Mathematical and Computational Analysis of Central Carbon Pathways for Efficient Metabolic Engineering

Vassily Hatzimanikatis
Northwestern University
2145 Sheridan Road E136
Evanston, IL 60208-3120
Phone: 847-491-5357
Fax: 847-491-3728
Email: vassily@northwestern.edu

The availability of the genome sequence for an organism and the application bioinformatics analysis allow the reconstruction of the biochemical networks present in this organism. Based on this knowledge and on information from experimental studies on metabolic fluxes, the intracellular metabolic fluxes can be accurately estimated. However, knowledge about the (steady state) fluxes in a biochemical network does not allow the determination of the responses of the network to changes in its kinetic parameters, such as changes in the activity of the participating enzymes.

In order to overcome this limitation we have developed a bioinformatics framework that employs knowledge about the stoichiometry of biochemical networks and the estimated values of the associated metabolic fluxes, modeling concepts from metabolic control analysis, computational methods, and nonparametric statistics. This framework allows a quantitative ranking of the enzyme manipulations with respect to their probabilities of success in achieving a desired change in metabolic fluxes. Furthermore, we can also characterize and quantify the robustness of a biochemical network in terms of its stability characteristic.

The utility and power of the methodology are illustrated on two examples: a branched biosynthetic pathway and the glycolytic pathway in yeast.

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