Phenotypic characterization of Corynebacterium glutamicum using elementary modes towards synthesis of amino acids

Abstract

The online version of this article (doi:10.1007/s11693-011-9073-8) contains supplementary material, which is available to authorized users.

Structural and dynamical analysis of biological networks

“…When the target is maximization of the production of some compound, the compound is usually included in the objective function to enforce solutions where its production is active. Other formulations for the objective function may be designed to mimic disparate growth conditions, not necessarily focusing on fast growth [81][82][83][84][85][86][87][88][89][90][91].…”

A graph-based approach to analyze flux-balanced pathways in metabolic networks

“…EFMs [5,6] have been used in several biological applications such as bioengineering [7], phenotypic characterization [8], drug target prediction [9] and strain design [10]. The incorporation of kinetic analysis into EFMs enables a more complete description of cellular functions for which kinetics play a dominant role [11].…”

Lysine overproducing Corynebacterium glutamicum is characterized by a robust linear combination of two optimal phenotypic states

“…Studies on lysine synthesis by C. glutamicum have mainly focused on determining metabolic flux distribution of the network as well as at various branch points during the growth and overproduction of lysine (Vallino and Stephanopoulos 1993;Vallino and Stephanopoulos 1994a, b) and on the influence of environmental conditions, such as, salt stress (Rajvanshi and Venkatesh 2011;Benjamin et al 2010;Guillouet and Engasser 1995a, b Skjerdal et al 1995, 1996Kempf and Bremer 1998;Morbach and Kramer 2003;Varela et al 2003;Heermann and Jung 2004;Varela et al 2004), nutritional conditions with use of variety of sugars and organic acids as carbon sources (Wittmann et al 2004;Dominguez et al 1998;Cocaign and Lindley 1995;Gerstmeir et al 2003), on the physiological behavior and in vivo flux distribution of C. glutamicum. Various methodologies, such as, 13 C flux analysis (Wittmann et al 2004;Wendisch et al 2002), flux balance analysis (Takac et al 1998), metabolite balancing technique (Varela et al 2003;Vallino andStephanopoulos 1993, 1994a, b) and metabolic pathway analysis (elementary mode analysis (EMA) and extreme pathway analysis) (Rajvanshi and Venkatesh 2011;Radhakrishnan et al 2010;Gayen and Venkatesh 2006;Gayen et al 2007;Chen et al 2009;Kromer et al 2006) have been used for flux determination. EMA is a promising mathematical tool to represent the structure of a metabolic network and has been used to evaluate steady state flux distribution for different nutritional and environmental conditions (Schuster et al 1999;Edwards and Palsson 2000;Stelling et al 2002;…”

“…Various methodologies, such as, 13 C flux analysis (Wittmann et al 2004;Wendisch et al 2002), flux balance analysis (Takac et al 1998), metabolite balancing technique (Varela et al 2003;Vallino andStephanopoulos 1993, 1994a, b) and metabolic pathway analysis (elementary mode analysis (EMA) and extreme pathway analysis) (Rajvanshi and Venkatesh 2011;Radhakrishnan et al 2010;Gayen and Venkatesh 2006;Gayen et al 2007;Chen et al 2009;Kromer et al 2006) have been used for flux determination. EMA is a promising mathematical tool to represent the structure of a metabolic network and has been used to evaluate steady state flux distribution for different nutritional and environmental conditions (Schuster et al 1999;Edwards and Palsson 2000;Stelling et al 2002;Klamt and Stelling 2003;Papin et al 2004;Poolman et al 2004;Gayen and Venkatesh 2006;Schwartz and Kanehisa 2006;Radhakrishnan et al 2010;Rajvanshi and Venkatesh 2011). In addition to analyzing metabolic network and in identifying target genes for manipulations, elementary modes also give insights about the redundancy and robustness in the network.…”

“…Mutation causing inactivation of homoserine dehydrogenase (marked by X) resulted in inhibition of homoserine biosynthesis. This in turn resulted in release of feedback inhibition by threonine and lysine on aspartate kinase theoretical yields and bounds on nutrient uptake rates for production of individual metabolites under the constraint of the stoichiometry of the reactions of metabolic network (Radhakrishnan et al 2010;Llaneras and Picó 2008).…”