A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks

Schuster, Stefan; Fell, David A.; Dandekar, Thomas

doi:10.1038/73786

Cited by 846 publications

(658 citation statements)

References 37 publications

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“…In this connection, Young and coworkers 16,17 drew on the concept of elementary flux modes, first propounded by Clarke 18 referring to various routines in the network through which external substrate is converted into various fermentation products and biomass. Further, Young and coworkers 16,17 has resolved other difficulties with the cybernetic formulation of large networks by (i) decomposing the pathways into elementary flux modes as done by Schuster et al, 19,20 (ii) by generalizing cybernetic laws using optimal control theory as shown in Young and Ramkrishna 21 to include more general objective functions, and (iii) by incorporation of global objectives such as maximizing biomass or substrate uptake rate among the various modes and to further control of reactions in each mode to enforce the maximum flux throughput. The resulting models are robust and capable of describing dynamic behavior of multiple strains as shown by Young and coworkers.…”

Section: Introductionmentioning

confidence: 99%

A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variables

Kim

Varner

Ramkrishna

2008

Biotechnology Progress

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Flux balance analysis (FBA) in combination with the decomposition of metabolic networks into elementary modes has provided a route to modeling cellular metabolism. It is dependent, however, on the availability of external fluxes such as substrate uptake or growth rate before estimates can become available of intracellular fluxes. The framework classically does not allow modeling of metabolic regulation or the formulation of dynamic models except through dynamic measurement of external fluxes. The cybernetic modeling approach of Ramkrishna and coworkers provides a dynamic framework for modeling metabolic systems because of its focus on describing regulatory processes based on cybernetic arguments and hence has the capacity to describe both external and internal fluxes. In this article, we explore the alternative of developing hybrid models combining cybernetic models for the external fluxes with the flux balance approach for estimation of the internal fluxes. The approach has the merit of the simplicity of the early cybernetic models and hence computationally facile while also providing detailed information on intracellular fluxes. The hybrid model of this article is based on elementary mode decomposition of the metabolic network. The uptake rates for the various elementary modes are combined using global cybernetic variables based on maximizing substrate uptake rates. Estimation of intracellular metabolism is based on its stoichiometric coupling with the external fluxes under the assumption of (pseudo-) steady state conditions. The set of parameters of the hybrid model was estimated with the aid of nonlinear optimization routine, by fitting simulations with dynamic experimental data on concentrations of biomass, substrate, and fermentation products. The hybrid model estimations were tested with FBA (based on measured substrate uptake rate) for two different metabolic networks (one is a reduced network which fixes ATP contribution to the biomass and maintenance requirement of ATP, and the other network is a more complex network which has a separate reaction for maintenance.) for the same experiment involving anaerobic growth of E. coli GJT001. The hybrid model estimated glucose consumption and all fermentation byproducts to better than 10%. The FBA makes similar estimations of fermentation products, however, with the exception of succinate. The simulation results show that the global cybernetic variables alone can regulate the metabolic reactions obtaining a very satisfactory fit to the measured fermentation byproducts. In view of the hybrid model's ability to predict biomass growth and fermentation byproducts of anaerobic E. coli GJT001, this reduced order model offers a computationally efficient alternative to more detailed models of metabolism and hence useful for the simulation of bioreactors.

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Section: Introductionmentioning

confidence: 99%

A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variables

Kim

Varner

Ramkrishna

2008

Biotechnology Progress

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“…Hereby, flux balance analysis can highlight the most efficient pathway through the network in order to achieve the particular objective function. Elementary flux mode analysis systematically enumerates all independent minimal pathways through a network, each a unique elementary mode, that are stoichiometrically and thermodynamically feasible [70]. All possible steady-state flux distributions through the metabolic network are nonnegative linear combinations of the set of elementary modes [71].…”

Section: Stoichiometric Modelingmentioning

confidence: 99%

Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

Wittmann

2010

Biosystems Engineering I

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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.

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“…An EFM corresponds to a minimal set of reactions that can operate at steady state, thereby using all irreversible reactions in the appropriate direction 1. Here minimal means that no reaction can be removed from the set without losing the ability to form a non‐zero steady‐state flux.…”

Section: Introductionmentioning

confidence: 99%

Which sets of elementary flux modes form thermodynamically feasible flux distributions?

et al. 2016

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Elementary flux modes (EFMs) are non‐decomposable steady‐state fluxes through metabolic networks. Every possible flux through a network can be described as a superposition of EFMs. The definition of EFMs is based on the stoichiometry of the network, and it has been shown previously that not all EFMs are thermodynamically feasible. These infeasible EFMs cannot contribute to a biologically meaningful flux distribution. In this work, we show that a set of thermodynamically feasible EFMs need not be thermodynamically consistent. We use first principles of thermodynamics to define the feasibility of a flux distribution and present a method to compute the largest thermodynamically consistent sets (LTCSs) of EFMs. An LTCS contains the maximum number of EFMs that can be combined to form a thermodynamically feasible flux distribution. As a case study we analyze all LTCSs found in Escherichia coli when grown on glucose and show that only one LTCS shows the required phenotypical properties. Using our method, we find that in our E. coli model < 10% of all EFMs are thermodynamically relevant.

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A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks

Cited by 846 publications

References 37 publications

A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variables

A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variables

Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

Which sets of elementary flux modes form thermodynamically feasible flux distributions?

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