COBRA Toolbox 2.0

Abstract

Over the past decade, a growing community of researchers has emerged around the use of COnstraint-Based Reconstruction and Analysis (COBRA) methods to simulate, analyze and predict a variety of metabolic phenotypes using genome-scale models. The COBRA Toolbox, a MATLAB package for implementing COBRA methods, was presented earlier. Here we present a significant update of this in silico ToolBox. Version 2.0 of the COBRA Toolbox expands the scope of computations by including in silico analysis methods developed since its original release. New functions include: (1) network gap filling, (2) 13 C analysis, (3) metabolic engineering, (4) omics-guided analysis, and (5) visualization. As with the first version, the COBRA Toolbox reads and writes Systems Biology Markup Language formatted models. In version 2.0, we improved performance, usability, and the level of documentation. A suite of test scripts can now be used to learn the core functionality of the Toolbox and validate results. This Toolbox lowers the barrier of entry to use powerful COBRA methods.

Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates

“…The genome-derived stoichiometric P. aeruginosa model iM01056 developed by implementing the Gurobi 6 optimizer was used for FBA using the objective function of maximal biomass production [52]. FBA simulations used measured glucose uptake rates by strain PA01.…”

“…Such models are used to investigate the potential flows of carbon and other elements as well as cofactor balances and can extend to genome-wide coverage [50,52]. In addition to identifying reactions and conditions essential for growth and improving gene annotations, FBA and related tools allow the prediction of maximal growth rates and the exploration of predicted metabolic flux distributions under the assumption of different optimization strategies ("objective functions", most commonly maximal growth efficiency).…”

Metabolic engineering of Saccharomyces cerevisiae for the production of triacetic acid lactone

“…Using the iMM904 yeast metabolic network, we employed the OptKnock algorithm packaged within the Cobra Toolbox (Mo et al, 2009;Schellenberger et al, 2011). This algorithm has been designed to identify gene knockouts in an organism core model that will increase a target flux value as specified by the user (Burgard et al, 2003), and uses a bilevel optimization framework such that maximization of the target metabolite is subject to maximizing biomass flux.…”

“…After establishing an initial expression system, metabolic pathways were engineered for improved TAL biosynthesis. The computational tool OptKnock (Schellenberger et al, 2011) available in the COBRA Toolbox was used to aid the pathway engineering by identifying additional gene deletions for improved flux toward acetylCoA and malonyl-CoA. These strain modifications were evaluated independently and in combination to determine their effect on TAL production in S. cerevisiae, and final cultivations were done in fedbatch mode to increase titers.…”

Exploring biochemical pathways for mono-ethylene glycol (MEG) synthesis from synthesis gas

“…Flux balance analysis (FBA) (Orth et al, 2010) was used for maximizing the MEG-production objective function in the M. thermoacetica and C. ljungdahlii models. The COBRA toolbox (Becker et al, 2007;Hyduke et al, 2011) was used for FBA-implementation, and all model simulations were conducted in the MATLAB environment (the MathWorks Inc., Natick, MA) using the IBM ILOG's CPLEX 12.5.1 optimization solver.…”