proteins of much higher connectivity and centrality values in the human network. Gene Ontology enrichment analysis of the human proteins targeted by pathogens indicates crucial clues about the infection mechanisms of bacteria and viruses. As the main infection strategy, bacteria interact with human proteins that function in immune response to disrupt human defense mechanisms. Indispensable viral strategy, on the other hand, is the manipulation of human cellular processes in order to use that transcriptional machinery for their own genetic material transcription. A novel observation about pathogen–human systems is that the human proteins targeted by both pathogens are enriched in the regulation of metabolic processes.

Effect of carbon source perturbations on transcriptional regulation of metabolic fluxes in Saccharomyces cerevisiae

BackgroundControl effective flux (CEF) of a reaction is the weighted sum of all fluxes through that reaction, derived from elementary flux modes (EFM) of a metabolic network. Change in CEFs under different environmental conditions has earlier been proven to be correlated with the corresponding changes in the transcriptome. Here we use this to investigate the degree of transcriptional regulation of fluxes in the metabolism of Saccharomyces cerevisiae. We do this by quantifying correlations between changes in CEFs and changes in transcript levels for shifts in carbon source, i.e. between the fermentative carbon source glucose and nonfermentative carbon sources like ethanol, acetate, and lactate. The CEF analysis is based on a simple stoichiometric model that includes reactions of the central carbon metabolism and the amino acid metabolism.ResultsThe effect of the carbon shift on the metabolic fluxes was investigated for both batch and chemostat cultures. For growth on glucose in batch (respiro-fermentative) cultures, EFMs with no by-product formation were removed from the analysis of the CEFs, whereas those including any by-products (ethanol, glycerol, acetate, succinate) were omitted in the analysis of growth on glucose in chemostat (respiratory) cultures. This resulted in improved correlations between CEF changes and transcript levels. A regression correlation coefficient of 0.60 was obtained between CEF changes and gene expression changes in the central carbon metabolism for the analysis of 5 different perturbations. Out of 45 data points there were no more than 6 data points deviating from the correlation. Additionally, up- or down-regulation of at least 75% of the genes were in qualitative agreement with the CEF changes for all perturbations studied.ConclusionThe analysis indicates that changes in carbon source are associated with a high degree of hierarchical regulation of metabolic fluxes in the central carbon metabolism as the change in fluxes are correlating directly with the change in transcript levels of genes encoding their corresponding enzymes. For amino acid biosynthesis there was, however, not found to exist a similar correlation, and this may point to either post-transcriptional and/or metabolic regulation, or be due to the absence of a direct perturbation on the amino acid pathways in these experiments.

Integrative investigation of metabolic and transcriptomic data

BackgroundNew analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods.ResultsTranscriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures – PLS) using PLS toolbox in Matlab.ConclusionThe experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Molecular facets of sphingolipids: mediators of diseases.

Sphingolipids constitute a biologically active lipid class that is significantly important from both structural and regulatory aspects. The manipulation of sphingolipid metabolism is currently being studied as a novel strategy for cancer therapy. The basics of this therapeutic approach lie in the regulation property of sphingolipids on cellular processes, which are important in a cells fate, such as cell proliferation, apoptosis, cell cycle arrest, senescence, and inflammation. Furthermore, the mutations in the enzymes catalyzing some specific reactions in the sphingolipid metabolism cause mortal lysosomal storage diseases like Fabry, Gaucher, Niemann‐Pick, Farber, Krabbe, and Metachromatic Leukodystrophy. Therefore, the alteration of the sphingolipid metabolic pathway determines the choice between life and death. Understanding the sphingolipid metabolism and regulation is significant for the development of new therapeutic approaches for all sphingolipid‐related diseases, as well as for cancer. An important feature of the sphingolipid metabolic pathway is the compartmentalization into endoplasmic reticulum, the Golgi apparatus, lysosome and plasma membrane, and this compartmentalization makes the transport of sphingolipids critical for proper functioning. This paper focuses on the structures, metabolic pathways, localization, transport mechanisms, and diseases of sphingolipids in Saccharomyces cerevisiae and humans, and provides the latest comprehensive information on sphingolipid research.

Integration of Metabolic Modeling and Phenotypic Data in Evaluation and Improvement of Ethanol Production Using Respiration-Deficient Mutants of Saccharomyces cerevisiae

ABSTRACT Flux balance analysis and phenotypic data were used to provide clues to the relationships between the activities of gene products and the phenotypes resulting from the deletion of genes involved in respiratory function in Saccharomyces cerevisiae. The effect of partial or complete respiratory deficiency on the ethanol production and growth characteristics of hap4Δ/hap4Δ, mig1Δ/mig1Δ, qdr3Δ/qdr3Δ, pdr3Δ/pdr3Δ, qcr7Δ/qcr7Δ, cyt1Δ/cyt1Δ, and rip1Δ/rip1Δ mutants grown in microaerated chemostats was investigated. The study provided additional evidence for the importance of the selection of a physiologically relevant objective function, and it may improve quantitative predictions of exchange fluxes, as well as qualitative estimations of changes in intracellular fluxes. Ethanol production was successfully predicted by flux balance analysis in the case of the qdr3Δ/qdr3Δ mutant, with maximization of ethanol production as the objective function, suggesting an additional role for Qdr3p in respiration. The absence of similar changes in estimated intracellular fluxes in the qcr7Δ/qcr7Δ mutant compared to the rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants indicated that the effect of the deletion of this subunit of complex III was somehow compensated for. Analysis of predicted flux distributions indicated self-organization of intracellular fluxes to avoid NAD+/NADH imbalance in rip1Δ/rip1Δ and cyt1Δ/cyt1Δ mutants, but not the qcr7Δ/qcr7Δ mutant. The flux through the glycerol efflux channel, Fps1p, was estimated to be zero in all strains under the investigated conditions. This indicates that previous strategies for improving ethanol production, such as the overexpression of the glutamate synthase gene GLT1 in a GDH1 deletion background or deletion of the glycerol efflux channel gene FPS1 and overexpression of GLT1, are unnecessary in a respiration-deficient background.