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Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2013年第47期110卷 19166-19171页

作者： Wagner, Allon Zarecki, Raphy Reshef, Leah Gochev, Camelia Sorek, Rotem Gophna, Uri Ruppin, Eytan Tel Aviv Univ Fac Life Sci Blavatnik Sch Comp Sci IL-69978 Tel Aviv Israel Tel Aviv Univ Fac Life Sci Sackler Sch Med IL-69978 Tel Aviv Israel Tel Aviv Univ Fac Life Sci Dept Mol Microbiol & Biotechnol IL-69978 Tel Aviv Israel Weizmann Inst Sci Dept Mol Genet IL-76100 Rehovot Israel Natl Evolutionary Synth Ctr Durham NC 27705 USA

Gene suppression and overexpression are both fundamental tools in linking genotype to phenotype in model organisms. Computational methods have proven invaluable in studying and predicting the deleterious effects of gene deletions, and yet parallel computational methods for overexpression are still lacking. Here, we present Expression-Dependent Gene Effects (EDGE), an in silico method that can predict the deleterious effects resulting from overexpression of either native or foreign metabolic genes. We first test and validate EDGE's predictive power in bacteria through a combination of small-scale growth experiments that we performed and analysis of extant large-scale datasets. Second, a broad cross-species analysis, ranging from microorganisms to multiple plant and human tissues, shows that genes that EDGE predicts to be deleterious when overexpressed are indeed typically down-regulated. This reflects a universal selection force keeping the expression of potentially deleterious genes in check. Third, EDGE-based analysis shows that cancer genetic reprogramming specifically suppresses genes whose overexpression impedes proliferation. The magnitude of this suppression is large enough to enable an almost perfect distinction between normal and cancerous tissues based solely on EDGE results. We expect EDGE to advance our understanding of human pathologies associated with up-regulation of particular transcripts and to facilitate the utilization of gene overexpression in metabolic engineering.

关键词： systems metabolic engineering metabolic modeling constraint-based modeling flux balance analysis horizontal gene transfer

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Systems-level characterization of a host-microbe metabolic symbiosis in the mammalian gut

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GUT MICROBES 2013年第1期4卷 28-40页

作者： Heinken, Almut Sahoo, Swagatika Fleming, Ronan M. T. Thiele, Ines Univ Iceland Ctr Syst Biol Reykjavik Iceland Univ Iceland Fac Med Dept Biochem & Mol Biol Reykjavik Iceland Univ Iceland Mech Engn & Comp Sci Fac Ind Engn Reykjavik Iceland

The human gut microbiota consists of ten times more microorganisms than there are cells in our body, processes otherwise indigestible nutrients, and produces important energy precursors, essential amino acids, and vitamins. In this study, we assembled and validated a genome-scale metabolic reconstruction of Bacteroides thetaiotaomicron (iAH991), a prominent representative of the human gut microbiota, consisting of 1,488 reactions, 1,152 metabolites, and 991 genes. To create a comprehensive metabolic model of host-microbe interactions, we integrated iAH991 with a previously published mouse metabolic reconstruction, which was extended for intestinal transport and absorption reactions. The two metabolic models were linked through a joint compartment, the lumen, allowing metabolite exchange and providing a route for simulating different dietary regimes. The resulting model consists of 7,239 reactions, 5,164 metabolites, and 2,769 genes. We simultaneously modeled growth of mouse and B. thetaiotaomicron on five different diets varying in fat, carbohydrate, and protein content. The integrated model captured mutually beneficial cross-feeding as well as competitive interactions. Furthermore, we identified metabolites that were exchanged between the two organisms, which were compared with published metabolomics data. This analysis resulted for the first time in a comprehensive description of the co-metabolism between a host and its commensal microbe. We also demonstrate in silico that the presence of B. thetaiotaomicron could rescue the growth phenotype of the host with an otherwise lethal enzymopathy and vice versa. This systems approach represents a powerful tool for modeling metabolic interactions between a gut microbe and its host in health and disease.

关键词： systems biology computational modeling metabolism host-microbe interactions Bacteroides thetaiotaomicron constraint-based modeling Mus musculus

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modeling Challenges in the Synthetic Biology of Secondary Metabolism

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ACS SYNTHETIC BIOLOGY 2013年第7期2卷 373-378页

作者： Breitling, Rainer Achcar, Fiona Takano, Eriko Univ Manchester Manchester Inst Biotechnol Fac Life Sci Manchester M1 7DN Lancs England Univ Glasgow Coll Med Vet & Life Sci Inst Mol Cell & Syst Biol Glasgow G12 8QQ Lanark Scotland

The successful engineering of secondary metabolite production relies on the availability of detailed computational models of metabolism. In this brief review we discuss the types of models used for synthetic biology and their application for the engineering of metabolism. We then highlight some of the major modeling challenges, in particular the need to make informative model predictions based on incomplete and uncertain information. This issue is particularly pressing in the synthetic biology of secondary metabolism, due to the genetic diversity of microbial secondary metabolite producers, the difficulty of enzyme-kinetic characterization of the complex biosynthetic machinery, and the need for engineered pathways to function efficiently in heterologous hosts. We argue that an explicit quantitative consideration of the resulting uncertainty of metabolic models can lead to more informative predictions to guide the design of improved production hosts for bioactive secondary metabolites.

关键词： synthetic biology secondary metabolite metabolism metabolic modeling constraint-based modeling kinetic modeling uncertainty Monte Carlo sampling metabolomics fluxomics

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Fifteen years of constraint-based tutors: what we have achieved and where we are going

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USER modeling AND USER-ADAPTED INTERACTION 2012年第1-2期22卷 39-72页

作者： Mitrovic, Antonija Univ Canterbury Intelligent Comp Tutoring Grp Dept Comp Sci & Software Engn Christchurch New Zealand

Fifteen years ago, research started on SQL-Tutor, the first constraint-based tutor. The initial efforts were focused on evaluating constraint-based modeling (CBM), its effectiveness and applicability to various instructional domains. Since then, we extended CBM in a number of ways, and developed many constraint-based tutors. Our tutors teach both well-and ill-defined domains and tasks, and deal with domain-and meta-level skills. We have supported mainly individual learning, but also the acquisition of collaborative skills. Authoring support for constraint-based tutors is now available, as well as mature, well-tested deployment environments. Our current research focuses on building affect-sensitive and motivational tutors. Over the period of fifteen years, CBM has progressed from a theoretical idea to a mature, reliable and effective methodology for developing effective tutors.

关键词： constraint-based modeling constraint-based tutors Authoring Affective modeling Metacognitive skills Collaborative learning

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

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METABOLIC ENGINEERING 2012年第4期14卷 366-379页

作者： Celton, Magalie Goelzer, Anne Camarasa, Carole Fromion, Vincent Dequin, Sylvie INRA UMR1083 F-34060 Montpellier France SupAgro UMR1083 Sci Oenol F-34060 Montpellier France Univ Montpellier I UMR1083 F-34060 Montpellier France INRA Math Informat & Genome UR1077 F-78350 Jouy En Josas France

Controlling the amounts of redox cofactors to manipulate metabolic fluxes is emerging as a useful approach to optimizing byproduct yields in yeast biotechnological processes. Redox cofactors are extensively interconnected metabolites, so predicting metabolite patterns is challenging and requires in-depth knowledge of how the metabolic network responds to a redox perturbation. Our aim was to analyze comprehensively the metabolic consequences of increased cytosolic NADPH oxidation during yeast fermentation. Using a genetic device based on the overexpression of a modified 2,3-butanediol dehydrogenase catalyzing the NADPH-dependent reduction of acetoin into 2,3-butanediol, we increased the NADPH demand to between 8 and 40-fold the anabolic demand. We developed (i) a dedicated constraint-based model of yeast fermentation and (ii) a constraint-based modeling method based on the dynamical analysis of mass distribution to quantify the in vivo contribution of pathways producing NADPH to the maintenance of redox homeostasis. We report that yeast responds to NADPH oxidation through a gradual increase in the flux through the PP and acetate pathways, providing 80% and 20% of the NADPH demand, respectively. However, for the highest NADPH demand, the model reveals a saturation of the PP pathway and predicts an exchange between NADH and NADPH in the cytosol that may be mediated by the glycerol-DHA futile cycle. We also reveal the contribution of mitochondrial shuttles, resulting in a net production of NADH in the cytosol, to fine-tune the NADH/NAD(+) balance. This systems level study helps elucidate the physiological adaptation of yeast to NADPH perturbation. Our findings emphasize the robustness of yeast to alterations in NADPH metabolism and highlight the role of the glycerol-DHA cycle as a redox valve, providing additional NADPH from NADH under conditions of very high demand. (C) 2012 Elsevier Inc. All rights reserved.

关键词： NADPH oxidation constraint-based modeling Redox cycles

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COBRApy: constraints-based Reconstruction and Analysis for Python

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BMC SYSTEMS BIOLOGY 2013年第1期7卷 74页

作者： Ebrahim, Ali Lerman, Joshua A. Palsson, Bernhard O. Hyduke, Daniel R. Univ Calif San Diego Dept Bioengn La Jolla CA 92093 USA Utah State Univ Biol Engn Dept Logan UT 84322 USA

Background: constraint-based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism;however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Results: Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function;however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. Conclusion: COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. Availability: http://***/

关键词： Genome-scale Network reconstruction Metabolism Gene expression constraint-based modeling

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Inferring ancient metabolism using ancestral core metabolic models of enterobacteria

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BMC SYSTEMS BIOLOGY 2013年第1期7卷 46页

作者： Baumler, David J. Ma, Bing Reed, Jennifer L. Perna, Nicole T. Univ Wisconsin Genome Ctr Wisconsin Madison WI 53706 USA Univ Wisconsin Dept Chem & Biol Engn Madison WI USA Univ Wisconsin Dept Genet Madison WI 53706 USA

Background: Enterobacteriaceae diversified from an ancestral lineage similar to 300-500 million years ago (mya) into a wide variety of free-living and host-associated lifestyles. Nutrient availability varies across niches, and evolution of metabolic networks likely played a key role in adaptation. Results: Here we use a paleo systems biology approach to reconstruct and model metabolic networks of ancestral nodes of the enterobacteria phylogeny to investigate metabolism of ancient microorganisms and evolution of the networks. Specifically, we identified orthologous genes across genomes of 72 free-living enterobacteria (16 genera), and constructed core metabolic networks capturing conserved components for ancestral lineages leading to E. coli/Shigella (similar to 10 mya), E. coli/Shigella/Salmonella (similar to 100 mya), and all enterobacteria (similar to 300-500 mya). Using these models we analyzed the capacity for carbon, nitrogen, phosphorous, sulfur, and iron utilization in aerobic and anaerobic conditions, identified conserved and differentiating catabolic phenotypes, and validated predictions by comparison to experimental data from extant organisms. Conclusions: This is a novel approach using quantitative ancestral models to study metabolic network evolution and may be useful for identification of new targets to control infectious diseases caused by enterobacteria.

关键词： constraint-based modeling Enterobacteria Metabolic network reconstruction Ancient metabolism Paleo systems biology Ancestral core

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Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

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MOLECULAR SYSTEMS BIOLOGY 2013年第1期9卷 661页

作者： McCloskey, Douglas Palsson, Bernhard O. Feist, Adam M. Univ Calif San Diego Dept Bioengn La Jolla CA 92093 USA Tech Univ Denmark Novo Nordisk Fdn Ctr Biosustainabil DK-2800 Lyngby Denmark

The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges include the expansion of GEMs by integrating additional cellular processes beyond metabolism, the identification of key constraints based on emerging data types, and the development of computational methods able to handle such large-scale network models with sufficient accuracy.

关键词： constraint-based modeling Escherichia coli metabolic engineering metabolism network reconstruction

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MC³: a steady-state model and constraint consistency checker for biochemical networks

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BMC SYSTEMS BIOLOGY 2013年第1期7卷 129页

作者： Yousofshahi, Mona Ullah, Ehsan Stern, Russell Hassoun, Soha Tufts Univ Dept Comp Sci Medford MA 02155 USA

Background: Stoichiometric models provide a structural framework for analyzing steady-state cellular behavior. Models are developed either through augmentations of existing models or more recently through automatic reconstruction tools. There is currently no standardized practice or method for validating the properties of a model before placing it in the public domain. Considerable effort is often required to understand a model's inconsistencies before its reuse within new research efforts. Results: We present a review of common issues in stoichiometric models typically uncovered during pathway analysis and constraint-based optimization, and we detail succinct and efficient ways to find them. We present MC3, Model and constraint Consistency Checker, a computational tool that can be used for two purposes: (a) identifying potential connectivity and topological issues for a given stoichiometric matrix, S, and (b) flagging issues that arise during constraint-based optimization. The MC3 tool includes three distinct checking components. The first examines the results of computing the basis for the null space for Sv = 0;the second uses connectivity analysis;and the third utilizes Flux Variability Analysis. MC3 takes as input a stoichiometric matrix and flux constraints, and generates a report summarizing issues. Conclusions: We report the results of applying MC3 to published models for several systems including Escherichia coli, an adipocyte cell, a Chinese Hamster Ovary cell, and Leishmania major. Several issues with no prior documentation are identified. MC3 provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools.

关键词： constraint-based modeling Pathway analysis Model validation Consistency checking Model reuse

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A Guide to Integrating Transcriptional Regulatory and Metabolic Networks Using PROM (Probabilistic Regulation of Metabolism)

A Guide to Integrating Transcriptional Regulatory and Metabo...

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作者： Evangelos Simeonidis Sriram Chandrasekaran Nathan D. Price

The integration of transcriptional regulatory and metabolic networks is a crucial step in the process of predicting metabolic behaviors that emerge from either genetic or environmental changes. Here, we present a guide to PROM (probabilistic regulation of metabolism), an automated method for the construction and simulation of integrated metabolic and transcriptional regulatory networks that enables large-scale phenotypic predictions for a wide range of model organisms. less

关键词： Microarray Statistical Inference Systems biology Metabolic networks constraint-based modeling Transcriptional regulatory networks Probabilistic regulation of metabolism

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