Development of a kinetic model for L-lysine biosynthesis in Corynebacterium glutamicum and its application to metabolic control analysis

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

Elementary flux mode (EFM) analysis is a powerful tool to represent the metabolic network structure and can be further utilized for flux analysis. The method enables characterization and quantification of feasible phenotypes in microbes. EFM analysis was employed to characterize the phenotype of Corynebacterium glutamicum to yield various amino acids. The metabolic network of C. glutamicum yielded 62 elementary modes by incorporating the accumulation of amino acids namely, lysine, alanine, valine, glutamine and glutamate. The analysis also allowed us to compute the maximum theoretical yield for the synthesis of various amino acids. These 62 elementary modes were further used to obtain optimal phenotypic space towards accumulation of biomass and lysine. The study indicated that the optimal solution space from 62 elementary modes forms a super space which incorporates various mutants including lysine producing strain of C. glutamicum. The analysis was also extended to obtain sensitivity of the network to variation in the stoichiometry of NADP in the definition of biomass.

ELECTRONIC SUPPLEMENTARY MATERIAL

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Analysis and engineering of metabolic pathway fluxes in Corynebacterium glutamicum

The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research - analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

Metabolomics: current state and evolving methodologies and tools

In recent years, metabolomics developed to an accepted and valuable tool in life sciences. Substantial improvements of analytical hardware allow metabolomics to run routinely now. Data are successfully used to investigate genotype-phenotype relations of strains and mutants. Metabolomics facilitates metabolic engineering to optimise mircoorganisms for white biotechnology and spreads to the investigation of biotransformations and cell culture. Metabolomics serves not only as a source of qualitative but also quantitative data of intra-cellular metabolites essential for the model-based description of the metabolic network operating under in vivo conditions. To collect reliable metabolome data sets, culture and sampling conditions, as well as the cells' metabolic state, are crucial. Hence, application of biochemical engineering principles and method standardisation efforts become important. Together with the other more established omics technologies, metabolomics will strengthen its claim to contribute to the detailed understanding of the in vivo function of gene products, biochemical and regulatory networks and, even more ambitious, the mathematical description and simulation of the whole cell in the systems biology approach. This knowledge will allow the construction of designer organisms for process application using biotransformation and fermentative approaches making effective use of single enzymes, whole microbial and even higher cells.

A phenomenological model to represent the kinetics of growth by Corynebacterium glutamicum for lysine production

Corynebacterium glutamicum is commonly used for lysine production. In the last decade, several metabolic engineering approaches have been successfully applied to C. glutamicum. However, only few studies have been focused on the kinetics of growth and lysine production. Here, we present a phenomenological model that captures the growth and lysine production during different phases of fermentation at various initial dextrose concentrations. The model invokes control coefficients to capture the dynamics of lysine and trehalose synthesis. The analysis indicated that maximum lysine productivity can be obtained using 72 g/L of initial dextrose concentration in the media, while growth was optimum at 27 g/L of dextrose concentration. The predictive capability was demonstrated through a two-stage fermentation strategy to enhance the productivity of lysine by 1.5 times of the maximum obtained in the batch fermentation. Two-stage fermentation indicated that the kinetic model could be further extended to predict the optimal feeding strategy for fed-batch fermentation.

Modeling of enzyme production kinetics

Models of single cells, cell populations, and cultures can be most useful in organizing information in a comprehensive system description, as well as in optimizing and controlling actual production operations. Models discussed in this article are of various degrees of biological structure and mathematical complexity. The models are developed based on the biomass formation, substrate consumption, and product formation. the potentials asn the limitations of all the models have been reported. The parameter estimation by different methods has been discussed in this communication. These parameters will be helpful to explore the areas where future-modeling studies may be especially valuable.

Effects of the changes in enzyme activities on metabolic flux redistribution around the 2-oxoglutarate branch in glutamate production by Corynebacterium glutamicum

An experimental method for metabolic control analysis (MCA) was applied to the investigation of a metabolic network of glutamate production by Corynebacterium glutamicum. A metabolic reaction (MR) model was constructed and used for flux distribution analysis (MFA). The flux distribution at a key branch point, 2-oxoglutarate, was investigated in detail. Activities of isocitrate dehydrogenase (ICDH), glutamate dehydrogenase (GDH), and 2-oxoglutarate dehydrogenase complex (ODHC) around this the branch point were changed, using two genetically engineered strains (one with enhanced ICDH activity and the other with enhanced GDH activity) and by controlling environmental conditions (i.e. biotin-deficient conditions). The mole flux distribution was determined by an MR model, and the effects of the changes in the enzyme activities on the mole flux distribution were compared. Even though both GDH and ICDH activities were enhanced, the mole flux distribution was not significantly changed. When the ODHC activity was attenuated, the flux through ODHC decreased, and glutamate production was markedly increased. The flux control coefficients of the above three enzymes for glutamate production were determined based on changes in enzyme activities and the mole flux distributions. It was found that the factor with greatest impact on glutamate production in the metabolic network was obtained by attenuation of ODHC activity.

Control of the threonine-synthesis pathway in Escherichia coli: a theoretical and experimental approach

A computer simulation of the threonine-synthesis pathway in Escherichia coli Tir-8 has been developed based on our previous measurements of the kinetics of the pathway enzymes under near-physiological conditions. The model successfully simulates the main features of the time courses of threonine synthesis previously observed in a cell-free extract without alteration of the experimentally determined parameters, although improved quantitative fits can be obtained with small parameter adjustments. At the concentrations of enzymes, precursors and products present in cells, the model predicts a threonine-synthesis flux close to that required to support cell growth. Furthermore, the first two enzymes operate close to equilibrium, providing an example of a near-equilibrium feedback-inhibited enzyme. The predicted flux control coefficients of the pathway enzymes under physiological conditions show that the control of flux is shared between the first three enzymes: aspartate kinase, aspartate semialdehyde dehydrogenase and homoserine dehydrogenase, with no single activity dominating the control. The response of the model to the external metabolites shows that the sharing of control between the three enzymes holds across a wide range of conditions, but that the pathway flux is sensitive to the aspartate concentration. When the model was embedded in a larger model to simulate the variable demands for threonine at different growth rates, it showed the accumulation of free threonine that is typical of the Tir-8 strain at low growth rates. At low growth rates, the control of threonine flux remains largely with the pathway enzymes. As an example of the predictive power of the model, we studied the consequences of over-expressing different enzymes in the pathway.