Simultaneous Parameters Identifiability and Estimation of an<i>E. coli</i>Metabolic Network Model

Alberton, Kese P.F.; Alberton, André L.; Maggio, Jimena Andrea Di; Estrada, Vanina; Díaz, María Soledad; Secchi, Argimiro Resende

doi:10.1155/2015/454765

Cited by 7 publications

(5 citation statements)

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“…Experimental observations of intracellular metabolite concentrations under transient response conditions were used to estimate the kinetic parameters. Recently, Pontes Freitas Alberton et al [ 15 ] and Peskov et al [ 16 ] built dynamic models based on more than 100 biochemical reactions to predict changes in steady-state flux distributions of gene knockout mutants and simulated a transient response to a short pulse of substrate addition. Khodayari et al [ 17 ] integrated the ensemble modeling formalism with an efficient genetic algorithm-based technique, which satisfied the steady-state experimental flux data for a wild type (WT) and seven mutant strains in a continuous culture.…”

Section: Introductionmentioning

confidence: 99%

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

et al. 2016

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BackgroundA kinetic model provides insights into the dynamic response of biological systems and predicts how their complex metabolic and gene regulatory networks generate particular functions. Of many biological systems, Escherichia coli metabolic pathways have been modeled extensively at the enzymatic and genetic levels, but existing models cannot accurately reproduce experimental behaviors in a batch culture, due to the inadequate estimation of a specific cell growth rate and a large number of unmeasured parameters.ResultsIn this study, we developed a detailed kinetic model for the central carbon metabolism of E. coli in a batch culture, which includes the glycolytic pathway, tricarboxylic acid cycle, pentose phosphate pathway, Entner-Doudoroff pathway, anaplerotic pathway, glyoxylate shunt, oxidative phosphorylation, phosphotransferase system (Pts), non-Pts and metabolic gene regulations by four protein transcription factors: cAMP receptor, catabolite repressor/activator, pyruvate dehydrogenase complex repressor and isocitrate lyase regulator. The kinetic parameters were estimated by a constrained optimization method on a supercomputer. The model estimated a specific growth rate based on reaction kinetics and accurately reproduced the dynamics of wild-type E. coli and multiple genetic mutants in a batch culture.ConclusionsThis model overcame the intrinsic limitations of existing kinetic models in a batch culture, predicted the effects of multilayer regulations (allosteric effectors and gene expression) on central carbon metabolism and proposed rationally designed fast-growing cells based on understandings of molecular processes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-016-0511-x) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

et al. 2016

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“…bacteria (Reeves and Sols, 1973;Bennett et al, 2009;Flamholz et al, 2013;Alberton et al, 2015)." "However, modeling in detail the glycolysis kinetics and its regulation is a difficult task due to its high complexity.…”

Section: Dynamic Models For the Oscillatory Glycolysis And For The Osmentioning

confidence: 99%

In silico Determination of Some Conditions Leading to Glycolytic Oscillations and Their Interference With Some Other Processes in E. coli Cells

Maria

2020

Front. Chem.

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Autonomous oscillations of species levels in the glycolysis express the self-control of this essential cellular pathway belonging to the central carbon metabolism (CCM), and this phenomenon takes place in a large number of bacteria. Oscillations of glycolytic intermediates in living cells occur according to the environmental conditions and to the cell characteristics, especially the adenosine triphosphate (ATP) recovery system. Determining the conditions that lead to the occurrence and maintenance of the glycolytic oscillations can present immediate practical applications. Such a model-based analysis allows in silico (model-based) design of genetically modified microorganisms (GMO) with certain characteristics of interest for the biosynthesis industry, medicine, etc. Based on our kinetic model validated in previous works, this paper aims to in silico identify operating parameters and cell factors leading to the occurrence of stable glycolytic oscillations in the Escherichia coli cells. As long as most of the glycolytic intermediates are involved in various cellular metabolic pathways belonging to the CCM, evaluation of the dynamics and average level of its intermediates is of high importance for further applicative analyses. As an example, by using a lumped kinetic model for tryptophan (TRP) synthesis from literature, and its own kinetic model for the oscillatory glycolysis, this paper highlights the influence of glycolytic oscillations on the oscillatory TRP synthesis through the PEP (phosphoenolpyruvate) glycolytic node shared by the two oscillatory processes. The numerical analysis allows further TRP production maximization in a fed-batch bioreactor (FBR).

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“…Pep is also the starting point for the synthesis of essential aminoacids such as tryptophan, cysteine, arginine, serine, etc. 15,16 Due to the tremendous importance of this metabolic process in simulating the cell CCM, intense efforts have been made both in the experimental study, and in modeling the glycolysis dynamics in Escherichia coli, [17][18][19][20] and other cell types.…”

Section: Kinetic Model Of Glycolysis In the E Coli Prokaryotic Bacteriamentioning

confidence: 99%

Model-based Identification of Some Conditions Leading to Glycolytic Oscillations in E. coli Cells

Maria

Mihalachi

Gîjiu

2019

Chem.Biochem.Eng.Q.

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Autonomous oscillations of glycolytic intermediate concentrations reflect the dynamics of the control and regulation of this major catabolic pathway, and this phenomenon has been reported in a broad range of bacteria. Understanding glycolytic oscillations might therefore prove crucial for the general understanding of the regulation of cell metabolism with immediate practical applications, allowing in silico design of modified cells with desirable 'motifs' of practical applications in the biosynthesis industry, environmental engineering, and medicine. By using a kinetic model from literature, this paper is aiming at in silico (model-based) identification of some conditions leading to the occurrence of stable glycolytic oscillations in the E. coli cells.

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Simultaneous Parameters Identifiability and Estimation of anE. coliMetabolic Network Model

Cited by 7 publications

References 40 publications

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

Development of an accurate kinetic model for the central carbon metabolism of Escherichia coli

In silico Determination of Some Conditions Leading to Glycolytic Oscillations and Their Interference With Some Other Processes in E. coli Cells

Model-based Identification of Some Conditions Leading to Glycolytic Oscillations in E. coli Cells

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