Quantitative Prediction of Cellular Metabolism with Constraint-based Models: The COBRA Toolbox
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.
- SourceAvailable from: Alejandro H. Buschmann
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- "and C x the biomass concentration . It was assumed that the rates remain constant during each 0 . 5 h integration step . The solution to this equation was fitted to the experimental data . All simulations were per - formed using MATLAB and the COBRA Toolbox software packages with Gurobi TM Optimizer ( Gurobi Optimization , Inc . , Houston , TX ) ( Becker et al . , 2007 ; Schellenberger et al . , 2011 ) ."
ABSTRACT: Macroalgae have high potential to be an efficient, and sustainable feedstock for the production of biofuels and other more valuable chemicals. Attempts have been made to enable the co-fermentation of alginate and mannitol by Saccharomyces cerevisiae to unlock the full potential of this marine biomass. However, the efficient use of the sugars derived from macroalgae depends on the equilibrium of cofactors derived from the alginate and mannitol catabolic pathways. There are a number of strong metabolic limitations that have to be tackled before this bioconversion can be carried out efficiently by engineered yeast cells.
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- "Recon2 and MPS models were done by COnstraints Based Reconstruction and Analysis (COBRA) . For the analysis we focused on the cell compartments present in Recon2 (cytosol, extracellular, nucleus, mitochondria, Golgi apparatus, endoplasmic reticulum, peroxisome, lysosome), used all the 100 pathways of metabolism and no additional restrictions were applied to the model. "
ABSTRACT: Mucopolysaccharidosis (MPS) is a group of lysosomal storage diseases (LSD), characterized by the deficiency of a lysosomal enzyme responsible for the degradation of glycosaminoglycans (GAG). This deficiency leads to the lysosomal accumulation of partially degraded GAG. Nevertheless, deficiency of a single lysosomal enzyme has been associated with impairment in other cell mechanism, such as apoptosis and redox balance. Although GAG analysis represents the main biomarker for MPS diagnosis, it has several limitations that can lead to a misdiagnosis, whereby the identification of new biomarkers represents an important issue for MPS. In this study, we used a system biology approach, through the use of a genome-scale human metabolic reconstruction to understand the effect of metabolism alterations in cell homeostasis and to identify potential new biomarkers in MPS. In-silico MPS models were generated by silencing of MPS-related enzymes, and were analyzed through a flux balance and variability analysis. We found that MPS models used approximately 2286 reactions to satisfy the objective function. Impaired reactions were mainly involved in cellular respiration, mitochondrial process, amino acid and lipid metabolism, and ion exchange. Metabolic changes were similar for MPS I and II, and MPS III A to C; while the remaining MPS showed unique metabolic profiles. Eight and thirteen potential high-confidence biomarkers were identified for MPS IVB and VII, respectively, which were associated with the secondary pathologic process of LSD. In vivo evaluation of predicted intermediate confidence biomarkers (β-hexosaminidase and β-glucoronidase) for MPS IVA and VI correlated with the in-silico prediction. These results show the potential of a computational human metabolic reconstruction to understand the molecular mechanisms this group of diseases, which can be used to identify new biomarkers for MPS. Copyright © 2015. Published by Elsevier Inc.Molecular Genetics and Metabolism 08/2015; DOI:10.1016/j.ymgme.2015.08.001 · 2.63 Impact Factor
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- "Calculations were made with MATLAB software version 7.12.0 (Mathworks Inc., MA) utilizing the SBML  and COBRA  toolboxes. The GNU linear programming kit (GLPK) package was used to solve LP problems. "
ABSTRACT: A novel fed-batch strategy based on a pH control system was devised in order to address some of the disadvantages associated with available control strategies for Pichia pastoris cultures. Changing settings of the controller, the t ON /t OFF time ratio, adjusted the speed in which the ammonium hydroxide was added for pH control and the sole nitrogen source. Setting the t ON /t OFF ratio to 0.5/0.5, 0.5/10 and 0.5/15 resulted in a decrease in the growth rate as the t OFF value increased. Therefore, the design allows running the culture at lower growth rates in a controlled way. Two high cell density cultures with t ON /t OFF ratio of 0.5/10 and 0.5/20 were also fed ammonia with the same controller. Setting t ON /t OFF at 0.5/10 and 0.5/20 led to an increase in final biomass and protein as the t OFF decreased. A metabolic model assessed the effect of nitrogen-limitation in high cell density cultures on the yeast metabolism. Model results show that fluxes of intracellular reactions such as glycolysis, the tricarboxylic cycle and the pentose-phosphate pathway are higher at t ON /t OFF = 0.5/10. Additionally, higher sensitivity of growth and protein production to oxygen at t ON /t OFF = 0.5/10 proves that oxygen limitation led to higher protein production in this case.Biochemical Engineering Journal 06/2015; 98:1-9. DOI:10.1016/j.bej.2015.02.016 · 2.47 Impact Factor