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

FEBS Journal

Volumn 283, Issue 9, 2016, Pages 1782-1794

  Gerstl, Matthias P ^a,b   Jungreuthmayer, Christian ^a,b   Müller, Stefan ^c   Zanghellini, Jürgen ^a,b  

^a UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES   (Austria)

^b AUSTRIAN CENTRE OF INDUSTRIAL BIOTECHNOLOGY   (Austria)

^c JOHANN RADON INSTITUTE FOR COMPUTATIONAL AND APPLIED MATHEMATICS   (Austria)

Author keywords

constraint based analysis; metabolic pathway analysis; metabolomics; steady state flux cone; thermodynamics

Indexed keywords

ADENOSINE TRIPHOSPHATE; FUMARATE REDUCTASE; GLUCOSE 6 PHOSPHATE ISOMERASE; SUCCINATE DEHYDROGENASE; GLUCOSE;

ARTICLE; BIOMASS PRODUCTION; CARBON SOURCE; CULTURE MEDIUM; ELEMENTARY FLUX MODE ANALYSIS; ESCHERICHIA COLI; GLUCONEOGENESIS; GLYCOLYSIS; ION TRANSPORT; LIPID METABOLISM; METABOLIC ENGINEERING; NONHUMAN; OPERON; OXIDATIVE PHOSPHORYLATION; PENTOSE PHOSPHATE CYCLE; PHAEODACTYLUM TRICORNUTUM; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; STEADY STATE; STOICHIOMETRY; SYSTEMS BIOLOGY; THERMODYNAMICS; ALGORITHM; BIOLOGICAL MODEL; COMPUTER SIMULATION; KINETICS; METABOLISM; PHYSIOLOGY; STATISTICAL MODEL;

ADENOSINE TRIPHOSPHATE; ALGORITHMS; COMPUTER SIMULATION; ESCHERICHIA COLI; GLUCOSE; KINETICS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; THERMODYNAMICS;

EID: 84962678128     PISSN: 1742464X     EISSN: 17424658     Source Type: Journal    
DOI: 10.1111/febs.13702     Document Type: Article

References (44)

1. Schuster S, Fell DA, &, Dandekar T, (2000) A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat Biotechnol, 18, 326-332.
2. Müller S, Regensburger G, &, Steuer R, (2014) Enzyme allocation problems in kinetic metabolic networks: optimal solutions are elementary flux modes. J Theor Biol, 347, 182-190.
3. Urbanczik R, &, Wagner C, (2005) Functional stoichiometric analysis of metabolic networks. Bioinformatics 21, 4176-4180.
4. Bachem A, &, Kern W, (1992) An Introduction to Oriented Matroids. Linear Programming Duality. Springer-Verlag, Berlin.
5. N. In Combinatorial Mathematics and its Applications (Proc. Conf., Univ. North Carolina, Chapel Hill, N.C., 1967), pp. 104-127. Univ. North Carolina Press, Chapel Hill, NC.
6. Gerstl MP, Klamt S, Jungreuthmayer C, &, Zanghellini J, (2016) Exact quantification of cellular robustness in genome-scale metabolic networks. Bioinformatics 32, 730-737.
7. Trinh CT, Unrean P, &, Srienc F, (2008) Minimal Escherichia coli cell for the most efficient production of ethanol from hexoses and pentoses. Appl Environ Microbiol 74, 3634-3643
8. Hädicke O, &, Klamt S, (2011) Computing complex metabolic intervention strategies using constrained minimal cut sets. Metab Eng 13, 204-213.
9. Jungreuthmayer C, &, Zanghellini J, (2012) Designing optimal cell factories: integer programming couples elementary mode analysis with regulation. BMC Syst Biol 6, 103.
10. Nair G, Jungreuthmayer C, Hanscho M, &, Zanghellini J, (2015) Designing minimal microbial strains of desired functionality using a genetic algorithm. Algorithms Mol Biol 10, 29.
11. Ruckerbauer DE, Jungreuthmayer C, &, Zanghellini J, (2014) Design of optimally constructed metabolic networks of minimal functionality. PLoS One 9, e92583.
12. Ruckerbauer DE, Jungreuthmayer C, &, Zanghellini J, (2015) Predicting genetic engineering targets with elementary flux mode analysis: a review of four current methods. New Biotechnol 32, 534-546.
13. Zanghellini J, Ruckerbauer DE, Hanscho M, &, Jungreuthmayer C, (2013) Elementary flux modes in a nutshell: properties, calculation and applications. Biotechnol J 8, 1009-1016.
14. Klamt S, &, Stelling J, (2002) Combinatorial complexity of pathway analysis in metabolic networks. Mol Biol Rep 29, 233-236.
15. Hunt KA, Folsom JP, Taffs RL, &, Carlson RP, (2014) Complete enumeration of elementary flux modes through scalable demand-based subnetwork definition. Bioinformatics 30, 1569-1578.
16. Kaleta C, De Figueiredo LF, Behre J, &, Schuster S, (2009) EFMEvolver: computing elementary flux modes in genome-scale metabolic networks. In Lecture Notes in Informatics (LNI) P-157-Proceedings of the German Conference on Bioinformatics, pp. 179-190. Gesellschaft fr Informatik, Bonn.
17. Machado D, Soons Z, Patil KR, Ferreira EC, &, Rocha I, (2012) Random sampling of elementary flux modes in large-scale metabolic networks. Bioinformatics 28, i515-i521.
18. Pey J, Villar JA, Tobalina L, Rezola A, García JM, Beasley JE, &, Planes FJ, (2015) TreeEFM calculating elementary flux modes using linear optimization in a tree-based algorithm. Bioinformatics, 31, 897-904.
19. De Figueiredo LF, Podhorski A, Rubio A, Kaleta C, Beasley JE, Schuster S, &, Planes FJ, (2009) Computing the shortest elementary flux modes in genome-scale metabolic networks. Bioinformatics 25, 3158-3165.
20. Kelk SM, Olivier BG, Stougie L, &, Bruggeman FJ, (2012) Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks. Sci Rep 2, 580.
21. Pey J, &, Planes FJ, (2014) Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks. Bioinformatics 30, 2197-2203.
22. Rezola A, Pey J, Figueiredo LFD, Podhorski A, Schuster S, Rubio A, &, Planes FJ, (2013) Selection of human tissue-specific elementary flux modes using gene expression data. Bioinformatics 29, 2009-2016.
23. Jol SJ, Kümmel A, Terzer M, Stelling J, &, Heinemann M, (2012) System-level insights into yeast metabolism by thermodynamic analysis of elementary flux modes. PLoS Comput Biol 8, e1002415.
24. Gerstl MP, Jungreuthmayer C, &, Zanghellini J, (2015) tEFMA: computing thermodynamically feasible elementary flux modes in metabolic networks. Bioinformatics 31, 22324.
25. Gerstl MP, Ruckerbauer DE, Mattanovich D, Jungreuthmayer C, &, Zanghellini J, (2015) Metabolomics integrated elementary flux mode analysis in large metabolic networks. Sci Rep 5, 8930.
26. Schwartz J-M, &, Kanehisa M, (2006) Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis. BMC Bioinformatics 7, 1-20.
27. Alberty RA, (2003) Thermodynamics of Biochemical Reactions. John Wiley & Sons, Inc., New Jersey.
28. Ataman M, &, Hatzimanikatis V, (2015) Heading in the right direction: thermodynamics-based network analysis and pathway engineering. Curr Opin Biotechnol 36, 176-182.
29. Hoppe A, Hoffmann S, &, Holzhütter H-G, (2007) Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks. BMC Syst Biol 1, 23.
30. Schuster S, &, Heinrich R, (1991) Minimization of intermediate concentrations as a suggested optimality principle for biochemical networks. J Math Biol 29, 425-442.
31. Andersen KB, &, von Meyenburg K, (1980) Are growth rates of Escherichia coli in batch cultures limited by respiration ? J Bacteriol 144, 114-123.
32. Shen J, &, Gunsalus RP, (1997) Role of multiple ArcA recognition sites in anaerobic regulation of succinate dehydrogenase (sdhCDAB) gene expression in Escherichia coli. Mol Microbiol 26, 223-236.
33. Jones HM, &, Gunsalus RP, (1985) Transcription of the Escherichia coli fumarate reductase genes (frdABCD) and their coordinate regulation by oxygen, nitrate, and fumarate. J Bacteriol 164, 1100-1109.
34. 13C metabolic flux analysis. Microb Cell Fact, 11, 87.
35. Schuetz R, Zamboni N, Zampieri M, Heinemann M, &, Sauer U, (2012) Multidimensional optimality of microbial metabolism. Science 336, 601-604.
36. Chan SHJ, &, Ji P, (2011) Decomposing flux distributions into elementary flux modes in genome-scale metabolic networks. Bioinformatics 27, 2256-2262.
37. Chan SHJ, Solem C, Jensen PR, &, Ji P, (2014) Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property. Bioinformatics 30, 3232-3239.
38. Ip K, Colijn C, &, Lun D, (2011) Analysis of complex metabolic behavior through pathway decomposition. BMC Syst Biol 5, 91.
39. Poolman M, Venkatesh K, Pidcock M, &, Fell D, (2004) A method for the determination of flux in elementary modes, and its application to Lactobacillus rhamnosus. Biotechnol Bioeng 88, 601-612.
40. Schwartz J-M, &, Kanehisa M, (2005) A quadratic programming approach for decomposing steady-state metabolic flux distributions onto elementary modes. Bioinformatics 21 (Suppl 2), ii204-ii205.
41. Jungreuthmayer C, Ruckerbauer DE, Gerstl MP, Hanscho M, &, Zanghellini J, (2015) Avoiding the enumeration of infeasible elementary flux modes by including transcriptional regulatory rules in the enumeration process saves computational costs. PLoS One 10, e0129840.
42. Jungreuthmayer C, Ruckerbauer DE, &, Zanghellini J, (2013) regEfmtool: speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of three-state logic. Biosystems 113, 37-39.
43. Bennett BD, Kimball EH, Gao M, Osterhout R, Van Dien SJ, &, Rabinowitz JD, (2009) Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli. Nat Chem Biol 5, 593-599.
44. Flamholz A, Noor E, Bar-Even A, &, Milo R, (2012) eQuilibrator-the biochemical thermodynamics calculator. Nucleic Acids Res, 40, D770-D775.