Multi-objective steady state optimization of biochemical reaction networks using a constrained genetic algorithm

A newton cooperative genetic algorithm method for in silico optimization of metabolic pathway production

This paper presents an in silico optimization method of metabolic pathway production. The metabolic pathway can be represented by a mathematical model known as the generalized mass action model, which leads to a complex nonlinear equations system. The optimization process becomes difficult when steady state and the constraints of the components in the metabolic pathway are involved. To deal with this situation, this paper presents an in silico optimization method, namely the Newton Cooperative Genetic Algorithm (NCGA). The NCGA used Newton method in dealing with the metabolic pathway, and then integrated genetic algorithm and cooperative co-evolutionary algorithm. The proposed method was experimentally applied on the benchmark metabolic pathways, and the results showed that the NCGA achieved better results compared to the existing methods.

FastPros: screening of reaction knockout strategies for metabolic engineering

Motivation: Although constraint-based flux analysis of knockout strains has facilitated the production of desirable metabolites in microbes, current screening methods have placed a limitation on the number knockouts that can be simultaneously analyzed.

Results: Here, we propose a novel screening method named FastPros. In this method, the potential of a given reaction knockout for production of a specific metabolite is evaluated by shadow pricing of the constraint in the flux balance analysis, which generates a screening score to obtain candidate knockout sets. To evaluate the performance of FastPros, we screened knockout sets to produce each metabolite in the entire Escherichia coli metabolic network. We found that 75% of these metabolites could be produced under biomass maximization conditions by adding up to 25 reaction knockouts. Furthermore, we demonstrated that using FastPros in tandem with another screening method, OptKnock, could further improve target metabolite productivity.

Availability and implementation: Source code is freely available at http://www-shimizu.ist.osaka-u.ac.jp/shimizu_lab/FastPros/, implemented in MATLAB and COBRA toolbox.

Contact:chikara.furusawa@riken.jp or shimizu@ist.osaka-u.ac.jp

Supplementary information:Supplementary data are available at Bioinformatics online.

Biochemical Systems Theory: A Review

Biochemical systems theory (BST) is the foundation for a set of analytical andmodeling tools that facilitate the analysis of dynamic biological systems. This paper depicts major developments in BST up to the current state of the art in 2012. It discusses its rationale, describes the typical strategies and methods of designing, diagnosing, analyzing, and utilizing BST models, and reviews areas of application. The paper is intended as a guide for investigators entering the fascinating field of biological systems analysis and as a resource for practitioners and experts.