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Sample records for cerevisiae genome-scale metabolic

  1. Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

    DEFF Research Database (Denmark)

    Olivares Hernandez, Roberto

    Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

  2. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.

    2003-01-01

    The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

  3. Genome-scale modeling enables metabolic engineering of Saccharomyces cerevisiae for succinic acid production.

    Science.gov (United States)

    Agren, Rasmus; Otero, José Manuel; Nielsen, Jens

    2013-07-01

    In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.

  4. Genome scale metabolic modeling of cancer

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Nielsen, Jens

    2017-01-01

    of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...

  5. Genome scale engineering techniques for metabolic engineering.

    Science.gov (United States)

    Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T

    2015-11-01

    Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  6. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

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    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  7. Genome-scale consequences of cofactor balancing in engineered pentose utilization pathways in Saccharomyces cerevisiae.

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    Amit Ghosh

    Full Text Available Biofuels derived from lignocellulosic biomass offer promising alternative renewable energy sources for transportation fuels. Significant effort has been made to engineer Saccharomyces cerevisiae to efficiently ferment pentose sugars such as D-xylose and L-arabinose into biofuels such as ethanol through heterologous expression of the fungal D-xylose and L-arabinose pathways. However, one of the major bottlenecks in these fungal pathways is that the cofactors are not balanced, which contributes to inefficient utilization of pentose sugars. We utilized a genome-scale model of S. cerevisiae to predict the maximal achievable growth rate for cofactor balanced and imbalanced D-xylose and L-arabinose utilization pathways. Dynamic flux balance analysis (DFBA was used to simulate batch fermentation of glucose, D-xylose, and L-arabinose. The dynamic models and experimental results are in good agreement for the wild type and for the engineered D-xylose utilization pathway. Cofactor balancing the engineered D-xylose and L-arabinose utilization pathways simulated an increase in ethanol batch production of 24.7% while simultaneously reducing the predicted substrate utilization time by 70%. Furthermore, the effects of cofactor balancing the engineered pentose utilization pathways were evaluated throughout the genome-scale metabolic network. This work not only provides new insights to the global network effects of cofactor balancing but also provides useful guidelines for engineering a recombinant yeast strain with cofactor balanced engineered pathways that efficiently co-utilizes pentose and hexose sugars for biofuels production. Experimental switching of cofactor usage in enzymes has been demonstrated, but is a time-consuming effort. Therefore, systems biology models that can predict the likely outcome of such strain engineering efforts are highly useful for motivating which efforts are likely to be worth the significant time investment.

  8. Genome-scale modeling for metabolic engineering.

    Science.gov (United States)

    Simeonidis, Evangelos; Price, Nathan D

    2015-03-01

    We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

  9. Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

    OpenAIRE

    Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

    2017-01-01

    Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

  10. Use of genome-scale microbial models for metabolic engineering

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

    2004-01-01

    Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

  11. Next-generation genome-scale models for metabolic engineering

    DEFF Research Database (Denmark)

    King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

  12. Analysis of Aspergillus nidulans metabolism at the genome-scale

    DEFF Research Database (Denmark)

    David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald

    2008-01-01

    of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated...... a function. Results: In this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways......, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene...

  13. Environmental versatility promotes modularity in genome-scale metabolic networks.

    Science.gov (United States)

    Samal, Areejit; Wagner, Andreas; Martin, Olivier C

    2011-08-24

    The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple

  14. Environmental versatility promotes modularity in genome-scale metabolic networks

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    Wagner Andreas

    2011-08-01

    Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional

  15. Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

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    Bharat Manna

    2017-10-01

    Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

  16. Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

    Science.gov (United States)

    Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

    2013-05-01

    Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Enhancing sesquiterpene production in Saccharomyces cerevisiae through in silico driven metabolic engineering

    DEFF Research Database (Denmark)

    Asadollahi, Mohammadali; Maury, Jerome; Patil, Kiran Raosaheb

    2009-01-01

    A genome-scale metabolic model was used to identify new target genes for enhanced biosynthesis of sesquiterpenes in the yeast Saccharomyces cerevisiae. The effect of gene deletions on the flux distributions in the metabolic model of S. cerevisiae was assessed using OptGene as the modeling framework...

  18. Metabolite coupling in genome-scale metabolic networks

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    Palsson Bernhard Ø

    2006-03-01

    metabolites. Conclusion The coupling of metabolites is an important topological property of metabolic networks. By computing coupling quantitatively for the first time in genome-scale metabolic networks, we provide insight into the basic structure of these networks.

  19. Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

    Science.gov (United States)

    Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

    2017-11-01

    The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

  20. In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

    NARCIS (Netherlands)

    Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

    2005-01-01

    A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all

  1. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes

  2. Genome-scale metabolic models as platforms for strain design and biological discovery.

    Science.gov (United States)

    Mienda, Bashir Sajo

    2017-07-01

    Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

  3. In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

    DEFF Research Database (Denmark)

    Geng, Jun; Nielsen, Jens

    2017-01-01

    The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

  4. Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism

    Science.gov (United States)

    Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.

    2011-01-01

    The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001

  5. Genome-scale metabolic representation of Amycolatopsis balhimycina

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Figueiredo, L. F.; Förster, Jochen

    2012-01-01

    Infection caused by methicillin‐resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin...... to reconstruct a genome‐scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC‐genome (∼69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR...

  6. A protocol for generating a high-quality genome-scale metabolic reconstruction.

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    Thiele, Ines; Palsson, Bernhard Ø

    2010-01-01

    Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

  7. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

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    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  8. Metingear: a development environment for annotating genome-scale metabolic models.

    Science.gov (United States)

    May, John W; James, A Gordon; Steinbeck, Christoph

    2013-09-01

    Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

  9. Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

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    Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2017-02-01

    Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

  10. Reconstruction of genome-scale human metabolic models using omics data

    DEFF Research Database (Denmark)

    Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

    2015-01-01

    used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

  11. Integration of expression data in genome-scale metabolic network reconstructions

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    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  12. Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

    2015-01-01

    Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

  13. Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

    Science.gov (United States)

    2016-03-15

    RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

  14. Enumeration of smallest intervention strategies in genome-scale metabolic networks.

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    Axel von Kamp

    2014-01-01

    Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

  15. Predicting growth of the healthy infant using a genome scale metabolic model.

    Science.gov (United States)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

  16. Probing the genome-scale metabolic landscape of Bordetella pertussis, the causative agent of whooping cough.

    Science.gov (United States)

    Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe

    2017-08-25

    Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussi s. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content. IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis , and challenged its predictions

  17. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  18. Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

    2016-06-01

    We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  20. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  1. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  2. Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

    Energy Technology Data Exchange (ETDEWEB)

    Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

    2015-03-10

    There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

  3. Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

    Directory of Open Access Journals (Sweden)

    Balagurunathan Balaji

    2012-02-01

    Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale

  4. Toward the automated generation of genome-scale metabolic networks in the SEED.

    Science.gov (United States)

    DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

    2007-04-26

    Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

  5. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  6. Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

    Science.gov (United States)

    McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

    2012-05-14

    Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

  7. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins.

    Science.gov (United States)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens

    2016-05-01

    Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.

  8. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  9. Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

    Science.gov (United States)

    Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

    2016-05-01

    We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  10. Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

    Directory of Open Access Journals (Sweden)

    Katsunori Yoshikawa

    Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

  11. Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

    2008-01-01

    Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

  12. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  13. Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

    Directory of Open Access Journals (Sweden)

    María P. Cortés

    2017-12-01

    Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

  14. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Science.gov (United States)

    De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

    2014-01-01

    The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  15. Identifying all moiety conservation laws in genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

  16. Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Benjamin eMerlet

    2016-02-01

    Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  17. Novel insights into obesity and diabetes through genome-scale metabolic modeling

    Directory of Open Access Journals (Sweden)

    Leif eVäremo

    2013-04-01

    Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

  18. A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

    Science.gov (United States)

    Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

    2016-01-01

    This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

  19. Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

    Science.gov (United States)

    Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

    2013-01-01

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

  20. Quantitative assessment of thermodynamic constraints on the solution space of genome-scale metabolic models.

    Science.gov (United States)

    Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L

    2013-07-16

    Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  1. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    web server allowing constraint based simulations of the genome scale metabolic reaction networks of E. coli, S. cerevisiae and M. tuberculosis. Conclusions Acorn is a free software package, which can be installed by research groups to create a web based environment for computer simulations of genome scale metabolic reaction networks. It facilitates shared access to models and creation of publicly available constraint based modelling resources.

  2. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

  3. Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

    DEFF Research Database (Denmark)

    Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

    2017-01-01

    orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...

  4. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    KAUST Repository

    Hefzi, Hooman

    2016-11-23

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

  5. Genome-scale metabolic models applied to human health and disease.

    Science.gov (United States)

    Cook, Daniel J; Nielsen, Jens

    2017-11-01

    Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

  6. Improving the phenotype predictions of a yeast genome-scale metabolic model by incorporating enzymatic constraints

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant

    2017-01-01

    , which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...

  7. 13C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

    DEFF Research Database (Denmark)

    Ghosh, Amit; Ando, David; Gin, Jennifer

    2016-01-01

    Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13C labeling data with comprehensive genome-scale models...

  8. Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

    Science.gov (United States)

    Henson, Michael A

    2015-12-01

    Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

  9. Reframed Genome-Scale Metabolic Model to Facilitate Genetic Design and Integration with Expression Data.

    Science.gov (United States)

    Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang

    2017-01-01

    Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.

  10. Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

    Directory of Open Access Journals (Sweden)

    Brooks J Paul

    2010-03-01

    Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

  11. Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

    Directory of Open Access Journals (Sweden)

    Jorge Fernandez-de-Cossio-Diaz

    2017-11-01

    Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

  12. Fumaric acid production in Saccharomyces cerevisiae by in silico aided metabolic engineering.

    Directory of Open Access Journals (Sweden)

    Guoqiang Xu

    Full Text Available Fumaric acid (FA is a promising biomass-derived building-block chemical. Bio-based FA production from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. Here we report on FA production by direct fermentation using metabolically engineered Saccharomyces cerevisiae with the aid of in silico analysis of a genome-scale metabolic model. First, FUM1 was selected as the target gene on the basis of extensive literature mining. Flux balance analysis (FBA revealed that FUM1 deletion can lead to FA production and slightly lower growth of S. cerevisiae. The engineered S. cerevisiae strain obtained by deleting FUM1 can produce FA up to a concentration of 610±31 mg L(-1 without any apparent change in growth in fed-batch culture. FT-IR and (1H and (13C NMR spectra confirmed that FA was synthesized by the engineered S. cerevisiae strain. FBA identified pyruvate carboxylase as one of the factors limiting higher FA production. When the RoPYC gene was introduced, S. cerevisiae produced 1134±48 mg L(-1 FA. Furthermore, the final engineered S. cerevisiae strain was able to produce 1675±52 mg L(-1 FA in batch culture when the SFC1 gene encoding a succinate-fumarate transporter was introduced. These results demonstrate that the model shows great predictive capability for metabolic engineering. Moreover, FA production in S. cerevisiae can be efficiently developed with the aid of in silico metabolic engineering.

  13. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model

    NARCIS (Netherlands)

    Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.

    2006-01-01

    A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for

  14. Revisiting the chlorophyll biosynthesis pathway using genome scale metabolic model of Oryza sativa japonica

    Science.gov (United States)

    Chatterjee, Ankita; Kundu, Sudip

    2015-01-01

    Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104

  15. Determining the control circuitry of redox metabolism at the genome-scale.

    Directory of Open Access Journals (Sweden)

    Stephen Federowicz

    2014-04-01

    Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.

  16. Investigating genotype-phenotype relationships in Saccharomyces cerevisiae metabolic network through stoichiometric modeling

    DEFF Research Database (Denmark)

    Brochado, Ana Rita

    processes. Metabolism is an extensively studied and characterised subcellular system, for which several modeling approaches have been proposed over the last 20 years. Nowadays, stoichiometric modeling of metabolism is done at the genome scale and it has diverse applications, many of them for helping....... This chapter aims at providing the reader with relevant state-of-the-art information concerning Systems Biology, Genome-Scale Metabolic Modeling and Metabolic Engineering. Particular attention is given to the yeast Saccharomyces cerevisiae, the eukaryotic model organism used thought the thesis.......A holistic view of the cell is fundamental for gaining insights into genotype to phenotype relationships. Systems Biology is a discipline within Biology, which uses such holistic approach by focusing on the development and application of tools for studying the structure and dynamics of cellular...

  17. Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

    Directory of Open Access Journals (Sweden)

    Tyler W. H. Backman

    2018-01-01

    Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

  18. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  19. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2014-09-01

    Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

  20. Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

    Science.gov (United States)

    Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

    2016-01-01

    The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

  1. Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model

    International Nuclear Information System (INIS)

    Dash, Satyakam; Mueller, Thomas J.; Venkataramanan, Keerthi P.; Papoutsakis, Eleftherios T.; Maranas, Costas D.

    2014-01-01

    Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation

  2. Fatty acid metabolism in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    van Roermund, C. W. T.; Waterham, H. R.; IJlst, L.; Wanders, R. J. A.

    2003-01-01

    Peroxisomes are essential subcellular organelles involved in a variety of metabolic processes. Their importance is underlined by the identification of a large group of inherited diseases in humans in which one or more of the peroxisomal functions are impaired. The yeast Saccharomyces cerevisiae has

  3. Saccharomyces cerevisiae metabolism in ecological context

    OpenAIRE

    Jouhten, Paula; Ponomarova, Olga; González García, Ramón; Patil, Kiran R.

    2016-01-01

    The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype?metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype?phenotype relations may originate in the evolutionarily shaped cellular operating principles ...

  4. The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum

    Science.gov (United States)

    Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens

    2013-01-01

    We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215

  5. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets.

    Science.gov (United States)

    Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

    2016-08-20

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

    Science.gov (United States)

    Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

    2018-01-01

    Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

  7. IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

    Science.gov (United States)

    Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

    2017-04-07

    Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

  8. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-03-27

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

  9. Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

    Science.gov (United States)

    Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk

    2017-03-01

    Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  10. Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III-reducer Rhodoferax ferrireducens

    Directory of Open Access Journals (Sweden)

    Daugherty Sean

    2009-09-01

    Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

  11. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    DEFF Research Database (Denmark)

    Hefzi, Hooman; Ang, Kok Siong; Hanscho, Michael

    2016-01-01

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways...

  12. Stoichiometric network constraints on xylose metabolism by recombinant Saccharomyces cerevisiae

    Science.gov (United States)

    Yong-Su Jin; Thomas W. Jeffries

    2004-01-01

    Metabolic pathway engineering is constrained by the thermodynamic and stoichiometric feasibility of enzymatic activities of introduced genes. Engineering of xylose metabolism in Saccharomyces cerevisiae has focused on introducing genes for the initial xylose assimilation steps from Pichia stipitis, a xylose-fermenting yeast, into S. cerevisiae, a yeast raditionally...

  13. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    Science.gov (United States)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  14. MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

    Science.gov (United States)

    Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

    2017-08-15

    Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  15. Determining the Control Circuitry of Redox Metabolism at the Genome-Scale

    DEFF Research Database (Denmark)

    Federowicz, Stephen; Kim, Donghyuk; Ebrahim, Ali

    2014-01-01

    -scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes...

  16. A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

    KAUST Repository

    Hefzi, Hooman; Ang, Kok  Siong; Hanscho, Michael; Bordbar, Aarash; Ruckerbauer, David; Lakshmanan, Meiyappan; Orellana, Camila  A.; Baycin-Hizal, Deniz; Huang, Yingxiang; Ley, Daniel; Martinez, Veronica  S.; Kyriakopoulos, Sarantos; Jimé nez, Natalia  E.; Zielinski, Daniel  C.; Quek, Lake-Ee; Wulff, Tune; Arnsdorf, Johnny; Li, Shangzhong; Lee, Jae  Seong; Paglia, Giuseppe; Loira, Nicolas; Spahn, Philipp  N.; Pedersen, Lasse  E.; Gutierrez, Jahir  M.; King, Zachary  A.; Lund, Anne  Mathilde; Nagarajan, Harish; Thomas, Alex; Abdel-Haleem, Alyaa M.; Zanghellini, Juergen; Kildegaard, Helene  F.; Voldborg, Bjø rn  G.; Gerdtzen, Ziomara  P.; Betenbaugh, Michael  J.; Palsson, Bernhard  O.; Andersen, Mikael  R.; Nielsen, Lars  K.; Borth, Nicole; Lee, Dong-Yup; Lewis, Nathan  E.

    2016-01-01

    Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess

  17. In silico method for modelling metabolism and gene product expression at genome scale

    Energy Technology Data Exchange (ETDEWEB)

    Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.

    2012-07-03

    Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.

  18. Using a genome-scale metabolic network model to elucidate the mechanism of chloroquine action in Plasmodium falciparum

    Directory of Open Access Journals (Sweden)

    Shivendra G. Tewari

    2017-08-01

    Full Text Available Chloroquine, long the default first-line treatment against malaria, is now abandoned in large parts of the world because of widespread drug-resistance in Plasmodium falciparum. In spite of its importance as a cost-effective and efficient drug, a coherent understanding of the cellular mechanisms affected by chloroquine and how they influence the fitness and survival of the parasite remains elusive. Here, we used a systems biology approach to integrate genome-scale transcriptomics to map out the effects of chloroquine, identify targeted metabolic pathways, and translate these findings into mechanistic insights. Specifically, we first developed a method that integrates transcriptomic and metabolomic data, which we independently validated against a recently published set of such data for Krebs-cycle mutants of P. falciparum. We then used the method to calculate the effect of chloroquine treatment on the metabolic flux profiles of P. falciparum during the intraerythrocytic developmental cycle. The model predicted dose-dependent inhibition of DNA replication, in agreement with earlier experimental results for both drug-sensitive and drug-resistant P. falciparum strains. Our simulations also corroborated experimental findings that suggest differences in chloroquine sensitivity between ring- and schizont-stage P. falciparum. Our analysis also suggests that metabolic fluxes that govern reduced thioredoxin and phosphoenolpyruvate synthesis are significantly decreased and are pivotal to chloroquine-based inhibition of P. falciparum DNA replication. The consequences of impaired phosphoenolpyruvate synthesis and redox metabolism are reduced carbon fixation and increased oxidative stress, respectively, both of which eventually facilitate killing of the parasite. Our analysis suggests that a combination of chloroquine (or an analogue and another drug, which inhibits carbon fixation and/or increases oxidative stress, should increase the clearance of P

  19. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

    Science.gov (United States)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-08-01

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

  20. Presentation : Development of an age-specific genome-scale model of skeletal muscle metabolism

    NARCIS (Netherlands)

    Cabbia, A.; van Riel, N.A.W.

    2017-01-01

    Skeletal myocytes are among the most metabolically active cell types, implicated in nutrient balance, contributing to the insulin-stimulated clearance of glucose from the blood, and secreting myokines that contribute in regulating inflammation and the ageing process. The loss of muscle mass and

  1. Predicting growth of the healthy infant using a genome scale metabolic model

    DEFF Research Database (Denmark)

    Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

    2017-01-01

    to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body...

  2. Flux balance analysis of genome-scale metabolic model of rice ...

    Indian Academy of Sciences (India)

    2015-09-28

    Sep 28, 2015 ... biologists are also trying to understand the plant's systems level biochemistry ... metabolism to observe the effect of intracellular transporters' transport ..... [The information about this pathway and associated genes in .... 2013 A method for accounting for mainte- ... Biological control of rice diseases pp 1–11.

  3. Genome-scale model of Streptococcus thermophilus LMG18311 for metabolic comparison.

    NARCIS (Netherlands)

    Pastink, M.I.; Teusink, B.; Hols, P.; Visser, S.; Vos, W.M.; Hugenholtz, J.

    2009-01-01

    In this report, we describe the amino acid metabolism and amino acid dependency of the dairy bacterium Streptococcus thermophilus LMG18311 and compare them with those of two other characterized lactic acid bacteria, Lactococcus lactis and Lactobacillus plantarum. Through the construction of a

  4. Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052

    Directory of Open Access Journals (Sweden)

    Kim Pan-Jun

    2011-08-01

    Full Text Available Abstract Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis. Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925 for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test

  5. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  6. Systematic construction of kinetic models from genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Natalie J Stanford

    Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

  7. Systematic Construction of Kinetic Models from Genome-Scale Metabolic Networks

    Science.gov (United States)

    Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram

    2013-01-01

    The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments. PMID:24324546

  8. Data-driven integration of genome-scale regulatory and metabolic network models

    Science.gov (United States)

    Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

    2015-01-01

    Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

  9. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  10. Understanding the Representative Gut Microbiota Dysbiosis in Metformin-Treated Type 2 Diabetes Patients Using Genome-Scale Metabolic Modeling

    Directory of Open Access Journals (Sweden)

    Dorines Rosario

    2018-06-01

    Full Text Available Dysbiosis in the gut microbiome composition may be promoted by therapeutic drugs such as metformin, the world’s most prescribed antidiabetic drug. Under metformin treatment, disturbances of the intestinal microbes lead to increased abundance of Escherichia spp., Akkermansia muciniphila, Subdoligranulum variabile and decreased abundance of Intestinibacter bartlettii. This alteration may potentially lead to adverse effects on the host metabolism, with the depletion of butyrate producer genus. However, an increased production of butyrate and propionate was verified in metformin-treated Type 2 diabetes (T2D patients. The mechanisms underlying these nutritional alterations and their relation with gut microbiota dysbiosis remain unclear. Here, we used Genome-scale Metabolic Models of the representative gut bacteria Escherichia spp., I. bartlettii, A. muciniphila, and S. variabile to elucidate their bacterial metabolism and its effect on intestinal nutrient pool, including macronutrients (e.g., amino acids and short chain fatty acids, minerals and chemical elements (e.g., iron and oxygen. We applied flux balance analysis (FBA coupled with synthetic lethality analysis interactions to identify combinations of reactions and extracellular nutrients whose absence prevents growth. Our analyses suggest that Escherichia sp. is the bacteria least vulnerable to nutrient availability. We have also examined bacterial contribution to extracellular nutrients including short chain fatty acids, amino acids, and gasses. For instance, Escherichia sp. and S. variabile may contribute to the production of important short chain fatty acids (e.g., acetate and butyrate, respectively involved in the host physiology under aerobic and anaerobic conditions. We have also identified pathway susceptibility to nutrient availability and reaction changes among the four bacteria using both FBA and flux variability analysis. For instance, lipopolysaccharide synthesis, nucleotide sugar

  11. Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth

    Science.gov (United States)

    2012-01-01

    Background Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. Results Here we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype). Conclusion This study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data. PMID:22631437

  12. 13C Metabolic Flux Analysis for systematic metabolic engineering of S. cerevisiae for overproduction of fatty acids.

    Directory of Open Access Journals (Sweden)

    Amit Ghosh

    2016-10-01

    Full Text Available Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here we used flux-based modeling approaches to improve yields of fatty acids in S. cerevisiae. We combined 13C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Y. lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for down-regulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg L of free fatty acids. With the addition of ATP citrate lyase and down-regulation of malate synthase the engineered strain produced 26 per cent more free fatty acids. Further increases in free fatty acid production of 33 per cent were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by 70 per cent.

  13. Constraining genome-scale models to represent the bow tie structure of metabolism for 13C metabolic flux analysis

    DEFF Research Database (Denmark)

    Backman, Tyler W.H.; Ando, David; Singh, Jahnavi

    2018-01-01

    for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S- 13C MFA, as well as provide for a substantially lower set of flux bounds......Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used...

  14. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism

    NARCIS (Netherlands)

    Yuan, H.; Cheung, C.Y. Maurice; Poolman, M.G.; Hilbers, P.A.J.; van Riel, N.A.W.

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the

  15. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

    2016-09-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

  16. Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

    Science.gov (United States)

    Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

    2016-01-01

    The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

  17. Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

    Science.gov (United States)

    Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

    2018-01-01

    Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

  18. Genome scale models of yeast: towards standardized evaluation and consistent omic integration

    DEFF Research Database (Denmark)

    Sanchez, Benjamin J.; Nielsen, Jens

    2015-01-01

    Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

  19. Evaluation of a Genome-Scale In Silico Metabolic Model for Geobacter metallireducens by Using Proteomic Data from a Field Biostimulation Experiment

    Science.gov (United States)

    Fang, Yilin; Yabusaki, Steven B.; Lipton, Mary S.; Long, Philip E.

    2012-01-01

    Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment. PMID:23042184

  20. Horizontal and vertical growth of S. cerevisiae metabolic network.

    KAUST Repository

    Grassi, Luigi

    2011-10-14

    BACKGROUND: The growth and development of a biological organism is reflected by its metabolic network, the evolution of which relies on the essential gene duplication mechanism. There are two current views about the evolution of metabolic networks. The retrograde model hypothesizes that a pathway evolves by recruiting novel enzymes in a direction opposite to the metabolic flow. The patchwork model is instead based on the assumption that the evolution is based on the exploitation of broad-specificity enzymes capable of catalysing a variety of metabolic reactions. RESULTS: We analysed a well-studied unicellular eukaryotic organism, S. cerevisiae, and studied the effect of the removal of paralogous gene products on its metabolic network. Our results, obtained using different paralog and network definitions, show that, after an initial period when gene duplication was indeed instrumental in expanding the metabolic space, the latter reached an equilibrium and subsequent gene duplications were used as a source of more specialized enzymes rather than as a source of novel reactions. We also show that the switch between the two evolutionary strategies in S. cerevisiae can be dated to about 350 million years ago. CONCLUSIONS: Our data, obtained through a novel analysis methodology, strongly supports the hypothesis that the patchwork model better explains the more recent evolution of the S. cerevisiae metabolic network. Interestingly, the effects of a patchwork strategy acting before the Euascomycete-Hemiascomycete divergence are still detectable today.

  1. Engineering of aromatic amino acid metabolism in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Vuralhan, Z.

    2006-01-01

    Saccharomyces cerevisiae is a popular industrial microorganism. It has since long been used in bread, beer and wine making. More recently it is also being applied for heterologous protein production and as a target organism for metabolic engineering. The work presented in this thesis describes how

  2. Dynamics of Storage Carbohydrates Metabolism in Saccharomyces cerevisiae

    OpenAIRE

    Suarez-Mendez, C.A.

    2015-01-01

    Production of chemicals via biotechnological routes are becoming rapidly an alternative to oil-based processes. Several microorganisms including yeast, bacteria, fungi and algae can transform feedstocks into high-value molecules at industrial scale. Improvement of the bioprocess performance is a key factor for making this technology economically feasible. Despite the vast knowledge on microbial metabolism, some gaps still remain open. In Saccharomyces cerevisiae, metabolism of storage carbohy...

  3. Metabolic alterations during ascosporogenesis of Saccharomyces cerevisiae

    International Nuclear Information System (INIS)

    Carvalho, Sandra; Nadkarni, G.B.

    1977-01-01

    Sporulation of S. cerevisiae has been shown to alter the profiles of enzymes involved in gluconeogenesis and glycolysis. The enhancement in the levels of total cellular carbohydrates could be correlated with the enhancement in fructose 1,6-diphosphatase and trehalose-phosphate synthetase. The latter activity could account for the 15-fold increase in trehalose levels in sporulating cells. Glucose-6-phosphatase, pyruvate kinase and phosphofructokinase showed continuous decline during ascosporogenesis. The relative incorporation of radioactivity from possible precursors of gluconeogenesis indicated that acetate-2- 14 C alone could contribute to carbohydrate synthesis. (author)

  4. Metabolic engineering of Saccharomyces cerevisiae for overproduction of triacylglycerols

    DEFF Research Database (Denmark)

    Ferreira, Raphael; Teixeira, Paulo Goncalves; Gossing, Michael

    2018-01-01

    Triacylglycerols (TAGs) are valuable versatile compounds that can be used as metabolites for nutrition and health, as well as feedstocks for biofuel production. Although Saccharomyces cerevisiae is the favored microbial cell factory for industrial production of biochemicals, it does not produce...... large amounts of lipids and TAGs comprise only ~1% of its cell dry weight. Here, we engineered S. cerevisiae to reorient its metabolism for overproduction of TAGs, by regulating lipid droplet associated-proteins involved in TAG synthesis and hydrolysis. We implemented a push-and-pull strategy...... PXA1 led to accumulation of  254 mg∙gCDW−1. The TAG levels achieved here are the highest titer reported in S. cerevisiae, reaching 27.4% of the maximum theoretical yield in minimal medium with 2% glucose. This work shows the potential of using an industrially established and robust yeast species...

  5. Metabolic impact of redox cofactor perturbations in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hou, Jin; Lages, Nuno; Oldiges, M.

    2009-01-01

    to induce widespread changes in metabolism. We present a detailed analysis of the impact of perturbations in redox cofactors in the cytosol or mitochondria on glucose and energy metabolism in Saccharomyces cerevisiae to aid metabolic engineering decisions that involve cofactor engineering. We enhanced NADH...... oxidation by introducing NADH oxidase or alternative oxidase, its ATP-mediated conversion to NADPH using NADH kinase as well as the interconversion of NADH and NADPH independent of ATP by the soluble, non-proton-translocating bacterial transhydrogenase. Decreasing cytosolic NADH level lowered glycerol...

  6. Reconstruction of Oryza sativa indica Genome Scale Metabolic Model and Its Responses to Varying RuBisCO Activity, Light Intensity, and Enzymatic Cost Conditions

    Directory of Open Access Journals (Sweden)

    Ankita Chatterjee

    2017-11-01

    Full Text Available To combat decrease in rice productivity under different stresses, an understanding of rice metabolism is needed. Though there are different genome scale metabolic models (GSMs of Oryza sativa japonica, no GSM with gene-protein-reaction association exist for Oryza sativa indica. Here, we report a GSM, OSI1136 of O.s. indica, which includes 3602 genes and 1136 metabolic reactions and transporters distributed across the cytosol, mitochondrion, peroxisome, and chloroplast compartments. Flux balance analysis of the model showed that for varying RuBisCO activity (Vc/Vo (i the activity of the chloroplastic malate valve increases to transport reducing equivalents out of the chloroplast under increased photorespiratory conditions and (ii glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase can act as source of cytosolic ATP under decreased photorespiration. Under increasing light conditions we observed metabolic flexibility, involving photorespiration, chloroplastic triose phosphate and the dicarboxylate transporters of the chloroplast and mitochondrion for redox and ATP exchanges across the intracellular compartments. Simulations under different enzymatic cost conditions revealed (i participation of peroxisomal glutathione-ascorbate cycle in photorespiratory H2O2 metabolism (ii different modes of the chloroplastic triose phosphate transporters and malate valve, and (iii two possible modes of chloroplastic Glu–Gln transporter which were related with the activity of chloroplastic and cytosolic isoforms of glutamine synthetase. Altogether, our results provide new insights into plant metabolism.

  7. In vivo dynamics of galactose metabolism in Saccharomyces cerevisiae: Metabolic fluxes and metabolite levels

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Nielsen, Jens

    2001-01-01

    The dynamics of galactose metabolism in Saccharomyces cerevisiae was studied by analyzing the metabolic response of the CEN.PK 113-7D wild-type strain when exposed to a galactose pulse during aerobic growth in a galactose-limited steady-state cultivation at a dilution rate of 0.097 h(-1). A fast...

  8. Increasing NADH oxidation reduces overflow metabolism in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Vemuri, Goutham; Eiteman, M.A; McEwen, J.E

    2007-01-01

    effect is due to limited respiratory capacity or is caused by glucose-mediated repression of respiration. When respiration in S. cerevisiae was increased by introducing a heterologous alternative oxidase, we observed reduced aerobic ethanol formation. In contrast, increasing nonrespiratory NADH oxidation...... Crabtree effect.’’ The yeast Saccharomyces cerevisiae has served as an important model organism for studying the Crabtree effect. When subjected to increasing glycolytic fluxes under aerobic conditions, there is a threshold value of the glucose uptake rate at which the metabolism shifts from purely...... respiratory to mixed respiratory and fermentative. It is well known that glucose repression of respiratory pathways occurs at high glycolytic fluxes, resulting in a decrease in respiratory capacity. Despite many years of detailed studies on this subject, it is not known whether the onset of the Crabtree...

  9. Reconstruction and in silico analysis of an Actinoplanes sp. SE50/110 genome-scale metabolic model for acarbose production

    Directory of Open Access Journals (Sweden)

    Yali eWang

    2015-06-01

    Full Text Available Actinoplanes sp. SE50/110 produces the -glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites and 1219 reactions. 122 and 81 genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78% and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110.

  10. Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

    Directory of Open Access Journals (Sweden)

    Heavner Benjamin D

    2012-06-01

    Full Text Available Abstract Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Additional file 1 Function testYeastModel.m.m. Click here for file Additional file 2 Function model

  11. Genome-scale metabolic reconstructions and theoretical investigation of methane conversion in Methylomicrobium buryatense strain 5G(B1).

    Science.gov (United States)

    de la Torre, Andrea; Metivier, Aisha; Chu, Frances; Laurens, Lieve M L; Beck, David A C; Pienkos, Philip T; Lidstrom, Mary E; Kalyuzhnaya, Marina G

    2015-11-25

    Methane-utilizing bacteria (methanotrophs) are capable of growth on methane and are attractive systems for bio-catalysis. However, the application of natural methanotrophic strains to large-scale production of value-added chemicals/biofuels requires a number of physiological and genetic alterations. An accurate metabolic model coupled with flux balance analysis can provide a solid interpretative framework for experimental data analyses and integration. A stoichiometric flux balance model of Methylomicrobium buryatense strain 5G(B1) was constructed and used for evaluating metabolic engineering strategies for biofuels and chemical production with a methanotrophic bacterium as the catalytic platform. The initial metabolic reconstruction was based on whole-genome predictions. Each metabolic step was manually verified, gapfilled, and modified in accordance with genome-wide expression data. The final model incorporates a total of 841 reactions (in 167 metabolic pathways). Of these, up to 400 reactions were recruited to produce 118 intracellular metabolites. The flux balance simulations suggest that only the transfer of electrons from methanol oxidation to methane oxidation steps can support measured growth and methane/oxygen consumption parameters, while the scenario employing NADH as a possible source of electrons for particulate methane monooxygenase cannot. Direct coupling between methane oxidation and methanol oxidation accounts for most of the membrane-associated methane monooxygenase activity. However the best fit to experimental results is achieved only after assuming that the efficiency of direct coupling depends on growth conditions and additional NADH input (about 0.1-0.2 mol of incremental NADH per one mol of methane oxidized). The additional input is proposed to cover loss of electrons through inefficiency and to sustain methane oxidation at perturbations or support uphill electron transfer. Finally, the model was used for testing the carbon conversion

  12. Using a Genome-Scale Metabolic Network Model to Elucidate the Mechanism of Chloroquine Action in Plasmodium falciparum

    Science.gov (United States)

    2017-03-22

    The transcriptome data of P. falciparum obtained under different stress conditions (e.g., drug exposure, genetic mutation , etc.) contain information...Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p. Proc. Natl. Acad

  13. Genome-scale metabolic modeling to provide insight into the production of storage compounds during feast-famine cycles of activated sludge.

    Science.gov (United States)

    Tajparast, Mohammad; Frigon, Dominic

    2013-01-01

    Studying storage metabolism during feast-famine cycles of activated sludge treatment systems provides profound insight in terms of both operational issues (e.g., foaming and bulking) and process optimization for the production of value added by-products (e.g., bioplastics). We examined the storage metabolism (including poly-β-hydroxybutyrate [PHB], glycogen, and triacylglycerols [TAGs]) during feast-famine cycles using two genome-scale metabolic models: Rhodococcus jostii RHA1 (iMT1174) and Escherichia coli K-12 (iAF1260) for growth on glucose, acetate, and succinate. The goal was to develop the proper objective function (OF) for the prediction of the main storage compound produced in activated sludge for given feast-famine cycle conditions. For the flux balance analysis, combinations of three OFs were tested. For all of them, the main OF was to maximize growth rates. Two additional sub-OFs were used: (1) minimization of biochemical fluxes, and (2) minimization of metabolic adjustments (MoMA) between the feast and famine periods. All (sub-)OFs predicted identical substrate-storage associations for the feast-famine growth of the above-mentioned metabolic models on a given substrate when glucose and acetate were set as sole carbon sources (i.e., glucose-glycogen and acetate-PHB), in agreement with experimental observations. However, in the case of succinate as substrate, the predictions depended on the network structure of the metabolic models such that the E. coli model predicted glycogen accumulation and the R. jostii model predicted PHB accumulation. While the accumulation of both PHB and glycogen was observed experimentally, PHB showed higher dynamics during an activated sludge feast-famine growth cycle with succinate as substrate. These results suggest that new modeling insights between metabolic predictions and population ecology will be necessary to properly predict metabolisms likely to emerge within the niches of activated sludge communities. Nonetheless

  14. Compositions and methods for modeling Saccharomyces cerevisiae metabolism

    DEFF Research Database (Denmark)

    2012-01-01

    The invention provides an in silica model for determining a S. cerevisiae physiological function. The model includes a data structure relating a plurality of S. cerevisiae reactants to a plurality of S. cerevisiae reactions, a constraint set for the plurality of S. cerevisiae reactions, and comma...

  15. Influence of organic acids and organochlorinated insecticides on metabolism of Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Pejin Dušanka J.

    2005-01-01

    Full Text Available Saccharomyces cerevisiae is exposed to different stress factors during the production: osmotic, temperature, oxidative. The response to these stresses is the adaptive mechanism of cells. The raw materials Saccharomyces cerevisiae is produced from, contain metabolism products of present microorganisms and protective agents used during the growth of sugar beet for example the influence of acetic and butyric acid and organochlorinated insecticides, lindan and heptachlor, on the metabolism of Saccharomyces cerevisiae was investigated and presented in this work. The mentioned compounds affect negatively the specific growth rate, yield, content of proteins, phosphorus, total ribonucleic acids. These compounds influence the increase of trechalose and glycogen content in the Saccharomyces cerevisiae cells.

  16. Analysis of metabolic networks of Streptomyces leeuwenhoekii C34 by means of a genome scale model: Prediction of modifications that enhance the production of specialized metabolites.

    Science.gov (United States)

    Razmilic, Valeria; Castro, Jean F; Andrews, Barbara; Asenjo, Juan A

    2018-07-01

    The first genome scale model (GSM) for Streptomyces leeuwenhoekii C34 was developed to study the biosynthesis pathways of specialized metabolites and to find metabolic engineering targets for enhancing their production. The model, iVR1007, consists of 1,722 reactions, 1,463 metabolites, and 1,007 genes, it includes the biosynthesis pathways of chaxamycins, chaxalactins, desferrioxamines, ectoine, and other specialized metabolites. iVR1007 was validated using experimental information of growth on 166 different sources of carbon, nitrogen and phosphorous, showing an 83.7% accuracy. The model was used to predict metabolic engineering targets for enhancing the biosynthesis of chaxamycins and chaxalactins. Gene knockouts, such as sle03600 (L-homoserine O-acetyltransferase), and sle39090 (trehalose-phosphate synthase), that enhance the production of the specialized metabolites by increasing the pool of precursors were identified. Using the algorithm of flux scanning based on enforced objective flux (FSEOF) implemented in python, 35 and 25 over-expression targets for increasing the production of chaxamycin A and chaxalactin A, respectively, that were not directly associated with their biosynthesis routes were identified. Nineteen over-expression targets that were common to the two specialized metabolites studied, like the over-expression of the acetyl carboxylase complex (sle47660 (accA) and any of the following genes: sle44630 (accA_1) or sle39830 (accA_2) or sle27560 (bccA) or sle59710) were identified. The predicted knockouts and over-expression targets will be used to perform metabolic engineering of S. leeuwenhoekii C34 and obtain overproducer strains. © 2018 Wiley Periodicals, Inc.

  17. Saccharomyces cerevisiae engineered for xylose metabolism exhibits a respiratory response

    Science.gov (United States)

    Yong-Su Jin; Jose M. Laplaza; Thomas W. Jeffries

    2004-01-01

    Native strains of Saccharomyces cerevisiae do not assimilate xylose. S. cerevisiae engineered for D-xylose utilization through the heterologous expression of genes for aldose reductase ( XYL1), xylitol dehydrogenase (XYL2), and D-xylulokinase ( XYL3 or XKS1) produce only limited amounts of ethanol in xylose medium. In recombinant S. cerevisiae expressing XYL1, XYL2,...

  18. Natural and modified promoters for tailored metabolic engineering of the yeast Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Hubmann, Georg; Thevelein, Johan M; Nevoigt, Elke

    2014-01-01

    The ease of highly sophisticated genetic manipulations in the yeast Saccharomyces cerevisiae has initiated numerous initiatives towards development of metabolically engineered strains for novel applications beyond its traditional use in brewing, baking, and wine making. In fact, baker's yeast has

  19. Metabolism and Regulation of Glycerolipids in the Yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Henry, Susan A.; Kohlwein, Sepp D.; Carman, George M.

    2012-01-01

    Due to its genetic tractability and increasing wealth of accessible data, the yeast Saccharomyces cerevisiae is a model system of choice for the study of the genetics, biochemistry, and cell biology of eukaryotic lipid metabolism. Glycerolipids (e.g., phospholipids and triacylglycerol) and their precursors are synthesized and metabolized by enzymes associated with the cytosol and membranous organelles, including endoplasmic reticulum, mitochondria, and lipid droplets. Genetic and biochemical analyses have revealed that glycerolipids play important roles in cell signaling, membrane trafficking, and anchoring of membrane proteins in addition to membrane structure. The expression of glycerolipid enzymes is controlled by a variety of conditions including growth stage and nutrient availability. Much of this regulation occurs at the transcriptional level and involves the Ino2–Ino4 activation complex and the Opi1 repressor, which interacts with Ino2 to attenuate transcriptional activation of UASINO-containing glycerolipid biosynthetic genes. Cellular levels of phosphatidic acid, precursor to all membrane phospholipids and the storage lipid triacylglycerol, regulates transcription of UASINO-containing genes by tethering Opi1 to the nuclear/endoplasmic reticulum membrane and controlling its translocation into the nucleus, a mechanism largely controlled by inositol availability. The transcriptional activator Zap1 controls the expression of some phospholipid synthesis genes in response to zinc availability. Regulatory mechanisms also include control of catalytic activity of glycerolipid enzymes by water-soluble precursors, products and lipids, and covalent modification of phosphorylation, while in vivo function of some enzymes is governed by their subcellular location. Genome-wide genetic analysis indicates coordinate regulation between glycerolipid metabolism and a broad spectrum of metabolic pathways. PMID:22345606

  20. Dynamic optimal metabolic control theory: a cybernetic approach for modelling of the central nitrogen metabolism of S. cerevisiae

    NARCIS (Netherlands)

    Riel, van N.A.W.; Giuseppin, M.L.F.; Verrips, C.T.

    2000-01-01

    The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the

  1. Phenotypic and metabolic traits of commercial Saccharomyces cerevisiae yeasts.

    Science.gov (United States)

    Barbosa, Catarina; Lage, Patrícia; Vilela, Alice; Mendes-Faia, Arlete; Mendes-Ferreira, Ana

    2014-01-01

    Currently, pursuing yeast strains that display both a high potential fitness for alcoholic fermentation and a favorable impact on quality is a major goal in the alcoholic beverage industry. This considerable industrial interest has led to many studies characterizing the phenotypic and metabolic traits of commercial yeast populations. In this study, 20 Saccharomyces cerevisiae strains from different geographical origins exhibited high phenotypic diversity when their response to nine biotechnologically relevant conditions was examined. Next, the fermentation fitness and metabolic traits of eight selected strains with a unique phenotypic profile were evaluated in a high-sugar synthetic medium under two nitrogen regimes. Although the strains exhibited significant differences in nitrogen requirements and utilization rates, a direct relationship between nitrogen consumption, specific growth rate, cell biomass, cell viability, acetic acid and glycerol formation was only observed under high-nitrogen conditions. In contrast, the strains produced more succinic acid under the low-nitrogen regime, and a direct relationship with the final cell biomass was established. Glucose and fructose utilization patterns depended on both yeast strain and nitrogen availability. For low-nitrogen fermentation, three strains did not fully degrade the fructose. This study validates phenotypic and metabolic diversity among commercial wine yeasts and contributes new findings on the relationship between nitrogen availability, yeast cell growth and sugar utilization. We suggest that measuring nitrogen during the stationary growth phase is important because yeast cells fermentative activity is not exclusively related to population size, as previously assumed, but it is also related to the quantity of nitrogen consumed during this growth phase.

  2. Ethylene production in relation to nitrogen metabolism in Saccharomyces cerevisiae.

    Science.gov (United States)

    Johansson, Nina; Persson, Karl O; Quehl, Paul; Norbeck, Joakim; Larsson, Christer

    2014-11-01

    We have previously shown that ethylene production in Saccharomyces cerevisiae expressing the ethylene-forming enzyme (EFE) from Pseudomonas syringae is strongly influenced by variations in the mode of cultivation as well as the choice of nitrogen source. Here, we have studied the influence of nitrogen metabolism on the production of ethylene further. Using ammonium, glutamate, glutamate/arginine, and arginine as nitrogen sources, it was found that glutamate (with or without arginine) correlates with a high ethylene production, most likely linked to an observed increase in 2-oxoglutarate levels. Arginine as a sole nitrogen source caused a reduced ethylene production. A reduction of arginine levels, accomplished using an arginine auxotrophic ARG4-deletion strain in the presence of limiting amounts of arginine or through CAR1 overexpression, did however not correlate with an increased ethylene production. As expected, arginine was necessary for ethylene production as ethylene production in the ARG4-deletion strain ceased at the time when arginine was depleted. In conclusion, our data suggest that high levels of 2-oxoglutarate and a limited amount of arginine are required for successful ethylene production in yeast. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  3. Dynamic Metabolic Footprinting Reveals the Key Components of Metabolic Network in Yeast Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Chumnanpuen, Pramote; Hansen, Michael Adsetts Edberg; Smedsgaard, Jørn

    2014-01-01

    relies on analysis at a single time point. Using direct infusion-mass spectrometry (DI-MS), we could observe the dynamic metabolic footprinting in yeast S. cerevisiae BY4709 (wild type) cultured on 3 different C-sources (glucose, glycerol, and ethanol) and sampled along 10 time points with 5 biological...... replicates. In order to analyze the dynamic mass spectrometry data, we developed the novel analysis methods that allow us to perform correlation analysis to identify metabolites that significantly correlate over time during growth on the different carbon sources. Both positive and negative electrospray...... reconstructed an interaction map that provides information of how different metabolic pathways have correlated patterns during growth on the different carbon sources....

  4. Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

    Science.gov (United States)

    Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

    2016-09-01

    Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.

  5. Horizontal and vertical growth of S. cerevisiae metabolic network.

    KAUST Repository

    Grassi, Luigi; Tramontano, Anna

    2011-01-01

    of more specialized enzymes rather than as a source of novel reactions. We also show that the switch between the two evolutionary strategies in S. cerevisiae can be dated to about 350 million years ago. CONCLUSIONS: Our data, obtained through a novel

  6. Genome-scale biological models for industrial microbial systems.

    Science.gov (United States)

    Xu, Nan; Ye, Chao; Liu, Liming

    2018-04-01

    The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.

  7. Energetic and metabolic transient response of Saccharomyces cerevisiae to benzoic acid.

    Science.gov (United States)

    Kresnowati, M T A P; van Winden, W A; van Gulik, W M; Heijnen, J J

    2008-11-01

    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.

  8. Advances in metabolic engineering of yeast Saccharomyces cerevisiae for production of chemicals

    DEFF Research Database (Denmark)

    Borodina, Irina; Nielsen, Jens

    2014-01-01

    Yeast Saccharomyces cerevisiae is an important industrial host for production of enzymes, pharmaceutical and nutraceutical ingredients and recently also commodity chemicals and biofuels. Here, we review the advances in modeling and synthetic biology tools and how these tools can speed up the deve......Yeast Saccharomyces cerevisiae is an important industrial host for production of enzymes, pharmaceutical and nutraceutical ingredients and recently also commodity chemicals and biofuels. Here, we review the advances in modeling and synthetic biology tools and how these tools can speed up...... the development of yeast cell factories. We also present an overview of metabolic engineering strategies for developing yeast strains for production of polymer monomers: lactic, succinic, and cis,cis-muconic acids. S. cerevisiae has already firmly established itself as a cell factory in industrial biotechnology...

  9. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    NARCIS (Netherlands)

    Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Blüthgen, Nils; Borger, Simon; Costenoble, Roeland; Heinemann, Matthias; Hucka, Michael; Novère, Nicolas Le; Li, Peter; Liebermeister, Wolfram; Mo, Monica L.; Oliveira, Ana Paula; Petranovic, Dina; Pettifer, Stephen; Simeonidis, Evangelos; Smallbone, Kieran; Spasić, Irena; Weichart, Dieter; Brent, Roger; Broomhead, David S.; Westerhoff, Hans V.; Kırdar, Betül; Penttilä, Merja; Klipp, Edda; Palsson, Bernhard Ø.; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B.

    2008-01-01

    Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and

  10. Engineering the fatty acid metabolic pathway in Saccharomyces cerevisiae for advanced biofuel production

    Directory of Open Access Journals (Sweden)

    Xiaoling Tang

    2015-12-01

    Full Text Available Fatty acid-derived fuels and chemicals have attracted a great deal of attention in recent decades, due to their following properties of high compatibility to gasoline-based fuels and existing infrastructure for their direct utilization, storage and distribution. The yeast Saccharomyces cerevisiae is the ideal biofuel producing candidate, based on the wealth of available genetic information and versatile tools designed to manipulate its metabolic pathways. Engineering the fatty acid metabolic pathways in S. cerevisiae is an effective strategy to increase its fatty acid biosynthesis and provide more pathway precursors for production of targeted products. This review summarizes the recent progress in metabolic engineering of yeast cells for fatty acids and fatty acid derivatives production, including the regulation of acetyl-CoA biosynthesis, NADPH production, fatty acid elongation, and the accumulation of activated precursors of fatty acids for converting enzymes. By introducing specific enzymes in the engineered strains, a powerful platform with a scalable, controllable and economic route for advanced biofuel production has been established. Keywords: Metabolic engineering, Fatty acid biosynthesis, Fatty acid derivatives, Saccharomyces cerevisiae

  11. ¹³C-based metabolic flux analysis of Saccharomyces cerevisiae with a reduced Crabtree effect.

    Science.gov (United States)

    Kajihata, Shuichi; Matsuda, Fumio; Yoshimi, Mika; Hayakawa, Kenshi; Furusawa, Chikara; Kanda, Akihisa; Shimizu, Hiroshi

    2015-08-01

    Saccharomyces cerevisiae shows a Crabtree effect that produces ethanol in a high glucose concentration even under fully aerobic condition. For efficient production of cake yeast or compressed yeast for baking, ethanol by-production is not desired since glucose limited chemostat or fed-batch cultivations are performed to suppress the Crabtree effect. In this study, the (13)C-based metabolic flux analysis ((13)C-MFA) was performed for the S288C derived S. cerevisiae strain to characterize a metabolic state under the reduced Crabtree effect. S. cerevisiae cells were cultured at a low dilution rate (0.1 h(-1)) under the glucose-limited chemostat condition. The estimated metabolic flux distribution showed that the acetyl-CoA in mitochondria was mainly produced from pyruvate by pyruvate dehydrogenase (PDH) reaction and that the level of the metabolic flux through the pentose phosphate pathway was much higher than that of the Embden-Meyerhof-Parnas pathway, which contributes to high biomass yield at low dilution rate by supplying NADPH required for cell growth. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  12. Calorie restriction hysteretically primes aging Saccharomyces cerevisiae toward more effective oxidative metabolism.

    Directory of Open Access Journals (Sweden)

    Erich B Tahara

    Full Text Available Calorie restriction (CR is an intervention known to extend the lifespan of a wide variety of organisms. In S. cerevisiae, chronological lifespan is prolonged by decreasing glucose availability in the culture media, a model for CR. The mechanism has been proposed to involve an increase in the oxidative (versus fermentative metabolism of glucose. Here, we measured wild-type and respiratory incompetent (ρ(0 S. cerevisiae biomass formation, pH, oxygen and glucose consumption, and the evolution of ethanol, glycerol, acetate, pyruvate and succinate levels during the course of 28 days of chronological aging, aiming to identify metabolic changes responsible for the effects of CR. The concomitant and quantitative measurements allowed for calculations of conversion factors between different pairs of substrates and products, maximum specific substrate consumption and product formation rates and maximum specific growth rates. Interestingly, we found that the limitation of glucose availability in CR S. cerevisiae cultures hysteretically increases oxygen consumption rates many hours after the complete exhaustion of glucose from the media. Surprisingly, glucose-to-ethanol conversion and cellular growth supported by glucose were not quantitatively altered by CR. Instead, we found that CR primed the cells for earlier, faster and more efficient metabolism of respiratory substrates, especially ethanol. Since lifespan-enhancing effects of CR are absent in respiratory incompetent ρ(0 cells, we propose that the hysteretic effect of glucose limitation on oxidative metabolism is central toward chronological lifespan extension by CR in this yeast.

  13. Improving flavor metabolism of Saccharomyces cerevisiae by mixed culture with Bacillus licheniformis for Chinese Maotai-flavor liquor making.

    Science.gov (United States)

    Meng, Xing; Wu, Qun; Wang, Li; Wang, Diqiang; Chen, Liangqiang; Xu, Yan

    2015-12-01

    Microbial interactions could impact the metabolic behavior of microbes involved in food fermentation, and therefore they are important for improving food quality. This study investigated the effect of Bacillus licheniformis, the dominant bacteria in the fermentation process of Chinese Maotai-flavor liquor, on the metabolic activity of Saccharomyces cerevisiae. Results indicated that S. cerevisiae inhibited the growth of B. licheniformis in all mixed culture systems and final viable cell count was lower than 20 cfu/mL. Although growth of S. cerevisiae was barely influenced by B. licheniformis, its metabolism was changed as initial inoculation ratio varied. The maximum ethanol productions were observed in S. cerevisiae and B. licheniformis at 10(6):10(7) and 10(6):10(8) ratios and have increased by 16.8 % compared with single culture of S. cerevisiae. According to flavor compounds, the culture ratio 10(6):10(6) showed the highest level of total concentrations of all different kinds of flavor compounds. Correlation analyses showed that 12 flavor compounds, including 4 fatty acids and their 2 corresponding esters, 1 terpene, and 5 aromatic compounds, that could only be produced by S. cerevisiae were significantly correlated with the initial inoculation amount of B. licheniformis. These metabolic changes in S. cerevisiae were not only a benefit for liquor aroma, but may also be related to its inhibition effect in mixed culture. This study could help to reveal the microbial interactions in Chinese liquor fermentation and provide guidance for optimal arrangement of mixed culture fermentation systems.

  14. Metabolic engineering of Saccharomyces cerevisiae: a key cell factory platform for future biorefineries.

    Science.gov (United States)

    Hong, Kuk-Ki; Nielsen, Jens

    2012-08-01

    Metabolic engineering is the enabling science of development of efficient cell factories for the production of fuels, chemicals, pharmaceuticals, and food ingredients through microbial fermentations. The yeast Saccharomyces cerevisiae is a key cell factory already used for the production of a wide range of industrial products, and here we review ongoing work, particularly in industry, on using this organism for the production of butanol, which can be used as biofuel, and isoprenoids, which can find a wide range of applications including as pharmaceuticals and as biodiesel. We also look into how engineering of yeast can lead to improved uptake of sugars that are present in biomass hydrolyzates, and hereby allow for utilization of biomass as feedstock in the production of fuels and chemicals employing S. cerevisiae. Finally, we discuss the perspectives of how technologies from systems biology and synthetic biology can be used to advance metabolic engineering of yeast.

  15. Effects of furfural on the respiratory metabolism of Saccharomyces cerevisiae in glucose-limited chemostats,

    OpenAIRE

    Sarvari Horvath, I; Franzén, C J; Taherzadeh, M J; Niklasson, C; Lidén, Gunnar

    2003-01-01

    Effects of furfural on the aerobic metabolism of the yeast Saccharomyces cerevisiae were studied by performing chemostat experiments, and the kinetics of furfural conversion was analyzed by performing dynamic experiments. Furfural, an important inhibitor present in lignocellulosic hydrolysates, was shown to have an inhibitory effect on yeast cells growing respiratively which was much greater than the inhibitory effect previously observed for anaerobically growing yeast cells. The residual fur...

  16. Impact of systems biology on metabolic engineering of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Nielsen, Jens; Jewett, Michael Christopher

    2008-01-01

    in the industrial application of this yeast. Developments in genomics and high-throughput systems biology tools are enhancing one's ability to rapidly characterize cellular behaviour, which is valuable in the field of metabolic engineering where strain characterization is often the bottleneck in strain development...... programmes. Here, the impact of systems biology on metabolic engineering is reviewed and perspectives on the role of systems biology in the design of cell factories are given....

  17. Metabolic engineering of Saccharomyces cerevisiae for caffeine and theobromine production.

    Directory of Open Access Journals (Sweden)

    Lu Jin

    Full Text Available Caffeine (1, 3, 7-trimethylxanthine and theobromine (3, 7-dimethylxanthine are the major purine alkaloids in plants, e.g., tea (Camellia sinensis and coffee (Coffea arabica. Caffeine is a major component of coffee and is used widely in food and beverage industries. Most of the enzymes involved in the caffeine biosynthetic pathway have been reported previously. Here, we demonstrated the biosynthesis of caffeine (0.38 mg/L by co-expression of Coffea arabica xanthosine methyltransferase (CaXMT and Camellia sinensis caffeine synthase (TCS in Saccharomyces cerevisiae. Furthermore, we endeavored to develop this production platform for making other purine-based alkaloids. To increase the catalytic activity of TCS in an effort to increase theobromine production, we identified four amino acid residues based on structural analyses of 3D-model of TCS. Two TCS1 mutants (Val317Met and Phe217Trp slightly increased in theobromine accumulation and simultaneously decreased in caffeine production. The application and further optimization of this biosynthetic platform are discussed.

  18. Metabolic engineering of Saccharomyces cerevisiae for caffeine and theobromine production.

    Science.gov (United States)

    Jin, Lu; Bhuiya, Mohammad Wadud; Li, Mengmeng; Liu, XiangQi; Han, Jixiang; Deng, WeiWei; Wang, Min; Yu, Oliver; Zhang, Zhengzhu

    2014-01-01

    Caffeine (1, 3, 7-trimethylxanthine) and theobromine (3, 7-dimethylxanthine) are the major purine alkaloids in plants, e.g., tea (Camellia sinensis) and coffee (Coffea arabica). Caffeine is a major component of coffee and is used widely in food and beverage industries. Most of the enzymes involved in the caffeine biosynthetic pathway have been reported previously. Here, we demonstrated the biosynthesis of caffeine (0.38 mg/L) by co-expression of Coffea arabica xanthosine methyltransferase (CaXMT) and Camellia sinensis caffeine synthase (TCS) in Saccharomyces cerevisiae. Furthermore, we endeavored to develop this production platform for making other purine-based alkaloids. To increase the catalytic activity of TCS in an effort to increase theobromine production, we identified four amino acid residues based on structural analyses of 3D-model of TCS. Two TCS1 mutants (Val317Met and Phe217Trp) slightly increased in theobromine accumulation and simultaneously decreased in caffeine production. The application and further optimization of this biosynthetic platform are discussed.

  19. Robust metabolic responses to varied carbon sources in natural and laboratory strains of Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Wayne A Van Voorhies

    Full Text Available Understanding factors that regulate the metabolism and growth of an organism is of fundamental biologic interest. This study compared the influence of two different carbon substrates, dextrose and galactose, on the metabolic and growth rates of the yeast Saccharomyces cerevisiae. Yeast metabolic and growth rates varied widely depending on the metabolic substrate supplied. The metabolic and growth rates of a yeast strain maintained under long-term laboratory conditions was compared to strain isolated from natural condition when grown on different substrates. Previous studies had determined that there are numerous genetic differences between these two strains. However, the overall metabolic and growth rates of a wild isolate of yeast was very similar to that of a strain that had been maintained under laboratory conditions for many decades. This indicates that, at in least this case, metabolism and growth appear to be well buffered against genetic differences. Metabolic rate and cell number did not co-vary in a simple linear manner. When grown in either dextrose or galactose, both strains showed a growth pattern in which the number of cells continued to increase well after the metabolic rate began a sharp decline. Previous studied have reported that O₂ consumption in S. cerevisiae grown in reduced dextrose levels were elevated compared to higher levels. Low dextrose levels have been proposed to induce caloric restriction and increase life span in yeast. However, there was no evidence that reduced levels of dextrose increased metabolic rates, measured by either O₂ consumption or CO₂ production, in the strains used in this study.

  20. Validation of a metabolic network for Saccharomyces cerevisiae using mixed substrate studies.

    Science.gov (United States)

    Vanrolleghem, P A; de Jong-Gubbels, P; van Gulik, W M; Pronk, J T; van Dijken, J P; Heijnen, S

    1996-01-01

    Setting up a metabolic network model for respiratory growth of Saccharomyces cerevisiae requires the estimation of only two (energetic) stoichiometric parameters: (1) the operational PO ratio and (2) a growth-related maintenance factor k. It is shown, both theoretically and practically, how chemostat cultivations with different mixtures of two substrates allow unique values to be given to these unknowns of the proposed metabolic model. For the yeast and model considered, an effective PO ratio of 1.09 mol of ATP/mol of O (95% confidence interval 1.07-1.11) and a k factor of 0.415 mol of ATP/C-mol of biomass (0.385-0.445) were obtained from biomass substrate yield data on glucose/ethanol mixtures. Symbolic manipulation software proved very valuable in this study as it supported the proof of theoretical identifiability and significantly reduced the necessary computations for parameter estimation. In the transition from 100% glucose to 100% ethanol in the feed, four metabolic regimes occur. Switching between these regimes is determined by cessation of an irreversible reaction and initiation of an alternative reaction. Metabolic network predictions of these metabolic switches compared well with activity measurements of key enzymes. As a second validation of the network, the biomass yield of S. cerevisiae on acetate was also compared to the network prediction. An excellent agreement was found for a network in which acetate transport was modeled with a proton symport, while passive diffusion of acetate gave significantly higher yield predictions.

  1. The OME Framework for genome-scale systems biology

    Energy Technology Data Exchange (ETDEWEB)

    Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)

    2014-12-19

    The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale

  2. Advances in metabolic engineering of yeast Saccharomyces cerevisiae for production of chemicals.

    Science.gov (United States)

    Borodina, Irina; Nielsen, Jens

    2014-05-01

    Yeast Saccharomyces cerevisiae is an important industrial host for production of enzymes, pharmaceutical and nutraceutical ingredients and recently also commodity chemicals and biofuels. Here, we review the advances in modeling and synthetic biology tools and how these tools can speed up the development of yeast cell factories. We also present an overview of metabolic engineering strategies for developing yeast strains for production of polymer monomers: lactic, succinic, and cis,cis-muconic acids. S. cerevisiae has already firmly established itself as a cell factory in industrial biotechnology and the advances in yeast strain engineering will stimulate development of novel yeast-based processes for chemicals production. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. Reserve carbohydrates metabolism in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    François, J; Parrou, J L

    2001-01-01

    Glycogen and trehalose are the two glucose stores of yeast cells. The large variations in the cell content of these two compounds in response to different environmental changes indicate that their metabolism is controlled by complex regulatory systems. In this review we present information on the regulation of the activity of the enzymes implicated in the pathways of synthesis and degradation of glycogen and trehalose as well as on the transcriptional control of the genes encoding them. cAMP and the protein kinases Snf1 and Pho85 appear as major actors in this regulation. From a metabolic point of view, glucose-6-phosphate seems the major effector in the net synthesis of glycogen and trehalose. We discuss also the implication of the recently elucidated TOR-dependent nutrient signalling pathway in the control of the yeast glucose stores and its integration in growth and cell division. The unexpected roles of glycogen and trehalose found in the control of glycolytic flux, stress responses and energy stores for the budding process, demonstrate that their presence confers survival and reproductive advantages to the cell. The findings discussed provide for the first time a teleonomic value for the presence of two different glucose stores in the yeast cell.

  4. Metabolic link between phosphatidylethanolamine and triacylglycerol metabolism in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Horvath, Susanne E; Wagner, Andrea; Steyrer, Ernst; Daum, Günther

    2011-12-01

    In the yeast Saccharomyces cerevisiae triacylglycerols (TAG) are synthesized by the acyl-CoA dependent acyltransferases Dga1p, Are1p, Are2p and the acyl-CoA independent phospholipid:diacylglycerol acyltransferase (PDAT) Lro1p which uses phosphatidylethanolamine (PE) as a preferred acyl donor. In the present study we investigated a possible link between TAG and PE metabolism by analyzing the contribution of the four different PE biosynthetic pathways to TAG formation, namely de novo PE synthesis via Psd1p and Psd2p, the CDP-ethanolamine (CDP-Etn) pathway and lyso-PE acylation by Ale1p. In cells grown on the non-fermentable carbon source lactate supplemented with 5mM ethanolamine (Etn) the CDP-Etn pathway contributed most to the cellular TAG level, whereas mutations in the other pathways displayed only minor effects. In cki1∆dpl1∆eki1∆ mutants bearing defects in the CDP-Etn pathway both the cellular and the microsomal levels of PE were markedly decreased, whereas in other mutants of PE biosynthetic routes depletion of this aminoglycerophospholipid was less pronounced in microsomes. This observation is important because Lro1p similar to the enzymes of the CDP-Etn pathway is a component of the ER. We conclude from these results that in cki1∆dpl1∆eki1∆ insufficient supply of PE to the PDAT Lro1p was a major reason for the strongly reduced TAG level. Moreover, we found that Lro1p activity was markedly decreased in cki1∆dpl1∆eki1∆, although transcription of LRO1 was not affected. Our findings imply that (i) TAG and PE syntheses in the yeast are tightly linked; and (ii) TAG formation by the PDAT Lro1p strongly depends on PE synthesis through the CDP-Etn pathway. Moreover, it is very likely that local availability of PE in microsomes is crucial for TAG synthesis through the Lro1p reaction. Copyright © 2011 Elsevier B.V. All rights reserved.

  5. Alleviation of glucose repression of maltose metabolism by MIG1 disruption in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Klein, Christopher; Olsson, Lisbeth; Rønnow, B.

    1996-01-01

    The MIG1 gene was disrupted in a haploid laboratory strain (B224) and in an industrial polyploid strain (DGI 342) of Saccharomyces cerevisiae. The alleviation of glucose repression of the expression of MAL genes and alleviation of glucose control of maltose metabolism were investigated in batch...... cultivations on glucose-maltose mixtures. In the MIG1-disrupted haploid strain, glucose repression was partly alleviated; i.e., maltose metabolism was initiated at higher glucose concentrations than in the corresponding wild-type strain. In contrast, the polyploid Delta mig1 strain exhibited an even more...... stringent glucose control of maltose metabolism than the corresponding wild-type strain, which could be explained by a more rigid catabolite inactivation of maltose permease, affecting the uptake of maltose. Growth on the glucose-sucrose mixture showed that the polyploid Delta mig1 strain was relieved...

  6. Production of 3-hydroxypropionic acid from glucose and xylose by metabolically engineered Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Kanchana R. Kildegaard

    2015-12-01

    Full Text Available Biomass, the most abundant carbon source on the planet, may in the future become the primary feedstock for production of fuels and chemicals, replacing fossil feedstocks. This will, however, require development of cell factories that can convert both C6 and C5 sugars present in lignocellulosic biomass into the products of interest. We engineered Saccharomyces cerevisiae for production of 3-hydroxypropionic acid (3HP, a potential building block for acrylates, from glucose and xylose. We introduced the 3HP biosynthetic pathways via malonyl-CoA or β-alanine intermediates into a xylose-consuming yeast. Using controlled fed-batch cultivation, we obtained 7.37±0.17 g 3HP L−1 in 120 hours with an overall yield of 29±1% Cmol 3HP Cmol−1 xylose. This study is the first demonstration of the potential of using S. cerevisiae for production of 3HP from the biomass sugar xylose. Keywords: Metabolic engineering, Biorefineries, 3-hydroxypropionic acid, Saccharomyces cerevisiae, Xylose utilization

  7. Glycerol positive promoters for tailored metabolic engineering of the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Ho, Ping-Wei; Klein, Mathias; Futschik, Matthias; Nevoigt, Elke

    2018-05-01

    Glycerol offers several advantages as a substrate for biotechnological applications. An important step toward using the popular production host Saccharomyces cerevisiae for glycerol-based bioprocesses has been the fact that in recent studies commonly used S. cerevisiae strains were engineered to grow in synthetic medium containing glycerol as the sole carbon source. For metabolic engineering projects of S. cerevisiae growing on glycerol, characterized promoters are missing. In the current study, we used transcriptome analysis and a yECitrine-based fluorescence reporter assay to select and characterize 25 useful promoters. The promoters of the genes ALD4 and ADH2 showed 4.2-fold and 3-fold higher activities compared to the well-known strong TEF1 promoter. Moreover, the collection contains promoters with graded activities in synthetic glycerol medium and different degrees of glucose repression. To demonstrate the general applicability of the promoter collection, we successfully used a subset of the characterized promoters with graded activities in order to optimize growth on glycerol in an engineered derivative of CEN.PK, in which glycerol catabolism exclusively occurs via a non-native DHA pathway.

  8. Regulation of Lactobacillus plantarum contamination on the carbohydrate and energy related metabolisms of Saccharomyces cerevisiae during bioethanol fermentation.

    Science.gov (United States)

    Dong, Shi-Jun; Lin, Xiang-Hua; Li, Hao

    2015-11-01

    During the industrial bioethanol fermentation, Saccharomyces cerevisiae cells are often stressed by bacterial contaminants, especially lactic acid bacteria. Generally, lactic acid bacteria contamination can inhibit S. cerevisiae cell growth through secreting lactic acid and competing with yeast cells for micronutrients and living space. However, whether are there still any other influences of lactic acid bacteria on yeast or not? In this study, Lactobacillus plantarum ATCC 8014 was co-cultivated with S. cerevisiae S288c to mimic the L. plantarum contamination in industrial bioethanol fermentation. The contaminative L. plantarum-associated expression changes of genes involved in carbohydrate and energy related metabolisms in S. cerevisiae cells were determined by quantitative real-time polymerase chain reaction to evaluate the influence of L. plantarum on carbon source utilization and energy related metabolism in yeast cells during bioethanol fermentation. Contaminative L. plantarum influenced the expression of most of genes which are responsible for encoding key enzymes involved in glucose related metabolisms in S. cerevisiae. Specific for, contaminated L. plantarum inhibited EMP pathway but promoted TCA cycle, glyoxylate cycle, HMP, glycerol synthesis pathway, and redox pathway in S. cerevisiae cells. In the presence of L. plantarum, the carbon flux in S. cerevisiae cells was redistributed from fermentation to respiratory and more reducing power was produced to deal with the excess NADH. Moreover, L. plantarum contamination might confer higher ethanol tolerance to yeast cells through promoting accumulation of glycerol. These results also highlighted our knowledge about relationship between contaminative lactic acid bacteria and S. cerevisiae during bioethanol fermentation. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. The fungicide triadimefon affects beer flavor and composition by influencing Saccharomyces cerevisiae metabolism

    Science.gov (United States)

    Kong, Zhiqiang; Li, Minmin; An, Jingjing; Chen, Jieying; Bao, Yuming; Francis, Frédéric; Dai, Xiaofeng

    2016-09-01

    Despite the fact that beer is produced on a large scale, the effects of pesticide residues on beer have been rarely investigated. In this study, we used micro-brewing settings to determine the effect of triadimefon on the growth of Saccharomyces cerevisiae and beer flavor. The yeast growth in medium was significantly inhibited (45%) at concentrations higher than 5 mg L-1, reaching 80% and 100% inhibition at 10 mg L-1 and 50 mg L-1, respectively. There were significant differences in sensory quality between beer samples fermented with and without triadimefon based on data obtained with an electronic tongue and nose. Such an effect was most likely underlain by changes in yeast fermentation activity, including decreased utilization of maltotriose and most amino acids, reduced production of isobutyl and isoamyl alcohols, and increased ethyl acetate content in the fungicide treated samples. Furthermore, yeast metabolic profiling by phenotype microarray and UPLC/TOF-MS showed that triadimefon caused significant changes in the metabolism of glutathione, phenylalanine and sphingolipids, and in sterol biosynthesis. Thus, triadimefon negatively affects beer sensory qualities by influencing the metabolic activity of S. cerevisiae during fermentation, emphasizing the necessity of stricter control over fungicide residues in brewing by the food industry.

  10. L-carnosine affects the growth of Saccharomyces cerevisiae in a metabolism-dependent manner.

    Science.gov (United States)

    Cartwright, Stephanie P; Bill, Roslyn M; Hipkiss, Alan R

    2012-01-01

    The dipeptide L-carnosine (β-alanyl-L-histidine) has been described as enigmatic: it inhibits growth of cancer cells but delays senescence in cultured human fibroblasts and extends the lifespan of male fruit flies. In an attempt to understand these observations, the effects of L-carnosine on the model eukaryote, Saccharomyces cerevisiae, were examined on account of its unique metabolic properties; S. cerevisiae can respire aerobically, but like some tumor cells, it can also exhibit a metabolism in which aerobic respiration is down regulated. L-Carnosine exhibited both inhibitory and stimulatory effects on yeast cells, dependent upon the carbon source in the growth medium. When yeast cells were not reliant on oxidative phosphorylation for energy generation (e.g. when grown on a fermentable carbon source such as 2% glucose), 10-30 mM L-carnosine slowed growth rates in a dose-dependent manner and increased cell death by up to 17%. In contrast, in media containing a non-fermentable carbon source in which yeast are dependent on aerobic respiration (e.g. 2% glycerol), L-carnosine did not provoke cell death. This latter observation was confirmed in the respiratory yeast, Pichia pastoris. Moreover, when deletion strains in the yeast nutrient-sensing pathway were treated with L-carnosine, the cells showed resistance to its inhibitory effects. These findings suggest that L-carnosine affects cells in a metabolism-dependent manner and provide a rationale for its effects on different cell types.

  11. Metabolic flux analysis during the exponential growth phase of Saccharomyces cerevisiae in wine fermentations.

    Directory of Open Access Journals (Sweden)

    Manuel Quirós

    Full Text Available As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations.

  12. Acetate metabolism of Saccharomyces cerevisiae at different temperatures during lychee wine fermentation

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    Yu-hui Shang

    2016-05-01

    Full Text Available The yeast (Saccharomyces cerevisiae strain 2137 involved in lychee wine production was used to investigate acetate metabolism at different temperatures during lychee wine fermentation. Fermentation tests were conducted using lychee juice supplemented with acetic acid. The ability of yeast cells to metabolize acetic acid was stronger at 20 °C than at 25 °C or 30 °C. The addition of acetic acid suppressed the yeast cell growth at the tested temperatures. The viability was higher and the reactive oxygen species concentration was lower at 20 °C than at 30 °C; this result indicated that acid stress adaptation protects S. cerevisiae from acetic-acid-mediated programmed cell death. The acetic acid enhanced the thermal death of yeast at high temperatures. The fermentation temperature modified the metabolism of the yeasts and the activity of related enzymes during deacidification, because less acetaldehyde, less glycerol, more ethanol, more succinic acid and more malic acid were produced, with higher level of acetyl–CoA synthetase and isocitrate lyase activity, at 20 °C.

  13. The Genome-Scale Integrated Networks in Microorganisms

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    Tong Hao

    2018-02-01

    Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

  14. Improved Xylose Metabolism by a CYC8 Mutant of Saccharomyces cerevisiae.

    Science.gov (United States)

    Nijland, Jeroen G; Shin, Hyun Yong; Boender, Leonie G M; de Waal, Paul P; Klaassen, Paul; Driessen, Arnold J M

    2017-06-01

    Engineering Saccharomyces cerevisiae for the utilization of pentose sugars is an important goal for the production of second-generation bioethanol and biochemicals. However, S. cerevisiae lacks specific pentose transporters, and in the presence of glucose, pentoses enter the cell inefficiently via endogenous hexose transporters (HXTs). By means of in vivo engineering, we have developed a quadruple hexokinase deletion mutant of S. cerevisiae that evolved into a strain that efficiently utilizes d-xylose in the presence of high d-glucose concentrations. A genome sequence analysis revealed a mutation (Y353C) in the general corepressor CYC8 , or SSN6 , which was found to be responsible for the phenotype when introduced individually in the nonevolved strain. A transcriptome analysis revealed altered expression of 95 genes in total, including genes involved in (i) hexose transport, (ii) maltose metabolism, (iii) cell wall function (mannoprotein family), and (iv) unknown functions (seripauperin multigene family). Of the 18 known HXTs, genes for 9 were upregulated, especially the low or nonexpressed HXT10 , HXT13 , HXT15 , and HXT16 Mutant cells showed increased uptake rates of d-xylose in the presence of d-glucose, as well as elevated maximum rates of metabolism ( V max ) for both d-glucose and d-xylose transport. The data suggest that the increased expression of multiple hexose transporters renders d-xylose metabolism less sensitive to d-glucose inhibition due to an elevated transport rate of d-xylose into the cell. IMPORTANCE The yeast Saccharomyces cerevisiae is used for second-generation bioethanol formation. However, growth on xylose is limited by pentose transport through the endogenous hexose transporters (HXTs), as uptake is outcompeted by the preferred substrate, glucose. Mutant strains were obtained with improved growth characteristics on xylose in the presence of glucose, and the mutations mapped to the regulator Cyc8. The inactivation of Cyc8 caused increased

  15. Regulation of NAD+ metabolism, signaling and compartmentalization in the yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Kato, Michiko; Lin, Su-Ju

    2014-01-01

    Pyridine nucleotides are essential coenzymes in many cellular redox reactions in all living systems. In addition to functioning as a redox carrier, NAD+ is also a required co-substrate for the conserved sirtuin deacetylases. Sirtuins regulate transcription, genome maintenance and metabolism and function as molecular links between cells and their environment. Maintaining NAD+ homeostasis is essential for proper cellular function and aberrant NAD+ metabolism has been implicated in a number of metabolic- and age-associated diseases. Recently, NAD+ metabolism has been linked to the phosphate-responsive signaling pathway (PHO pathway) in the budding yeast Saccharomyces cerevisiae. Activation of the PHO pathway is associated with the production and mobilization of the NAD+ metabolite nicotinamide riboside (NR), which is mediated in part by PHO-regulated nucleotidases. Cross-regulation between NAD+ metabolism and the PHO pathway has also been reported; however, detailed mechanisms remain to be elucidated. The PHO pathway also appears to modulate the activities of common downstream effectors of multiple nutrient-sensing pathways (Ras-PKA, TOR, Sch9/AKT). These signaling pathways were suggested to play a role in calorie restriction-mediated beneficial effects, which have also been linked to Sir2 function and NAD+ metabolism. Here, we discuss the interactions of these pathways and their potential roles in regulating NAD+ metabolism. In eukaryotic cells, intracellular compartmentalization facilitates the regulation of enzymatic functions and also concentrates or sequesters specific metabolites. Various NAD+-mediated cellular functions such as mitochondrial oxidative phosphorylation are compartmentalized. Therefore, we also discuss several key players functioning in mitochondrial, cytosolic and vacuolar compartmentalization of NAD+ intermediates, and their potential roles in NAD+ homeostasis. To date, it remains unclear how NAD+ and NAD+ intermediates shuttle between different

  16. Regulation of NAD+ metabolism, signaling and compartmentalization in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Kato, Michiko; Lin, Su-Ju

    2014-11-01

    Pyridine nucleotides are essential coenzymes in many cellular redox reactions in all living systems. In addition to functioning as a redox carrier, NAD(+) is also a required co-substrate for the conserved sirtuin deacetylases. Sirtuins regulate transcription, genome maintenance and metabolism and function as molecular links between cells and their environment. Maintaining NAD(+) homeostasis is essential for proper cellular function and aberrant NAD(+) metabolism has been implicated in a number of metabolic- and age-associated diseases. Recently, NAD(+) metabolism has been linked to the phosphate-responsive signaling pathway (PHO pathway) in the budding yeast Saccharomyces cerevisiae. Activation of the PHO pathway is associated with the production and mobilization of the NAD(+) metabolite nicotinamide riboside (NR), which is mediated in part by PHO-regulated nucleotidases. Cross-regulation between NAD(+) metabolism and the PHO pathway has also been reported; however, detailed mechanisms remain to be elucidated. The PHO pathway also appears to modulate the activities of common downstream effectors of multiple nutrient-sensing pathways (Ras-PKA, TOR, Sch9/AKT). These signaling pathways were suggested to play a role in calorie restriction-mediated beneficial effects, which have also been linked to Sir2 function and NAD(+) metabolism. Here, we discuss the interactions of these pathways and their potential roles in regulating NAD(+) metabolism. In eukaryotic cells, intracellular compartmentalization facilitates the regulation of enzymatic functions and also concentrates or sequesters specific metabolites. Various NAD(+)-mediated cellular functions such as mitochondrial oxidative phosphorylation are compartmentalized. Therefore, we also discuss several key players functioning in mitochondrial, cytosolic and vacuolar compartmentalization of NAD(+) intermediates, and their potential roles in NAD(+) homeostasis. To date, it remains unclear how NAD(+) and NAD(+) intermediates

  17. L-carnosine affects the growth of Saccharomyces cerevisiae in a metabolism-dependent manner.

    Directory of Open Access Journals (Sweden)

    Stephanie P Cartwright

    Full Text Available The dipeptide L-carnosine (β-alanyl-L-histidine has been described as enigmatic: it inhibits growth of cancer cells but delays senescence in cultured human fibroblasts and extends the lifespan of male fruit flies. In an attempt to understand these observations, the effects of L-carnosine on the model eukaryote, Saccharomyces cerevisiae, were examined on account of its unique metabolic properties; S. cerevisiae can respire aerobically, but like some tumor cells, it can also exhibit a metabolism in which aerobic respiration is down regulated. L-Carnosine exhibited both inhibitory and stimulatory effects on yeast cells, dependent upon the carbon source in the growth medium. When yeast cells were not reliant on oxidative phosphorylation for energy generation (e.g. when grown on a fermentable carbon source such as 2% glucose, 10-30 mM L-carnosine slowed growth rates in a dose-dependent manner and increased cell death by up to 17%. In contrast, in media containing a non-fermentable carbon source in which yeast are dependent on aerobic respiration (e.g. 2% glycerol, L-carnosine did not provoke cell death. This latter observation was confirmed in the respiratory yeast, Pichia pastoris. Moreover, when deletion strains in the yeast nutrient-sensing pathway were treated with L-carnosine, the cells showed resistance to its inhibitory effects. These findings suggest that L-carnosine affects cells in a metabolism-dependent manner and provide a rationale for its effects on different cell types.

  18. Starmerella bombicola influences the metabolism of Saccharomyces cerevisiae at pyruvate decarboxylase and alcohol dehydrogenase level during mixed wine fermentation

    Science.gov (United States)

    2012-01-01

    Background The use of a multistarter fermentation process with Saccharomyces cerevisiae and non-Saccharomyces wine yeasts has been proposed to simulate natural must fermentation and to confer greater complexity and specificity to wine. In this context, the combined use of S. cerevisiae and immobilized Starmerella bombicola cells (formerly Candida stellata) was assayed to enhance glycerol concentration, reduce ethanol content and to improve the analytical composition of wine. In order to investigate yeast metabolic interaction during controlled mixed fermentation and to evaluate the influence of S. bombicola on S. cerevisiae, the gene expression and enzymatic activity of two key enzymes of the alcoholic fermentation pathway such as pyruvate decarboxylase (Pdc1) and alcohol dehydrogenase (Adh1) were studied. Results The presence of S. bombicola immobilized cells in a mixed fermentation trial confirmed an increase in fermentation rate, a combined consumption of glucose and fructose, an increase in glycerol and a reduction in the production of ethanol as well as a modification in the fermentation of by products. The alcoholic fermentation of S. cerevisiae was also influenced by S. bombicola immobilized cells. Indeed, Pdc1 activity in mixed fermentation was lower than that exhibited in pure culture while Adh1 activity showed an opposite behavior. The expression of both PDC1 and ADH1 genes was highly induced at the initial phase of fermentation. The expression level of PDC1 at the end of fermentation was much higher in pure culture while ADH1 level was similar in both pure and mixed fermentations. Conclusion In mixed fermentation, S. bombicola immobilized cells greatly affected the fermentation behavior of S. cerevisiae and the analytical composition of wine. The influence of S. bombicola on S. cerevisiae was not limited to a simple additive contribution. Indeed, its presence caused metabolic modifications during S. cerevisiae fermentation causing variation in the gene

  19. Starmerella bombicola influences the metabolism of Saccharomyces cerevisiae at pyruvate decarboxylase and alcohol dehydrogenase level during mixed wine fermentation

    Directory of Open Access Journals (Sweden)

    Milanovic Vesna

    2012-02-01

    Full Text Available Abstract Background The use of a multistarter fermentation process with Saccharomyces cerevisiae and non-Saccharomyces wine yeasts has been proposed to simulate natural must fermentation and to confer greater complexity and specificity to wine. In this context, the combined use of S. cerevisiae and immobilized Starmerella bombicola cells (formerly Candida stellata was assayed to enhance glycerol concentration, reduce ethanol content and to improve the analytical composition of wine. In order to investigate yeast metabolic interaction during controlled mixed fermentation and to evaluate the influence of S. bombicola on S. cerevisiae, the gene expression and enzymatic activity of two key enzymes of the alcoholic fermentation pathway such as pyruvate decarboxylase (Pdc1 and alcohol dehydrogenase (Adh1 were studied. Results The presence of S. bombicola immobilized cells in a mixed fermentation trial confirmed an increase in fermentation rate, a combined consumption of glucose and fructose, an increase in glycerol and a reduction in the production of ethanol as well as a modification in the fermentation of by products. The alcoholic fermentation of S. cerevisiae was also influenced by S. bombicola immobilized cells. Indeed, Pdc1 activity in mixed fermentation was lower than that exhibited in pure culture while Adh1 activity showed an opposite behavior. The expression of both PDC1 and ADH1 genes was highly induced at the initial phase of fermentation. The expression level of PDC1 at the end of fermentation was much higher in pure culture while ADH1 level was similar in both pure and mixed fermentations. Conclusion In mixed fermentation, S. bombicola immobilized cells greatly affected the fermentation behavior of S. cerevisiae and the analytical composition of wine. The influence of S. bombicola on S. cerevisiae was not limited to a simple additive contribution. Indeed, its presence caused metabolic modifications during S. cerevisiae fermentation

  20. Effects of Furfural on the Respiratory Metabolism of Saccharomyces cerevisiae in Glucose-Limited Chemostats

    Science.gov (United States)

    Sárvári Horváth, Ilona; Franzén, Carl Johan; Taherzadeh, Mohammad J.; Niklasson, Claes; Lidén, Gunnar

    2003-01-01

    Effects of furfural on the aerobic metabolism of the yeast Saccharomyces cerevisiae were studied by performing chemostat experiments, and the kinetics of furfural conversion was analyzed by performing dynamic experiments. Furfural, an important inhibitor present in lignocellulosic hydrolysates, was shown to have an inhibitory effect on yeast cells growing respiratively which was much greater than the inhibitory effect previously observed for anaerobically growing yeast cells. The residual furfural concentration in the bioreactor was close to zero at all steady states obtained, and it was found that furfural was exclusively converted to furoic acid during respiratory growth. A metabolic flux analysis showed that furfural affected fluxes involved in energy metabolism. There was a 50% increase in the specific respiratory activity at the highest steady-state furfural conversion rate. Higher furfural conversion rates, obtained during pulse additions of furfural, resulted in respirofermentative metabolism, a decrease in the biomass yield, and formation of furfuryl alcohol in addition to furoic acid. Under anaerobic conditions, reduction of furfural partially replaced glycerol formation as a way to regenerate NAD+. At concentrations above the inlet concentration of furfural, which resulted in complete replacement of glycerol formation by furfuryl alcohol production, washout occurred. Similarly, when the maximum rate of oxidative conversion of furfural to furoic acid was exceeded aerobically, washout occurred. Thus, during both aerobic growth and anaerobic growth, the ability to tolerate furfural appears to be directly coupled to the ability to convert furfural to less inhibitory compounds. PMID:12839784

  1. Introduction and expression of genes for metabolic engineering applications in Saccharomyces cerevisiae.

    Science.gov (United States)

    Da Silva, Nancy A; Srikrishnan, Sneha

    2012-03-01

    Metabolic pathway engineering in the yeast Saccharomyces cerevisiae leads to improved production of a wide range of compounds, ranging from ethanol (from biomass) to natural products such as sesquiterpenes. The introduction of multienzyme pathways requires precise control over the level and timing of expression of the associated genes. Gene number and promoter strength/regulation are two critical control points, and multiple studies have focused on modulating these in yeast. This MiniReview focuses on methods for introducing genes and controlling their copy number and on the many promoters (both constitutive and inducible) that have been successfully employed. The advantages and disadvantages of the methods will be presented, and applications to pathway engineering will be highlighted. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  2. Improved Production of a Heterologous Amylase in Saccharomyces cerevisiae by Inverse Metabolic Engineering

    DEFF Research Database (Denmark)

    Liu, Zihe; Liu, Lifang; Osterlund, Tobias

    2014-01-01

    this modification alone, the amylase secretion could be improved by 35%. As a complement to the identification of genomic variants, transcriptome analysis was also performed in order to understand on a global level the transcriptional changes associated with the improved amylase production caused by UV mutagenesis.......The increasing demand for industrial enzymes and biopharmaceutical proteins relies on robust production hosts with high protein yield and productivity. Being one of the best-studied model organisms and capable of performing posttranslational modifications, the yeast Saccharomyces cerevisiae...... is widely used as a cell factory for recombinant protein production. However, many recombinant proteins are produced at only 1% (or less) of the theoretical capacity due to the complexity of the secretory pathway, which has not been fully exploited. In this study, we applied the concept of inverse metabolic...

  3. Metabolic response of Danaüs archippus and Saccharomyces cerevisiae to weak oscillatory magnetic fields

    Science.gov (United States)

    Russell, D. N.; Webb, S. J.

    1981-09-01

    Respiration of the insect larva, Danaüs archippus, and the yeast, Saccharomyces cerevisiae, in log phase has been monitored before and after an oscillatory magnetic insult of 0.005 Gauss rms amplitude and 40 50 min duration. Frequencies used were 10 16 Hz for the insect and 100 200 Hz for the yeast. Depression of as much as 30% in metabolic rate has been found to occur immediately after the field is both imposed and eliminated with a general recovery over the 30-min period thereafter both in and out of the imposed field, although complete recovery to original levels may take much longer. Evidence is given that the response may depend on the frequency pattern used. This data is used to formulate an hypothesis whereby changes in the geomagnetic field variability pattern may act as a biochronometric zeitgeber.

  4. Enhancement of Naringenin Biosynthesis from Tyrosine by Metabolic Engineering of Saccharomyces cerevisiae.

    Science.gov (United States)

    Lyu, Xiaomei; Ng, Kuan Rei; Lee, Jie Lin; Mark, Rita; Chen, Wei Ning

    2017-08-09

    Flavonoids are an important class of plant polyphenols that possess a variety of health benefits. In this work, S. cerevisiae was metabolically engineered to produce the flavonoid naringenin, using tyrosine as the precursor. Our strategy to improve naringenin production comprised three modules. In module 1, we employed a modified GAL system to overexpress the genes of the naringenin biosynthesis pathway and investigated their synergistic action. In module 2, we simultaneously up-regulated acetyl-CoA production and down-regulated fatty acid biosynthesis in order to increase the precursor supply, malonyl-CoA. In module 3, we engineered the tyrosine biosynthetic pathway to eliminate the feedback inhibition of tyrosine and also down-regulated competing pathways. It was found that modules 1 and 3 played important roles in improving naringenin production. We succeeded in producing up to ∼90 mg/L of naringenin in our final strain, which is a 20-fold increase as compared to the parental strain.

  5. Increased isobutanol production in Saccharomyces cerevisiae by overexpression of genes in valine metabolism

    Directory of Open Access Journals (Sweden)

    Karhumaa Kaisa

    2011-07-01

    Full Text Available Abstract Background Isobutanol can be a better biofuel than ethanol due to its higher energy density and lower hygroscopicity. Furthermore, the branched-chain structure of isobutanol gives a higher octane number than the isomeric n-butanol. Saccharomyces cerevisiae was chosen as the production host because of its relative tolerance to alcohols, robustness in industrial fermentations, and the possibility for future combination of isobutanol production with fermentation of lignocellulosic materials. Results The yield of isobutanol was improved from 0.16 to 0.97 mg per g glucose by simultaneous overexpression of biosynthetic genes ILV2, ILV3, and ILV5 in valine metabolism in anaerobic fermentation of glucose in mineral medium in S. cerevisiae. Isobutanol yield was further improved by twofold by the additional overexpression of BAT2, encoding the cytoplasmic branched-chain amino-acid aminotransferase. Overexpression of ILV6, encoding the regulatory subunit of Ilv2, in the ILV2 ILV3 ILV5 overexpression strain decreased isobutanol production yield by threefold. In aerobic cultivations in shake flasks in mineral medium, the isobutanol yield of the ILV2 ILV3 ILV5 overexpression strain and the reference strain were 3.86 and 0.28 mg per g glucose, respectively. They increased to 4.12 and 2.4 mg per g glucose in yeast extract/peptone/dextrose (YPD complex medium under aerobic conditions, respectively. Conclusions Overexpression of genes ILV2, ILV3, ILV5, and BAT2 in valine metabolism led to an increase in isobutanol production in S. cerevisiae. Additional overexpression of ILV6 in the ILV2 ILV3 ILV5 overexpression strain had a negative effect, presumably by increasing the sensitivity of Ilv2 to valine inhibition, thus weakening the positive impact of overexpression of ILV2, ILV3, and ILV5 on isobutanol production. Aerobic cultivations of the ILV2 ILV3 ILV5 overexpression strain and the reference strain showed that supplying amino acids in cultivation media

  6. Effects of NADH-preferring xylose reductase expression on ethanol production from xylose in xylose-metabolizing recombinant Saccharomyces cerevisiae.

    Science.gov (United States)

    Lee, Sung-Haeng; Kodaki, Tsutomu; Park, Yong-Cheol; Seo, Jin-Ho

    2012-04-30

    Efficient conversion of xylose to ethanol is an essential factor for commercialization of lignocellulosic ethanol. To minimize production of xylitol, a major by-product in xylose metabolism and concomitantly improve ethanol production, Saccharomyces cerevisiae D452-2 was engineered to overexpress NADH-preferable xylose reductase mutant (XR(MUT)) and NAD⁺-dependent xylitol dehydrogenase (XDH) from Pichia stipitis and endogenous xylulokinase (XK). In vitro enzyme assay confirmed the functional expression of XR(MUT), XDH and XK in recombinant S. cerevisiae strains. The change of wild type XR to XR(MUT) along with XK overexpression led to reduction of xylitol accumulation in microaerobic culture. More modulation of the xylose metabolism including overexpression of XR(MUT) and transaldolase, and disruption of the chromosomal ALD6 gene encoding aldehyde dehydrogenase (SX6(MUT)) improved the performance of ethanol production from xylose remarkably. Finally, oxygen-limited fermentation of S. cerevisiae SX6(MUT) resulted in 0.64 g l⁻¹ h⁻¹ xylose consumption rate, 0.25 g l⁻¹ h⁻¹ ethanol productivity and 39% ethanol yield based on the xylose consumed, which were 1.8, 4.2 and 2.2 times higher than the corresponding values of recombinant S. cerevisiae expressing XR(MUT), XDH and XK only. Copyright © 2011 Elsevier B.V. All rights reserved.

  7. Use of pantothenate as a metabolic switch increases the genetic stability of farnesene producing Saccharomyces cerevisiae.

    Science.gov (United States)

    Sandoval, Celeste M; Ayson, Marites; Moss, Nathan; Lieu, Bonny; Jackson, Peter; Gaucher, Sara P; Horning, Tizita; Dahl, Robert H; Denery, Judith R; Abbott, Derek A; Meadows, Adam L

    2014-09-01

    We observed that removing pantothenate (vitamin B5), a precursor to co-enzyme A, from the growth medium of Saccharomyces cerevisiae engineered to produce β-farnesene reduced the strain׳s farnesene flux by 70%, but increased its viability, growth rate and biomass yield. Conversely, the growth rate and biomass yield of wild-type yeast were reduced. Cultivation in media lacking pantothenate eliminates the growth advantage of low-producing mutants, leading to improved production upon scale-up to lab-scale bioreactor testing. An omics investigation revealed that when exogenous pantothenate levels are limited, acyl-CoA metabolites decrease, β-oxidation decreases from unexpectedly high levels in the farnesene producer, and sterol and fatty acid synthesis likely limits the growth rate of the wild-type strain. Thus pantothenate supplementation can be utilized as a "metabolic switch" for tuning the synthesis rates of molecules relying on CoA intermediates and aid the economic scale-up of strains producing acyl-CoA derived molecules to manufacturing facilities. Copyright © 2014 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  8. Modeling Lactococcus lactis using a genome-scale flux model

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2005-06-01

    Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

  9. The rate of metabolism as a factor determining longevity of the Saccharomyces cerevisiae yeast.

    Science.gov (United States)

    Molon, Mateusz; Szajwaj, Monika; Tchorzewski, Marek; Skoczowski, Andrzej; Niewiadomska, Ewa; Zadrag-Tecza, Renata

    2016-02-01

    Despite many controversies, the yeast Saccharomyces cerevisiae continues to be used as a model organism for the study of aging. Numerous theories and hypotheses have been created for several decades, yet basic mechanisms of aging have remained unclear. Therefore, the principal aim of this work is to propose a possible mechanism leading to increased longevity in yeast. In this paper, we suggest for the first time that there is a link between decreased metabolic activity, fertility and longevity expressed as time of life in yeast. Determination of reproductive potential and total lifespan with the use of fob1Δ and sfp1Δ mutants allows us to compare the "longevity" presented as the number of produced daughters with the longevity expressed as the time of life. The results of analyses presented in this paper suggest the need for a change in the definition of longevity of yeast by taking into consideration the time parameter. The mutants that have been described as "long-lived" in the literature, such as the fob1Δ mutant, have an increased reproductive potential but live no longer than their standard counterparts. On the other hand, the sfp1Δ mutant and the wild-type strain produce a similar number of daughter cells, but the former lives much longer. Our results demonstrate a correlation between the decreased efficiency of the translational apparatus and the longevity of the sfp1Δ mutant. We suggest that a possible factor regulating the lifespan is the rate of cell metabolism. To measure the basic metabolism of the yeast cells, we used the isothermal microcalorimetry method. In the case of sfp1Δ, the flow of energy, ATP concentration, polysome profile and translational fitness are significantly lower in comparison with the wild-type strain and the fob1Δ mutant.

  10. Impact of xylose and mannose on central metabolism of yeast Saccharomyces cerevisiae

    Energy Technology Data Exchange (ETDEWEB)

    Pitkaenen, J.P.

    2005-07-01

    In this study, understanding of the central metabolism was improved by quantification of metabolite concentrations, enzyme activities, protein abundances, and gene transcript concentrations. Intracellular fluxes were estimated by applying stoichiometric models of metabolism. The methods were applied in the study of yeast Saccharomyces cerevisiae in two separate projects. A xylose project aimed at improved utilization of D- xylose as a substrate for, e.g., producing biomaterial- based fuel ethanol. A mannose project studied the production of GDP-mannose from D-mannose in a strain lacking the gene for phosphomannose isomerase (PMI40 deletion). Hexose, D-glucose is the only sugar more abundant than pentose D-xylose. D-xylose is common in hardwoods (e.g. birch) and crop residues (ca. 25% of dry weight). However, S. cerevisiae is unable to utilize D- xylose without a recombinant pathway where D-xylose is converted to Dxylulose. In this study D-xylose was converted in two steps via xylitol: by D-xylose reductase and xylitol dehydrogenase encoded by XYL1 and XYL2 from Pichia stipitis, respectively. Additionally, endogenous xylulokinase (XKS1) was overexpressed in order to increase the consumption of D-xylose by enhancing the phosphorylation of D-xylulose. Despite of the functional recombinant pathway the utilization rates of D xylose still remained low. This study proposes a set of limitations that are responsible for the low utilization rates of D-xylose under microaerobic conditions. Cells compensated for the cofactor imbalance, caused by the conversion of D-xylose to D- xylulose, by increasing the flux through the oxidative pentose phosphate pathway and by shuttling NADH redox potential to mitochondrion to be oxidized in oxidative phosphorylation. However, mitochondrial NADH inhibits citrate synthase in citric acid cycle, and consequently lower flux through citric acid cycle limits oxidative phosphorylation. Further, limitations in the uptake of D- xylose, in the

  11. Metabolic suppressors of trimethoprim and ultraviolet light sensitivities of Saccharomyces cerevisiae rad6 mutants

    International Nuclear Information System (INIS)

    Lawrence, C.W.; Christensen, R.B.

    1979-01-01

    Dominant mutations at two newly identified loci, designated SRS1 and SRS2, that metabolically suppress the trimethoprim sensitivity of rad6 and rad18 strains, have been isolated from trimethorprim-resistant mutants arising spontaneously in rad6-1 rad18-2 strains of the yeast Saccharomyces cerevisiae. The SRS2 mutations also efficiently suppress the ultraviolet light sensitivity of the parent strains. They do not, however, suppress their sensitivity to ionizing radiation or their deficiency with respect to induced mutagenesis and sporulation. Such observations support the hypothesis that RAD6-dependent activities can be separated into two functionally distinct groups: a group of error-free repair activities that are responsible for a large amount of the radiation resistance of wild-type strains and also for their resistance to trimethoprim, and a group of error-prone activities that are responsible for induced mutagenesis and are also important in sporulation, but which account at best for only a very small amount of wild-type recovery

  12. Efficient fermentation of xylose to ethanol at high formic acid concentrations by metabolically engineered Saccharomyces cerevisiae

    Energy Technology Data Exchange (ETDEWEB)

    Hasunuma, Tomohisa; Yoshimura, Kazuya; Matsuda, Fumio [Kobe Univ., Hyogo (Japan). Organization of Advanced Science and Technology; Sung, Kyung-mo; Sanda, Tomoya; Kondo, Akihiko [Kobe Univ., Hyogo (Japan). Dept. of Chemical Science and Engineering

    2011-05-15

    Recombinant yeast strains highly tolerant to formic acid during xylose fermentation were constructed. Microarray analysis of xylose-fermenting Saccharomyces cerevisiae strain overexpressing endogenous xylulokinase in addition to xylose reductase and xylitol dehydrogenase from Pichia stipitis revealed that upregulation of formate dehydrogenase genes (FDH1 and FDH2) was one of the most prominent transcriptional events against excess formic acid. The quantification of formic acid in medium indicated that the innate activity of FDH was too weak to detoxify formic acid. To reinforce the capability for formic acid breakdown, the FDH1 gene was additionally overexpressed in the xylose-metabolizing recombinant yeast. This modification allowed the yeast to rapidly decompose excess formic acid. The yield and final ethanol concentration in the presence of 20 mM formic acid is as essentially same as that of control. The fermentation profile also indicated that the production of xylitol and glycerol, major by-products in xylose fermentation, was not affected by the upregulation of FDH activity. (orig.)

  13. BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

    DEFF Research Database (Denmark)

    King, Zachary A.; Lu, Justin; Dräger, Andreas

    2016-01-01

    Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

  14. Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Trey K Sato

    2016-10-01

    Full Text Available The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3, a component of MAP Kinase (MAPK signaling (HOG1, a regulator of Protein Kinase A (PKA signaling (IRA2, and a scaffolding protein for mitochondrial iron-sulfur (Fe-S cluster biogenesis (ISU1. Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

  15. Directed Evolution Reveals Unexpected Epistatic Interactions That Alter Metabolic Regulation and Enable Anaerobic Xylose Use by Saccharomyces cerevisiae.

    Science.gov (United States)

    Sato, Trey K; Tremaine, Mary; Parreiras, Lucas S; Hebert, Alexander S; Myers, Kevin S; Higbee, Alan J; Sardi, Maria; McIlwain, Sean J; Ong, Irene M; Breuer, Rebecca J; Avanasi Narasimhan, Ragothaman; McGee, Mick A; Dickinson, Quinn; La Reau, Alex; Xie, Dan; Tian, Mingyuan; Reed, Jennifer L; Zhang, Yaoping; Coon, Joshua J; Hittinger, Chris Todd; Gasch, Audrey P; Landick, Robert

    2016-10-01

    The inability of native Saccharomyces cerevisiae to convert xylose from plant biomass into biofuels remains a major challenge for the production of renewable bioenergy. Despite extensive knowledge of the regulatory networks controlling carbon metabolism in yeast, little is known about how to reprogram S. cerevisiae to ferment xylose at rates comparable to glucose. Here we combined genome sequencing, proteomic profiling, and metabolomic analyses to identify and characterize the responsible mutations in a series of evolved strains capable of metabolizing xylose aerobically or anaerobically. We report that rapid xylose conversion by engineered and evolved S. cerevisiae strains depends upon epistatic interactions among genes encoding a xylose reductase (GRE3), a component of MAP Kinase (MAPK) signaling (HOG1), a regulator of Protein Kinase A (PKA) signaling (IRA2), and a scaffolding protein for mitochondrial iron-sulfur (Fe-S) cluster biogenesis (ISU1). Interestingly, the mutation in IRA2 only impacted anaerobic xylose consumption and required the loss of ISU1 function, indicating a previously unknown connection between PKA signaling, Fe-S cluster biogenesis, and anaerobiosis. Proteomic and metabolomic comparisons revealed that the xylose-metabolizing mutant strains exhibit altered metabolic pathways relative to the parental strain when grown in xylose. Further analyses revealed that interacting mutations in HOG1 and ISU1 unexpectedly elevated mitochondrial respiratory proteins and enabled rapid aerobic respiration of xylose and other non-fermentable carbon substrates. Our findings suggest a surprising connection between Fe-S cluster biogenesis and signaling that facilitates aerobic respiration and anaerobic fermentation of xylose, underscoring how much remains unknown about the eukaryotic signaling systems that regulate carbon metabolism.

  16. Metabolic Engineering of Saccharomyces cerevisiae Microbial Cell Factories for Succinic Acid Production

    DEFF Research Database (Denmark)

    Otero, José Manuel; Nielsen, Jens; Olsson, Lisbeth

    2007-01-01

    anhydride. There are several biomass platforms, all prokaryotic, for succinic acid production; however, overproduction of succinic acid in S. cerevisiae offers distinct process advantages. For example, S. cerevisiae has been awarded GRAS status for use in human consumables, grows well at low p......H significantly minimizing purification and acidification costs associated with organic acid production, and can utilize diverse carbon substrates in chemically defined medium. S. cerevisiae offers the unique advantage of being the most well characterized eukaryotic expression system. Here we describe the use...

  17. Metabolic efficiency in yeast Saccharomyces cerevisiae in relation to temperature dependent growth and biomass yield.

    Science.gov (United States)

    Zakhartsev, Maksim; Yang, Xuelian; Reuss, Matthias; Pörtner, Hans Otto

    2015-08-01

    Canonized view on temperature effects on growth rate of microorganisms is based on assumption of protein denaturation, which is not confirmed experimentally so far. We develop an alternative concept, which is based on view that limits of thermal tolerance are based on imbalance of cellular energy allocation. Therefore, we investigated growth suppression of yeast Saccharomyces cerevisiae in the supraoptimal temperature range (30-40°C), i.e. above optimal temperature (Topt). The maximal specific growth rate (μmax) of biomass, its concentration and yield on glucose (Yx/glc) were measured across the whole thermal window (5-40°C) of the yeast in batch anaerobic growth on glucose. Specific rate of glucose consumption, specific rate of glucose consumption for maintenance (mglc), true biomass yield on glucose (Yx/glc(true)), fractional conservation of substrate carbon in product and ATP yield on glucose (Yatp/glc) were estimated from the experimental data. There was a negative linear relationship between ATP, ADP and AMP concentrations and specific growth rate at any growth conditions, whilst the energy charge was always high (~0.83). There were two temperature regions where mglc differed 12-fold, which points to the existence of a 'low' (within 5-31°C) and a 'high' (within 33-40°C) metabolic mode regarding maintenance requirements. The rise from the low to high mode occurred at 31-32°C in step-wise manner and it was accompanied with onset of suppression of μmax. High mglc at supraoptimal temperatures indicates a significant reduction of scope for growth, due to high maintenance cost. Analysis of temperature dependencies of product formation efficiency and Yatp/glc revealed that the efficiency of energy metabolism approaches its lower limit at 26-31°C. This limit is reflected in the predetermined combination of Yx/glc(true), elemental biomass composition and degree of reduction of the growth substrate. Approaching the limit implies a reduction of the safety margin

  18. Functional analysis of the global repressor Tup1 for maltose metabolism in Saccharomyces cerevisiae: different roles of the functional domains.

    Science.gov (United States)

    Lin, Xue; Yu, Ai-Qun; Zhang, Cui-Ying; Pi, Li; Bai, Xiao-Wen; Xiao, Dong-Guang

    2017-11-09

    Tup1 is a general transcriptional repressor of diverse gene families coordinately controlled by glucose repression, mating type, and other mechanisms in Saccharomyces cerevisiae. Several functional domains of Tup1 have been identified, each of which has differing effects on transcriptional repression. In this study, we aim to investigate the role of Tup1 and its domains in maltose metabolism of industrial baker's yeast. To this end, a battery of in-frame truncations in the TUP1 gene coding region were performed in the industrial baker's yeasts with different genetic background, and the maltose metabolism, leavening ability, MAL gene expression levels, and growth characteristics were investigated. The results suggest that the TUP1 gene is essential to maltose metabolism in industrial baker's yeast. Importantly, different domains of Tup1 play different roles in glucose repression and maltose metabolism of industrial baker's yeast cells. The Ssn6 interaction, N-terminal repression and C-terminal repression domains might play roles in the regulation of MAL transcription by Tup1 for maltose metabolism of baker's yeast. The WD region lacking the first repeat could influence the regulation of maltose metabolism directly, rather than indirectly through glucose repression. These findings lay a foundation for the optimization of industrial baker's yeast strains for accelerated maltose metabolism and facilitate future research on glucose repression in other sugar metabolism.

  19. Genome-scale neurogenetics: methodology and meaning.

    Science.gov (United States)

    McCarroll, Steven A; Feng, Guoping; Hyman, Steven E

    2014-06-01

    Genetic analysis is currently offering glimpses into molecular mechanisms underlying such neuropsychiatric disorders as schizophrenia, bipolar disorder and autism. After years of frustration, success in identifying disease-associated DNA sequence variation has followed from new genomic technologies, new genome data resources, and global collaborations that could achieve the scale necessary to find the genes underlying highly polygenic disorders. Here we describe early results from genome-scale studies of large numbers of subjects and the emerging significance of these results for neurobiology.

  20. Analysis of metabolisms and transports of xylitol using xylose- and xylitol-assimilating Saccharomyces cerevisiae.

    Science.gov (United States)

    Tani, Tatsunori; Taguchi, Hisataka; Akamatsu, Takashi

    2017-05-01

    To clarify the relationship between NAD(P) + /NAD(P)H redox balances and the metabolisms of xylose or xylitol as carbon sources, we analyzed aerobic and anaerobic batch cultures of recombinant Saccharomyces cerevisiae in a complex medium containing 20 g/L xylose or 20 g/L xylitol at pH 5.0 and 30°C. The TDH3p-GAL2 or gal80Δ strain completely consumed the xylose within 24 h and aerobically consumed 92-100% of the xylitol within 96 h, but anaerobically consumed only 20% of the xylitol within 96 h. Cells of both strains grew well in aerobic culture. The addition of acetaldehyde (an effective oxidizer of NADH) increased the xylitol consumption by the anaerobically cultured strain. These results indicate that in anaerobic culture, NAD + generated in the NAD(P)H-dependent xylose reductase reaction was likely needed in the NAD + -dependent xylitol dehydrogenase reaction, whereas in aerobic culture, the NAD + generated by oxidation of NADH in the mitochondria is required in the xylitol dehydrogenase reaction. The role of Gal2 and Fps1 in importing xylitol into the cytosol and exporting it from the cells was analyzed by examining the xylitol consumption in aerobic culture and the export of xylitol metabolized from xylose in anaerobic culture, respectively. The xylitol consumptions of gal80Δ gal2Δ and gal80Δ gal2Δ fps1Δ strains were reduced by 81% and 88% respectively, relative to the gal80Δ strain. The maximum xylitol concentration accumulated by the gal80Δ, gal80Δ gal2Δ, and gal80Δ gal2Δ fps1Δ strains was 7.25 g/L, 5.30 g/L, and 4.27 g/L respectively, indicating that Gal2 and Fps1 transport xylitol both inward and outward. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  1. Transcription activator-like effector nucleases mediated metabolic engineering for enhanced fatty acids production in Saccharomyces cerevisiae

    KAUST Repository

    Aouida, Mustapha; Li, Lixin; Mahjoub, Ali; Alshareef, Sahar; Ali, Zahir; Piatek, Agnieszka Anna; Mahfouz, Magdy M.

    2015-01-01

    Targeted engineering of microbial genomes holds much promise for diverse biotechnological applications. Transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats/Cas9 systems are capable of efficiently editing microbial genomes, including that of Saccharomyces cerevisiae. Here, we demonstrate the use of TALENs to edit the genome of S.cerevisiae with the aim of inducing the overproduction of fatty acids. Heterodimeric TALENs were designed to simultaneously edit the FAA1 and FAA4 genes encoding acyl-CoA synthetases in S.cerevisiae. Functional yeast double knockouts generated using these TALENs over-produce large amounts of free fatty acids into the cell. This study demonstrates the use of TALENs for targeted engineering of yeast and demonstrates that this technology can be used to stimulate the enhanced production of free fatty acids, which are potential substrates for biofuel production. This proof-of-principle study extends the utility of TALENs as excellent genome editing tools and highlights their potential use for metabolic engineering of yeast and other organisms, such as microalgae and plants, for biofuel production. © 2015 The Society for Biotechnology, Japan.

  2. Transcription activator-like effector nucleases mediated metabolic engineering for enhanced fatty acids production in Saccharomyces cerevisiae

    KAUST Repository

    Aouida, Mustapha

    2015-04-01

    Targeted engineering of microbial genomes holds much promise for diverse biotechnological applications. Transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats/Cas9 systems are capable of efficiently editing microbial genomes, including that of Saccharomyces cerevisiae. Here, we demonstrate the use of TALENs to edit the genome of S.cerevisiae with the aim of inducing the overproduction of fatty acids. Heterodimeric TALENs were designed to simultaneously edit the FAA1 and FAA4 genes encoding acyl-CoA synthetases in S.cerevisiae. Functional yeast double knockouts generated using these TALENs over-produce large amounts of free fatty acids into the cell. This study demonstrates the use of TALENs for targeted engineering of yeast and demonstrates that this technology can be used to stimulate the enhanced production of free fatty acids, which are potential substrates for biofuel production. This proof-of-principle study extends the utility of TALENs as excellent genome editing tools and highlights their potential use for metabolic engineering of yeast and other organisms, such as microalgae and plants, for biofuel production. © 2015 The Society for Biotechnology, Japan.

  3. Improvement of ethanol yield from glycerol via conversion of pyruvate to ethanol in metabolically engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Yu, Kyung Ok; Jung, Ju; Ramzi, Ahmad Bazli; Kim, Seung Wook; Park, Chulhwan; Han, Sung Ok

    2012-02-01

    The conversion of low-priced glycerol to higher value products has been proposed as a way to improve the economic viability of the biofuels industry. In a previous study, the conversion of glycerol to ethanol in a metabolically engineered strain of Saccharomyces cerevisiae was accomplished by minimizing the synthesis of glycerol, the main by-product in ethanol fermentation processing. To further improve ethanol production, overexpression of the native genes involved in conversion of pyruvate to ethanol in S. cerevisiae was successfully accomplished. The overexpression of an alcohol dehydrogenase (adh1) and a pyruvate decarboxylase (pdc1) caused an increase in growth rate and glycerol consumption under fermentative conditions, which led to a slight increase of the final ethanol yield. The overall expression of the adh1 and pdc1 genes in the modified strains, combined with the lack of the fps1 and gpd2 genes, resulted in a 1.4-fold increase (about 5.4 g/L ethanol produced) in fps1Δgpd2Δ (pGcyaDak, pGupCas) (about 4.0 g/L ethanol produced). In summary, it is possible to improve the ethanol yield by overexpression of the genes involved in the conversion of pyruvate to ethanol in engineered S. cerevisiae using glycerol as substrate.

  4. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  5. Niche-driven evolution of metabolic and life-history strategies in natural and domesticated populations of Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Sicard Delphine

    2009-12-01

    Full Text Available Abstract Background Variation of resource supply is one of the key factors that drive the evolution of life-history strategies, and hence the interactions between individuals. In the yeast Saccharomyces cerevisiae, two life-history strategies related to different resource utilization have been previously described in strains from different industrial origins. In this work, we analyzed metabolic traits and life-history strategies in a broader collection of yeast strains sampled in various ecological niches (forest, human body, fruits, laboratory and industrial environments. Results By analysing the genetic and plastic variation of six life-history and three metabolic traits, we showed that S. cerevisiae populations harbour different strategies depending on their ecological niches. On one hand, the forest and laboratory strains, referred to as extreme "ants", reproduce quickly, reach a large carrying capacity and a small cell size in fermentation, but have a low reproduction rate in respiration. On the other hand, the industrial strains, referred to as extreme "grasshoppers", reproduce slowly, reach a small carrying capacity but have a big cell size in fermentation and a high reproduction rate in respiration. "Grasshoppers" have usually higher glucose consumption rate than "ants", while they produce lower quantities of ethanol, suggesting that they store cell resources rather than secreting secondary products to cross-feed or poison competitors. The clinical and fruit strains are intermediate between these two groups. Conclusions Altogether, these results are consistent with a niche-driven evolution of S. cerevisiae, with phenotypic convergence of populations living in similar habitat. They also revealed that competition between strains having contrasted life-history strategies ("ants" and "grasshoppers" seems to occur at low frequency or be unstable since opposite life-history strategies appeared to be maintained in distinct ecological niches.

  6. Overexpression of a water-forming NADH oxidase improves the metabolism and stress tolerance of Saccharmyces cerevisiae in aerobic fermenation

    Directory of Open Access Journals (Sweden)

    Xinchi Shi

    2016-09-01

    Full Text Available Redox homeostasis is fundamental to the maintenance of metabolism. Redox imbalance can cause oxidative stress, which affects metabolism and growth. Water-forming NADH oxidase regulates the redox balance by oxidizing cytosolic NADH to NAD+, which relieves cytosolic NADH accumulation through rapid glucose consumption in Saccharomyces cerevisiae, thus decreasing the production of the byproduct glycerol in industrial ethanol production. Here, we studied the effects of overexpression of a water-forming NADH oxidase from Lactococcus lactis on the stress response of S. cerevisiae in aerobic batch fermentation, and we constructed an interaction network of transcriptional regulation and metabolic networks to study the effects of and mechanisms underlying NADH oxidase regulation. The oxidase-overexpressing strain (NOX showed increased glucose consumption, growth, and ethanol production, while glycerol production was remarkably lower. Glucose was exhausted by NOX at 26 h, while 18.92 ± 0.94 g/L residual glucose was left in the fermentation broth of the control strain (CON at this time point. At 29.5 h, the ethanol concentration for NOX peaked at 35.25 ± 1.76 g/L, which was 14.37 % higher than that for CON (30.82 ± 1.54 g/L. Gene expression involved in the synthesis of thiamine, which is associated with stress responses in various organisms, was increased in NOX. The transcription factor HAP4 was significantly upregulated in NOX at the late-exponential phase, indicating a diauxic shift in response to starvation. The apoptosis-inducing factor Nuc1 was downregulated while the transcription factor Sok2, which regulates the production of the small signaling molecule ammonia, was upregulated at the late-exponential phase, benefiting young cells on the rim. Reactive oxygen species production was decreased by 10% in NOX, supporting a decrease in apoptosis. The HOG pathway was not activated, although the osmotic stress was truly higher, indicating improved

  7. Promiscuous activities of heterologous enzymes lead to unintended metabolic rerouting in Saccharomyces cerevisiae engineered to assimilate various sugars from renewable biomass.

    Science.gov (United States)

    Yun, Eun Ju; Oh, Eun Joong; Liu, Jing-Jing; Yu, Sora; Kim, Dong Hyun; Kwak, Suryang; Kim, Kyoung Heon; Jin, Yong-Su

    2018-01-01

    Understanding the global metabolic network, significantly perturbed upon promiscuous activities of foreign enzymes and different carbon sources, is crucial for systematic optimization of metabolic engineering of yeast Saccharomyces cerevisiae . Here, we studied the effects of promiscuous activities of overexpressed enzymes encoded by foreign genes on rerouting of metabolic fluxes of an engineered yeast capable of assimilating sugars from renewable biomass by profiling intracellular and extracellular metabolites. Unbiased metabolite profiling of the engineered S. cerevisiae strain EJ4 revealed promiscuous enzymatic activities of xylose reductase and xylitol dehydrogenase on galactose and galactitol, respectively, resulting in accumulation of galactitol and tagatose during galactose fermentation. Moreover, during glucose fermentation, a trisaccharide consisting of glucose accumulated outside of the cells probably owing to the promiscuous and transglycosylation activity of β-glucosidase expressed for hydrolyzing cellobiose. Meanwhile, higher accumulation of fatty acids and secondary metabolites was observed during xylose and cellobiose fermentations, respectively. The heterologous enzymes functionally expressed in S. cerevisiae showed promiscuous activities that led to unintended metabolic rerouting in strain EJ4. Such metabolic rerouting could result in a low yield and productivity of a final product due to the formation of unexpected metabolites. Furthermore, the global metabolic network can be significantly regulated by carbon sources, thus yielding different patterns of metabolite production. This metabolomic study can provide useful information for yeast strain improvement and systematic optimization of yeast metabolism to manufacture bio-based products.

  8. Metabolic engineering of Saccharomyces cerevisiae ethanol strains PE-2 and CAT-1 for efficient lignocellulosic fermentation.

    Science.gov (United States)

    Romaní, Aloia; Pereira, Filipa; Johansson, Björn; Domingues, Lucília

    2015-03-01

    In this work, Saccharomyces cerevisiae strains PE-2 and CAT-1, commonly used in the Brazilian fuel ethanol industry, were engineered for xylose fermentation, where the first fermented xylose faster than the latter, but also produced considerable amounts of xylitol. An engineered PE-2 strain (MEC1121) efficiently consumed xylose in presence of inhibitors both in synthetic and corn-cob hydrolysates. Interestingly, the S. cerevisiae MEC1121 consumed xylose and glucose simultaneously, while a CEN.PK based strain consumed glucose and xylose sequentially. Deletion of the aldose reductase GRE3 lowered xylitol production to undetectable levels and increased xylose consumption rate which led to higher final ethanol concentrations. Fermentation of corn-cob hydrolysate using this strain, MEC1133, resulted in an ethanol yield of 0.47 g/g of total sugars which is 92% of the theoretical yield. Copyright © 2014 Elsevier Ltd. All rights reserved.

  9. Dynamic optimal control of homeostasis: an integrative system approach for modeling of the central nitrogen metabolism in Saccharomyces cerevisiae.

    Science.gov (United States)

    van Riel, N A; Giuseppin, M L; Verrips, C T

    2000-01-01

    The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the source of the cellular amino acids and proteins, including flavors and potentially valuable biomolecules; therefore, it is also of industrial interest. In the DOMC approach the cell is regarded as an optimally controlled system. Given the metabolic genotype, the cell faces a control problem to maintain an optimal flux distribution in a changing environment. The regulation is based on strategies and balances feedback control of homeostasis and feedforward regulation for adaptation. The DOMC approach is an integrative, holistic approach, not based on mechanistic descriptions and (therefore) not biased by the variation present in biochemical and molecular biological data. It is an effective tool to structure the rapidly increasing amount of data on the function of genes and pathways. The DOMC model is used successfully to predict the responses of pulses of ammonia and glutamine to nitrogen-limited continuous cultures of a wild-type strain and a glutamine synthetase-negative mutant. The simulation results are validated with experimental data.

  10. Metabolic engineering of Saccharomyces cerevisiae for the production of n-butanol

    Energy Technology Data Exchange (ETDEWEB)

    Steen, EricJ.; Chan, Rossana; Prasad, Nilu; Myers, Samuel; Petzold, Christopher; Redding, Alyssa; Ouellet, Mario; Keasling, JayD.

    2008-11-25

    BackgroundIncreasing energy costs and environmental concerns have motivated engineering microbes for the production of ?second generation? biofuels that have better properties than ethanol.Results& ConclusionsSaccharomyces cerevisiae was engineered with an n-butanol biosynthetic pathway, in which isozymes from a number of different organisms (S. cerevisiae, Escherichia coli, Clostridium beijerinckii, and Ralstonia eutropha) were substituted for the Clostridial enzymes and their effect on n-butanol production was compared. By choosing the appropriate isozymes, we were able to improve production of n-butanol ten-fold to 2.5 mg/L. The most productive strains harbored the C. beijerinckii 3-hydroxybutyryl-CoA dehydrogenase, which uses NADH as a co-factor, rather than the R. eutropha isozyme, which uses NADPH, and the acetoacetyl-CoA transferase from S. cerevisiae or E. coli rather than that from R. eutropha. Surprisingly, expression of the genes encoding the butyryl-CoA dehydrogenase from C. beijerinckii (bcd and etfAB) did not improve butanol production significantly as previously reported in E. coli. Using metabolite analysis, we were able to determine which steps in the n-butanol biosynthetic pathway were the most problematic and ripe for future improvement.

  11. Role of glutathione metabolism status in the definition of some cellular parameters and oxidative stress tolerance of Saccharomyces cerevisiae cells growing as biofilms.

    Science.gov (United States)

    Gales, Grégoire; Penninckx, Michel; Block, Jean-Claude; Leroy, Pierre

    2008-08-01

    The resistance of Saccharomyces cerevisiae to oxidative stress (H(2)O(2) and Cd(2+)) was compared in biofilms and planktonic cells, with the help of yeast mutants deleted of genes related to glutathione metabolism and oxidative stress. Biofilm-forming cells were found predominantly in the G1 stage of the cell cycle. This might explain their higher tolerance to oxidative stress and the young replicative age of these cells in an old culture. The reduced glutathione status of S. cerevisiae was affected by the growth phase and apparently plays an important role in oxidative stress tolerance in cells growing as a biofilm.

  12. Genome-scale modeling of yeast: chronology, applications and critical perspectives.

    Science.gov (United States)

    Lopes, Helder; Rocha, Isabel

    2017-08-01

    Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.

  13. Reconstruction of metabolic module with improved promoter strength increases the productivity of 2-phenylethanol in Saccharomyces cerevisiae.

    Science.gov (United States)

    Wang, Zhaoyue; Jiang, Mingyue; Guo, Xuena; Liu, Zhaozheng; He, Xiuping

    2018-04-11

    2-phenylethanol (2-PE) is an important aromatic compound with a lovely rose-like scent. Saccharomyces cerevisiae is a desirable microbe for 2-PE production but its natural yield is not high, and one or two crucial genes' over-expression in S. cerevisiae did not improve 2-PE greatly. A new metabolic module was established here, in which, permease Gap1p for L-phenylalanine transportation, catalytic enzymes Aro8p, Aro10p and Adh2p in Ehrlich pathway respectively responsible for transamination, decarboxylation and reduction were assembled, besides, glutamate dehydrogenase Gdh2p was harbored for re-supplying another substrate 2-oxoglutarate, relieving product glutamate repression and regenerating cofactor NADH. Due to different promoter strengths, GAP1, ARO8, ARO9, ARO10, ADH2 and GDH2 in the new modularized YS58(G1-A8-A10-A2)-GDH strain enhanced 11.6-, 15.4-, 3.6-, 17.7-, 12.4- and 7.5-folds respectively, and crucial enzyme activities of aromatic aminotransferases and phenylpyruvate decarboxylase were 4.8- and 7-folds respectively higher than that of the control. Under the optimum medium and cell density, YS58(G1-A8-A10-A2)-GDH presented efficient 2-PE synthesis ability with ~ 6.3 g L -1 of 2-PE titer in 5-L fermenter reaching 95% of conversation ratio. Under fed-batch fermentation, 2-PE productivity at 24 h increased 29% than that of single-batch fermentation. Metabolic modularization with promoter strategy provides a new prospective for efficient 2-PE production.

  14. Tight Coupling of Metabolic Oscillations and Intracellular Water Dynamics in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Thoke, Henrik Seir; Tobiesen, Asger; Brewer, Jonathan R.

    2015-01-01

    We detected very strong coupling between the oscillating concentration of ATP and the dynamics of intracellular water during glycolysis in Saccharomyces cerevisiae. Our results indicate that: i) dipolar relaxation of intracellular water is heterogeneous within the cell and different from dilute...... conditions, ii) water dipolar relaxation oscillates with glycolysis and in phase with ATP concentration, iii) this phenomenon is scale-invariant from the subcellular to the ensemble of synchronized cells and, iv) the periodicity of both glycolytic oscillations and dipolar relaxation are equally affected by D...

  15. Multiplex metabolic pathway engineering using CRISPR/Cas9 in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Jakociunas, Tadas; Bonde, Ida; Herrgard, Markus

    2015-01-01

    CRISPR/Cas9 is a simple and efficient tool for targeted and marker-free genome engineering. Here, we report the development and successful application of a multiplex CRISPR/Cas9 system for genome engineering of up to 5 different genomic loci in one transformation step in baker's yeast Saccharomyces...... cerevisiae. To assess the specificity of the tool we employed genome re-sequencing to screen for off-target sites in all single knock-out strains targeted by different gRNAs. This extensive analysis identified no more genome variants in CRISPR/Cas9 engineered strains compared to wild-type reference strains...

  16. Increased isobutanol production in Saccharomyces cerevisiae by overexpression of genes in valine metabolism

    DEFF Research Database (Denmark)

    Chen, Xiao; Nielsen, Kristian Fog; Borodina, Irina

    2011-01-01

    BACKGROUND: Isobutanol can be a better biofuel than ethanol due to its higher energy density and lower hygroscopicity. Furthermore, the branched-chain structure of isobutanol gives a higher octane number than the isomeric n-butanol. Saccharomyces cerevisiae was chosen as the production host because...... of its relative tolerance to alcohols, robustness in industrial fermentations, and the possibility for future combination of isobutanol production with fermentation of lignocellulosic materials. RESULTS: The yield of isobutanol was improved from 0.16 to 0.97 mg per g glucose by simultaneous...

  17. Effects of cell entrapment in Ca-alginate on the metabolism of yeast Saccharomyces cerevisiae

    International Nuclear Information System (INIS)

    Galazzo, J.L.

    1989-01-01

    Saccharomyces cerevisiae cells grown in suspension have been immobilized in calcium-alginate beads. Fermentation rates and intracellular composition have been determined under nongrowing conditions in these Ca-alginate entrapped cells and for identical cells in suspension. Glucose uptake and ethanol and glycerol production are approximately two times faster in immobilized cells than in suspended cells. Intermediate metabolite levels such as fructose-1,6-diphosphate, glucose-6-phosphate and 3-phosphoglycerate have been determined by phosphorus-31 nuclear magnetic resonance (NMR) spectroscopy under glucose fermenting conditions. Carbon-13 NMR shows an increase in polysaccharide production in immobilized cells. S. cerevisiae cells grown within a Ca-alginate matrix have a specific growth rate 40% lower than the growth rate of similar cells cultivated in suspension. Alginate-grown cells have been used to compare glucose fermentation under nongrowing conditions in suspended and Ca-entrapped cells. Fermentation rate is higher in immobilized cells than in suspended cells. The observed differences in intracellular components between suspended and immobilized cells are qualitatively similar to the differences observed for cells grown in suspension. Ethanol production rate is 2.7 times faster in immobilized alginate-grown cells than in suspended suspension-grown cells

  18. Metabolic engineering applications of in vivo 31P and 13C NMR studies of Saccharomyces cerevisiae

    International Nuclear Information System (INIS)

    Shanks, J.V.

    1989-01-01

    With intent to quantify NMR measurements as much as possible, analysis techniques of the in vivo 31 P NMR spectrum are developed. A systematic procedure is formulated for estimating the relative intracellular concentrations of the sugar phosphates in S. cerevisiae from the 31 P NMR spectrum. In addition, in vivo correlation of inorganic phosphate chemical shift with the chemical shifts of 3-phosphoglycerate, β-fructose 1,6-diphosphate, fructose 6-phosphate, and glucose 6-phosphate are determined. Also, a method was developed for elucidation of the cytoplasmic and vacuolar components of inorganic phosphate in the 31 P NMR spectrum of S. cerevisiae. An in vivo correlation relating the inorganic phosphate chemical shift of the vacuole with the chemical shift of the resonance for pyrophosphate and the terminal phosphate of polyphosphate (PP 1 ) is established. Transient measurements provided by 31 P NMR are applied to reg1 mutant and standard strains. 31 P and 13 C NMR measurements are used to analyze the performance of recombinant strains in which the glucose phosphorylation step had been altered

  19. Metabolic engineering for high glycerol production by the anaerobic cultures of Saccharomyces cerevisiae.

    Science.gov (United States)

    Semkiv, Marta V; Dmytruk, Kostyantyn V; Abbas, Charles A; Sibirny, Andriy A

    2017-06-01

    Glycerol is used by the cosmetic, paint, automotive, food, and pharmaceutical industries and for production of explosives. Currently, glycerol is available in commercial quantities as a by-product from biodiesel production, but the purity and the cost of its purification are prohibitive. The industrial production of glycerol by glucose aerobic fermentation using osmotolerant strains of the yeasts Candida sp. and Saccharomyces cerevisiae has been described. A major drawback of the aerobic process is the high cost of production. For this reason, the development of yeast strains that effectively convert glucose to glycerol anaerobically is of great importance. Due to its ability to grow under anaerobic conditions, the yeast S. cerevisiae is an ideal system for the development of this new biotechnological platform. To increase glycerol production and accumulation from glucose, we lowered the expression of TPI1 gene coding for triose phosphate isomerase; overexpressed the fused gene consisting the GPD1 and GPP2 parts coding for glycerol-3-phosphate dehydrogenase and glycerol-3-phosphate phosphatase, respectively; overexpressed the engineered FPS1 gene that codes for aquaglyceroporin; and overexpressed the truncated gene ILV2 that codes for acetolactate synthase. The best constructed strain produced more than 20 g of glycerol/L from glucose under micro-aerobic conditions and 16 g of glycerol/L under anaerobic conditions. The increase in glycerol production led to a drop in ethanol and biomass accumulation.

  20. Metabolic response to MMS-mediated DNA damage in Saccharomyces cerevisiae is dependent on the glucose concentration in the medium.

    Science.gov (United States)

    Kitanovic, Ana; Walther, Thomas; Loret, Marie Odile; Holzwarth, Jinda; Kitanovic, Igor; Bonowski, Felix; Van Bui, Ngoc; Francois, Jean Marie; Wölfl, Stefan

    2009-06-01

    Maintenance and adaptation of energy metabolism could play an important role in the cellular ability to respond to DNA damage. A large number of studies suggest that the sensitivity of cells to oxidants and oxidative stress depends on the activity of cellular metabolism and is dependent on the glucose concentration. In fact, yeast cells that utilize fermentative carbon sources and hence rely mainly on glycolysis for energy appear to be more sensitive to oxidative stress. Here we show that treatment of the yeast Saccharomyces cerevisiae growing on a glucose-rich medium with the DNA alkylating agent methyl methanesulphonate (MMS) triggers a rapid inhibition of respiration and enhances reactive oxygen species (ROS) production, which is accompanied by a strong suppression of glycolysis. Further, diminished activity of pyruvate kinase and glyceraldehyde-3-phosphate dehydrogenase upon MMS treatment leads to a diversion of glucose carbon to glycerol, trehalose and glycogen accumulation and an increased flux through the pentose-phosphate pathway. Such conditions finally result in a significant decline in the ATP level and energy charge. These effects are dependent on the glucose concentration in the medium. Our results clearly demonstrate that calorie restriction reduces MMS toxicity through increased respiration and reduced ROS accumulation, enhancing the survival and recovery of cells.

  1. Effects of Long-Term Cultivation on Medium with Alpha-Ketoglutarate Supplementation on Metabolic Processes of Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Nadia Burdyliuk

    2017-01-01

    Full Text Available During last years, alpha-ketoglutarate (AKG, an important intermediate in the Krebs cycle, has been intensively studied as a dietary supplement with stress-protective and potential antiaging effects. Here, we examined the effects of exogenous AKG on metabolic processes and survival of yeast Saccharomyces cerevisiae during long-term cultivation. Growth on AKG had no effect on the total cell number but increased the number of reproductively active cells at the late days of cultivation (from day 7 to day 15. A gradual increase in levels of total protein, glycogen, and trehalose was found over 7-day cultivation with more pronounced effects in AKG-grown cells. In control cells, metabolic activity and the activities of superoxide dismutase and catalase decreased, whereas levels of carbonyl proteins and low-molecular-mass thiols increased during 7-day cultivation. This suggests development of oxidative stress in stationary phase cells. Meanwhile, stationary phase cells cultured on AKG possessed higher levels of low-molecular-mass thiols and lower levels of carbonyl proteins and α-dicarbonyl compounds when compared to control ones. Collectively, higher levels of storage carbohydrates and an activation of antioxidant defense with diminishing oxidative protein damage can prevent a loss of reproductive ability in yeast cells during long-term cultivation on AKG-supplemented medium.

  2. The interplay between sulphur and selenium metabolism influences the intracellular redox balance in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Mapelli, Valeria; Hillestrøm, Peter René; Patil, Kalpesh

    2012-01-01

    oxidative stress response is active when yeast actively metabolizes Se, and this response is linked to the generation of intracellular redox imbalance. The redox imbalance derives from a disproportionate ratio between the reduced and oxidized forms of glutathione and also from the influence of Se metabolism...

  3. Supplementation of Saccharomyces cerevisiae modulates the metabolic response to lipopolysaccharide challenge in feedlot steers

    Science.gov (United States)

    Live yeast has the potential to serve as an alternative to the use of low-dose supplementation of antibiotics in cattle due to the ability to alter ruminant metabolism; which in turn may influence the immune response. Therefore, the objective of this study was to determine the metabolic response to ...

  4. In Vivo Analysis of NH4+ Transport and Central Nitrogen Metabolism in Saccharomyces cerevisiae during Aerobic Nitrogen-Limited Growth

    Science.gov (United States)

    Maleki Seifar, R.; ten Pierick, A.; van Helmond, W.; Pieterse, M. M.; Heijnen, J. J.

    2016-01-01

    ABSTRACT Ammonium is the most common N source for yeast fermentations. Although its transport and assimilation mechanisms are well documented, there have been only a few attempts to measure the in vivo intracellular concentration of ammonium and assess its impact on gene expression. Using an isotope dilution mass spectrometry (IDMS)-based method, we were able to measure the intracellular ammonium concentration in N-limited aerobic chemostat cultivations using three different N sources (ammonium, urea, and glutamate) at the same growth rate (0.05 h−1). The experimental results suggest that, at this growth rate, a similar concentration of intracellular (IC) ammonium, about 3.6 mmol NH4+/literIC, is required to supply the reactions in the central N metabolism, independent of the N source. Based on the experimental results and different assumptions, the vacuolar and cytosolic ammonium concentrations were estimated. Furthermore, we identified a futile cycle caused by NH3 leakage into the extracellular space, which can cost up to 30% of the ATP production of the cell under N-limited conditions, and a futile redox cycle between Gdh1 and Gdh2 reactions. Finally, using shotgun proteomics with protein expression determined relative to a labeled reference, differences between the various environmental conditions were identified and correlated with previously identified N compound-sensing mechanisms. IMPORTANCE In our work, we studied central N metabolism using quantitative approaches. First, intracellular ammonium was measured under different N sources. The results suggest that Saccharomyces cerevisiae cells maintain a constant NH4+ concentration (around 3 mmol NH4+/literIC), independent of the applied nitrogen source. We hypothesize that this amount of intracellular ammonium is required to obtain sufficient thermodynamic driving force. Furthermore, our calculations based on thermodynamic analysis of the transport mechanisms of ammonium suggest that ammonium is not equally

  5. Inter-Kingdom Modification of Metabolic Behavior: [GAR+] Prion Induction in Saccharomyces cerevisiae Mediated by Wine Ecosystem Bacteria

    Directory of Open Access Journals (Sweden)

    Linda F Bisson

    2016-11-01

    Full Text Available The yeast Saccharomyces cerevisiae has evolved to dominate grape juice fermentation. A suite of cellular properties, rapid nutrient depletion, production of inhibitory compounds and the metabolic narrowing of the niche, all enable a minor resident of the initial population to dramatically increase its relative biomass in the ecosystem. This dominance of the grape juice environment is fueled by a rapid launch of glycolysis and energy generation mediated by transport of hexoses and an efficient coupling of transport and catabolism. Fermentation occurs in the presence of molecular oxygen as the choice between respiratory or fermentative growth is regulated by the availability of sugar a phenomenon known as glucose or catabolite repression. Induction of the GAR+ prion alters the expression of the major hexose transporter active under these conditions, Hxt3, reducing glycolytic capacity. Bacteria present in the grape juice ecosystem were able to induce the GAR+ prion in wine strains of S. cerevisiae. This induction reduced fermentation capacity but did not block it entirely. However, dominance factors such as the rapid depletion of amino acids and other nitrogen sources from the environment were impeded enabling greater access to these substrates for the bacteria. Bacteria associated with arrested commercial wine fermentations were able to induce the prion state, and yeast cells isolated from arrested commercial fermentations were found to be GAR+ thus confirming the ecological relevance of prion induction. Subsequent analyses demonstrated that the presence of environmental acetic acid could lead to GAR+ induction in yeast strains under certain conditions. The induction of the prion enabled yeast growth on non-preferred substrates, oxidation and reduction products of glucose and fructose, present as a consequence of bacterial energy production. In native ecosystems prion induction never exceeded roughly 50-60% of the population of yeast cells

  6. Coutilization of D-Glucose, D-Xylose, and L-Arabinose in Saccharomyces cerevisiae by Coexpressing the Metabolic Pathways and Evolutionary Engineering

    Directory of Open Access Journals (Sweden)

    Chengqiang Wang

    2017-01-01

    Full Text Available Efficient and cost-effective fuel ethanol production from lignocellulosic materials requires simultaneous cofermentation of all hydrolyzed sugars, mainly including D-glucose, D-xylose, and L-arabinose. Saccharomyces cerevisiae is a traditional D-glucose fermenting strain and could utilize D-xylose and L-arabinose after introducing the initial metabolic pathways. The efficiency and simultaneous coutilization of the two pentoses and D-glucose for ethanol production in S. cerevisiae still need to be optimized. Previously, we constructed an L-arabinose-utilizing S. cerevisiae BSW3AP. In this study, we further introduced the XI and XR-XDH metabolic pathways of D-xylose into BSW3AP to obtain D-glucose, D-xylose, and L-arabinose cofermenting strain. Benefits of evolutionary engineering: the resulting strain BSW4XA3 displayed a simultaneous coutilization of D-xylose and L-arabinose with similar consumption rates, and the D-glucose metabolic capacity was not decreased. After 120 h of fermentation on mixed D-glucose, D-xylose, and L-arabinose, BSW4XA3 consumed 24% more amounts of pentoses and the ethanol yield of mixed sugars was increased by 30% than that of BSW3AP. The resulting strain BSW4XA3 was a useful chassis for further enhancing the coutilization efficiency of mixed sugars for bioethanol production.

  7. Involvement of Sac1 phosphoinositide phosphatase in the metabolism of phosphatidylserine in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Tani, Motohiro; Kuge, Osamu

    2014-04-01

    Sac1 is a phosphoinositide phosphatase that preferentially dephosphorylates phosphatidylinositol 4-phosphate. Mutation of SAC1 causes not only the accumulation of phosphoinositides but also reduction of the phosphatidylserine (PS) level in the yeast Saccharomyces cerevisiae. In this study, we characterized the mechanism underlying the PS reduction in SAC1-deleted cells. Incorporation of (32) P into PS was significantly delayed in sac1∆ cells. Such a delay was also observed in SAC1- and PS decarboxylase gene-deleted cells, suggesting that the reduction in the PS level is caused by a reduction in the rate of biosynthesis of PS. A reduction in the PS level was also observed with repression of STT4 encoding phosphatidylinositol 4-kinase or deletion of VPS34 encoding phophatidylinositol 3-kinase. However, the combination of mutations of SAC1 and STT4 or VPS34 did not restore the reduced PS level, suggesting that both the synthesis and degradation of phosphoinositides are important for maintenance of the PS level. Finally, we observed an abnormal PS distribution in sac1∆ cells when a specific probe for PS was expressed. Collectively, these results suggested that Sac1 is involved in the maintenance of a normal rate of biosynthesis and distribution of PS. Copyright © 2014 John Wiley & Sons, Ltd.

  8. Effects of high medium pH on growth, metabolism and transport in Saccharomyces cerevisiae.

    Science.gov (United States)

    Peña, Antonio; Sánchez, Norma Silvia; Álvarez, Helber; Calahorra, Martha; Ramírez, Jorge

    2015-03-01

    Growth of Saccharomyces cerevisiae stopped by maintaining the pH of the medium in a pH-stat at pH 8.0 or 9.0. Studying its main physiological capacities and comparing cells after incubation at pH 6.0 vs. 8.0 or 9.0, we found that (a) fermentation was moderately decreased by high pH and respiration was similar and sensitive to the addition of an uncoupler, (b) ATP and glucose-6-phosphate levels upon glucose addition increased to similar levels and (c) proton pumping and K(+) transport were also not affected; all this indicating that energy mechanisms were preserved. Growth inhibition at high pH was also not due to a significant lower amino acid transport by the cells or incorporation into proteins. The cell cycle stopped at pH 9.0, probably due to an arrest as a result of adjustments needed by the cells to contend with the changes under these conditions, and microarray experiments showed some relevant changes to this response. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

  9. Increasing galactose consumption by Saccharomyces cerevisiae through metabolic engineering of the GAL gene regulatory network

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Johnston, M.

    2000-01-01

    Increasing the flux through central carbon metabolism is difficult because of rigidity in regulatory structures, at both the genetic and the enzymatic levels. Here we describe metabolic engineering of a regulatory network to obtain a balanced increase in the activity of all the enzymes in the pat...... media. The improved galactose consumption of the gal mutants did not favor biomass formation, but rather caused excessive respiro-fermentative metabolism, with the ethanol production rate increasing linearly with glycolytic flux....... by eliminating three known negative regulators of the GAL system: Gale, Gal80, and Mig1. This led to a 41% increase in flux through the galactose utilization pathway compared with the wild-type strain. This is of significant interest within the field of biotechnology since galactose is present in many industrial...

  10. Improving the productivity of S-adenosyl-l-methionine by metabolic engineering in an industrial Saccharomyces cerevisiae strain.

    Science.gov (United States)

    Zhao, Weijun; Hang, Baojian; Zhu, Xiangcheng; Wang, Ri; Shen, Minjie; Huang, Lei; Xu, Zhinan

    2016-10-20

    S-Adenosyl-l-methionine (SAM) is an important metabolite having prominent roles in treating various diseases. In order to improve the production of SAM, the regulation of three metabolic pathways involved in SAM biosynthesis were investigated in an industrial yeast strain ZJU001. GLC3 encoded glycogen-branching enzyme (GBE), SPE2 encoded SAM decarboxylase, as well as ERG4 and ERG6 encoded key enzymes in ergosterol biosynthesis, were knocked out in ZJU001 accordingly. The results indicated that blocking of either glycogen pathway or SAM decarboxylation pathway could improve the SAM accumulation significantly in ZJU001, while single disruption of either ERG4 or ERG6 gene had no obvious effect on SAM production. Moreover, the double mutant ZJU001-GS with deletion of both GLC3 and SPE2 genes was also constructed, which showed further improvement of SAM accumulation. Finally, SAM2 was overexpressed in ZJU001-GS to give the best SAM-producing recombinant strain ZJU001-GS-SAM2, in which 12.47g/L SAM was produced by following our developed pseudo-exponential fed-batch cultivation strategy, about 81.0% increase comparing to its parent strain ZJU001. The present work laid a solid base for large-scale SAM production with the industrial Saccharomyces cerevisiae strain. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Nitrogen and carbon source balance determines longevity, independently of fermentative or respiratory metabolism in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Santos, Júlia; Leitão-Correia, Fernanda; Sousa, Maria João; Leão, Cecília

    2016-04-26

    Dietary regimens have proven to delay aging and age-associated diseases in several eukaryotic model organisms but the input of nutritional balance to longevity regulation is still poorly understood. Here, we present data on the role of single carbon and nitrogen sources and their interplay in yeast longevity. Data demonstrate that ammonium, a rich nitrogen source, decreases chronological life span (CLS) of the prototrophic Saccharomyces cerevisiae strain PYCC 4072 in a concentration-dependent manner and, accordingly, that CLS can be extended through ammonium restriction, even in conditions of initial glucose abundance. We further show that CLS extension depends on initial ammonium and glucose concentrations in the growth medium, as long as other nutrients are not limiting. Glutamine, another rich nitrogen source, induced CLS shortening similarly to ammonium, but this effect was not observed with the poor nitrogen source urea. Ammonium decreased yeast CLS independently of the metabolic process activated during aging, either respiration or fermentation, and induced replication stress inhibiting a proper cell cycle arrest in G0/G1 phase. The present results shade new light on the nutritional equilibrium as a key factor on cell longevity and may contribute for the definition of interventions to promote life span and healthy aging.

  12. Alterations in Phosphatidylcholine and Phosphatidylethanolamine Content During Fermentative Metabolism in Saccharomyces cerevisiae Brewer’s Yeast

    Directory of Open Access Journals (Sweden)

    Gordana Čanadi Jurešić

    2009-01-01

    Full Text Available During beer production and serial recycling, brewer’s yeasts are exposed to various stress factors that, overpowering the cellular defence mechanisms, can impair yeast growth and fermentation performance. It is well known that yeast cells acclimatize to stress conditions in part by changing the lipid composition of their membranes. The main focus of this study is the effect of stressful fermentation conditions on two phospholipid species, phosphatidylcholine (PtdCho and phosphatidylethanolamine (PtdEtn, in Saccharomyces cerevisiae bottom-fermenting brewer’s yeast. For this purpose the content and fatty acid profile of these major classes of phospholipids have been compared, as well as their ratio in the whole cells of the starter culture, non-stressed yeast population, and the first three recycled yeast generations. The stressed yeast generations showed an increased mass fraction of PtdCho and a decreased mass fraction of PtdEtn, which led to an increased PtdCho/PtdEtn ratio in the recycled cells as compared to the non-stressed yeast culture. The most pronounced variation of PtdCho/PtdEtn ratio was found in the second yeast generation, yielding a 78 % increase with respect to the starter culture. Variations in the content of both, PtdCho and PtdEtn, were accompanied by a higher mass fraction of unsaturated fatty acids in both phospholipid species (palmitoleic acid in PtdCho, and palmitoleic and oleic in PtdEtn and by the increased ratio of C16/C18 acids in PtdCho. The results suggest that both phospholipid species, including their fatty acids, are highly involved in the adaptation of brewer’s yeast to stressful fermentation conditions.

  13. The metabolic costs of improving ethanol yield by reducing glycerol formation capacity under anaerobic conditions in Saccharomyces cerevisiae.

    Science.gov (United States)

    Pagliardini, Julien; Hubmann, Georg; Alfenore, Sandrine; Nevoigt, Elke; Bideaux, Carine; Guillouet, Stephane E

    2013-03-28

    Finely regulating the carbon flux through the glycerol pathway by regulating the expression of the rate controlling enzyme, glycerol-3-phosphate dehydrogenase (GPDH), has been a promising approach to redirect carbon from glycerol to ethanol and thereby increasing the ethanol yield in ethanol production. Here, strains engineered in the promoter of GPD1 and deleted in GPD2 were used to investigate the possibility of reducing glycerol production of Saccharomyces cerevisiae without jeopardising its ability to cope with process stress during ethanol production. For this purpose, the mutant strains TEFmut7 and TEFmut2 with different GPD1 residual expression were studied in Very High Ethanol Performance (VHEP) fed-batch process under anaerobic conditions. Both strains showed a drastic reduction of the glycerol yield by 44 and 61% while the ethanol yield improved by 2 and 7% respectively. TEFmut2 strain showing the highest ethanol yield was accompanied by a 28% reduction of the biomass yield. The modulation of the glycerol formation led to profound redox and energetic changes resulting in a reduction of the ATP yield (YATP) and a modulation of the production of organic acids (acetate, pyruvate and succinate). Those metabolic rearrangements resulted in a loss of ethanol and stress tolerance of the mutants, contrarily to what was previously observed under aerobiosis. This work demonstrates the potential of fine-tuned pathway engineering, particularly when a compromise has to be found between high product yield on one hand and acceptable growth, productivity and stress resistance on the other hand. Previous study showed that, contrarily to anaerobiosis, the resulting gain in ethanol yield was accompanied with no loss of ethanol tolerance under aerobiosis. Moreover those mutants were still able to produce up to 90 gl-1 ethanol in an anaerobic SSF process. Fine tuning metabolic strategy may then open encouraging possibilities for further developing robust strains with improved

  14. Metabolic engineering of free-energy (ATP) conserving reactions in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    De Kok, S.

    2012-01-01

    Metabolic engineering – the improvement of cellular activities by manipulation of enzymatic, transport and regulatory functions of the cell – has enabled the industrial production of a wide variety of biological molecules from renewable resources. Microbial production of fuels and chemicals thereby

  15. Trehalose, glycogen and ethanol metabolism in the gcr1 mutant of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Seker, Tamay; Hamamci, H.

    2003-01-01

    Since Gcr1p is pivotal in controlling the transcription of glycolytic enzymes and trehalose metabolism seems to be one of the control points of glycolysis, we examined trehalose and glycogen synthesis in response to 2 % glucose pulse during batch growth in gcr1 (glucose regulation-1) mutant lacking...... fully functional glycolytic pathway and in the wild-type strain. An increase in both trehalose and glycogen stores was observed 1 and 2 h after the pulse followed by a steady decrease in both the wild-type and the gcr1 mutant. The accumulation was faster while the following degradation was slower in gcr......1 cells compared to wild-type ones. Although there was no distinct glucose consumption in the mutant cells it seemed that the glucose repression mechanism is similar in gcr1 mutant and in wild-type strain at least with respect to trehalose and glycogen metabolism....

  16. A modular metabolic engineering approach for the production of 1,2-propanediol from glycerol by Saccharomyces cerevisiae.

    Science.gov (United States)

    Islam, Zia-Ul; Klein, Mathias; Aßkamp, Maximilian R; Ødum, Anders S R; Nevoigt, Elke

    2017-11-01

    Compared to sugars, a major advantage of using glycerol as a feedstock for industrial bioprocesses is the fact that this molecule is more reduced than sugars. A compound whose biotechnological production might greatly profit from the substrate's higher reducing power is 1,2-propanediol (1,2-PDO). Here we present a novel metabolic engineering approach to produce 1,2-PDO from glycerol in S. cerevisiae. Apart from implementing the heterologous methylglyoxal (MG) pathway for 1,2-PDO formation from dihydroxyacetone phosphate (DHAP) and expressing a heterologous glycerol facilitator, the employed genetic modifications included the replacement of the native FAD-dependent glycerol catabolic pathway by the 'DHA pathway' for delivery of cytosolic NADH and the reduction of triosephosphate isomerase (TPI) activity for increased precursor (DHAP) supply. The choice of the medium had a crucial impact on both the strength of the metabolic switch towards fermentation in general (as indicated by the production of ethanol and 1,2-PDO) and on the ratio at which these two fermentation products were formed. For example, virtually no 1,2-PDO but only ethanol was formed in synthetic glycerol medium with urea as the nitrogen source. When nutrient-limited complex YG medium was used, significant amounts of 1,2-PDO were formed and it became obvious that the concerted supply of NADH and DHAP are essential for boosting 1,2-PDO production. Additionally, optimizing the flux into the MG pathway improved 1,2-PDO formation at the expense of ethanol. Cultivation of the best-performing strain in YG medium and a controlled bioreactor set-up resulted in a maximum titer of > 4gL -1 1,2-PDO which, to the best of our knowledge, has been the highest titer of 1,2-PDO obtained in yeast so far. Surprisingly, significant 1,2-PDO production was also obtained in synthetic glycerol medium after changing the nitrogen source towards ammonium sulfate and adding a buffer. Copyright © 2017 International Metabolic

  17. Metabolic engineering of Saccharomyces cerevisiae for production of germacrene A, a precursor of beta-elemene

    DEFF Research Database (Denmark)

    Hu, Yating; Zhou, Yongjin J.; Bao, Jichen

    2017-01-01

    inefficient and suffers from limited natural resources. Here, we engineered a yeast cell factory for the sustainable production of germacrene A, which can be transformed to beta-elemene by a one-step chemical reaction in vitro. Two heterologous germacrene A synthases (GASs) converting farnesyl pyrophosphate...... (FPP) to germacrene A were evaluated in yeast for their ability to produce germacrene A. Thereafter, several metabolic engineering strategies were used to improve the production level. Overexpression of truncated 3-hydroxyl-3-methylglutaryl-CoA reductase and fusion of FPP synthase with GAS, led...

  18. (13)C-metabolic flux analysis in S-adenosyl-L-methionine production by Saccharomyces cerevisiae.

    Science.gov (United States)

    Hayakawa, Kenshi; Kajihata, Shuichi; Matsuda, Fumio; Shimizu, Hiroshi

    2015-11-01

    S-Adenosyl-L-methionine (SAM) is a major biological methyl group donor, and is used as a nutritional supplement and prescription drug. Yeast is used for the industrial production of SAM owing to its high intracellular SAM concentrations. To determine the regulation mechanisms responsible for such high SAM production, (13)C-metabolic flux analysis ((13)C-MFA) was conducted to compare the flux distributions in the central metabolism between Kyokai no. 6 (high SAM-producing) and S288C (control) strains. (13)C-MFA showed that the levels of tricarboxylic acid (TCA) cycle flux in SAM-overproducing strain were considerably increased compared to those in the S228C strain. Analysis of ATP balance also showed that a larger amount of excess ATP was produced in the Kyokai 6 strain because of increased oxidative phosphorylation. These results suggest that high SAM production in Kyokai 6 strains could be attributed to enhanced ATP regeneration with high TCA cycle fluxes and respiration activity. Thus, maintaining high respiration efficiency during cultivation is important for improving SAM production. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  19. Transcription Factor Reb1p Regulates DGK1-encoded Diacylglycerol Kinase and Lipid Metabolism in Saccharomyces cerevisiae*

    Science.gov (United States)

    Qiu, Yixuan; Fakas, Stylianos; Han, Gil-Soo; Barbosa, Antonio Daniel; Siniossoglou, Symeon; Carman, George M.

    2013-01-01

    In the yeast Saccharomyces cerevisiae, the DGK1-encoded diacylglycerol kinase catalyzes the CTP-dependent phosphorylation of diacylglycerol to form phosphatidate. This enzyme, in conjunction with PAH1-encoded phosphatidate phosphatase, controls the levels of phosphatidate and diacylglycerol for phospholipid synthesis, membrane growth, and lipid droplet formation. In this work, we showed that a functional level of diacylglycerol kinase is regulated by the Reb1p transcription factor. In the electrophoretic mobility shift assay, purified recombinant Reb1p was shown to specifically bind its consensus recognition sequence (CGGGTAA, −166 to −160) in the DGK1 promoter. Analysis of cells expressing the PDGK1-lacZ reporter gene showed that mutations (GT→TG) in the Reb1p-binding sequence caused an 8.6-fold reduction in β-galactosidase activity. The expression of DGK1(reb1), a DGK1 allele containing the Reb1p-binding site mutation, was greatly lower than that of the wild type allele, as indicated by analyses of DGK1 mRNA, Dgk1p, and diacylglycerol kinase activity. In the presence of cerulenin, an inhibitor of de novo fatty acid synthesis, the dgk1Δ mutant expressing DGK1(reb1) exhibited a significant defect in growth as well as in the synthesis of phospholipids from triacylglycerol mobilization. Unlike DGK1, the DGK1(reb1) expressed in the dgk1Δ pah1Δ mutant did not result in the nuclear/endoplasmic reticulum membrane expansion, which occurs in cells lacking phosphatidate phosphatase activity. Taken together, these results indicate that the Reb1p-mediated regulation of diacylglycerol kinase plays a major role in its in vivo functions in lipid metabolism. PMID:23970552

  20. Transcription factor Reb1p regulates DGK1-encoded diacylglycerol kinase and lipid metabolism in Saccharomyces cerevisiae.

    Science.gov (United States)

    Qiu, Yixuan; Fakas, Stylianos; Han, Gil-Soo; Barbosa, Antonio Daniel; Siniossoglou, Symeon; Carman, George M

    2013-10-04

    In the yeast Saccharomyces cerevisiae, the DGK1-encoded diacylglycerol kinase catalyzes the CTP-dependent phosphorylation of diacylglycerol to form phosphatidate. This enzyme, in conjunction with PAH1-encoded phosphatidate phosphatase, controls the levels of phosphatidate and diacylglycerol for phospholipid synthesis, membrane growth, and lipid droplet formation. In this work, we showed that a functional level of diacylglycerol kinase is regulated by the Reb1p transcription factor. In the electrophoretic mobility shift assay, purified recombinant Reb1p was shown to specifically bind its consensus recognition sequence (CGGGTAA, -166 to -160) in the DGK1 promoter. Analysis of cells expressing the PDGK1-lacZ reporter gene showed that mutations (GT→TG) in the Reb1p-binding sequence caused an 8.6-fold reduction in β-galactosidase activity. The expression of DGK1(reb1), a DGK1 allele containing the Reb1p-binding site mutation, was greatly lower than that of the wild type allele, as indicated by analyses of DGK1 mRNA, Dgk1p, and diacylglycerol kinase activity. In the presence of cerulenin, an inhibitor of de novo fatty acid synthesis, the dgk1Δ mutant expressing DGK1(reb1) exhibited a significant defect in growth as well as in the synthesis of phospholipids from triacylglycerol mobilization. Unlike DGK1, the DGK1(reb1) expressed in the dgk1Δ pah1Δ mutant did not result in the nuclear/endoplasmic reticulum membrane expansion, which occurs in cells lacking phosphatidate phosphatase activity. Taken together, these results indicate that the Reb1p-mediated regulation of diacylglycerol kinase plays a major role in its in vivo functions in lipid metabolism.

  1. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production

    Directory of Open Access Journals (Sweden)

    Laura Navone

    2018-06-01

    Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  2. Microaerobic conversion of xylose to ethanol in recombinant Saccharomyces cerevisiae SX6(MUT) expressing cofactor-balanced xylose metabolic enzymes and deficient in ALD6.

    Science.gov (United States)

    Jo, Sung-Eun; Seong, Yeong-Je; Lee, Hyun-Soo; Lee, Soo Min; Kim, Soo-Jung; Park, Kyungmoon; Park, Yong-Cheol

    2016-06-10

    Xylose is a major monosugar in cellulosic biomass and should be utilized for cost-effective ethanol production. In this study, xylose-converting ability of recombinant Saccharomyces cerevisiae SX6(MUT) expressing NADH-preferring xylose reductase mutant (R276H) and other xylose-metabolic enzymes, and deficient in aldehyde dehydrogenase 6 (Ald6p) were characterized at microaerobic conditions using various sugar mixtures. The reduction of air supply from 0.5vvm to 0.1vvm increased specific ethanol production rate by 75% and did not affect specific xylose consumption rate. In batch fermentations using various concentrations of xylose (50-104g/L), higher xylose concentration enhanced xylose consumption rate and ethanol productivity but reduced ethanol yield, owing to the accumulation of xylitol and glycerol from xylose. SX6(MUT) consumed monosugars in pitch pine hydrolysates and produced 23.1g/L ethanol from 58.7g/L sugars with 0.39g/g ethanol yield, which was 14% higher than the host strain of S. cerevisiae D452-2 without the xylose assimilating enzymes. In conclusion, S. cerevisiae SX6(MUT) was characterized to possess high xylose-consuming ability in microaerobic conditions and a potential for ethanol production from cellulosic biomass. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Cross-Talk between Carbon Metabolism and the DNA Damage Response in S. cerevisiae

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    Kobi J. Simpson-Lavy

    2015-09-01

    Full Text Available Yeast cells with DNA damage avoid respiration, presumably because products of oxidative metabolism can be harmful to DNA. We show that DNA damage inhibits the activity of the Snf1 (AMP-activated protein kinase (AMPK, which activates expression of genes required for respiration. Glucose and DNA damage upregulate SUMOylation of Snf1, catalyzed by the SUMO E3 ligase Mms21, which inhibits SNF1 activity. The DNA damage checkpoint kinases Mec1/ATR and Tel1/ATM, as well as the nutrient-sensing protein kinase A (PKA, regulate Mms21 activity toward Snf1. Mec1 and Tel1 are required for two SNF1-regulated processes—glucose sensing and ADH2 gene expression—even without exogenous genotoxic stress. Our results imply that inhibition of Snf1 by SUMOylation is a mechanism by which cells lower their respiration in response to DNA damage. This raises the possibility that activation of DNA damage checkpoint mechanisms could contribute to aerobic fermentation (Warburg effect, a hallmark of cancer cells.

  4. Using Genome-scale Models to Predict Biological Capabilities

    DEFF Research Database (Denmark)

    O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.

    2015-01-01

    Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...

  5. H. guilliermondii impacts growth kinetics and metabolic activity of S. cerevisiae: the role of initial nitrogen concentration.

    Science.gov (United States)

    Lage, Patrícia; Barbosa, Catarina; Mateus, Beatriz; Vasconcelos, Isabel; Mendes-Faia, Arlete; Mendes-Ferreira, Ana

    2014-02-17

    Non-Saccharomyces yeasts include different species which comprise an ecologically and biochemically diverse group capable of altering fermentation dynamics and wine composition and flavour. In this study, single- and mixed-culture of Hanseniaspora guilliermondii and Saccharomyces cerevisiae were used to ferment natural grape-juice, under two nitrogen regimes. In single-culture the strain H. guilliermondii failed to complete total sugar breakdown even though the nitrogen available has not been a limiting factor of its growth or fermentative activity. In mixed-culture, that strain negatively interfered with the growth and fermentative performance of S. cerevisiae, resulting in lower fermentation rate and longer fermentation length, irrespective of the initial nitrogen concentration. The impact of co-inoculation on the volatile compounds profile was more evident in the wines obtained from DAP-supplemented musts, characterised by increased levels of ethyl and acetate esters, associated with fruity and floral character of wines. Moreover, the levels of fatty acids and sulphur compounds which are responsible for unpleasant odours that depreciate wine sensory quality were significantly lower. Accordingly, data obtained suggests that the strain H. guilliermondii has potential to be used as adjunct of S. cerevisiae in wine industry, although possible interactions with S. cerevisiae still need to be elucidated. Copyright © 2013 Elsevier B.V. All rights reserved.

  6. Impact of overexpressing NADH kinase on glucose and xylose metabolism in recombinant xylose-utilizing Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hou, Jin; Vemuri, G. N.; Bao, X. M.

    2009-01-01

    of overexpressing the native NADH kinase (encoded by the POS5 gene) in xylose-consuming recombinant S. cerevisiae directed either into the cytosol or to the mitochondria was evaluated. The physiology of the NADH kinase containing strains was also evaluated during growth on glucose. Overexpressing NADH kinase...

  7. Impact of two ionic liquids, 1-ethyl-3-methylimidazolium acetate and 1-ethyl-3-methylimidazolium methylphosphonate, on Saccharomyces cerevisiae: metabolic, physiologic, and morphological investigations.

    Science.gov (United States)

    Mehmood, Nasir; Husson, Eric; Jacquard, Cédric; Wewetzer, Sandra; Büchs, Jochen; Sarazin, Catherine; Gosselin, Isabelle

    2015-01-01

    Ionic liquids (ILs) are considered as suitable candidates for lignocellulosic biomass pretreatment prior enzymatic saccharification and, obviously, for second-generation bioethanol production. However, several reports showed toxic or inhibitory effects of residual ILs on microorganisms, plants, and animal cells which could affect a subsequent enzymatic saccharification and fermentation process. In this context, the impact of two hydrophilic imidazolium-based ILs already used in lignocellulosic biomass pretreatment was investigated: 1-ethyl-3-methylimidazolium acetate [Emim][OAc] and 1-ethyl-3-methylimidazolium methylphosphonate [Emim][MeO(H)PO2]. Their effects were assessed on the model yeast for ethanolic fermentation, Saccharomyces cerevisiae, grown in a culture medium containing glucose as carbon source and various IL concentrations. Classical fermentation parameters were followed: growth, glucose consumption and ethanol production, and two original factors: the respiratory status with the oxygen transfer rate (OTR) and carbon dioxide transfer rate (CTR) of yeasts which were monitored online by respiratory activity monitoring systems (RAMOS). In addition, yeast morphology was characterized by environmental scanning electron microscope (ESEM). The addition of ILs to the growth medium inhibited the OTR and switched the metabolism from respiration (conversion of glucose into biomass) to fermentation (conversion of glucose to ethanol). This behavior could be observed at low IL concentrations (≤5% IL) while above there is no significant growth or ethanol production. The presence of IL in the growth medium also induced changes of yeast morphology, which exhibited wrinkled, softened, and holed shapes. Both ILs showed the same effects, but [Emim][MeO(H)PO2] was more biocompatible than [Emim][OAc] and could be better tolerated by S. cerevisiae. These two imidazolium-derived ILs were appropriate candidates for useful pretreatment of lignocellulosic biomass in the

  8. Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Bojsen, Rasmus K; Andersen, Kaj Scherz; Regenberg, Birgitte

    2012-01-01

    Microbial biofilms can be defined as multi-cellular aggregates adhering to a surface and embedded in an extracellular matrix (ECM). The nonpathogenic yeast, Saccharomyces cerevisiae, follows the common traits of microbial biofilms with cell-cell and cell-surface adhesion. S. cerevisiae is shown t...

  9. Identification of Important Amino Acids in Gal2p for Improving the L-arabinose Transport and Metabolism in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Chengqiang Wang

    2017-07-01

    Full Text Available Efficient and cost-effective bioethanol production from lignocellulosic materials requires co-fermentation of the main hydrolyzed sugars, including glucose, xylose, and L-arabinose. Saccharomyces cerevisiae is a glucose-fermenting yeast that is traditionally used for ethanol production. Fermentation of L-arabinose is also possible after metabolic engineering. Transport into the cell is the first and rate-limiting step for L-arabinose metabolism. The galactose permease, Gal2p, is a non-specific, endogenous monosaccharide transporter that has been shown to transport L-arabinose. However, Gal2p-mediated transport of L-arabinose occurs at a low efficiency. In this study, homologous modeling and L-arabinose docking were used to predict amino acids in Gal2p that are crucial for L-arabinose transport. Nine amino acid residues in Gal2p were identified and were the focus for site-directed mutagenesis. In the Gal2p transport-deficient chassis cells, the capacity for L-arabinose transport of the different Gal2p mutants was compared by testing growth rates using L-arabinose as the sole carbon source. Almost all the tested mutations affected L-arabinose transport capacity. Among them, F85 is a unique site. The F85S, F85G, F85C, and F85T point mutations significantly increased L-arabinose transport activities, while, the F85E and F85R mutations decreased L-arabinose transport activities compared to the Gal2p-expressing wild-type strain. These results verified F85 as a key residue in L-arabinose transport. The F85S mutation, having the most significant effect, elevated the exponential growth rate by 40%. The F85S mutation also improved xylose transport efficiency and weakened the glucose transport preference. Overall, enhancing the L-arabinose transport capacity further improved the L-arabinose metabolism of engineered S. cerevisiae.

  10. Evolutionary programming as a platform for in silico metabolic engineering

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    Förster Jochen

    2005-12-01

    Full Text Available Abstract Background Through genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms. Results In this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters in industrial fermentations, one linear and other non-linear, by using a genome-scale model of the yeast Saccharomyces cerevisiae. Potential metabolic engineering targets for improved production of succinic acid, glycerol and vanillin are identified and underlying flux changes for the predicted mutants are discussed. Conclusion We show that evolutionary programming enables solving large gene knockout problems in relatively short computational time. The proposed algorithm also allows the optimization of non-linear objective functions or incorporation of non-linear constraints and additionally provides a family of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span

  11. Principles of proteome allocation are revealed using proteomic data and genome-scale models

    DEFF Research Database (Denmark)

    Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

    2016-01-01

    to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally...

  12. Metabolic and transcriptomic response of the wine yeast Saccharomyces cerevisiae strain EC1118 after an oxygen impulse under carbon-sufficient, nitrogen-limited fermentative conditions.

    Science.gov (United States)

    Orellana, Marcelo; Aceituno, Felipe F; Slater, Alex W; Almonacid, Leonardo I; Melo, Francisco; Agosin, Eduardo

    2014-05-01

    During alcoholic fermentation, Saccharomyces cerevisiae is exposed to continuously changing environmental conditions, such as decreasing sugar and increasing ethanol concentrations. Oxygen, a critical nutrient to avoid stuck and sluggish fermentations, is only discretely available throughout the process after pump-over operation. In this work, we studied the physiological response of the wine yeast S. cerevisiae strain EC1118 to a sudden increase in dissolved oxygen, simulating pump-over operation. With this aim, an impulse of dissolved oxygen was added to carbon-sufficient, nitrogen-limited anaerobic continuous cultures. Results showed that genes related to mitochondrial respiration, ergosterol biosynthesis, and oxidative stress, among other metabolic pathways, were induced after the oxygen impulse. On the other hand, mannoprotein coding genes were repressed. The changes in the expression of these genes are coordinated responses that share common elements at the level of transcriptional regulation. Beneficial and detrimental effects of these physiological processes on wine quality highlight the dual role of oxygen in 'making or breaking wines'. These findings will facilitate the development of oxygen addition strategies to optimize yeast performance in industrial fermentations. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  13. Systematic optimization of fed-batch simultaneous saccharification and fermentation at high-solid loading based on enzymatic hydrolysis and dynamic metabolic modeling of Saccharomyces cerevisiae.

    Science.gov (United States)

    Unrean, Pornkamol; Khajeeram, Sutamat; Laoteng, Kobkul

    2016-03-01

    An integrative simultaneous saccharification and fermentation (SSF) modeling is a useful guiding tool for rapid process optimization to meet the techno-economic requirement of industrial-scale lignocellulosic ethanol production. In this work, we have developed the SSF model composing of a metabolic network of a Saccharomyces cerevisiae cell associated with fermentation kinetics and enzyme hydrolysis model to quantitatively capture dynamic responses of yeast cell growth and fermentation during SSF. By using model-based design of feeding profiles for substrate and yeast cell in the fed-batch SSF process, an efficient ethanol production with high titer of up to 65 g/L and high yield of 85 % of theoretical yield was accomplished. The ethanol titer and productivity was increased by 47 and 41 %, correspondingly, in optimized fed-batch SSF as compared to batch process. The developed integrative SSF model is, therefore, considered as a promising approach for systematic design of economical and sustainable SSF bioprocessing of lignocellulose.

  14. Fermentation of Xylose Causes Inefficient Metabolic State Due to Carbon/Energy Starvation and Reduced Glycolytic Flux in Recombinant Industrial Saccharomyces cerevisiae

    Science.gov (United States)

    Matsushika, Akinori; Nagashima, Atsushi; Goshima, Tetsuya; Hoshino, Tamotsu

    2013-01-01

    In the present study, comprehensive, quantitative metabolome analysis was carried out on the recombinant glucose/xylose-cofermenting S. cerevisiae strain MA-R4 during fermentation with different carbon sources, including glucose, xylose, or glucose/xylose mixtures. Capillary electrophoresis time-of-flight mass spectrometry was used to determine the intracellular pools of metabolites from the central carbon pathways, energy metabolism pathways, and the levels of twenty amino acids. When xylose instead of glucose was metabolized by MA-R4, glycolytic metabolites including 3- phosphoglycerate, 2- phosphoglycerate, phosphoenolpyruvate, and pyruvate were dramatically reduced, while conversely, most pentose phosphate pathway metabolites such as sedoheptulose 7- phosphate and ribulose 5-phosphate were greatly increased. These results suggest that the low metabolic activity of glycolysis and the pool of pentose phosphate pathway intermediates are potential limiting factors in xylose utilization. It was further demonstrated that during xylose fermentation, about half of the twenty amino acids declined, and the adenylate/guanylate energy charge was impacted due to markedly decreased adenosine triphosphate/adenosine monophosphate and guanosine triphosphate/guanosine monophosphate ratios, implying that the fermentation of xylose leads to an inefficient metabolic state where the biosynthetic capabilities and energy balance are severely impaired. In addition, fermentation with xylose alone drastically increased the level of citrate in the tricarboxylic acid cycle and increased the aromatic amino acids tryptophan and tyrosine, strongly supporting the view that carbon starvation was induced. Interestingly, fermentation with xylose alone also increased the synthesis of the polyamine spermidine and its precursor S-adenosylmethionine. Thus, differences in carbon substrates, including glucose and xylose in the fermentation medium, strongly influenced the dynamic metabolism of MA-R4

  15. Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.

    Science.gov (United States)

    Navone, Laura; McCubbin, Tim; Gonzalez-Garcia, Ricardo A; Nielsen, Lars K; Marcellin, Esteban

    2018-06-01

    Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp . shermanii and the pan- Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp . shermanii , two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in

  16. MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

    Science.gov (United States)

    Zhou, Yikang; Li, Gang; Dong, Junkai; Xing, Xin-Hui; Dai, Junbiao; Zhang, Chong

    2018-05-01

    Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using β-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  17. SWITCH: a dynamic CRISPR tool for genome engineering and metabolic pathway control for cell factory construction in Saccharomyces cerevisiae.

    Science.gov (United States)

    Vanegas, Katherina García; Lehka, Beata Joanna; Mortensen, Uffe Hasbro

    2017-02-08

    The yeast Saccharomyces cerevisiae is increasingly used as a cell factory. However, cell factory construction time is a major obstacle towards using yeast for bio-production. Hence, tools to speed up cell factory construction are desirable. In this study, we have developed a new Cas9/dCas9 based system, SWITCH, which allows Saccharomyces cerevisiae strains to iteratively alternate between a genetic engineering state and a pathway control state. Since Cas9 induced recombination events are crucial for SWITCH efficiency, we first developed a technique TAPE, which we have successfully used to address protospacer efficiency. As proof of concept of the use of SWITCH in cell factory construction, we have exploited the genetic engineering state of a SWITCH strain to insert the five genes necessary for naringenin production. Next, the naringenin cell factory was switched to the pathway control state where production was optimized by downregulating an essential gene TSC13, hence, reducing formation of a byproduct. We have successfully integrated two CRISPR tools, one for genetic engineering and one for pathway control, into one system and successfully used it for cell factory construction.

  18. Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production

    Directory of Open Access Journals (Sweden)

    Kim Tae

    2011-06-01

    Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The

  19. Bio-succinic acid production: Escherichia coli strains design from genome-scale perspectives

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    Bashir Sajo Mienda

    2017-10-01

    Full Text Available Escherichia coli (E. coli has been established to be a native producer of succinic acid (a platform chemical with different applications via mixed acid fermentation reactions. Genome-scale metabolic models (GEMs of E. coli have been published with capabilities of predicting strain design strategies for the production of bio-based succinic acid. Proof-of-principle strains are fundamentally constructed as a starting point for systems strategies for industrial strains development. Here, we review for the first time, the use of E. coli GEMs for construction of proof-of-principles strains for increasing succinic acid production. Specific case studies, where E. coli proof-of-principle strains were constructed for increasing bio-based succinic acid production from glucose and glycerol carbon sources have been highlighted. In addition, a propose systems strategies for industrial strain development that could be applicable for future microbial succinic acid production guided by GEMs have been presented.

  20. Exercise and Beta-Glucan Consumption (Saccharomyces cerevisiae) Improve the Metabolic Profile and Reduce the Atherogenic Index in Type 2 Diabetic Rats (HFD/STZ).

    Science.gov (United States)

    Andrade, Eric Francelino; Lima, Andressa Ribeiro Veiga; Nunes, Ingrid Edwiges; Orlando, Débora Ribeiro; Gondim, Paula Novato; Zangeronimo, Márcio Gilberto; Alves, Fernando Henrique Ferrari; Pereira, Luciano José

    2016-12-17

    Physical activity and the ingestion of dietary fiber are non-drug alternatives commonly used as adjuvants to glycemic control in diabetic individuals. Among these fibers, we can highlight beta-glucans. However, few studies have compared isolated and synergic effects of physical exercise and beta-glucan ingestion, especially in type 2 diabetic rats. Therefore, we evaluated the effects beta-glucan ( Saccharomyces cerevisiae ) consumption, associated or not to exercise, on metabolic parameters of diabetic Wistar rats. The diabetes mellitus (DM) was induced by high-fat diet (HFD) associated with a low dose of streptozotocin (STZ-35 mg/kg). Trained groups were submitted to eight weeks of exercise in aquatic environment. In the last 28 days of experiment, animals received 30 mg/kg/day of beta-glucan by gavage. Isolated use of beta-glucan decreased glucose levels in fasting, Glycated hemoglobin (HbA1c), triglycerides (TAG), total cholesterol (TC), low-density lipoprotein (LDL-C), the atherogenic index of plasma. Exercise alone also decreased blood glucose levels, HbA1c, and renal lesions. An additive effect for reducing the atherogenic index of plasma and renal lesions was observed when both treatments were combined. It was concluded that both beta-glucan and exercise improved metabolic parameters in type 2 (HFD/STZ) diabetic rats.

  1. Saccharomyces cerevisiae single-copy plasmids for auxotrophy compensation, multiple marker selection, and for designing metabolically cooperating communities [version 1; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Michael Mülleder

    2016-09-01

    Full Text Available Auxotrophic markers are useful tools in cloning and genome editing, enable a large spectrum of genetic techniques, as well as facilitate the study of metabolite exchange interactions in microbial communities. If unused background auxotrophies are left uncomplemented however, yeast cells need to be grown in nutrient supplemented or rich growth media compositions, which precludes the analysis of biosynthetic metabolism, and which leads to a profound impact on physiology and gene expression. Here we present a series of 23 centromeric plasmids designed to restore prototrophy in typical Saccharomyces cerevisiae laboratory strains. The 23 single-copy plasmids complement for deficiencies in HIS3, LEU2, URA3, MET17 or LYS2 genes and in their combinations, to match the auxotrophic background of the popular functional-genomic yeast libraries that are based on the S288c strain. The plasmids are further suitable for designing self-establishing metabolically cooperating (SeMeCo communities, and possess a uniform multiple cloning site to exploit multiple parallel selection markers in protein expression experiments.

  2. In vivo analysis of NH4+ transport and central N-metabolism of Saccharomyces cerevisiae under aerobic N-limited conditions.

    Science.gov (United States)

    Cueto-Rojas, H F; Maleki Seifar, R; Ten Pierick, A; van Helmond, W; Pieterse M, M; Heijnen, J J; Wahl, S A

    2016-09-16

    Ammonium is the most common N-source for yeast fermentations. Although, its transport and assimilation mechanisms are well documented, there have been only few attempts to measure the in vivo intracellular concentration of ammonium and assess its impact on gene expression. Using an isotope dilution mass spectrometry (IDMS)-based method we were able to measure the intracellular ammonium concentration in N-limited aerobic chemostat cultivations using three different N-sources (ammonium, urea and glutamate) at the same growth rate (0.05 h -1 ). The experimental results suggest that, at this growth rate, a similar concentration of intracellular ammonium, about 3.6 mmol NH 4 + /L IC , is required to supply the reactions in the central N-metabolism independent of the N-source. Based on the experimental results and different assumptions, the vacuolar and cytosolic ammonium concentrations were estimated. Furthermore, we identified a futile cycle caused by NH 3 leakage to the extracellular space, which can cost up to 30% of the ATP production of the cell under N-limited conditions, and a futile redox cycle between reactions Gdh1 and Gdh2. Finally, using shotgun proteomics with labeled reference-relative protein expression, differences between the various environmental conditions were identified and correlated with previously identified N-compound sensing mechanisms. In our work, we study central N-metabolism using quantitative approaches. First, intracellular ammonium was measured under different N-sources. The results suggest that Saccharomyces cerevisiae cells keep a constant NH 4 + concentration (around 3 mmol NH 4 + /L IC ), independent of the applied nitrogen source. We hypothesize that this amount of intracellular ammonium is required to obtain sufficient thermodynamic driving force.Furthermore, our calculations based on thermodynamic analysis of the transport mechanisms of ammonium suggest that ammonium is not equally distributed, indicating a high degree of

  3. ISC1-dependent metabolic adaptation reveals an indispensable role for mitochondria in induction of nuclear genes during the diauxic shift in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kitagaki, Hiroshi; Cowart, L Ashley; Matmati, Nabil; Montefusco, David; Gandy, Jason; de Avalos, Silvia Vaena; Novgorodov, Sergei A; Zheng, Jim; Obeid, Lina M; Hannun, Yusuf A

    2009-04-17

    Growth of Saccharomyces cerevisiae following glucose depletion (the diauxic shift) depends on a profound metabolic adaptation accompanied by a global reprogramming of gene expression. In this study, we provide evidence for a heretofore unsuspected role for Isc1p in mediating this reprogramming. Initial studies revealed that yeast cells deleted in ISC1, the gene encoding inositol sphingolipid phospholipase C, which resides in mitochondria in the post-diauxic phase, showed defective aerobic respiration in the post-diauxic phase but retained normal intrinsic mitochondrial functions, including intact mitochondrial DNA, normal oxygen consumption, and normal mitochondrial polarization. Microarray analysis revealed that the Deltaisc1 strain failed to up-regulate genes required for nonfermentable carbon source metabolism during the diauxic shift, thus suggesting a mechanism for the defective supply of respiratory substrates into mitochondria in the post-diauxic phase. This defect in regulating nuclear gene induction in response to a defect in a mitochondrial enzyme raised the possibility that mitochondria may initiate diauxic shift-associated regulation of nucleus-encoded genes. This was established by demonstrating that in respiratory-deficient petite cells these genes failed to be up-regulated across the diauxic shift in a manner similar to the Deltaisc1 strain. Isc1p- and mitochondrial function-dependent genes significantly overlapped with Adr1p-, Snf1p-, and Cat8p-dependent genes, suggesting some functional link among these factors. However, the retrograde response was not activated in Deltaisc1, suggesting that the response of Deltaisc1 cannot be simply attributed to mitochondrial dysfunction. These results suggest a novel role for Isc1p in allowing the reprogramming of gene expression during the transition from anaerobic to aerobic metabolism.

  4. Industrial systems biology of Saccharomyces cerevisiae enables novel succinic acid cell factory.

    Directory of Open Access Journals (Sweden)

    José Manuel Otero

    Full Text Available Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol, and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2(nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we

  5. Improvement of d-Lactic Acid Production in Saccharomyces cerevisiae Under Acidic Conditions by Evolutionary and Rational Metabolic Engineering.

    Science.gov (United States)

    Baek, Seung-Ho; Kwon, Eunice Y; Bae, Sang-Jeong; Cho, Bo-Ram; Kim, Seon-Young; Hahn, Ji-Sook

    2017-10-01

    Microbial lactic acid (LA) production under acidic fermentation conditions is favorable to reduce the production cost, but circumventing LA toxicity is a major challenge. A d-LA-producing Saccharomyces cerevisiae strain JHY5610 is generated by expressing d-lactate dehydrogenase gene (Lm. ldhA) from Leuconostoc mesenteroides, while deleting genes involved in ethanol production (ADH1, ADH2, ADH3, ADH4, and ADH5), glycerol production (GPD1 and GPD2), and degradation of d-LA (DLD1). Adaptive laboratory evolution of JHY5610 lead to a strain JHY5710 having higher LA tolerance and d-LA-production capability. Genome sequencing of JHY5710 reveal that SUR1 I245S mutation increases LA tolerance and d-LA-production, whereas a loss-of-function mutation of ERF2 only contributes to increasing d-LA production. Introduction of both SUR1 I245S and erf2Δ mutations into JHY5610 largely mimic the d-LA-production capability of JHY5710, suggesting that these two mutations, which could modulate sphingolipid production and protein palmitoylation, are mainly responsible for the improved d-LA production in JHY5710. JHY5710 is further improved by deleting PDC1 encoding pyruvate decarboxylase and additional integration of Lm. ldhA gene. The resulting strain JHY5730 produce up to 82.6 g L -1 of d-LA with a yield of 0.83 g g -1 glucose and a productivity of 1.50 g/(L · h) in fed-batch fermentation at pH 3.5. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Metabolic pathway engineering based on metabolomics confers acetic and formic acid tolerance to a recombinant xylose-fermenting strain of Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Ishii Jun

    2011-01-01

    Full Text Available Abstract Background The development of novel yeast strains with increased tolerance toward inhibitors in lignocellulosic hydrolysates is highly desirable for the production of bio-ethanol. Weak organic acids such as acetic and formic acids are necessarily released during the pretreatment (i.e. solubilization and hydrolysis of lignocelluloses, which negatively affect microbial growth and ethanol production. However, since the mode of toxicity is complicated, genetic engineering strategies addressing yeast tolerance to weak organic acids have been rare. Thus, enhanced basic research is expected to identify target genes for improved weak acid tolerance. Results In this study, the effect of acetic acid on xylose fermentation was analyzed by examining metabolite profiles in a recombinant xylose-fermenting strain of Saccharomyces cerevisiae. Metabolome analysis revealed that metabolites involved in the non-oxidative pentose phosphate pathway (PPP [e.g. sedoheptulose-7-phosphate, ribulose-5-phosphate, ribose-5-phosphate and erythrose-4-phosphate] were significantly accumulated by the addition of acetate, indicating the possibility that acetic acid slows down the flux of the pathway. Accordingly, a gene encoding a PPP-related enzyme, transaldolase or transketolase, was overexpressed in the xylose-fermenting yeast, which successfully conferred increased ethanol productivity in the presence of acetic and formic acid. Conclusions Our metabolomic approach revealed one of the molecular events underlying the response to acetic acid and focuses attention on the non-oxidative PPP as a target for metabolic engineering. An important challenge for metabolic engineering is identification of gene targets that have material importance. This study has demonstrated that metabolomics is a powerful tool to develop rational strategies to confer tolerance to stress through genetic engineering.

  7. A potential mechanism of energy-metabolism oscillation in an aerobic chemostat culture of the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Xu, Zhaojun; Tsurugi, Kunio

    2006-04-01

    The energy-metabolism oscillation in aerobic chemostat cultures of yeast is a periodic change of the respiro-fermentative and respiratory phase. In the respiro-fermentative phase, the NADH level was kept high and respiration was suppressed, and glucose was anabolized into trehalose and glycogen at a rate comparable to that of catabolism. On the transition to the respiratory phase, cAMP levels increased triggering the breakdown of storage carbohydrates and the increased influx of glucose into the glycolytic pathway activated production of glycerol and ethanol consuming NADH. The resulting increase in the NAD(+)/NADH ratio stimulated respiration in combination with a decrease in the level of ATP, which was consumed mainly in the formation of biomass accompanying budding, and the accumulated ethanol and glycerol were gradually degraded by respiration via NAD(+)-dependent oxidation to acetate and the respiratory phase ceased after the recovery of NADH and ATP levels. However, the mRNA levels of both synthetic and degradative enzymes of storage carbohydrates were increased around the early respiro-fermentative phase, when storage carbohydrates are being synthesized, suggesting that the synthetic enzymes were expressed directly as active forms while the degradative enzymes were activated late by cAMP. In summary, the energy-metabolism oscillation is basically regulated by a feedback loop of oxido-reductive reactions of energy metabolism mediated by metabolites like NADH and ATP, and is modulated by metabolism of storage carbohydrates in combination of post-translational and transcriptional regulation of the related enzymes. A potential mechanism of energy-metabolism oscillation is proposed.

  8. Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Arkin Adam P

    2009-03-01

    Full Text Available Abstract Background Iron-deficiency anemia is the most prevalent form of anemia world-wide. The yeast Saccharomyces cerevisiae has been used as a model of cellular iron deficiency, in part because many of its cellular pathways are conserved. To better understand how cells respond to changes in iron availability, we profiled the yeast genome with a parallel analysis of homozygous deletion mutants to identify essential components and cellular processes required for optimal growth under iron-limited conditions. To complement this analysis, we compared those genes identified as important for fitness to those that were differentially-expressed in the same conditions. The resulting analysis provides a global perspective on the cellular processes involved in iron metabolism. Results Using functional profiling, we identified several genes known to be involved in high affinity iron uptake, in addition to novel genes that may play a role in iron metabolism. Our results provide support for the primary involvement in iron homeostasis of vacuolar and endosomal compartments, as well as vesicular transport to and from these compartments. We also observed an unexpected importance of the peroxisome for growth in iron-limited media. Although these components were essential for growth in low-iron conditions, most of them were not differentially-expressed. Genes with altered expression in iron deficiency were mainly associated with iron uptake and transport mechanisms, with little overlap with those that were functionally required. To better understand this relationship, we used expression-profiling of selected mutants that exhibited slow growth in iron-deficient conditions, and as a result, obtained additional insight into the roles of CTI6, DAP1, MRS4 and YHR045W in iron metabolism. Conclusion Comparison between functional and gene expression data in iron deficiency highlighted the complementary utility of these two approaches to identify important functional

  9. Role of Gts1p in regulation of energy-metabolism oscillation in continuous cultures of the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Xu, Zhaojun; Tsurugi, Kunio

    2007-03-01

    Energy-metabolism oscillation (EMO) in an aerobic chemostat culture of yeast is basically regulated by a feedback loop of redox reactions in energy metabolism and modulated by metabolism of storage carbohydrates. In this study, we investigated the role of Gts1p in the stabilization of EMO, using the GTS1-deleted transformant gts1Delta. We found that fluctuations in the redox state of the NAD co-factor and levels of redox-regulated metabolites in glycolysis, especially of ethanol, are markedly reduced in amplitude during EMO of gts1Delta, while respiration indicated by the oxygen uptake rate (OUR) and energy charge is not so affected throughout EMO in gts1Delta. Further, the transitions of the levels of OUR, NAD(+) : NADH ratio and intracellular pH between the two phases were apparently retarded compared with those in the wild-type, suggesting attenuation of EMO in gts1Delta. Furthermore, the mRNA levels of genes encoding enzymes for the synthesis of trehalose and glycogen are fairly reduced in gts1Delta, consistent with the decreased synthesis of storage carbohydrates. In addition, the level of inorganic phosphate, which is required for the reduction of NAD(+) and mainly supplied from trehalose synthesis, was decreased in the early respiro-fermentative phase in gts1Delta. Thus, we suggested that the deletion of GTS1 as a transcriptional co-activator for these genes inhibited the metabolism of storage carbohydrates, which causes attenuation of the feedback loop of dehydrogenase reactions in glycolysis with the restricted fluctuation of ethanol as a main synchronizing agent for EMO in a cell population.

  10. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Science.gov (United States)

    Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

    2017-01-01

    Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

  11. Expanding a dynamic flux balance model of yeast fermentation to genome-scale

    Science.gov (United States)

    2011-01-01

    Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919

  12. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

    Directory of Open Access Journals (Sweden)

    Marko Budinich

    Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.

  13. A modular metabolic engineering approach for the production of 1,2-propanediol from glycerol by Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Islam, Zia-Ul; Klein, Mathias; Aßkamp, Maximilian R.

    2017-01-01

    Compared to sugars, a major advantage of using glycerol as a feedstock for industrial bioprocesses is the fact that this molecule is more reduced than sugars. A compound whose biotechnological production might greatly profit from the substrate's higher reducing power is 1,2-propanediol (1,2-PDO...... as the nitrogen source. When nutrient-limited complex YG medium was used, significant amounts of 1,2-PDO were formed and it became obvious that the concerted supply of NADH and DHAP are essential for boosting 1,2-PDO production. Additionally, optimizing the flux into the MG pathway improved 1,2-PDO formation...... on both the strength of the metabolic switch towards fermentation in general (as indicated by the production of ethanol and 1,2-PDO) and on the ratio at which these two fermentation products were formed. For example, virtually no 1,2-PDO but only ethanol was formed in synthetic glycerol medium with urea...

  14. Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.

    Science.gov (United States)

    Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup

    2018-03-19

    Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.

  15. Directed evolution of pyruvate decarboxylase-negative Saccharomyces cerevisiae, yielding a C2-independent, glucose-tolerant, and pyruvate-hyperproducing yeast

    NARCIS (Netherlands)

    A.J. van Maris; J.M. Geertman; A. Vermeulen; M.K. Groothuizen; A.A. Winkler; M.D. Piper; J.P. van Dijken; J.T. Pronk

    2004-01-01

    textabstractThe absence of alcoholic fermentation makes pyruvate decarboxylase-negative (Pdc(-)) strains of Saccharomyces cerevisiae an interesting platform for further metabolic engineering of central metabolism. However, Pdc(-) S. cerevisiae strains have two growth defects:

  16. Use of an uncertainty analysis for genome-scale models as a prediction tool for microbial growth processes in subsurface environments.

    Science.gov (United States)

    Klier, Christine

    2012-03-06

    The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.

  17. Dynamic flux balancing elucidates NAD(P)H production as limiting response to furfural inhibition in Saccharomyces cerevisiae.

    Science.gov (United States)

    Pornkamol, Unrean; Franzen, Carl J

    2015-08-01

    Achieving efficient and economical lignocellulose-based bioprocess requires a robust organism tolerant to furfural, a major inhibitory compound present in lignocellulosic hydrolysate. The aim of this study was to develop a model that could generate quantitative descriptions of cell metabolism for elucidating the cell's adaptive response to furfural. Such a modelling tool could provide strategies for the design of more robust cells. A dynamic flux balance (dFBA) model of Saccharomyces cerevisiae was created by coupling a kinetic fermentation model with a previously published genome-scale stoichiometric model. The dFBA model was used for studying intracellular and extracellular flux responses to furfural perturbations under steady state and dynamic conditions. The predicted effects of furfural on dynamic flux profiles agreed well with previously published experimental results. The model showed that the yeast cell adjusts its metabolism in response to furfural challenge by increasing fluxes through the pentose phosphate pathway, TCA cycle, and proline and serine biosynthesis in order to meet the high demand of NAD(P)H cofactors. The model described here can be used to aid in systematic optimization of the yeast, as well as of the fermentation process, for efficient lignocellulosic ethanol production. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Adaption of Saccharomyces cerevisiae expressing a heterologous protein

    DEFF Research Database (Denmark)

    Krogh, Astrid Mørkeberg; Beck, Vibe; Højlund Christensen, Lars

    2008-01-01

    Production of the heterologous protein, bovine aprotinin, in Saccharomyces cerevisiae was shown to affect the metabolism of the host cell to various extent depending on the strain genotype. Strains with different genotypes, industrial and laboroatory, respectively, were investigated. The maximal...

  19. Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi

    Science.gov (United States)

    Giguere, Andrew T.; Murthy, Ganti S.; Bottomley, Peter J.; Sayavedra-Soto, Luis A.

    2018-01-01

    ABSTRACT Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO2, and N2O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi. The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH4+). Up to 60% of NH4+-based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO3−), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO2], and nitrous oxide [N2O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification. PMID:29577088

  20. Genome-Scale, Constraint-Based Modeling of Nitrogen Oxide Fluxes during Coculture of Nitrosomonas europaea and Nitrobacter winogradskyi.

    Science.gov (United States)

    Mellbye, Brett L; Giguere, Andrew T; Murthy, Ganti S; Bottomley, Peter J; Sayavedra-Soto, Luis A; Chaplen, Frank W R

    2018-01-01

    Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO 2 , and N 2 O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi . The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH 4 + ). Up to 60% of NH 4 + -based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO 3 - ), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO 2 ], and nitrous oxide [N 2 O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification.

  1. Glucose repression in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kayikci, Ömur; Nielsen, Jens

    2015-09-01

    Glucose is the primary source of energy for the budding yeast Saccharomyces cerevisiae. Although yeast cells can utilize a wide range of carbon sources, presence of glucose suppresses molecular activities involved in the use of alternate carbon sources as well as it represses respiration and gluconeogenesis. This dominant effect of glucose on yeast carbon metabolism is coordinated by several signaling and metabolic interactions that mainly regulate transcriptional activity but are also effective at post-transcriptional and post-translational levels. This review describes effects of glucose repression on yeast carbon metabolism with a focus on roles of the Snf3/Rgt2 glucose-sensing pathway and Snf1 signal transduction in establishment and relief of glucose repression. © FEMS 2015.

  2. Expression induction of P450 genes by imidacloprid in Nilaparvata lugens: A genome-scale analysis.

    Science.gov (United States)

    Zhang, Jianhua; Zhang, Yixi; Wang, Yunchao; Yang, Yuanxue; Cang, Xinzhu; Liu, Zewen

    2016-09-01

    The overexpression of P450 monooxygenase genes is a main mechanism for the resistance to imidacloprid, a representative neonicotinoid insecticide, in Nilaparvata lugens (brown planthopper, BPH). However, only two P450 genes (CYP6AY1 and CYP6ER1), among fifty-four P450 genes identified from BPH genome database, have been reported to play important roles in imidacloprid resistance until now. In this study, after the confirmation of important roles of P450s in imidacloprid resistance by the synergism analysis, the expression induction by imidacloprid was determined for all P450 genes. In the susceptible (Sus) strain, eight P450 genes in Clade4, eight in Clade3 and two in Clade2 were up-regulated by imidacloprid, among which three genes (CYP6CS1, CYP6CW1 and CYP6ER1, all in Clade3) were increased to above 4.0-fold and eight genes to above 2.0-fold. In contrast, no P450 genes were induced in Mito clade. Eight genes induced to above 2.0-fold were selected to determine their expression and induced levels in Huzhou population, in which piperonyl butoxide showed the biggest effects on imidacloprid toxicity among eight field populations. The expression levels of seven P450 genes were higher in Huzhou population than that in Sus strain, with the biggest differences for CYP6CS1 (9.8-fold), CYP6ER1 (7.7-fold) and CYP6AY1 (5.1-fold). The induction levels for all tested genes were bigger in Sus strain than that in Huzhou population except CYP425B1. Screening the induction of P450 genes by imidacloprid in the genome-scale will provide an overall view on the possible metabolic factors in the resistance to neonicotinoid insecticides. The further work, such as the functional study of recombinant proteins, will be performed to validate the roles of these P450s in imidacloprid resistance. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Analysis of genetic variation and potential applications in genome-scale metabolic modeling

    DEFF Research Database (Denmark)

    Cardoso, Joao; Andersen, Mikael Rørdam; Herrgard, Markus

    2015-01-01

    scale and resolution by re-sequencing thousands of strains systematically. In this article, we review challenges in the integration and analysis of large-scale re-sequencing data, present an extensive overview of bioinformatics methods for predicting the effects of genetic variants on protein function......Genetic variation is the motor of evolution and allows organisms to overcome the environmental challenges they encounter. It can be both beneficial and harmful in the process of engineering cell factories for the production of proteins and chemicals. Throughout the history of biotechnology......, there have been efforts to exploit genetic variation in our favor to create strains with favorable phenotypes. Genetic variation can either be present in natural populations or it can be artificially created by mutagenesis and selection or adaptive laboratory evolution. On the other hand, unintended genetic...

  4. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    International Nuclear Information System (INIS)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-01-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species, multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  5. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model.

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R

    2011-03-25

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  6. Direct coupling of a genome-scale microbial in silico model and a groundwater reactive transport model

    Science.gov (United States)

    Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.

    2011-03-01

    The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The

  7. Population FBA predicts metabolic phenotypes in yeast.

    Directory of Open Access Journals (Sweden)

    Piyush Labhsetwar

    2017-09-01

    Full Text Available Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen, while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but

  8. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

  9. The Transcriptional Response of Diverse Saccharomyces cerevisiae Strains to Simulated Microgravity

    Science.gov (United States)

    Neff, Lily S.; Fleury, Samantha T.; Galazka, Jonathan M.

    2018-01-01

    Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and its response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

  10. Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

    Science.gov (United States)

    Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

    2016-09-19

    Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

  11. Increased iron supplied through Fet3p results in replicative life span extension of Saccharomyces cerevisiae under conditions requiring respiratory metabolism.

    Science.gov (United States)

    Botta, Gabriela; Turn, Christina S; Quintyne, Nicholas J; Kirchman, Paul A

    2011-10-01

    We have previously shown that copper supplementation extends the replicative life span of Saccharomyces cerevisiae when grown under conditions forcing cells to respire. We now show that copper's effect on life span is through Fet3p, a copper containing enzyme responsible for high affinity transport of iron into yeast cells. Life span extensions can also be obtained by supplementing the growth medium with 1mM ferric chloride. Extension by high iron levels is still dependent on the presence of Fet3p. Life span extension by iron or copper requires growth on media containing glycerol as the sole carbon source, which forces yeast to respire. Yeast grown on glucose containing media supplemented with iron show no extension of life span. The iron associated with cells grown in media supplemented with copper or iron is 1.4-1.8 times that of cells grown without copper or iron supplementation. As with copper supplementation, iron supplementation partially rescues the life span of superoxide dismutase mutants. Cells grown with copper supplementation display decreased production of superoxide as measured by dihydroethidium staining. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. ATP synthesis in the energy metabolism pathway: a new perspective for manipulating CdSe quantum dots biosynthesized in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Zhang R

    2017-05-01

    Full Text Available Rong Zhang,1–3 Ming Shao,1–3 Xu Han,1–3 Chuan Wang,3–4 Yong Li,3–4 Bin Hu,3–4 Daiwen Pang,3–4 Zhixiong Xie1–31Hubei Key Laboratory of Cell Homeostasis, 2College of Life Sciences, Wuhan University, 3Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education, 4College of Chemistry and Molecular Science, Wuhan University, Wuhan, People’s Republic of ChinaAbstract: Due to a growing trend in their biomedical application, biosynthesized nanomaterials are of great interest to researchers nowadays with their biocompatible, low-energy consumption, economic, and tunable characteristics. It is important to understand the mechanism of biosynthesis in order to achieve more efficient applications. Since there are only rare studies on the influences of cellular energy levels on biosynthesis, the influence of energy is often overlooked. Through determination of the intracellular ATP concentrations during the biosynthesis process, significant changes were observed. In addition, ATP synthesis deficiency caused great decreases in quantum dots (QDs biosynthesis in the Δatp1, Δatp2, Δatp14, and Δatp17 strains. With inductively coupled plasma-atomic emission spectrometry and atomic absorption spectroscopy analyses, it was found that ATP affected the accumulation of the seleno-precursor and helped with the uptake of Cd and the formation of QDs. We successfully enhanced the fluorescence intensity 1.5 or 2 times through genetic modification to increase ATP or SeAM (the seleno analog of S-adenosylmethionine, the product that would accumulate when ATP is accrued. This work explains the mechanism for the correlation of the cellular energy level and QDs biosynthesis in living cells, demonstrates control of the biosynthesis using this mechanism, and thus provides a new manipulation strategy for the biosynthesis of other nanomaterials to widen their applications. Keywords: ATP, biosynthesis, Saccharomyces cerevisiae, QDs, CdSe

  13. Saccharomyces cerevisiae engineered for xylose metabolism requires gluconeogenesis and the oxidative branch of the pentose phosphate pathway for aerobic xylose assimilation

    Science.gov (United States)

    Saccharomyces strains engineered to ferment xylose using Scheffersomyces stipitis xylose reductase (XR) and xylitol dehydrogenase (XDH) genes appear to be limited by metabolic imbalances due to differing cofactor specificities of XR and XDH. The S. stipitis XR, which uses nicotinamide adenine dinucl...

  14. Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening.

    Science.gov (United States)

    Quarterman, Josh; Kim, Soo Rin; Kim, Pan-Jun; Jin, Yong-Su

    2015-01-20

    In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Divergence of iron metabolism in wild Malaysian yeast.

    Science.gov (United States)

    Lee, Hana N; Mostovoy, Yulia; Hsu, Tiffany Y; Chang, Amanda H; Brem, Rachel B

    2013-12-09

    Comparative genomic studies have reported widespread variation in levels of gene expression within and between species. Using these data to infer organism-level trait divergence has proven to be a key challenge in the field. We have used a wild Malaysian population of S. cerevisiae as a test bed in the search to predict and validate trait differences based on observations of regulatory variation. Malaysian yeast, when cultured in standard medium, activated regulatory programs that protect cells from the toxic effects of high iron. Malaysian yeast also showed a hyperactive regulatory response during culture in the presence of excess iron and had a unique growth defect in conditions of high iron. Molecular validation experiments pinpointed the iron metabolism factors AFT1, CCC1, and YAP5 as contributors to these molecular and cellular phenotypes; in genome-scale sequence analyses, a suite of iron toxicity response genes showed evidence for rapid protein evolution in Malaysian yeast. Our findings support a model in which iron metabolism has diverged in Malaysian yeast as a consequence of a change in selective pressure, with Malaysian alleles shifting the dynamic range of iron response to low-iron concentrations and weakening resistance to extreme iron toxicity. By dissecting the iron scarcity specialist behavior of Malaysian yeast, our work highlights the power of expression divergence as a signpost for biologically and evolutionarily relevant variation at the organismal level. Interpreting the phenotypic relevance of gene expression variation is one of the primary challenges of modern genomics.

  16. Rapid prototyping of microbial cell factories via genome-scale engineering.

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2015-11-15

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering

    Science.gov (United States)

    Si, Tong; Xiao, Han; Zhao, Huimin

    2014-01-01

    Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192

  18. Genome-scale modeling of the protein secretory machinery in yeast

    DEFF Research Database (Denmark)

    Feizi, Amir; Österlund, Tobias; Petranovic, Dina

    2013-01-01

    The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...

  19. Metabolism

    Science.gov (United States)

    ... Are More Common in People With Type 1 Diabetes Metabolic Syndrome Your Child's Weight Healthy Eating Endocrine System Blood Test: Basic Metabolic Panel (BMP) Activity: Endocrine System Growth Disorders Diabetes Center Thyroid Disorders Your Endocrine System Movie: Endocrine ...

  20. Inferring metabolic states in uncharacterized environments using gene-expression measurements.

    Directory of Open Access Journals (Sweden)

    Sergio Rossell

    Full Text Available The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of

  1. Invertase SUC2 Is the Key Hydrolase for Inulin Degradation in Saccharomyces cerevisiae

    OpenAIRE

    Wang, Shi-An; Li, Fu-Li

    2013-01-01

    Specific Saccharomyces cerevisiae strains were recently found to be capable of efficiently utilizing inulin, but genetic mechanisms of inulin hydrolysis in yeast remain unknown. Here we report functional characteristics of invertase SUC2 from strain JZ1C and demonstrate that SUC2 is the key enzyme responsible for inulin metabolism in S. cerevisiae.

  2. Development of Efficient Xylose Fermentation in Saccharomyces cerevisiae : Xylose Isomerase as a Key Component

    NARCIS (Netherlands)

    Van Maris, A.J.A.; Winkler, A.A.; Kuyper, M.; De Laat, W.T.; Van Dijken, J.P.; Pronk, J.T.

    2007-01-01

    Metabolic engineering of Saccharomyces cerevisiae for ethanol production from d-xylose, an abundant sugar in plant biomass hydrolysates, has been pursued vigorously for the past 15 years. Whereas wild-type S. cerevisiae cannot ferment d-xylose, the ketoisomer d-xylulose can be metabolised slowly.

  3. Modular Ligation Extension of Guide RNA Operons (LEGO) for Multiplexed dCas9 Regulation of Metabolic Pathways in Saccharomyces cerevisiae.

    Science.gov (United States)

    Deaner, Matthew; Holzman, Allison; Alper, Hal S

    2018-04-16

    Metabolic engineering typically utilizes a suboptimal step-wise gene target optimization approach to parse a highly connected and regulated cellular metabolism. While the endonuclease-null CRISPR/Cas system has enabled gene expression perturbations without genetic modification, it has been mostly limited to small sets of gene targets in eukaryotes due to inefficient methods to assemble and express large sgRNA operons. In this work, we develop a TEF1p-tRNA expression system and demonstrate that the use of tRNAs as splicing elements flanking sgRNAs provides higher efficiency than both Pol III and ribozyme-based expression across a variety of single sgRNA and multiplexed contexts. Next, we devise and validate a scheme to allow modular construction of tRNA-sgRNA (TST) operons using an iterative Type IIs digestion/ligation extension approach, termed CRISPR-Ligation Extension of sgRNA Operons (LEGO). This approach enables facile construction of large TST operons. We demonstrate this utility by constructing a metabolic rewiring prototype for 2,3-butanediol production in 2 distinct yeast strain backgrounds. These results demonstrate that our approach can act as a surrogate for traditional genetic modification on a much shorter design-cycle timescale. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Predicting the accumulation of storage compounds by Rhodococcus jostii RHA1 in the feast-famine growth cycles using genome-scale flux balance analysis.

    Science.gov (United States)

    Tajparast, Mohammad; Frigon, Dominic

    2018-01-01

    Feast-famine cycles in biological wastewater resource recovery systems select for bacterial species that accumulate intracellular storage compounds such as poly-β-hydroxybutyrate (PHB), glycogen, and triacylglycerols (TAG). These species survive better the famine phase and resume rapid substrate uptake at the beginning of the feast phase faster than microorganisms unable to accumulate storage. However, ecophysiological conditions favouring the accumulation of either storage compounds remain to be clarified, and predictive capabilities need to be developed to eventually rationally design reactors producing these compounds. Using a genome-scale metabolic modelling approach, the storage metabolism of Rhodococcus jostii RHA1 was investigated for steady-state feast-famine cycles on glucose and acetate as the sole carbon sources. R. jostii RHA1 is capable of accumulating the three storage compounds (PHB, TAG, and glycogen) simultaneously. According to the experimental observations, when glucose was the substrate, feast phase chemical oxygen demand (COD) accumulation was similar for the three storage compounds; when acetate was the substrate, however, PHB accumulation was 3 times higher than TAG accumulation and essentially no glycogen was accumulated. These results were simulated using the genome-scale metabolic model of R. jostii RHA1 (iMT1174) by means of flux balance analysis (FBA) to determine the objective functions capable of predicting these behaviours. Maximization of the growth rate was set as the main objective function, while minimization of total reaction fluxes and minimization of metabolic adjustment (environmental MOMA) were considered as the sub-objective functions. The environmental MOMA sub-objective performed better than the minimization of total reaction fluxes sub-objective function at predicting the mixture of storage compounds accumulated. Additional experiments with 13C-labelled bicarbonate (HCO3-) found that the fluxes through the central

  5. A genetic screen for increasing metabolic flux in the isoprenoid pathway of Saccharomyces cerevisiae: Isolation of SPT15 mutants using the screen

    Directory of Open Access Journals (Sweden)

    M. Wadhwa

    2016-12-01

    Full Text Available A genetic screen to identify mutants that can increase flux in the isoprenoid pathway of yeast has been lacking. We describe a carotenoid-based visual screen built with the core carotenogenic enzymes from the red yeast Rhodosporidium toruloides. Enzymes from this yeast displayed the required, higher capacity in the carotenoid pathway. The development also included the identification of the metabolic bottlenecks, primarily phytoene dehydrogenase, that was subjected to a directed evolution strategy to yield more active mutants. To further limit phytoene pools, a less efficient version of GGPP synthase was employed. The screen was validated with a known flux increasing gene, tHMG1. New mutants in the TATA binding protein SPT15 were isolated using this screen that increased the yield of carotenoids, and an alternate isoprenoid, α-Farnesene confirming increase in overall flux. The findings indicate the presence of previously unknown links to the isoprenoid pathway that can be uncovered using this screen. Keywords: Metabolic engineering, Carotenoids, Isoprenoids, α-Farnesene, Rhodosporidium toruloides, SPT15

  6. From genomes to in silico cells via metabolic networks

    DEFF Research Database (Denmark)

    Borodina, Irina; Nielsen, Jens

    2005-01-01

    Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

  7. Sucrose and Saccharomyces cerevisiae: a relationship most sweet.

    Science.gov (United States)

    Marques, Wesley Leoricy; Raghavendran, Vijayendran; Stambuk, Boris Ugarte; Gombert, Andreas Karoly

    2016-02-01

    Sucrose is an abundant, readily available and inexpensive substrate for industrial biotechnology processes and its use is demonstrated with much success in the production of fuel ethanol in Brazil. Saccharomyces cerevisiae, which naturally evolved to efficiently consume sugars such as sucrose, is one of the most important cell factories due to its robustness, stress tolerance, genetic accessibility, simple nutrient requirements and long history as an industrial workhorse. This minireview is focused on sucrose metabolism in S. cerevisiae, a rather unexplored subject in the scientific literature. An analysis of sucrose availability in nature and yeast sugar metabolism was performed, in order to understand the molecular background that makes S. cerevisiae consume this sugar efficiently. A historical overview on the use of sucrose and S. cerevisiae by humans is also presented considering sugarcane and sugarbeet as the main sources of this carbohydrate. Physiological aspects of sucrose consumption are compared with those concerning other economically relevant sugars. Also, metabolic engineering efforts to alter sucrose catabolism are presented in a chronological manner. In spite of its extensive use in yeast-based industries, a lot of basic and applied research on sucrose metabolism is imperative, mainly in fields such as genetics, physiology and metabolic engineering. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  8. Metabolism

    Science.gov (United States)

    ... lin), which signals cells to increase their anabolic activities. Metabolism is a complicated chemical process, so it's not ... how those enzymes or hormones work. When the metabolism of body chemicals is ... Hyperthyroidism (pronounced: hi-per-THIGH-roy-dih-zum). Hyperthyroidism ...

  9. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    Energy Technology Data Exchange (ETDEWEB)

    Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

    2016-01-28

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

  10. Moving image analysis to the cloud: A case study with a genome-scale tomographic study

    International Nuclear Information System (INIS)

    Mader, Kevin; Stampanoni, Marco

    2016-01-01

    Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures

  11. Genome-scale analysis of positional clustering of mouse testis-specific genes

    Directory of Open Access Journals (Sweden)

    Lee Bernett TK

    2005-01-01

    Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.

  12. Targeted and genome-scale methylomics reveals gene body signatures in human cell lines

    Science.gov (United States)

    Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.

    2012-01-01

    Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998

  13. [Saccharomyces cerevisiae infections].

    Science.gov (United States)

    Souza Goebel, Cristine; de Mattos Oliveira, Flávio; Severo, Luiz Carlos

    2013-01-01

    Saccharomyces cerevisiae is an ubiquitous yeast widely used in industry and it is also a common colonizer of the human mucosae. However, the incidence of invasive infection by these fungi has significantly increased in the last decades. To evaluate the infection by S. cerevisiae in a hospital in southern Brazil during a period of 10 years (2000-2010). Review of medical records of patients infected by this fungus. In this period, 6 patients were found to be infected by S. cerevisiae. The age range of the patients was from 10 years to 84. Urine, blood, ascitic fluid, peritoneal dialysis fluid, and esophageal biopsy samples were analyzed. The predisposing factors were cancer, transplant, surgical procedures, renal failure, use of venous catheters, mechanical ventilation, hospitalization in Intensive Care Unit, diabetes mellitus, chemotherapy, corticosteroid use, and parenteral nutrition. Amphotericin B and fluconazole were the treatments of choice. Three of the patients died and the other 3 were discharged from hospital. We must take special precautions in emerging infections, especially when there are predisposing conditions such as immunosuppression or patients with serious illnesses. The rapid and specific diagnosis of S. cerevisiae infections is important for therapeutic decision. Furthermore, epidemiological and efficacy studies of antifungal agents are necessary for a better therapeutic approach. Copyright © 2012 Revista Iberoamericana de Micología. Published by Elsevier Espana. All rights reserved.

  14. [Mitochondria inheritance in yeast saccharomyces cerevisiae].

    Science.gov (United States)

    Fizikova, A Iu

    2011-01-01

    The review is devoted to the main mechanisms of mitochondria inheritance in yeast Saccharonmyces cerevisiae. The genetic mechanisms of functionally active mitochondria inheritance in eukaryotic cells is one of the most relevant in modem researches. A great number of genetic diseases are associated with mitochondria dysfunction. Plasticity of eukaryotic cell metabolism according to the environmental changes is ensured by adequate mitochondria functioning by means of ATP synthesis coordination, reactive oxygen species accumulation, apoptosis regulation and is an important factor of cell adaptation to stress. Mitochondria participation in important for cell vitality processes masters the presence of accurate mechanisms of mitochondria functions regulation according to environment fluctuations. The mechanisms of mitochondria division and distribution are highly conserved. Baker yeast S. cerevisiae is an ideal model object for mitochondria researches due to energetic metabolism lability, ability to switch over respiration to fermentation, and petite-positive phenotype. Correction of metabolism according to the environmental changes is necessary for cell vitality. The influence of respiratory, carbon, amino acid and phosphate metabolism on mitochondria functions was shown. As far as the mechanisms that stabilize functions of mitochondria and mtDNA are highly conserve, we can project yeast regularities on higher eukaryotes systems. This makes it possible to approximate understanding the etiology and pathogenesis of a great number of human diseases.

  15. Thermodynamic principles governing metabolic operation : inference, analysis, and prediction

    NARCIS (Netherlands)

    Niebel, Bastian

    2015-01-01

    The principles governing metabolic flux are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that fundamental thermodynamic constraints might shape cellular metabolism. We developed a constraint-based model for Saccharomyces cerevisiae that included

  16. RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

    Science.gov (United States)

    Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

    2013-11-01

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

  17. Reducing the genetic complexity of glycolysis in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Solis Escalante, D.

    2015-01-01

    Glycolysis, a biochemical pathway that oxidizes glucose to pyruvate, is at the core of sugar metabolism in Saccharomyces cerevisiae (bakers’ yeast). Glycolysis is not only a catabolic route involved in energy conservation, but also provides building blocks for anabolism. From an applied perspective,

  18. Switching the mode of sucrose utilization by Saccharomyces cerevisiae

    OpenAIRE

    Badotti, Fernanda; Dário, Marcelo G; Alves, Sergio L; Cordioli, Maria Luiza A; Miletti, Luiz C; de Araujo, Pedro S; Stambuk, Boris U

    2008-01-01

    Abstract Background Overflow metabolism is an undesirable characteristic of aerobic cultures of Saccharomyces cerevisiae during biomass-directed processes. It results from elevated sugar consumption rates that cause a high substrate conversion to ethanol and other bi-products, severely affecting cell physiology, bioprocess performance, and biomass yields. Fed-batch culture, where sucro...

  19. Effects of various types of stress on the metabolism of reserve carbohydrates in Saccharomyces cerevisiae: genetic evidence for a stress-induced recycling of glycogen and trehalose.

    Science.gov (United States)

    Parrou, J L; Teste, M A; François, J

    1997-06-01

    It is well known that glycogen and trehalose accumulate in yeast under nutrient starvation or entering into the stationary phase of growth, and that high levels of trehalose are found in heat-shocked cells. However, effects of various types of stress on trehalose, and especially on glycogen, are poorly documented. Taking into account that almost all genes encoding the enzymes involved in the metabolism of these two reserve carbohydrates contain between one and several copies of the stress-responsive element (STRE), an investigation was made of the possibility of a link between the potential transcriptional induction of these genes and the accumulation of glycogen and trehalose under different stress conditions. Using transcriptional fusions, it was found that all these genes were induced in a similar fashion, although to various extents, by temperature, osmotic and oxidative stresses. Experiments performed with an msn2/msn4 double mutant proved that the transcriptional induction of the genes encoding glycogen synthase (GSY2) and trehalose-6-phosphate synthase (TPS1) was needed for the small increase in glycogen and trehalose upon exposure to a mild heat stress and salt shock. However, the extent of transcriptional activation of these genes upon stresses in wild-type strains was not correlated with a proportional rise in either glycogen or trehalose. The major explanation for this lack of correlation comes from the fact that genes encoding the enzymes of the biosynthetic and of the biodegradative pathways were almost equally induced. Hence, trehalose and glycogen accumulated to much higher levels in cells lacking neutral trehalose or glycogen phosphorylase exposed to stress conditions, which suggested that one of the major effects of stress in yeast is to induce a wasteful expenditure of energy by increasing the recycling of these molecules. We also found that transcriptional induction of STRE-controlled genes was abolished at temperatures above 40 degree C, while

  20. GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

    Directory of Open Access Journals (Sweden)

    Radhakrishnan Mahadevan

    2012-10-01

    With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  1. Engineering strategy of yeast metabolism for higher alcohol production

    Directory of Open Access Journals (Sweden)

    Shimizu Hiroshi

    2011-09-01

    Full Text Available Abstract Background While Saccharomyces cerevisiae is a promising host for cost-effective biorefinary processes due to its tolerance to various stresses during fermentation, the metabolically engineered S. cerevisiae strains exhibited rather limited production of higher alcohols than that of Escherichia coli. Since the structure of the central metabolism of S. cerevisiae is distinct from that of E. coli, there might be a problem in the structure of the central metabolism of S. cerevisiae. In this study, the potential production of higher alcohols by S. cerevisiae is compared to that of E. coli by employing metabolic simulation techniques. Based on the simulation results, novel metabolic engineering strategies for improving higher alcohol production by S. cerevisiae were investigated by in silico modifications of the metabolic models of S. cerevisiae. Results The metabolic simulations confirmed that the high production of butanols and propanols by the metabolically engineered E. coli strains is derived from the flexible behavior of their central metabolism. Reducing this flexibility by gene deletion is an effective strategy to restrict the metabolic states for producing target alcohols. In contrast, the lower yield using S. cerevisiae originates from the structurally limited flexibility of its central metabolism in which gene deletions severely reduced cell growth. Conclusions The metabolic simulation demonstrated that the poor productivity of S. cerevisiae was improved by the introduction of E. coli genes to compensate the structural difference. This suggested that gene supplementation is a promising strategy for the metabolic engineering of S. cerevisiae to produce higher alcohols which should be the next challenge for the synthetic bioengineering of S. cerevisiae for the efficient production of higher alcohols.

  2. The architecture of ArgR-DNA complexes at the genome-scale in Escherichia coli

    DEFF Research Database (Denmark)

    Cho, Suhyung; Cho, Yoo-Bok; Kang, Taek Jin

    2015-01-01

    DNA-binding motifs that are recognized by transcription factors (TFs) have been well studied; however, challenges remain in determining the in vivo architecture of TF-DNA complexes on a genome-scale. Here, we determined the in vivo architecture of Escherichia coli arginine repressor (ArgR)-DNA co...

  3. Growth-rate dependency of de novo resveratrol production in chemostat cultures of an engineered Saccharomyces cerevisiae strain

    NARCIS (Netherlands)

    Vos, T.; De la Torre Cortes, P.; Van Gulik, W.M.; Pronk, J.T.; Daran-Lapujade, P.A.S.

    2015-01-01

    Introduction: Saccharomyces cerevisiae has become a popular host for production of non-native compounds. The metabolic pathways involved generally require a net input of energy. To maximize the ATP yield on sugar in S. cerevisiae, industrial cultivation is typically performed in aerobic,

  4. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

    Science.gov (United States)

    Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

    2011-07-26

    Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  5. Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

    Science.gov (United States)

    Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

    2012-01-01

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

  6. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows

    Directory of Open Access Journals (Sweden)

    Sztromwasser Paweł

    2011-06-01

    Full Text Available Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  7. Survey of protein–DNA interactions in Aspergillus oryzae on a genomic scale

    Science.gov (United States)

    Wang, Chao; Lv, Yangyong; Wang, Bin; Yin, Chao; Lin, Ying; Pan, Li

    2015-01-01

    The genome-scale delineation of in vivo protein–DNA interactions is key to understanding genome function. Only ∼5% of transcription factors (TFs) in the Aspergillus genus have been identified using traditional methods. Although the Aspergillus oryzae genome contains >600 TFs, knowledge of the in vivo genome-wide TF-binding sites (TFBSs) in aspergilli remains limited because of the lack of high-quality antibodies. We investigated the landscape of in vivo protein–DNA interactions across the A. oryzae genome through coupling the DNase I digestion of intact nuclei with massively parallel sequencing and the analysis of cleavage patterns in protein–DNA interactions at single-nucleotide resolution. The resulting map identified overrepresented de novo TF-binding motifs from genomic footprints, and provided the detailed chromatin remodeling patterns and the distribution of digital footprints near transcription start sites. The TFBSs of 19 known Aspergillus TFs were also identified based on DNase I digestion data surrounding potential binding sites in conjunction with TF binding specificity information. We observed that the cleavage patterns of TFBSs were dependent on the orientation of TF motifs and independent of strand orientation, consistent with the DNA shape features of binding motifs with flanking sequences. PMID:25883143

  8. GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing.

    Science.gov (United States)

    Wang, Xuewen; Wang, Le

    2016-01-01

    Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

  9. Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

    DEFF Research Database (Denmark)

    Liu, Lifang; Feizi, Amir; Osterlund, Tobias

    2014-01-01

    related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three a-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER......Background: The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due...... to the poorly annotated proteome. Results: Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely...

  10. Noise analysis of genome-scale protein synthesis using a discrete computational model of translation

    Energy Technology Data Exchange (ETDEWEB)

    Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-07-28

    Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.

  11. Genome-scale analysis of aberrant DNA methylation in colorectal cancer

    Science.gov (United States)

    Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.

    2012-01-01

    Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424

  12. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional....... While many large-scale TRN reconstructions have been reported for yeast, these reconstructions still need to be improved regarding the functionality and dynamic property of the regulatory interactions. In addition, mathematical modeling approaches need to be further developed to efficiently integrate...

  13. Recon2Neo4j: applying graph database technologies for managing comprehensive genome-scale networks.

    Science.gov (United States)

    Balaur, Irina; Mazein, Alexander; Saqi, Mansoor; Lysenko, Artem; Rawlings, Christopher J; Auffray, Charles

    2017-04-01

    The goal of this work is to offer a computational framework for exploring data from the Recon2 human metabolic reconstruction model. Advanced user access features have been developed using the Neo4j graph database technology and this paper describes key features such as efficient management of the network data, examples of the network querying for addressing particular tasks, and how query results are converted back to the Systems Biology Markup Language (SBML) standard format. The Neo4j-based metabolic framework facilitates exploration of highly connected and comprehensive human metabolic data and identification of metabolic subnetworks of interest. A Java-based parser component has been developed to convert query results (available in the JSON format) into SBML and SIF formats in order to facilitate further results exploration, enhancement or network sharing. The Neo4j-based metabolic framework is freely available from: https://diseaseknowledgebase.etriks.org/metabolic/browser/ . The java code files developed for this work are available from the following url: https://github.com/ibalaur/MetabolicFramework . ibalaur@eisbm.org. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  14. Reconstruction and Quality Control of a Genome-Scale Metabolic Model for Methylococcus capsulatus

    DEFF Research Database (Denmark)

    Lieven, Christian

    Climate-change induced food scarcity is a grim prospect for the future of humanity. Alas, increasingly detrimental effects of global warming and overpopulation are predicted to beget this outlook by the year 2050. Fortunately, the production of single-cell protein (SCP) from microbial fermentations...

  15. Genome-scale metabolic model of Pichia pastoris with native and humanized glycosylation of recombinant proteins

    DEFF Research Database (Denmark)

    Irani, Zahra Azimzadeh; Kerkhoven, Eduard J.; Shojaosadati, Seyed Abbas

    2016-01-01

    prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required...... for using these models to understand and optimize protein production processes....

  16. Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach.

    Science.gov (United States)

    Knies, David; Wittmüß, Philipp; Appel, Sebastian; Sawodny, Oliver; Ederer, Michael; Feuer, Ronny

    2015-10-28

    The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA) that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

  17. Modeling and Simulation of Optimal Resource Management during the Diurnal Cycle in Emiliania huxleyi by Genome-Scale Reconstruction and an Extended Flux Balance Analysis Approach

    Directory of Open Access Journals (Sweden)

    David Knies

    2015-10-01

    Full Text Available The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.

  18. LocateP: Genome-scale subcellular-location predictor for bacterial proteins

    Directory of Open Access Journals (Sweden)

    Zhou Miaomiao

    2008-03-01

    Full Text Available Abstract Background In the past decades, various protein subcellular-location (SCL predictors have been developed. Most of these predictors, like TMHMM 2.0, SignalP 3.0, PrediSi and Phobius, aim at the identification of one or a few SCLs, whereas others such as CELLO and Psortb.v.2.0 aim at a broader classification. Although these tools and pipelines can achieve a high precision in the accurate prediction of signal peptides and transmembrane helices, they have a much lower accuracy when other sequence characteristics are concerned. For instance, it proved notoriously difficult to identify the fate of proteins carrying a putative type I signal peptidase (SPIase cleavage site, as many of those proteins are retained in the cell membrane as N-terminally anchored membrane proteins. Moreover, most of the SCL classifiers are based on the classification of the Swiss-Prot database and consequently inherited the inconsistency of that SCL classification. As accurate and detailed SCL prediction on a genome scale is highly desired by experimental researchers, we decided to construct a new SCL prediction pipeline: LocateP. Results LocateP combines many of the existing high-precision SCL identifiers with our own newly developed identifiers for specific SCLs. The LocateP pipeline was designed such that it mimics protein targeting and secretion processes. It distinguishes 7 different SCLs within Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally membrane anchored, C-terminally membrane anchored, lipid-anchored, LPxTG-type cell-wall anchored, and secreted/released proteins. Moreover, it distinguishes pathways for Sec- or Tat-dependent secretion and alternative secretion of bacteriocin-like proteins. The pipeline was tested on data sets extracted from literature, including experimental proteomics studies. The tests showed that LocateP performs as well as, or even slightly better than other SCL predictors for some locations and outperforms

  19. Genome-scale Evaluation of the Biotechnological Potential of Red Sea Bacilli Strains

    KAUST Repository

    Othoum, Ghofran K.

    2018-01-01

    production of industrial enzymes has encouraged the screening of new environments for efficient microbial cell factories. The unique ecological niche of the Red Sea points to the promising metabolic and biosynthetic potential of its microbial system. Here

  20. Energy-dependent effects of resveratrol in Saccharomyces cerevisiae.

    Science.gov (United States)

    Madrigal-Perez, Luis Alberto; Canizal-Garcia, Melina; González-Hernández, Juan Carlos; Reynoso-Camacho, Rosalia; Nava, Gerardo M; Ramos-Gomez, Minerva

    2016-06-01

    The metabolic effects induced by resveratrol have been associated mainly with the consumption of high-calorie diets; however, its effects with standard or low-calorie diets remain unclear. To better understand the interactions between resveratrol and cellular energy levels, we used Saccharomyces cerevisiae as a model. Herein it is shown that resveratrol: (a) decreased cell viability in an energy-dependent manner; (b) lessening of cell viability occurred specifically when cells were under cellular respiration; and (c) inhibition of oxygen consumption in state 4 occurred at low and standard energy levels, whereas at high energy levels oxygen consumption was promoted. These findings indicate that the effects of resveratrol are dependent on the cellular energy status and linked to metabolic respiration. Importantly, our study also revealed that S. cerevisiae is a suitable and useful model to elucidate the molecular targets of resveratrol under different nutritional statuses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Fungal genomics beyond Saccharomyces cerevisiae?

    DEFF Research Database (Denmark)

    Hofmann, Gerald; Mcintyre, Mhairi; Nielsen, Jens

    2003-01-01

    Fungi are used extensively in both fundamental research and industrial applications. Saccharomyces cerevisiae has been the model organism for fungal research for many years, particularly in functional genomics. However, considering the diversity within the fungal kingdom, it is obvious...

  2. Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

    Science.gov (United States)

    Liu, Lifang; Feizi, Amir; Österlund, Tobias; Hjort, Carsten; Nielsen, Jens

    2014-06-24

    The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.

  3. Microarray analysis of serum mRNA in patients with head and neck squamous cell carcinoma at whole-genome scale

    Czech Academy of Sciences Publication Activity Database

    Čapková, M.; Šáchová, Jana; Strnad, Hynek; Kolář, Michal; Hroudová, Miluše; Chovanec, M.; Čada, Z.; Štefl, M.; Valach, J.; Kastner, J.; Smetana, K. Jr.; Plzák, J.

    -, April 23 (2014) ISSN 2314-6141 R&D Projects: GA MZd(CZ) NT13488 Institutional support: RVO:68378050 Keywords : Microarray Analysis * Head and Neck Squamous Cell Carcinoma * whole-genome scale Subject RIV: EB - Genetics ; Molecular Biology

  4. Applied systems biology - vanillin production in Saccharomyces cerevisiae

    OpenAIRE

    Strucko, Tomas; Eriksen, Jens Christian; Nielsen, J.; Mortensen, Uffe Hasbro

    2012-01-01

    Vanillin is the most important aroma compound based on market value, and natural vanillin is extracted from the cured seed pods of the Vanilla orchid. Most of the world’s vanillin, however, is obtained by chemical synthesis from petrochemicals or wood pulp lignins. As an alternative, de novo biosynthesis of vanillin in baker’s yeast Saccharomyces cerevisiae was recently demonstrated by successfully introducing the metabolic pathway for vanillin production in yeast. Nevertheless, the amount of...

  5. Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

    Science.gov (United States)

    Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

    2008-06-18

    Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

  6. Metabollic Engineering of Saccharomyces Cereviae a,omi acid metabolism for production of products of industrial interest

    DEFF Research Database (Denmark)

    Chen, Xiao

    -based processes. This study has focused on metabolic engineering of the amino acid metabolism in S. cerevisiae for production of two types of chemicals of industrial interest. The first chemical is δ-(L-α-aminoadipyl)–L-cysteinyl–D-valine (LLD-ACV). ACV belongs to non-ribosomal peptides (NRPs), which......Saccharomyces cerevisiae is widely used in microbial production of chemicals, metabolites and proteins, mainly because genetic manipulation of S. cerevisiae is relatively easy and experiences from its wide application in the existing industrial fermentations directly benefit new S. cerevisiae...

  7. Reconstructing the backbone of the Saccharomycotina yeast phylogeny using genome-scale data

    Science.gov (United States)

    Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multi-locus data sets has greatly advanced our understanding ...

  8. 21 CFR 866.5785 - Anti-Saccharomyces cerevisiae (S. cerevisiae) antibody (ASCA) test systems.

    Science.gov (United States)

    2010-04-01

    ...) antibody (ASCA) test systems. 866.5785 Section 866.5785 Food and Drugs FOOD AND DRUG ADMINISTRATION... Immunological Test Systems § 866.5785 Anti-Saccharomyces cerevisiae (S. cerevisiae) antibody (ASCA) test systems. (a) Identification. The Anti-Saccharomyces cerevisiae (S. cerevisiae) antibody (ASCA) test system is...

  9. Using proteomic data to assess a genome-scale "in silico" model of metal reducing bacteria in the simulation of field-scale uranium bioremediation

    Science.gov (United States)

    Yabusaki, S.; Fang, Y.; Wilkins, M. J.; Long, P.; Rifle IFRC Science Team

    2011-12-01

    A series of field experiments in a shallow alluvial aquifer at a former uranium mill tailings site have demonstrated that indigenous bacteria can be stimulated with acetate to catalyze the conversion of hexavalent uranium in a groundwater plume to immobile solid-associated uranium in the +4 oxidation state. While this bioreduction of uranium has been shown to lower groundwater concentrations below actionable standards, a viable remediation methodology will need a mechanistic, predictive and quantitative understanding of the microbially-mediated reactions that catalyze the reduction of uranium in the context of site-specific processes, properties, and conditions. At the Rifle IFRC site, we are investigating the impacts on uranium behavior of pulsed acetate amendment, acetate-oxidizing iron and sulfate reducing bacteria, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. The simulation of three-dimensional, variably saturated flow and biogeochemical reactive transport during a uranium bioremediation field experiment includes a genome-scale in silico model of Geobacter sp. to represent the Fe(III) terminal electron accepting process (TEAP). The Geobacter in silico model of cell-scale physiological metabolic pathways is comprised of hundreds of intra-cellular and environmental exchange reactions. One advantage of this approach is that the TEAP reaction stoichiometry and rate are now functions of the metabolic status of the microorganism. The linkage of in silico model reactions to specific Geobacter proteins has enabled the use of groundwater proteomic analyses to assess the accuracy of the model under evolving hydrologic and biogeochemical conditions. In this case, the largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions (e.g. the condensation reaction catalyzed by the protein

  10. Microbial cells as biosorbents for heavy metals: accumulation of Uranium by Saccharomyces cerevisiae and Pseudomonas aeruginosa

    International Nuclear Information System (INIS)

    Strandberg, G.W.; Shumate, S.E. II; Parrott, J.R. Jr.

    1981-01-01

    Uranium accumulated extracellularly on the surfaces of Saccharomyces cerevisiae cells. The rate and extent of accumulation were subject to environmental parameters, such as pH, temperature, and interference by certain anions and cations. Uranium accumulation by Pseudomonas aeruginosa occurred intracellularly and was extremely rapid (<10 s), and no response to environmental parameters could be detected. Metabolism was not required for metal uptake by either organism. Cell-bound uranium reached a concentration of 10 to 15% of the dry cell weight, but only 32% of the S. cerevisiae cells and 44% of the P. aeruginosa cells within a given population possessed visible uranium deposits when examined by electron microscopy. Rates of uranium uptake by S. cerevisiae were increased by chemical pretreatment of the cells. Uranium could be removed chemically from S. cerevisiae cells, and the cells could then be reused as a biosorbent

  11. Enhancing Fatty Acid Production of Saccharomyces cerevisiae as an Animal Feed Supplement.

    Science.gov (United States)

    You, Seung Kyou; Joo, Young-Chul; Kang, Dae Hee; Shin, Sang Kyu; Hyeon, Jeong Eun; Woo, Han Min; Um, Youngsoon; Park, Chulhwan; Han, Sung Ok

    2017-12-20

    Saccharomyces cerevisiae is used for edible purposes, such as human food or as an animal feed supplement. Fatty acids are also beneficial as feed supplements, but S. cerevisiae produces small amounts of fatty acids. In this study, we enhanced fatty acid production of S. cerevisiae by overexpressing acetyl-CoA carboxylase, thioesterase, and malic enzyme associated with fatty acid metabolism. The enhanced strain pAMT showed 2.4-fold higher fatty acids than the wild-type strain. To further increase the fatty acids, various nitrogen sources were analyzed and calcium nitrate was selected as an optimal nitrogen source for fatty acid production. By concentration optimization, 672 mg/L of fatty acids was produced, which was 4.7-fold higher than wild-type strain. These results complement the low level fatty acid production and make it possible to obtain the benefits of fatty acids as an animal feed supplement while, simultaneously, maintaining the advantages of S. cerevisiae.

  12. Generalized framework for context-specific metabolic model extraction methods

    Directory of Open Access Journals (Sweden)

    Semidán eRobaina Estévez

    2014-09-01

    Full Text Available Genome-scale metabolic models are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application.

  13. Genome-scale portrait and evolutionary significance of human-specific core promoter tri- and tetranucleotide short tandem repeats.

    Science.gov (United States)

    Nazaripanah, N; Adelirad, F; Delbari, A; Sahaf, R; Abbasi-Asl, T; Ohadi, M

    2018-04-05

    While there is an ongoing trend to identify single nucleotide substitutions (SNSs) that are linked to inter/intra-species differences and disease phenotypes, short tandem repeats (STRs)/microsatellites may be of equal (if not more) importance in the above processes. Genes that contain STRs in their promoters have higher expression divergence compared to genes with fixed or no STRs in the gene promoters. In line with the above, recent reports indicate a role of repetitive sequences in the rise of young transcription start sites (TSSs) in human evolution. Following a comparative genomics study of all human protein-coding genes annotated in the GeneCards database, here we provide a genome-scale portrait of human-specific short- and medium-size (≥ 3-repeats) tri- and tetranucleotide STRs and STR motifs in the critical core promoter region between - 120 and + 1 to the TSS and evidence of skewing of this compartment in reference to the STRs that are not human-specific (Levene's test p human-specific transcripts was detected in the tri and tetra human-specific compartments (mid-p genome-scale skewing of STRs at a specific region of the human genome and a link between a number of these STRs and TSS selection/transcript specificity. The STRs and genes listed here may have a role in the evolution and development of characteristics and phenotypes that are unique to the human species.

  14. Effects of fermentation by Saccharomyces cerevisiae and ...

    African Journals Online (AJOL)

    yassine

    2013-02-13

    Feb 13, 2013 ... Effect of Saccharomyces cerevisiae fermentation on the ... beetroot, fermentation, Saccharomyces cerevisiae, betalain compounds. ... by Saccharomyces cerevisiae strains (González et al., .... Both red and yellow pigments were influenced during S. .... in beverages such as white wine, grape fruit, and green.

  15. Integrative proteomics and biochemical analyses define Ptc6p as the Saccharomyces cerevisiae pyruvate dehydrogenase phosphatase.

    Science.gov (United States)

    Guo, Xiao; Niemi, Natalie M; Coon, Joshua J; Pagliarini, David J

    2017-07-14

    The pyruvate dehydrogenase complex (PDC) is the primary metabolic checkpoint connecting glycolysis and mitochondrial oxidative phosphorylation and is important for maintaining cellular and organismal glucose homeostasis. Phosphorylation of the PDC E1 subunit was identified as a key inhibitory modification in bovine tissue ∼50 years ago, and this regulatory process is now known to be conserved throughout evolution. Although Saccharomyces cerevisiae is a pervasive model organism for investigating cellular metabolism and its regulation by signaling processes, the phosphatase(s) responsible for activating the PDC in S. cerevisiae has not been conclusively defined. Here, using comparative mitochondrial phosphoproteomics, analyses of protein-protein interactions by affinity enrichment-mass spectrometry, and in vitro biochemistry, we define Ptc6p as the primary PDC phosphatase in S. cerevisiae Our analyses further suggest additional substrates for related S. cerevisiae phosphatases and describe the overall phosphoproteomic changes that accompany mitochondrial respiratory dysfunction. In summary, our quantitative proteomics and biochemical analyses have identified Ptc6p as the primary-and likely sole- S. cerevisiae PDC phosphatase, closing a key knowledge gap about the regulation of yeast mitochondrial metabolism. Our findings highlight the power of integrative omics and biochemical analyses for annotating the functions of poorly characterized signaling proteins. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  16. Saccharomyces cerevisiae in the Production of Fermented Beverages

    Directory of Open Access Journals (Sweden)

    Graeme M Walker

    2016-11-01

    Full Text Available Alcoholic beverages are produced following the fermentation of sugars by yeasts, mainly (but not exclusively strains of the species, Saccharomyces cerevisiae. The sugary starting materials may emanate from cereal starches (which require enzymatic pre-hydrolysis in the case of beers and whiskies, sucrose-rich plants (molasses or sugar juice from sugarcane in the case of rums, or from fruits (which do not require pre-hydrolysis in the case of wines and brandies. In the presence of sugars, together with other essential nutrients such as amino acids, minerals and vitamins, S. cerevisiae will conduct fermentative metabolism to ethanol and carbon dioxide (as the primary fermentation metabolites as the cells strive to make energy and regenerate the coenzyme NAD+ under anaerobic conditions. Yeasts will also produce numerous secondary metabolites which act as important beverage flavour congeners, including higher alcohols, esters, carbonyls and sulphur compounds. These are very important in dictating the final flavour and aroma characteristics of beverages such as beer and wine, but also in distilled beverages such as whisky, rum and brandy. Therefore, yeasts are of vital importance in providing the alcohol content and the sensory profiles of such beverages. This Introductory Chapter reviews, in general, the growth, physiology and metabolism of S. cerevisiae in alcoholic beverage fermentations.

  17. Genome-scale Evaluation of the Biotechnological Potential of Red Sea Bacilli Strains

    KAUST Repository

    Othoum, Ghofran K.

    2018-02-01

    The increasing spectrum of multidrug-resistant bacteria has caused a major global public health concern, necessitating the discovery of novel antimicrobial agents. Additionally, recent advancements in the use of microbial cells for the scalable production of industrial enzymes has encouraged the screening of new environments for efficient microbial cell factories. The unique ecological niche of the Red Sea points to the promising metabolic and biosynthetic potential of its microbial system. Here, ten sequenced Bacilli strains, that are isolated from microbial mat and mangrove mud samples from the Red Sea, were evaluated for their use as platforms for protein production and biosynthesis of bioactive compounds. Two of the species (B.paralicheniformis Bac48 and B. litoralis Bac94) were found to secrete twice as much protein as Bacillus subtilis 168, and B. litoralis Bac94 had complete Tat and Sec protein secretion systems. Additionally, four Red Sea Species (B. paralicheniformis Bac48, Virgibacillus sp. Bac330, B. vallismortis Bac111, B. amyloliquefaciens Bac57) showed capabilities for genetic transformation and possessed competence genes. More specifically, the distinctive biosynthetic potential evident in the genomes of B. paralicheniformis Bac48 and B. paralicheniformis Bac84 was assessed and compared to nine available complete genomes of B. licheniformis and three genomes of B. paralicheniformis. A uniquely-structured trans-acyltransferase (trans-AT) polyketide synthase/nonribosomal peptide synthetase (PKS/NRPS) cluster in strains of this species was identified in the genome of B. paralicheniformis 48. In total, the two B. paralicheniformis Red Sea strains were found to be more enriched in modular clusters compared to B. licheniformis strains and B. paralicheniformis strains from other environments. These findings provided more insights into the potential of B. paralicheniformis 48 as a microbial cell factory and encouraged further focus on the strain

  18. Uncovering transcriptional regulation of metabolism by using metabolic network topology

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Nielsen, Jens

    2005-01-01

    in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic......Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional...... therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns...

  19. Glucose repression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Kayikci, Omur; Nielsen, Jens

    2015-01-01

    Glucose is the primary source of energy for the budding yeast Saccharomyces cerevisiae. Although yeast cells can utilize a wide range of carbon sources, presence of glucose suppresses molecular activities involved in the use of alternate carbon sources as well as it represses respiration and gluc......Glucose is the primary source of energy for the budding yeast Saccharomyces cerevisiae. Although yeast cells can utilize a wide range of carbon sources, presence of glucose suppresses molecular activities involved in the use of alternate carbon sources as well as it represses respiration...

  20. Redox balancing in recombinant strains of Saccharomyces cerevisiae

    Energy Technology Data Exchange (ETDEWEB)

    Anderlund, M

    1998-09-01

    In metabolically engineered Saccharomyces cerevisiae expressing Pichia stipitis XYL1 and XYL2 genes, encoding xylose reductase (XR) and xylitol dehydrogenase (XDH), respectively, xylitol is excreted as the major product during anaerobic xylose fermentation and only low yields of ethanol are produced. This has been interpreted as a result of the dual cofactor dependence of XR and the exclusive use of NAD{sup +} by XDH. The excretion of xylitol was completely stopped and the formation of glycerol and acetic acid were reduced in xylose utilising S. cerevisiae strains cultivated in oxygen-limited conditions by expressing lower levels of XR than of XDH. The expression level of XYL1 and XYL2 were controlled by changing the promoters and transcription directions of the genes. A new functional metabolic pathway was established when Thermus thermophilus xylA gene was expressed in S. cerevisiae. The recombinant strain was able to ferment xylose to ethanol when cultivated on a minimal medium containing xylose as only carbon source. In order to create a channeled metabolic transfer in the two first steps of the xylose metabolism, XYL1 and XYL2 were fused in-frame and expressed in S. cerevisiae. When the fusion protein, containing a linker of three amino acids, was co expressed together with native XR and XDH monomers, enzyme complexes consisting of chimeric and native subunits were formed. The total activity of these complexes exhibited 10 and 9 times higher XR and XDH activity, respectively, than the original conjugates, consisting of only chimeric subunits. This strain produced less xylitol and the xylitol yield was lower than with strains only expressing native XR and XDH monomers. In addition, more ethanol and less acetic acid were formed. A new gene encoding the cytoplasmic transhydrogenase from Azotobacter vinelandii was cloned. The enzyme showed high similarity to the family of pyridine nucleotide-disulphide oxidoreductase. To analyse the physiological effect of

  1. Functional expression and evaluation of heterologous phosphoketolases in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Bergman, Alexandra; Siewers, Verena; Nielsen, Jens

    2016-01-01

    Phosphoketolases catalyze an energy-and redox-independent cleavage of certain sugar phosphates. Hereby, the two-carbon (C2) compound acetyl-phosphate is formed, which enzymatically can be converted into acetyl-CoA-a key precursor in central carbon metabolism. Saccharomyces cerevisiae does...... not demonstrate efficient phosphoketolase activity naturally. In this study, we aimed to compare and identify efficient heterologous phosphoketolase enzyme candidates that in yeast have the potential to reduce carbon loss compared to the native acetyl-CoA producing pathway by redirecting carbon flux directly from...... C5 and C6 sugars towards C2-synthesis. Nine phosphoketolase candidates were expressed in S. cerevisiae of which seven produced significant amounts of acetyl-phosphate after provision of sugar phosphate substrates in vitro. The candidates showed differing substrate specificities, and some...

  2. levadura Saccharomyces Cerevisiae

    Directory of Open Access Journals (Sweden)

    B. Aguilar Uscanga

    2005-01-01

    Full Text Available La pared celular de levaduras representa entre 20 a 30 % de la célula en peso seco. Está compuesta de polisacáridos complejos de β-glucanos, manoproteínas y quitina. Se estudió la composición de los polisacáridos contenidos en la pared celular de la Saccharomyces cerevisiae CEN.PK 113 y se observó el efecto de la variación de la fuente carbono (glucosa, sacarosa, galactosa, maltosa, manosa, etanol y pH (3, 4, 5, 6 en un medio mineral “cell factory”. Las células fueron recolectadas en fase exponencial y se extrajo la pared celular. Los extractos de pared se hidrolizaron con H2SO4 al 72% y las muestras fueron analizadas por cromatografía HPLC. Se realizó una prueba de resistencia al rompimiento celular con una β(1,3-glucanasa, y las células cultivadas a diferentes fuentes carbono y pH. Los resultados del análisis por HPLC, mostraron que la composición de los polisacáridos en la pared celular, varía considerablemente con las modificaciones del medio de cultivo. Se observó que las levaduras cultivadas en sacarosa tienen mayor porcentaje de pared celular (25% y mayor cantidad de glucanos (115µg/mg peso seco y mananos (131µg/mg peso seco, que aquellas levaduras cultivadas en etanol (13% en peso seco. Las levaduras cultivadas a pH 5 presentaron 19% de pared celular en peso seco, mientras que a pH 6 el porcentaje fue menor (14%. El análisis de resistencia al rompimiento celular, mostró que las células cultivadas en etanol y galactosa fueron resistentes al rompimiento enzimático. Se comparó este resultado con el contenido de polisacáridos en la pared celular y concluimos que la resistencia de la célula al rompimiento, no está ligada con la cantidad de β-glucanos contenidos en la pared celular, sino que va a depender del número de enlaces β(1,3 y β(1,6-glucanos, los cuales juegan un rol importante durante el ensamblaje de la pared

  3. Intracellular metabolite profiling of Saccharomyces cerevisiae evolved under furfural.

    Science.gov (United States)

    Jung, Young Hoon; Kim, Sooah; Yang, Jungwoo; Seo, Jin-Ho; Kim, Kyoung Heon

    2017-03-01

    Furfural, one of the most common inhibitors in pre-treatment hydrolysates, reduces the cell growth and ethanol production of yeast. Evolutionary engineering has been used as a selection scheme to obtain yeast strains that exhibit furfural tolerance. However, the response of Saccharomyces cerevisiae to furfural at the metabolite level during evolution remains unknown. In this study, evolutionary engineering and metabolomic analyses were applied to determine the effects of furfural on yeasts and their metabolic response to continuous exposure to furfural. After 50 serial transfers of cultures in the presence of furfural, the evolved strains acquired the ability to stably manage its physiological status under the furfural stress. A total of 98 metabolites were identified, and their abundance profiles implied that yeast metabolism was globally regulated. Under the furfural stress, stress-protective molecules and cofactor-related mechanisms were mainly induced in the parental strain. However, during evolution under the furfural stress, S. cerevisiae underwent global metabolic allocations to quickly overcome the stress, particularly by maintaining higher levels of metabolites related to energy generation, cofactor regeneration and recovery from cellular damage. Mapping the mechanisms of furfural tolerance conferred by evolutionary engineering in the present study will be led to rational design of metabolically engineered yeasts. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

  4. Recon3D enables a three-dimensional view of gene variation in human metabolism

    DEFF Research Database (Denmark)

    Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C.

    2018-01-01

    Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D...

  5. Systems Biology of Metabolism: A Driver for Developing Personalized and Precision Medicine

    DEFF Research Database (Denmark)

    Nielsen, Jens

    2017-01-01

    for advancing the development of personalized and precision medicine to treat metabolic diseases like insulin resistance, obesity, NAFLD, NASH, and cancer. It will be illustrated how the concept of genome-scale metabolic models can be used for integrative analysis of big data with the objective of identifying...... novel biomarkers that are foundational for personalized and precision medicine....

  6. A genome-scale integration and analysis of Lactococcus lactis translation data.

    Directory of Open Access Journals (Sweden)

    Julien Racle

    Full Text Available Protein synthesis is a template polymerization process composed by three main steps: initiation, elongation, and termination. During translation, ribosomes are engaged into polysomes whose size is used for the quantitative characterization of translatome. However, simultaneous transcription and translation in the bacterial cytosol complicates the analysis of translatome data. We established a procedure for robust estimation of the ribosomal density in hundreds of genes from Lactococcus lactis polysome size measurements. We used a mechanistic model of translation to integrate the information about the ribosomal density and for the first time we estimated the protein synthesis rate for each gene and identified the rate limiting steps. Contrary to conventional considerations, we find significant number of genes to be elongation limited. This number increases during stress conditions compared to optimal growth and proteins synthesized at maximum rate are predominantly elongation limited. Consistent with bacterial physiology, we found proteins with similar rate and control characteristics belonging to the same functional categories. Under stress conditions, we found that synthesis rate of regulatory proteins is becoming comparable to proteins favored under optimal growth. These findings suggest that the coupling of metabolic states and protein synthesis is more important than previously thought.

  7. Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

    Directory of Open Access Journals (Sweden)

    Xing-Xing Shen

    2016-12-01

    Full Text Available Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence and two data matrices (amino acids or the first two codon positions yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast.

  8. Genome-scale prediction of proteins with long intrinsically disordered regions.

    Science.gov (United States)

    Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

    2014-01-01

    Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

  9. Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

    Science.gov (United States)

    Shen, Xing-Xing; Zhou, Xiaofan; Kominek, Jacek; Kurtzman, Cletus P.; Hittinger, Chris Todd; Rokas, Antonis

    2016-01-01

    Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence) and two data matrices (amino acids or the first two codon positions) yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast. PMID:27672114

  10. Saccharomyces cerevisiae variety diastaticus friend or foe?-spoilage potential and brewing ability of different Saccharomyces cerevisiae variety diastaticus yeast isolates by genetic, phenotypic and physiological characterization.

    Science.gov (United States)

    Meier-Dörnberg, Tim; Kory, Oliver Ingo; Jacob, Fritz; Michel, Maximilian; Hutzler, Mathias

    2018-06-01

    Saccharomyces cerevisiae variety diastaticus is generally considered to be an obligatory spoilage microorganism and spoilage yeast in beer and beer-mixed beverages. Their super-attenuating ability causes increased carbon dioxide concentrations, beer gushing and potential bottle explosion along with changes in flavor, sedimentation and increased turbidity. This research shows clear differences in the super-attenuating properties of S. cerevisiae var. diastaticus yeast strains and their potential for industrial brewing applications. Nineteen unknown spoilage yeast cultures were obtained as isolates and characterized using a broad spectrum of genetic and phenotypic methods. Results indicated that all isolates represent genetically different S. cerevisiae var. diastaticus strains except for strain TUM PI BA 124. Yeast strains were screened for their super-attenuating ability and sporulation. Even if the STA1 gene responsible for super-attenuation by encoding for the enzyme glucoamylase could be verified by real-time polymerase chain reaction, no correlation to the spoilage potential could be demonstrated. Seven strains were further characterized focusing on brewing and sensory properties according to the yeast characterization platform developed by Meier-Dörnberg. Yeast strain TUM 3-H-2 cannot metabolize dextrin and soluble starch and showed no spoilage potential or super-attenuating ability even when the strain belongs to the species S. cerevisiae var. diastaticus. Overall, the beer produced with S. cerevisiae var. diastaticus has a dry and winey body with noticeable phenolic off-flavors desirable in German wheat beers.

  11. Evaluation of cytochrome P-450 concentration in Saccharomyces cerevisiae strains

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    Míriam Cristina Sakuragui Matuo

    2010-09-01

    Full Text Available Saccharomyces cerevisiae has been widely used in mutagenicity tests due to the presence of a cytochrome P-450 system, capable of metabolizing promutagens to active mutagens. There are a large number of S. cerevisiae strains with varying abilities to produce cytochrome P-450. However, strain selection and ideal cultivation conditions are not well defined. We compared cytochrome P-450 levels in four different S. cerevisiae strains and evaluated the cultivation conditions necessary to obtain the highest levels. The amount of cytochrome P-450 produced by each strain varied, as did the incubation time needed to reach the maximum level. The highest cytochrome P-450 concentrations were found in media containing fermentable sugars. The NCYC 240 strain produced the highest level of cytochrome P-450 when grown in the presence of 20 % (w/v glucose. The addition of ethanol to the media also increased cytochrome P-450 synthesis in this strain. These results indicate cultivation conditions must be specific and well-established for the strain selected in order to assure high cytochrome P-450 levels and reliable mutagenicity results.Linhagens de Saccharomyces cerevisiae tem sido amplamente empregadas em testes de mutagenicidade devido à presença de um sistema citocromo P-450 capaz de metabolizar substâncias pró-mutagênicas à sua forma ativa. Devido à grande variedade de linhagens de S. cerevisiae com diferentes capacidades de produção de citocromo P-450, torna-se necessária a seleção de cepas, bem como a definição das condições ideais de cultivo. Neste trabalho, foram comparados os níveis de citocromo P-450 em quatro diferentes linhagens de S. cerevisiae e avaliadas as condições de cultivo necessárias para obtenção de altas concentrações deste sistema enzimático. O maior nível enzimático foi encontrado na linhagem NCYC 240 em presença de 20 % de glicose (p/v. A adição de etanol ao meio de cultura também produziu um aumento na s

  12. Sucrose fermentation by Saccharomyces cerevisiae lacking hexose transport.

    Science.gov (United States)

    Batista, Anderson S; Miletti, Luiz C; Stambuk, Boris U

    2004-01-01

    Sucrose is the major carbon source used by Saccharomyces cerevisiae during production of baker's yeast, fuel ethanol and several distilled beverages. It is generally accepted that sucrose fermentation proceeds through extracellular hydrolysis of the sugar, mediated by the periplasmic invertase, producing glucose and fructose that are transported into the cells and metabolized. In the present work we analyzed the contribution to sucrose fermentation of a poorly characterized pathway of sucrose utilization by S. cerevisiae cells, the active transport of the sugar through the plasma membrane and its intracellular hydrolysis. A yeast strain that lacks the major hexose transporters (hxt1-hxt7 and gal2) is incapable of growing on or fermenting glucose or fructose. Our results show that this hxt-null strain is still able to ferment sucrose due to direct uptake of the sugar into the cells. Deletion of the AGT1 gene, which encodes a high-affinity sucrose-H(+) symporter, rendered cells incapable of sucrose fermentation. Since sucrose is not an inducer of the permease, expression of the AGT1 must be constitutive in order to allow growth of the hxt-null strain on sucrose. The molecular characterization of active sucrose transport and fermentation by S. cerevisiae cells opens new opportunities to optimize yeasts for sugarcane-based industrial processes.

  13. Exploring the Saccharomyces cerevisiae Volatile Metabolome: Indigenous versus Commercial Strains

    Science.gov (United States)

    Alves, Zélia; Melo, André; Figueiredo, Ana Raquel; Coimbra, Manuel A.; Gomes, Ana C.; Rocha, Sílvia M.

    2015-01-01

    Winemaking is a highly industrialized process and a number of commercial Saccharomyces cerevisiae strains are used around the world, neglecting the diversity of native yeast strains that are responsible for the production of wines peculiar flavours. The aim of this study was to in-depth establish the S. cerevisiae volatile metabolome and to assess inter-strains variability. To fulfill this objective, two indigenous strains (BT2652 and BT2453 isolated from spontaneous fermentation of grapes collected in Bairrada Appellation, Portugal) and two commercial strains (CSc1 and CSc2) S. cerevisiae were analysed using a methodology based on advanced multidimensional gas chromatography (HS-SPME/GC×GC-ToFMS) tandem with multivariate analysis. A total of 257 volatile metabolites were identified, distributed over the chemical families of acetals, acids, alcohols, aldehydes, ketones, terpenic compounds, esters, ethers, furan-type compounds, hydrocarbons, pyrans, pyrazines and S-compounds. Some of these families are related with metabolic pathways of amino acid, carbohydrate and fatty acid metabolism as well as mono and sesquiterpenic biosynthesis. Principal Component Analysis (PCA) was used with a dataset comprising all variables (257 volatile components), and a distinction was observed between commercial and indigenous strains, which suggests inter-strains variability. In a second step, a subset containing esters and terpenic compounds (C10 and C15), metabolites of particular relevance to wine aroma, was also analysed using PCA. The terpenic and ester profiles express the strains variability and their potential contribution to the wine aromas, specially the BT2453, which produced the higher terpenic content. This research contributes to understand the metabolic diversity of indigenous wine microflora versus commercial strains and achieved knowledge that may be further exploited to produce wines with peculiar aroma properties. PMID:26600152

  14. Enhanced isoprenoid production from xylose by engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Kwak, Suryang; Kim, Soo Rin; Xu, Haiqing; Zhang, Guo-Chang; Lane, Stephan; Kim, Heejin; Jin, Yong-Su

    2017-11-01

    Saccharomyces cerevisiae has limited capabilities for producing fuels and chemicals derived from acetyl-CoA, such as isoprenoids, due to a rigid flux partition toward ethanol during glucose metabolism. Despite numerous efforts, xylose fermentation by engineered yeast harboring heterologous xylose metabolic pathways was not as efficient as glucose fermentation for producing ethanol. Therefore, we hypothesized that xylose metabolism by engineered yeast might be a better fit for producing non-ethanol metabolites. We indeed found that engineered S. cerevisiae on xylose showed higher expression levels of the enzymes involved in ethanol assimilation and cytosolic acetyl-CoA synthesis than on glucose. When genetic perturbations necessary for overproducing squalene and amorphadiene were introduced into engineered S. cerevisiae capable of fermenting xylose, we observed higher titers and yields of isoprenoids under xylose than glucose conditions. Specifically, co-overexpression of a truncated HMG1 (tHMG1) and ERG10 led to substantially higher squalene accumulation under xylose than glucose conditions. In contrast to glucose utilization producing massive amounts of ethanol regardless of aeration, xylose utilization allowed much less amounts of ethanol accumulation, indicating ethanol is simultaneously re-assimilated with xylose consumption and utilized for the biosynthesis of cytosolic acetyl-CoA. In addition, xylose utilization by engineered yeast with overexpression of tHMG1, ERG10, and ADS coding for amorphadiene synthase, and the down-regulation of ERG9 resulted in enhanced amorphadiene production as compared to glucose utilization. These results suggest that the problem of the rigid flux partition toward ethanol production in yeast during the production of isoprenoids and other acetyl-CoA derived chemicals can be bypassed by using xylose instead of glucose as a carbon source. Biotechnol. Bioeng. 2017;114: 2581-2591. © 2017 Wiley Periodicals, Inc. © 2017 Wiley

  15. Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

    Directory of Open Access Journals (Sweden)

    Eddy J Bautista

    Full Text Available Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.

  16. Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

    DEFF Research Database (Denmark)

    Kavvas, Erol S.; Seif, Yara; Yurkovich, James T.

    2018-01-01

    previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations...

  17. Progress in terpene synthesis strategies through engineering of Saccharomyces cerevisiae.

    Science.gov (United States)

    Paramasivan, Kalaivani; Mutturi, Sarma

    2017-12-01

    Terpenes are natural products with a remarkable diversity in their chemical structures and they hold a significant market share commercially owing to their distinct applications. These potential molecules are usually derived from terrestrial plants, marine and microbial sources. In vitro production of terpenes using plant tissue culture and plant metabolic engineering, although receiving some success, the complexity in downstream processing because of the interference of phenolics and product commercialization due to regulations that are significant concerns. Industrial workhorses' viz., Escherichia coli and Saccharomyces cerevisiae have become microorganisms to produce non-native terpenes in order to address critical issues such as demand-supply imbalance, sustainability and commercial viability. S. cerevisiae enjoys several advantages for synthesizing non-native terpenes with the most significant being the compatibility for expressing cytochrome P450 enzymes from plant origin. Moreover, achievement of high titers such as 40 g/l of amorphadiene, a sesquiterpene, boosts commercial interest and encourages the researchers to envisage both molecular and process strategies for developing yeast cell factories to produce these compounds. This review contains a brief consideration of existing strategies to engineer S. cerevisiae toward the synthesis of terpene molecules. Some of the common targets for synthesis of terpenes in S. cerevisiae are as follows: overexpression of tHMG1, ERG20, upc2-1 in case of all classes of terpenes; repression of ERG9 by replacement of the native promoter with a repressive methionine promoter in case of mono-, di- and sesquiterpenes; overexpression of BTS1 in case of di- and tetraterpenes. Site-directed mutagenesis such as Upc2p (G888A) in case of all classes of terpenes, ERG20p (K197G) in case of monoterpenes, HMG2p (K6R) in case of mono-, di- and sesquiterpenes could be some generic targets. Efforts are made to consolidate various studies

  18. Switching the mode of sucrose utilization by Saccharomyces cerevisiae

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    Miletti Luiz C

    2008-02-01

    Full Text Available Abstract Background Overflow metabolism is an undesirable characteristic of aerobic cultures of Saccharomyces cerevisiae during biomass-directed processes. It results from elevated sugar consumption rates that cause a high substrate conversion to ethanol and other bi-products, severely affecting cell physiology, bioprocess performance, and biomass yields. Fed-batch culture, where sucrose consumption rates are controlled by the external addition of sugar aiming at its low concentrations in the fermentor, is the classical bioprocessing alternative to prevent sugar fermentation by yeasts. However, fed-batch fermentations present drawbacks that could be overcome by simpler batch cultures at relatively high (e.g. 20 g/L initial sugar concentrations. In this study, a S. cerevisiae strain lacking invertase activity was engineered to transport sucrose into the cells through a low-affinity and low-capacity sucrose-H+ symport activity, and the growth kinetics and biomass yields on sucrose analyzed using simple batch cultures. Results We have deleted from the genome of a S. cerevisiae strain lacking invertase the high-affinity sucrose-H+ symporter encoded by the AGT1 gene. This strain could still grow efficiently on sucrose due to a low-affinity and low-capacity sucrose-H+ symport activity mediated by the MALx1 maltose permeases, and its further intracellular hydrolysis by cytoplasmic maltases. Although sucrose consumption by this engineered yeast strain was slower than with the parental yeast strain, the cells grew efficiently on sucrose due to an increased respiration of the carbon source. Consequently, this engineered yeast strain produced less ethanol and 1.5 to 2 times more biomass when cultivated in simple batch mode using 20 g/L sucrose as the carbon source. Conclusion Higher cell densities during batch cultures on 20 g/L sucrose were achieved by using a S. cerevisiae strain engineered in the sucrose uptake system. Such result was accomplished by

  19. Switching the mode of sucrose utilization by Saccharomyces cerevisiae.

    Science.gov (United States)

    Badotti, Fernanda; Dário, Marcelo G; Alves, Sergio L; Cordioli, Maria Luiza A; Miletti, Luiz C; de Araujo, Pedro S; Stambuk, Boris U

    2008-02-27

    Overflow metabolism is an undesirable characteristic of aerobic cultures of Saccharomyces cerevisiae during biomass-directed processes. It results from elevated sugar consumption rates that cause a high substrate conversion to ethanol and other bi-products, severely affecting cell physiology, bioprocess performance, and biomass yields. Fed-batch culture, where sucrose consumption rates are controlled by the external addition of sugar aiming at its low concentrations in the fermentor, is the classical bioprocessing alternative to prevent sugar fermentation by yeasts. However, fed-batch fermentations present drawbacks that could be overcome by simpler batch cultures at relatively high (e.g. 20 g/L) initial sugar concentrations. In this study, a S. cerevisiae strain lacking invertase activity was engineered to transport sucrose into the cells through a low-affinity and low-capacity sucrose-H+ symport activity, and the growth kinetics and biomass yields on sucrose analyzed using simple batch cultures. We have deleted from the genome of a S. cerevisiae strain lacking invertase the high-affinity sucrose-H+ symporter encoded by the AGT1 gene. This strain could still grow efficiently on sucrose due to a low-affinity and low-capacity sucrose-H+ symport activity mediated by the MALx1 maltose permeases, and its further intracellular hydrolysis by cytoplasmic maltases. Although sucrose consumption by this engineered yeast strain was slower than with the parental yeast strain, the cells grew efficiently on sucrose due to an increased respiration of the carbon source. Consequently, this engineered yeast strain produced less ethanol and 1.5 to 2 times more biomass when cultivated in simple batch mode using 20 g/L sucrose as the carbon source. Higher cell densities during batch cultures on 20 g/L sucrose were achieved by using a S. cerevisiae strain engineered in the sucrose uptake system. Such result was accomplished by effectively reducing sucrose uptake by the yeast cells

  20. Proteome-wide analysis of lysine acetylation suggests its broad regulatory scope in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Henriksen, Peter; Wagner, Sebastian Alexander; Weinert, Brian Tate

    2012-01-01

    Post-translational modification of proteins by lysine acetylation plays important regulatory roles in living cells. The budding yeast Saccharomyces cerevisiae is a widely used unicellular eukaryotic model organism in biomedical research. S. cerevisiae contains several evolutionary conserved lysine...... acetyltransferases and deacetylases. However, only a few dozen acetylation sites in S. cerevisiae are known, presenting a major obstacle for further understanding the regulatory roles of acetylation in this organism. Here we use high resolution mass spectrometry to identify about 4000 lysine acetylation sites in S....... cerevisiae. Acetylated proteins are implicated in the regulation of diverse cytoplasmic and nuclear processes including chromatin organization, mitochondrial metabolism, and protein synthesis. Bioinformatic analysis of yeast acetylation sites shows that acetylated lysines are significantly more conserved...

  1. Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.

    Science.gov (United States)

    Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

    2016-12-13

    Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.

  2. A genome-scale RNA-interference screen identifies RRAS signaling as a pathologic feature of Huntington's disease.

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    John P Miller

    Full Text Available A genome-scale RNAi screen was performed in a mammalian cell-based assay to identify modifiers of mutant huntingtin toxicity. Ontology analysis of suppressor data identified processes previously implicated in Huntington's disease, including proteolysis, glutamate excitotoxicity, and mitochondrial dysfunction. In addition to established mechanisms, the screen identified multiple components of the RRAS signaling pathway as loss-of-function suppressors of mutant huntingtin toxicity in human and mouse cell models. Loss-of-function in orthologous RRAS pathway members also suppressed motor dysfunction in a Drosophila model of Huntington's disease. Abnormal activation of RRAS and a down-stream effector, RAF1, was observed in cellular models and a mouse model of Huntington's disease. We also observe co-localization of RRAS and mutant huntingtin in cells and in mouse striatum, suggesting that activation of R-Ras may occur through protein interaction. These data indicate that mutant huntingtin exerts a pathogenic effect on this pathway that can be corrected at multiple intervention points including RRAS, FNTA/B, PIN1, and PLK1. Consistent with these results, chemical inhibition of farnesyltransferase can also suppress mutant huntingtin toxicity. These data suggest that pharmacological inhibition of RRAS signaling may confer therapeutic benefit in Huntington's disease.

  3. Systems Biology of Saccharomyces cerevisiae Physiology and its DNA Damage Response

    DEFF Research Database (Denmark)

    Fazio, Alessandro

    The yeast Saccharomyces cerevisiae is a model organism in biology, being widely used in fundamental research, the first eukaryotic organism to be fully sequenced and the platform for the development of many genomics techniques. Therefore, it is not surprising that S. cerevisiae has also been widely...... used in the field of systems biology during the last decade. This thesis investigates S. cerevisiae growth physiology and DNA damage response by using a systems biology approach. Elucidation of the relationship between growth rate and gene expression is important to understand the mechanisms regulating...... set of growth dependent genes by using a multi-factorial experimental design. Moreover, new insights into the metabolic response and transcriptional regulation of these genes have been provided by using systems biology tools (Chapter 3). One of the prerequisite of systems biology should...

  4. Sugar and Glycerol Transport in Saccharomyces cerevisiae.

    Science.gov (United States)

    Bisson, Linda F; Fan, Qingwen; Walker, Gordon A

    2016-01-01

    In Saccharomyces cerevisiae the process of transport of sugar substrates into the cell comprises a complex network of transporters and interacting regulatory mechanisms. Members of the large family of hexose (HXT) transporters display uptake efficiencies consistent with their environmental expression and play physiological roles in addition to feeding the glycolytic pathway. Multiple glucose-inducing and glucose-independent mechanisms serve to regulate expression of the sugar transporters in yeast assuring that expression levels and transporter activity are coordinated with cellular metabolism and energy needs. The expression of sugar transport activity is modulated by other nutritional and environmental factors that may override glucose-generated signals. Transporter expression and activity is regulated transcriptionally, post-transcriptionally and post-translationally. Recent studies have expanded upon this suite of regulatory mechanisms to include transcriptional expression fine tuning mediated by antisense RNA and prion-based regulation of transcription. Much remains to be learned about cell biology from the continued analysis of this dynamic process of substrate acquisition.

  5. Heterooligomeric phosphoribosyl diphosphate synthase of Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hove-Jensen, Bjarne

    2004-01-01

    The yeast Saccharomyces cerevisiae contains five phosphoribosyl diphosphate (PRPP) synthase-homologous genes (PRS1-5), which specify PRPP synthase subunits 1-5. Expression of the five S. cerevisiae PRS genes individually in an Escherichia coli PRPP-less strain (Deltaprs) showed that a single PRS...

  6. Fatal Saccharomyces Cerevisiae Aortic Graft Infection

    Science.gov (United States)

    Meyer, Michael (Technical Monitor); Smith, Davey; Metzgar, David; Wills, Christopher; Fierer, Joshua

    2002-01-01

    Saccharomyces cerevisiae is a yeast commonly used in baking and a frequent colonizer of human mucosal surfaces. It is considered relatively nonpathogenic in immunocompetent adults. We present a case of S. cerevisiae fungemia and aortic graft infection in an immunocompetent adult. This is the first reported case of S. cerevisiue fungemia where the identity of the pathogen was confirmed by rRNA sequencing.

  7. Predicción a escala genómica de Componentes de Saccharomyces cerevisiae mediante Análisis de Balance de Flujos

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    César Augusto Vargas García

    2012-01-01

    Full Text Available Título en ingles: Prediction of genome scale  of Saccharomyces cerevisiae by flux balance analysis Resumen: El microorganismo Saccharomyces cerevisiae cuenta con gran número de modelos biológicos conocidos como reconstrucciones, las cuales pueden ser a escala genómica. De estas reconstrucciones a escala genómica provienen los modelos matemáticos, también llamados modelos estequiométricos. Una de las técnicas más usadas para estudiar estos modelos es el Análisis de Balance de Flujos (FBA. El proposito del FBA es predecir el crecimiento del microorganismo bajo estudio, y la producción y consumo de componentes como el etanol, CO2 glicerol, sucinato, acetato y piruvato. Para determinar si las predicciones obtenidas mediante FBA son únicas se utiliza la técnica de Análisis de Variabilidad Flujos (FVA. El presente trabajo muestra los resultados de aplicar el FBA a la reconstrucción reciente del microorganismo S. cerevisiae, la denominada iMM904 y los compara con un conjunto de datos experimentales presente en la literatura. Este trabajo también estudia la existencia de múltiples predicciones FBA utilizando la técnica FVA. Los resultados ilustran que es posible predecir el crecimiento del microorganimo S. cerevisiae, con errores entre el 11% y 28%;  la producción de CO2, con errores entre el 0.3% y 4.5% y la producción de etanol, con errores entre el 11% y 13%. Palabras clave: analisis de balance de flujos, reconstrucción a escala genómica, iMM904, S. cerevisiae. Abstract: Several biological models, named reconstructions, are used for the study of the S. cerevisiae microorganism. The reconstructions can be genomic scaled. Mathematical models are generated from the reconstructions and they are called stoichiometric models. The flux balance analysis (FBA is one of the tools used for the analysis of these models. The FBA attempts to predict the evolution of the microorganism and the consumption and production of components like

  8. Context-specific metabolic networks are consistent with experiments.

    Directory of Open Access Journals (Sweden)

    Scott A Becker

    2008-05-01

    Full Text Available Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are "genome-scale" and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.

  9. Improvement of Lead Tolerance of Saccharomyces cerevisiae by Random Mutagenesis of Transcription Regulator SPT3.

    Science.gov (United States)

    Zhu, Liying; Gao, Shan; Zhang, Hongman; Huang, He; Jiang, Ling

    2018-01-01

    Bioremediation of heavy metal pollution with biomaterials such as bacteria and fungi usually suffer from limitations because of microbial sensitivity to high concentration of heavy metals. Herein, we adopted a novel random mutagenesis technique called RAISE to manipulate the transcription regulator SPT3 of Saccharomyces cerevisiae to improve cell lead tolerance. The best strain Mutant VI was selected from the random mutagenesis libraries on account of the growth performance, with higher specific growth rate than the control strain (0.068 vs. 0.040 h -1 ) at lead concentration as high as 1.8 g/L. Combined with the transcriptome analysis of S. cerevisiae, expressing the SPT3 protein was performed to make better sense of the global regulatory effects of SPT3. The data analysis revealed that 57 of S. cerevisiae genes were induced and 113 genes were suppressed, ranging from those for trehalose synthesis, carbon metabolism, and nucleotide synthesis to lead resistance. Especially, the accumulation of intracellular trehalose in S. cerevisiae under certain conditions of stress is considered important to lead resistance. The above results represented that SPT3 was acted as global transcription regulator in the exponential phase of strain and accordingly improved heavy metal tolerance in the heterologous host S. cerevisiae. The present study provides a route to complex phenotypes that are not readily accessible by traditional methods.

  10. Transcriptome-based characterization of interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus in lactose-grown chemostat cocultures.

    Science.gov (United States)

    Mendes, Filipa; Sieuwerts, Sander; de Hulster, Erik; Almering, Marinka J H; Luttik, Marijke A H; Pronk, Jack T; Smid, Eddy J; Bron, Peter A; Daran-Lapujade, Pascale

    2013-10-01

    Mixed populations of Saccharomyces cerevisiae yeasts and lactic acid bacteria occur in many dairy, food, and beverage fermentations, but knowledge about their interactions is incomplete. In the present study, interactions between Saccharomyces cerevisiae and Lactobacillus delbrueckii subsp. bulgaricus, two microorganisms that co-occur in kefir fermentations, were studied during anaerobic growth on lactose. By combining physiological and transcriptome analysis of the two strains in the cocultures, five mechanisms of interaction were identified. (i) Lb. delbrueckii subsp. bulgaricus hydrolyzes lactose, which cannot be metabolized by S. cerevisiae, to galactose and glucose. Subsequently, galactose, which cannot be metabolized by Lb. delbrueckii subsp. bulgaricus, is excreted and provides a carbon source for yeast. (ii) In pure cultures, Lb. delbrueckii subsp. bulgaricus grows only in the presence of increased CO2 concentrations. In anaerobic mixed cultures, the yeast provides this CO2 via alcoholic fermentation. (iii) Analysis of amino acid consumption from the defined medium indicated that S. cerevisiae supplied alanine to the bacterium. (iv) A mild but significant low-iron response in the yeast transcriptome, identified by DNA microarray analysis, was consistent with the chelation of iron by the lactate produced by Lb. delbrueckii subsp. bulgaricus. (v) Transcriptome analysis of Lb. delbrueckii subsp. bulgaricus in mixed cultures showed an overrepresentation of transcripts involved in lipid metabolism, suggesting either a competition of the two microorganisms for fatty acids or a response to the ethanol produced by S. cerevisiae. This study demonstrates that chemostat-based transcriptome analysis is a powerful tool to investigate microbial interactions in mixed populations.

  11. Data on dynamic study of cytoophidia in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Hui Li

    2016-09-01

    Full Text Available The data in this paper are related to the research article entitled “Filamentation of metabolic enzymes in Saccharomyces cerevisiae” Q.J. Shen et al. (2016 [1]. Cytoophidia are filamentous structures discovered in fruit flies (doi:10.1016/S1673-8527(0960046-1 J.L. Liu (2010 [2], bacteria (doi:10.1038/ncb2087 M. Ingerson-Mahar et al. (2010 [3], yeast (doi:10.1083/jcb.201003001; doi:10.1242/bio.20149613 C. Noree et al. (2010 and J. Zhang, L. Hulme, J.L. Liu (2014 [4,5] and human cells (doi:10.1371/journal.pone.0029690; doi:10.1016/j.jgg.2011.08.004 K. Chen et al. (2011 and W.C. Carcamo et al. (2011 ( [6,7]. However, there is little research on the motility of the cytoophidia. Here we selected cytoophidia formed by 6 filament-forming proteins in the budding yeast S. cerevisiae, and performed living-cell imaging of cells expressing the proteins fused with GFP. The dynamic features of the six types of cytoophidia were analyzed. In the data, both raw movies and analysed results of the dynamics of cytoophidia are presented. Keywords: Saccharomyces cerevisiae, CTP synthase, Cytoophidium, Metabolism, Filamentation

  12. Lactose fermentation by engineered Saccharomyces cerevisiae capable of fermenting cellobiose.

    Science.gov (United States)

    Liu, Jing-Jing; Zhang, Guo-Chang; Oh, Eun Joong; Pathanibul, Panchalee; Turner, Timothy L; Jin, Yong-Su

    2016-09-20

    Lactose is an inevitable byproduct of the dairy industry. In addition to cheese manufacturing, the growing Greek yogurt industry generates excess acid whey, which contains lactose. Therefore, rapid and efficient conversion of lactose to fuels and chemicals would be useful for recycling the otherwise harmful acid whey. Saccharomyces cerevisiae, a popular metabolic engineering host, cannot natively utilize lactose. However, we discovered that an engineered S. cerevisiae strain (EJ2) capable of fermenting cellobiose can also ferment lactose. This finding suggests that a cellobiose transporter (CDT-1) can transport lactose and a β-glucosidase (GH1-1) can hydrolyze lactose by acting as a β-galactosidase. While the lactose fermentation by the EJ2 strain was much slower than the cellobiose fermentation, a faster lactose-fermenting strain (EJ2e8) was obtained through serial subcultures on lactose. The EJ2e8 strain fermented lactose with a consumption rate of 2.16g/Lh. The improved lactose fermentation by the EJ2e8 strain was due to the increased copy number of cdt-1 and gh1-1 genes. Looking ahead, the EJ2e8 strain could be exploited for the production of other non-ethanol fuels and chemicals from lactose through further metabolic engineering. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

    Science.gov (United States)

    Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

    2017-01-01

    As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  14. The impact of respiration and oxidative stress response on recombinant α-amylase production by Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Martinez Ruiz, José Luis; Meza, Eugenio; Petranovic, Dina

    2016-01-01

    by overexpressing the endogenous HAP1 gene in a S. cerevisiae strain overproducing recombinant α-amylase. We demonstrate how Hap1p can activate a set of oxidative stress response genes and meanwhile contribute to increase the metabolic rate of the yeast strains, therefore mitigating the negative effect of the ROS...

  15. Key Process Conditions for Production of C4 Dicarboxylic Acids in Bioreactor Batch Cultures of an Engineered Saccharomyces cerevisiae Strain

    NARCIS (Netherlands)

    Zelle, R.M.; De Hulster, E.; Kloezen, W.; Pronk, J.T.; Van Maris, A.J.A.

    2010-01-01

    A recent effort to improve malic acid production by Saccharomyces cerevisiae by means of metabolic engineering resulted in a strain that produced up to 59 g liter(-1) of malate at a yield of 0.42 mol (mol glucose)(-1) in calcium carbonate-buffered shake flask cultures. With shake flasks, process

  16. Influence of genetic background of engineered xylose-fermenting industrial Saccharomyces cerevisiae strains for ethanol production from lignocellulosic hydrolysates

    Science.gov (United States)

    An industrial ethanol-producing Saccharomyces cerevisiae strain with genes needed for xylose-fermentation integrated into its genome was used to obtain haploids and diploid isogenic strains. The isogenic strains were more effective in metabolizing xylose than their parental strain (p < 0.05) and abl...

  17. Modulating the distribution of fluxes among respiration and fermentation by overexpression of HAP4 in Saccharomyces cerevisiae.

    NARCIS (Netherlands)

    van Maris, A.J.A.; Bakker, B.M.; Brandt, M.; Boorsma, A.; Teixeira de Mattos, M.J.; Grivell, L.A.; Pronk, J.T.

    2001-01-01

    The tendency of Saccharomyces cerevisiae to favor alcoholic fermentation over respiration is a complication in aerobic, biomass-directed applications of this yeast. Overproduction of Hap4p, a positive transcriptional regulator of genes involved in respiratory metabolism, has been reported to

  18. Removal of Pyrimethanil and Fenhexamid from Saccharomyces cerevisiae Liquid Cultures

    Directory of Open Access Journals (Sweden)

    Etjen Bizaj

    2011-01-01

    Full Text Available The capacity for the removal of pyrimethanil and fenhexamid, two fungicides commonly used for the control of Botrytis cinerea in vineyards, has been evaluated during an alcoholic fermentation process in batch system. Commercial and wild strains of Saccharomyces cerevisiae were used. Batch fermentations were carried out in yeast extract-malt extract medium (YM with 18.0 % (by mass glucose, and the fungicides were added separately at three concentrations: 0.1, 1.0 and 10.0 mg/L. The removal capacity of yeast strains was also examined in stationary phase cultures of Saccharomyces cerevisiae. Stationary assays were performed with yeast biomass harvested from the stationary phase of an anaerobic fermentation process, with separate additions of 0.1, 1.0 and 10.0 mg/L of both fungicides. Removal studies with stationary phase cells were performed with viable and non-viable cells inactivated with sodium azide. This study clearly shows that both Saccharomyces cerevisiae strains were able to remove fenhexamid and pyrimethanil in stationary and fermentative assays. The removal potential is shown to be strain dependent in stationary but not in fermentative assays. However, the removal potential is dependent on the type of fungicide in both stationary and fermentative assays. In stationary phase cultures no significant difference in fungicide removal potential between viable and non-viable cells was observed, indicating that both pesticides were not degraded by metabolically active cells. However, the presence of both pesticides influenced fermentation kinetics and only pyrimethanil at 10.0 mg/L increased the production of volatile acidity of both strains.

  19. Saccharomyces cerevisiae biofilm tolerance towards systemic antifungals depends on growth phase

    DEFF Research Database (Denmark)

    Bojsen, Rasmus Kenneth; Regenberg, Birgitte; Folkesson, Sven Anders

    2014-01-01

    Background : Biofilm-forming Candida species cause infections that can be difficult to eradicate, possibly because of antifungal drug tolerance mechanisms specific to biofilms. In spite of decades of research, the connection between biofilm and drug tolerance is not fully understood. Results : We...... used Saccharomyces cerevisiae as a model for drug susceptibility of yeast biofilms. Confocal laser scanning microscopy showed that S. cerevisiae and C. glabrata form similarly structured biofilms and that the viable cell numbers were significantly reduced by treatment of mature biofilms...... with amphotericin B but not voriconazole, flucytosine, or caspofungin. We showed that metabolic activity in yeast biofilm cells decreased with time, as visualized by FUN-1 staining, and mature, 48-hour biofilms contained cells with slow metabolism and limited growth. Time-kill studies showed that in exponentially...

  20. Production of volatile and sulfur compounds by ten Saccharomyces cerevisiae strains inoculated in Trebbiano must

    Directory of Open Access Journals (Sweden)

    Francesca ePatrignani

    2016-03-01

    Full Text Available In wines, the presence of sulphur compounds is the resulting of several contributions among which yeast metabolism. The characterization of the starter Saccharomyces cerevisiae needs to be performed also taking into account this ability even if evaluated together with the overall metabolic profile. In this perspective, principal aim of this experimental research was the evaluation of the volatile profiles, throughout GC/MS technique coupled with solid phase micro extraction, of wines obtained throughout the fermentation of 10 strains of Saccharomyces cerevisiae. In addition, the production of sulphur compounds was further evaluated by using a gas-chromatograph coupled with a Flame Photometric Detector. Specifically, the ten strains were inoculated in Trebbiano musts and the fermentations were monitored for 19 days. In the produced wines, volatile and sulphur compounds as well as amino acid concentrations were investigated. Also the physico-chemical characteristics of the wines and their electronic nose profiles were evaluated.

  1. Acetylation dynamics and stoichiometry in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Weinert, Brian Tate; Iesmantavicius, Vytautas; Moustafa, Tarek

    2014-01-01

    Lysine acetylation is a frequently occurring posttranslational modification; however, little is known about the origin and regulation of most sites. Here we used quantitative mass spectrometry to analyze acetylation dynamics and stoichiometry in Saccharomyces cerevisiae. We found that acetylation...

  2. Genome-Scale Analysis Reveals Sst2 as the Principal Regulator of Mating Pheromone Signaling in the Yeast Saccharomyces cerevisiae†

    Science.gov (United States)

    Chasse, Scott A.; Flanary, Paul; Parnell, Stephen C.; Hao, Nan; Cha, Jiyoung Y.; Siderovski, David P.; Dohlman, Henrik G.

    2006-01-01

    A common property of G protein-coupled receptors is that they become less responsive with prolonged stimulation. Regulators of G protein signaling (RGS proteins) are well known to accelerate G protein GTPase activity and do so by stabilizing the transition state conformation of the G protein α subunit. In the yeast Saccharomyces cerevisiae there are four RGS-homologous proteins (Sst2, Rgs2, Rax1, and Mdm1) and two Gα proteins (Gpa1 and Gpa2). We show that Sst2 is the only RGS protein that binds selectively to the transition state conformation of Gpa1. The other RGS proteins also bind Gpa1 and modulate pheromone signaling, but to a lesser extent and in a manner clearly distinct from Sst2. To identify other candidate pathway regulators, we compared pheromone responses in 4,349 gene deletion mutants representing nearly all nonessential genes in yeast. A number of mutants produced an increase (sst2, bar1, asc1, and ygl024w) or decrease (cla4) in pheromone sensitivity or resulted in pheromone-independent signaling (sst2, pbs2, gas1, and ygl024w). These findings suggest that Sst2 is the principal regulator of Gpa1-mediated signaling in vivo but that other proteins also contribute in distinct ways to pathway regulation. PMID:16467474

  3. Genome-scale study of the importance of binding site context for transcription factor binding and gene regulation

    Directory of Open Access Journals (Sweden)

    Ronne Hans

    2008-11-01

    Full Text Available Abstract Background The rate of mRNA transcription is controlled by transcription factors that bind to specific DNA motifs in promoter regions upstream of protein coding genes. Recent results indicate that not only the presence of a motif but also motif context (for example the orientation of a motif or its location relative to the coding sequence is important for gene regulation. Results In this study we present ContextFinder, a tool that is specifically aimed at identifying cases where motif context is likely to affect gene regulation. We used ContextFinder to examine the role of motif context in S. cerevisiae both for DNA binding by transcription factors and for effects on gene expression. For DNA binding we found significant patterns of motif location bias, whereas motif orientations did not seem to matter. Motif context appears to affect gene expression even more than it affects DNA binding, as biases in both motif location and orientation were more frequent in promoters of co-expressed genes. We validated our results against data on nucleosome positioning, and found a negative correlation between preferred motif locations and nucleosome occupancy. Conclusion We conclude that the requirement for stable binding of transcription factors to DNA and their subsequent function in gene regulation can impose constraints on motif context.

  4. Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

    Science.gov (United States)

    Kim, Woonsu; Park, Hyesun; Seo, Seongwon

    2016-01-01

    The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle. PMID

  5. The effect of medium structure complexity on the growth of Saccharomyces cerevisiae in gelatin-dextran systems.

    Science.gov (United States)

    Boons, Kathleen; Noriega, Estefanía; Verherstraeten, Niels; David, Charlotte C; Hofkens, Johan; Van Impe, Jan F

    2015-04-16

    As most food systems are (semi-)solid, the effect of food structure on bacterial growth has been widely acknowledged. However, studies on the growth dynamics of yeasts have neglected the effect of food structure. In this paper, the growth dynamics of the spoilage yeast Saccharomyces cerevisiae was investigated at 23.5 °C in broth, singular, homogeneous biopolymer systems and binary biopolymer systems with a heterogeneous microstructure. The biopolymers gelatin and dextran were used to introduce the different levels of structure. The metabolizing ability of gelatin and dextran by S. cerevisiae was examined. To study microbial behavior in the binary systems at the micro level, mixtures were imaged with confocal laser scanning microscopy (CLSM). Growth dynamics and microscopic images of S. cerevisiae were compared with those obtained for Escherichia coli in the same model system (Boons et al., 2014). Different phase-separated, heterogeneous microstructures were obtained by changing the amount of added gelatin and dextran. Regardless of the microstructure, S. cerevisiae was preferentially located in the dextran phase. Metabolizing ability-tests indicated that gelatin could be consumed by S. cerevisiae but in the presence of glucose, no change in gelatin concentration was observed. No indication of dextran metabolizing ability was observed. When supplementing broth with gelatin or dextran alone, an enhanced growth rate and maximum cell density were observed. This enhancement was further increased by adding a second biopolymer, introducing a heterogeneous microstructure and hence increasing the medium structure complexity. The results obtained indicate that food structure complexity plays a significant role in the growth dynamics of S. cerevisiae, an important food spoiler. Copyright © 2014. Published by Elsevier B.V.

  6. Omics analysis of acetic acid tolerance in Saccharomyces cerevisiae.

    Science.gov (United States)

    Geng, Peng; Zhang, Liang; Shi, Gui Yang

    2017-05-01

    Acetic acid is an inhibitor in industrial processes such as wine making and bioethanol production from cellulosic hydrolysate. It causes energy depletion, inhibition of metabolic enzyme activity, growth arrest and ethanol productivity losses in Saccharomyces cerevisiae. Therefore, understanding the mechanisms of the yeast responses to acetic acid stress is essential for improving acetic acid tolerance and ethanol production. Although 329 genes associated with acetic acid tolerance have been identified in the Saccharomyces genome and included in the database ( http://www.yeastgenome.org/observable/resistance_to_acetic_acid/overview ), the cellular mechanistic responses to acetic acid remain unclear in this organism. Post-genomic approaches such as transcriptomics, proteomics, metabolomics and chemogenomics are being applied to yeast and are providing insight into the mechanisms and interactions of genes, proteins and other components that together determine complex quantitative phenotypic traits such as acetic acid tolerance. This review focuses on these omics approaches in the response to acetic acid in S. cerevisiae. Additionally, several novel strains with improved acetic acid tolerance have been engineered by modifying key genes, and the application of these strains and recently acquired knowledge to industrial processes is also discussed.

  7. Rapid and efficient galactose fermentation by engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Quarterman, Josh; Skerker, Jeffrey M; Feng, Xueyang; Liu, Ian Y; Zhao, Huimin; Arkin, Adam P; Jin, Yong-Su

    2016-07-10

    In the important industrial yeast Saccharomyces cerevisiae, galactose metabolism requires energy production by respiration; therefore, this yeast cannot metabolize galactose under strict anaerobic conditions. While the respiratory dependence of galactose metabolism provides benefits in terms of cell growth and population stability, it is not advantageous for producing fuels and chemicals since a substantial fraction of consumed galactose is converted to carbon dioxide. In order to force S. cerevisiae to use galactose without respiration, a subunit (COX9) of a respiratory enzyme was deleted, but the resulting deletion mutant (Δcox9) was impaired in terms of galactose assimilation. Interestingly, after serial sub-cultures on galactose, the mutant evolved rapidly and was able to use galactose via fermentation only. The evolved strain (JQ-G1) produced ethanol from galactose with a 94% increase in yield and 6.9-fold improvement in specific productivity as compared to the wild-type strain. (13)C-metabolic flux analysis demonstrated a three-fold reduction in carbon flux through the TCA cycle of the evolved mutant with redirection of flux toward the fermentation pathway. Genome sequencing of the JQ-G1 strain revealed a loss of function mutation in a master negative regulator of the Leloir pathway (Gal80p). The mutation (Glu348*) in Gal80p was found to act synergistically with deletion of COX9 for efficient galactose fermentation, and thus the double deletion mutant Δcox9Δgal80 produced ethanol 2.4 times faster and with 35% higher yield than a single knockout mutant with deletion of GAL80 alone. When we introduced a functional COX9 cassette back into the JQ-G1 strain, the JQ-G1-COX9 strain showed a 33% reduction in specific galactose uptake rate and a 49% reduction in specific ethanol production rate as compared to JQ-G1. The wild-type strain was also subjected to serial sub-cultures on galactose but we failed to isolate a mutant capable of utilizing galactose without

  8. De novo production of the flavonoid naringenin in engineered Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Koopman Frank

    2012-12-01

    Full Text Available Abstract Background Flavonoids comprise a large family of secondary plant metabolic intermediates that exhibit a wide variety of antioxidant and human health-related properties. Plant production of flavonoids is limited by the low productivity and the complexity of the recovered flavonoids. Thus to overcome these limitations, metabolic engineering of specific pathway in microbial systems have been envisaged to produce high quantity of a single molecules. Result Saccharomyces cerevisiae was engineered to produce the key intermediate flavonoid, naringenin, solely from glucose. For this, specific naringenin biosynthesis genes from Arabidopsis thaliana were selected by comparative expression profiling and introduced in S. cerevisiae. The sole expression of these A. thaliana genes yielded low extracellular naringenin concentrations ( Conclusion The results reported in this study demonstrate that S. cerevisiae is capable of de novo production of naringenin by coexpressing the naringenin production genes from A. thaliana and optimization of the flux towards the naringenin pathway. The engineered yeast naringenin production host provides a metabolic chassis for production of a wide range of flavonoids and exploration of their biological functions.

  9. Comparative proteomics analysis of engineered Saccharomyces cerevisiae with enhanced biofuel precursor production.

    Directory of Open Access Journals (Sweden)

    Xiaoling Tang

    Full Text Available The yeast Saccharomyces cerevisiae was metabolically modified for enhanced biofuel precursor production by knocking out genes encoding mitochondrial isocitrate dehydrogenase and over-expression of a heterologous ATP-citrate lyase. A comparative iTRAQ-coupled 2D LC-MS/MS analysis was performed to obtain a global overview of ubiquitous protein expression changes in S. cerevisiae engineered strains. More than 300 proteins were identified. Among these proteins, 37 were found differentially expressed in engineered strains and they were classified into specific categories based on their enzyme functions. Most of the proteins involved in glycolytic and pyruvate branch-point pathways were found to be up-regulated and the proteins involved in respiration and glyoxylate pathway were however found to be down-regulated in engineered strains. Moreover, the metabolic modification of S. cerevisiae cells resulted in a number of up-regulated proteins involved in stress response and differentially expressed proteins involved in amino acid metabolism and protein biosynthesis pathways. These LC-MS/MS based proteomics analysis results not only offered extensive information in identifying potential protein-protein interactions, signal pathways and ubiquitous cellular changes elicited by the engineered pathways, but also provided a meaningful biological information platform serving further modification of yeast cells for enhanced biofuel production.

  10. Evaluation of Ethanol Production Activity by Engineered Saccharomyces cerevisiae Fermenting Cellobiose through the Phosphorolytic Pathway in Simultaneous Saccharification and Fermentation of Cellulose.

    Science.gov (United States)

    Lee, Won-Heong; Jin, Yong-Su

    2017-09-28

    In simultaneous saccharification and fermentation (SSF) for production of cellulosic biofuels, engineered Saccharomyces cerevisiae capable of fermenting cellobiose has provided several benefits, such as lower enzyme costs and faster fermentation rate compared with wild-type S. cerevisiae fermenting glucose. In this study, the effects of an alternative intracellular cellobiose utilization pathway-a phosphorolytic pathway based on a mutant cellodextrin transporter (CDT-1 (F213L)) and cellobiose phosphorylase (SdCBP)-was investigated by comparing with a hydrolytic pathway based on the same transporter and an intracellular β-glucosidase (GH1-1) for their SSF performances under various conditions. Whereas the phosphorolytic and hydrolytic cellobiose-fermenting S. cerevisiae strains performed similarly under the anoxic SSF conditions, the hydrolytic S. cerevisiae performed slightly better than the phosphorolytic S. cerevisiae under the microaerobic SSF conditions. Nonetheless, the phosphorolytic S. cerevisiae expressing the mutant CDT-1 showed better ethanol production than the glucose-fermenting S. cerevisiae with an extracellular β-glucosidase, regardless of SSF conditions. These results clearly prove that introduction of the intracellular cellobiose metabolic pathway into yeast can be effective on cellulosic ethanol production in SSF. They also demonstrate that enhancement of cellobiose transport activity in engineered yeast is the most important factor affecting the efficiency of SSF of cellulose.

  11. Engineering and Evolution of Saccharomyces cerevisiae to Produce Biofuels and Chemicals.

    Science.gov (United States)

    Turner, Timothy L; Kim, Heejin; Kong, In Iok; Liu, Jing-Jing; Zhang, Guo-Chang; Jin, Yong-Su

    To mitigate global climate change caused partly by the use of fossil fuels, the production of fuels and chemicals from renewable biomass has been attempted. The conversion of various sugars from renewable biomass into biofuels by engineered baker's yeast (Saccharomyces cerevisiae) is one major direction which has grown dramatically in recent years. As well as shifting away from fossil fuels, the production of commodity chemicals by engineered S. cerevisiae has also increased significantly. The traditional approaches of biochemical and metabolic engineering to develop economic bioconversion processes in laboratory and industrial settings have been accelerated by rapid advancements in the areas of yeast genomics, synthetic biology, and systems biology. Together, these innovations have resulted in rapid and efficient manipulation of S. cerevisiae to expand fermentable substrates and diversify value-added products. Here, we discuss recent and major advances in rational (relying on prior experimentally-derived knowledge) and combinatorial (relying on high-throughput screening and genomics) approaches to engineer S. cerevisiae for producing ethanol, butanol, 2,3-butanediol, fatty acid ethyl esters, isoprenoids, organic acids, rare sugars, antioxidants, and sugar alcohols from glucose, xylose, cellobiose, galactose, acetate, alginate, mannitol, arabinose, and lactose.

  12. Ethanol production from xylose in engineered Saccharomyces cerevisiae strains. Current state and perspectives

    Energy Technology Data Exchange (ETDEWEB)

    Matsushika, Akinori; Inoue, Hiroyuki; Sawayama, Shigeki [National Inst. of Advanced Industrial Science and Technology (AIST), Hiroshima (JP). Biomass Technology Research Center (BTRC); Kodaki, Tsutomu [Kyoto Univ. (Japan). Inst. of Advanced Energy

    2009-08-15

    Bioethanol production from xylose is important for utilization of lignocellulosic biomass as raw materials. The research on yeast conversion of xylose to ethanol has been intensively studied especially for genetically engineered Saccharomyces cerevisiae during the last 20 years. S. cerevisiae, which is a very safe microorganism that plays a traditional and major role in industrial bioethanol production, has several advantages due to its high ethanol productivity, as well as its high ethanol and inhibitor tolerance. However, this yeast cannot ferment xylose, which is the dominant pentose sugar in hydrolysates of lignocellulosic biomass. A number of different strategies have been applied to engineer yeasts capable of efficiently producing ethanol from xylose, including the introduction of initial xylose metabolism and xylose transport, changing the intracellular redox balance, and overexpression of xylulokinase and pentose phosphate pathways. In this review, recent progress with regard to these studies is discussed, focusing particularly on xylose-fermenting strains of S. cerevisiae. Recent studies using several promising approaches such as host strain selection and adaptation to obtain further improved xylose-utilizing S. cerevisiae are also addressed. (orig.)

  13. Comprehensive reanalysis of transcription factor knockout expression data in Saccharomyces cerevisiae reveals many new targets.

    Science.gov (United States)

    Reimand, Jüri; Vaquerizas, Juan M; Todd, Annabel E; Vilo, Jaak; Luscombe, Nicholas M

    2010-08-01

    Transcription factor (TF) perturbation experiments give valuable insights into gene regulation. Genome-scale evidence from microarray measurements may be used to identify regulatory interactions between TFs and targets. Recently, Hu and colleagues published a comprehensive study covering 269 TF knockout mutants for the yeast Saccharomyces cerevisiae. However, the information that can be extracted from this valuable dataset is limited by the method employed to process the microarray data. Here, we present a reanalysis of the original data using improved statistical techniques freely available from the BioConductor project. We identify over 100,000 differentially expressed genes-nine times the total reported by Hu et al. We validate the biological significance of these genes by assessing their functions, the occurrence of upstream TF-binding sites, and the prevalence of protein-protein interactions. The reanalysed dataset outperforms the original across all measures, indicating that we have uncovered a vastly expanded list of relevant targets. In summary, this work presents a high-quality reanalysis that maximizes the information contained in the Hu et al. compendium. The dataset is available from ArrayExpress (accession: E-MTAB-109) and it will be invaluable to any scientist interested in the yeast transcriptional regulatory system.

  14. In vivo NMR study of yeast fermentative metabolism in the presence ...

    Indian Academy of Sciences (India)

    2011-03-14

    Mar 14, 2011 ... Changes in the ion levels of nutrient media alter the intracellular ... influence the metabolic behaviour of microorganisms. We clearly have already ... during the sugar fermentation by cultures of S. cerevisiae. (Martini et al. 2004 ...

  15. Environmental versatility promotes modularity in large scale metabolic networks

    OpenAIRE

    Samal A.; Wagner Andreas; Martin O.C.

    2011-01-01

    Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chem...

  16. Metabolomic comparison of Saccharomyces cerevisiae and the cryotolerant species S. bayanus var. uvarum and S. kudriavzevii during wine fermentation at low temperature.

    Directory of Open Access Journals (Sweden)

    María López-Malo

    Full Text Available Temperature is one of the most important parameters affecting the length and rate of alcoholic fermentation and final wine quality. Wine produced at low temperature is often considered to have improved sensory qualities. However, there are certain drawbacks to low temperature fermentations such as reduced growth rate, long lag phase, and sluggish or stuck fermentations. To investigate the effects of temperature on commercial wine yeast, we compared its metabolome growing at 12 °C and 28 °C in a synthetic must. Some species of the Saccharomyces genus have shown better adaptation at low temperature than Saccharomyces cerevisiae. This is the case of the cryotolerant yeasts Saccharomyces bayanus var. uvarum and Saccharomyces kudriavzevii. In an attempt to detect inter-specific metabolic differences, we characterized the metabolome of these species growing at 12°C, which we compared with the metabolome of S. cerevisiae (not well adapted at low temperature at the same temperature. Our results show that the main differences between the metabolic profiling of S. cerevisiae growing at 12 °C and 28 °C were observed in lipid metabolism and redox homeostasis. Moreover, the global metabolic comparison among the three species revealed that the main differences between the two cryotolerant species and S. cerevisiae were in carbohydrate metabolism, mainly fructose metabolism. However, these two species have developed different strategies for cold resistance. S. bayanus var. uvarum presented elevated shikimate pathway activity, while S. kudriavzevii displayed increased NAD(+ synthesis.

  17. Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

    Science.gov (United States)

    Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

    2018-01-01

    In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

  18. Scheffersomyces stipitis: a comparative systems biology study with the Crabtree positive yeast Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Papini, Marta; Nookaew, Intawat; Uhlén, Mathias

    2012-01-01

    , but is regulated by a decrease in oxygen levels. Even though S. stipitis has been extensively studied due to its potential application in pentoses fermentation, a limited amount of information is available about its metabolism during aerobic growth on glucose. Here, we provide a systems biology based comparison....... To describe gene expression levels under the two conditions, we performed RNA sequencing and the results were used to quantify transcript abundances of genes from the central carbon metabolism and compared with those obtained with S. cerevisiae. Interestingly, genes involved in central pathways showed...

  19. Metabolic response to exogenous ethanol in yeast

    Indian Academy of Sciences (India)

    In this study, we applied this approach to evaluate the effects of increasing concentration of exogenous ethanol on the Saccharomyces cerevisiae fermentative metabolism. We show that the STOCSY analysis correctly identifies the different types of correlations among the enriched metabolites involved in the fermentation, ...

  20. [Urinary infection by Saccharomyces cerevisiae: Emerging yeast?].

    Science.gov (United States)

    Elkhihal, B; Elhalimi, M; Ghfir, B; Mostachi, A; Lyagoubi, M; Aoufi, S

    2015-12-01

    Saccharomyces cerevisiae is a commensal yeast of the digestive, respiratory and genito-urinary tract. It is widely used as a probiotic for the treatment of post-antibiotic diarrhea. It most often occurs in immunocompromised patients frequently causing fungemia. We report the case of an adult diabetic patient who had a urinary tract infection due to S. cerevisiae. The disease started with urination associated with urinary frequency burns without fever. The diagnosis was established by the presence of yeasts on direct examination and positivity of culture on Sabouraud-chloramphenicol three times. The auxanogramme gallery (Auxacolor BioRad(®)) allowed the identification of S. cerevisiae. The patient was put on fluconazole with good outcome. This observation points out that this is an opportunistic yeast in immunocompromised patients. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  1. Metabolic engineering of Saccharomyces cerevisiae for optimizing 3HP production

    DEFF Research Database (Denmark)

    Jensen, Niels Bjerg; Maury, Jerome; Oberg, Fredrik

    2012-01-01

    . Polyacrylates are a substantial part of the different plastic varieties found on the market. This kind of plastic is derived from acrylic acid, which is currently produced from propylene, a by-product of ethylene and gasoline production. Annually, more than one billion kilograms of acrylic acid is produced...

  2. A novel pathway of ceramide metabolism in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Voynova, Natalia S; Vionnet, Christine; Ejsing, Christer S.

    2012-01-01

    The hydrolysis of ceramides in yeast is catalysed by the alkaline ceramidases Ypc1p and Ydc1p, two highly homologous membrane proteins localized to the ER (endoplasmic reticulum). As observed with many enzymes, Ypc1p can also catalyse the reverse reaction, i.e. condense a non-esterified fatty aci...

  3. Dynamics of Storage Carbohydrates Metabolism in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Suarez-Mendez, C.A.

    2015-01-01

    Production of chemicals via biotechnological routes are becoming rapidly an alternative to oil-based processes. Several microorganisms including yeast, bacteria, fungi and algae can transform feedstocks into high-value molecules at industrial scale. Improvement of the bioprocess performance is a key

  4. Novel strategies for engineering redox metabolism in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Guadalupe Medina, V.G.

    2013-01-01

    In its search to decrease the environmental impact of the production of materials and food, and for other socio-economic reasons, mankind has recently taken the first steps into a paradigm shift from a petrochemical-based society to a new, sustainable and to a significant extent bio-based society.

  5. Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

    Science.gov (United States)

    Wlodarski, Tomasz; Kutner, Jan; Towpik, Joanna; Knizewski, Lukasz; Rychlewski, Leszek; Kudlicki, Andrzej; Rowicka, Maga; Dziembowski, Andrzej; Ginalski, Krzysztof

    2011-01-01

    Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

  6. Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

    Directory of Open Access Journals (Sweden)

    Tomasz Wlodarski

    Full Text Available Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity. Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

  7. Saccharomyces cerevisiae Boulardii Reduces the Deoxynivalenol-Induced Alteration of the Intestinal Transcriptome

    Directory of Open Access Journals (Sweden)

    Imourana Alassane-Kpembi

    2018-05-01

    Full Text Available Type B trichothecene mycotoxin deoxynivalenol (DON is one of the most frequently occurring food contaminants. By inducing trans-activation of a number of pro-inflammatory cytokines and increasing the stability of their mRNA, trichothecene can impair intestinal health. Several yeast products, especially Saccharomyces cerevisiae, have the potential for improving the enteric health of piglets, but little is known about the mechanisms by which the administration of yeast counteracts the DON-induced intestinal alterations. Using a pig jejunum explant model, a whole-transcriptome analysis was performed to decipher the early response of the small intestine to the deleterious effects of DON after administration of S. cerevisiae boulardii strain CNCM I-1079. Compared to the control condition, no differentially expressed gene (DE was observed after treatment by yeast only. By contrast, 3619 probes—corresponding to 2771 genes—were differentially expressed following exposure to DON, and 32 signaling pathways were identified from the IPA software functional analysis of the set of DE genes. When the intestinal explants were treated with S. cerevisiae boulardii prior to DON exposure, the number of DE genes decreased by half (1718 probes corresponding to 1384 genes. Prototypical inflammation signaling pathways triggered by DON, including NF-κB and p38 MAPK, were reversed, although the yeast demonstrated limited efficacy toward some other pathways. S. cerevisiae boulardii also restored the lipid metabolism signaling pathway, and reversed the down-regulation of the antioxidant action of vitamin C signaling pathway. The latter effect could reduce the burden of DON-induced oxidative stress. Altogether, the results show that S. cerevisiae boulardii reduces the DON-induced alteration of intestinal transcriptome, and point to new mechanisms for the healing of tissue injury by yeast.

  8. Functional expression of a heterologous nickel-dependent, ATP-independent urease in Saccharomyces cerevisiae.

    Science.gov (United States)

    Milne, N; Luttik, M A H; Cueto Rojas, H F; Wahl, A; van Maris, A J A; Pronk, J T; Daran, J M

    2015-07-01

    In microbial processes for production of proteins, biomass and nitrogen-containing commodity chemicals, ATP requirements for nitrogen assimilation affect product yields on the energy producing substrate. In Saccharomyces cerevisiae, a current host for heterologous protein production and potential platform for production of nitrogen-containing chemicals, uptake and assimilation of ammonium requires 1 ATP per incorporated NH3. Urea assimilation by this yeast is more energy efficient but still requires 0.5 ATP per NH3 produced. To decrease ATP costs for nitrogen assimilation, the S. cerevisiae gene encoding ATP-dependent urease (DUR1,2) was replaced by a Schizosaccharomyces pombe gene encoding ATP-independent urease (ure2), along with its accessory genes ureD, ureF and ureG. Since S. pombe ure2 is a Ni(2+)-dependent enzyme and Saccharomyces cerevisiae does not express native Ni(2+)-dependent enzymes, the S. pombe high-affinity nickel-transporter gene (nic1) was also expressed. Expression of the S. pombe genes into dur1,2Δ S. cerevisiae yielded an in vitro ATP-independent urease activity of 0.44±0.01 µmol min(-1) mg protein(-1) and restored growth on urea as sole nitrogen source. Functional expression of the Nic1 transporter was essential for growth on urea at low Ni(2+) concentrations. The maximum specific growth rates of the engineered strain on urea and ammonium were lower than those of a DUR1,2 reference strain. In glucose-limited chemostat cultures with urea as nitrogen source, the engineered strain exhibited an increased release of ammonia and reduced nitrogen content of the biomass. Our results indicate a new strategy for improving yeast-based production of nitrogen-containing chemicals and demonstrate that Ni(2+)-dependent enzymes can be functionally expressed in S. cerevisiae. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  9. Saccharomyces cerevisiae Boulardii Reduces the Deoxynivalenol-Induced Alteration of the Intestinal Transcriptome.

    Science.gov (United States)

    Alassane-Kpembi, Imourana; Pinton, Philippe; Hupé, Jean-François; Neves, Manon; Lippi, Yannick; Combes, Sylvie; Castex, Mathieu; Oswald, Isabelle P

    2018-05-15

    Type B trichothecene mycotoxin deoxynivalenol (DON) is one of the most frequently occurring food contaminants. By inducing trans-activation of a number of pro-inflammatory cytokines and increasing the stability of their mRNA, trichothecene can impair intestinal health. Several yeast products, especially Saccharomyces cerevisiae , have the potential for improving the enteric health of piglets, but little is known about the mechanisms by which the administration of yeast counteracts the DON-induced intestinal alterations. Using a pig jejunum explant model, a whole-transcriptome analysis was performed to decipher the early response of the small intestine to the deleterious effects of DON after administration of S. cerevisiae boulardii strain CNCM I-1079. Compared to the control condition, no differentially expressed gene (DE) was observed after treatment by yeast only. By contrast, 3619 probes-corresponding to 2771 genes-were differentially expressed following exposure to DON, and 32 signaling pathways were identified from the IPA software functional analysis of the set of DE genes. When the intestinal explants were treated with S. cerevisiae boulardii prior to DON exposure, the number of DE genes decreased by half (1718 probes corresponding to 1384 genes). Prototypical inflammation signaling pathways triggered by DON, including NF-κB and p38 MAPK, were reversed, although the yeast demonstrated limited efficacy toward some other pathways. S. cerevisiae boulardii also restored the lipid metabolism signaling pathway, and reversed the down-regulation of the antioxidant action of vitamin C signaling pathway. The latter effect could reduce the burden of DON-induced oxidative stress. Altogether, the results show that S. cerevisiae boulardii reduces the DON-induced alteration of intestinal transcriptome, and point to new mechanisms for the healing of tissue injury by yeast.

  10. Mobilomics in Saccharomyces cerevisiae strains.

    Science.gov (United States)

    Menconi, Giulia; Battaglia, Giovanni; Grossi, Roberto; Pisanti, Nadia; Marangoni, Roberto

    2013-03-20

    Mobile Genetic Elements (MGEs) are selfish DNA integrated in the genomes. Their detection is mainly based on consensus-like searches by scanning the investigated genome against the sequence of an already identified MGE. Mobilomics aims at discovering all the MGEs in a genome and understanding their dynamic behavior: The data for this kind of investigation can be provided by comparative genomics of closely related organisms. The amount of data thus involved requires a strong computational effort, which should be alleviated. Our approach proposes to exploit the high similarity among homologous chromosomes of different strains of the same species, following a progressive comparative genomics philosophy. We introduce a software tool based on our new fast algorithm, called regender, which is able to identify the conserved regions between chromosomes. Our case study is represented by a unique recently available dataset of 39 different strains of S.cerevisiae, which regender is able to compare in few minutes. By exploring the non-conserved regions, where MGEs are mainly retrotransposons called Tys, and marking the candidate Tys based on their length, we are able to locate a priori and automatically all the already known Tys and map all the putative Tys in all the strains. The remaining putative mobile elements (PMEs) emerging from this intra-specific comparison are sharp markers of inter-specific evolution: indeed, many events of non-conservation among different yeast strains correspond to PMEs. A clustering based on the presence/absence of the candidate Tys in the strains suggests an evolutionary interconnection that is very similar to classic phylogenetic trees based on SNPs analysis, even though it is computed without using phylogenetic information. The case study indicates that the proposed methodology brings two major advantages: (a) it does not require any template sequence for the wanted MGEs and (b) it can be applied to infer MGEs also for low coverage genomes

  11. Mobilomics in Saccharomyces cerevisiae strains

    Science.gov (United States)

    2013-01-01

    Background Mobile Genetic Elements (MGEs) are selfish DNA integrated in the genomes. Their detection is mainly based on consensus–like searches by scanning the investigated genome against the sequence of an already identified MGE. Mobilomics aims at discovering all the MGEs in a genome and understanding their dynamic behavior: The data for this kind of investigation can be provided by comparative genomics of closely related organisms. The amount of data thus involved requires a strong computational effort, which should be alleviated. Results Our approach proposes to exploit the high similarity among homologous chromosomes of different strains of the same species, following a progressive comparative genomics philosophy. We introduce a software tool based on our new fast algorithm, called regender, which is able to identify the conserved regions between chromosomes. Our case study is represented by a unique recently available dataset of 39 different strains of S.cerevisiae, which regender is able to compare in few minutes. By exploring the non–conserved regions, where MGEs are mainly retrotransposons called Tys, and marking the candidate Tys based on their length, we are able to locate a priori and automatically all the already known Tys and map all the putative Tys in all the strains. The remaining putative mobile elements (PMEs) emerging from this intra–specific comparison are sharp markers of inter–specific evolution: indeed, many events of non–conservation among different yeast strains correspond to PMEs. A clustering based on the presence/absence of the candidate Tys in the strains suggests an evolutionary interconnection that is very similar to classic phylogenetic trees based on SNPs analysis, even though it is computed without using phylogenetic information. Conclusions The case study indicates that the proposed methodology brings two major advantages: (a) it does not require any template sequence for the wanted MGEs and (b) it can be applied to

  12. Value-added biotransformation of cellulosic sugars by engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Lane, Stephan; Dong, Jia; Jin, Yong-Su

    2018-07-01

    The substantial research efforts into lignocellulosic biofuels have generated an abundance of valuable knowledge and technologies for metabolic engineering. In particular, these investments have led to a vast growth in proficiency of engineering the yeast Saccharomyces cerevisiae for consuming lignocellulosic sugars, enabling the simultaneous assimilation of multiple carbon sources, and producing a large variety of value-added products by introduction of heterologous metabolic pathways. While microbial conversion of cellulosic sugars into large-volume low-value biofuels is not currently economically feasible, there may still be opportunities to produce other value-added chemicals as regulation of cellulosic sugar metabolism is quite different from glucose metabolism. This review summarizes these recent advances with an emphasis on employing engineered yeast for the bioconversion of lignocellulosic sugars into a variety of non-ethanol value-added products. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Fermentation performance of engineered and evolved xylose-fermenting Saccharomyces cerevisiae strains

    DEFF Research Database (Denmark)

    Sonderegger, M.; Jeppsson, M.; Larsson, C.

    2004-01-01

    Lignocellulose hydrolysate is an abundant substrate for bioethanol production. The ideal microorganism for such a fermentation process should combine rapid and efficient conversion of the available carbon sources to ethanol with high tolerance to ethanol and to inhibitory components in the hydrol......Lignocellulose hydrolysate is an abundant substrate for bioethanol production. The ideal microorganism for such a fermentation process should combine rapid and efficient conversion of the available carbon sources to ethanol with high tolerance to ethanol and to inhibitory components...... in the hydrolysate. A particular biological problem are the pentoses, which are not naturally metabolized by the main industrial ethanol producer Saccharomyces cerevisiae. Several recombinant, mutated, and evolved xylose fermenting S. cerevisiae strains have been developed recently. We compare here the fermentation...

  14. The effect of Saccharomyces cerevisiae on the stability of the herbicide glyphosate during bread leavening.

    Science.gov (United States)

    Low, F L; Shaw, I C; Gerrard, J A

    2005-01-01

    To investigate the ability of baker's yeast (Saccharomyces cerevisiae) to degrade the herbicide glyphosate during the fermentation cycle of the breadmaking process. Aqueous glyphosate was added to bread ingredients and kneaded by commercially available breadmaking equipment into dough cultures. Cultures were incubated in the breadmaker throughout the fermentation cycle. The recovery of glyphosate levels following fermentation was determined, thus allowing an estimation of glyphosate degradation by yeast. It was shown, for the first time, that S. cerevisiae plays a role in metabolizing glyphosate during the fermentation stages of breadmaking. Approximately 21% was degraded within 1 h. As a result of projected increases in the glyphosate use on wheat and the role of bread as a dietary staple, this may contribute to more informed decisions being made relating to the use of glyphosate on glyphosate-resistant wheat, from a public health/regulatory perspective.

  15. Engineering high-level production of fatty alcohols by Saccharomyces cerevisiae from lignocellulosic feedstocks

    DEFF Research Database (Denmark)

    d'Espaux, Leo; Ghosh, Amit; Runguphan, Weerawat

    2017-01-01

    to similar to 20% of the maximum theoretical yield from glucose, the highest titers and yields reported to date in S. cerevisiae. We further demonstrate high-level production from lignocellulosic feedstocks derived from ionic-liquid treated switchgrass and sorghum, reaching 0.7 g/L in shake flasks......Fatty alcohols in the C12-C18 range are used in personal care products, lubricants, and potentially biofuels. These compounds can be produced from the fatty acid pathway by a fatty acid reductase (FAR), yet yields from the preferred industrial host Saccharomyces cerevisiae remain under 2......% of the theoretical maximum from glucose. Here we improved titer and yield of fatty alcohols using an approach involving quantitative analysis of protein levels and metabolic flux, engineering enzyme level and localization, pull-push-block engineering of carbon flux, and cofactor balancing. We compared four...

  16. Bioconversion of lignocellulose-derived sugars to ethanol by engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Madhavan, Anjali; Srivastava, Aradhana; Kondo, Akihiko; Bisaria, Virendra S

    2012-03-01

    Lignocellulosic biomass from agricultural and agro-industrial residues represents one of the most important renewable resources that can be utilized for the biological production of ethanol. The yeast Saccharomyces cerevisiae is widely used for the commercial production of bioethanol from sucrose or starch-derived glucose. While glucose and other hexose sugars like galactose and mannose can be fermented to ethanol by S. cerevisiae, the major pentose sugars D-xylose and L-arabinose remain unutilized. Nevertheless, D-xylulose, the keto isomer of xylose, can be fermented slowly by the yeast and thus, the incorporation of functional routes for the conversion of xylose and arabinose to xylulose or xylulose-5-phosphate in Saccharomyces cerevisiae can help to improve the ethanol productivity and make the fermentation process more cost-effective. Other crucial bottlenecks in pentose fermentation include low activity of the pentose phosphate pathway enzymes and competitive inhibition of xylose and arabinose transport into the cell cytoplasm by glucose and other hexose sugars. Along with a brief introduction of the pretreatment of lignocellulose and detoxification of the hydrolysate, this review provides an updated overview of (a) the key steps involved in the uptake and metabolism of the hexose sugars: glucose, galactose, and mannose, together with the pentose sugars: xylose and arabinose, (b) various factors that play a major role in the efficient fermentation of pentose sugars along with hexose sugars, and (c) the approaches used to overcome the metabolic constraints in the production of bioethanol from lignocellulose-derived sugars by developing recombinant S. cerevisiae strains.

  17. Ferrofluid modified Saccharomyces cerevisiae cells for biocatalysis

    Czech Academy of Sciences Publication Activity Database

    Šafaříková, Miroslava; Maděrová, Zdeňka; Šafařík, Ivo

    2009-01-01

    Roč. 42, - (2009), s. 521-524 ISSN 0963-9969 R&D Projects: GA MPO 2A-1TP1/094; GA MŠk(CZ) OC 157 Institutional research plan: CEZ:AV0Z60870520 Keywords : Saccharomyces cerevisiae * magnetic fluid * hydrogen peroxide Subject RIV: EI - Biotechnology ; Bionics Impact factor: 2.414, year: 2009

  18. Excision repair and mutagenesis in Saccharomyces cerevisiae

    International Nuclear Information System (INIS)

    Kilbey, Brian

    1987-01-01

    This and succeeding letters discuss the James and Kilbey (1977 and 1978) model for the initiation of u.v. mutagenesis in Saccharomyces cerevisiae and its application to include a number of chemical mutagens. The Baranowska et al (1987) results indicating the role of DNA replication, the differing mechanisms in Escherichia coli, are all discussed. (UK)

  19. Nitrogen Catabolite Repression in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hofman-Bang, H Jacob Peider

    1999-01-01

    In Saccharomyces cerevisiae the expression of all known nitrogen catabolite pathways are regulated by four regulators known as Gln3, Gat1, Da180, and Deh1. This is known as nitrogen catabolite repression (NCR). They bind to motifs in the promoter region to the consensus sequence S' GATAA 3'. Gln3...

  20. Effects of fermentation by Saccharomyces cerevisiae and ...

    African Journals Online (AJOL)

    yassine

    2013-02-13

    Feb 13, 2013 ... Full Length Research Paper. Effect of Saccharomyces cerevisiae fermentation on the ... 2003). Besides, several alcoholic beverages such as wine or liqueurs are obtained from fruit juices fermented by Saccharomyces ..... (2003). Kinetics of pigment release from hairy root cultures of Beta vulgaris under the ...

  1. Characterisation of Saccharomyces cerevisiae hybrids selected for ...

    African Journals Online (AJOL)

    Wine yeasts (Saccharomyces cerevisiae) vary in their ability to develop the full aroma potential of Sauvignon blanc wine due to an inability to release volatile thiols. Subsequently, the use of 'thiolreleasing' wine yeasts (TRWY) has increased in popularity. However, anecdotal evidence suggests that some commercially ...

  2. Hybridization of Palm Wine Yeasts ( Saccharomyces Cerevisiae ...

    African Journals Online (AJOL)

    Haploid auxotrophic strains of Saccharomyces cerevisiae were selected from palm wine and propagated by protoplast fusion with Brewers yeast. Fusion resulted in an increase in both ethanol production and tolerance against exogenous ethanol. Mean fusion frequencies obtained for a mating types ranged between 8 x ...

  3. Substrate Channelling and Energetics of Saccharomyces cerevisiae ...

    African Journals Online (AJOL)

    Data collected during the high-cell-density cultivation of Saccharomyces cerevisiae DSM 2155 on glucose in a simulated five-phase feeding strategy of fed-batch process, executed on the Universal BIoprocess CONtrol (UBICON) system using 150L bioreactor over a period of 24h have been analysed. The consistency of the ...

  4. Evolutionary engineering of Saccharomyces cerevisiae for efficient conversion of red algal biosugars to bioethanol.

    Science.gov (United States)

    Lee, Hye-Jin; Kim, Soo-Jung; Yoon, Jeong-Jun; Kim, Kyoung Heon; Seo, Jin-Ho; Park, Yong-Cheol

    2015-09-01

    The aim of this work was to apply the evolutionary engineering to construct a mutant Saccharomyces cerevisiae HJ7-14 resistant on 2-deoxy-D-glucose and with an enhanced ability of bioethanol production from galactose, a mono-sugar in red algae. In batch and repeated-batch fermentations, HJ7-14 metabolized 5-fold more galactose and produced ethanol 2.1-fold faster than the parental D452-2 strain. Transcriptional analysis of genes involved in the galactose metabolism revealed that moderate relief from the glucose-mediated repression of the transcription of the GAL genes might enable HJ7-14 to metabolize galactose rapidly. HJ7-14 produced 7.4 g/L ethanol from hydrolysates of the red alga Gelidium amansii within 12 h, which was 1.5-times faster than that observed with D452-2. We demonstrate conclusively that evolutionary engineering is a promising tool to manipulate the complex galactose metabolism in S. cerevisiae to produce bioethanol from red alga. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Effects of introducing heterologous pathways on microbial metabolism with respect to metabolic optimality

    DEFF Research Database (Denmark)

    Kim, Hyun Uk; Kim, Byoungjin; Seung, Do Young

    2014-01-01

    reactions are more frequently introduced into various microbial hosts. The genome-scale metabolic simulations of Escherichia coli strains engineered to produce 1,4-butanediol, 1,3-propanediol, and amorphadiene suggest that microbial metabolism shows much different responses to the introduced heterologous...... reactions in a strain-specific manner than typical gene knockouts in terms of the energetic status (e.g., ATP and biomass generation) and chemical production capacity. The 1,4-butanediol and 1,3-propanediol producers showed greater metabolic optimality than the wild-type strains and gene knockout mutants...... for the energetic status, while the amorphadiene producer was metabolically less optimal. For the optimal chemical production capacity, additional gene knockouts were most effective for the strain producing 1,3-propanediol, but not for the one producing 1,4-butanediol. These observations suggest that strains having...

  6. Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities.

    Science.gov (United States)

    Mahadevan, Radhakrishnan; Henson, Michael A

    2012-01-01

    Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

  7. Nutrient sensing and signaling in the yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Conrad, Michaela; Schothorst, Joep; Kankipati, Harish Nag; Van Zeebroeck, Griet; Rubio-Texeira, Marta; Thevelein, Johan M

    2014-01-01

    The yeast Saccharomyces cerevisiae has been a favorite organism for pioneering studies on nutrient-sensing and signaling mechanisms. Many specific nutrient responses have been elucidated in great detail. This has led to important new concepts and insight into nutrient-controlled cellular regulation. Major highlights include the central role of the Snf1 protein kinase in the glucose repression pathway, galactose induction, the discovery of a G-protein-coupled receptor system, and role of Ras in glucose-induced cAMP signaling, the role of the protein synthesis initiation machinery in general control of nitrogen metabolism, the cyclin-controlled protein kinase Pho85 in phosphate regulation, nitrogen catabolite repression and the nitrogen-sensing target of rapamycin pathway, and the discovery of transporter-like proteins acting as nutrient sensors. In addition, a number of cellular targets, like carbohydrate stores, stress tolerance, and ribosomal gene expression, are controlled by the presence of multiple nutrients. The protein kinase A signaling pathway plays a major role in this general nutrient response. It has led to the discovery of nutrient transceptors (transporter receptors) as nutrient sensors. Major shortcomings in our knowledge are the relationship between rapid and steady-state nutrient signaling, the role of metabolic intermediates in intracellular nutrient sensing, and the identity of the nutrient sensors controlling cellular growth. PMID:24483210

  8. Effects of gene orientation and use of multiple promoters on the expression of XYL1 and XYL2 in Saccharomyces cerevisiae

    Science.gov (United States)

    Ju Yun Bae; Jose Laplaza; Thomas W. Jeffries

    2008-01-01

    Orientation of adjacent genes has been reported to affect their expression in eukaryotic systems, and metabolic engineering also often makes repeated use of a few promoters to obtain high expression. To improve transcriptional control in heterologous expression, we examined how these factors affect gene expression and enzymatic activity in Saccharomyces cerevisiae. We...

  9. Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

    Science.gov (United States)

    Aurich, Maike K; Thiele, Ines

    2016-01-01

    Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

  10. Adaptive Evolution of Phosphorus Metabolism in Prochlorococcus

    DEFF Research Database (Denmark)

    Casey, John R; Mardinoglu, Adil; Nielsen, Jens

    2016-01-01

    Inorganic phosphorus is scarce in the eastern Mediterranean Sea, where the high-light-adapted ecotype HLI of the marine picocyanobacterium Prochlorococcus marinus thrives. Physiological and regulatory control of phosphorus acquisition and partitioning has been observed in HLI both in culture...... and in the field; however, the optimization of phosphorus metabolism and associated gains for its phosphorus-limited-growth (PLG) phenotype have not been studied. Here, we reconstructed a genome-scale metabolic network of the HLI axenic strain MED4 (iJC568), consisting of 568 metabolic genes in relation to 794...... through drastic depletion of phosphorus-containing biomass components but also through network-wide reductions in phosphate-reaction participation and the loss of a key enzyme, succinate dehydrogenase. These alterations occur despite the stringency of having relatively few pathway redundancies...

  11. The impact of respiration and oxidative stress response on recombinant α-amylase production by Saccharomyces cerevisiae.

    Science.gov (United States)

    Martínez, José L; Meza, Eugenio; Petranovic, Dina; Nielsen, Jens

    2016-12-01

    Studying protein production is important for fundamental research on cell biology and applied research for biotechnology. Yeast Saccharomyces cerevisiae is an attractive workhorse for production of recombinant proteins as it does not secrete many endogenous proteins and it is therefore easy to purify a secreted product. However, recombinant production at high rates represents a significant metabolic burden for the yeast cells, which results in oxidative stress and ultimately affects the protein production capacity. Here we describe a method to reduce the overall oxidative stress by overexpressing the endogenous HAP1 gene in a S. cerevisiae strain overproducing recombinant α-amylase. We demonstrate how Hap1p can activate a set of oxidative stress response genes and meanwhile contribute to increase the metabolic rate of the yeast strains, therefore mitigating the negative effect of the ROS accumulation associated to protein folding and hence increasing the production capacity during batch fermentations.

  12. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    Directory of Open Access Journals (Sweden)

    Kim Hyun

    2011-12-01

    Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  13. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

    Science.gov (United States)

    Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

    2011-01-01

    Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

  14. Saccharomyces cerevisiae can secrete Sapp1p proteinase of Candida parapsilosis but cannot use it for efficient nitrogen acquisition

    Czech Academy of Sciences Publication Activity Database

    Vinterová, Zuzana; Bauerová, Václava; Dostál, Jiří; Sychrová, Hana; Hrušková-Heidingsfeldová, Olga; Pichová, Iva

    2013-01-01

    Roč. 51, č. 3 (2013), s. 336-344 ISSN 1225-8873 R&D Projects: GA ČR GA310/09/1945; GA ČR GAP302/12/1151 Institutional support: RVO:61388963 ; RVO:67985823 Keywords : Candida parapsilosis * Saccharomyces cerevisiae * secreted aspartic proteinase * SAPP1 * nitrogen metabolism Subject RIV: EE - Microbiology, Virology; EE - Microbiology, Virology (FGU-C) Impact factor: 1.529, year: 2013

  15. Hydrostatic Pressure Enhances Vital Staining with Carboxyfluorescein or Carboxydichlorofluorescein in Saccharomyces cerevisiae: Efficient Detection of Labeled Yeasts by Flow Cytometry

    Science.gov (United States)

    Abe, Fumiyoshi

    1998-01-01

    The extent of intracellular accumulation of the fluorescent dye carboxyfluorescein or carboxydichlorofluorescein (CDCF) in Saccharomyces cerevisiae was found to be increased 5- to 10-fold under a nonlethal hydrostatic pressure of 30 to 50 MPa. This observation was confirmed by analysis of individual labeled cells by flow cytometry. The pressure-induced enhancement of staining with CDCF required d-glucose and was markedly inhibited by 2-deoxy-d-glucose, suggesting that glucose metabolism has a role in the process. PMID:9501452

  16. Systems biology analysis of hepatitis C virus infection reveals the role of copy number increases in regions of chromosome 1q in hepatocellular carcinoma metabolism

    DEFF Research Database (Denmark)

    Elsemman, Ibrahim; Mardinoglu, Adil; Shoaie, Saeed

    2016-01-01

    on hepatocellular metabolism. Here, we integrated HCV assembly reactions with a genome-scale hepatocyte metabolic model to identify metabolic targets for HCV assembly and metabolic alterations that occur between different HCV progression states (cirrhosis, dysplastic nodule, and early and advanced hepatocellular...... carcinoma (HCC)) and healthy liver tissue. We found that diacylglycerolipids were essential for HCV assembly. In addition, the metabolism of keratan sulfate and chondroitin sulfate was significantly changed in the cirrhosis stage, whereas the metabolism of acyl-carnitine was significantly changed...

  17. Engineered Production of Short-Chain Acyl-Coenzyme A Esters in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Krink-Koutsoubelis, Nicolas; Loechner, Anne C.; Lechner, Anna

    2018-01-01

    Short-chain acyl-coenzyme A esters serve as intermediate compounds in fatty acid biosynthesis, and the production of polyketides, biopolymers and other value-added chemicals. S. cerevisiae is a model organism that has been utilized for the biosynthesis of such biologically and economically valuable...... compounds. However, its limited repertoire of short-chain acyl-CoAs effectively prevents its application as a production host for a plethora of natural products. Therefore, we introduced biosynthetic metabolic pathways to five different acyl-CoA esters into S. cerevisiae. Our engineered strains provide......-CoA at 0.5 μM; and isovaleryl-CoA, n-butyryl-CoA, and n-hexanoyl-CoA at 6 μM each. The acyl-CoAs produced in this study are common building blocks of secondary metabolites and will enable the engineered production of a variety of natural products in S. cerevisiae. By providing this toolbox of acyl...

  18. Terminal acidic shock inhibits sour beer bottle conditioning by Saccharomyces cerevisiae.

    Science.gov (United States)

    Rogers, Cody M; Veatch, Devon; Covey, Adam; Staton, Caleb; Bochman, Matthew L

    2016-08-01

    During beer fermentation, the brewer's yeast Saccharomyces cerevisiae experiences a variety of shifting growth conditions, culminating in a low-oxygen, low-nutrient, high-ethanol, acidic environment. In beers that are bottle conditioned (i.e., carbonated in the bottle by supplying yeast with a small amount of sugar to metabolize into CO2), the S. cerevisiae cells must overcome these stressors to perform the ultimate act in beer production. However, medium shock caused by any of these variables can slow, stall, or even kill the yeast, resulting in production delays and economic losses. Here, we describe a medium shock caused by high lactic acid levels in an American sour beer, which we refer to as "terminal acidic shock". Yeast exposed to this shock failed to bottle condition the beer, though they remained viable. The effects of low pH/high [lactic acid] conditions on the growth of six different brewing strains of S. cerevisiae were characterized, and we developed a method to adapt the yeast to growth in acidic beer, enabling proper bottle conditioning. Our findings will aid in the production of sour-style beers, a trending category in the American craft beer scene. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Saccharomyces cerevisiae KNU5377 stress response during high-temperature ethanol fermentation.

    Science.gov (United States)

    Kim, Il-Sup; Kim, Young-Saeng; Kim, Hyun; Jin, Ingnyol; Yoon, Ho-Sung

    2013-03-01

    Fuel ethanol production is far more costly to produce than fossil fuels. There are a number of approaches to cost-effective fuel ethanol production from biomass. We characterized stress response of thermotolerant Saccharomyces cerevisiae KNU5377 during glucose-based batch fermentation at high temperature (40°C). S. cerevisiae KNU5377 (KNU5377) transcription factors (Hsf1, Msn2/4, and Yap1), metabolic enzymes (hexokinase, glyceraldehyde-3-phosphate dehydrogenase, glucose-6-phosphate dehydrogenase, isocitrate dehydrogenase, and alcohol dehydrogenase), antioxidant enzymes (thioredoxin 3, thioredoxin reductase, and porin), and molecular chaperones and its cofactors (Hsp104, Hsp82, Hsp60, Hsp42, Hsp30, Hsp26, Cpr1, Sti1, and Zpr1) are upregulated during fermentation, in comparison to S. cerevisiae S288C (S288C). Expression of glyceraldehyde-3-phosphate dehydrogenase increased significantly in KNU5377 cells. In addition, cellular hydroperoxide and protein oxidation, particularly lipid peroxidation of triosephosphate isomerase, was lower in KNU5377 than in S288C. Thus, KNU5377 activates various cell rescue proteins through transcription activators, improving tolerance and increasing alcohol yield by rapidly responding to fermentation stress through redox homeostasis and proteostasis.

  20. Central roles of iron in the regulation of oxidative stress in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Matsuo, Ryo; Mizobuchi, Shogo; Nakashima, Maya; Miki, Kensuke; Ayusawa, Dai; Fujii, Michihiko

    2017-10-01

    Oxygen is essential for aerobic organisms but causes cytotoxicity probably through the generation of reactive oxygen species (ROS). In this study, we screened for the genes that regulate oxidative stress in the yeast Saccharomyces cerevisiae, and found that expression of CTH2/TIS11 caused an increased resistance to ROS. CTH2 is up-regulated upon iron starvation and functions to remodel metabolism to adapt to iron starvation. We showed here that increased resistance to ROS by CTH2 would likely be caused by the decreased ROS production due to the decreased activity of mitochondrial respiration, which observation is consistent with the fact that CTH2 down-regulates the mitochondrial respiratory proteins. We also found that expression of CTH1, a paralog of CTH2, also caused an increased resistance to ROS. This finding supported the above view, because mitochondrial respiratory proteins are the common targets of CTH1 and CTH2. We further showed that supplementation of iron in medium augmented the growth of S. cerevisiae under oxidative stress, and expression of CTH2 and supplementation of iron collectively enhanced its growth under oxidative stress. Since CTH2 is regulated by iron, these findings suggested that iron played crucial roles in the regulation of oxidative stress in S. cerevisiae.

  1. L-histidine inhibits biofilm formation and FLO11-associated phenotypes in Saccharomyces cerevisiae flor yeasts.

    Science.gov (United States)

    Bou Zeidan, Marc; Zara, Giacomo; Viti, Carlo; Decorosi, Francesca; Mannazzu, Ilaria; Budroni, Marilena; Giovannetti, Luciana; Zara, Severino

    2014-01-01

    Flor yeasts of Saccharomyces cerevisiae have an innate diversity of Flo11p which codes for a highly hydrophobic and anionic cell-wall glycoprotein with a fundamental role in biofilm formation. In this study, 380 nitrogen compounds were administered to three S. cerevisiae flor strains handling Flo11p alleles with different expression levels. S. cerevisiae strain S288c was used as the reference strain as it cannot produce Flo11p. The flor strains generally metabolized amino acids and dipeptides as the sole nitrogen source, although with some exceptions regarding L-histidine and histidine containing dipeptides. L-histidine completely inhibited growth and its effect on viability was inversely related to Flo11p expression. Accordingly, L-histidine did not affect the viability of the Δflo11 and S288c strains. Also, L-histidine dramatically decreased air-liquid biofilm formation and adhesion to polystyrene of the flor yeasts with no effect on the transcription level of the Flo11p gene. Moreover, L-histidine modified the chitin and glycans content on the cell-wall of flor yeasts. These findings reveal a novel biological activity of L-histidine in controlling the multicellular behavior of yeasts [corrected].

  2. Sporulation in the Budding Yeast Saccharomyces cerevisiae

    Science.gov (United States)

    Neiman, Aaron M.

    2011-01-01

    In response to nitrogen starvation in the presence of a poor carbon source, diploid cells of the yeast Saccharomyces cerevisiae undergo meiosis and package the haploid nuclei produced in meiosis into spores. The formation of spores requires an unusual cell division event in which daughter cells are formed within the cytoplasm of the mother cell. This process involves the de novo generation of two different cellular structures: novel membrane compartments within the cell cytoplasm that give rise to the spore plasma membrane and an extensive spore wall that protects the spore from environmental insults. This article summarizes what is known about the molecular mechanisms controlling spore assembly with particular attention to how constitutive cellular functions are modified to create novel behaviors during this developmental process. Key regulatory points on the sporulation pathway are also discussed as well as the possible role of sporulation in the natural ecology of S. cerevisiae. PMID:22084423

  3. Growth on Alpha-Ketoglutarate Increases Oxidative Stress Resistance in the Yeast Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Maria Bayliak

    2017-01-01

    Full Text Available Alpha-ketoglutarate (AKG is an important intermediate in cell metabolism, linking anabolic and catabolic processes. The effect of exogenous AKG on stress resistance in S. cerevisiae cells was studied. The growth on AKG increased resistance of yeast cells to stresses, but the effects depended on AKG concentration and type of stressor. Wild-type yeast cells grown on AKG were more resistant to hydrogen peroxide, menadione, and transition metal ions (Fe2+ and Cu2+ but not to ethanol and heat stress as compared with control ones. Deficiency in SODs or catalases abolished stress-protective effects of AKG. AKG-supplemented growth led to higher values of total metabolic activity, level of low-molecular mass thiols, and activities of catalase and glutathione reductase in wild-type cells compared with the control. The results suggest that exogenous AKG may enhance cell metabolism leading to induction of mild oxidative stress. It turn, it results in activation of antioxidant system that increases resistance of S. cerevisiae cells to H2O2 and other stresses. The presence of genes encoding SODs or catalases is required for the expression of protective effects of AKG.

  4. Physiological studies in aerobic batch cultivations of Saccharomyces cerevisiae strains harboring the MEL1 gene

    DEFF Research Database (Denmark)

    Østergaard, Simon; Roca, Christophe Francois Aime; Ronnow, B.

    2000-01-01

    Physiological studies of Saccharomyces cerevisiae strains harboring the MEL1 gene were carried out in aerobic batch cultivations on glucose-galactose mixtures and on the disaccharide melibiose, which is hydrolyzed by the enzyme melibiase (Mel1, EC 3.2.1.22) into a glucose and a galactose moiety...... rates were 2.5-3.3-fold higher on glucose than on galactose for all the strains examined, and hence, ethanol production was pronounced on glucose due to respiro-fermentative metabolism. The T256 strain and the T200 strain having the MEL1 gene inserted in the HXK2 locus and the LEU2 locus, respectively...

  5. Induction of homologous recombination in Saccharomyces cerevisiae.

    Science.gov (United States)

    Simon, J R; Moore, P D

    1988-09-01

    We have investigated the effects of UV irradiation of Saccharomyces cerevisiae in order to distinguish whether UV-induced recombination results from the induction of enzymes required for homologous recombination, or the production of substrate sites for recombination containing regions of DNA damage. We utilized split-dose experiments to investigate the induction of proteins required for survival, gene conversion, and mutation in a diploid strain of S. cerevisiae. We demonstrate that inducing doses of UV irradiation followed by a 6 h period of incubation render the cells resistant to challenge doses of UV irradiation. The effects of inducing and challenge doses of UV irradiation upon interchromosomal gene conversion and mutation are strictly additive. Using the yeast URA3 gene cloned in non-replicating single- and double-stranded plasmid vectors that integrate into chromosomal genes upon transformation, we show that UV irradiation of haploid yeast cells and homologous plasmid DNA sequences each stimulate homologous recombination approximately two-fold, and that these effects are additive. Non-specific DNA damage has little effect on the stimulation of homologous recombination, as shown by studies in which UV-irradiated heterologous DNA was included in transformation/recombination experiments. We further demonstrate that the effect of competing single- and double-stranded heterologous DNA sequences differs in UV-irradiated and unirradiated cells, suggesting an induction of recombinational machinery in UV-irradiated S. cerevisiae cells.

  6. Bacterial xylose isomerases from the mammal gut Bacteroidetes cluster function in Saccharomyces cerevisiae for effective xylose fermentation.

    Science.gov (United States)

    Peng, Bingyin; Huang, Shuangcheng; Liu, Tingting; Geng, Anli

    2015-05-17

    Xylose isomerase (XI) catalyzes the conversion of xylose to xylulose, which is the key step for anaerobic ethanolic fermentation of xylose. Very few bacterial XIs can function actively in Saccharomyces cerevisiae. Here, we illustrate a group of XIs that would function for xylose fermentation in S. cerevisiae through phylogenetic analysis, recombinant yeast strain construction, and xylose fermentation. Phylogenetic analysis of deposited XI sequences showed that XI evolutionary relationship was highly consistent with the bacterial taxonomic orders and quite a few functional XIs in S. cerevisiae were clustered with XIs from mammal gut Bacteroidetes group. An XI from Bacteroides valgutus in this cluster was actively expressed in S. cerevisiae with an activity comparable to the fungal XI from Piromyces sp. Two XI genes were isolated from the environmental metagenome and they were clustered with XIs from environmental Bacteroidetes group. These two XIs could not be expressed in yeast with activity. With the XI from B. valgutus expressed in S. cerevisiae, background yeast strains were optimized by pentose metabolizing pathway enhancement and adaptive evolution in xylose medium. Afterwards, more XIs from the mammal gut Bacteroidetes group, including those from B. vulgatus, Tannerella sp. 6_1_58FAA_CT1, Paraprevotella xylaniphila and Alistipes sp. HGB5, were individually transformed into S. cerevisiae. The known functional XI from Orpinomyces sp. ukk1, a mammal gut fungus, was used as the control. All the resulting recombinant yeast strains were able to ferment xylose. The respiration-deficient strains harboring B. vulgatus and Alistipes sp. HGB5 XI genes respectively obtained specific xylose consumption rate of 0.662 and 0.704 g xylose gcdw(-1) h(-1), and ethanol specific productivity of 0.277 and 0.283 g ethanol gcdw(-1) h(-1), much comparable to those obtained by the control strain carrying Orpinomyces sp. ukk1 XI gene. This study demonstrated that XIs clustered in the

  7. Construction and analysis of the model of energy metabolism in E. coli.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E. coli's energy metabolism. We first constructed a metabolic weighted network using the rates of free energy consumption within metabolic reactions as the weights. We then analyzed some structural characters of the metabolic weighted network that we constructed. We found that the distribution of the weight values was uneven, that most of the weight values were zero while reactions with abstract large weight values were rare and that the relationship between w (weight values and v (flux values was not of linear correlation. At last, we have done some research on the equilibrium of free energy for the energy metabolism system of E. coli. We found that E(out (free energy rate input from the environment can meet the demand of E(ch(in (free energy rate dissipated by chemical process and that chemical process plays a great role in the dissipation of free energy in cells. By these research and to a certain extend, we can understand more about the energy metabolism of E. coli.

  8. A review of metabolic and enzymatic engineering strategies for designing and optimizing performance of microbial cell factories

    Directory of Open Access Journals (Sweden)

    Amanda K. Fisher

    2014-08-01

    Full Text Available Microbial cell factories (MCFs are of considerable interest to convert low value renewable substrates to biofuels and high value chemicals. This review highlights the progress of computational models for the rational design of an MCF to produce a target bio-commodity. In particular, the rational design of an MCF involves: (i product selection, (ii de novo biosynthetic pathway identification (i.e., rational, heterologous, or artificial, (iii MCF chassis selection, (iv enzyme engineering of promiscuity to enable the formation of new products, and (v metabolic engineering to ensure optimal use of the pathway by the MCF host. Computational tools such as (i de novo biosynthetic pathway builders, (ii docking, (iii molecular dynamics (MD and steered MD (SMD, and (iv genome-scale metabolic flux modeling all play critical roles in the rational design of an MCF. Genome-scale metabolic flux models are of considerable use to the design process since they can reveal metabolic capabilities of MCF hosts. These can be used for host selection as well as optimizing precursors and cofactors of artificial de novo biosynthetic pathways. In addition, recent advances in genome-scale modeling have enabled the derivation of metabolic engineering strategies, which can be implemented using the genomic tools reviewed here as well.

  9. Determinism and Contingency Shape Metabolic Complementation in an Endosymbiotic Consortium.

    Science.gov (United States)

    Ponce-de-Leon, Miguel; Tamarit, Daniel; Calle-Espinosa, Jorge; Mori, Matteo; Latorre, Amparo; Montero, Francisco; Pereto, Juli

    2017-01-01

    Bacterial endosymbionts and their insect hosts establish an intimate metabolic relationship. Bacteria offer a variety of essential nutrients to their hosts, whereas insect cells provide the necessary sources of matter and energy to their tiny metabolic allies. These nutritional complementations sustain themselves on a diversity of metabolite exchanges between the cell host and the reduced yet highly specialized bacterial metabolism-which, for instance, overproduces a small set of essential amino acids and vitamins. A well-known case of metabolic complementation is provided by the cedar aphid Cinara cedri that harbors two co-primary endosymbionts, Buchnera aphidicola BCc and Ca . Serratia symbiotica SCc, and in which some metabolic pathways are partitioned between different partners. Here we present a genome-scale metabolic network (GEM) for the bacterial consortium from the cedar aphid i BSCc. The analysis of this GEM allows us the confirmation of cases of metabolic complementation previously described by genome analysis (i.e., tryptophan and biotin biosynthesis) and the redefinition of an event of metabolic pathway sharing between the two endosymbionts, namely the biosynthesis of tetrahydrofolate. In silico knock-out experiments with i BSCc showed that the consortium metabolism is a highly integrated yet fragile network. We also have explored the evolutionary pathways leading to the emergence of metabolic complementation between reduced metabolisms starting from individual, complete networks. Our results suggest that, during the establishment of metabolic complementation in endosymbionts, adaptive evolution is significant in the case of tryptophan biosynthesis, whereas vitamin production pathways seem to adopt suboptimal solutions.

  10. Genome-scale data suggest reclassifications in the Leisingera-Phaeobacter cluster including proposals for Sedimentitalea gen. nov. and Pseudophaeobacter gen. nov.

    Directory of Open Access Journals (Sweden)

    Sven eBreider

    2014-08-01

    Full Text Available Earlier phylogenetic analyses of the marine Rhodobacteraceae (class Alphaproteobacteria genera Leisingera and Phaeobacter indicated that neither genus might be monophyletic. We here used phylogenetic reconstruction from genome-scale data, MALDI-TOF mass-spectrometry analysis and a re-assessment of the phenotypic data from the literature to settle this matter, aiming at a reclassification of the two genera. Neither Phaeobacter nor Leisingera formed a clade in any of the phylogenetic analyses conducted. Rather, smaller monophyletic assemblages emerged, which were phenotypically more homogeneous, too. We thus propose the reclassification of Leisingera nanhaiensis as the type species of a new genus as Sedimentitalea nanhaiensis gen. nov., comb. nov., the reclassification of Phaeobacter arcticus and Phaeobacter leonis as Pseudophaeobacter arcticus gen. nov., comb. nov. and Pseudophaeobacter leonis comb. nov., and the reclassification of Phaeobacter aquaemixtae, Phaeobacter caeruleus and Phaeobacter daeponensis as Leisingera aquaemixtae comb. nov., Leisingera caerulea comb. nov. and Leisingera daeponensis comb. nov. The genera Phaeobacter and Leisingera are accordingly emended.

  11. Dynamics of the Saccharomyces cerevisiae Transcriptome during Bread Dough Fermentation

    Science.gov (United States)

    Aslankoohi, Elham; Zhu, Bo; Rezaei, Mohammad Naser; Voordeckers, Karin; De Maeyer, Dries; Marchal, Kathleen; Dornez, Emmie

    2013-01-01

    The behavior of yeast cells during industrial processes such as the production of beer, wine, and bioethanol has been extensively studied. In contrast, our knowledge about yeast physiology during solid-state processes, such as bread dough, cheese, or cocoa fermentation, remains limited. We investigated changes in the transcriptomes of three genetically distinct Saccharomyces cerevisiae strains during bread dough fermentation. Our results show that regardless of the genetic background, all three strains exhibit similar changes in expression patterns. At the onset of fermentation, expression of glucose-regulated genes changes dramatically, and the osmotic stress response is activated. The middle fermentation phase is characterized by the induction of genes involved in amino acid metabolism. Finally, at the latest time point, cells suffer from nutrient depletion and activate pathways associated with starvation and stress responses. Further analysis shows that genes regulated by the high-osmolarity glycerol (HOG) pathway, the major pathway involved in the response to osmotic stress and glycerol homeostasis, are among the most differentially expressed genes at the onset of fermentation. More importantly, deletion of HOG1 and other genes of this pathway significantly reduces the fermentation capacity. Together, our results demonstrate that cells embedded in a solid matrix such as bread dough suffer severe osmotic stress and that a proper induction of the HOG pathway is critical for optimal fermentation. PMID:24056467

  12. Dynamics of the Saccharomyces cerevisiae transcriptome during bread dough fermentation.

    Science.gov (United States)

    Aslankoohi, Elham; Zhu, Bo; Rezaei, Mohammad Naser; Voordeckers, Karin; De Maeyer, Dries; Marchal, Kathleen; Dornez, Emmie; Courtin, Christophe M; Verstrepen, Kevin J

    2013-12-01

    The behavior of yeast cells during industrial processes such as the production of beer, wine, and bioethanol has been extensively studied. In contrast, our knowledge about yeast physiology during solid-state processes, such as bread dough, cheese, or cocoa fermentation, remains limited. We investigated changes in the transcriptomes of three genetically distinct Saccharomyces cerevisiae strains during bread dough fermentation. Our results show that regardless of the genetic background, all three strains exhibit similar changes in expression patterns. At the onset of fermentation, expression of glucose-regulated genes changes dramatically, and the osmotic stress response is activated. The middle fermentation phase is characterized by the induction of genes involved in amino acid metabolism. Finally, at the latest time point, cells suffer from nutrient depletion and activate pathways associated with starvation and stress responses. Further analysis shows that genes regulated by the high-osmolarity glycerol (HOG) pathway, the major pathway involved in the response to osmotic stress and glycerol homeostasis, are among the most differentially expressed genes at the onset of fermentation. More importantly, deletion of HOG1 and other genes of this pathway significantly reduces the fermentation capacity. Together, our results demonstrate that cells embedded in a solid matrix such as bread dough suffer severe osmotic stress and that a proper induction of the HOG pathway is critical for optimal fermentation.

  13. Functional expression of rat VPAC1 receptor in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hansen, M.K.; Tams, J.W.; Fahrenkrug, Jan

    1999-01-01

    G protein-coupled receptor; heterologous expression; membrane protein; Saccharomyces cerevisiae, vasoactive intestinal polypeptide; yeast mating factor-pre-pro *Ga-leader peptide......G protein-coupled receptor; heterologous expression; membrane protein; Saccharomyces cerevisiae, vasoactive intestinal polypeptide; yeast mating factor-pre-pro *Ga-leader peptide...

  14. Investigation of autonomous cell cycle oscillation in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Hansen, Morten Skov

    2007-01-01

    Autonome Oscillationer i kontinuert kultivering af Saccharomyces cerevisiae Udgangspunktet for dette Ph.d. projekt var at søge at forstå, hvad der gør det muligt at opnå multiple statiske tilstande ved kontinuert kultivering af Saccharomyces cerevisiae med glukose som begrænsende substrat...

  15. Flux-Enabled Exploration of the Role of Sip1 in galactose yeast metabolism

    DEFF Research Database (Denmark)

    Shymansky, Christopher M.; Wang, George; Baidoo, Edward E. K.

    2017-01-01

    13C metabolic flux analysis (13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon kn...

  16. A tetO Toolkit To Alter Expression of Genes in Saccharomyces cerevisiae.

    Science.gov (United States)

    Cuperus, Josh T; Lo, Russell S; Shumaker, Lucia; Proctor, Julia; Fields, Stanley

    2015-07-17

    Strategies to optimize a metabolic pathway often involve building a large collection of strains, each containing different versions of sequences that regulate the expression of pathway genes. Here, we develop reagents and methods to carry out this process at high efficiency in the yeast Saccharomyces cerevisiae. We identify variants of the Escherichia coli tet operator (tetO) sequence that bind a TetR-VP16 activator with differential affinity and therefore result in different TetR-VP16 activator-driven expression. By recombining these variants upstream of the genes of a pathway, we generate unique combinations of expression levels. Here, we built a tetO toolkit, which includes the I-OnuI homing endonuclease to create double-strand breaks, which increases homologous recombination by 10(5); a plasmid carrying six variant tetO sequences flanked by I-OnuI sites, uncoupling transformation and recombination steps; an S. cerevisiae-optimized TetR-VP16 activator; and a vector to integrate constructs into the yeast genome. We introduce into the S. cerevisiae genome the three crt genes from Erwinia herbicola required for yeast to synthesize lycopene and carry out the recombination process to produce a population of cells with permutations of tetO variants regulating the three genes. We identify 0.7% of this population as making detectable lycopene, of which the vast majority have undergone recombination at all three crt genes. We estimate a rate of ∼20% recombination per targeted site, much higher than that obtained in other studies. Application of this toolkit to medically or industrially important end products could reduce the time and labor required to optimize the expression of a set of metabolic genes.

  17. Flux networks in metabolic graphs

    International Nuclear Information System (INIS)

    Warren, P B; Queiros, S M Duarte; Jones, J L

    2009-01-01

    A metabolic model can be represented as a bipartite graph comprising linked reaction and metabolite nodes. Here it is shown how a network of conserved fluxes can be assigned to the edges of such a graph by combining the reaction fluxes with a conserved metabolite property such as molecular weight. A similar flux network can be constructed by combining the primal and dual solutions to the linear programming problem that typically arises in constraint-based modelling. Such constructions may help with the visualization of flux distributions in complex metabolic networks. The analysis also explains the strong correlation observed between metabolite shadow prices (the dual linear programming variables) and conserved metabolite properties. The methods were applied to recent metabolic models for Escherichia coli, Saccharomyces cerevisiae and Methanosarcina barkeri. Detailed results are reported for E. coli; similar results were found for other organisms

  18. Metabolism related toxicity of diclofenac in yeast as model system

    NARCIS (Netherlands)

    van Leeuwen, J.S.; Vredenburg, G.; Dragovic, S.; Tjong, T.F.; Vos, J.C.; Vermeulen, N.P.E.

    2010-01-01

    Diclofenac is a widely used drug that can cause serious hepatotoxicity, which has been linked to metabolism by cytochrome P450s (P450). To investigate the role of oxidative metabolites in diclofenac toxicity, a model for P450-related toxicity was set up in Saccharomyces cerevisiae. We expressed a

  19. Modeling metabolic response to changes of enzyme amount in ...

    African Journals Online (AJOL)

    Based on the work of Hynne et al. (2001), in an in silico model of glycolysis, Saccharomyces cerevisiae is established by introducing an enzyme amount multiple factor (.) into the kinetic equations. The model is aimed to predict the metabolic response to the change of enzyme amount. With the help of .α, the amounts of ...

  20. Engineering and two-stage evolution of a lignocellulosic hydrolysate-tolerant Saccharomyces cerevisiae strain for anaerobic fermentation of xylose from AFEX pretreated corn stover.

    Directory of Open Access Journals (Sweden)

    Lucas S Parreiras

    Full Text Available The inability of the yeast Saccharomyces cerevisiae to ferment xylose effectively under anaerobic conditions is a major barrier to economical production of lignocellulosic biofuels. Although genetic approaches have enabled engineering of S. cerevisiae to convert xylose efficiently into ethanol in defined lab medium, few strains are able to ferment xylose from lignocellulosic hydrolysates in the absence of oxygen. This limited xylose conversion is believed to result from small molecules generated during biomass pretreatment and hydrolysis, which induce cellular stress and impair metabolism. Here, we describe the development of a xylose-fermenting S. cerevisiae strain with tolerance to a range of pretreated and hydrolyzed lignocellulose, including Ammonia Fiber Expansion (AFEX-pretreated corn stover hydrolysate (ACSH. We genetically engineered a hydrolysate-resistant yeast strain with bacterial xylose isomerase and then applied two separate stages of aerobic and anaerobic directed evolution. The emergent S. cerevisiae strain rapidly converted xylose from lab medium and ACSH to ethanol under strict anaerobic conditions. Metabolomic, genetic and biochemical analyses suggested that a missense mutation in GRE3, which was acquired during the anaerobic evolution, contributed toward improved xylose conversion by reducing intracellular production of xylitol, an inhibitor of xylose isomerase. These results validate our combinatorial approach, which utilized phenotypic strain selection, rational engineering and directed evolution for the generation of a robust S. cerevisiae strain with the ability to ferment xylose anaerobically from ACSH.

  1. Apoptosis - Triggering Effects: UVB-irradiation and Saccharomyces cerevisiae.

    Science.gov (United States)

    Behzadi, Payam; Behzadi, Elham

    2012-12-01

    The pathogenic disturbance of Saccharomyces cerevisiae is known as a rare but invasive nosocomial fungal infection. This survey is focused on the evaluation of apoptosis-triggering effects of UVB-irradiation in Saccharomyces cerevisiae. The well-growth colonies of Saccharomyces cerevisiae on Sabouraud Dextrose Agar (SDA) were irradiated within an interval of 10 minutes by UVB-light (302 nm). Subsequently, the harvested DNA molecules of control and UV-exposed yeast colonies were run through the 1% agarose gel electrophoresis comprising the luminescent dye of ethidium bromide. No unusual patterns including DNA laddering bands or smears were detected. The applied procedure for UV exposure was not effective for inducing apoptosis in Saccharomyces cerevisiae. So, it needs another UV-radiation protocol for inducing apoptosis phenomenon in Saccharomyces cerevisiae.

  2. Metabolic Engineering of Probiotic Saccharomyces boulardii

    OpenAIRE

    Liu, Jing-Jing; Kong, In Iok; Zhang, Guo-Chang; Jayakody, Lahiru N.; Kim, Heejin; Xia, Peng-Fei; Kwak, Suryang; Sung, Bong Hyun; Sohn, Jung-Hoon; Walukiewicz, Hanna E.; Rao, Christopher V.; Jin, Yong-Su

    2016-01-01

    Saccharomyces boulardii is a probiotic yeast that has been used for promoting gut health as well as preventing diarrheal diseases. This yeast not only exhibits beneficial phenotypes for gut health but also can stay longer in the gut than Saccharomyces cerevisiae. Therefore, S. boulardii is an attractive host for metabolic engineering to produce biomolecules of interest in the gut. However, the lack of auxotrophic strains with defined genetic backgrounds has hampered the use of this strain for...

  3. Kinetics of phosphomevalonate kinase from Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    David E Garcia

    Full Text Available The mevalonate-based isoprenoid biosynthetic pathway is responsible for producing cholesterol in humans and is used commercially to produce drugs, chemicals, and fuels. Heterologous expression of this pathway in Escherichia coli has enabled high-level production of the antimalarial drug artemisinin and the proposed biofuel bisabolane. Understanding the kinetics of the enzymes in the biosynthetic pathway is critical to optimize the pathway for high flux. We have characterized the kinetic parameters of phosphomevalonate kinase (PMK, EC 2.7.4.2 from Saccharomyces cerevisiae, a previously unstudied enzyme. An E. coli codon-optimized version of the S. cerevisiae gene was cloned into pET-52b+, then the C-terminal 6X His-tagged protein was expressed in E. coli BL21(DE3 and purified on a Ni²⁺ column. The KM of the ATP binding site was determined to be 98.3 µM at 30°C, the optimal growth temperature for S. cerevisiae, and 74.3 µM at 37°C, the optimal growth temperature for E. coli. The K(M of the mevalonate-5-phosphate binding site was determined to be 885 µM at 30°C and 880 µM at 37°C. The V(max was determined to be 4.51 µmol/min/mg enzyme at 30°C and 5.33 µmol/min/mg enzyme at 37°C. PMK is Mg²⁺ dependent, with maximal activity achieved at concentrations of 10 mM or greater. Maximum activity was observed at pH = 7.2. PMK was not found to be substrate inhibited, nor feedback inhibited by FPP at concentrations up to 10 µM FPP.

  4. Perspectives in metabolic engineering: understanding cellular regulation towards the control of metabolic routes.

    Science.gov (United States)

    Zadran, Sohila; Levine, Raphael D

    2013-01-01

    Metabolic engineering seeks to redirect metabolic pathways through the modification of specific biochemical reactions or the introduction of new ones with the use of recombinant technology. Many of the chemicals synthesized via introduction of product-specific enzymes or the reconstruction of entire metabolic pathways into engineered hosts that can sustain production and can synthesize high yields of the desired product as yields of natural product-derived compounds are frequently low, and chemical processes can be both energy and material expensive; current endeavors have focused on using biologically derived processes as alternatives to chemical synthesis. Such economically favorable manufacturing processes pursue goals related to sustainable development and "green chemistry". Metabolic engineering is a multidisciplinary approach, involving chemical engineering, molecular biology, biochemistry, and analytical chemistry. Recent advances in molecular biology, genome-scale models, theoretical understanding, and kinetic modeling has increased interest in using metabolic engineering to redirect metabolic fluxes for industrial and therapeutic purposes. The use of metabolic engineering has increased the productivity of industrially pertinent small molecules, alcohol-based biofuels, and biodiesel. Here, we highlight developments in the practical and theoretical strategies and technologies available for the metabolic engineering of simple systems and address current limitations.

  5. Construction of novel Saccharomyces cerevisiae strains for bioethanol active dry yeast (ADY) production.

    Science.gov (United States)

    Zheng, Daoqiong; Zhang, Ke; Gao, Kehui; Liu, Zewei; Zhang, Xing; Li, Ou; Sun, Jianguo; Zhang, Xiaoyang; Du, Fengguang; Sun, Peiyong; Qu, Aimin; Wu, Xuechang

    2013-01-01

    The application of active dry yeast (ADY) in bioethanol production simplifies operation processes and reduces the risk of bacterial contamination. In the present study, we constructed a novel ADY strain with improved stress tolerance and ethanol fermentation performances under stressful conditions. The industrial Saccharomyces cerevisiae strain ZTW1 showed excellent properties and thus subjected to a modified whole-genome shuffling (WGS) process to improve its ethanol titer, proliferation capability, and multiple stress tolerance for ADY production. The best-performing mutant, Z3-86, was obtained after three rounds of WGS, producing 4.4% more ethanol and retaining 2.15-fold higher viability than ZTW1 after drying. Proteomics and physiological analyses indicated that the altered expression patterns of genes involved in protein metabolism, plasma membrane composition, trehalose metabolism, and oxidative responses contribute to the trait improvement of Z3-86. This work not only successfully developed a novel S. cerevisiae mutant for application in commercial bioethanol production, but also enriched the current understanding of how WGS improves the complex traits of microbes.

  6. Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

    Science.gov (United States)

    Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

    2014-05-01

    Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

  7. Enhanced production of para-hydroxybenzoic acid by genetically engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Averesch, Nils J H; Prima, Alex; Krömer, Jens O

    2017-08-01

    Saccharomyces cerevisiae is a popular organism for metabolic engineering; however, studies aiming at over-production of bio-replacement precursors for the chemical industry often fail to overcome proof-of-concept stage. When intending to show real industrial attractiveness, the challenge is twofold: formation of the target compound must be increased, while minimizing the formation of side and by-products to maximize titer, rate and yield. To tackle these, the metabolism of the organism, as well as the parameters of the process, need to be optimized. Addressing both we show that S. cerevisiae is well-suited for over-production of aromatic compounds, which are valuable in chemical industry and are particularly useful in space technology. Specifically, a strain engineered to accumulate chorismate was optimized for formation of para-hydroxybenzoic acid. Then a fed-batch bioreactor process was developed, which delivered a final titer of 2.9 g/L, a maximum rate of 18.625 mg pHBA /(g CDW  × h) and carbon-yields of up to 3.1 mg pHBA /g glucose .

  8. Repurposing the Saccharomyces cerevisiae peroxisome for compartmentalizing multi-enzyme pathways

    Energy Technology Data Exchange (ETDEWEB)

    DeLoache, William [Univ. of California, Berkeley, CA (United States); Russ, Zachary [Univ. of California, Berkeley, CA (United States); Samson, Jennifer [Univ. of California, Berkeley, CA (United States); Dueber, John [Univ. of California, Berkeley, CA (United States)

    2017-09-25

    The peroxisome of Saccharomyces cerevisiae was targeted for repurposing in order to create a synthetic organelle that provides a generalizable compartment for engineered metabolic pathways. Compartmentalization of enzymes into organelles is a promising strategy for limiting metabolic crosstalk, improving pathway efficiency, and ultimately modifying the chemical environment to be distinct from that of the cytoplasm. We focused on the Saccharomyces cerevisiae peroxisome, as this organelle is not required for viability when grown on conventional media. We identified an enhanced peroxisomal targeting signal type 1 (PTS1) for rapidly importing non-native cargo proteins. Additionally, we performed the first systematic in vivo measurements of nonspecific metabolite permeability across the peroxisomal membrane using a polymer exclusion assay and characterized the size dependency of metabolite trafficking. Finally, we applied these new insights to compartmentalize a two-enzyme pathway in the peroxisome and characterize the expression regimes where compartmentalization leads to improved product titer. This work builds a foundation for using the peroxisome as a synthetic organelle, highlighting both promise and future challenges on the way to realizing this goal.

  9. The genetic basis of natural variation in oenological traits in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Francisco Salinas

    Full Text Available Saccharomyces cerevisiae is the main microorganism responsible for wine alcoholic fermentation. The oenological phenotypes resulting from fermentation, such as the production of acetic acid, glycerol, and residual sugar concentration are regulated by multiple genes and vary quantitatively between different strain backgrounds. With the aim of identifying the quantitative trait loci (QTLs that regulate oenological phenotypes, we performed linkage analysis using three crosses between highly diverged S. cerevisiae strains. Segregants from each cross were used as starter cultures for 20-day fermentations, in synthetic wine must, to simulate actual winemaking conditions. Linkage analysis on phenotypes of primary industrial importance resulted in the mapping of 18 QTLs. We tested 18 candidate genes, by reciprocal hemizygosity, for their contribution to the observed phenotypic variation, and validated five genes and the chromosome II right subtelomeric region. We observed that genes involved in mitochondrial metabolism, sugar transport, nitrogen metabolism, and the uncharacterized ORF YJR030W explained most of the phenotypic variation in oenological traits. Furthermore, we experimentally validated an exceptionally strong epistatic interaction resulting in high level of succinic acid between the Sake FLX1 allele and the Wine/European MDH2 allele. Overall, our work demonstrates the complex genetic basis underlying wine traits, including natural allelic variation, antagonistic linked QTLs and complex epistatic interactions between alleles from strains with different evolutionary histories.

  10. Construction of novel Saccharomyces cerevisiae strains for bioethanol active dry yeast (ADY production.

    Directory of Open Access Journals (Sweden)

    Daoqiong Zheng

    Full Text Available The application of active dry yeast (ADY in bioethanol production simplifies operation processes and reduces the risk of bacterial contamination. In the present study, we constructed a novel ADY strain with improved stress tolerance and ethanol fermentation performances under stressful conditions. The industrial Saccharomyces cerevisiae strain ZTW1 showed excellent properties and thus subjected to a modified whole-genome shuffling (WGS process to improve its ethanol titer, proliferation capability, and multiple stress tolerance for ADY production. The best-performing mutant, Z3-86, was obtained after three rounds of WGS, producing 4.4% more ethanol and retaining 2.15-fold higher viability than ZTW1 after drying. Proteomics and physiological analyses indicated that the altered expression patterns of genes involved in protein metabolism, plasma membrane composition, trehalose metabolism, and oxidative responses contribute to the trait improvement of Z3-86. This work not only successfully developed a novel S. cerevisiae mutant for application in commercial bioethanol production, but also enriched the current understanding of how WGS improves the complex traits of microbes.

  11. Mechanisms of iron sensing and regulation in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Martínez-Pastor, María Teresa; Perea-García, Ana; Puig, Sergi

    2017-04-01

    Iron is a redox active element that functions as an essential cofactor in multiple metabolic pathways, including respiration, DNA synthesis and translation. While indispensable for eukaryotic life, excess iron can lead to oxidative damage of macromolecules. Therefore, living organisms have developed sophisticated strategies to optimally regulate iron acquisition, storage and utilization in response to fluctuations in environmental iron bioavailability. In the yeast Saccharomyces cerevisiae, transcription factors Aft1/Aft2 and Yap5 regulate iron metabolism in response to low and high iron levels, respectively. In addition to producing and assembling iron cofactors, mitochondrial iron-sulfur (Fe/S) cluster biogenesis has emerged as a central player in iron sensing. A mitochondrial signal derived from Fe/S synthesis is exported and converted into an Fe/S cluster that interacts directly with Aft1/Aft2 and Yap5 proteins to regulate their transcriptional function. Various conserved proteins, such as ABC mitochondrial transporter Atm1 and, for Aft1/Aft2, monothiol glutaredoxins Grx3 and Grx4 are implicated in this iron-signaling pathway. The analysis of a wide range of S. cerevisiae strains of different geographical origins and sources has shown that yeast strains adapted to high iron display growth defects under iron-deficient conditions, and highlighted connections that exist in the response to both opposite conditions. Changes in iron accumulation and gene expression profiles suggest differences in the regulation of iron homeostasis genes.

  12. New paradigms for metabolic modeling of human cells

    DEFF Research Database (Denmark)

    Mardinoglu, Adil; Nielsen, Jens

    2015-01-01

    review recent work on reconstruction of GEMs for human cell/tissue types and cancer, and the use of GEMs for identification of metabolic changes occurring in response to disease development. We further discuss how GEMs can be used for the development of efficient therapeutic strategies. Finally......, challenges in integration of cell/tissue models for simulation of whole body functions as well as integration of GEMs with other biological networks for generating complete cell/tissue models are presented.......Abnormalities in cellular functions are associated with the progression of human diseases, often resulting in metabolic reprogramming. GEnome-scale metabolic Models (GEMs) have enabled studying global metabolic reprogramming in connection with disease development in a systematic manner. Here we...

  13. Efficient screening of environmental isolates for Saccharomyces cerevisiae strains that are suitable for brewing.

    Science.gov (United States)

    Fujihara, Hidehiko; Hino, Mika; Takashita, Hideharu; Kajiwara, Yasuhiro; Okamoto, Keiko; Furukawa, Kensuke

    2014-01-01

    We developed an efficient screening method for Saccharomyces cerevisiae strains from environmental isolates. MultiPlex PCR was performed targeting four brewing S. cerevisiae genes (SSU1, AWA1, BIO6, and FLO1). At least three genes among the four were amplified from all S. cerevisiae strains. The use of this method allowed us to successfully obtain S. cerevisiae strains.

  14. In vitro screening of probiotic properties of Saccharomyces cerevisiae var. boulardii and food-borne Saccharomyces cerevisiae strains

    DEFF Research Database (Denmark)

    van der Aa Kuhle, Alis; Skovgaard, Kerstin; Jespersen, Lene

    2005-01-01

    .6-16.8%) recorded for two isolates from blue veined cheeses. Merely 25% of the S. cerevisiae var. boulardii strains displayed good adhesive properties (16.2-28.0%). The expression of the proinflammatory cytokine IL-1α decreased strikingly in IPEC-J2 cells exposed to a Shiga-like toxin 2e producing Escherichia coli...... strain when the cells were pre- and coincubated with S. cerevisiae var. boulardii even though this yeast strain was low adhesive (5.4%), suggesting that adhesion is not a mandatory prerequisite for such a probiotic effect. A strain of S. cerevisiae isolated from West African sorghum beer exerted similar......The probiotic potential of IS Saccharomyces cerevisiae strains used for production of foods or bevel-ages or isolated from such, and eight strains of Saccharomyces cerevisiae var. boulardii, was investigated. All strains included were able to withstand pH 2.5 and 0.3% Ox-all. Adhesion...

  15. Simultaneous and Sequential Integration by Cre/loxP Site-Specific Recombination in Saccharomyces cerevisiae.

    Science.gov (United States)

    Choi, Ho-Jung; Kim, Yeon-Hee

    2018-05-28

    A Cre/ loxP -δ-integration system was developed to allow sequential and simultaneous integration of a multiple gene expression cassette in Saccharomyces cerevisiae . To allow repeated integrations, the reusable Candida glabrata MARKER ( CgMARKER ) carrying loxP sequences was used, and the integrated CgMARKER was efficiently removed by inducing Cre recombinase. The XYLP and XYLB genes encoding endoxylanase and β-xylosidase, respectively, were used as model genes for xylan metabolism in this system, and the copy number of these genes was increased to 15.8 and 16.9 copies/cell, respectively, by repeated integration. This integration system is a promising approach for the easy construction of yeast strains with enhanced metabolic pathways through multicopy gene expression.

  16. Fatty acid-derived biofuels and chemicals production in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Yongjin J. Zhou

    2014-09-01

    Full Text Available Volatile energy costs and environmental concerns have spurred interest in the development of alternative, renewable, sustainable and cost-effective energy resources. Advanced biofuels have potential to replace fossil fuels in supporting high-power demanding machinery such as aircrafts and trucks. Microbial biosynthesis is generally considered as an environmental friendly refinery process, and fatty acid biosynthesis is an attractive route to synthesize chemicals and especially drop-in biofuels due to the high degree of reduction of fatty acids. The robustness and excellent accessibility to molecular genetics make the yeast S. cerevisiae a suitable host for the production of biofuels, chemicals and pharmaceuticals, and recent advances in metabolic engineering as well as systems and synthetic biology allow us to engineer the yeast fatty acid metabolism and modification pathways for production of advanced biofuels and chemicals.

  17. EasyCloneMulti: A Set of Vectors for Simultaneous and Multiple Genomic Integrations in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Maury, Jerome; Germann, Susanne Manuela; Jacobsen,