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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. 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...

  5. 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.

  6. 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...

  7. 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...

  8. 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...

  9. 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...

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

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    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.

  11. 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.

  12. 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....

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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....

  16. 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.

  17. 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.

  18. 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...

  19. 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...

  20. 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....

  1. 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...

  2. 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

  3. 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

  4. 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.

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

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    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.

  6. 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

  7. 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

  8. Genomic structural variation contributes to phenotypic change of industrial bioethanol yeast Saccharomyces cerevisiae.

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    Zhang, Ke; Zhang, Li-Jie; Fang, Ya-Hong; Jin, Xin-Na; Qi, Lei; Wu, Xue-Chang; Zheng, Dao-Qiong

    2016-03-01

    Genomic structural variation (GSV) is a ubiquitous phenomenon observed in the genomes of Saccharomyces cerevisiae strains with different genetic backgrounds; however, the physiological and phenotypic effects of GSV are not well understood. Here, we first revealed the genetic characteristics of a widely used industrial S. cerevisiae strain, ZTW1, by whole genome sequencing. ZTW1 was identified as an aneuploidy strain and a large-scale GSV was observed in the ZTW1 genome compared with the genome of a diploid strain YJS329. These GSV events led to copy number variations (CNVs) in many chromosomal segments as well as one whole chromosome in the ZTW1 genome. Changes in the DNA dosage of certain functional genes directly affected their expression levels and the resultant ZTW1 phenotypes. Moreover, CNVs of large chromosomal regions triggered an aneuploidy stress in ZTW1. This stress decreased the proliferation ability and tolerance of ZTW1 to various stresses, while aneuploidy response stress may also provide some benefits to the fermentation performance of the yeast, including increased fermentation rates and decreased byproduct generation. This work reveals genomic characters of the bioethanol S. cerevisiae strain ZTW1 and suggests that GSV is an important kind of mutation that changes the traits of industrial S. cerevisiae strains. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

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    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. 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.

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

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    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.

  12. 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.

  13. 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...

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

    Science.gov (United States)

    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.

  15. 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.

  16. 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...

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

    Directory of Open Access Journals (Sweden)

    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

  18. 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.

  19. 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.

  20. Large-scale functional genomic analysis of sporulation and meiosis in Saccharomyces cerevisiae.

    OpenAIRE

    Enyenihi, Akon H; Saunders, William S

    2003-01-01

    We have used a single-gene deletion mutant bank to identify the genes required for meiosis and sporulation among 4323 nonessential Saccharomyces cerevisiae annotated open reading frames (ORFs). Three hundred thirty-four sporulation-essential genes were identified, including 78 novel ORFs and 115 known genes without previously described sporulation defects in the comprehensive Saccharomyces Genome (SGD) or Yeast Proteome (YPD) phenotype databases. We have further divided the uncharacterized sp...

  1. Metabolite coupling in genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Palsson Bernhard Ø

    2006-03-01

    Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

  2. 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....

  3. 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.

  4. 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.

  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. Genomic reconstruction to improve bioethanol and ergosterol production of industrial yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Zhang, Ke; Tong, Mengmeng; Gao, Kehui; Di, Yanan; Wang, Pinmei; Zhang, Chunfang; Wu, Xuechang; Zheng, Daoqiong

    2015-02-01

    Baker's yeast (Saccharomyces cerevisiae) is the common yeast used in the fields of bread making, brewing, and bioethanol production. Growth rate, stress tolerance, ethanol titer, and byproducts yields are some of the most important agronomic traits of S. cerevisiae for industrial applications. Here, we developed a novel method of constructing S. cerevisiae strains for co-producing bioethanol and ergosterol. The genome of an industrial S. cerevisiae strain, ZTW1, was first reconstructed through treatment with an antimitotic drug followed by sporulation and hybridization. A total of 140 mutants were selected for ethanol fermentation testing, and a significant positive correlation between ergosterol content and ethanol production was observed. The highest performing mutant, ZG27, produced 7.9 % more ethanol and 43.2 % more ergosterol than ZTW1 at the end of fermentation. Chromosomal karyotyping and proteome analysis of ZG27 and ZTW1 suggested that this breeding strategy caused large-scale genome structural variations and global gene expression diversities in the mutants. Genetic manipulation further demonstrated that the altered expression activity of some genes (such as ERG1, ERG9, and ERG11) involved in ergosterol synthesis partly explained the trait improvement in ZG27.

  7. 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.

  8. 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.

  9. 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

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

    Directory of Open Access Journals (Sweden)

    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

  11. Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

    Directory of Open Access Journals (Sweden)

    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.

  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. 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.

  14. 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.

  15. 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.

  16. EasyCloneMulti: A Set of Vectors for Simultaneous and Multiple Genomic Integrations in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Maury, Jerome; Germann, Susanne Manuela; Jacobsen, Simo Abdessamad

    2016-01-01

    Saccharomyces cerevisiae is widely used in the biotechnology industry for production of ethanol, recombinant proteins, food ingredients and other chemicals. In order to generate highly producing and stable strains, genome integration of genes encoding metabolic pathway enzymes is the preferred...... of integrative vectors, EasyCloneMulti, that enables multiple and simultaneous integration of genes in S. cerevisiae. By creating vector backbones that combine consensus sequences that aim at targeting subsets of Ty sequences and a quickly degrading selective marker, integrations at multiple genomic loci...... and a range of expression levels were obtained, as assessed with the green fluorescent protein (GFP) reporter system. The EasyCloneMulti vector set was applied to balance the expression of the rate-controlling step in the β-alanine pathway for biosynthesis of 3-hydroxypropionic acid (3HP). The best 3HP...

  17. 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.

  18. 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

  19. 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

  20. 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 ...

  1. GEMMER: GEnome-wide tool for Multi-scale Modeling data Extraction and Representation for Saccharomyces cerevisiae.

    Science.gov (United States)

    Mondeel, Thierry D G A; Crémazy, Frédéric; Barberis, Matteo

    2018-02-01

    Multi-scale modeling of biological systems requires integration of various information about genes and proteins that are connected together in networks. Spatial, temporal and functional information is available; however, it is still a challenge to retrieve and explore this knowledge in an integrated, quick and user-friendly manner. We present GEMMER (GEnome-wide tool for Multi-scale Modelling data Extraction and Representation), a web-based data-integration tool that facilitates high quality visualization of physical, regulatory and genetic interactions between proteins/genes in Saccharomyces cerevisiae. GEMMER creates network visualizations that integrate information on function, temporal expression, localization and abundance from various existing databases. GEMMER supports modeling efforts by effortlessly gathering this information and providing convenient export options for images and their underlying data. GEMMER is freely available at http://gemmer.barberislab.com. Source code, written in Python, JavaScript library D3js, PHP and JSON, is freely available at https://github.com/barberislab/GEMMER. M.Barberis@uva.nl. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

  2. 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

  3. 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....

  4. 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

  5. Phylogenetic distribution of large-scale genome patchiness

    Directory of Open Access Journals (Sweden)

    Hackenberg Michael

    2008-04-01

    Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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....

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  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. Metabolic engineering of strains: from industrial-scale to lab-scale chemical production.

    Science.gov (United States)

    Sun, Jie; Alper, Hal S

    2015-03-01

    A plethora of successful metabolic engineering case studies have been published over the past several decades. Here, we highlight a collection of microbially produced chemicals using a historical framework, starting with titers ranging from industrial scale (more than 50 g/L), to medium-scale (5-50 g/L), and lab-scale (0-5 g/L). Although engineered Escherichia coli and Saccharomyces cerevisiae emerge as prominent hosts in the literature as a result of well-developed genetic engineering tools, several novel native-producing strains are gaining attention. This review catalogs the current progress of metabolic engineering towards production of compounds such as acids, alcohols, amino acids, natural organic compounds, and others.

  19. Techniques for Large-Scale Bacterial Genome Manipulation and Characterization of the Mutants with Respect to In Silico Metabolic Reconstructions.

    Science.gov (United States)

    diCenzo, George C; Finan, Turlough M

    2018-01-01

    The rate at which all genes within a bacterial genome can be identified far exceeds the ability to characterize these genes. To assist in associating genes with cellular functions, a large-scale bacterial genome deletion approach can be employed to rapidly screen tens to thousands of genes for desired phenotypes. Here, we provide a detailed protocol for the generation of deletions of large segments of bacterial genomes that relies on the activity of a site-specific recombinase. In this procedure, two recombinase recognition target sequences are introduced into known positions of a bacterial genome through single cross-over plasmid integration. Subsequent expression of the site-specific recombinase mediates recombination between the two target sequences, resulting in the excision of the intervening region and its loss from the genome. We further illustrate how this deletion system can be readily adapted to function as a large-scale in vivo cloning procedure, in which the region excised from the genome is captured as a replicative plasmid. We next provide a procedure for the metabolic analysis of bacterial large-scale genome deletion mutants using the Biolog Phenotype MicroArray™ system. Finally, a pipeline is described, and a sample Matlab script is provided, for the integration of the obtained data with a draft metabolic reconstruction for the refinement of the reactions and gene-protein-reaction relationships in a metabolic reconstruction.

  20. 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...

  1. 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.

  2. 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

  3. 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

  4. 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

  5. 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

  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. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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

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

    Directory of Open Access Journals (Sweden)

    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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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

  4. 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.

  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. 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

  7. 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...

  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. 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...

  10. Genomic Evolution of Saccharomyces cerevisiae under Chinese Rice Wine Fermentation

    Science.gov (United States)

    Li, Yudong; Zhang, Weiping; Zheng, Daoqiong; Zhou, Zhan; Yu, Wenwen; Zhang, Lei; Feng, Lifang; Liang, Xinle; Guan, Wenjun; Zhou, Jingwen; Chen, Jian; Lin, Zhenguo

    2014-01-01

    Rice wine fermentation represents a unique environment for the evolution of the budding yeast, Saccharomyces cerevisiae. To understand how the selection pressure shaped the yeast genome and gene regulation, we determined the genome sequence and transcriptome of a S. cerevisiae strain YHJ7 isolated from Chinese rice wine (Huangjiu), a popular traditional alcoholic beverage in China. By comparing the genome of YHJ7 to the lab strain S288c, a Japanese sake strain K7, and a Chinese industrial bioethanol strain YJSH1, we identified many genomic sequence and structural variations in YHJ7, which are mainly located in subtelomeric regions, suggesting that these regions play an important role in genomic evolution between strains. In addition, our comparative transcriptome analysis between YHJ7 and S288c revealed a set of differentially expressed genes, including those involved in glucose transport (e.g., HXT2, HXT7) and oxidoredutase activity (e.g., AAD10, ADH7). Interestingly, many of these genomic and transcriptional variations are directly or indirectly associated with the adaptation of YHJ7 strain to its specific niches. Our molecular evolution analysis suggested that Japanese sake strains (K7/UC5) were derived from Chinese rice wine strains (YHJ7) at least approximately 2,300 years ago, providing the first molecular evidence elucidating the origin of Japanese sake strains. Our results depict interesting insights regarding the evolution of yeast during rice wine fermentation, and provided a valuable resource for genetic engineering to improve industrial wine-making strains. PMID:25212861

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. Genomic evolution of Saccharomyces cerevisiae under Chinese rice wine fermentation.

    Science.gov (United States)

    Li, Yudong; Zhang, Weiping; Zheng, Daoqiong; Zhou, Zhan; Yu, Wenwen; Zhang, Lei; Feng, Lifang; Liang, Xinle; Guan, Wenjun; Zhou, Jingwen; Chen, Jian; Lin, Zhenguo

    2014-09-10

    Rice wine fermentation represents a unique environment for the evolution of the budding yeast, Saccharomyces cerevisiae. To understand how the selection pressure shaped the yeast genome and gene regulation, we determined the genome sequence and transcriptome of a S. cerevisiae strain YHJ7 isolated from Chinese rice wine (Huangjiu), a popular traditional alcoholic beverage in China. By comparing the genome of YHJ7 to the lab strain S288c, a Japanese sake strain K7, and a Chinese industrial bioethanol strain YJSH1, we identified many genomic sequence and structural variations in YHJ7, which are mainly located in subtelomeric regions, suggesting that these regions play an important role in genomic evolution between strains. In addition, our comparative transcriptome analysis between YHJ7 and S288c revealed a set of differentially expressed genes, including those involved in glucose transport (e.g., HXT2, HXT7) and oxidoredutase activity (e.g., AAD10, ADH7). Interestingly, many of these genomic and transcriptional variations are directly or indirectly associated with the adaptation of YHJ7 strain to its specific niches. Our molecular evolution analysis suggested that Japanese sake strains (K7/UC5) were derived from Chinese rice wine strains (YHJ7) at least approximately 2,300 years ago, providing the first molecular evidence elucidating the origin of Japanese sake strains. Our results depict interesting insights regarding the evolution of yeast during rice wine fermentation, and provided a valuable resource for genetic engineering to improve industrial wine-making strains. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  18. 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

  19. 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...

  20. Additions, losses, and rearrangements on the evolutionary route from a reconstructed ancestor to the modern Saccharomyces cerevisiae genome.

    Directory of Open Access Journals (Sweden)

    Jonathan L Gordon

    2009-05-01

    Full Text Available Comparative genomics can be used to infer the history of genomic rearrangements that occurred during the evolution of a species. We used the principle of parsimony, applied to aligned synteny blocks from 11 yeast species, to infer the gene content and gene order that existed in the genome of an extinct ancestral yeast about 100 Mya, immediately before it underwent whole-genome duplication (WGD. The reconstructed ancestral genome contains 4,703 ordered loci on eight chromosomes. The reconstruction is complete except for the subtelomeric regions. We then inferred the series of rearrangement steps that led from this ancestor to the current Saccharomyces cerevisiae genome; relative to the ancestral genome we observe 73 inversions, 66 reciprocal translocations, and five translocations involving telomeres. Some fragile chromosomal sites were reused as evolutionary breakpoints multiple times. We identified 124 genes that have been gained by S. cerevisiae in the time since the WGD, including one that is derived from a hAT family transposon, and 88 ancestral loci at which S. cerevisiae did not retain either of the gene copies that were formed by WGD. Sites of gene gain and evolutionary breakpoints both tend to be associated with tRNA genes and, to a lesser extent, with origins of replication. Many of the gained genes in S. cerevisiae have functions associated with ethanol production, growth in hypoxic environments, or the uptake of alternative nutrient sources.

  1. 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.

  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. 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.

  4. The Genome-Scale Integrated Networks in Microorganisms

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. Adaptive Response and Tolerance to Acetic Acid in Saccharomyces cerevisiae and Zygosaccharomyces bailii: A Physiological Genomics Perspective.

    Science.gov (United States)

    Palma, Margarida; Guerreiro, Joana F; Sá-Correia, Isabel

    2018-01-01

    Acetic acid is an important microbial growth inhibitor in the food industry; it is used as a preservative in foods and beverages and is produced during normal yeast metabolism in biotechnological processes. Acetic acid is also a major inhibitory compound present in lignocellulosic hydrolysates affecting the use of this promising carbon source for sustainable bioprocesses. Although the molecular mechanisms underlying Saccharomyces cerevisiae response and adaptation to acetic acid have been studied for years, only recently they have been examined in more detail in Zygosaccharomyces bailii . However, due to its remarkable tolerance to acetic acid and other weak acids this yeast species is a major threat in the spoilage of acidic foods and beverages and considered as an interesting alternative cell factory in Biotechnology. This review paper emphasizes genome-wide strategies that are providing global insights into the molecular targets, signaling pathways and mechanisms behind S. cerevisiae and Z. bailii tolerance to acetic acid, and extends this information to other weak acids whenever relevant. Such comprehensive perspective and the knowledge gathered in these two yeast species allowed the identification of candidate molecular targets, either for the design of effective strategies to overcome yeast spoilage in acidic foods and beverages, or for the rational genome engineering to construct more robust industrial strains. Examples of successful applications are provided.

  10. Mms1 binds to G-rich regions in Saccharomyces cerevisiae and influences replication and genome stability

    NARCIS (Netherlands)

    Wanzek, Katharina; Schwindt, Eike; Capra, John A.; Paeschke, Katrin

    2017-01-01

    The regulation of replication is essential to preserve genome integrity. Mms1 is part of the E3 ubiquitin ligase complex that is linked to replication fork progression. By identifying Mms1 binding sites genome-wide in Saccharomyces cerevisiae we connected Mms1 function to genome integrity and

  11. 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

  12. Genome duplication and mutations in ACE2 cause multicellular, fast-sedimenting phenotypes in evolved Saccharomyces cerevisiae.

    Science.gov (United States)

    Oud, Bart; Guadalupe-Medina, Victor; Nijkamp, Jurgen F; de Ridder, Dick; Pronk, Jack T; van Maris, Antonius J A; Daran, Jean-Marc

    2013-11-05

    Laboratory evolution of the yeast Saccharomyces cerevisiae in bioreactor batch cultures yielded variants that grow as multicellular, fast-sedimenting clusters. Knowledge of the molecular basis of this phenomenon may contribute to the understanding of natural evolution of multicellularity and to manipulating cell sedimentation in laboratory and industrial applications of S. cerevisiae. Multicellular, fast-sedimenting lineages obtained from a haploid S. cerevisiae strain in two independent evolution experiments were analyzed by whole genome resequencing. The two evolved cell lines showed different frameshift mutations in a stretch of eight adenosines in ACE2, which encodes a transcriptional regulator involved in cell cycle control and mother-daughter cell separation. Introduction of the two ace2 mutant alleles into the haploid parental strain led to slow-sedimenting cell clusters that consisted of just a few cells, thus representing only a partial reconstruction of the evolved phenotype. In addition to single-nucleotide mutations, a whole-genome duplication event had occurred in both evolved multicellular strains. Construction of a diploid reference strain with two mutant ace2 alleles led to complete reconstruction of the multicellular-fast sedimenting phenotype. This study shows that whole-genome duplication and a frameshift mutation in ACE2 are sufficient to generate a fast-sedimenting, multicellular phenotype in S. cerevisiae. The nature of the ace2 mutations and their occurrence in two independent evolution experiments encompassing fewer than 500 generations of selective growth suggest that switching between unicellular and multicellular phenotypes may be relevant for competitiveness of S. cerevisiae in natural environments.

  13. Genome-wide map of Apn1 binding sites under oxidative stress in Saccharomyces cerevisiae.

    Science.gov (United States)

    Morris, Lydia P; Conley, Andrew B; Degtyareva, Natalya; Jordan, I King; Doetsch, Paul W

    2017-11-01

    The DNA is cells is continuously exposed to reactive oxygen species resulting in toxic and mutagenic DNA damage. Although the repair of oxidative DNA damage occurs primarily through the base excision repair (BER) pathway, the nucleotide excision repair (NER) pathway processes some of the same lesions. In addition, damage tolerance mechanisms, such as recombination and translesion synthesis, enable cells to tolerate oxidative DNA damage, especially when BER and NER capacities are exceeded. Thus, disruption of BER alone or disruption of BER and NER in Saccharomyces cerevisiae leads to increased mutations as well as large-scale genomic rearrangements. Previous studies demonstrated that a particular region of chromosome II is susceptible to chronic oxidative stress-induced chromosomal rearrangements, suggesting the existence of DNA damage and/or DNA repair hotspots. Here we investigated the relationship between oxidative damage and genomic instability utilizing chromatin immunoprecipitation combined with DNA microarray technology to profile DNA repair sites along yeast chromosomes under different oxidative stress conditions. We targeted the major yeast AP endonuclease Apn1 as a representative BER protein. Our results indicate that Apn1 target sequences are enriched for cytosine and guanine nucleotides. We predict that BER protects these sites in the genome because guanines and cytosines are thought to be especially susceptible to oxidative attack, thereby preventing large-scale genome destabilization from chronic accumulation of DNA damage. Information from our studies should provide insight into how regional deployment of oxidative DNA damage management systems along chromosomes protects against large-scale rearrangements. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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

  20. 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...

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

    Directory of Open Access Journals (Sweden)

    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.

  2. Genome Mutational and Transcriptional Hotspots Are Traps for Duplicated Genes and Sources of Adaptations.

    Science.gov (United States)

    Fares, Mario A; Sabater-Muñoz, Beatriz; Toft, Christina

    2017-05-01

    Gene duplication generates new genetic material, which has been shown to lead to major innovations in unicellular and multicellular organisms. A whole-genome duplication occurred in the ancestor of Saccharomyces yeast species but 92% of duplicates returned to single-copy genes shortly after duplication. The persisting duplicated genes in Saccharomyces led to the origin of major metabolic innovations, which have been the source of the unique biotechnological capabilities in the Baker's yeast Saccharomyces cerevisiae. What factors have determined the fate of duplicated genes remains unknown. Here, we report the first demonstration that the local genome mutation and transcription rates determine the fate of duplicates. We show, for the first time, a preferential location of duplicated genes in the mutational and transcriptional hotspots of S. cerevisiae genome. The mechanism of duplication matters, with whole-genome duplicates exhibiting different preservation trends compared to small-scale duplicates. Genome mutational and transcriptional hotspots are rich in duplicates with large repetitive promoter elements. Saccharomyces cerevisiae shows more tolerance to deleterious mutations in duplicates with repetitive promoter elements, which in turn exhibit higher transcriptional plasticity against environmental perturbations. Our data demonstrate that the genome traps duplicates through the accelerated regulatory and functional divergence of their gene copies providing a source of novel adaptations in yeast. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  3. 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.

  4. 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.

  5. Genomic Sequence of Saccharomyces cerevisiae BAW-6, a Yeast Strain Optimal for Brewing Barley Shochu.

    Science.gov (United States)

    Kajiwara, Yasuhiro; Mori, Kazuki; Tashiro, Kosuke; Higuchi, Yujiro; Takegawa, Kaoru; Takashita, Hideharu

    2018-04-05

    Here, we report the draft genome sequence of Saccharomyces cerevisiae strain BAW-6, which is used for the production of barley shochu, a traditional Japanese spirit. This genomic information can be used to elucidate the genetic basis underlying the high alcohol production capacity and citric acid tolerance of shochu yeast. Copyright © 2018 Kajiwara et al.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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

  11. Genome wide transcriptional response of Saccharomyces cerevisiae to stress-induced perturbations

    Directory of Open Access Journals (Sweden)

    Hilal eTaymaz-Nikerel

    2016-02-01

    Full Text Available Cells respond to environmental and/or genetic perturbations in order to survive and proliferate. Characterization of the changes after various stimuli at different -omics levels is crucial to comprehend the adaptation of cells to changing conditions. Genome wide quantification and analysis of transcript levels, the genes affected by perturbations, extends our understanding of cellular metabolism by pointing out the mechanisms that play role in sensing the stress caused by those perturbations and related signaling pathways, and in this way guides us to achieve endeavors such as rational engineering of cells or interpretation of disease mechanisms. Saccharomyces cerevisiae as a model system has been studied in response to different perturbations and corresponding transcriptional profiles were followed either statically or/and dynamically, short- and long- term. This review focuses on response of yeast cells to diverse stress inducing perturbations including nutritional changes, ionic stress, salt stress, oxidative stress, osmotic shock, as well as to genetic interventions such as deletion and over-expression of genes. It is aimed to conclude on common regulatory phenomena that allow yeast to organize its transcriptomic response after any perturbation under different external conditions.

  12. 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.

  13. 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

  14. 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.

  15. 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

  16. 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.

  17. 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....

  18. 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

  19. Properties of promoters cloned randomly from the Saccharomyces cerevisiae genome.

    Science.gov (United States)

    Santangelo, G M; Tornow, J; McLaughlin, C S; Moldave, K

    1988-01-01

    Promoters were isolated at random from the genome of Saccharomyces cerevisiae by using a plasmid that contains a divergently arrayed pair of promoterless reporter genes. A comprehensive library was constructed by inserting random (DNase I-generated) fragments into the intergenic region upstream from the reporter genes. Simple in vivo assays for either reporter gene product (alcohol dehydrogenase or beta-galactosidase) allowed the rapid identification of promoters from among these random fragments. Poly(dA-dT) homopolymer tracts were present in three of five randomly cloned promoters. With two exceptions, each RNA start site detected was 40 to 100 base pairs downstream from a TATA element. All of the randomly cloned promoters were capable of activating reporter gene transcription bidirectionally. Interestingly, one of the promoter fragments originated in a region of the S. cerevisiae rDNA spacer; regulated divergent transcription (presumably by RNA polymerase II) initiated in the same region. Images PMID:2847031

  20. 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.

  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. 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.

  3. Comparative genomics of xylose-fermenting fungi for enhanced biofuel production

    Energy Technology Data Exchange (ETDEWEB)

    Wohlbach, Dana J.; Kuo, Alan; Sato, Trey K.; Potts, Katlyn M.; Salamov, Asaf A.; LaButti, Kurt M.; Sun, Hui; Clum, Alicia; Pangilinan, Jasmyn L.; Lindquist, Erika A.; Lucas, Susan; Lapidus, Alla; Jin, Mingjie; Gunawan, Christa; Balan, Venkatesh; Dale, Bruce E.; Jeffries, Thomas W.; Zinkel, Robert; Barry, Kerrie W.; Grigoriev, Igor V.; Gasch, Audrey P.

    2011-02-24

    Cellulosic biomass is an abundant and underused substrate for biofuel production. The inability of many microbes to metabolize the pentose sugars abundant within hemicellulose creates specific challenges for microbial biofuel production from cellulosic material. Although engineered strains of Saccharomyces cerevisiae can use the pentose xylose, the fermentative capacity pales in comparison with glucose, limiting the economic feasibility of industrial fermentations. To better understand xylose utilization for subsequent microbial engineering, we sequenced the genomes of two xylose-fermenting, beetle-associated fungi, Spathaspora passalidarum and Candida tenuis. To identify genes involved in xylose metabolism, we applied a comparative genomic approach across 14 Ascomycete genomes, mapping phenotypes and genotypes onto the fungal phylogeny, and measured genomic expression across five Hemiascomycete species with different xylose-consumption phenotypes. This approach implicated many genes and processes involved in xylose assimilation. Several of these genes significantly improved xylose utilization when engineered into S. cerevisiae, demonstrating the power of comparative methods in rapidly identifying genes for biomass conversion while reflecting on fungal ecology.

  4. 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...

  5. Benchmark data for identifying N6-methyladenosine sites in the Saccharomyces cerevisiae genome

    Directory of Open Access Journals (Sweden)

    Wei Chen

    2015-12-01

    Full Text Available This data article contains the benchmark dataset for training and testing iRNA-Methyl, a web-server predictor for identifying N6-methyladenosine sites in RNA (Chen et al., 2015 [15]. It can also be used to develop other predictors for identifying N6-methyladenosine sites in the Saccharomyces cerevisiae genome.

  6. 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.

  7. 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...

  8. 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...

  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. 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.

  11. 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.

  12. Genome Dynamics of Hybrid Saccharomyces cerevisiae During Vegetative and Meiotic Divisions

    Directory of Open Access Journals (Sweden)

    Abhishek Dutta

    2017-11-01

    Full Text Available Mutation and recombination are the major sources of genetic diversity in all organisms. In the baker’s yeast, all mutation rate estimates are in homozygous background. We determined the extent of genetic change through mutation and loss of heterozygosity (LOH in a heterozygous Saccharomyces cerevisiae genome during successive vegetative and meiotic divisions. We measured genome-wide LOH and base mutation rates during vegetative and meiotic divisions in a hybrid (S288c/YJM789 S. cerevisiae strain. The S288c/YJM789 hybrid showed nearly complete reduction in heterozygosity within 31 generations of meioses and improved spore viability. LOH in the meiotic lines was driven primarily by the mating of spores within the tetrad. The S288c/YJM789 hybrid lines propagated vegetatively for the same duration as the meiotic lines, showed variable LOH (from 2 to 3% and up to 35%. Two of the vegetative lines with extensive LOH showed frequent and large internal LOH tracts that suggest a high frequency of recombination repair. These results suggest significant LOH can occur in the S288c/YJM789 hybrid during vegetative propagation presumably due to return to growth events. The average base substitution rates for the vegetative lines (1.82 × 10−10 per base per division and the meiotic lines (1.22 × 10−10 per base per division are the first genome-wide mutation rate estimates for a hybrid yeast. This study therefore provides a novel context for the analysis of mutation rates (especially in the context of detecting LOH during vegetative divisions, compared to previous mutation accumulation studies in yeast that used homozygous backgrounds.

  13. 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.

  14. 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.

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  17. Genome-wide RNAi screen reveals the E3 SUMO-protein ligase gene SIZ1 as a novel determinant of furfural tolerance in Saccharomyces cerevisiae

    OpenAIRE

    Xiao, Han; Zhao, Huimin

    2014-01-01

    Background Furfural is a major growth inhibitor in lignocellulosic hydrolysates and improving furfural tolerance of microorganisms is critical for rapid and efficient fermentation of lignocellulosic biomass. In this study, we used the RNAi-Assisted Genome Evolution (RAGE) method to select for furfural resistant mutants of Saccharomyces cerevisiae, and identified a new determinant of furfural tolerance. Results By using a genome-wide RNAi (RNA-interference) screen in S. cerevisiae for genes in...

  18. 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...

  19. 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.

  20. 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

  1. Gleaning evolutionary insights from the genome sequence of a probiotic yeast Saccharomyces boulardii.

    Science.gov (United States)

    Khatri, Indu; Akhtar, Akil; Kaur, Kamaldeep; Tomar, Rajul; Prasad, Gandham Satyanarayana; Ramya, Thirumalai Nallan Chakravarthy; Subramanian, Srikrishna

    2013-10-22

    The yeast Saccharomyces boulardii is used worldwide as a probiotic to alleviate the effects of several gastrointestinal diseases and control antibiotics-associated diarrhea. While many studies report the probiotic effects of S. boulardii, no genome information for this yeast is currently available in the public domain. We report the 11.4 Mbp draft genome of this probiotic yeast. The draft genome was obtained by assembling Roche 454 FLX + shotgun data into 194 contigs with an N50 of 251 Kbp. We compare our draft genome with all other Saccharomyces cerevisiae genomes. Our analysis confirms the close similarity of S. boulardii to S. cerevisiae strains and provides a framework to understand the probiotic effects of this yeast, which exhibits unique physiological and metabolic properties.

  2. Genome-centric resolution of microbial diversity, metabolism and interactions in anaerobic digestion.

    Science.gov (United States)

    Vanwonterghem, Inka; Jensen, Paul D; Rabaey, Korneel; Tyson, Gene W

    2016-09-01

    Our understanding of the complex interconnected processes performed by microbial communities is hindered by our inability to culture the vast majority of microorganisms. Metagenomics provides a way to bypass this cultivation bottleneck and recent advances in this field now allow us to recover a growing number of genomes representing previously uncultured populations from increasingly complex environments. In this study, a temporal genome-centric metagenomic analysis was performed of lab-scale anaerobic digesters that host complex microbial communities fulfilling a series of interlinked metabolic processes to enable the conversion of cellulose to methane. In total, 101 population genomes that were moderate to near-complete were recovered based primarily on differential coverage binning. These populations span 19 phyla, represent mostly novel species and expand the genomic coverage of several rare phyla. Classification into functional guilds based on their metabolic potential revealed metabolic networks with a high level of functional redundancy as well as niche specialization, and allowed us to identify potential roles such as hydrolytic specialists for several rare, uncultured populations. Genome-centric analyses of complex microbial communities across diverse environments provide the key to understanding the phylogenetic and metabolic diversity of these interactive communities. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

  3. 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...

  4. 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.

  5. Genome-wide identification of Saccharomyces cerevisiae genes required for tolerance to acetic acid

    Directory of Open Access Journals (Sweden)

    Sá-Correia Isabel

    2010-10-01

    Full Text Available Abstract Background Acetic acid is a byproduct of Saccharomyces cerevisiae alcoholic fermentation. Together with high concentrations of ethanol and other toxic metabolites, acetic acid may contribute to fermentation arrest and reduced ethanol productivity. This weak acid is also a present in lignocellulosic hydrolysates, a highly interesting non-feedstock substrate in industrial biotechnology. Therefore, the better understanding of the molecular mechanisms underlying S. cerevisiae tolerance to acetic acid is essential for the rational selection of optimal fermentation conditions and the engineering of more robust industrial strains to be used in processes in which yeast is explored as cell factory. Results The yeast genes conferring protection against acetic acid were identified in this study at a genome-wide scale, based on the screening of the EUROSCARF haploid mutant collection for susceptibility phenotypes to this weak acid (concentrations in the range 70-110 mM, at pH 4.5. Approximately 650 determinants of tolerance to acetic acid were identified. Clustering of these acetic acid-resistance genes based on their biological function indicated an enrichment of genes involved in transcription, internal pH homeostasis, carbohydrate metabolism, cell wall assembly, biogenesis of mitochondria, ribosome and vacuole, and in the sensing, signalling and uptake of various nutrients in particular iron, potassium, glucose and amino acids. A correlation between increased resistance to acetic acid and the level of potassium in the growth medium was found. The activation of the Snf1p signalling pathway, involved in yeast response to glucose starvation, is demonstrated to occur in response to acetic acid stress but no evidence was obtained supporting the acetic acid-induced inhibition of glucose uptake. Conclusions Approximately 490 of the 650 determinants of tolerance to acetic acid identified in this work are implicated, for the first time, in tolerance to

  6. Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR.

    Science.gov (United States)

    Jakočiūnas, Tadas; Jensen, Emil D; Jensen, Michael K; Keasling, Jay D

    2018-01-01

    Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.

  7. 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.

  8. 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...

  9. 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.

  10. [High-level expression of heterologous protein based on increased copy number in Saccharomyces cerevisiae].

    Science.gov (United States)

    Zhang, Xinjie; He, Peng; Tao, Yong; Yang, Yi

    2013-11-04

    High-level expression system of heterologous protein mediated by internal ribosome entry site (IRES) in Saccharomyces cerevisiae was constructed, which could be used for other applications of S. cerevisiae in metabolic engineering. We constructed co-expression cassette (promoter-mCherry-TIF4631 IRES-URA3) containing promoters Pilv5, Padh2 and Ptdh3 and recombined the co-expression cassette into the genome of W303-1B-A. The URA3+ transformants were selected. By comparing the difference in the mean florescence value of mCherry in transformants, the effect of three promoters was detected in the co-expression cassette. The copy numbers of the interested genes in the genome were determined by Real-Time PCR. We analyzed genetic stability by continuous subculturing transformants in the absence of selection pressure. To verify the application of co-expression cassette, the ORF of mCherry was replaced by beta-galactosidase (LACZ) and xylose reductase (XYL1). The enzyme activities and production of beta-galactosidase and xylose reductase were detected. mCherry has been expressed in the highest-level in transformants with co-expression cassette containing Pilv5 promoter. The highest copy number of DNA fragment integrating in the genome was 47 in transformants containing Pilv5. The engineering strains showed good genetic stability. Xylose reductase was successfully expressed in the co-expression cassette containing Pilv5 promoter and TIF4631 IRES. The highest enzyme activity was 0. 209 U/mg crude protein in the transformants WIX-10. Beta-galactosidase was also expressed successfully. The transformants that had the highest enzyme activity was WIL-1 and the enzyme activity was 12.58 U/mg crude protein. The system mediated by Pilv5 promoter and TIF4631 IRES could express heterologous protein efficiently in S. cerevisiae. This study offered a new strategy for expression of heterologous protein in S. cerevisiae and provided sufficient experimental evidence for metabolic engineering

  11. Genome Sequences of Industrially Relevant Saccharomyces cerevisiae Strain M3707, Isolated from a Sample of Distillers Yeast and Four Haploid Derivatives

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Steven D.; Klingeman, Dawn M.; Johnson, Courtney M.; Clum, Alicia; Aerts, Andrea; Salamov, Asaf; Sharma, Aditi; Zane, Matthew; Barry, Kerrie; Grigoriev, Igor V.; Davison, Brian H.; Lynd, Lee R.; Gilna, Paul; Hau, Heidi; Hogsett, David A.; Froehlich, Allan C.

    2013-04-19

    Saccharomyces cerevisiae strain M3707 was isolated from a sample of commercial distillers yeast, and its genome sequence together with the genome sequences for the four derived haploid strains M3836, M3837, M3838, and M3839 has been determined. Yeasts have potential for consolidated bioprocessing (CBP) for biofuel production, and access to these genome sequences will facilitate their development.

  12. 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.

  13. 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

  14. Genome-Wide Screen for Saccharomyces cerevisiae Genes Contributing to Opportunistic Pathogenicity in an Invertebrate Model Host

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    Sujal S. Phadke

    2018-01-01

    Full Text Available Environmental opportunistic pathogens can exploit vulnerable hosts through expression of traits selected for in their natural environments. Pathogenicity is itself a complicated trait underpinned by multiple complex traits, such as thermotolerance, morphology, and stress response. The baker’s yeast, Saccharomyces cerevisiae, is a species with broad environmental tolerance that has been increasingly reported as an opportunistic pathogen of humans. Here we leveraged the genetic resources available in yeast and a model insect species, the greater waxmoth Galleria mellonella, to provide a genome-wide analysis of pathogenicity factors. Using serial passaging experiments of genetically marked wild-type strains, a hybrid strain was identified as the most fit genotype across all replicates. To dissect the genetic basis for pathogenicity in the hybrid isolate, bulk segregant analysis was performed which revealed eight quantitative trait loci significantly differing between the two bulks with alleles from both parents contributing to pathogenicity. A second passaging experiment with a library of deletion mutants for most yeast genes identified a large number of mutations whose relative fitness differed in vivo vs. in vitro, including mutations in genes controlling cell wall integrity, mitochondrial function, and tyrosine metabolism. Yeast is presumably subjected to a massive assault by the innate insect immune system that leads to melanization of the host and to a large bottleneck in yeast population size. Our data support that resistance to the innate immune response of the insect is key to survival in the host and identifies shared genetic mechanisms between S. cerevisiae and other opportunistic fungal pathogens.

  15. 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.

  16. Genome Sequence of Saccharomyces cerevisiae Strain Kagoshima No. 2, Used for Brewing the Japanese Distilled Spirit Shōchū.

    Science.gov (United States)

    Mori, Kazuki; Kadooka, Chihiro; Masuda, Chika; Muto, Ai; Okutsu, Kayu; Yoshizaki, Yumiko; Takamine, Kazunori; Futagami, Taiki; Tamaki, Hisanori

    2017-10-12

    Here, we report a draft genome sequence of Saccharomyces cerevisiae strain Kagoshima no. 2, which is used for brewing shōchū, a traditional distilled spirit in Japan. The genome data will facilitate an understanding of the evolutional traits and genetic background related to the characteristic features of strain Kagoshima no. 2. Copyright © 2017 Mori et al.

  17. 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.

  18. 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.

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

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    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

  20. Scaling of Metabolic Scaling within Physical Limits

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    Douglas S. Glazier

    2014-10-01

    Full Text Available Both the slope and elevation of scaling relationships between log metabolic rate and log body size vary taxonomically and in relation to physiological or developmental state, ecological lifestyle and environmental conditions. Here I discuss how the recently proposed metabolic-level boundaries hypothesis (MLBH provides a useful conceptual framework for explaining and predicting much, but not all of this variation. This hypothesis is based on three major assumptions: (1 various processes related to body volume and surface area exert state-dependent effects on the scaling slope for metabolic rate in relation to body mass; (2 the elevation and slope of metabolic scaling relationships are linked; and (3 both intrinsic (anatomical, biochemical and physiological and extrinsic (ecological factors can affect metabolic scaling. According to the MLBH, the diversity of metabolic scaling relationships occurs within physical boundary limits related to body volume and surface area. Within these limits, specific metabolic scaling slopes can be predicted from the metabolic level (or scaling elevation of a species or group of species. In essence, metabolic scaling itself scales with metabolic level, which is in turn contingent on various intrinsic and extrinsic conditions operating in physiological or evolutionary time. The MLBH represents a “meta-mechanism” or collection of multiple, specific mechanisms that have contingent, state-dependent effects. As such, the MLBH is Darwinian in approach (the theory of natural selection is also meta-mechanistic, in contrast to currently influential metabolic scaling theory that is Newtonian in approach (i.e., based on unitary deterministic laws. Furthermore, the MLBH can be viewed as part of a more general theory that includes other mechanisms that may also affect metabolic scaling.

  1. GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes

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    Nakayama Yoichi

    2006-03-01

    Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

  2. [Genomic research of traditional Chinese medicines in vivo metabolism].

    Science.gov (United States)

    Xiao, Shui-Ming; Bai, Rui; Zhang, Xiao-Yan

    2016-11-01

    Gene is the base of in vivo metabolism and effectiveness for traditional Chinese medicines (TCM), and the gene expression, regulation and modification are used as the research directions to perform the TCM multi-component, multi-link and multi-target in vivo metabolism studies, which will improve the research on TCM metabolic proecess, effect target and molecular mechanism. Humans are superorganisms with 1% genes inherited from parents and 99% genes from various parts of the human body, mainly coming from the microorganisms in intestinal flora. These indicate that genetically inherited human genome and "second genome" could affect the TCM in vivo metabolism from inheritance and "environmental" aspects respectively. In the present paper, typical case study was used to discuss related TCM in vivo metabolic genomics research, mainly including TCM genomics research and gut metagenomics research, as well as the personalized medicine evoked from the individual difference of above genomics (metagenomics). Copyright© by the Chinese Pharmaceutical Association.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

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

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    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.

  9. 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...

  10. 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.

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

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    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

  12. Genome shuffling of Saccharomyces cerevisiae through recursive population mating to evolve tolerance to inhibitors of Spent Sulfite Liquor

    Energy Technology Data Exchange (ETDEWEB)

    Martin, V.J.J.; Pinel, D.J.; D' aoust, F. [Concordia Univ., Montreal, PQ (Canada). Dept. of Biological Sciences; Bajwa, P.K.; Trevors, J.T.; Lee, H. [Guelph Univ., ON (Canada). Dept. of Environmental Biology

    2009-07-01

    The biochemical steps in the conversion of cellulosics to biofuels include the pretreatment, hydrolysis and fermentation of substrates into a final product. Fermentation of lignocellulosic substrates derived from waste biomass requires metabolic engineering. A biochemical flow chart from the Tembec Biorefinery plant was presented in which Spent Sulfite Liquor (SSL) was used to add value to the pulp and paper industry. The sugars contained in this carbohydrate-rich effluent from sulfite pulping were used to produce ethanol. A robust, ethanologenic microorganism that can withstand the substrate toxicity was needed. Saccharomyces cerevisiae is currently used for the production of ethanol from SSL. This yeast will succumb to toxicity and inhibition, particularly in the most inhibitor rich forms of SSL such as hardwood SSL (HWSSL). A genome shuffling method was therefore developed to create a better SSL fermenting strain. This method was designed to improve polygenic traits by generating pools of mutants with improved phenotypes, followed by iterative recombination between their genomes. Through 5 rounds of recursive mating and screening, 3 strains that could survive and grow in undiluted HWSSL were obtained. The study demonstrated that the tolerance of these strains to SSL translates into an increased capacity to produce ethanol over time using this substrate, due to continued viability of the yeast population. Phenotypic analysis of the three strains revealed that the genome shuffling approach successfully co-evolved tolerance to acetic acid, NaCl (osmotic) and HMF. A systems biology analysis of strain R57 was initiated in order to establish the genetic basis for HWSSL tolerance. tabs., figs.

  13. 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.

  14. 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.

  15. Two-Scale 13C Metabolic Flux Analysis for Metabolic Engineering.

    Science.gov (United States)

    Ando, David; Garcia Martin, Hector

    2018-01-01

    Accelerating the Design-Build-Test-Learn (DBTL) cycle in synthetic biology is critical to achieving rapid and facile bioengineering of organisms for the production of, e.g., biofuels and other chemicals. The Learn phase involves using data obtained from the Test phase to inform the next Design phase. As part of the Learn phase, mathematical models of metabolic fluxes give a mechanistic level of comprehension to cellular metabolism, isolating the principle drivers of metabolic behavior from the peripheral ones, and directing future experimental designs and engineering methodologies. Furthermore, the measurement of intracellular metabolic fluxes is specifically noteworthy as providing a rapid and easy-to-understand picture of how carbon and energy flow throughout the cell. Here, we present a detailed guide to performing metabolic flux analysis in the Learn phase of the DBTL cycle, where we show how one can take the isotope labeling data from a 13 C labeling experiment and immediately turn it into a determination of cellular fluxes that points in the direction of genetic engineering strategies that will advance the metabolic engineering process.For our modeling purposes we use the Joint BioEnergy Institute (JBEI) Quantitative Metabolic Modeling (jQMM) library, which provides an open-source, python-based framework for modeling internal metabolic fluxes and making actionable predictions on how to modify cellular metabolism for specific bioengineering goals. It presents a complete toolbox for performing different types of flux analysis such as Flux Balance Analysis, 13 C Metabolic Flux Analysis, and it introduces the capability to use 13 C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale 13 C Metabolic Flux Analysis (2S- 13 C MFA) [1]. In addition to several other capabilities, the jQMM is also able to predict the effects of knockouts using the MoMA and ROOM methodologies. The use of the jQMM library is

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

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    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.

  17. Novel starters for old processes: use of Saccharomyces cerevisiae strains isolated from artisanal sourdough for craft beer production at a brewery scale.

    Science.gov (United States)

    Marongiu, Antonella; Zara, Giacomo; Legras, Jean-Luc; Del Caro, Alessandra; Mascia, Ilaria; Fadda, Costantino; Budroni, Marilena

    2015-01-01

    The deliberate inoculation of yeast strains isolated from food matrices such as wine or bread, could allow the transfer of novel properties to beer. In this work, the feasibility of the use of baker's yeast strains as starters for craft beer production has been evaluated at laboratory and brewery scale. Nine out of 12 Saccharomyces cerevisiae strains isolated from artisanal sourdoughs metabolized 2 % maltose, glucose and trehalose and showed growth rates and cell populations higher than those of the brewer's strain Safbrew-S33. Analysis of allelic variation at 12 microsatellite loci clustered seven baker's strains and Safbrew-S33 in the main group of bread isolates. Chemical analyses of beers produced at a brewery scale showed significant differences among the beers produced with the baker's strain S38 or Safbrew-S33, while no significant differences were observed when S38 or the brewer's strain Safbrew-F2 was used for re-fermentation. The sensory profile of beers obtained with S38 or the brewer's yeasts did not show significant differences, thus suggesting that baker's strains of S. cerevisiae could represent a reservoir of biodiversity for the selection of starter strains for craft beer production.

  18. Large-scale genomic 2D visualization reveals extensive CG-AT skew correlation in bird genomes

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    Deng Xuemei

    2007-11-01

    Full Text Available Abstract Background Bird genomes have very different compositional structure compared with other warm-blooded animals. The variation in the base skew rules in the vertebrate genomes remains puzzling, but it must relate somehow to large-scale genome evolution. Current research is inclined to relate base skew with mutations and their fixation. Here we wish to explore base skew correlations in bird genomes, to develop methods for displaying and quantifying such correlations at different scales, and to discuss possible explanations for the peculiarities of the bird genomes in skew correlation. Results We have developed a method called Base Skew Double Triangle (BSDT for exhibiting the genome-scale change of AT/CG skew as a two-dimensional square picture, showing base skews at many scales simultaneously in a single image. By this method we found that most chicken chromosomes have high AT/CG skew correlation (symmetry in 2D picture, except for some microchromosomes. No other organisms studied (18 species show such high skew correlations. This visualized high correlation was validated by three kinds of quantitative calculations with overlapping and non-overlapping windows, all indicating that chicken and birds in general have a special genome structure. Similar features were also found in some of the mammal genomes, but clearly much weaker than in chickens. We presume that the skew correlation feature evolved near the time that birds separated from other vertebrate lineages. When we eliminated the repeat sequences from the genomes, the AT and CG skews correlation increased for some mammal genomes, but were still clearly lower than in chickens. Conclusion Our results suggest that BSDT is an expressive visualization method for AT and CG skew and enabled the discovery of the very high skew correlation in bird genomes; this peculiarity is worth further study. Computational analysis indicated that this correlation might be a compositional characteristic

  19. 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...

  20. 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.

  1. 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,...

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

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    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

  3. 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...

  4. Context based computational analysis and characterization of ARS consensus sequences (ACS of Saccharomyces cerevisiae genome

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    Vinod Kumar Singh

    2016-09-01

    Full Text Available Genome-wide experimental studies in Saccharomyces cerevisiae reveal that autonomous replicating sequence (ARS requires an essential consensus sequence (ACS for replication activity. Computational studies identified thousands of ACS like patterns in the genome. However, only a few hundreds of these sites act as replicating sites and the rest are considered as dormant or evolving sites. In a bid to understand the sequence makeup of replication sites, a content and context-based analysis was performed on a set of replicating ACS sequences that binds to origin-recognition complex (ORC denoted as ORC-ACS and non-replicating ACS sequences (nrACS, that are not bound by ORC. In this study, DNA properties such as base composition, correlation, sequence dependent thermodynamic and DNA structural profiles, and their positions have been considered for characterizing ORC-ACS and nrACS. Analysis reveals that ORC-ACS depict marked differences in nucleotide composition and context features in its vicinity compared to nrACS. Interestingly, an A-rich motif was also discovered in ORC-ACS sequences within its nucleosome-free region. Profound changes in the conformational features, such as DNA helical twist, inclination angle and stacking energy between ORC-ACS and nrACS were observed. Distribution of ACS motifs in the non-coding segments points to the locations of ORC-ACS which are found far away from the adjacent gene start position compared to nrACS thereby enabling an accessible environment for ORC-proteins. Our attempt is novel in considering the contextual view of ACS and its flanking region along with nucleosome positioning in the S. cerevisiae genome and may be useful for any computational prediction scheme.

  5. 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....

  6. Genomics and the making of yeast biodiversity.

    Science.gov (United States)

    Hittinger, Chris Todd; Rokas, Antonis; Bai, Feng-Yan; Boekhout, Teun; Gonçalves, Paula; Jeffries, Thomas W; Kominek, Jacek; Lachance, Marc-André; Libkind, Diego; Rosa, Carlos A; Sampaio, José Paulo; Kurtzman, Cletus P

    2015-12-01

    Yeasts are unicellular fungi that do not form fruiting bodies. Although the yeast lifestyle has evolved multiple times, most known species belong to the subphylum Saccharomycotina (syn. Hemiascomycota, hereafter yeasts). This diverse group includes the premier eukaryotic model system, Saccharomyces cerevisiae; the common human commensal and opportunistic pathogen, Candida albicans; and over 1000 other known species (with more continuing to be discovered). Yeasts are found in every biome and continent and are more genetically diverse than angiosperms or chordates. Ease of culture, simple life cycles, and small genomes (∼10-20Mbp) have made yeasts exceptional models for molecular genetics, biotechnology, and evolutionary genomics. Here we discuss recent developments in understanding the genomic underpinnings of the making of yeast biodiversity, comparing and contrasting natural and human-associated evolutionary processes. Only a tiny fraction of yeast biodiversity and metabolic capabilities has been tapped by industry and science. Expanding the taxonomic breadth of deep genomic investigations will further illuminate how genome function evolves to encode their diverse metabolisms and ecologies. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR

    DEFF Research Database (Denmark)

    Jakočiūnas, Tadas; Jensen, Emil D.; Jensen, Michael Krogh

    2018-01-01

    and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking......Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome...... engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. Cas...

  8. 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.

  9. 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

  10. 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

  11. 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.

  12. Metabolic Engineering of Probiotic Saccharomyces boulardii.

    Science.gov (United States)

    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

    2016-04-01

    Saccharomyces boulardiiis 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. boulardiiis 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 metabolic engineering. Here, we report the development of well-defined auxotrophic mutants (leu2,ura3,his3, and trp1) through clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9-based genome editing. The resulting auxotrophic mutants can be used as a host for introducing various genetic perturbations, such as overexpression or deletion of a target gene, using existing genetic tools forS. cerevisiae We demonstrated the overexpression of a heterologous gene (lacZ), the correct localization of a target protein (red fluorescent protein) into mitochondria by using a protein localization signal, and the introduction of a heterologous metabolic pathway (xylose-assimilating pathway) in the genome ofS. boulardii We further demonstrated that human lysozyme, which is beneficial for human gut health, could be secreted by S. boulardii Our results suggest that more sophisticated genetic perturbations to improveS. boulardii can be performed without using a drug resistance marker, which is a prerequisite for in vivo applications using engineeredS. boulardii. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  13. Sugar Lego: gene composition of bacterial carbohydrate metabolism genomic loci.

    Science.gov (United States)

    Kaznadzey, Anna; Shelyakin, Pavel; Gelfand, Mikhail S

    2017-11-25

    Bacterial carbohydrate metabolism is extremely diverse, since carbohydrates serve as a major energy source and are involved in a variety of cellular processes. Bacterial genes belonging to same metabolic pathway are often co-localized in the chromosome, but it is not a strict rule. Gene co-localization in linked to co-evolution and co-regulation. This study focuses on a large-scale analysis of bacterial genomic loci related to the carbohydrate metabolism. We demonstrate that only 53% of 148,000 studied genes from over six hundred bacterial genomes are co-localized in bacterial genomes with other carbohydrate metabolism genes, which points to a significant role of singleton genes. Co-localized genes form cassettes, ranging in size from two to fifteen genes. Two major factors influencing the cassette-forming tendency are gene function and bacterial phylogeny. We have obtained a comprehensive picture of co-localization preferences of genes for nineteen major carbohydrate metabolism functional classes, over two hundred gene orthologous clusters, and thirty bacterial classes, and characterized the cassette variety in size and content among different species, highlighting a significant role of short cassettes. The preference towards co-localization of carbohydrate metabolism genes varies between 40 and 76% for bacterial taxa. Analysis of frequently co-localized genes yielded forty-five significant pairwise links between genes belonging to different functional classes. The number of such links per class range from zero to eight, demonstrating varying preferences of respective genes towards a specific chromosomal neighborhood. Genes from eleven functional classes tend to co-localize with genes from the same class, indicating an important role of clustering of genes with similar functions. At that, in most cases such co-localization does not originate from local duplication events. Overall, we describe a complex web formed by evolutionary relationships of bacterial

  14. 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.

  15. The footprint of metabolism in the organization of mammalian genomes

    Directory of Open Access Journals (Sweden)

    Berná Luisa

    2012-05-01

    Full Text Available Abstract Background At present five evolutionary hypotheses have been proposed to explain the great variability of the genomic GC content among and within genomes: the mutational bias, the biased gene conversion, the DNA breakpoints distribution, the thermal stability and the metabolic rate. Several studies carried out on bacteria and teleostean fish pointed towards the critical role played by the environment on the metabolic rate in shaping the base composition of genomes. In mammals the debate is still open, and evidences have been produced in favor of each evolutionary hypothesis. Human genes were assigned to three large functional categories (as well as to the corresponding functional classes according to the KOG database: (i information storage and processing, (ii cellular processes and signaling, and (iii metabolism. The classification was extended to the organisms so far analyzed performing a reciprocal Blastp and selecting the best reciprocal hit. The base composition was calculated for each sequence of the whole CDS dataset. Results The GC3 level of the above functional categories was increasing from (i to (iii. This specific compositional pattern was found, as footprint, in all mammalian genomes, but not in frog and lizard ones. Comparative analysis of human versus both frog and lizard functional categories showed that genes involved in the metabolic processes underwent the highest GC3 increment. Analyzing the KOG functional classes of genes, again a well defined intra-genomic pattern was found in all mammals. Not only genes of metabolic pathways, but also genes involved in chromatin structure and dynamics, transcription, signal transduction mechanisms and cytoskeleton, showed an average GC3 level higher than that of the whole genome. In the case of the human genome, the genes of the aforementioned functional categories showed a high probability to be associated with the chromosomal bands. Conclusions In the light of different

  16. 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.

  17. 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

  18. Functional co-operation between the nuclei of Saccharomyces cerevisiae and mitochondria from other yeast species

    DEFF Research Database (Denmark)

    Spirek, M.; Horvath, A.; Piskur, Jure

    2000-01-01

    We elaborated a simple method that allows the transfer of mitochondria from collection yeasts to Saccharomyces cerevisiae. Protoplasts prepared from different yeasts were fused to the protoplasts of the ade2-1, ura3-52, kar1-1, rho (0) strain of S. cerevisiae and were selected for respiring cybrids....... italicus, S, oviformis, S. capensis and S. chevalieri) exhibited complete compatibility with S. cerevisiae nuclei. The closely related S. douglasii mitochondrial genome could also partially restore respiration-deficiency in rho (0) S. cerevisiae, whereas mitochondrial genomes from phylogenetically less...

  19. Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities.

    Science.gov (United States)

    Zomorrodi, Ali R; Segrè, Daniel

    2017-11-16

    Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial "games". We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Furthermore, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.

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

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    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

  1. 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.

  2. Deciphering the hybridisation history leading to the Lager lineage based on the mosaic genomes of Saccharomyces bayanus strains NBRC1948 and CBS380.

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    Huu-Vang Nguyen

    Full Text Available Saccharomyces bayanus is a yeast species described as one of the two parents of the hybrid brewing yeast S. pastorianus. Strains CBS380(T and NBRC1948 have been retained successively as pure-line representatives of S. bayanus. In the present study, sequence analyses confirmed and upgraded our previous finding: S. bayanus type strain CBS380(T harbours a mosaic genome. The genome of strain NBRC1948 was also revealed to be mosaic. Both genomes were characterized by amplification and sequencing of different markers, including genes involved in maltotriose utilization or genes detected by array-CGH mapping. Sequence comparisons with public Saccharomyces spp. nucleotide sequences revealed that the CBS380(T and NBRC1948 genomes are composed of: a predominant non-cerevisiae genetic background belonging to S. uvarum, a second unidentified species provisionally named S. lagerae, and several introgressed S. cerevisiae fragments. The largest cerevisiae-introgressed DNA common to both genomes totals 70kb in length and is distributed in three contigs, cA, cB and cC. These vary in terms of length and presence of MAL31 or MTY1 (maltotriose-transporter gene. In NBRC1948, two additional cerevisiae-contigs, cD and cE, totaling 12kb in length, as well as several smaller cerevisiae fragments were identified. All of these contigs were partially detected in the genomes of S. pastorianus lager strains CBS1503 (S. monacensis and CBS1513 (S. carlsbergensis explaining the noticeable common ability of S. bayanus and S. pastorianus to metabolize maltotriose. NBRC1948 was shown to be inter-fertile with S. uvarum CBS7001. The cross involving these two strains produced F1 segregants resembling the strains CBS380(T or NRRLY-1551. This demonstrates that these S. bayanus strains were the offspring of a cross between S. uvarum and a strain similar to NBRC1948. Phylogenies established with selected cerevisiae and non-cerevisiae genes allowed us to decipher the complex hybridisation

  3. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases

    Science.gov (United States)

    Caspi, Ron; Altman, Tomer; Dale, Joseph M.; Dreher, Kate; Fulcher, Carol A.; Gilham, Fred; Kaipa, Pallavi; Karthikeyan, Athikkattuvalasu S.; Kothari, Anamika; Krummenacker, Markus; Latendresse, Mario; Mueller, Lukas A.; Paley, Suzanne; Popescu, Liviu; Pujar, Anuradha; Shearer, Alexander G.; Zhang, Peifen; Karp, Peter D.

    2010-01-01

    The MetaCyc database (MetaCyc.org) is a comprehensive and freely accessible resource for metabolic pathways and enzymes from all domains of life. The pathways in MetaCyc are experimentally determined, small-molecule metabolic pathways and are curated from the primary scientific literature. With more than 1400 pathways, MetaCyc is the largest collection of metabolic pathways currently available. Pathways reactions are linked to one or more well-characterized enzymes, and both pathways and enzymes are annotated with reviews, evidence codes, and literature citations. BioCyc (BioCyc.org) is a collection of more than 500 organism-specific Pathway/Genome Databases (PGDBs). Each BioCyc PGDB contains the full genome and predicted metabolic network of one organism. The network, which is predicted by the Pathway Tools software using MetaCyc as a reference, consists of metabolites, enzymes, reactions and metabolic pathways. BioCyc PGDBs also contain additional features, such as predicted operons, transport systems, and pathway hole-fillers. The BioCyc Web site offers several tools for the analysis of the PGDBs, including Omics Viewers that enable visualization of omics datasets on two different genome-scale diagrams and tools for comparative analysis. The BioCyc PGDBs generated by SRI are offered for adoption by any party interested in curation of metabolic, regulatory, and genome-related information about an organism. PMID:19850718

  4. Genome-wide high-resolution mapping of UV-induced mitotic recombination events in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Yi Yin

    2013-10-01

    Full Text Available In the yeast Saccharomyces cerevisiae and most other eukaryotes, mitotic recombination is important for the repair of double-stranded DNA breaks (DSBs. Mitotic recombination between homologous chromosomes can result in loss of heterozygosity (LOH. In this study, LOH events induced by ultraviolet (UV light are mapped throughout the genome to a resolution of about 1 kb using single-nucleotide polymorphism (SNP microarrays. UV doses that have little effect on the viability of diploid cells stimulate crossovers more than 1000-fold in wild-type cells. In addition, UV stimulates recombination in G1-synchronized cells about 10-fold more efficiently than in G2-synchronized cells. Importantly, at high doses of UV, most conversion events reflect the repair of two sister chromatids that are broken at approximately the same position whereas at low doses, most conversion events reflect the repair of a single broken chromatid. Genome-wide mapping of about 380 unselected crossovers, break-induced replication (BIR events, and gene conversions shows that UV-induced recombination events occur throughout the genome without pronounced hotspots, although the ribosomal RNA gene cluster has a significantly lower frequency of crossovers.

  5. BioMet Toolbox: genome-wide analysis of metabolism

    DEFF Research Database (Denmark)

    Cvijovic, M.; Olivares Hernandez, Roberto; Agren, R.

    2010-01-01

    The rapid progress of molecular biology tools for directed genetic modifications, accurate quantitative experimental approaches, high-throughput measurements, together with development of genome sequencing has made the foundation for a new area of metabolic engineering that is driven by metabolic...

  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. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

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    Kovaleva Galina

    2011-06-01

    Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

  8. 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...

  9. Correlation exploration of metabolic and genomic diversity in rice

    Directory of Open Access Journals (Sweden)

    Shinozaki Kazuo

    2009-12-01

    Full Text Available Abstract Background It is essential to elucidate the relationship between metabolic and genomic diversity to understand the genetic regulatory networks associated with the changing metabolo-phenotype among natural variation and/or populations. Recent innovations in metabolomics technologies allow us to grasp the comprehensive features of the metabolome. Metabolite quantitative trait analysis is a key approach for the identification of genetic loci involved in metabolite variation using segregated populations. Although several attempts have been made to find correlative relationships between genetic and metabolic diversity among natural populations in various organisms, it is still unclear whether it is possible to discover such correlations between each metabolite and the polymorphisms found at each chromosomal location. To assess the correlative relationship between the metabolic and genomic diversity found in rice accessions, we compared the distance matrices for these two "omics" patterns in the rice accessions. Results We selected 18 accessions from the world rice collection based on their population structure. To determine the genomic diversity of the rice genome, we genotyped 128 restriction fragment length polymorphism (RFLP markers to calculate the genetic distance among the accessions. To identify the variations in the metabolic fingerprint, a soluble extract from the seed grain of each accession was analyzed with one dimensional 1H-nuclear magnetic resonance (NMR. We found no correlation between global metabolic diversity and the phylogenetic relationships among the rice accessions (rs = 0.14 by analyzing the distance matrices (calculated from the pattern of the metabolic fingerprint in the 4.29- to 0.71-ppm 1H chemical shift and the genetic distance on the basis of the RFLP markers. However, local correlation analysis between the distance matrices (derived from each 0.04-ppm integral region of the 1H chemical shift against genetic

  10. 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.

  11. Multiplexed precision genome editing with trackable genomic barcodes in yeast.

    Science.gov (United States)

    Roy, Kevin R; Smith, Justin D; Vonesch, Sibylle C; Lin, Gen; Tu, Chelsea Szu; Lederer, Alex R; Chu, Angela; Suresh, Sundari; Nguyen, Michelle; Horecka, Joe; Tripathi, Ashutosh; Burnett, Wallace T; Morgan, Maddison A; Schulz, Julia; Orsley, Kevin M; Wei, Wu; Aiyar, Raeka S; Davis, Ronald W; Bankaitis, Vytas A; Haber, James E; Salit, Marc L; St Onge, Robert P; Steinmetz, Lars M

    2018-07-01

    Our understanding of how genotype controls phenotype is limited by the scale at which we can precisely alter the genome and assess the phenotypic consequences of each perturbation. Here we describe a CRISPR-Cas9-based method for multiplexed accurate genome editing with short, trackable, integrated cellular barcodes (MAGESTIC) in Saccharomyces cerevisiae. MAGESTIC uses array-synthesized guide-donor oligos for plasmid-based high-throughput editing and features genomic barcode integration to prevent plasmid barcode loss and to enable robust phenotyping. We demonstrate that editing efficiency can be increased more than fivefold by recruiting donor DNA to the site of breaks using the LexA-Fkh1p fusion protein. We performed saturation editing of the essential gene SEC14 and identified amino acids critical for chemical inhibition of lipid signaling. We also constructed thousands of natural genetic variants, characterized guide mismatch tolerance at the genome scale, and ascertained that cryptic Pol III termination elements substantially reduce guide efficacy. MAGESTIC will be broadly useful to uncover the genetic basis of phenotypes in yeast.

  12. The Genome Sequence of Saccharomyces eubayanus and the Domestication of Lager-Brewing Yeasts

    Science.gov (United States)

    Baker, EmilyClare; Wang, Bing; Bellora, Nicolas; Peris, David; Hulfachor, Amanda Beth; Koshalek, Justin A.; Adams, Marie; Libkind, Diego; Hittinger, Chris Todd

    2015-01-01

    The dramatic phenotypic changes that occur in organisms during domestication leave indelible imprints on their genomes. Although many domesticated plants and animals have been systematically compared with their wild genetic stocks, the molecular and genomic processes underlying fungal domestication have received less attention. Here, we present a nearly complete genome assembly for the recently described yeast species Saccharomyces eubayanus and compare it to the genomes of multiple domesticated alloploid hybrids of S. eubayanus × S. cerevisiae (S. pastorianus syn. S. carlsbergensis), which are used to brew lager-style beers. We find that the S. eubayanus subgenomes of lager-brewing yeasts have experienced increased rates of evolution since hybridization, and that certain genes involved in metabolism may have been particularly affected. Interestingly, the S. eubayanus subgenome underwent an especially strong shift in selection regimes, consistent with more extensive domestication of the S. cerevisiae parent prior to hybridization. In contrast to recent proposals that lager-brewing yeasts were domesticated following a single hybridization event, the radically different neutral site divergences between the subgenomes of the two major lager yeast lineages strongly favor at least two independent origins for the S. cerevisiae × S. eubayanus hybrids that brew lager beers. Our findings demonstrate how this industrially important hybrid has been domesticated along similar evolutionary trajectories on multiple occasions. PMID:26269586

  13. metabolicMine: an integrated genomics, genetics and proteomics data warehouse for common metabolic disease research.

    Science.gov (United States)

    Lyne, Mike; Smith, Richard N; Lyne, Rachel; Aleksic, Jelena; Hu, Fengyuan; Kalderimis, Alex; Stepan, Radek; Micklem, Gos

    2013-01-01

    Common metabolic and endocrine diseases such as diabetes affect millions of people worldwide and have a major health impact, frequently leading to complications and mortality. In a search for better prevention and treatment, there is ongoing research into the underlying molecular and genetic bases of these complex human diseases, as well as into the links with risk factors such as obesity. Although an increasing number of relevant genomic and proteomic data sets have become available, the quantity and diversity of the data make their efficient exploitation challenging. Here, we present metabolicMine, a data warehouse with a specific focus on the genomics, genetics and proteomics of common metabolic diseases. Developed in collaboration with leading UK metabolic disease groups, metabolicMine integrates data sets from a range of experiments and model organisms alongside tools for exploring them. The current version brings together information covering genes, proteins, orthologues, interactions, gene expression, pathways, ontologies, diseases, genome-wide association studies and single nucleotide polymorphisms. Although the emphasis is on human data, key data sets from mouse and rat are included. These are complemented by interoperation with the RatMine rat genomics database, with a corresponding mouse version under development by the Mouse Genome Informatics (MGI) group. The web interface contains a number of features including keyword search, a library of Search Forms, the QueryBuilder and list analysis tools. This provides researchers with many different ways to analyse, view and flexibly export data. Programming interfaces and automatic code generation in several languages are supported, and many of the features of the web interface are available through web services. The combination of diverse data sets integrated with analysis tools and a powerful query system makes metabolicMine a valuable research resource. The web interface makes it accessible to first

  14. Metabolic 'engines' of flight drive genome size reduction in birds.

    Science.gov (United States)

    Wright, Natalie A; Gregory, T Ryan; Witt, Christopher C

    2014-03-22

    The tendency for flying organisms to possess small genomes has been interpreted as evidence of natural selection acting on the physical size of the genome. Nonetheless, the flight-genome link and its mechanistic basis have yet to be well established by comparative studies within a volant clade. Is there a particular functional aspect of flight such as brisk metabolism, lift production or maneuverability that impinges on the physical genome? We measured genome sizes, wing dimensions and heart, flight muscle and body masses from a phylogenetically diverse set of bird species. In phylogenetically controlled analyses, we found that genome size was negatively correlated with relative flight muscle size and heart index (i.e. ratio of heart to body mass), but positively correlated with body mass and wing loading. The proportional masses of the flight muscles and heart were the most important parameters explaining variation in genome size in multivariate models. Hence, the metabolic intensity of powered flight appears to have driven genome size reduction in birds.

  15. Development Of An Efficient Glycerol Utilizing Saccharomyces Cerevisiae Strain Via Adaptive Laboratory Evolution

    DEFF Research Database (Denmark)

    Strucko, Tomas; Zirngibl, Katharina; Tharwat Tolba Mohamed, Elsayed

    2015-01-01

    that popular wild-type laboratory yeast strains, commonly applied in metabolic engineering studies, did not grow or grew very slowly in glycerol medium.In this work, an adaptive laboratory evolution approach to obtain S. cerevisiae strains with an improved ability to grow on glycerol was applied. A broad array...... of evolved strains, which exhibited a significant increase in the specific growth rate and a higher glycerol consumption rate, were isolated. The best performing strains were further analyzed by classical genetics and whole genome re-sequencing in order to understand the molecular basis of glycerol...

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

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    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

  17. Engineering yeast metabolism for production of fuels and chemicals

    DEFF Research Database (Denmark)

    Nielsen, Jens

    2016-01-01

    faster development of metabolically engineered strains that can be used for production of fuels and chemicals. The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals and materials. Through metabolic engineering of this yeast a number of novel industrial...... as for metabolic design. In this lecture it will be demonstrated how the Design-Build-Test cycle of metabolic engineering has allowed for development of yeast cell factories for production of a range of different fuels and chemicals. Some examples of different technologies will be presented together with examples......Metabolic engineering relies on the Design-Build-Test cycle. This cycle includes technologies like mathematical modeling of metabolism, genome editing and advanced tools for phenotypic characterization. In recent years there have been advances in several of these technologies, which has enabled...

  18. The Genome-Based Metabolic Systems Engineering to Boost Levan Production in a Halophilic Bacterial Model.

    Science.gov (United States)

    Aydin, Busra; Ozer, Tugba; Oner, Ebru Toksoy; Arga, Kazim Yalcin

    2018-03-01

    Metabolic systems engineering is being used to redirect microbial metabolism for the overproduction of chemicals of interest with the aim of transforming microbial hosts into cellular factories. In this study, a genome-based metabolic systems engineering approach was designed and performed to improve biopolymer biosynthesis capability of a moderately halophilic bacterium Halomonas smyrnensis AAD6 T producing levan, which is a fructose homopolymer with many potential uses in various industries and medicine. For this purpose, the genome-scale metabolic model for AAD6 T was used to characterize the metabolic resource allocation, specifically to design metabolic engineering strategies for engineered bacteria with enhanced levan production capability. Simulations were performed in silico to determine optimal gene knockout strategies to develop new strains with enhanced levan production capability. The majority of the gene knockout strategies emphasized the vital role of the fructose uptake mechanism, and pointed out the fructose-specific phosphotransferase system (PTS fru ) as the most promising target for further metabolic engineering studies. Therefore, the PTS fru of AAD6 T was restructured with insertional mutagenesis and triparental mating techniques to construct a novel, engineered H. smyrnensis strain, BMA14. Fermentation experiments were carried out to demonstrate the high efficiency of the mutant strain BMA14 in terms of final levan concentration, sucrose consumption rate, and sucrose conversion efficiency, when compared to the AAD6 T . The genome-based metabolic systems engineering approach presented in this study might be considered an efficient framework to redirect microbial metabolism for the overproduction of chemicals of interest, and the novel strain BMA14 might be considered a potential microbial cell factory for further studies aimed to design levan production processes with lower production costs.

  19. Relationship between metabolic and genomic diversity in sesame (Sesamum indicum L.

    Directory of Open Access Journals (Sweden)

    Karlovsky Petr

    2008-05-01

    Full Text Available Abstract Background Diversity estimates in cultivated plants provide a rationale for conservation strategies and support the selection of starting material for breeding programs. Diversity measures applied to crops usually have been limited to the assessment of genome polymorphism at the DNA level. Occasionally, selected morphological features are recorded and the content of key chemical constituents determined, but unbiased and comprehensive chemical phenotypes have not been included systematically in diversity surveys. Our objective in this study was to assess metabolic diversity in sesame by nontargeted metabolic profiling and elucidate the relationship between metabolic and genome diversity in this crop. Results Ten sesame accessions were selected that represent most of the genome diversity of sesame grown in India, Western Asia, Sudan and Venezuela based on previous AFLP studies. Ethanolic seed extracts were separated by HPLC, metabolites were ionized by positive and negative electrospray and ions were detected with an ion trap mass spectrometer in full-scan mode for m/z from 50 to 1000. Genome diversity was determined by Amplified Fragment Length Polymorphism (AFLP using eight primer pair combinations. The relationship between biodiversity at the genome and at the metabolome levels was assessed by correlation analysis and multivariate statistics. Conclusion Patterns of diversity at the genomic and metabolic levels differed, indicating that selection played a significant role in the evolution of metabolic diversity in sesame. This result implies that when used for the selection of genotypes in breeding and conservation, diversity assessment based on neutral DNA markers should be complemented with metabolic profiles. We hypothesize that this applies to all crops with a long history of domestication that possess commercially relevant traits affected by chemical phenotypes.

  20. The Saccharomyces Genome Database Variant Viewer.

    Science.gov (United States)

    Sheppard, Travis K; Hitz, Benjamin C; Engel, Stacia R; Song, Giltae; Balakrishnan, Rama; Binkley, Gail; Costanzo, Maria C; Dalusag, Kyla S; Demeter, Janos; Hellerstedt, Sage T; Karra, Kalpana; Nash, Robert S; Paskov, Kelley M; Skrzypek, Marek S; Weng, Shuai; Wong, Edith D; Cherry, J Michael

    2016-01-04

    The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org) is the authoritative community resource for the Saccharomyces cerevisiae reference genome sequence and its annotation. In recent years, we have moved toward increased representation of sequence variation and allelic differences within S. cerevisiae. The publication of numerous additional genomes has motivated the creation of new tools for their annotation and analysis. Here we present the Variant Viewer: a dynamic open-source web application for the visualization of genomic and proteomic differences. Multiple sequence alignments have been constructed across high quality genome sequences from 11 different S. cerevisiae strains and stored in the SGD. The alignments and summaries are encoded in JSON and used to create a two-tiered dynamic view of the budding yeast pan-genome, available at http://www.yeastgenome.org/variant-viewer. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  1. Predicción a escala genómica de Componentes de Saccharomyces cerevisiae mediante Análisis de Balance de Flujos

    Directory of Open Access Journals (Sweden)

    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

  2. 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

  3. 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.

  4. Genome and metabolic engineering in non-conventional yeasts: Current advances and applications.

    Science.gov (United States)

    Löbs, Ann-Kathrin; Schwartz, Cory; Wheeldon, Ian

    2017-09-01

    Microbial production of chemicals and proteins from biomass-derived and waste sugar streams is a rapidly growing area of research and development. While the model yeast Saccharomyces cerevisia e is an excellent host for the conversion of glucose to ethanol, production of other chemicals from alternative substrates often requires extensive strain engineering. To avoid complex and intensive engineering of S. cerevisiae, other yeasts are often selected as hosts for bioprocessing based on their natural capacity to produce a desired product: for example, the efficient production and secretion of proteins, lipids, and primary metabolites that have value as commodity chemicals. Even when using yeasts with beneficial native phenotypes, metabolic engineering to increase yield, titer, and production rate is essential. The non-conventional yeasts Kluyveromyces lactis, K. marxianus, Scheffersomyces stipitis, Yarrowia lipolytica, Hansenula polymorpha and Pichia pastoris have been developed as eukaryotic hosts because of their desirable phenotypes, including thermotolerance, assimilation of diverse carbon sources, and high protein secretion. However, advanced metabolic engineering in these yeasts has been limited. This review outlines the challenges of using non-conventional yeasts for strain and pathway engineering, and discusses the developed solutions to these problems and the resulting applications in industrial biotechnology.

  5. Genome scan for nonadditive heterotic trait loci reveals mainly underdominant effects in Saccharomyces cerevisiae.

    Science.gov (United States)

    Laiba, Efrat; Glikaite, Ilana; Levy, Yael; Pasternak, Zohar; Fridman, Eyal

    2016-04-01

    The overdominant model of heterosis explains the superior phenotype of hybrids by synergistic allelic interaction within heterozygous loci. To map such genetic variation in yeast, we used a population doubling time dataset of Saccharomyces cerevisiae 16 × 16 diallel and searched for major contributing heterotic trait loci (HTL). Heterosis was observed for the majority of hybrids, as they surpassed their best parent growth rate. However, most of the local heterozygous loci identified by genome scan were surprisingly underdominant, i.e., reduced growth. We speculated that in these loci adverse effects on growth resulted from incompatible allelic interactions. To test this assumption, we eliminated these allelic interactions by creating hybrids with local hemizygosity for the underdominant HTLs, as well as for control random loci. Growth of hybrids was indeed elevated for most hemizygous to HTL genes but not for control genes, hence validating the results of our genome scan. Assessing the consequences of local heterozygosity by reciprocal hemizygosity and allele replacement assays revealed the influence of genetic background on the underdominant effects of HTLs. Overall, this genome-wide study on a multi-parental hybrid population provides a strong argument against single gene overdominance as a major contributor to heterosis, and favors the dominance complementation model.

  6. Systems Biology for Mapping Genotype-Phenotype Relations in Yeast

    KAUST Repository

    Nielsen, Jens

    2016-01-01

    . Besides its wide industrial use, S. cerevisiae serves as an eukaryal model organism, and many systems biology tools have therefore been developed for this organism. Among these genome-scale metabolic models have shown to be most successful as they easy

  7. 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.

  8. 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.

  9. Genomic diversity and versatility of Lactobacillus plantarum, a natural metabolic engineer

    Science.gov (United States)

    2011-01-01

    In the past decade it has become clear that the lactic acid bacterium Lactobacillus plantarum occupies a diverse range of environmental niches and has an enormous diversity in phenotypic properties, metabolic capacity and industrial applications. In this review, we describe how genome sequencing, comparative genome hybridization and comparative genomics has provided insight into the underlying genomic diversity and versatility of L. plantarum. One of the main features appears to be genomic life-style islands consisting of numerous functional gene cassettes, in particular for carbohydrates utilization, which can be acquired, shuffled, substituted or deleted in response to niche requirements. In this sense, L. plantarum can be considered a “natural metabolic engineer”. PMID:21995294

  10. 2μ plasmid in Saccharomyces species and in Saccharomyces cerevisiae.

    Science.gov (United States)

    Strope, Pooja K; Kozmin, Stanislav G; Skelly, Daniel A; Magwene, Paul M; Dietrich, Fred S; McCusker, John H

    2015-12-01

    We determined that extrachromosomal 2μ plasmid was present in 67 of the Saccharomyces cerevisiae 100-genome strains; in addition to variation in the size and copy number of 2μ, we identified three distinct classes of 2μ. We identified 2μ presence/absence and class associations with populations, clinical origin and nuclear genotypes. We also screened genome sequences of S. paradoxus, S. kudriavzevii, S. uvarum, S. eubayanus, S. mikatae, S. arboricolus and S. bayanus strains for both integrated and extrachromosomal 2μ. Similar to S. cerevisiae, we found no integrated 2μ sequences in any S. paradoxus strains. However, we identified part of 2μ integrated into the genomes of some S. uvarum, S. kudriavzevii, S. mikatae and S. bayanus strains, which were distinct from each other and from all extrachromosomal 2μ. We identified extrachromosomal 2μ in one S. paradoxus, one S. eubayanus, two S. bayanus and 13 S. uvarum strains. The extrachromosomal 2μ in S. paradoxus, S. eubayanus and S. cerevisiae were distinct from each other. In contrast, the extrachromosomal 2μ in S. bayanus and S. uvarum strains were identical with each other and with one of the three classes of S. cerevisiae 2μ, consistent with interspecific transfer. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  11. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Science.gov (United States)

    Barnes, Kayla G; Weedall, Gareth D; Ndula, Miranda; Irving, Helen; Mzihalowa, Themba; Hemingway, Janet; Wondji, Charles S

    2017-02-01

    Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  12. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control.

    Directory of Open Access Journals (Sweden)

    Kayla G Barnes

    2017-02-01

    Full Text Available Insecticide resistance in mosquito populations threatens recent successes in malaria prevention. Elucidating patterns of genetic structure in malaria vectors to predict the speed and direction of the spread of resistance is essential to get ahead of the 'resistance curve' and to avert a public health catastrophe. Here, applying a combination of microsatellite analysis, whole genome sequencing and targeted sequencing of a resistance locus, we elucidated the continent-wide population structure of a major African malaria vector, Anopheles funestus. We identified a major selective sweep in a genomic region controlling cytochrome P450-based metabolic resistance conferring high resistance to pyrethroids. This selective sweep occurred since 2002, likely as a direct consequence of scaled up vector control as revealed by whole genome and fine-scale sequencing of pre- and post-intervention populations. Fine-scaled analysis of the pyrethroid resistance locus revealed that a resistance-associated allele of the cytochrome P450 monooxygenase CYP6P9a has swept through southern Africa to near fixation, in contrast to high polymorphism levels before interventions, conferring high levels of pyrethroid resistance linked to control failure. Population structure analysis revealed a barrier to gene flow between southern Africa and other areas, which may prevent or slow the spread of the southern mechanism of pyrethroid resistance to other regions. By identifying a genetic signature of pyrethroid-based interventions, we have demonstrated the intense selective pressure that control interventions exert on mosquito populations. If this level of selection and spread of resistance continues unabated, our ability to control malaria with current interventions will be compromised.

  13. Progress in terpene synthesis strategies through engineering of Saccharomyces cerevisiae.

    Science.gov (United States)

    Paramasivan, Kalaivani; Mutturi, Sarma

    2017-12-01

    (including patents) on this subject to understand the similarities, to identify novel strategies and to contemplate potential possibilities to build a robust yeast cell factory for terpene or terpenoid production. Emphasis is not restricted to metabolic engineering strategies pertaining to sterol and mevalonate pathway, but also other holistic approaches for elsewhere exploitation in the S. cerevisiae genome are discussed. This review also focuses on process considerations and challenges during the mass production of these potential compounds from the engineered strain for commercial exploitation.

  14. CRISPR–Cas system enables fast and simple genome editing of industrial Saccharomyces cerevisiae strains

    Directory of Open Access Journals (Sweden)

    Vratislav Stovicek

    2015-12-01

    Full Text Available There is a demand to develop 3rd generation biorefineries that integrate energy production with the production of higher value chemicals from renewable feedstocks. Here, robust and stress-tolerant industrial strains of Saccharomyces cerevisiae will be suitable production organisms. However, their genetic manipulation is challenging, as they are usually diploid or polyploid. Therefore, there is a need to develop more efficient genetic engineering tools. We applied a CRISPR–Cas9 system for genome editing of different industrial strains, and show simultaneous disruption of two alleles of a gene in several unrelated strains with the efficiency ranging between 65% and 78%. We also achieved simultaneous disruption and knock-in of a reporter gene, and demonstrate the applicability of the method by designing lactic acid-producing strains in a single transformation event, where insertion of a heterologous gene and disruption of two endogenous genes occurred simultaneously. Our study provides a foundation for efficient engineering of industrial yeast cell factories. Keywords: CRISPR–Cas9, Genome editing, Industrial yeast, Biorefineries, Chemical production

  15. 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

  16. DNA Precursor Metabolism and Mitochondrial Genome Stability

    National Research Council Canada - National Science Library

    Mathews, Christopher K

    2003-01-01

    ...) metabolism and mutagenesis in the mitochondrial genome. Specific contributions include: (1) We found that conditions altering the normal balance among the four dNTP pools within the mitochondrion stimulate both point and deletion mutagenesis...

  17. 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.

  18. The Genome Sequence of Saccharomyces eubayanus and the Domestication of Lager-Brewing Yeasts.

    Science.gov (United States)

    Baker, EmilyClare; Wang, Bing; Bellora, Nicolas; Peris, David; Hulfachor, Amanda Beth; Koshalek, Justin A; Adams, Marie; Libkind, Diego; Hittinger, Chris Todd

    2015-11-01

    The dramatic phenotypic changes that occur in organisms during domestication leave indelible imprints on their genomes. Although many domesticated plants and animals have been systematically compared with their wild genetic stocks, the molecular and genomic processes underlying fungal domestication have received less attention. Here, we present a nearly complete genome assembly for the recently described yeast species Saccharomyces eubayanus and compare it to the genomes of multiple domesticated alloploid hybrids of S. eubayanus × S. cerevisiae (S. pastorianus syn. S. carlsbergensis), which are used to brew lager-style beers. We find that the S. eubayanus subgenomes of lager-brewing yeasts have experienced increased rates of evolution since hybridization, and that certain genes involved in metabolism may have been particularly affected. Interestingly, the S. eubayanus subgenome underwent an especially strong shift in selection regimes, consistent with more extensive domestication of the S. cerevisiae parent prior to hybridization. In contrast to recent proposals that lager-brewing yeasts were domesticated following a single hybridization event, the radically different neutral site divergences between the subgenomes of the two major lager yeast lineages strongly favor at least two independent origins for the S. cerevisiae × S. eubayanus hybrids that brew lager beers. Our findings demonstrate how this industrially important hybrid has been domesticated along similar evolutionary trajectories on multiple occasions. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  19. 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.

  20. 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.

  1. 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...

  2. Sterol synthesis and cell size distribution under oscillatory growth conditions in Saccharomyces cerevisiae scale-down cultivations.

    Science.gov (United States)

    Marbà-Ardébol, Anna-Maria; Bockisch, Anika; Neubauer, Peter; Junne, Stefan

    2018-02-01

    Physiological responses of yeast to oscillatory environments as they appear in the liquid phase in large-scale bioreactors have been the subject of past studies. So far, however, the impact on the sterol content and intracellular regulation remains to be investigated. Since oxygen is a cofactor in several reaction steps within sterol metabolism, changes in oxygen availability, as occurs in production-scale aerated bioreactors, might have an influence on the regulation and incorporation of free sterols into the cell lipid layer. Therefore, sterol and fatty acid synthesis in two- and three-compartment scale-down Saccharomyces cerevisiae cultivation were studied and compared with typical values obtained in homogeneous lab-scale cultivations. While cells were exposed to oscillating substrate and oxygen availability in the scale-down cultivations, growth was reduced and accumulation of carboxylic acids was increased. Sterol synthesis was elevated to ergosterol at the same time. The higher fluxes led to increased concentrations of esterified sterols. The cells thus seem to utilize the increased availability of precursors to fill their sterol reservoirs; however, this seems to be limited in the three-compartment reactor cultivation due to a prolonged exposure to oxygen limitation. Besides, a larger heterogeneity within the single-cell size distribution was observed under oscillatory growth conditions with three-dimensional holographic microscopy. Hence the impact of gradients is also observable at the morphological level. The consideration of such a single-cell-based analysis provides useful information about the homogeneity of responses among the population. Copyright © 2017 John Wiley & Sons, Ltd.

  3. Transcription factor control of growth rate dependent genes in Saccharomyces cerevisiae: A three factor design

    DEFF Research Database (Denmark)

    Fazio, Alessandro; Jewett, Michael Christopher; Daran-Lapujade, Pascale

    2008-01-01

    , such as Ace2 and Swi6, and stress response regulators, such as Yap1, were also shown to have significantly enriched target sets. Conclusion: Our work, which is the first genome-wide gene expression study to investigate specific growth rate and consider the impact of oxygen availability, provides a more......Background: Characterization of cellular growth is central to understanding living systems. Here, we applied a three-factor design to study the relationship between specific growth rate and genome-wide gene expression in 36 steady-state chemostat cultures of Saccharomyces cerevisiae. The three...... factors we considered were specific growth rate, nutrient limitation, and oxygen availability. Results: We identified 268 growth rate dependent genes, independent of nutrient limitation and oxygen availability. The transcriptional response was used to identify key areas in metabolism around which m...

  4. 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.

  5. 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.

  6. General metabolism of Laribacter hongkongensis: a genome-wide analysis

    Directory of Open Access Journals (Sweden)

    Curreem Shirly O

    2011-04-01

    Full Text Available Abstract Background Laribacter hongkongensis is associated with community-acquired gastroenteritis and traveler's diarrhea. In this study, we performed an in-depth annotation of the genes and pathways of the general metabolism of L. hongkongensis and correlated them with its phenotypic characteristics. Results The L. hongkongensis genome possesses the pentose phosphate and gluconeogenesis pathways and tricarboxylic acid and glyoxylate cycles, but incomplete Embden-Meyerhof-Parnas and Entner-Doudoroff pathways, in agreement with its asaccharolytic phenotype. It contains enzymes for biosynthesis and β-oxidation of saturated fatty acids, biosynthesis of all 20 universal amino acids and selenocysteine, the latter not observed in Neisseria gonorrhoeae, Neisseria meningitidis and Chromobacterium violaceum. The genome contains a variety of dehydrogenases, enabling it to utilize different substrates as electron donors. It encodes three terminal cytochrome oxidases for respiration using oxygen as the electron acceptor under aerobic and microaerophilic conditions and four reductases for respiration with alternative electron acceptors under anaerobic conditions. The presence of complete tetrathionate reductase operon may confer survival advantage in mammalian host in association with diarrhea. The genome contains CDSs for incorporating sulfur and nitrogen by sulfate assimilation, ammonia assimilation and nitrate reduction. The existence of both glutamate dehydrogenase and glutamine synthetase/glutamate synthase pathways suggests an importance of ammonia metabolism in the living environments that it may encounter. Conclusions The L. hongkongensis genome possesses a variety of genes and pathways for carbohydrate, amino acid and lipid metabolism, respiratory chain and sulfur and nitrogen metabolism. These allow the bacterium to utilize various substrates for energy production and survive in different environmental niches.

  7. Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast

    Science.gov (United States)

    Oud, Bart; Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

    2012-01-01

    Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. PMID:22152095

  8. Genome-wide analytical approaches for reverse metabolic engineering of industrially relevant phenotypes in yeast.

    Science.gov (United States)

    Oud, Bart; van Maris, Antonius J A; Daran, Jean-Marc; Pronk, Jack T

    2012-03-01

    Successful reverse engineering of mutants that have been obtained by nontargeted strain improvement has long presented a major challenge in yeast biotechnology. This paper reviews the use of genome-wide approaches for analysis of Saccharomyces cerevisiae strains originating from evolutionary engineering or random mutagenesis. On the basis of an evaluation of the strengths and weaknesses of different methods, we conclude that for the initial identification of relevant genetic changes, whole genome sequencing is superior to other analytical techniques, such as transcriptome, metabolome, proteome, or array-based genome analysis. Key advantages of this technique over gene expression analysis include the independency of genome sequences on experimental context and the possibility to directly and precisely reproduce the identified changes in naive strains. The predictive value of genome-wide analysis of strains with industrially relevant characteristics can be further improved by classical genetics or simultaneous analysis of strains derived from parallel, independent strain improvement lineages. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

  9. 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.

  10. 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...

  11. Genome and metabolic engineering in non-conventional yeasts: Current advances and applications

    Directory of Open Access Journals (Sweden)

    Ann-Kathrin Löbs

    2017-09-01

    Full Text Available Microbial production of chemicals and proteins from biomass-derived and waste sugar streams is a rapidly growing area of research and development. While the model yeast Saccharomyces cerevisiae is an excellent host for the conversion of glucose to ethanol, production of other chemicals from alternative substrates often requires extensive strain engineering. To avoid complex and intensive engineering of S. cerevisiae, other yeasts are often selected as hosts for bioprocessing based on their natural capacity to produce a desired product: for example, the efficient production and secretion of proteins, lipids, and primary metabolites that have value as commodity chemicals. Even when using yeasts with beneficial native phenotypes, metabolic engineering to increase yield, titer, and production rate is essential. The non-conventional yeasts Kluyveromyces lactis, K. marxianus, Scheffersomyces stipitis, Yarrowia lipolytica, Hansenula polymorpha and Pichia pastoris have been developed as eukaryotic hosts because of their desirable phenotypes, including thermotolerance, assimilation of diverse carbon sources, and high protein secretion. However, advanced metabolic engineering in these yeasts has been limited. This review outlines the challenges of using non-conventional yeasts for strain and pathway engineering, and discusses the developed solutions to these problems and the resulting applications in industrial biotechnology.

  12. 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:

  13. Saccharomyces cerevisiae strains for second-generation ethanol production: from academic exploration to industrial implementation

    Science.gov (United States)

    Jansen, Mickel L. A.; Bracher, Jasmine M.; Papapetridis, Ioannis; Verhoeven, Maarten D.; de Bruijn, Hans; de Waal, Paul P.; van Maris, Antonius J. A.; Klaassen, Paul

    2017-01-01

    Abstract The recent start-up of several full-scale ‘second generation’ ethanol plants marks a major milestone in the development of Saccharomyces cerevisiae strains for fermentation of lignocellulosic hydrolysates of agricultural residues and energy crops. After a discussion of the challenges that these novel industrial contexts impose on yeast strains, this minireview describes key metabolic engineering strategies that have been developed to address these challenges. Additionally, it outlines how proof-of-concept studies, often developed in academic settings, can be used for the development of robust strain platforms that meet the requirements for industrial application. Fermentation performance of current engineered industrial S. cerevisiae strains is no longer a bottleneck in efforts to achieve the projected outputs of the first large-scale second-generation ethanol plants. Academic and industrial yeast research will continue to strengthen the economic value position of second-generation ethanol production by further improving fermentation kinetics, product yield and cellular robustness under process conditions. PMID:28899031

  14. 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.

  15. 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.

  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. Oxidative DNA damage causes mitochondrial genomic instability in Saccharomyces cerevisiae.

    Science.gov (United States)

    Doudican, Nicole A; Song, Binwei; Shadel, Gerald S; Doetsch, Paul W

    2005-06-01

    Mitochondria contain their own genome, the integrity of which is required for normal cellular energy metabolism. Reactive oxygen species (ROS) produced by normal mitochondrial respiration can damage cellular macromolecules, including mitochondrial DNA (mtDNA), and have been implicated in degenerative diseases, cancer, and aging. We developed strategies to elevate mitochondrial oxidative stress by exposure to antimycin and H(2)O(2) or utilizing mutants lacking mitochondrial superoxide dismutase (sod2Delta). Experiments were conducted with strains compromised in mitochondrial base excision repair (ntg1Delta) and oxidative damage resistance (pif1Delta) in order to delineate the relationship between these pathways. We observed enhanced ROS production, resulting in a direct increase in oxidative mtDNA damage and mutagenesis. Repair-deficient mutants exposed to oxidative stress conditions exhibited profound genomic instability. Elimination of Ntg1p and Pif1p resulted in a synergistic corruption of respiratory competency upon exposure to antimycin and H(2)O(2). Mitochondrial genomic integrity was substantially compromised in ntg1Delta pif1Delta sod2Delta strains, since these cells exhibit a total loss of mtDNA. A stable respiration-defective strain, possessing a normal complement of mtDNA damage resistance pathways, exhibited a complete loss of mtDNA upon exposure to antimycin and H(2)O(2). This loss was preventable by Sod2p overexpression. These results provide direct evidence that oxidative mtDNA damage can be a major contributor to mitochondrial genomic instability and demonstrate cooperation of Ntg1p and Pif1p to resist the introduction of lesions into the mitochondrial genome.

  18. Ensembl Genomes 2013: scaling up access to genome-wide data.

    Science.gov (United States)

    Kersey, Paul Julian; Allen, James E; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Hughes, Daniel Seth Toney; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Langridge, Nicholas; McDowall, Mark D; Maheswari, Uma; Maslen, Gareth; Nuhn, Michael; Ong, Chuang Kee; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Tuli, Mary Ann; Walts, Brandon; Williams, Gareth; Wilson, Derek; Youens-Clark, Ken; Monaco, Marcela K; Stein, Joshua; Wei, Xuehong; Ware, Doreen; Bolser, Daniel M; Howe, Kevin Lee; Kulesha, Eugene; Lawson, Daniel; Staines, Daniel Michael

    2014-01-01

    Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies 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. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future.

  19. [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.

  20. 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.

  1. Physiological impact and context dependency of transcriptional responses : A chemostat study in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Tai, S.L.

    2007-01-01

    This thesis is a compilation of a four-year PhD project on bakers' yeast (Saccharomyces cerevisiae). Since the entire S. cerevisiae genome sequence became available in 1996, DNA-microarray analysis has become a popular high-information-density tool for analyzing gene expression in this important

  2. History of genome editing in yeast.

    Science.gov (United States)

    Fraczek, Marcin G; Naseeb, Samina; Delneri, Daniela

    2018-05-01

    For thousands of years humans have used the budding yeast Saccharomyces cerevisiae for the production of bread and alcohol; however, in the last 30-40 years our understanding of the yeast biology has dramatically increased, enabling us to modify its genome. Although S. cerevisiae has been the main focus of many research groups, other non-conventional yeasts have also been studied and exploited for biotechnological purposes. Our experiments and knowledge have evolved from recombination to high-throughput PCR-based transformations to highly accurate CRISPR methods in order to alter yeast traits for either research or industrial purposes. Since the release of the genome sequence of S. cerevisiae in 1996, the precise and targeted genome editing has increased significantly. In this 'Budding topic' we discuss the significant developments of genome editing in yeast, mainly focusing on Cre-loxP mediated recombination, delitto perfetto and CRISPR/Cas. © 2018 The Authors. Yeast published by John Wiley & Sons, Ltd.

  3. Differential metabolism of Mycoplasma species as revealed by their genomes

    Directory of Open Access Journals (Sweden)

    Fabricio B.M. Arraes

    2007-01-01

    Full Text Available The annotation and comparative analyses of the genomes of Mycoplasma synoviae and Mycoplasma hyopneumonie, as well as of other Mollicutes (a group of bacteria devoid of a rigid cell wall, has set the grounds for a global understanding of their metabolism and infection mechanisms. According to the annotation data, M. synoviae and M. hyopneumoniae are able to perform glycolytic metabolism, but do not possess the enzymatic machinery for citrate and glyoxylate cycles, gluconeogenesis and the pentose phosphate pathway. Both can synthesize ATP by lactic fermentation, but only M. synoviae can convert acetaldehyde to acetate. Also, our genome analysis revealed that M. synoviae and M. hyopneumoniae are not expected to synthesize polysaccharides, but they can take up a variety of carbohydrates via the phosphoenolpyruvate-dependent phosphotransferase system (PEP-PTS. Our data showed that these two organisms are unable to synthesize purine and pyrimidine de novo, since they only possess the sequences which encode salvage pathway enzymes. Comparative analyses of M. synoviae and M. hyopneumoniae with other Mollicutes have revealed differential genes in the former two genomes coding for enzymes that participate in carbohydrate, amino acid and nucleotide metabolism and host-pathogen interaction. The identification of these metabolic pathways will provide a better understanding of the biology and pathogenicity of these organisms.

  4. 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

  5. Genomic diversity of Saccharomyces cerevisiae yeasts associated with alcoholic fermentation of bacanora produced by artisanal methods.

    Science.gov (United States)

    Álvarez-Ainza, M L; Zamora-Quiñonez, K A; Moreno-Ibarra, G M; Acedo-Félix, E

    2015-03-01

    Bacanora is a spirituous beverage elaborated with Agave angustifolia Haw in an artisanal process. Natural fermentation is mostly performed with native yeasts and bacteria. In this study, 228 strains of yeast like Saccharomyces were isolated from the natural alcoholic fermentation on the production of bacanora. Restriction analysis of the amplified region ITS1-5.8S-ITS2 of the ribosomal DNA genes (RFLPr) were used to confirm the genus, and 182 strains were identified as Saccharomyces cerevisiae. These strains displayed high genomic variability in their chromosomes profiles by karyotyping. Electrophoretic profiles of the strains evaluated showed a large number of chromosomes the size of which ranged between 225 and 2200 kpb approximately.

  6. 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.

  7. Metabolic Engineering for Probiotics and their Genome-Wide Expression Profiling.

    Science.gov (United States)

    Yadav, Ruby; Singh, Puneet K; Shukla, Pratyoosh

    2018-01-01

    Probiotic supplements in food industry have attracted a lot of attention and shown a remarkable growth in this field. Metabolic engineering (ME) approaches enable understanding their mechanism of action and increases possibility of designing probiotic strains with desired functions. Probiotic microorganisms generally referred as industrially important lactic acid bacteria (LAB) which are involved in fermenting dairy products, food, beverages and produces lactic acid as final product. A number of illustrations of metabolic engineering approaches in industrial probiotic bacteria have been described in this review including transcriptomic studies of Lactobacillus reuteri and improvement in exopolysaccharide (EPS) biosynthesis yield in Lactobacillus casei LC2W. This review summaries various metabolic engineering approaches for exploring metabolic pathways. These approaches enable evaluation of cellular metabolic state and effective editing of microbial genome or introduction of novel enzymes to redirect the carbon fluxes. In addition, various system biology tools such as in silico design commonly used for improving strain performance is also discussed. Finally, we discuss the integration of metabolic engineering and genome profiling which offers a new way to explore metabolic interactions, fluxomics and probiogenomics using probiotic bacteria like Bifidobacterium spp and Lactobacillus spp. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  8. Genome-wide screening of Saccharomyces cerevisiae genes regulated by vanillin.

    Science.gov (United States)

    Park, Eun-Hee; Kim, Myoung-Dong

    2015-01-01

    During pretreatment of lignocellulosic biomass, a variety of fermentation inhibitors, including acetic acid and vanillin, are released. Using DNA microarray analysis, this study explored genes of the budding yeast Saccharomyces cerevisiae that respond to vanillin-induced stress. The expression of 273 genes was upregulated and that of 205 genes was downregulated under vanillin stress. Significantly induced genes included MCH2, SNG1, GPH1, and TMA10, whereas NOP2, UTP18, FUR1, and SPR1 were down regulated. Sequence analysis of the 5'-flanking region of upregulated genes suggested that vanillin might regulate gene expression in a stress response element (STRE)-dependent manner, in addition to a pathway that involved the transcription factor Yap1p. Retardation in the cell growth of mutant strains indicated that MCH2, SNG1, and GPH1 are intimately involved in vanillin stress response. Deletion of the genes whose expression levels were decreased under vanillin stress did not result in a notable change in S. cerevisiae growth under vanillin stress. This study will provide the basis for a better understanding of the stress response of the yeast S. cerevisiae to fermentation inhibitors.

  9. 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.

  10. 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

  11. Genome-wide association studies of obesity and metabolic syndrome.

    Science.gov (United States)

    Fall, Tove; Ingelsson, Erik

    2014-01-25

    Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  12. 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...

  13. A novel strategy to construct yeast Saccharomyces cerevisiae strains for very high gravity fermentation.

    Directory of Open Access Journals (Sweden)

    Xianglin Tao

    Full Text Available Very high gravity (VHG fermentation is aimed to considerably increase both the fermentation rate and the ethanol concentration, thereby reducing capital costs and the risk of bacterial contamination. This process results in critical issues, such as adverse stress factors (ie., osmotic pressure and ethanol inhibition and high concentrations of metabolic byproducts which are difficult to overcome by a single breeding method. In the present paper, a novel strategy that combines metabolic engineering and genome shuffling to circumvent these limitations and improve the bioethanol production performance of Saccharomyces cerevisiae strains under VHG conditions was developed. First, in strain Z5, which performed better than other widely used industrial strains, the gene GPD2 encoding glycerol 3-phosphate dehydrogenase was deleted, resulting in a mutant (Z5ΔGPD2 with a lower glycerol yield and poor ethanol productivity. Second, strain Z5ΔGPD2 was subjected to three rounds of genome shuffling to improve its VHG fermentation performance, and the best performing strain SZ3-1 was obtained. Results showed that strain SZ3-1 not only produced less glycerol, but also increased the ethanol yield by up to 8% compared with the parent strain Z5. Further analysis suggested that the improved ethanol yield in strain SZ3-1 was mainly contributed by the enhanced ethanol tolerance of the strain. The differences in ethanol tolerance between strains Z5 and SZ3-1 were closely associated with the cell membrane fatty acid compositions and intracellular trehalose concentrations. Finally, genome rearrangements in the optimized strain were confirmed by karyotype analysis. Hence, a combination of genome shuffling and metabolic engineering is an efficient approach for the rapid improvement of yeast strains for desirable industrial phenotypes.

  14. Genome-wide identification of genes involved in growth and fermentation activity at low temperature in Saccharomyces cerevisiae.

    Science.gov (United States)

    Salvadó, Zoel; Ramos-Alonso, Lucía; Tronchoni, Jordi; Penacho, Vanessa; García-Ríos, Estéfani; Morales, Pilar; Gonzalez, Ramon; Guillamón, José Manuel

    2016-11-07

    Fermentation at low temperatures is one of the most popular current winemaking practices because of its reported positive impact on the aromatic profile of wines. However, low temperature is an additional hurdle to develop Saccharomyces cerevisiae wine yeasts, which are already stressed by high osmotic pressure, low pH and poor availability of nitrogen sources in grape must. Understanding the mechanisms of adaptation of S. cerevisiae to fermentation at low temperature would help to design strategies for process management, and to select and improve wine yeast strains specifically adapted to this winemaking practice. The problem has been addressed by several approaches in recent years, including transcriptomic and other high-throughput strategies. In this work we used a genome-wide screening of S. cerevisiae diploid mutant strain collections to identify genes that potentially contribute to adaptation to low temperature fermentation conditions. Candidate genes, impaired for growth at low temperatures (12°C and 18°C), but not at a permissive temperature (28°C), were deleted in an industrial homozygous genetic background, wine yeast strain FX10, in both heterozygosis and homozygosis. Some candidate genes were required for growth at low temperatures only in the laboratory yeast genetic background, but not in FX10 (namely the genes involved in aromatic amino acid biosynthesis). Other genes related to ribosome biosynthesis (SNU66 and PAP2) were required for low-temperature fermentation of synthetic must (SM) in the industrial genetic background. This result coincides with our previous findings about translation efficiency with the fitness of different wine yeast strains at low temperature. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. 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.

  16. 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.

  17. 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

  18. Acidithiobacillus ferrooxidans metabolism: from genome sequence to industrial applications

    Directory of Open Access Journals (Sweden)

    Blake Robert

    2008-12-01

    Full Text Available Abstract Background Acidithiobacillus ferrooxidans is a major participant in consortia of microorganisms used for the industrial recovery of copper (bioleaching or biomining. It is a chemolithoautrophic, γ-proteobacterium using energy from the oxidation of iron- and sulfur-containing minerals for growth. It thrives at extremely low pH (pH 1–2 and fixes both carbon and nitrogen from the atmosphere. It solubilizes copper and other metals from rocks and plays an important role in nutrient and metal biogeochemical cycling in acid environments. The lack of a well-developed system for genetic manipulation has prevented thorough exploration of its physiology. Also, confusion has been caused by prior metabolic models constructed based upon the examination of multiple, and sometimes distantly related, strains of the microorganism. Results The genome of the type strain A. ferrooxidans ATCC 23270 was sequenced and annotated to identify general features and provide a framework for in silico metabolic reconstruction. Earlier models of iron and sulfur oxidation, biofilm formation, quorum sensing, inorganic ion uptake, and amino acid metabolism are confirmed and extended. Initial models are presented for central carbon metabolism, anaerobic metabolism (including sulfur reduction, hydrogen metabolism and nitrogen fixation, stress responses, DNA repair, and metal and toxic compound fluxes. Conclusion Bioinformatics analysis provides a valuable platform for gene discovery and functional prediction that helps explain the activity of A. ferrooxidans in industrial bioleaching and its role as a primary producer in acidic environments. An analysis of the genome of the type strain provides a coherent view of its gene content and metabolic potential.

  19. Comparative genomics of Westiellopsis prolifica a freshwater cyanobacteria uncovers the prolific and distinctive metabolic potentials

    Directory of Open Access Journals (Sweden)

    Vineeta Verma

    2017-10-01

    Full Text Available Cyanobacteria are one of the ancient Micro-organisms that originated about 2.5 billion years ago. They are a very rich source for production of various natural compounds that are largely scalable in pharmaceutical and biotechnology industries. The unicellular Cyanobacteria are more ancient than the multicellular forms. In this study, we are exploring the genomes of a multi cellular, heterocystous, true branching Cyanobacteria, Westiellopsis prolifica belonging to order Nostocales. Complete genome is essential to serve as a reference for other sequencing projects and from which we can confirm the presence of various useful metabolic genes which are important for manufacturing pharmaceutical products. Here we report the draft assembly of Westiellopsis prolifica genome of 7.2 Mb with 19 scaffolds and the N50 and largest contig sizes are 2650655 bp and 3476031 bp, respectively. The phylogenomic studies from the literature reveal the closest relative of Westiellopsis prolifica are Fischerella sp. pcc 9431, Fischerella sp. pcc 9939 and Hapalosiphon welwitschii. Our preliminary comparative genomic analysis revealed that the sequence identity with the neighbouring clades were less, although we observed the large set of genes were syntenic and arranged in conserved in clusters. Genome mining on these organisms identified several clusters of NRPS, polyketide biosynthesis, two-component system, heterocyst differentiation genes and Nif genes were conserved in these genomes. We identified 21 clusters of secondary metabolites, which include NRPS and polyketide genes. For extraction of metabolites, we used several organic solvents. These extract contain various metabolic products which can be further exploited for the large scale production by genetic engineering approaches. Our Future work includes checking the RNAseq expressions of these metabolite producing genes.

  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. Improving ethanol fermentation performance of Saccharomyces cerevisiae in very high-gravity fermentation through chemical mutagenesis and meiotic recombination

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Jing-Jing; Ding, Wen-Tao; Zhang, Guo-Chang; Wang, Jing-Yu [Tianjin Univ. (China). Dept. of Biochemical Engineering

    2011-08-15

    Genome shuffling is an efficient way to improve complex phenotypes under the control of multiple genes. For the improvement of strain's performance in very high-gravity (VHG) fermentation, we developed a new method of genome shuffling. A diploid ste2/ste2 strain was subjected to EMS (ethyl methanesulfonate) mutagenesis followed by meiotic recombination-mediated genome shuffling. The resulting haploid progenies were intrapopulation sterile and therefore haploid recombinant cells with improved phenotypes were directly selected under selection condition. In VHG fermentation, strain WS1D and WS5D obtained by this approach exhibited remarkably enhanced tolerance to ethanol and osmolarity, increased metabolic rate, and 15.12% and 15.59% increased ethanol yield compared to the starting strain W303D, respectively. These results verified the feasibility of the strain improvement strategy and suggested that it is a powerful and high throughput method for development of Saccharomyces cerevisiae strains with desired phenotypes that is complex and cannot be addressed with rational approaches. (orig.)

  2. Extreme-Scale De Novo Genome Assembly

    Energy Technology Data Exchange (ETDEWEB)

    Georganas, Evangelos [Intel Corporation, Santa Clara, CA (United States); Hofmeyr, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.; Rokhsar, Daniel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division; Yelick, Katherine [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint Genome Inst.

    2017-09-26

    De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern genomics. This work presents HipMER, a high-quality end-to-end de novo assembler designed for extreme scale analysis, via efficient parallelization of the Meraculous code. Genome assembly software has many components, each of which stresses different components of a computer system. This chapter explains the computational challenges involved in each step of the HipMer pipeline, the key distributed data structures, and communication costs in detail. We present performance results of assembling the human genome and the large hexaploid wheat genome on large supercomputers up to tens of thousands of cores.

  3. Functional expression of amine oxidase from Aspergillus niger (AO-I) in Saccharomyces cerevisiae.

    Science.gov (United States)

    Kolaríková, Katerina; Galuszka, Petr; Sedlárová, Iva; Sebela, Marek; Frébort, Ivo

    2009-01-01

    The aim of this work was to prepare recombinant amine oxidase from Aspergillus niger after overexpressing in yeast. The yeast expression vector pDR197 that includes a constitutive PMA1 promoter was used for the expression in Saccharomyces cerevisiae. Recombinant amine oxidase was extracted from the growth medium of the yeast, purified to homogeneity and identified by activity assay and MALDI-TOF peptide mass fingerprinting. Similarity search in the newly published A. niger genome identified six genes coding for copper amine oxidase, two of them corresponding to the previously described enzymes AO-I a methylamine oxidase and three other genes coding for FAD amine oxidases. Thus, A. niger possesses an enormous metabolic gear to grow on amine compounds and thus support its saprophytic lifestyle.

  4. 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.

  5. 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

  6. 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.

  7. Multiplex engineering of industrial yeast genomes using CRISPRm.

    Science.gov (United States)

    Ryan, Owen W; Cate, Jamie H D

    2014-01-01

    Global demand has driven the use of industrial strains of the yeast Saccharomyces cerevisiae for large-scale production of biofuels and renewable chemicals. However, the genetic basis of desired domestication traits is poorly understood because robust genetic tools do not exist for industrial hosts. We present an efficient, marker-free, high-throughput, and multiplexed genome editing platform for industrial strains of S. cerevisiae that uses plasmid-based expression of the CRISPR/Cas9 endonuclease and multiple ribozyme-protected single guide RNAs. With this multiplex CRISPR (CRISPRm) system, it is possible to integrate DNA libraries into the chromosome for evolution experiments, and to engineer multiple loci simultaneously. The CRISPRm tools should therefore find use in many higher-order synthetic biology applications to accelerate improvements in industrial microorganisms.

  8. 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

  9. 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.

  10. From pathways to genomes and beyond. The metabolic engineering toolbox and its place in biofuels production

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Leqian; Reed, Ben; Alper, Hal [Texas Univ., Austin, TX (United States). Dept. of Chemical Engineering

    2011-07-01

    Concerns about the availability of petroleum-derived fuels and chemicals have led to the exploration of metabolically engineered organisms as novel hosts for biofuels and chemicals production. However, the complexity inherent in metabolic and regulatory networks makes this undertaking a complex task. To address these limitations, metabolic engineering has adapted a wide-variety of tools for altering phenotypes. In this review, we will highlight traditional and recent metabolic engineering tools for optimizing cells including pathway-based, global, and genomic-enabled approaches. Specifically, we describe these tools as well as provide demonstrations of their effectiveness in optimizing biofuels production. However, each of these tools provides stepping stones towards the grand goal of biofuels production. Thus, developing methods for large-scale cellular optimization and integrative approaches are invaluable for further cell optimization. This review highlights the challenges that still must be met to accomplish this goal. (orig.)

  11. Metabolic Trade-offs between Biomass Synthesis and Photosynthate Export at Different Light Intensities in a Genome–Scale Metabolic Model of Rice

    Directory of Open Access Journals (Sweden)

    Mark Graham Poolman

    2014-11-01

    Full Text Available Previously we have used a genome scale model of rice metabolism to describe how metabolism reconfigures at different light intensities in an expanding leaf of rice. Although this established that the metabolism of the leaf was adequatelyrepresented, in the model, the scenario was not that of the typical function of the leaf --- to provide material for the rest of the plant. Here we extend our analysis to explore the transition to a source leaf as export of photosynthate increases at the expense of making leaf biomass precursors, again as a function of light intensity. In particular we investigate whether, when the leaf is making a smaller range of compounds for export to the phloem, the same changes occur in the interactions between mitochondrial and chloroplast metabolism as seen in biomass synthesis for growth when light intensity increases. Our results show that the same changes occur qualitatively, though there are slight quantitative differences reflecting differences in the energy and redox requirements for the different metabolic outputs.

  12. Gene Amplification on Demand Accelerates Cellobiose Utilization in Engineered Saccharomyces cerevisiae.

    Science.gov (United States)

    Oh, Eun Joong; Skerker, Jeffrey M; Kim, Soo Rin; Wei, Na; Turner, Timothy L; Maurer, Matthew J; Arkin, Adam P; Jin, Yong-Su

    2016-06-15

    Efficient microbial utilization of cellulosic sugars is essential for the economic production of biofuels and chemicals. Although the yeast Saccharomyces cerevisiae is a robust microbial platform widely used in ethanol plants using sugar cane and corn starch in large-scale operations, glucose repression is one of the significant barriers to the efficient fermentation of cellulosic sugar mixtures. A recent study demonstrated that intracellular utilization of cellobiose by engineered yeast expressing a cellobiose transporter (encoded by cdt-1) and an intracellular β-glucosidase (encoded by gh1-1) can alleviate glucose repression, resulting in the simultaneous cofermentation of cellobiose and nonglucose sugars. Here we report enhanced cellobiose fermentation by engineered yeast expressing cdt-1 and gh1-1 through laboratory evolution. When cdt-1 and gh1-1 were integrated into the genome of yeast, the single copy integrant showed a low cellobiose consumption rate. However, cellobiose fermentation rates by engineered yeast increased gradually during serial subcultures on cellobiose. Finally, an evolved strain exhibited a 15-fold-higher cellobiose fermentation rate. To identify the responsible mutations in the evolved strain, genome sequencing was performed. Interestingly, no mutations affecting cellobiose fermentation were identified, but the evolved strain contained 9 copies of cdt-1 and 23 copies of gh1-1 We also traced the copy numbers of cdt-1 and gh1-1 of mixed populations during the serial subcultures. The copy numbers of cdt-1 and gh1-1 in the cultures increased gradually with similar ratios as cellobiose fermentation rates of the cultures increased. These results suggest that the cellobiose assimilation pathway (transport and hydrolysis) might be a rate-limiting step in engineered yeast and copies of genes coding for metabolic enzymes might be amplified in yeast if there is a growth advantage. This study indicates that on-demand gene amplification might be an

  13. Yeast "make-accumulate-consume" life strategy evolved as a multi-step process that predates the whole genome duplication.

    Science.gov (United States)

    Hagman, Arne; Säll, Torbjörn; Compagno, Concetta; Piskur, Jure

    2013-01-01

    When fruits ripen, microbial communities start a fierce competition for the freely available fruit sugars. Three yeast lineages, including baker's yeast Saccharomyces cerevisiae, have independently developed the metabolic activity to convert simple sugars into ethanol even under fully aerobic conditions. This fermentation capacity, named Crabtree effect, reduces the cell-biomass production but provides in nature a tool to out-compete other microorganisms. Here, we analyzed over forty Saccharomycetaceae yeasts, covering over 200 million years of the evolutionary history, for their carbon metabolism. The experiments were done under strictly controlled and uniform conditions, which has not been done before. We show that the origin of Crabtree effect in Saccharomycetaceae predates the whole genome duplication and became a settled metabolic trait after the split of the S. cerevisiae and Kluyveromyces lineages, and coincided with the origin of modern fruit bearing plants. Our results suggest that ethanol fermentation evolved progressively, involving several successive molecular events that have gradually remodeled the yeast carbon metabolism. While some of the final evolutionary events, like gene duplications of glucose transporters and glycolytic enzymes, have been deduced, the earliest molecular events initiating Crabtree effect are still to be determined.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. Controlled mixed fermentation at winery scale using Zygotorulaspora florentina and Saccharomyces cerevisiae.

    Science.gov (United States)

    Lencioni, Livio; Romani, Cristina; Gobbi, Mirko; Comitini, Francesca; Ciani, Maurizio; Domizio, Paola

    2016-10-03

    Over the last few years the use of multi-starter inocula has become an attractive biotechnological practice in the search for wine with high flavour complexity or distinctive characters. This has been possible through exploiting the particular oenological features of some non-Saccharomyces yeast strains, and the effects that derive from their specific interactions with Saccharomyces. In the present study, we evaluated the selected strain Zygotorulaspora florentina (formerly Zygosaccharomyces florentinus) in mixed culture fermentations with Saccharomyces cerevisiae, from the laboratory scale to the winery scale. The scale-up fermentation and substrate composition (i.e., white or red musts) influenced the analytical composition of the mixed fermentation. At the laboratory scale, mixed fermentation with Z. florentina exhibited an enhancement of polysaccharides and 2-phenylethanol content and a reduction of volatile acidity. At the winery scale, different fermentation characteristics of Z. florentina were observed. Using Sangiovese red grape juice, sequential fermentation trials showed a significantly higher concentration of glycerol and esters while the sensorial analysis of the resulting wines showed higher floral notes and lower perception of astringency. To our knowledge, this is the first time that this yeasts association has been evaluated at the winery scale indicating the potential use of this mixed culture in red grape varieties. Copyright © 2016. Published by Elsevier B.V.

  19. A novel approach for the improvement of ethanol fermentation by Saccharomyces cerevisiae

    Energy Technology Data Exchange (ETDEWEB)

    Hou, L.; Cao, X.; Wang, C. [Tianjin Univ. of Science and Technology, Tianjin (China). Key Laboratory of Food Nutrition and Safety

    2010-06-15

    The partial substitution of fossil fuels with bioethanol has become an important strategy for the use of renewable energy. Ethanol production is generally achieved through fermentation of starch or sugar-based feedstock by Saccharomyces cerevisiae. In order to meet the growing demand for ethanol, there is a need for new yeast strains that can produce ethanol more efficiently and cost effectively. This paper presented a new genome engineering approach that was developed to improve ethanol production by S. cerevisiae. In this study, the aneuploid strain constructed on the base of tetraploid cells was shown to have favourable metabolic traits in very high gravity (VHG) fermentation with 300 g/L glucose as the carbon source. The tetraploid strain was constructed using the plasmid YCplac33-GHK, which comprised the HO gene encoding the site-specific HO endonucleases. The aneuploid strain, WT4-M, was chosen and screened once the tetraploid cells were treated with methyl benzimidazole-2-yl-carbamate to induce loss of mitotic chromosomes. The aneuploid strain WT4-M increased ethanol production as well as osmotic and thermal tolerance. The sugar to ethanol conversion rate also improved. It was concluded that this new approach is valuable for creating yeast strains with better fermentation characteristics. 25 refs., 3 figs.

  20. Novel strategy to improve vanillin tolerance and ethanol fermentation performances of Saccharomycere cerevisiae strains.

    Science.gov (United States)

    Zheng, Dao-Qiong; Jin, Xin-Na; Zhang, Ke; Fang, Ya-Hong; Wu, Xue-Chang

    2017-05-01

    The aim of this work was to develop a novel strategy for improving the vanillin tolerance and ethanol fermentation performances of Saccharomyces cerevisiae strains. Isogeneic diploid, triploid, and tetraploid S. cerevisiae strains were generated by genome duplication of haploid strain CEN.PK2-1C. Ploidy increments improved vanillin tolerance and diminished proliferation capability. Antimitotic drug methyl benzimidazol-2-ylcarbamate (MBC) was used to introduce chromosomal aberrations into the tetraploid S. cerevisiae strain. Interestingly, aneuploid mutants with DNA contents between triploid and tetraploid were more resistant to vanillin and showed faster ethanol fermentation rates than all euploid strains. The physiological characteristics of these mutants suggest that higher bioconversion capacities of vanillin and ergosterol contents might contribute to improved vanillin tolerance. This study demonstrates that genome duplication and MBC treatment is a powerful strategy to improve the vanillin tolerance of yeast strains. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

    Directory of Open Access Journals (Sweden)

    Adam Alexander Thil Smith

    2012-05-01

    Full Text Available Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes, a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short. The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

  2. 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)

  3. 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.

  4. 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.

  5. 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.

  6. G-quadruplex DNA sequences are evolutionarily conserved and associated with distinct genomic features in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    John A Capra

    2010-07-01

    Full Text Available G-quadruplex DNA is a four-stranded DNA structure formed by non-Watson-Crick base pairing between stacked sets of four guanines. Many possible functions have been proposed for this structure, but its in vivo role in the cell is still largely unresolved. We carried out a genome-wide survey of the evolutionary conservation of regions with the potential to form G-quadruplex DNA structures (G4 DNA motifs across seven yeast species. We found that G4 DNA motifs were significantly more conserved than expected by chance, and the nucleotide-level conservation patterns suggested that the motif conservation was the result of the formation of G4 DNA structures. We characterized the association of conserved and non-conserved G4 DNA motifs in Saccharomyces cerevisiae with more than 40 known genome features and gene classes. Our comprehensive, integrated evolutionary and functional analysis confirmed the previously observed associations of G4 DNA motifs with promoter regions and the rDNA, and it identified several previously unrecognized associations of G4 DNA motifs with genomic features, such as mitotic and meiotic double-strand break sites (DSBs. Conserved G4 DNA motifs maintained strong associations with promoters and the rDNA, but not with DSBs. We also performed the first analysis of G4 DNA motifs in the mitochondria, and surprisingly found a tenfold higher concentration of the motifs in the AT-rich yeast mitochondrial DNA than in nuclear DNA. The evolutionary conservation of the G4 DNA motif and its association with specific genome features supports the hypothesis that G4 DNA has in vivo functions that are under evolutionary constraint.

  7. 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...

  8. 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

  9. Comparative Genomics and Disorder Prediction Identify Biologically Relevant SH3 Protein Interactions.

    Directory of Open Access Journals (Sweden)

    2005-08-01

    Full Text Available Protein interaction networks are an important part of the post-genomic effort to integrate a part-list view of the cell into system-level understanding. Using a set of 11 yeast genomes we show that combining comparative genomics and secondary structure information greatly increases consensus-based prediction of SH3 targets. Benchmarking of our method against positive and negative standards gave 83% accuracy with 26% coverage. The concept of an optimal divergence time for effective comparative genomics studies was analyzed, demonstrating that genomes of species that diverged very recently from Saccharomyces cerevisiae(S. mikatae, S. bayanus, and S. paradoxus, or a long time ago (Neurospora crassa and Schizosaccharomyces pombe, contain less information for accurate prediction of SH3 targets than species within the optimal divergence time proposed. We also show here that intrinsically disordered SH3 domain targets are more probable sites of interaction than equivalent sites within ordered regions. Our findings highlight several novel S. cerevisiae SH3 protein interactions, the value of selection of optimal divergence times in comparative genomics studies, and the importance of intrinsic disorder for protein interactions. Based on our results we propose novel roles for the S. cerevisiae proteins Abp1p in endocytosis and Hse1p in endosome protein sorting.

  10. Comparative genomics and disorder prediction identify biologically relevant SH3 protein interactions.

    Directory of Open Access Journals (Sweden)

    Pedro Beltrao

    2005-08-01

    Full Text Available Protein interaction networks are an important part of the post-genomic effort to integrate a part-list view of the cell into system-level understanding. Using a set of 11 yeast genomes we show that combining comparative genomics and secondary structure information greatly increases consensus-based prediction of SH3 targets. Benchmarking of our method against positive and negative standards gave 83% accuracy with 26% coverage. The concept of an optimal divergence time for effective comparative genomics studies was analyzed, demonstrating that genomes of species that diverged very recently from Saccharomyces cerevisiae(S. mikatae, S. bayanus, and S. paradoxus, or a long time ago (Neurospora crassa and Schizosaccharomyces pombe, contain less information for accurate prediction of SH3 targets than species within the optimal divergence time proposed. We also show here that intrinsically disordered SH3 domain targets are more probable sites of interaction than equivalent sites within ordered regions. Our findings highlight several novel S. cerevisiae SH3 protein interactions, the value of selection of optimal divergence times in comparative genomics studies, and the importance of intrinsic disorder for protein interactions. Based on our results we propose novel roles for the S. cerevisiae proteins Abp1p in endocytosis and Hse1p in endosome protein sorting.

  11. 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

  12. 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.

  13. Increased mannoprotein content in wines produced by Saccharomyces kudriavzevii×Saccharomyces cerevisiae hybrids.

    Science.gov (United States)

    Pérez-Través, Laura; Querol, Amparo; Pérez-Torrado, Roberto

    2016-11-21

    Several wine quality aspects are influenced by yeast mannoproteins on account of aroma compounds retention, lactic-acid bacterial growth stimulation, protection against protein haze and astringency reduction. Thus selecting a yeast strain that produces high levels of mannoproteins is important for the winemaking industry. In this work, we observed increased levels of mannoproteins in S. cerevisiae×S. kudriavzevii hybrids, compared to the S. cerevisiae strain, in wine fermentations. Furthermore, the expression of a key gene related to mannoproteins biosynthesis, PMT1, increased in the S. cerevisiae×S. kudriavzevii hybrid. We showed that artificially constructed S. cerevisiae×S. kudriavzevii hybrids also increased the levels of mannoproteins. This work demonstrates that either natural or artificial S. cerevisiae×S. kudriavzevii hybrids present mannoprotein overproducing capacity under winemaking conditions, a desirable physiological feature for this industry. These results suggest that genome interaction in hybrids generates a physiological environment that enhances the release of mannoproteins. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. 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.

  15. Genome-wide transcription survey on flavour production in Saccharomyces cerevisiae

    NARCIS (Netherlands)

    Schoondermark-Stolk, Sung A.; Jansen, Michael; Verkleij, Arie J.; Verrips, C. Theo; Euverink, Gert-Jan W.; Dijkhuizen, Lubbert; Boonstra, Johannes

    2006-01-01

    The yeast Saccharomyces cerevisiae is widely used as aroma producer in the preparation of fermented foods and beverages. During food fermentations, secondary metabolites like 3-methyl-1-butanol, 4-methyl-2-oxopentanoate, 3-methyl-2-oxobutanoate and 3-methylbutyrate emerge. These four compounds have

  16. 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,

  17. The Aging Clock and Circadian Control of Metabolism and Genome Stability

    Directory of Open Access Journals (Sweden)

    Victoria P. Belancio

    2015-01-01

    Full Text Available It is widely accepted that aging is characterized by a gradual decline in the efficiency and accuracy of biological processes, leading to deterioration of physiological functions and development of age-associated diseases. Age-dependent accumulation of genomic instability and development of metabolic syndrome are well-recognized components of the aging phenotype, both of which have been extensively studied. Existing findings strongly support the view that the integrity of the cellular genome and metabolic function can be influenced by light at night (LAN and associated suppression of circadian melatonin production. While LAN is reported to accelerate aging by promoting age-associated carcinogenesis in several animal models, the specific molecular mechanism(s of its action are not fully understood. Here, we review literature supporting a connection between LAN-induced central circadian disruption of peripheral circadian rhythms and clock function, LINE-1 retrotransposon-associated genomic instability, metabolic deregulation, and aging. We propose that aging is a progressive decline in the stability, continuity and synchronization of multi-frequency oscillations in biological processes to a temporally disorganized state. By extension, healthy aging is the ability to maintain the most consistent, stable and entrainable rhythmicity and coordination of these oscillations, at the molecular, cellular, and systemic levels.

  18. 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.

  19. Genome, secretome and glucose transport highlight unique features of the protein production host Pichia pastoris

    Directory of Open Access Journals (Sweden)

    Mattanovich Diethard

    2009-06-01

    Full Text Available Abstract Background Pichia pastoris is widely used as a production platform for heterologous proteins and model organism for organelle proliferation. Without a published genome sequence available, strain and process development relied mainly on analogies to other, well studied yeasts like Saccharomyces cerevisiae. Results To investigate specific features of growth and protein secretion, we have sequenced the 9.4 Mb genome of the type strain DSMZ 70382 and analyzed the secretome and the sugar transporters. The computationally predicted secretome consists of 88 ORFs. When grown on glucose, only 20 proteins were actually secreted at detectable levels. These data highlight one major feature of P. pastoris, namely the low contamination of heterologous proteins with host cell protein, when applying glucose based expression systems. Putative sugar transporters were identified and compared to those of related yeast species. The genome comprises 2 homologs to S. cerevisiae low affinity transporters and 2 to high affinity transporters of other Crabtree negative yeasts. Contrary to other yeasts, P. pastoris possesses 4 H+/glycerol transporters. Conclusion This work highlights significant advantages of using the P. pastoris system with glucose based expression and fermentation strategies. As only few proteins and no proteases are actually secreted on glucose, it becomes evident that cell lysis is the relevant cause of proteolytic degradation of secreted proteins. The endowment with hexose transporters, dominantly of the high affinity type, limits glucose uptake rates and thus overflow metabolism as observed in S. cerevisiae. The presence of 4 genes for glycerol transporters explains the high specific growth rates on this substrate and underlines the suitability of a glycerol/glucose based fermentation strategy. Furthermore, we present an open access web based genome browser http://www.pichiagenome.org.

  20. 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.

  1. 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,

  2. 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.

  3. 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.

  4. Genomic and metabolic disposition of non-obese type 2 diabetic rats to increased myocardial fatty acid metabolism.

    Directory of Open Access Journals (Sweden)

    Sriram Devanathan

    Full Text Available Lipotoxicity of the heart has been implicated as a leading cause of morbidity in Type 2 Diabetes Mellitus (T2DM. While numerous reports have demonstrated increased myocardial fatty acid (FA utilization in obese T2DM animal models, this diabetic phenotype has yet to be demonstrated in non-obese animal models of T2DM. Therefore, the present study investigates functional, metabolic, and genomic differences in myocardial FA metabolism in non-obese type 2 diabetic rats. The study utilized Goto-Kakizaki (GK rats at the age of 24 weeks. Each rat was imaged with small animal positron emission tomography (PET to estimate myocardial blood flow (MBF and myocardial FA metabolism. Echocardiograms (ECHOs were performed to assess cardiac function. Levels of triglycerides (TG and non-esterified fatty acids (NEFA were measured in both plasma and cardiac tissues. Finally, expression profiles for 168 genes that have been implicated in diabetes and FA metabolism were measured using quantitative PCR (qPCR arrays. GK rats exhibited increased NEFA and TG in both plasma and cardiac tissue. Quantitative PET imaging suggests that GK rats have increased FA metabolism. ECHO data indicates that GK rats have a significant increase in left ventricle mass index (LVMI and decrease in peak early diastolic mitral annular velocity (E' compared to Wistar rats, suggesting structural remodeling and impaired diastolic function. Of the 84 genes in each the diabetes and FA metabolism arrays, 17 genes in the diabetes array and 41 genes in the FA metabolism array were significantly up-regulated in GK rats. Our data suggest that GK rats' exhibit increased genomic disposition to FA and TG metabolism independent of obesity.

  5. 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

  6. 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.

  7. Global mapping of DNA conformational flexibility on Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Giulia Menconi

    2015-04-01

    Full Text Available In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage; however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3'UTR, a region affecting mRNA translation, localization and stability. (TAn repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover; consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TAn repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3'-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in

  8. Global mapping of DNA conformational flexibility on Saccharomyces cerevisiae.

    Science.gov (United States)

    Menconi, Giulia; Bedini, Andrea; Barale, Roberto; Sbrana, Isabella

    2015-04-01

    In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage; however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3'UTR, a region affecting mRNA translation, localization and stability. (TA)n repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE) signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover; consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TA)n repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3'-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in genomes and a

  9. Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D

    DEFF Research Database (Denmark)

    Jenjaroenpun, Piroon; Wongsurawat, Thidathip; Pereira, Rui

    2018-01-01

    Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of secondgeneration sequencing. Saccharomyces cerevisiae strain CEN. PK113-7D, widely used as a model organism and a cell factory, was selected for this study...... to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error...... correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as themitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C...

  10. 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

  11. Multi-scale structural community organisation of the human genome.

    Science.gov (United States)

    Boulos, Rasha E; Tremblay, Nicolas; Arneodo, Alain; Borgnat, Pierre; Audit, Benjamin

    2017-04-11

    Structural interaction frequency matrices between all genome loci are now experimentally achievable thanks to high-throughput chromosome conformation capture technologies. This ensues a new methodological challenge for computational biology which consists in objectively extracting from these data the structural motifs characteristic of genome organisation. We deployed the fast multi-scale community mining algorithm based on spectral graph wavelets to characterise the networks of intra-chromosomal interactions in human cell lines. We observed that there exist structural domains of all sizes up to chromosome length and demonstrated that the set of structural communities forms a hierarchy of chromosome segments. Hence, at all scales, chromosome folding predominantly involves interactions between neighbouring sites rather than the formation of links between distant loci. Multi-scale structural decomposition of human chromosomes provides an original framework to question structural organisation and its relationship to functional regulation across the scales. By construction the proposed methodology is independent of the precise assembly of the reference genome and is thus directly applicable to genomes whose assembly is not fully determined.

  12. 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.

  13. Loss of lager specific genes and subtelomeric regions define two different Saccharomyces cerevisiae lineages for Saccharomyces pastorianus Group I and II strains.

    Science.gov (United States)

    Monerawela, Chandre; James, Tharappel C; Wolfe, Kenneth H; Bond, Ursula

    2015-03-01

    Lager yeasts, Saccharomyces pastorianus, are interspecies hybrids between S. cerevisiae and S. eubayanus and are classified into Group I and Group II clades. The genome of the Group II strain, Weihenstephan 34/70, contains eight so-called 'lager-specific' genes that are located in subtelomeric regions. We evaluated the origins of these genes through bioinformatic and PCR analyses of Saccharomyces genomes. We determined that four are of cerevisiae origin while four originate from S. eubayanus. The Group I yeasts contain all four S. eubayanus genes but individual strains contain only a subset of the cerevisiae genes. We identified S. cerevisiae strains that contain all four cerevisiae 'lager-specific' genes, and distinct patterns of loss of these genes in other strains. Analysis of the subtelomeric regions uncovered patterns of loss in different S. cerevisiae strains. We identify two classes of S. cerevisiae strains: ale yeasts (Foster O) and stout yeasts with patterns of 'lager-specific' genes and subtelomeric regions identical to Group I and II S. pastorianus yeasts, respectively. These findings lead us to propose that Group I and II S. pastorianus strains originate from separate hybridization events involving different S. cerevisiae lineages. Using the combined bioinformatic and PCR data, we describe a potential classification map for industrial yeasts. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

  14. Differential retention of metabolic genes following whole-genome duplication.

    Science.gov (United States)

    Gout, Jean-François; Duret, Laurent; Kahn, Daniel

    2009-05-01

    Classical studies in Metabolic Control Theory have shown that metabolic fluxes usually exhibit little sensitivity to changes in individual enzyme activity, yet remain sensitive to global changes of all enzymes in a pathway. Therefore, little selective pressure is expected on the dosage or expression of individual metabolic genes, yet entire pathways should still be constrained. However, a direct estimate of this selective pressure had not been evaluated. Whole-genome duplications (WGDs) offer a good opportunity to address this question by analyzing the fates of metabolic genes during the massive gene losses that follow. Here, we take advantage of the successive rounds of WGD that occurred in the Paramecium lineage. We show that metabolic genes exhibit different gene retention patterns than nonmetabolic genes. Contrary to what was expected for individual genes, metabolic genes appeared more retained than other genes after the recent WGD, which was best explained by selection for gene expression operating on entire pathways. Metabolic genes also tend to be less retained when present at high copy number before WGD, contrary to other genes that show a positive correlation between gene retention and preduplication copy number. This is rationalized on the basis of the classical concave relationship relating metabolic fluxes with enzyme expression.

  15. Exercise-induced maximum metabolic rate scaled to body mass by ...

    African Journals Online (AJOL)

    Exercise-induced maximum metabolic rate scaled to body mass by the fractal ... rate scaling is that exercise-induced maximum aerobic metabolic rate (MMR) is ... muscle stress limitation, and maximized oxygen delivery and metabolic rates.

  16. 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...

  17. Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, Iman; Palsson, Bernhard Ø

    2003-01-01

    evaluation was solely based on the topological properties of the metabolic network which is based on well-established reaction stoichiometry. No interaction or regulatory information was accounted for in the in silico model. False predictions were analyzed on a case-by-case basis for four possible...... inadequacies of the in silico model: (1) incomplete media composition, (2) substitutable biomass components, (3) incomplete biochemical information, and (4) missing regulation. This analysis eliminated a number of false predictions and suggested a number of experimentally testable hypotheses. A genome...

  18. Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

    Science.gov (United States)

    Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

    2017-12-11

    Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

  19. Increased ethanol accumulation from glucose via reduction of ATP level in a recombinant strain of Saccharomyces cerevisiae overexpressing alkaline phosphatase.

    Science.gov (United States)

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

    2014-05-15

    The production of ethyl alcohol by fermentation represents the largest scale application of Saccharomyces cerevisiae in industrial biotechnology. Increased worldwide demand for fuel bioethanol is anticipated over the next decade and will exceed 200 billion liters from further expansions. Our working hypothesis was that the drop in ATP level in S. cerevisiae cells during alcoholic fermentation should lead to an increase in ethanol production (yield and productivity) with a greater amount of the utilized glucose converted to ethanol. Our approach to achieve this goal is to decrease the intracellular ATP level via increasing the unspecific alkaline phosphatase activity. Intact and truncated versions of the S. cerevisiae PHO8 gene coding for vacuolar or cytosolic forms of alkaline phosphatase were fused with the alcohol dehydrogenase gene (ADH1) promoter. The constructed expression cassettes used for transformation vectors also contained the dominant selective marker kanMX4 and S. cerevisiae δ-sequence to facilitate multicopy integration to the genome. Laboratory and industrial ethanol producing strains BY4742 and AS400 overexpressing vacuolar form of alkaline phosphatase were characterized by a slightly lowered intracellular ATP level and biomass accumulation and by an increase in ethanol productivity (13% and 7%) when compared to the parental strains. The strains expressing truncated cytosolic form of alkaline phosphatase showed a prolonged lag-phase, reduced biomass accumulation and a strong defect in ethanol production. Overexpression of vacuolar alkaline phosphatase leads to an increased ethanol yield in S. cerevisiae.

  20. Combining magnetic sorting of mother cells and fluctuation tests to analyze genome instability during mitotic cell aging in Saccharomyces cerevisiae.

    Science.gov (United States)

    Patterson, Melissa N; Maxwell, Patrick H

    2014-10-16

    Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on

  1. Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

    Science.gov (United States)

    Rzhetsky, A; Gomez, S M

    2001-10-01

    Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

  2. Development of Computational Tools for Metabolic Model Curation, Flux Elucidation and Strain Design

    Energy Technology Data Exchange (ETDEWEB)

    Maranas, Costas D

    2012-05-21

    An overarching goal of the Department of Energy mission is the efficient deployment and engineering of microbial and plant systems to enable biomass conversion in pursuit of high energy density liquid biofuels. This has spurred the pace at which new organisms are sequenced and annotated. This torrent of genomic information has opened the door to understanding metabolism in not just skeletal pathways and a handful of microorganisms but for truly genome-scale reconstructions derived for hundreds of microbes and plants. Understanding and redirecting metabolism is crucial because metabolic fluxes are unique descriptors of cellular physiology that directly assess the current cellular state and quantify the effect of genetic engineering interventions. At the same time, however, trying to keep pace with the rate of genomic data generation has ushered in a number of modeling and computational challenges related to (i) the automated assembly, testing and correction of genome-scale metabolic models, (ii) metabolic flux elucidation using labeled isotopes, and (iii) comprehensive identification of engineering interventions leading to the desired metabolism redirection.

  3. 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.

  4. Genome-level comparisons provide insight into the phylogeny and metabolic diversity of species within the genus Lactococcus.

    Science.gov (United States)

    Yu, Jie; Song, Yuqin; Ren, Yan; Qing, Yanting; Liu, Wenjun; Sun, Zhihong

    2017-11-03

    The genomic diversity of different species within the genus Lactococcus and the relationships between genomic differentiation and environmental factors remain unclear. In this study, type isolates of ten Lactococcus species/subspecies were sequenced to assess their genomic characteristics, metabolic diversity, and phylogenetic relationships. The total genome sizes varied between 1.99 (Lactococcus plantarum) and 2.46 megabases (Mb; L. lactis subsp. lactis), and the G + C content ranged from 34.81 (L. lactis subsp. hordniae) to 39.67% (L. raffinolactis) with an average value of 37.02%. Analysis of genome dynamics indicated that the genus Lactococcus has an open pan-genome, while the core genome size decreased with sequential addition at the genus and species group levels. A phylogenetic dendrogram based on the concatenated amino acid sequences of 643 core genes was largely consistent with the phylogenetic tree obtained by 16S ribosomal RNA (rRNA) genes, but it provided a more robust phylogenetic resolution than the 16S rRNA gene-based analysis. Comparative genomics indicated that species in the genus Lactococcus had high degrees of diversity in genome size, gene content, and carbohydrate metabolism. This may be important for the specific adaptations that allow different Lactococcus species to survive in different environments. These results provide a quantitative basis for understanding the genomic and metabolic diversity within the genus Lactococcus, laying the foundation for future studies on taxonomy and functional genomics.

  5. 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.

  6. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Viranga Tilakaratna

    2017-09-01

    Full Text Available Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae, has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae, including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species.

  7. Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae.

    Science.gov (United States)

    Tilakaratna, Viranga; Bensasson, Douda

    2017-09-07

    Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae , has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae , including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species. Copyright © 2017 Tilakaratna and Bensasson.

  8. 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.

  9. 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...

  10. Genome Sequencing of Streptomyces atratus SCSIOZH16 and Activation Production of Nocardamine via Metabolic Engineering

    Directory of Open Access Journals (Sweden)

    Yan Li

    2018-06-01

    Full Text Available The Actinomycetes are metabolically flexible microorganisms capable of producing a wide range of interesting compounds, including but by no means limited to, siderophores which have high affinity for ferric iron. In this study, we report the complete genome sequence of marine-derived Streptomyces atratus ZH16 and the activation of an embedded siderophore gene cluster via the application of metabolic engineering methods. The S. atratus ZH16 genome reveals that this strain has the potential to produce 26 categories of natural products (NPs barring the ilamycins. Our activation studies revealed S. atratus SCSIO ZH16 to be a promising source of the production of nocardamine-type (desferrioxamine compounds which are important in treating acute iron intoxication and performing ecological remediation. We conclude that metabolic engineering provides a highly effective strategy by which to discover drug-like compounds and new NPs in the genomic era.

  11. 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...

  12. 16th Carbonyl Metabolism Meeting: from enzymology to genomics

    Directory of Open Access Journals (Sweden)

    Maser Edmund

    2012-12-01

    Full Text Available Abstract The 16th International Meeting on the Enzymology and Molecular Biology of Carbonyl Metabolism, Castle of Ploen (Schleswig-Holstein, Germany, July 10–15, 2012, covered all aspects of NAD(P-dependent oxido-reductases that are involved in the general metabolism of xenobiotic and physiological carbonyl compounds. Starting 30 years ago with enzyme purification, structure elucidation and enzyme kinetics, the Carbonyl Society members have meanwhile established internationally recognized enzyme nomenclature systems and now consider aspects of enzyme genomics and enzyme evolution along with their roles in diseases. The 16th international meeting included lectures from international speakers from all over the world.

  13. 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.

  14. Functional genomics of beer-related physiological processes in yeast

    NARCIS (Netherlands)

    Hazelwood, L.A.

    2009-01-01

    Since the release of the entire genome sequence of the S. cerevisiae laboratory strain S288C in 1996, many functional genomics tools have been introduced in fundamental and application-oriented yeast research. In this thesis, the applicability of functional genomics for the improvement of yeast in

  15. 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.

  16. Draft genome sequence of Micrococcus luteus strain O'Kane implicates metabolic versatility and the potential to degrade polyhydroxybutyrates.

    Science.gov (United States)

    Hanafy, Radwa A; Couger, M B; Baker, Kristina; Murphy, Chelsea; O'Kane, Shannon D; Budd, Connie; French, Donald P; Hoff, Wouter D; Youssef, Noha

    2016-09-01

    Micrococcus luteus is a predominant member of skin microbiome. We here report on the genomic analysis of Micrococcus luteus strain O'Kane that was isolated from an elevator. The partial genome assembly of Micrococcus luteus strain O'Kane is 2.5 Mb with 2256 protein-coding genes and 62 RNA genes. Genomic analysis revealed metabolic versatility with genes involved in the metabolism and transport of glucose, galactose, fructose, mannose, alanine, aspartate, asparagine, glutamate, glutamine, glycine, serine, cysteine, methionine, arginine, proline, histidine, phenylalanine, and fatty acids. Genomic comparison to other M. luteus representatives identified the potential to degrade polyhydroxybutyrates, as well as several antibiotic resistance genes absent from other genomes.

  17. Saccharomyces cerevisiae Hrq1 requires a long 3'-tailed DNA substrate for helicase activity.

    Science.gov (United States)

    Kwon, Sung-Hun; Choi, Do-Hee; Lee, Rina; Bae, Sung-Ho

    2012-10-26

    RecQ helicases are well conserved proteins from bacteria to human and function in various DNA metabolism for maintenance of genome stability. Five RecQ helicases are found in humans, whereas only one RecQ helicase has been described in lower eukaryotes. However, recent studies predicted the presence of a second RecQ helicase, Hrq1, in fungal genomes and verified it as a functional gene in fission yeast. Here we show that 3'-5' helicase activity is intrinsically associated with Hrq1 of Saccharomyces cerevisiae. We also determined several biochemical properties of Hrq1 helicase distinguishable from those of other RecQ helicase members. Hrq1 is able to unwind relatively long duplex DNA up to 120-bp and is significantly stimulated by a preexisting fork structure. Further, the most striking feature of Hrq1 is its absolute requirement for a long 3'-tail (⩾70-nt) for efficient unwinding of duplex DNA. We also found that Hrq1 has potent DNA strand annealing activity. Our results indicate that Hrq1 has vigorous helicase activity that deserves further characterization to expand our understanding of RecQ helicases. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. 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.

  19. 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.

  20. Cloning, production, and purification of proteins for a medium-scale structural genomics project.

    Science.gov (United States)

    Quevillon-Cheruel, Sophie; Collinet, Bruno; Trésaugues, Lionel; Minard, Philippe; Henckes, Gilles; Aufrère, Robert; Blondeau, Karine; Zhou, Cong-Zhao; Liger, Dominique; Bettache, Nabila; Poupon, Anne; Aboulfath, Ilham; Leulliot, Nicolas; Janin, Joël; van Tilbeurgh, Herman

    2007-01-01

    The South-Paris Yeast Structural Genomics Pilot Project (http://www.genomics.eu.org) aims at systematically expressing, purifying, and determining the three-dimensional structures of Saccharomyces cerevisiae proteins. We have already cloned 240 yeast open reading frames in the Escherichia coli pET system. Eighty-two percent of the targets can be expressed in E. coli, and 61% yield soluble protein. We have currently purified 58 proteins. Twelve X-ray structures have been solved, six are in progress, and six other proteins gave crystals. In this chapter, we present the general experimental flowchart applied for this project. One of the main difficulties encountered in this pilot project was the low solubility of a great number of target proteins. We have developed parallel strategies to recover these proteins from inclusion bodies, including refolding, coexpression with chaperones, and an in vitro expression system. A limited proteolysis protocol, developed to localize flexible regions in proteins that could hinder crystallization, is also described.

  1. 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.

  2. MicrobesOnline: an integrated portal for comparative and functional genomics

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir S.; Joachimiak, Marcin P.; Price, Morgan N.; Bates, John T.; Baumohl, Jason K.; Chivian, Dylan; Friedland, Greg D.; Huang, Katherine H.; Keller, Keith; Novichkov, Pavel S.; Dubchak, Inna L.; Alm, Eric J.; Arkin, Adam P.

    2009-09-17

    Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

  3. MicrobesOnline: an integrated portal for comparative and functional genomics

    Energy Technology Data Exchange (ETDEWEB)

    Dehal, Paramvir; Joachimiak, Marcin; Price, Morgan; Bates, John; Baumohl, Jason; Chivian, Dylan; Friedland, Greg; Huang, Kathleen; Keller, Keith; Novichkov, Pavel; Dubchak, Inna; Alm, Eric; Arkin, Adam

    2011-07-14

    Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

  4. Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa

    NARCIS (Netherlands)

    Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond K.; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura M.; Hinney, Anke; Daly, Mark J.; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M.; Adan, RAH

    2017-01-01

    Objective: The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Method: Following uniformquality control and imputation procedures using the 1000 Genomes Project (phase 3) in

  5. Significant locus and metabolic genetic correlations revealed in genome-wide association study of anorexia nervosa

    NARCIS (Netherlands)

    Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura; Hinney, Anke; Daly, Mark; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M; Kas, Martinus J.H.

    2017-01-01

    OBJECTIVE: The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. METHOD: Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3)

  6. Systems Biology for Mapping Genotype-Phenotype Relations in Yeast

    KAUST Repository

    Nielsen, Jens

    2016-01-25

    The yeast Saccharomyces cerevisiae is widely used for production of fuels, chemicals, pharmaceuticals and materials. Through metabolic engineering of this yeast a number of novel new industrial processes have been developed over the last 10 years. Besides its wide industrial use, S. cerevisiae serves as an eukaryal model organism, and many systems biology tools have therefore been developed for this organism. Among these genome-scale metabolic models have shown to be most successful as they easy integrate with omics data and at the same time have been shown to have excellent predictive power. Despite our extensive knowledge of yeast metabolism and its regulation we are still facing challenges when we want to engineer complex traits, such as improved tolerance to toxic metabolites like butanol and elevated temperatures or when we want to engineer the highly complex protein secretory pathway. In this presentation it will be demonstrated how we can combine directed evolution with systems biology analysis to identify novel targets for rational design-build-test of yeast strains that have improved phenotypic properties. In this lecture an overview of systems biology of yeast will be presented together with examples of how genome-scale metabolic modeling can be used for prediction of cellular growth at different conditions. Examples will also be given on how adaptive laboratory evolution can be used for identifying targets for improving tolerance towards butanol, increased temperature and low pH and for improving secretion of heterologous proteins.

  7. 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

  8. Insights on the evolution of metabolic networks of unicellular translationally biased organisms from transcriptomic data and sequence analysis.

    Science.gov (United States)

    Carbone, Alessandra; Madden, Richard

    2005-10-01

    Codon bias is related to metabolic functions in translationally biased organisms, and two facts are argued about. First, genes with high codon bias describe in meaningful ways the metabolic characteristics of the organism; important metabolic pathways corresponding to crucial characteristics of the lifestyle of an organism, such as photosynthesis, nitrification, anaerobic versus aerobic respiration, sulfate reduction, methanogenesis, and others, happen to involve especially biased genes. Second, gene transcriptional levels of sets of experiments representing a significant variation of biological conditions strikingly confirm, in the case of Saccharomyces cerevisiae, that metabolic preferences are detectable by purely statistical analysis: the high metabolic activity of yeast during fermentation is encoded in the high bias of enzymes involved in the associated pathways, suggesting that this genome was affected by a strong evolutionary pressure that favored a predominantly fermentative metabolism of yeast in the wild. The ensemble of metabolic pathways involving enzymes with high codon bias is rather well defined and remains consistent across many species, even those that have not been considered as translationally biased, such as Helicobacter pylori, for instance, reveal some weak form of translational bias for this genome. We provide numerical evidence, supported by experimental data, of these facts and conclude that the metabolic networks of translationally biased genomes, observable today as projections of eons of evolutionary pressure, can be analyzed numerically and predictions of the role of specific pathways during evolution can be derived. The new concepts of Comparative Pathway Index, used to compare organisms with respect to their metabolic networks, and Evolutionary Pathway Index, used to detect evolutionarily meaningful bias in the genetic code from transcriptional data, are introduced.

  9. 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.

  10. Draft genome sequence of Micrococcus luteus strain O'Kane implicates metabolic versatility and the potential to degrade polyhydroxybutyrates

    Directory of Open Access Journals (Sweden)

    Radwa A. Hanafy

    2016-09-01

    Full Text Available Micrococcus luteus is a predominant member of skin microbiome. We here report on the genomic analysis of Micrococcus luteus strain O'Kane that was isolated from an elevator. The partial genome assembly of Micrococcus luteus strain O'Kane is 2.5 Mb with 2256 protein-coding genes and 62 RNA genes. Genomic analysis revealed metabolic versatility with genes involved in the metabolism and transport of glucose, galactose, fructose, mannose, alanine, aspartate, asparagine, glutamate, glutamine, glycine, serine, cysteine, methionine, arginine, proline, histidine, phenylalanine, and fatty acids. Genomic comparison to other M. luteus representatives identified the potential to degrade polyhydroxybutyrates, as well as several antibiotic resistance genes absent from other genomes.

  11. 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...

  12. A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.

    Science.gov (United States)

    Mih, Nathan; Brunk, Elizabeth; Bordbar, Aarash; Palsson, Bernhard O

    2016-07-01

    Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.

  13. Jatropha curcas, a biofuel crop: functional genomics for understanding metabolic pathways and genetic improvement.

    Science.gov (United States)

    Maghuly, Fatemeh; Laimer, Margit

    2013-10-01

    Jatropha curcas is currently attracting much attention as an oilseed crop for biofuel, as Jatropha can grow under climate and soil conditions that are unsuitable for food production. However, little is known about Jatropha, and there are a number of challenges to be overcome. In fact, Jatropha has not really been domesticated; most of the Jatropha accessions are toxic, which renders the seedcake unsuitable for use as animal feed. The seeds of Jatropha contain high levels of polyunsaturated fatty acids, which negatively impact the biofuel quality. Fruiting of Jatropha is fairly continuous, thus increasing costs of harvesting. Therefore, before starting any improvement program using conventional or molecular breeding techniques, understanding gene function and the genome scale of Jatropha are prerequisites. This review presents currently available and relevant information on the latest technologies (genomics, transcriptomics, proteomics and metabolomics) to decipher important metabolic pathways within Jatropha, such as oil and toxin synthesis. Further, it discusses future directions for biotechnological approaches in Jatropha breeding and improvement. © 2013 The Authors. Biotechnology Journal published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. 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...

  15. 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...

  16. 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.

  17. Analysing human genomes at different scales

    DEFF Research Database (Denmark)

    Liu, Siyang

    The thriving of the Next-Generation sequencing (NGS) technologies in the past decade has dramatically revolutionized the field of human genetics. We are experiencing a wave of several large-scale whole genome sequencing studies of humans in the world. Those studies vary greatly regarding cohort...... will be reflected by the analysis of real data. This thesis covers studies in two human genome sequencing projects that distinctly differ in terms of studied population, sample size and sequencing depth. In the first project, we sequenced 150 Danish individuals from 50 trio families to 78x coverage....... The sophisticated experimental design enables high-quality de novo assembly of the genomes and provides a good opportunity for mapping the structural variations in the human population. We developed the AsmVar approach to discover, genotype and characterize the structural variations from the assemblies. Our...

  18. 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.

  19. 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...

  20. Targeting population heterogeneity in Saccharomyces cerevisiae batch fermentation for optimal cell factories

    DEFF Research Database (Denmark)

    Heins, Anna-Lena; Lencastre Fernandes, Rita; Lundin, L.

    )). Significant gradients of e.g. dissolved oxygen, substrates, and pH are typically observed in many industrial scale fermentation processes. Consequently, the microbial cells experience rapid changes in environmental conditions as they circulate throughout the reactor, which might pose stress on the cells...... and affect their metabolism and consequently affect the heterogeneity level of the population. To further investigate these phenomena and gain a deeper understanding of population heterogeneity, Saccharomyces cerevisiae growth reporter strains based on the expression of green fluorescent protein (GFP) were...... environmental factors on heterogeneity level and amount of living cells. A highly dynamic behavior with regard to subpopulation distribution during the different growth stages was seen for the batch cultivations. Moreover, it could be demonstrated that the glucose concentration had a clear influence...

  1. Rational and evolutionary engineering approaches uncover a small set of genetic changes efficient for rapid xylose fermentation in Saccharomyces cerevisiae.

    Directory of Open Access Journals (Sweden)

    Soo Rin Kim

    Full Text Available Economic bioconversion of plant cell wall hydrolysates into fuels and chemicals has been hampered mainly due to the inability of microorganisms to efficiently co-ferment pentose and hexose sugars, especially glucose and xylose, which are the most abundant sugars in cellulosic hydrolysates. Saccharomyces cerevisiae cannot metabolize xylose due to a lack of xylose-metabolizing enzymes. We developed a rapid and efficient xylose-fermenting S. cerevisiae through rational and inverse metabolic engineering strategies, comprising the optimization of a heterologous xylose-assimilating pathway and evolutionary engineering. Strong and balanced expression levels of the XYL1, XYL2, and XYL3 genes constituting the xylose-assimilating pathway increased ethanol yields and the xylose consumption rates from a mixture of glucose and xylose with little xylitol accumulation. The engineered strain, however, still exhibited a long lag time when metabolizing xylose above 10 g/l as a sole carbon source, defined here as xylose toxicity. Through serial-subcultures on xylose, we isolated evolved strains which exhibited a shorter lag time and improved xylose-fermenting capabilities than the parental strain. Genome sequencing of the evolved strains revealed that mutations in PHO13 causing loss of the Pho13p function are associated with the improved phenotypes of the evolved strains. Crude extracts of a PHO13-overexpressing strain showed a higher phosphatase activity on xylulose-5-phosphate (X-5-P, suggesting that the dephosphorylation of X-5-P by Pho13p might generate a futile cycle with xylulokinase overexpression. While xylose consumption rates by the evolved strains improved substantially as compared to the parental strain, xylose metabolism was interrupted by accumulated acetate. Deletion of ALD6 coding for acetaldehyde dehydrogenase not only prevented acetate accumulation, but also enabled complete and efficient fermentation of xylose as well as a mixture of glucose and

  2. Localization of nuclear retained mRNAs in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Thomsen, Rune; Libri, Domenico; Boulay, Jocelyne

    2003-01-01

    site of transcription, and known S. cerevisiae nuclear structures such as the nucleolus and the nucleolar body. Our results show that retained SSA4 RNA localizes to an area in close proximity to the SSA4 locus. On deletion of Rrp6p and release from the genomic locus, heat shock mRNAs produced...

  3. 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.

  4. 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.

  5. Whole-genome sequencing of a laboratory-evolved yeast strain

    Directory of Open Access Journals (Sweden)

    Dunham Maitreya J

    2010-02-01

    Full Text Available Abstract Background Experimental evolution of microbial populations provides a unique opportunity to study evolutionary adaptation in response to controlled selective pressures. However, until recently it has been difficult to identify the precise genetic changes underlying adaptation at a genome-wide scale. New DNA sequencing technologies now allow the genome of parental and evolved strains of microorganisms to be rapidly determined. Results We sequenced >93.5% of the genome of a laboratory-evolved strain of the yeast Saccharomyces cerevisiae and its ancestor at >28× depth. Both single nucleotide polymorphisms and copy number amplifications were found, with specific gains over array-based methodologies previously used to analyze these genomes. Applying a segmentation algorithm to quantify structural changes, we determined the approximate genomic boundaries of a 5× gene amplification. These boundaries guided the recovery of breakpoint sequences, which provide insights into the nature of a complex genomic rearrangement. Conclusions This study suggests that whole-genome sequencing can provide a rapid approach to uncover the genetic basis of evolutionary adaptations, with further applications in the study of laboratory selections and mutagenesis screens. In addition, we show how single-end, short read sequencing data can provide detailed information about structural rearrangements, and generate predictions about the genomic features and processes that underlie genome plasticity.

  6. Xylose-fermenting Pichia stipitis by genome shuffling for improved ethanol production.

    Science.gov (United States)

    Shi, Jun; Zhang, Min; Zhang, Libin; Wang, Pin; Jiang, Li; Deng, Huiping

    2014-03-01

    Xylose fermentation is necessary for the bioconversion of lignocellulose to ethanol as fuel, but wild-type Saccharomyces cerevisiae strains cannot fully metabolize xylose. Several efforts have been made to obtain microbial strains with enhanced xylose fermentation. However, xylose fermentation remains a serious challenge because of the complexity of lignocellulosic biomass hydrolysates. Genome shuffling has been widely used for the rapid improvement of industrially important microbial strains. After two rounds of genome shuffling, a genetically stable, high-ethanol-producing strain was obtained. Designated as TJ2-3, this strain could ferment xylose and produce 1.5 times more ethanol than wild-type Pichia stipitis after fermentation for 96 h. The acridine orange and propidium iodide uptake assays showed that the maintenance of yeast cell membrane integrity is important for ethanol fermentation. This study highlights the importance of genome shuffling in P. stipitis as an effective method for enhancing the productivity of industrial strains. © 2013 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

  7. 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

  8. Improved xylose and arabinose utilization by an industrial recombinant Saccharomyces cerevisiae strain using evolutionary engineering

    DEFF Research Database (Denmark)

    Sanchez, R.G.; Karhumaa, Kaisa; Fonseca, C.

    2010-01-01

    Background: Cost-effective fermentation of lignocellulosic hydrolysate to ethanol by Saccharomyces cerevisiae requires efficient mixed sugar utilization. Notably, the rate and yield of xylose and arabinose co-fermentation to ethanol must be enhanced. Results: Evolutionary engineering was used...... to improve the simultaneous conversion of xylose and arabinose to ethanol in a recombinant industrial Saccharomyces cerevisiae strain carrying the heterologous genes for xylose and arabinose utilization pathways integrated in the genome. The evolved strain TMB3130 displayed an increased consumption rate...... of our knowledge, this is the first report that characterizes the molecular mechanisms for improved mixed-pentose utilization obtained by evolutionary engineering of a recombinant S. cerevisiae strain. Increased transport of pentoses and increased activities of xylose converting enzymes contributed...

  9. Genome-Based Construction of the Metabolic Pathways of Orientia tsutsugamushi and Comparative Analysis within the Rickettsiales Order

    Directory of Open Access Journals (Sweden)

    Chan-Ki Min

    2008-01-01

    Full Text Available Orientia tsutsugamushi, the causative agent of scrub typhus, is an obligate intracellular bacterium that belongs to the order of Rickettsiales. Recently, we have reported that O. tsutsugamushi has a unique genomic structure, consisting of highly repetitive sequences, and suggested that it may provide valuable insight into the evolution of intracellular bacteria. Here, we have used genomic information to construct the major metabolic pathways of O. tsutsugamushi and performed a comparative analysis of the metabolic genes and pathways of O. tsutsugamushi with other members of the Rickettsiales order. While O. tsutsugamushi has the largest genome among the members of this order, mainly due to the presence of repeated sequences, its metabolic pathways have been highly streamlined. Overall, the metabolic pathways of O. tsutsugamushi were similar to Rickettsia but there were notable differences in several pathways including carbohydrate metabolism, the TCA cycle, and the synthesis of cell wall components as well as in the transport systems. Our results will provide a useful guide to the postgenomic analysis of O. tsutsugamushi and lead to a better understanding of the virulence and physiology of this intracellular pathogen.

  10. 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.)

  11. 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.

  12. Genome-Wide Fine-Scale Recombination Rate Variation in Drosophila melanogaster

    Science.gov (United States)

    Song, Yun S.

    2012-01-01

    Estimating fine-scale recombination maps of Drosophila from population genomic data is a challenging problem, in particular because of the high background recombination rate. In this paper, a new computational method is developed to address this challenge. Through an extensive simulation study, it is demonstrated that the method allows more accurate inference, and exhibits greater robustness to the effects of natural selection and noise, compared to a well-used previous method developed for studying fine-scale recombination rate variation in the human genome. As an application, a genome-wide analysis of genetic variation data is performed for two Drosophila melanogaster populations, one from North America (Raleigh, USA) and the other from Africa (Gikongoro, Rwanda). It is shown that fine-scale recombination rate variation is widespread throughout the D. melanogaster genome, across all chromosomes and in both populations. At the fine-scale, a conservative, systematic search for evidence of recombination hotspots suggests the existence of a handful of putative hotspots each with at least a tenfold increase in intensity over the background rate. A wavelet analysis is carried out to compare the estimated recombination maps in the two populations and to quantify the extent to which recombination rates are conserved. In general, similarity is observed at very broad scales, but substantial differences are seen at fine scales. The average recombination rate of the X chromosome appears to be higher than that of the autosomes in both populations, and this pattern is much more pronounced in the African population than the North American population. The correlation between various genomic features—including recombination rates, diversity, divergence, GC content, gene content, and sequence quality—is examined using the wavelet analysis, and it is shown that the most notable difference between D. melanogaster and humans is in the correlation between recombination and

  13. 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.

  14. Genome resolved analysis of a premature infant gut microbial community reveals a Varibaculum cambriense genome and a shift towards fermentation-based metabolism during the third week of life.

    Science.gov (United States)

    Brown, Christopher T; Sharon, Itai; Thomas, Brian C; Castelle, Cindy J; Morowitz, Michael J; Banfield, Jillian F

    2013-12-17

    The premature infant gut has low individual but high inter-individual microbial diversity compared with adults. Based on prior 16S rRNA gene surveys, many species from this environment are expected to be similar to those previously detected in the human microbiota. However, the level of genomic novelty and metabolic variation of strains found in the infant gut remains relatively unexplored. To study the stability and function of early microbial colonizers of the premature infant gut, nine stool samples were taken during the third week of life of a premature male infant delivered via Caesarean section. Metagenomic sequences were assembled and binned into near-complete and partial genomes, enabling strain-level genomic analysis of the microbial community.We reconstructed eleven near-complete and six partial bacterial genomes representative of the key members of the microbial community. Twelve of these genomes share >90% putative ortholog amino acid identity with reference genomes. Manual curation of the assembly of one particularly novel genome resulted in the first essentially complete genome sequence (in three pieces, the order of which could not be determined due to a repeat) for Varibaculum cambriense (strain Dora), a medically relevant species that has been implicated in abscess formation.During the period studied, the microbial community undergoes a compositional shift, in which obligate anaerobes (fermenters) overtake Escherichia coli as the most abundant species. Other species remain stable, probably due to their ability to either respire anaerobically or grow by fermentation, and their capacity to tolerate fluctuating levels of oxygen. Metabolic predictions for V. cambriense suggest that, like other members of the microbial community, this organism is able to process various sugar substrates and make use of multiple different electron acceptors during anaerobic respiration. Genome comparisons within the family Actinomycetaceae reveal important differences

  15. 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

  16. 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.

  17. 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.

  18. 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

  19. IdentiCS – Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence

    Directory of Open Access Journals (Sweden)

    Zeng An-Ping

    2004-08-01

    Full Text Available Abstract Background A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence. Results In this work a fast method is proposed to use unannotated genome sequence for predicting CDSs and for an in silico reconstruction of metabolic networks. Instead of using predicted genes or CDSs to query public databases, entries from public DNA or protein databases are used as queries to search a local database of the unannotated genome sequence to predict CDSs. Functions are assigned to the predicted CDSs simultaneously. The well-annotated genome of Salmonella typhimurium LT2 is used as an example to demonstrate the applicability of the method. 97.7% of the CDSs in the original annotation are correctly identified. The use of SWISS-PROT-TrEMBL databases resulted in an identification of 98.9% of CDSs that have EC-numbers in the published annotation. Furthermore, two versions of sequences of the bacterium Klebsiella pneumoniae with different genome coverage (3.9 and 7.9 fold, respectively are examined. The results suggest that a 3.9-fold coverage of the bacterial genome could be sufficiently used for the in silico reconstruction of the metabolic network. Compared to other gene finding methods such as CRITICA our method is more suitable for exploiting sequences of low genome coverage. Based on the new method, a program called IdentiCS (Identification of Coding Sequences from Unfinished Genome Sequences is delivered that combines the identification of CDSs with the reconstruction, comparison and visualization of metabolic networks (free to download

  20. 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

  1. 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.

  2. Current View on Phytoplasma Genomes and Encoded Metabolism

    Directory of Open Access Journals (Sweden)

    Michael Kube

    2012-01-01

    Full Text Available Phytoplasmas are specialised bacteria that are obligate parasites of plant phloem tissue and insects. These bacteria have resisted all attempts of cell-free cultivation. Genome research is of particular importance to analyse the genetic endowment of such bacteria. Here we review the gene content of the four completely sequenced ‘Candidatus Phytoplasma’ genomes that include those of ‘Ca. P. asteris’ strains OY-M and AY-WB, ‘Ca. P. australiense,’ and ‘Ca. P. mali’. These genomes are characterized by chromosome condensation resulting in sizes below 900 kb and a G + C content of less than 28%. Evolutionary adaption of the phytoplasmas to nutrient-rich environments resulted in losses of genetic modules and increased host dependency highlighted by the transport systems and limited metabolic repertoire. On the other hand, duplication and integration events enlarged the chromosomes and contribute to genome instability. Present differences in the content of membrane and secreted proteins reflect the host adaptation in the phytoplasma strains. General differences are obvious between different phylogenetic subgroups. ‘Ca. P. mali’ is separated from the other strains by its deviating chromosome organization, the genetic repertoire for recombination and excision repair of nucleotides or the loss of the complete energy-yielding part of the glycolysis. Apart from these differences, comparative analysis exemplified that all four phytoplasmas are likely to encode an alternative pathway to generate pyruvate and ATP.

  3. 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.

  4. Genome-enabled Modeling of Microbial Biogeochemistry using a Trait-based Approach. Does Increasing Metabolic Complexity Increase Predictive Capabilities?

    Science.gov (United States)

    King, E.; Karaoz, U.; Molins, S.; Bouskill, N.; Anantharaman, K.; Beller, H. R.; Banfield, J. F.; Steefel, C. I.; Brodie, E.

    2015-12-01

    The biogeochemical functioning of ecosystems is shaped in part by genomic information stored in the subsurface microbiome. Cultivation-independent approaches allow us to extract this information through reconstruction of thousands of genomes from a microbial community. Analysis of these genomes, in turn, gives an indication of the organisms present and their functional roles. However, metagenomic analyses can currently deliver thousands of different genomes that range in abundance/importance, requiring the identification and assimilation of key physiologies and metabolisms to be represented as traits for successful simulation of subsurface processes. Here we focus on incorporating -omics information into BioCrunch, a genome-informed trait-based model that represents the diversity of microbial functional processes within a reactive transport framework. This approach models the rate of nutrient uptake and the thermodynamics of coupled electron donors and acceptors for a range of microbial metabolisms including heterotrophs and chemolithotrophs. Metabolism of exogenous substrates fuels catabolic and anabolic processes, with the proportion of energy used for cellular maintenance, respiration, biomass development, and enzyme production based upon dynamic intracellular and environmental conditions. This internal resource partitioning represents a trade-off against biomass formation and results in microbial community emergence across a fitness landscape. Biocrunch was used here in simulations that included organisms and metabolic pathways derived from a dataset of ~1200 non-redundant genomes reflecting a microbial community in a floodplain aquifer. Metagenomic data was directly used to parameterize trait values related to growth and to identify trait linkages associated with respiration, fermentation, and key enzymatic functions such as plant polymer degradation. Simulations spanned a range of metabolic complexities and highlight benefits originating from simulations

  5. A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism.

    Directory of Open Access Journals (Sweden)

    Nathan Mih

    2016-07-01

    Full Text Available Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants in complex with their respective native metabolites or drug molecules. We find that changes in a protein's structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism.

  6. The genome of wine yeast Dekkera bruxellensis provides a tool to explore its food-related properties

    Energy Technology Data Exchange (ETDEWEB)

    Piskur, Jure; Ling, Zhihao; Marcet-Houben, Marina; Ishchuk, Olena P.; Aerts, Andrea; LaButti, Kurt; Copeland, Alex; Lindquist, Erika; Barry, Kerrie; Compagno, Concetta; Bisson, Linda; Grigoriev, Igor V.; Gabaldon, Toni; Phister, Trevor

    2012-03-14

    The yeast Dekkera/Brettanomyces bruxellensis can cause enormous economic losses in wine industry due to production of phenolic off-flavor compounds. D. bruxellensis is a distant relative of baker's yeast Saccharomyces cerevisiae. Nevertheless, these two yeasts are often found in the same habitats and share several food-related traits, such as production of high ethanol levels and ability to grow without oxygen. In some food products, like lambic beer, D. bruxellensis can importantly contribute to flavor development. We determined the 13.4 Mb genome sequence of the D. bruxellensis strain Y879 (CBS2499) and deduced the genetic background of several ?food-relevant? properties and evolutionary history of this yeast. Surprisingly, we find that this yeast is phylogenetically distant to other food-related yeasts and most related to Pichia (Komagataella) pastoris, which is an aerobic poor ethanol producer. We further show that the D. bruxellensis genome does not contain an excess of lineage specific duplicated genes nor a horizontally transferred URA1 gene, two crucial events that promoted the evolution of the food relevant traits in the S. cerevisiae lineage. However, D. bruxellensis has several independently duplicated ADH and ADH-like genes, which are likely responsible for metabolism of alcohols, including ethanol, and also a range of aromatic compounds.

  7. Maintaining replication origins in the face of genomic change.

    Science.gov (United States)

    Di Rienzi, Sara C; Lindstrom, Kimberly C; Mann, Tobias; Noble, William S; Raghuraman, M K; Brewer, Bonita J

    2012-10-01

    Origins of replication present a paradox to evolutionary biologists. As a collection, they are absolutely essential genomic features, but individually are highly redundant and nonessential. It is therefore difficult to predict to what extent and in what regard origins are conserved over evolutionary time. Here, through a comparative genomic analysis of replication origins and chromosomal replication patterns in the budding yeasts Saccharomyces cerevisiae and Lachancea waltii, we assess to what extent replication origins survived genomic change produced from 150 million years of evolution. We find that L. waltii origins exhibit a core consensus sequence and nucleosome occupancy pattern highly similar to those of S. cerevisiae origins. We further observe that the overall progression of chromosomal replication is similar between L. waltii and S. cerevisiae. Nevertheless, few origins show evidence of being conserved in location between the two species. Among the conserved origins are those surrounding centromeres and adjacent to histone genes, suggesting that proximity to an origin may be important for their regulation. We conclude that, over evolutionary time, origins maintain sequence, structure, and regulation, but are continually being created and destroyed, with the result that their locations are generally not conserved.

  8. Genome-Enabled Modeling of Biogeochemical Processes Predicts Metabolic Dependencies that Connect the Relative Fitness of Microbial Functional Guilds

    Science.gov (United States)

    Brodie, E.; King, E.; Molins, S.; Karaoz, U.; Steefel, C. I.; Banfield, J. F.; Beller, H. R.; Anantharaman, K.; Ligocki, T. J.; Trebotich, D.

    2015-12-01

    Pore-scale processes mediated by microorganisms underlie a range of critical ecosystem services, regulating carbon stability, nutrient flux, and the purification of water. Advances in cultivation-independent approaches now provide us with the ability to reconstruct thousands of genomes from microbial populations from which functional roles may be assigned. With this capability to reveal microbial metabolic potential, the next step is to put these microbes back where they belong to interact with their natural environment, i.e. the pore scale. At this scale, microorganisms communicate, cooperate and compete across their fitness landscapes with communities emerging that feedback on the physical and chemical properties of their environment, ultimately altering the fitness landscape and selecting for new microbial communities with new properties and so on. We have developed a trait-based model of microbial activity that simulates coupled functional guilds that are parameterized with unique combinations of traits that govern fitness under dynamic conditions. Using a reactive transport framework, we simulate the thermodynamics of coupled electron donor-acceptor reactions to predict energy available for cellular maintenance, respiration, biomass development, and enzyme production. From metagenomics, we directly estimate some trait values related to growth and identify the linkage of key traits associated with respiration and fermentation, macromolecule depolymerizing enzymes, and other key functions such as nitrogen fixation. Our simulations were carried out to explore abiotic controls on community emergence such as seasonally fluctuating water table regimes across floodplain organic matter hotspots. Simulations and metagenomic/metatranscriptomic observations highlighted the many dependencies connecting the relative fitness of functional guilds and the importance of chemolithoautotrophic lifestyles. Using an X-Ray microCT-derived soil microaggregate physical model combined

  9. 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.

  10. Effects of Contingency versus Constraints on the Body-Mass Scaling of Metabolic Rate

    Directory of Open Access Journals (Sweden)

    Douglas S. Glazier

    2018-01-01

    Full Text Available I illustrate the effects of both contingency and constraints on the body-mass scaling of metabolic rate by analyzing the significantly different influences of ambient temperature (Ta on metabolic scaling in ectothermic versus endothermic animals. Interspecific comparisons show that increasing Ta results in decreasing metabolic scaling slopes in ectotherms, but increasing slopes in endotherms, a pattern uniquely predicted by the metabolic-level boundaries hypothesis, as amended to include effects of the scaling of thermal conductance in endotherms outside their thermoneutral zone. No other published theoretical model explicitly predicts this striking variation in metabolic scaling, which I explain in terms of contingent effects of Ta and thermoregulatory strategy in the context of physical and geometric constraints related to the scaling of surface area, volume, and heat flow across surfaces. My analysis shows that theoretical models focused on an ideal 3/4-power law, as explained by a single universally applicable mechanism, are clearly inadequate for explaining the diversity and environmental sensitivity of metabolic scaling. An important challenge is to develop a theory of metabolic scaling that recognizes the contingent effects of multiple mechanisms that are modulated by several extrinsic and intrinsic factors within specified constraints.

  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. Exploring Protein Function Using the Saccharomyces Genome Database.

    Science.gov (United States)

    Wong, Edith D

    2017-01-01

    Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

  13. 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.

  14. 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

  15. Genomic Evidence of Chemotrophic Metabolisms in Deep-Dwelling Chloroflexi Conferred by Ancient Horizontal Gene Transfer Events

    Science.gov (United States)

    Momper, L. M.; Magnabosco, C.; Amend, J.; Osburn, M. R.; Fournier, G. P.

    2017-12-01

    The marine and terrestrial subsurface biospheres represent quite likely the largest reservoirs for life on Earth, directly impacting surface processes and global cycles throughout Earth's history. In the deep subsurface biosphere (DSB) organic carbon and energy are often extremely scarce. However, archaea and bacteria are able to persist in the DSB to at least 3.5 km below surface [1]. Understanding how they persist, and by what metabolisms they subsist, are key questions in this biosphere. To address these questions we investigated 5 global DSB environments: one legacy mine in South Dakota, USA, 3 mines in South Africa and marine fluids circulating beneath the Juan de Fuca Ridge. Boreholes within these mines provided access to fluids buried beneath the earth's surface and sampled depths down to 3.1 km. Geochemical data were collected concomitantly with DNA for metagenomic sequencing. We examined genomes of the ancient and deeply branching Chloroflexi for metabolic capabilities and interrogated the geochemical drivers behind those metabolisms with in situ thermodynamic modeling of reaction energetics. In total, 23 Chloroflexi genomes were identified and analyzed from the 5 subsurface sites. Genes for nitrate reduction (nar) and sulfite reduction (dsr) were found in many of the South Africa Chloroflexi but were absent from genomes collected in South Dakota. Indeed, nitrate reduction was among the most energetically favorable reactions in South African fluids (10-14 kJ cell-1 sec -1 per mol of reactant) and sulfur reduction with Fe2+ or H2 was also exergonic [2]. Conversely, genes for nitrite and nitrous oxide reduction (nrf, nir and nos) were found in genomes collected in South Dakota and Juan de Fuca, but not South Africa. We examined the origin of genes conferring these metabolisms in the Chloroflexi genomes. We discovered evidence for horizontal gene transfer (HGT) for all of these putative metabolisms. Retention of these genes in Chloroflexi lineages indicates

  16. Genome-Wide Analysis of the TORC1 and Osmotic Stress Signaling Network in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Jeremy Worley

    2016-02-01

    Full Text Available The Target of Rapamycin kinase Complex I (TORC1 is a master regulator of cell growth and metabolism in eukaryotes. Studies in yeast and human cells have shown that nitrogen/amino acid starvation signals act through Npr2/Npr3 and the small GTPases Gtr1/Gtr2 (Rags in humans to inhibit TORC1. However, it is unclear how other stress and starvation stimuli inhibit TORC1, and/or act in parallel with the TORC1 pathway, to control cell growth. To help answer these questions, we developed a novel automated pipeline and used it to measure the expression of a TORC1-dependent ribosome biogenesis gene (NSR1 during osmotic stress in 4700 Saccharomyces cerevisiae strains from the yeast knock-out collection. This led to the identification of 440 strains with significant and reproducible defects in NSR1 repression. The cell growth control and stress response proteins deleted in these strains form a highly connected network, including 56 proteins involved in vesicle trafficking and vacuolar function; 53 proteins that act downstream of TORC1 according to a rapamycin assay—including components of the HDAC Rpd3L, Elongator, and the INO80, CAF-1 and SWI/SNF chromatin remodeling complexes; over 100 proteins involved in signaling and metabolism; and 17 proteins that directly interact with TORC1. These data provide an important resource for labs studying cell growth control and stress signaling, and demonstrate the utility of our new, and easily adaptable, method for mapping gene regulatory networks.

  17. 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

  18. Novel Insights into the Diversity of Catabolic Metabolism from Ten Haloarchaeal Genomes

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Iain; Scheuner, Carmen; Goker, Markus; Mavromatis, Kostas; Hooper, Sean D.; Porat, Iris; Klenk, Hans-Peter; Ivanova, Natalia; Kyrpides, Nikos

    2011-05-03

    The extremely halophilic archaea are present worldwide in saline environments and have important biotechnological applications. Ten complete genomes of haloarchaea are now available, providing an opportunity for comparative analysis. We report here the comparative analysis of five newly sequenced haloarchaeal genomes with five previously published ones. Whole genome trees based on protein sequences provide strong support for deep relationships between the ten organisms. Using a soft clustering approach, we identified 887 protein clusters present in all halophiles. Of these core clusters, 112 are not found in any other archaea and therefore constitute the haloarchaeal signature. Four of the halophiles were isolated from water, and four were isolated from soil or sediment. Although there are few habitat-specific clusters, the soil/sediment halophiles tend to have greater capacity for polysaccharide degradation, siderophore synthesis, and cell wall modification. Halorhabdus utahensis and Haloterrigena turkmenica encode over forty glycosyl hydrolases each, and may be capable of breaking down naturally occurring complex carbohydrates. H. utahensis is specialized for growth on carbohydrates and has few amino acid degradation pathways. It uses the non-oxidative pentose phosphate pathway instead of the oxidative pathway, giving it more flexibility in the metabolism of pentoses. These new genomes expand our understanding of haloarchaeal catabolic pathways, providing a basis for further experimental analysis, especially with regard to carbohydrate metabolism. Halophilic glycosyl hydrolases for use in biofuel production are more likely to be found in halophiles isolated from soil or sediment.

  19. Systems assessment of transcriptional regulation on central carbon metabolism by Cra and CRP.

    Science.gov (United States)

    Kim, Donghyuk; Seo, Sang Woo; Gao, Ye; Nam, Hojung; Guzman, Gabriela I; Cho, Byung-Kwan; Palsson, Bernhard O

    2018-04-06

    Two major transcriptional regulators of carbon metabolism in bacteria are Cra and CRP. CRP is considered to be the main mediator of catabolite repression. Unlike for CRP, in vivo DNA binding information of Cra is scarce. Here we generate and integrate ChIP-exo and RNA-seq data to identify 39 binding sites for Cra and 97 regulon genes that are regulated by Cra in Escherichia coli. An integrated metabolic-regulatory network was formed by including experimentally-derived regulatory information and a genome-scale metabolic network reconstruction. Applying analysis methods of systems biology to this integrated network showed that Cra enables optimal bacterial growth on poor carbon sources by redirecting and repressing glycolysis flux, by activating the glyoxylate shunt pathway, and by activating the respiratory pathway. In these regulatory mechanisms, the overriding regulatory activity of Cra over CRP is fundamental. Thus, elucidation of interacting transcriptional regulation of core carbon metabolism in bacteria by two key transcription factors was possible by combining genome-wide experimental measurement and simulation with a genome-scale metabolic model.

  20. 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...

  1. An overview of bioinformatics methods for modeling biological pathways in yeast.

    Science.gov (United States)

    Hou, Jie; Acharya, Lipi; Zhu, Dongxiao; Cheng, Jianlin

    2016-03-01

    The advent of high-throughput genomics techniques, along with the completion of genome sequencing projects, identification of protein-protein interactions and reconstruction of genome-scale pathways, has accelerated the development of systems biology research in the yeast organism Saccharomyces cerevisiae In particular, discovery of biological pathways in yeast has become an important forefront in systems biology, which aims to understand the interactions among molecules within a cell leading to certain cellular processes in response to a specific environment. While the existing theoretical and experimental approaches enable the investigation of well-known pathways involved in metabolism, gene regulation and signal transduction, bioinformatics methods offer new insights into computational modeling of biological pathways. A wide range of computational approaches has been proposed in the past for reconstructing biological pathways from high-throughput datasets. Here we review selected bioinformatics approaches for modeling biological pathways inS. cerevisiae, including metabolic pathways, gene-regulatory pathways and signaling pathways. We start with reviewing the research on biological pathways followed by discussing key biological databases. In addition, several representative computational approaches for modeling biological pathways in yeast are discussed. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  2. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

    DEFF Research Database (Denmark)

    Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

    2016-01-01

    in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR

  3. Application of synthetic biology for production of chemicals in yeast Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Borodina, Irina; Li, Mingji

    2015-01-01

    Synthetic biology and metabolic engineering enable generation of novel cell factories that efficiently convert renewable feedstocks into biofuels, bulk, and fine chemicals, thus creating the basis for biosustainable economy independent on fossil resources. While over a hundred proof...... biology has the potential to bring down this cost by improving our ability to predictably engineer biological systems. This review highlights synthetic biology applications for design, assembly, and optimization of non-native biochemical pathways in baker's yeast Saccharomyces cerevisiae. We describe......-of-concept chemicals have been made in yeast, only a very small fraction of those has reached commercial-scale production so far. The limiting factor is the high research cost associated with the development of a robust cell factory that can produce the desired chemical at high titer, rate, and yield. Synthetic...

  4. 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.

  5. 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.)

  6. Directed Evolution towards Increased Isoprenoid Production in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Carlsen, Simon; Nielsen, Michael Lynge; Kielland-Brandt, Morten

    production can easily be scaled to meet current demands and it is also an environmental benign production method compared to organic synthesis. Thus it would be attractive to engineer a microorganism to produce high amounts of IPP and other immediate prenyl precursors such as geranyl pyrophosphate, farnesyl...... for discovering new genetic perturbations, which would results in and increased production of isoprenoids by S. cerevisiae has been very limited. This project is focus on creating diversity within a lycopene producing S. cerevisiae strain by construction of gDNA-, cDNA-, and transposon-libraries. The diversified...... coloration which is the result of higher amount of lycopene is being produced and hence high amount of isoprenoid precursor being available. This will elucidate novel genetic targets for increasing isoprenoid production in S. cerevisiae...

  7. The scaling of maximum and basal metabolic rates of mammals and birds

    Science.gov (United States)

    Barbosa, Lauro A.; Garcia, Guilherme J. M.; da Silva, Jafferson K. L.

    2006-01-01

    Allometric scaling is one of the most pervasive laws in biology. Its origin, however, is still a matter of dispute. Recent studies have established that maximum metabolic rate scales with an exponent larger than that found for basal metabolism. This unpredicted result sets a challenge that can decide which of the concurrent hypotheses is the correct theory. Here, we show that both scaling laws can be deduced from a single network model. Besides the 3/4-law for basal metabolism, the model predicts that maximum metabolic rate scales as M, maximum heart rate as M, and muscular capillary density as M, in agreement with data.

  8. 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...

  9. Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

    International Nuclear Information System (INIS)

    Tosato, Valentina; Grüning, Nana-Maria; Breitenbach, Michael; Arnak, Remigiusz; Ralser, Markus; Bruschi, Carlo V.

    2013-01-01

    Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  10. Warburg effect and translocation-induced genomic instability: two yeast models for cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Tosato, Valentina [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Grüning, Nana-Maria [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Breitenbach, Michael [Division of Genetics, Department of Cell Biology, University of Salzburg, Salzburg (Austria); Arnak, Remigiusz [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy); Ralser, Markus [Cambridge System Biology Center, Department of Biochemistry, University of Cambridge, Cambridge (United Kingdom); Bruschi, Carlo V., E-mail: bruschi@icgeb.org [International Centre for Genetic Engineering and Biotechnology, Trieste (Italy)

    2013-01-18

    Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression (i) the activity of pyruvate kinase (PK), which recapitulates metabolic features of cancer cells, including the Warburg effect, and (ii) chromosome bridge-induced translocation (BIT) mimiking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect), and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, PK, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and post-translational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (“translocants”), between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the BIT system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  11. WARBURG EFFECT AND TRANSLOCATION-INDUCED GENOMIC INSTABILITY: TWO YEAST MODELS FOR CANCER CELLS

    Directory of Open Access Journals (Sweden)

    Valentina eTosato

    2013-01-01

    Full Text Available Yeast has been established as an efficient model system to study biological principles underpinning human health. In this review we focus on yeast models covering two aspects of cancer formation and progression i the activity of pyruvate kinase (PK, which recapitulates metabolic features of cancer cells, including the Warburg effect, and ii Bridge-Induced chromosome Translocation (BIT mimicking genome instability in cancer. Saccharomyces cerevisiae is an excellent model to study cancer cell metabolism, as exponentially growing yeast cells exhibit many metabolic similarities with rapidly proliferating cancer cells. The metabolic reconfiguration includes an increase in glucose uptake and fermentation, at the expense of respiration and oxidative phosphorylation (the Warburg effect, and involves a broad reconfiguration of nucleotide and amino acid metabolism. Both in yeast and humans, the regulation of this process seems to have a central player, pyruvate kinase, which is up-regulated in cancer, and to occur mostly on a post-transcriptional and posttranslational basis. Furthermore, BIT allows to generate selectable translocation-derived recombinants (translocants, between any two desired chromosomal locations, in wild-type yeast strains transformed with a linear DNA cassette carrying a selectable marker flanked by two DNA sequences homologous to different chromosomes. Using the Bridge-Induced Translocation system, targeted non-reciprocal translocations in mitosis are easily inducible. An extensive collection of different yeast translocants exhibiting genome instability and aberrant phenotypes similar to cancer cells has been produced and subjected to analysis. In this review, we hence provide an overview upon two yeast cancer models, and extrapolate general principles for mimicking human disease mechanisms in yeast.

  12. 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.

  13. GIGGLE: a search engine for large-scale integrated genome analysis.

    Science.gov (United States)

    Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

    2018-02-01

    GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

  14. Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

    Science.gov (United States)

    Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

    2013-07-01

    In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. RPO41-independent maintenance of [rho-] mitochondrial DNA in Saccharomyces cerevisiae.

    Science.gov (United States)

    Fangman, W L; Henly, J W; Brewer, B J

    1990-01-01

    A subset of promoters in the mitochondrial DNA (mtDNA) of the yeast Saccharomyces cerevisiae has been proposed to participate in replication initiation, giving rise to a primer through site-specific cleavage of an RNA transcript. To test whether transcription is essential for mtDNA maintenance, we examined two simple mtDNA deletion ([rho-]) genomes in yeast cells. One genome (HS3324) contains a consensus promoter (ATATAAGTA) for the mitochondrial RNA polymerase encoded by the nuclear gene RPO41, and the other genome (4a) does not. As anticipated, in RPO41 cells transcripts from the HS3324 genome were more abundant than were transcripts from the 4a genome. When the RPO41 gene was disrupted, both [rho-] genomes were efficiently maintained. The level of transcripts from HS3324 mtDNA was decreased greater than 400-fold in cells carrying the RPO41 disrupted gene; however, the low-level transcripts from 4a mtDNA were undiminished. These results indicate that replication of [rho-] genomes can be initiated in the absence of wild-type levels of the RPO41-encoded RNA polymerase.

  16. Molecular cloning and expression in Saccharomyces cerevisiae and Neurospora crassa of the invertase gene from Neurospora crassa.

    Science.gov (United States)

    Carú, M; Cifuentes, V; Pincheira, G; Jiménez, A

    1989-10-01

    A plasmid (named pCN2) carrying a 7.6 kb BamHI DNA insert was isolated from a Neurospora crassa genomic library raised in the yeast vector YRp7. Saccharomyces cerevisiae suco and N. crassa inv strains transformed with pNC2 were able to grow on sucrose-based media and expressed invertase activity. Saccharomyces cerevisiae suco (pNC2) expressed a product which immunoreacted with antibody raised against purified invertase from wild type N. crassa, although S. cerevisiae suc+ did not. The cloned DNA hybridized with a 7.6 kb DNA fragment from BamHI-restricted wild type N. crassa DNA. Plasmid pNC2 transformed N. crassa Inv- to Inv+ by integration either near to the endogenous inv locus (40% events) or at other genomic sites (60% events). It appears therefore that the cloned DNA piece encodes the N. crassa invertase enzyme. A 3.8 kb XhoI DNA fragment, derived from pNC2, inserted in YRp7, in both orientation, was able to express invertase activity in yeast, suggesting that it contains an intact invertase gene which is not expressed from a vector promoter.

  17. Cellular responses of Saccharomyces cerevisiae at near-zero growth rates : Transcriptome analysis of anaerobic retentostat cultures

    NARCIS (Netherlands)

    Boender, L.G.M.; Van Maris, A.J.A.; De Hulster, E.A.F.; Almering, M.J.H.; Van der Klei, I.J.; Veenhuis, M.; De Winde, J.H.; Pronk, J.T.; Daran-Lapujade, P.A.S.

    2011-01-01

    Extremely low specific growth rates (below 0.01 h?1) represent a largely unexplored area of microbial physiology. In this study, anaerobic, glucose-limited retentostats were used to analyse physiological and genome-wide transcriptional responses of Saccharomyces cerevisiae to cultivation at

  18. Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa.

    Science.gov (United States)

    Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura; Hinney, Anke; Daly, Mark; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M

    2017-09-01

    The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h 2 SNP ]), partitioned heritability, and genetic correlations (r g ) between anorexia nervosa and 159 other phenotypes. Results were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h 2 SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Anorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

  19. 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.

  20. 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 .

  1. Length and GC content variability of introns among teleostean genomes in the light of the metabolic rate hypothesis.

    Science.gov (United States)

    Chaurasia, Ankita; Tarallo, Andrea; Bernà, Luisa; Yagi, Mitsuharu; Agnisola, Claudio; D'Onofrio, Giuseppe

    2014-01-01

    A comparative analysis of five teleostean genomes, namely zebrafish, medaka, three-spine stickleback, fugu and pufferfish was performed with the aim to highlight the nature of the forces driving both length and base composition of introns (i.e., bpi and GCi). An inter-genome approach using orthologous intronic sequences was carried out, analyzing independently both variables in pairwise comparisons. An average length shortening of introns was observed at increasing average GCi values. The result was not affected by masking transposable and repetitive elements harbored in the intronic sequences. The routine metabolic rate (mass specific temperature-corrected using the Boltzmann's factor) was measured for each species. A significant correlation held between average differences of metabolic rate, length and GC content, while environmental temperature of fish habitat was not correlated with bpi and GCi. Analyzing the concomitant effect of both variables, i.e., bpi and GCi, at increasing genomic GC content, a decrease of bpi and an increase of GCi was observed for the significant majority of the intronic sequences (from ∼ 40% to ∼ 90%, in each pairwise comparison). The opposite event, concomitant increase of bpi and decrease of GCi, was counter selected (from hypothesis that the metabolic rate plays a key role in shaping genome architecture and evolution of vertebrate genomes.

  2. Increasing cocoa butter-like lipid production of Saccharomyces cerevisiae by expression of selected cocoa genes

    DEFF Research Database (Denmark)

    Wei, Yongjun; Gossing, Michael; Bergenholm, David

    2017-01-01

    for CB biosynthesis from the cocoa genome using a phylogenetic analysis approach. By expressing the selected cocoa genes in S. cerevisiae, we successfully increased total fatty acid production, TAG production and CBL production in some S. cerevisiae strains. The relative CBL content in three yeast...... higher level of CBL compared with the control strain. In summary, CBL production by S. cerevisiae were increased through expressing selected cocoa genes potentially involved in CB biosynthesis.......Cocoa butter (CB) extracted from cocoa beans mainly consists of three different kinds of triacylglycerols (TAGs), 1,3-dipalmitoyl-2-oleoyl-glycerol (POP, C16:0-C18:1-C16:0), 1-palmitoyl-3-stearoyl-2-oleoyl-glycerol(POS,C16:0C18:1-C18:0) and 1,3-distearoyl-2-oleoyl-glycerol (SOS, C18:0-C18:1-C18...

  3. GIGGLE: a search engine for large-scale integrated genome analysis

    Science.gov (United States)

    Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

    2018-01-01

    GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation. PMID:29309061

  4. 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

  5. Inheritance and organisation of the mitochondrial genome differ between two Saccharomyces yeasts

    DEFF Research Database (Denmark)

    Petersen, Randi Føns; Langkjær, Rikke Breinhold; Hvidtfeldt, J.

    2002-01-01

    Petite-positive Saccharomyces yeasts can be roughly divided into the sensu stricto, including Saccharomyces cerevisiae, and sensu lato group, including Saccharomyces castellii; the latter was recently studied for transmission and the organisation of its mitochondrial genome. S. castellii mitochon......Petite-positive Saccharomyces yeasts can be roughly divided into the sensu stricto, including Saccharomyces cerevisiae, and sensu lato group, including Saccharomyces castellii; the latter was recently studied for transmission and the organisation of its mitochondrial genome. S. castellii...... mitochondrial molecules (mtDNA) carrying point mutations, which confer antibiotic resistance, behaved in genetic crosses as the corresponding point mutants of S. cerevisiae. While S. castellii generated spontaneous petite mutants in a similar way as S. cerevisiae, the petites exhibited a different inheritance...... pattern. In crosses with the wild type strains a majority of S. castellii petites was neutral, and the suppressivity in suppressive petites was never over 50%. The two yeasts also differ in organisation of their mtDNA molecules. The 25,753 bp sequence of S. castellii mtDNA was determined and the coding...

  6. The genome of Pelobacter carbinolicus reveals surprising metabolic capabilities and physiological features

    Energy Technology Data Exchange (ETDEWEB)

    Aklujkar, Muktak [University of Massachusetts, Amherst; Haveman, Shelley [University of Massachusetts, Amherst; DiDonatoJr, Raymond [University of Massachusetts, Amherst; Chertkov, Olga [Los Alamos National Laboratory (LANL); Han, Cliff [Los Alamos National Laboratory (LANL); Land, Miriam L [ORNL; Brown, Peter [University of Massachusetts, Amherst; Lovley, Derek [University of Massachusetts, Amherst

    2012-01-01

    Background: The bacterium Pelobacter carbinolicus is able to grow by fermentation, syntrophic hydrogen/formate transfer, or electron transfer to sulfur from short-chain alcohols, hydrogen or formate; it does not oxidize acetate and is not known to ferment any sugars or grow autotrophically. The genome of P. carbinolicus was sequenced in order to understand its metabolic capabilities and physiological features in comparison with its relatives, acetate-oxidizing Geobacter species. Results: Pathways were predicted for catabolism of known substrates: 2,3-butanediol, acetoin, glycerol, 1,2-ethanediol, ethanolamine, choline and ethanol. Multiple isozymes of 2,3-butanediol dehydrogenase, ATP synthase and [FeFe]-hydrogenase were differentiated and assigned roles according to their structural properties and genomic contexts. The absence of asparagine synthetase and the presence of a mutant tRNA for asparagine encoded among RNA-active enzymes suggest that P. carbinolicus may make asparaginyl-tRNA in a novel way. Catabolic glutamate dehydrogenases were discovered, implying that the tricarboxylic acid (TCA) cycle can function catabolically. A phosphotransferase system for uptake of sugars was discovered, along with enzymes that function in 2,3-butanediol production. Pyruvate: ferredoxin/flavodoxin oxidoreductase was identified as a potential bottleneck in both the supply of oxaloacetate for oxidation of acetate by the TCA cycle and the connection of glycolysis to production of ethanol. The P. carbinolicus genome was found to encode autotransporters and various appendages, including three proteins with similarity to the geopilin of electroconductive nanowires. Conclusions: Several surprising metabolic capabilities and physiological features were predicted from the genome of P. carbinolicus, suggesting that it is more versatile than anticipated.

  7. 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...

  8. Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

    Science.gov (United States)

    Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

    2015-03-07

    Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  9. Comparative studies on the fermentation performance of autochthonous Saccharomyces cerevisiae strains in Chinese light-fragrant liquor during solid-state or submerged fermentation.

    Science.gov (United States)

    Kong, Y; Wu, Q; Xu, Y

    2017-04-01

    To explore the metabolic characteristic of autochthonous Saccharomyces cerevisiae strains in Chinese light-fragrant liquor fermentation. Inter-delta amplification analysis was used to differentiate the S. cerevisiae strains at strain level. Twelve biotypes (I-XII) were identified among the 72 S. cerevisiae strains preselected. A comparison was conducted between solid-state fermentation (SSF) and submerged fermentation (SmF) with S. cerevisiae strains had different genotype, with a focus on the production of ethanol and the volatile compounds. The degree of ethanol ranged from 28·0 to 45·2 g l -1 in SmF and from 14·8 to 25·6 g kg -1 in SSF, and SSF was found to be more suitable for the production of ethanol with higher yield coefficient of all the S. cerevisiae strains. The metabolite profiles of each yeast strain showed obvious distinction in the two fermentations. The highest amounts of ethyl acetate in SmF and SSF were found in genotype VII (328·2 μg l -1 ) and genotype V (672 μg kg -1 ), respectively. In addition, the generation of some volatile compounds could be strictly related to the strain used. Compound β-damascenone was only detected in genotypes I, II, X and XII in the two fermentation processes. Furthermore, laboratory scale fermentations were clearly divided into SSF and SmF in hierarchical cluster analysis regardless of the inoculated yeast strains, indicating that the mode of fermentation was more important than the yeast strains inoculated. The autochthonous S. cerevisiae strains in Chinese light-fragrant liquor vary considerably in terms of their volatiles profiles during SSF and SmF. This work facilitates a better understanding of the fermentative mechanism in the SSF process for light-fragrant liquor production. © 2016 The Society for Applied Microbiology.

  10. 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.

  11. 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

  12. A Mutation in PGM2 Causing Inefficient Galactose Metabolism in the Probiotic Yeast Saccharomyces boulardii.

    Science.gov (United States)

    Liu, Jing-Jing; Zhang, Guo-Chang; Kong, In Iok; Yun, Eun Ju; Zheng, Jia-Qi; Kweon, Dae-Hyuk; Jin, Yong-Su

    2018-05-15

    The probiotic yeast Saccharomyces boulardii has been extensively studied for the prevention and treatment of diarrheal diseases, and it is now commercially available in some countries. S. boulardii displays notable phenotypic characteristics, such as a high optimal growth temperature, high tolerance against acidic conditions, and the inability to form ascospores, which differentiate S. boulardii from Saccharomyces cerevisiae The majority of prior studies stated that S. boulardii exhibits sluggish or halted galactose utilization. Nonetheless, the molecular mechanisms underlying inefficient galactose uptake have yet to be elucidated. When the galactose utilization of a widely used S. boulardii strain, ATCC MYA-796, was examined under various culture conditions, the S. boulardii strain could consume galactose, but at a much lower rate than that of S. cerevisiae While all GAL genes were present in the S. boulardii genome, according to analysis of genomic sequencing data in a previous study, a point mutation (G1278A) in PGM2 , which codes for phosphoglucomutase, was identified in the genome of the S. boulardii strain. As the point mutation resulted in the truncation of the Pgm2 protein, which is known to play a pivotal role in galactose utilization, we hypothesized that the truncated Pgm2 might be associated with inefficient galactose metabolism. Indeed, complementation of S. cerevisiae PGM2 in S. boulardii restored galactose utilization. After reverting the point mutation to a full-length PGM2 in S. boulardii by Cas9-based genome editing, the growth rates of wild-type (with a truncated PGM2 gene) and mutant (with a full-length PGM2 ) strains with glucose or galactose as the carbon source were examined. As expected, the mutant (with a full-length PGM2 ) was able to ferment galactose faster than the wild-type strain. Interestingly, the mutant showed a lower growth rate than that of the wild-type strain on glucose at 37°C. Also, the wild-type strain was enriched in the

  13. Multiplexed genome engineering and genotyping methods applications for synthetic biology and metabolic engineering.

    Science.gov (United States)

    Wang, Harris H; Church, George M

    2011-01-01

    Engineering at the scale of whole genomes requires fundamentally new molecular biology tools. Recent advances in recombineering using synthetic oligonucleotides enable the rapid generation of mutants at high efficiency and specificity and can be implemented at the genome scale. With these techniques, libraries of mutants can be generated, from which individuals with functionally useful phenotypes can be isolated. Furthermore, populations of cells can be evolved in situ by directed evolution using complex pools of oligonucleotides. Here, we discuss ways to utilize these multiplexed genome engineering methods, with special emphasis on experimental design and implementation. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Genome-Wide DNA Methylation Profiles of Phlegm-Dampness Constitution

    Directory of Open Access Journals (Sweden)

    Haiqiang Yao

    2018-03-01

    Full Text Available Background/Aims: Metabolic diseases are leading health concerns in today’s global society. In traditional Chinese medicine (TCM, one body type studied is the phlegm-dampness constitution (PC, which predisposes individuals to complex metabolic disorders. Genomic studies have revealed the potential metabolic disorders and the molecular features of PC. The role of epigenetics in the regulation of PC, however, is unknown. Methods: We analyzed a genome-wide DNA methylation in 12 volunteers using Illumina Infinium Human Methylation450 BeadChip on peripheral blood mononuclear cells (PBMCs. Eight volunteers had PC and 4 had balanced constitutions. Results: Methylation data indicated a genome-scale hyper-methylation pattern in PC. We located 288 differentially methylated probes (DMPs. A total of 256 genes were mapped, and some of these were metabolic-related. SQSTM1, DLGAP2 and DAB1 indicated diabetes mellitus; HOXC4 and SMPD3, obesity; and GRWD1 and ATP10A, insulin resistance. According to Ingenuity Pathway Analysis (IPA, differentially methylated genes were abundant in multiple metabolic pathways. Conclusion: Our results suggest the potential risk for metabolic disorders in individuals with PC. We also explain the clinical characteristics of PC with DNA methylation features.

  15. 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.

  16. 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...

  17. Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

    Science.gov (United States)

    Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

    2013-09-02

    In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome

  18. Generation of New Genotypic and Phenotypic Features in Artificial and Natural Yeast Hybrids

    Directory of Open Access Journals (Sweden)

    Walter P. Pfliegler

    2014-01-01

    Full Text Available Evolution and genome stabilization have mostly been studied on the Saccharomyces hybrids isolated from natural and alcoholic fermentation environments. Genetic and phenotypic properties have usually been compared to the laboratory and reference strains, as the true ancestors of the natural hybrid yeasts are unknown. In this way the exact impact of different parental fractions on the genome organization or metabolic activity of the hybrid yeasts is difficult to resolve completely. In the present work the evolution of geno- and phenotypic properties is studied in the interspecies hybrids created by the cross-breeding of S. cerevisiae with S. uvarum or S. kudriavzevii auxotrophic mutants. We hypothesized that the extent of genomic alterations in S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii should affect the physiology of their F1 offspring in different ways. Our results, obtained by amplified fragment length polymorphism (AFLP genotyping and karyotyping analyses, showed that both subgenomes of the S. cerevisiae x S. uvarum and of S. cerevisiae × S. kudriavzevii hybrids experienced various modifications. However, the S. cerevisiae × S. kudriavzevii F1 hybrids underwent more severe genomic alterations than the S. cerevisiae × S. uvarum ones. Generation of the new genotypes also influenced the physiological performances of the hybrids and the occurrence of novel phenotypes. Significant differences in carbohydrate utilization and distinct growth dynamics at increasing concentrations of sodium chloride, urea and miconazole were observed within and between the S. cerevisiae × S. uvarum and S. cerevisiae × S. kudriavzevii hybrids. Parental strains also demonstrated different contributions to the final metabolic outcomes of the hybrid yeasts. A comparison of the genotypic properties of the artificial hybrids with several hybrid isolates from the wine-related environments and wastewater demonstrated a greater genetic variability of

  19. 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...

  20. Mitochondrial genomic dysfunction causes dephosphorylation of Sch9 in the yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Kawai, Shigeyuki; Urban, Jörg; Piccolis, Manuele; Panchaud, Nicolas; De Virgilio, Claudio; Loewith, Robbie

    2011-10-01

    TORC1-dependent phosphorylation of Saccharomyces cerevisiae Sch9 was dramatically reduced upon exposure to a protonophore or in respiration-incompetent ρ(0) cells but not in respiration-incompetent pet mutants, providing important insight into the molecular mechanisms governing interorganellar signaling in general and retrograde signaling in particular.