Pathway Analysis and Optimization in Metabolic Engineering

Abstract

Facility in the targeted manipulation of the genetic and metabolic composition of organisms, combined with unprecedented computational power, is forging a niche for a new subspecialty of biotechnology called metabolic engineering. First published in 2002, this book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways, demonstrates the need for effective systems models, and discusses their design and analysis, while placing special emphasis on optimization. The authors propose power-law models and methods of biochemical systems theory toward these ends. All concepts are derived from first principles, and the text is richly illustrated with numerous graphs and examples throughout. Special features include: nontechnical and technical introductions to models of biochemical systems; a review of basic methods of model design and analysis; concepts of optimization; and detailed case studies.

A modified iterative IOM approach for optimization of biochemical systems

“…The kinetic order sensitivities can also be calculated by differentiation of the explicit solution (Voit, 2000;Torres and Voit, 2002). In a good model the sensitivities must be small, otherwise high sensitivities (i.e., absolute values upper than 50) (Vera et al, 2003b) indicate that the model is ill-determined.…”

“…Much research has been directed toward the development of model-based optimization strategies, including the mathematical foundations of such approaches (Voit, 1992;Regan et al, 1993;Hatzimanikatis et al, 1996aHatzimanikatis et al, , 1996bTorres et al, 1996Torres et al, , 1997Petkov and Maranas, 1997;Voit and Del Signore, 2001;Torres and Voit, 2002;Marín-Sanguino and Torres, 2003;Vera et al, _____________________ 2003a;Chang and Sahinidis, 2005) and their application to some processes (Heinrich et al, 1991;Hatzimanikatis et al, 1998;Torres, 2000, 2002;Alvarez-Vasquez et al, 2000;Vera et al, 2003b;Sevilla et al, 2005). One successful approach to the optimization of biochemical systems is the indirect optimization method (IOM) (Torres et al, 1996(Torres et al, , 1997Voit, 1992;Marín-Sanguino and Torres, 2003;Vera et al, 2003a), which is based on the approximation of the original nonlinear differential equation models describing the biochemical process as an S-system or a GMA system.…”

Reconstructing Metabolic Networks Using Interval Analysis

“…Each component of an S-system is made up of one positive and one negative term, corresponding to the production and consumption of the substance x i , respectively. In essence, an S-system is a condensed version of a more general GMA -General Mass Action -model, obtained by aggregating individual reactions into the net processes of synthesis and degradation, see [15]. Using the following short-hand notation for the parameters…”

“…Following [17], the search region for each of the kinetic orders g ij , and h ij was set to contain [−1, +1], whereas the rate orders α i and β i were sought for within [0,15]. The stopping tolerance (i.e., the diameters of the final parameter intervals) was set to 1 × 10 −3 .…”

Development and Application of a Modified Genetic Algorithm for Estimating Parameters in GMA Models

“…Within this formalism, several choices are available for the formulation of biochemical pathways, and the most successful one is Generalized Mass Action (GMA) system [5]. The basic concepts of the power-law formalism have been described many times [5] [8].…”