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Open AccessJournal ArticleDOI

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

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.

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What is flux balance analysis

TL;DR: This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.
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A protocol for generating a high-quality genome-scale metabolic reconstruction.

TL;DR: This protocol provides a helpful manual for all stages of the reconstruction process and presents a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction.
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A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information.

TL;DR: An updated genome‐scale reconstruction of the metabolic network in Escherichia coli K‐12 MG1655 with increased scope and computational capability is presented, expected to broaden the spectrum of both basic biology and applied systems biology studies of E. coli metabolism.

Ischaemic accumulation of succinate controls reperfusion injury through mitochondrial ROS

TL;DR: It is shown that selective accumulation of the citric acid cycle intermediate succinate is a universal metabolic signature of ischaemia in a range of tissues and is responsible for mitochondrial ROS production during reperfusion, and a new pathway for metabolic control of ROS production in vivo is revealed.
References
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Journal ArticleDOI

Genome‐scale models of bacterial metabolism: reconstruction and applications

TL;DR: An introduction to the key ideas of metabolic modeling is provided, the methods, and resources that enable model reconstruction and refinement are surveyed, and applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities are charted.
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High-throughput metabolic flux analysis based on gas chromatography–mass spectrometry derived 13C constraints

TL;DR: 13C-constrained flux balancing analysis based on gas chromatography-mass spectrometry data is presented here as a simple and robust method for the estimation of intracellular carbon fluxes and is promising for routine and high-throughput analysis on a miniaturized scale.
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Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems.

TL;DR: It turns out that isotopomers systems are not as complex as they appear at first glance, which enables some far-reaching conclusions to be drawn on the information potential of isotopomer experiments with respect to flux identification.
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Systems approach to refining genome annotation.

TL;DR: An optimization-based algorithm is introduced that predicts the missing reactions that are required to reconcile computation and experiment when they disagree and is demonstrated by a combination of experimental and computational approaches.
Journal ArticleDOI

Metabolic capabilities of Escherichia coli: I. synthesis of biosynthetic precursors and cofactors.

TL;DR: This work uses specific objective functions and linear optimization to investigate the capability of E. coli catabolism to maximally produce the 12 biosynthetic precursors and three key cofactors within this solution space.
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