A reliable simulator for dynamic flux balance analysis

Dynamic flux balance analysis (DFBA) provides a platform for detailed design, control and optimization of biochemical process technologies. It is a promising modeling framework that combines genome‐scale metabolic network analysis with dynamic simulation of the extracellular environment. Dynamic flux balance analysis assumes that the intracellular species concentrations are in equilibrium with the extracellular environment. The resulting underdetermined stoichiometric model is solved under the assumption of a biochemical objective such as growth rate maximization. The model of the metabolism is coupled with the dynamic mass balance equations of the extracellular environment via expressions for the rates of substrate uptake and product excretion, which imposes additional constraints on the linear program (LP) defined by growth rate maximization of the metabolism. The linear program is embedded into the dynamic model of the bioreactor, and together with the additional constraints this provides an accurate model of the substrate consumption, product secretion, and biomass production during operation. A DFBA model consists of a system of ordinary differential equations for which the evaluation of the right‐hand side requires not only function evaluations, but also the solution of one or more linear programs. The numerical tool presented here accurately and efficiently simulates large‐scale dynamic flux balance models. The main advantages that this approach has over existing implementation are that the integration scheme has a variable step size, that the linear program only has to be solved when qualitative changes in the optimal flux distribution of the metabolic network occur, and that it can reliably simulate behavior near the boundary of the domain where the model is defined. This is illustrated through large‐scale examples taken from the literature. Biotechnol. Bioeng. 2013; 110: 792–802. © 2012 Wiley Periodicals, Inc.

[1]  B. Palsson,et al.  Regulation of gene expression in flux balance models of metabolism. , 2001, Journal of theoretical biology.

[2]  Adam M. Feist,et al.  Reconstruction of biochemical networks in microorganisms , 2009, Nature Reviews Microbiology.

[3]  B. Palsson,et al.  Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110 , 1994, Applied and environmental microbiology.

[4]  M. Domach,et al.  Simple constrained‐optimization view of acetate overflow in E. coli , 1990, Biotechnology and bioengineering.

[5]  M A Henson,et al.  Steady-state and dynamic flux balance analysis of ethanol production by Saccharomyces cerevisiae. , 2009, IET systems biology.

[6]  B. Palsson,et al.  An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) , 2003, Genome Biology.

[7]  Lorenz T. Biegler,et al.  Parameter estimation in metabolic flux balance models for batch fermentation—Formulation & Solution using Differential Variational Inequalities (DVIs) , 2006, Ann. Oper. Res..

[8]  P. I. Barton,et al.  DAEPACK: An Open Modeling Environment for Legacy Models , 2000 .

[9]  Radhakrishnan Mahadevan,et al.  Genome-scale metabolic modeling of a clostridial co-culture for consolidated bioprocessing. , 2010, Biotechnology journal.

[10]  Ryan Nolan,et al.  Dynamic model of CHO cell metabolism. , 2011, Metabolic engineering.

[11]  Marty D Matlock,et al.  Measuring variability in trophic status in the Lake Waco/Bosque River Watershed , 2008, Journal of biological engineering.

[12]  B. Palsson,et al.  Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems. , 2000, Biotechnology and bioengineering.

[13]  R. Mahadevan,et al.  The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. , 2003, Metabolic engineering.

[14]  Radhakrishnan Mahadevan,et al.  Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments , 2011, The ISME Journal.

[15]  Adam M. Feist,et al.  A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 , 2011, Molecular systems biology.

[16]  Nagasuma R. Chandra,et al.  Flux balance analysis of biological systems: applications and challenges , 2009, Briefings Bioinform..

[17]  Evangelos Simeonidis,et al.  Flux balance analysis: a geometric perspective. , 2009, Journal of theoretical biology.

[18]  Adam L. Meadows,et al.  Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation. , 2010, Metabolic engineering.

[19]  F. Doyle,et al.  Dynamic flux balance analysis of diauxic growth in Escherichia coli. , 2002, Biophysical journal.

[20]  Jeffrey D Orth,et al.  What is flux balance analysis? , 2010, Nature Biotechnology.

[21]  B O Palsson,et al.  Flux-balance analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints. , 2001, American journal of physiology. Regulatory, integrative and comparative physiology.

[22]  David E Block,et al.  A dynamic, genome-scale flux model of Lactococcus lactis to increase specific recombinant protein expression. , 2009, Metabolic engineering.

[23]  Timothy J. Hanly,et al.  Dynamic flux balance modeling of microbial co‐cultures for efficient batch fermentation of glucose and xylose mixtures , 2011, Biotechnology and bioengineering.

[24]  Timothy J. Hanly,et al.  Dynamic flux balance modeling of S. cerevisiae and E. coli co-cultures for efficient consumption of glucose/xylose mixtures , 2011, Applied Microbiology and Biotechnology.

[25]  M. A. Henson,et al.  Genome‐scale analysis of Saccharomyces cerevisiae metabolism and ethanol production in fed‐batch culture , 2007, Biotechnology and bioengineering.

[26]  Shaoqun Zeng,et al.  Dynamic analysis of optimality in myocardial energy metabolism under normal and ischemic conditions , 2006, Molecular systems biology.

[27]  Kenneth J. Kauffman,et al.  Advances in flux balance analysis. , 2003, Current opinion in biotechnology.

[28]  Michael A Henson,et al.  Optimization of Fed‐Batch Saccharomyces cerevisiae Fermentation Using Dynamic Flux Balance Models , 2006, Biotechnology progress.

[29]  Paul I. Barton,et al.  State event location in differential-algebraic models , 1996, TOMC.

[30]  B. Palsson,et al.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[31]  P. Vanrolleghem,et al.  Dynamic Metabolic Flux Analysis Demonstrated on Cultures Where the Limiting Substrate Is Changed from Carbon to Nitrogen and Vice Versa , 2010, Journal of biomedicine & biotechnology.

[32]  Lijun Luo,et al.  Photosynthetic metabolism of C3 plants shows highly cooperative regulation under changing environments: A systems biological analysis , 2009, Proceedings of the National Academy of Sciences.

[33]  Bernhard O. Palsson,et al.  BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions , 2010, BMC Bioinformatics.

[34]  Sarah A. Lee,et al.  A co-fermentation strategy to consume sugar mixtures effectively , 2008, Journal of biological engineering.

[35]  James A. Eddy,et al.  Accomplishments in genome‐scale in silico modeling for industrial and medical biotechnology , 2009, Biotechnology journal.

[36]  Erwin P. Gianchandani,et al.  Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks , 2008, PLoS Comput. Biol..

[37]  Markus J. Herrgård,et al.  Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. , 2004, Genome research.

[38]  W. R. Cluett,et al.  Dynamic metabolic engineering for increasing bioprocess productivity. , 2008, Metabolic engineering.

[39]  Claudio Bruno,et al.  Coupling kinetic expressions and metabolic networks for predicting wine fermentations , 2007, Biotechnology and bioengineering.

[40]  G. Church,et al.  Analysis of optimality in natural and perturbed metabolic networks , 2002 .

[41]  Eduardo Agosin,et al.  Modeling of yeast metabolism and process dynamics in batch fermentation , 2003, Biotechnology and bioengineering.

[42]  Eduardo Agosin,et al.  Expanding a dynamic flux balance model of yeast fermentation to genome-scale , 2011, BMC Systems Biology.