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
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Evaluating Enzymatic Synthesis of Small Molecule Drugs
Matthew Moura,Justin D. Finkle,Sarah Stainbrook,Jennifer Greene,Linda J. Broadbelt,Keith E. J. Tyo +5 more
TL;DR: This work sought to evaluate the potential for biosynthesis beyond the limits of known biochemistry towards the production of small molecule drugs that do not exist in nature, and focused on drugs for diseases endemic to many resource poor regions, like tuberculosis and HIV.
Journal ArticleDOI
Reconstruction of a regulated two-cell metabolic model to study biohydrogen production in a diazotrophic cyanobacterium Anabaena variabilis ATCC 29413.
TL;DR: The predictions indicate that the removal of uptake hydrogenase improves hydrogen production which is consistent with previous empirical research and proposed activation of some reactions to provide redox cofactors which are required for improving hydrogen production up to 60% by bidirectional hydrogenase.
Journal ArticleDOI
Sequence-based network completion reveals the integrality of missing reactions in metabolic networks
TL;DR: To investigate whether functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes.
Journal ArticleDOI
Mathematical models of plant metabolism.
Hai Shi,Jörg Schwender +1 more
TL;DR: Recent developments in Constraint-Based modeling in plants are discussed with focus on issues of model reconstruction and flux prediction, including instationary (13)C-MFA used to probe autotrophic metabolism in photosynthetic tissue in the light.
Journal ArticleDOI
Modelling osmotic stress by Flux Balance Analysis at the genomic scale.
TL;DR: This work simulations show that the specific growth rate of Escherichia coli can be predicted by assuming, as an objective function, that the cells maximise their biomass production during balanced growth, but this objective function is not sufficient to explain the decrease of the growth rate due to osmotic stress.
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