A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis
Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper,...
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Published in | Bioprocess and biosystems engineering Vol. 41; no. 5; pp. 641 - 655 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.05.2018
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 1615-7591 1615-7605 1615-7605 |
DOI | 10.1007/s00449-018-1899-y |
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Abstract | Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for
Escherichia coli
and (2) for actual experimental data collected from the batch fermentation of
Bordetella Pertussis
(whooping cough). |
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AbstractList | Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough).Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough). Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough). Dynamic flux balance analysis (DFBA) has become an instrumental modeling tool for describing the dynamic behavior of bioprocesses. DFBA involves the maximization of a biologically meaningful objective subject to kinetic constraints on the rate of consumption/production of metabolites. In this paper, we propose a systematic data-based approach for finding both the biological objective function and a minimum set of active constraints necessary for matching the model predictions to the experimental data. The proposed algorithm accounts for the errors in the experiments and eliminates the need for ad hoc choices of objective function and constraints as done in previous studies. The method is illustrated for two cases: (1) for in silico (simulated) data generated by a mathematical model for Escherichia coli and (2) for actual experimental data collected from the batch fermentation of Bordetella Pertussis (whooping cough). |
Author | Budman, Hector M. Nikdel, Ali Braatz, Richard D. |
Author_xml | – sequence: 1 givenname: Ali surname: Nikdel fullname: Nikdel, Ali organization: Department of Chemical Engineering, University of Waterloo – sequence: 2 givenname: Richard D. surname: Braatz fullname: Braatz, Richard D. organization: Department of Chemical Engineering, Massachusetts Institute of Technology – sequence: 3 givenname: Hector M. surname: Budman fullname: Budman, Hector M. email: hbudman@uwaterloo.ca organization: Department of Chemical Engineering, University of Waterloo |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29387937$$D View this record in MEDLINE/PubMed |
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CitedBy_id | crossref_primary_10_5194_gmd_16_1683_2023 crossref_primary_10_1016_j_cej_2024_157852 crossref_primary_10_1016_j_compchemeng_2020_107070 crossref_primary_10_1016_j_ifacol_2021_08_258 crossref_primary_10_1016_j_ifacol_2024_08_367 crossref_primary_10_3390_pr9091577 crossref_primary_10_1016_j_ifacol_2019_06_042 crossref_primary_10_1007_s00449_018_2002_4 crossref_primary_10_1016_j_compchemeng_2018_07_013 |
Cites_doi | 10.1002/bit.260450110 10.1263/jbb.105.1 10.1002/(SICI)1097-0290(19971120)56:4<398::AID-BIT6>3.0.CO;2-J 10.1016/S0006-3495(02)73903-9 10.1002/bit.10617 10.1016/j.biologicals.2005.12.001 10.1038/nrm2030 10.1038/msb4100162 10.1093/bioinformatics/btl619 10.1002/btpr.1675 10.1006/jtbi.2000.1073 10.1002/btpr.1949 10.1038/nbt.1614 10.1016/S0022-5193(05)80161-4 10.1002/9781119188902 10.1096/fasebj.11.11.9285481 10.1016/j.jprocont.2012.09.001 10.1371/journal.pone.0068124 10.1186/1471-2105-9-43 10.1371/journal.pcbi.1004899 |
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References | Jaqaman, Danuser (CR2) 2006; 7 Shuler, Kargi (CR19) 1992 CR4 Mahadevan, Edwards, Doyle (CR7) 2002; 83 CR18 Budman (CR21) 2013; 29 CR16 Sanchez, Saez (CR8) 2014; 30 Schuetz, Kuepfer, Sauer (CR10) 2007; 3 CR14 Llaneras, Picó (CR15) 2008; 105 Thalen (CR20) 2006; 34 Varma, Palsson (CR6) 1995; 45 Burgard, Maranas (CR12) 2003; 82 Maranas, Zomorrodi (CR17) 2016 Knorr, Jain, Srivastava (CR11) 2007; 23 Llaneras, Sala, Picó (CR5) 2012; 22 Pramanik, Keasling (CR9) 1997; 56 Orth, Thiele, Palsson (CR3) 2010; 28 Savinell, Palsson (CR13) 1992; 154 Weiss (CR22) 1997; 11 Schilling, Letscher, Palsson (CR1) 2000; 203 AL Knorr (1899_CR11) 2007; 23 F Llaneras (1899_CR15) 2008; 105 CH Schilling (1899_CR1) 2000; 203 AP Burgard (1899_CR12) 2003; 82 JM Savinell (1899_CR13) 1992; 154 ML Shuler (1899_CR19) 1992 1899_CR4 F Llaneras (1899_CR5) 2012; 22 CD Maranas (1899_CR17) 2016 R Schuetz (1899_CR10) 2007; 3 JN Weiss (1899_CR22) 1997; 11 R Mahadevan (1899_CR7) 2002; 83 1899_CR16 A Varma (1899_CR6) 1995; 45 1899_CR18 CEG Sanchez (1899_CR8) 2014; 30 1899_CR14 JD Orth (1899_CR3) 2010; 28 J Pramanik (1899_CR9) 1997; 56 H Budman (1899_CR21) 2013; 29 K Jaqaman (1899_CR2) 2006; 7 M Thalen (1899_CR20) 2006; 34 |
References_xml | – volume: 45 start-page: 69 issue: 1 year: 1995 end-page: 79 ident: CR6 article-title: Parametric sensitivity of stoichiometric flux balance models applied to wild-type metabolism publication-title: Biotechnol Bioeng doi: 10.1002/bit.260450110 – volume: 105 start-page: 1 issue: 1 year: 2008 end-page: 11 ident: CR15 article-title: Stoichiometric modelling of cell metabolism publication-title: J Biosci Bioeng doi: 10.1263/jbb.105.1 – volume: 56 start-page: 398 issue: 4 year: 1997 end-page: 421 ident: CR9 article-title: Stoichiometric model of metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements publication-title: Biotechnol Bioeng doi: 10.1002/(SICI)1097-0290(19971120)56:4<398::AID-BIT6>3.0.CO;2-J – ident: CR18 – volume: 83 start-page: 1331 issue: 3 year: 2002 end-page: 1340 ident: CR7 article-title: Dynamic flux balance analysis of diauxic growth in publication-title: Biophys J doi: 10.1016/S0006-3495(02)73903-9 – volume: 82 start-page: 670 issue: 6 year: 2003 end-page: 677 ident: CR12 article-title: Optimization-based framework for inferring and testing hypothesized metabolic objective functions publication-title: Biotechnol Bioeng doi: 10.1002/bit.10617 – volume: 34 start-page: 289 issue: 4 year: 2006 end-page: 297 ident: CR20 article-title: Fed-batch cultivation of : metabolism and Pertussis Toxin production publication-title: Biologicals doi: 10.1016/j.biologicals.2005.12.001 – volume: 7 start-page: 813 issue: 11 year: 2006 end-page: 819 ident: CR2 article-title: Linking data to models: data regression publication-title: Nat Rev Mol Cell Biol doi: 10.1038/nrm2030 – volume: 3 start-page: 119 year: 2007 ident: CR10 article-title: Systematic evaluation of objective functions for predicting intracellular fluxes in publication-title: Mol Syst Biol doi: 10.1038/msb4100162 – volume: 23 start-page: 351 issue: 3 year: 2007 end-page: 357 ident: CR11 article-title: Bayesian-based selection of metabolic objective functions publication-title: Bioinformatics doi: 10.1093/bioinformatics/btl619 – ident: CR4 – ident: CR14 – ident: CR16 – start-page: 16+479 s year: 1992 ident: CR19 publication-title: Bioprocess engineering: basic concepts. Prentice Hall international series in the physical and chemical engineering sciences – volume: 29 start-page: 520 issue: 2 year: 2013 end-page: 531 ident: CR21 article-title: A dynamic metabolic flux balance based model of fed-batch fermentation of publication-title: Biotechnol Prog doi: 10.1002/btpr.1675 – volume: 203 start-page: 229 issue: 3 year: 2000 end-page: 248 ident: CR1 article-title: Theory for the systemic definition of metabolic pathways and their use in interpreting metabolic function from a pathway-oriented perspective publication-title: J Theor Biol doi: 10.1006/jtbi.2000.1073 – volume: 30 start-page: 985 issue: 5 year: 2014 end-page: 991 ident: CR8 article-title: Comparison and analysis of objective functions in flux balance analysis publication-title: Biotechnol Prog doi: 10.1002/btpr.1949 – volume: 28 start-page: 245 issue: 3 year: 2010 end-page: 248 ident: CR3 article-title: What is flux balance analysis? publication-title: Nat Biotechnol doi: 10.1038/nbt.1614 – volume: 154 start-page: 421 issue: 4 year: 1992 end-page: 454 ident: CR13 article-title: Network analysis of intermediary metabolism using linear optimization.1. Development of mathematical formalism publication-title: J Theor Biol doi: 10.1016/S0022-5193(05)80161-4 – year: 2016 ident: CR17 publication-title: Optimization methods in metabolic networks doi: 10.1002/9781119188902 – volume: 11 start-page: 835 issue: 11 year: 1997 end-page: 841 ident: CR22 article-title: The Hill equation revisited: uses and misuses publication-title: Faseb J doi: 10.1096/fasebj.11.11.9285481 – volume: 22 start-page: 1946 issue: 10 year: 2012 end-page: 1955 ident: CR5 article-title: Dynamic estimations of metabolic fluxes with constraint-based models and possibility theory publication-title: J Process Control doi: 10.1016/j.jprocont.2012.09.001 – volume: 30 start-page: 985 issue: 5 year: 2014 ident: 1899_CR8 publication-title: Biotechnol Prog doi: 10.1002/btpr.1949 – ident: 1899_CR16 – volume-title: Optimization methods in metabolic networks year: 2016 ident: 1899_CR17 doi: 10.1002/9781119188902 – volume: 29 start-page: 520 issue: 2 year: 2013 ident: 1899_CR21 publication-title: Biotechnol Prog doi: 10.1002/btpr.1675 – ident: 1899_CR18 doi: 10.1371/journal.pone.0068124 – volume: 22 start-page: 1946 issue: 10 year: 2012 ident: 1899_CR5 publication-title: J Process Control doi: 10.1016/j.jprocont.2012.09.001 – volume: 105 start-page: 1 issue: 1 year: 2008 ident: 1899_CR15 publication-title: J Biosci Bioeng doi: 10.1263/jbb.105.1 – volume: 83 start-page: 1331 issue: 3 year: 2002 ident: 1899_CR7 publication-title: Biophys J doi: 10.1016/S0006-3495(02)73903-9 – start-page: 16+479 s volume-title: Bioprocess engineering: basic concepts. Prentice Hall international series in the physical and chemical engineering sciences year: 1992 ident: 1899_CR19 – volume: 45 start-page: 69 issue: 1 year: 1995 ident: 1899_CR6 publication-title: Biotechnol Bioeng doi: 10.1002/bit.260450110 – volume: 3 start-page: 119 year: 2007 ident: 1899_CR10 publication-title: Mol Syst Biol doi: 10.1038/msb4100162 – ident: 1899_CR14 doi: 10.1186/1471-2105-9-43 – volume: 23 start-page: 351 issue: 3 year: 2007 ident: 1899_CR11 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btl619 – volume: 34 start-page: 289 issue: 4 year: 2006 ident: 1899_CR20 publication-title: Biologicals doi: 10.1016/j.biologicals.2005.12.001 – volume: 11 start-page: 835 issue: 11 year: 1997 ident: 1899_CR22 publication-title: Faseb J doi: 10.1096/fasebj.11.11.9285481 – volume: 203 start-page: 229 issue: 3 year: 2000 ident: 1899_CR1 publication-title: J Theor Biol doi: 10.1006/jtbi.2000.1073 – volume: 154 start-page: 421 issue: 4 year: 1992 ident: 1899_CR13 publication-title: J Theor Biol doi: 10.1016/S0022-5193(05)80161-4 – volume: 7 start-page: 813 issue: 11 year: 2006 ident: 1899_CR2 publication-title: Nat Rev Mol Cell Biol doi: 10.1038/nrm2030 – ident: 1899_CR4 doi: 10.1371/journal.pcbi.1004899 – volume: 82 start-page: 670 issue: 6 year: 2003 ident: 1899_CR12 publication-title: Biotechnol Bioeng doi: 10.1002/bit.10617 – volume: 28 start-page: 245 issue: 3 year: 2010 ident: 1899_CR3 publication-title: Nat Biotechnol doi: 10.1038/nbt.1614 – volume: 56 start-page: 398 issue: 4 year: 1997 ident: 1899_CR9 publication-title: Biotechnol Bioeng doi: 10.1002/(SICI)1097-0290(19971120)56:4<398::AID-BIT6>3.0.CO;2-J |
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SubjectTerms | algorithms batch fermentation Biomass Biotechnology Bordetella pertussis Chemical engineering Chemistry Chemistry and Materials Science Computer simulation Constraint modelling data collection E coli Environmental Engineering/Biotechnology Enzymes Escherichia coli Experimental data Fermentation Food Science Industrial and Production Engineering Industrial Chemistry/Chemical Engineering Mathematical models Metabolism Metabolites Model matching Objective function Optimization Pertussis Research Paper whooping cough |
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Title | A systematic approach for finding the objective function and active constraints for dynamic flux balance analysis |
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