Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Jan Schellenberger,Richard Que,Ronan M. T. Fleming,Ines Thiele,Jeffrey D. Orth,Adam M. Feist,Daniel C. Zielinski,Aarash Bordbar,Nathan E. Lewis,Sorena Rahmanian,Joseph Kang,Daniel R. Hyduke,Bernhard O. Palsson +12 more
TLDR
The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.Abstract:
The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.read more
Citations
More filters
Journal ArticleDOI
Multi-tissue computational modeling analyzes pathophysiology of type 2 diabetes in MKR mice.
Amit Kumar,Thomas F. Harrelson,Nathan E. Lewis,Emily J. Gallagher,Derek LeRoith,Joseph Shiloach,Michael J. Betenbaugh +6 more
TL;DR: It is found out that branched-chain amino acids' degradation and fatty acids oxidation pathway is downregulated in T2DM MKR mice, using the first multi-tissue genome-scale model of all metabolic pathways in T1DM.
Journal ArticleDOI
Computational analysis of phenotypic space in heterologous polyketide biosynthesis--applications to Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae.
TL;DR: Flux balance analysis on genome-scale models was applied to simulate cellular metabolism and 6-deoxyerythronolide B (the cyclized polyketide precursor to erythromycin) production in three common heterologous hosts and identified single and double gene-knockouts that resulted in increasedpolyketide production while maintaining cellular growth.
Journal ArticleDOI
In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production.
Annalisa Occhipinti,Filmon Eyassu,Thahira Rahman,Pattanathu K. S. M. Rahman,Pattanathu K. S. M. Rahman,Claudio Angione +5 more
TL;DR: A substantial increase in synthesis of rhamnolipids is identified by the engineered model compared to the control model, which is expected to provide a versatile methodology for integrating multi-omics data for topological and functional analysis of P. putida toward maximization of biosurfactant production.
Journal ArticleDOI
The landscape of tiered regulation of breast cancer cell metabolism.
Rotem Katzir,Ibrahim H. Polat,Ibrahim H. Polat,Michal Harel,Shir Katz,Carles Foguet,Vitaly A. Selivanov,Philippe Sabatier,Marta Cascante,Marta Cascante,Tamar Geiger,Eytan Ruppin +11 more
TL;DR: This study measures transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line across three different growth conditions, and finds that the flux of predicted indirectly regulated reactions is strongly coupled toThe flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast Cancer cell metabolism.
Journal ArticleDOI
Systematic applications of metabolomics in metabolic engineering.
TL;DR: Some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, are reviewed, and current computational approaches that explicitly use metabolomics data are discussed.
References
More filters
Journal ArticleDOI
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Paul Shannon,Andrew Markiel,Owen Ozier,Nitin S. Baliga,Jonathan T. Wang,Daniel Ramage,Nada Amin,Benno Schwikowski,Trey Ideker +8 more
TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
Journal ArticleDOI
KEGG: Kyoto Encyclopedia of Genes and Genomes
Minoru Kanehisa,Susumu Goto +1 more
TL;DR: The Kyoto Encyclopedia of Genes and Genomes (KEGG) as discussed by the authors is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules.
Journal ArticleDOI
The KEGG resource for deciphering the genome
TL;DR: A knowledge-based approach for network prediction is developed, which is to predict, given a complete set of genes in the genome, the protein interaction networks that are responsible for various cellular processes.
Journal ArticleDOI
The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models.
Michael Hucka,Andrew Finney,Herbert M. Sauro,Hamid Bolouri,Hamid Bolouri,John Doyle,Hiroaki Kitano,Adam P. Arkin,Benjamin Bornstein,Dennis Bray,Athel Cornish-Bowden,Autumn A. Cuellar,S. Dronov,E. D. Gilles,Martin Ginkel,V. Gor,Igor Goryanin,W. J. Hedley,T. C. Hodgman,J.-H.S. Hofmeyr,Peter Hunter,Nick Juty,J. L. Kasberger,Andreas Kremling,Ursula Kummer,N Le Novère,Leslie M. Loew,D. Lucio,Pedro Mendes,E. Minch,Eric Mjolsness,Yoichi Nakayama,Melanie R. Nelson,Poul M. F. Nielsen,T. Sakurada,James C. Schaff,Bruce E. Shapiro,Thomas S. Shimizu,H. D. Spence,Jörg Stelling,Koichi Takahashi,Masaru Tomita,John Wagner,J. Wang +43 more
TL;DR: This work summarizes the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks, a software-independent language for describing models common to research in many areas of computational biology.
Journal ArticleDOI
Global Mapping of the Yeast Genetic Interaction Network
Amy Hin Yan Tong,Guillaume Lesage,Gary D. Bader,Huiming Ding,Hong Xu,Xiaofeng Xin,James D. Young,Gabriel F. Berriz,Renee L. Brost,Michael Chang,Yiqun Chen,Xin Cheng,Gordon Chua,Helena Friesen,Debra S. Goldberg,Jennifer Haynes,Christine Humphries,Grace He,Shamiza Hussein,Lizhu Ke,Nevan J. Krogan,Zhijian Li,Joshua N. Levinson,Hong Lu,Patrice Menard,Christella Munyana,Ainslie B. Parsons,Owen Ryan,Raffi Tonikian,Tania Michelle Roberts,Anne-Marie Sdicu,Jesse Shapiro,Bilal N. Sheikh,Bernhard Suter,Sharyl L. Wong,Lan V. Zhang,Hongwei Zhu,Christopher G. Burd,Sean Munro,Chris Sander,Jasper Rine,Jack Greenblatt,Matthias Peter,Anthony Bretscher,Graham Bell,Frederick P. Roth,Grant W. Brown,Brenda J. Andrews,Howard Bussey,Charles Boone +49 more
TL;DR: Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.