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
Multispecific drug transporter Slc22a8 (Oat3) regulates multiple metabolic and signaling pathways.
Wei Wu,Neema Jamshidi,Satish A. Eraly,Henry C. Liu,Kevin T. Bush,Bernhard O. Palsson,Sanjay K. Nigam +6 more
TL;DR: Global gene expression in Oat3 knockout tissue was analyzed, which implicated OAT3 in phase I and phase II metabolism (drug metabolizing enzymes or DMEs), as well as signaling pathways, and suggests that Oat 3 is essential for the handling of dietary flavonoids and antioxidants.
Journal ArticleDOI
Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion.
Jahir M. Gutierrez,Amir Feizi,Shangzhong Li,Thomas Beuchert Kallehauge,Hooman Hefzi,Lise Marie Grav,Daniel Ley,Deniz Baycin Hizal,Michael J. Betenbaugh,Bjørn G. Voldborg,Helene Faustrup Kildegaard,Gyun Min Lee,Bernhard O. Palsson,Jens Nielsen,Jens Nielsen,Nathan E. Lewis +15 more
TL;DR: The authors integrate the core secretory pathway into genome-scale metabolic models of human, mouse, and CHO cells, enabling in silico analysis and finding that highly secretory cells have adapted to reduce expression and secretion of other expensive host cell proteins.
Book ChapterDOI
Flux Balance Analysis: Interrogating Genome-Scale Metabolic Networks
TL;DR: This chapter presents the methodology, theory, and common pitfalls of the application of FBA, a computational method to analyze reconstructions of biochemical networks.
Book ChapterDOI
Recent Advances, Challenges, and Opportunities in Bioremediation of Hazardous Materials
TL;DR: This chapter highlights recent advances and available bioremediation strategies and methodologies as a way to control and manage the different wastes with the use of biotechnology.
Journal ArticleDOI
Targeted Repression of Essential Genes To Arrest Growth and Increase Carbon Partitioning and Biofuel Titers in Cyanobacteria
TL;DR: Genetic strategies for a two-phase cultivation where biofuel-producing Synechocystis cultures are limited to an optimal cell density through inducible CRISPR interference (CRISPRi) repression of cell growth are investigated, and modulate GltA expression and carbon partitioning between growth and product to increase both specific and volumetric productivity.
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.