Biological organisms often operate under conditions of limited nutrients and energy; which necessitates trade-offs among essential processes. Under certain environmental conditions, improvement in performance of one biological process might benefit some processes and/or negatively impacting the activity of others. The determination of the optimal balance of these processes requires an understanding of how system objectives affect each other. Multi-objective flux analysis (MOFA) is an important technique for solving genome-scale constraint-based models to provide a quantitative answer to this question. At its core, MOFA uses multi-objective optimization, a form of analysis used in fields ranging from engineering and economics to biology. The leading software package for conducting a plethora of different types of analyses using constraint-based models is the COBRA Toolbox for MATLAB. COBRA is widely used to simulate genome-scale metabolic models of bacterial, algal, and even human systems. However, currently COBRA does not have the capability to conduct MOFA on problems of more than 3 objectives (i.e., phase plane analysis). We have created an added tool for COBRA that performs MOFA using a novel algorithm. The code is fully compatible with the toolbox and allows users to efficiently find the optimal solution of the balance of objectives, called the Pareto frontier for a relatively high number of dimensions (n&lt;10) in a reasonable period of time on a single CPU. This development will bring the MOFA technique to a large user base and allow its use in analyzing metabolic trade-offs in complicated biological systems.

Multi-objective flux analysis software for the COBRA toolbox

253rd National Meeting (2017)

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