The application of flux balance analysis in systems biology

Wiley Interdisciplinary Reviews: Systems Biology and Medicine

Volumn 2, Issue 3, 2010, Pages 372-382

  Gianchandani, Erwin P ^a   Chavali, Arvind K ^a   Papin, Jason A ^a  

^a University of Virginia   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEOME;

ALGORITHM; ANIMAL; BIOLOGICAL MODEL; COMPUTER SIMULATION; ENERGY METABOLISM; ENERGY TRANSFER; HUMAN; METABOLISM; METHODOLOGY; PHYSIOLOGY; PROTEIN ANALYSIS; REVIEW; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; THERMODYNAMICS;

ALGORITHMS; ANIMALS; COMPUTER SIMULATION; ENERGY METABOLISM; ENERGY TRANSFER; HUMANS; MODELS, BIOLOGICAL; PROTEIN INTERACTION MAPPING; PROTEOME; SIGNAL TRANSDUCTION; SYSTEMS BIOLOGY; THERMODYNAMICS;

EID: 78649631909     PISSN: 19395094     EISSN: 1939005X     Source Type: Journal    
DOI: 10.1002/wsbm.60     Document Type: Article

References (79)

1. Feist AM, Palsson BO. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nat Biotechnol 2008, 26(6):659-667.
2. Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR, et al. A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol 2007, 3:121.
3. Duarte NC, Herrgard MJ, Palsson BO. Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res 2004, 14(7):1298-1309.
4. Forster J, Famili I, Fu P, Palsson BO, Nielsen J. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res 2003, 13(2):244-253.
5. Herrgard MJ, Swainston N, Dobson P, Dunn WB, Arga KY, et al. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology. Nat Biotechnol 2008, 26(10):1155-1160.
6. Duarte NC, Becker SA, Jamshidi N, Thiele I, Mo ML, et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A 2007, 104(6):1777-1782.
7. Ma H, Sorokin A, Mazein A, Selkov A, Selkov E, et al. The Edinburgh human metabolic network reconstruction and its functional analysis. Mol Syst Biol 2007, 3:135.
8. Feist AM, Herrgard MJ, Thiele I, Reed JL, Palsson BO. Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 2009, 7(2):129-143.
9. Lee JM, Gianchandani EP, Papin JA. Flux balance analysis in the era of metabolomics. Brief Bioinform 2006, 7(2):140-150.
10. Price ND, Papin JA, Schilling CH, Palsson BO. Genome-scale microbial in silico models: the constraints-based approach. Trends Biotechnol 2003, 21(4):162-169.
11. Gianchandani EP, Brautigan DL, Papin JA. Systems analyses characterize integrated functions of biochemical networks. Trends Biochem Sci 2006, 31(5):284-291.
12. Oh YK, Palsson BO, Park SM, Schilling CH, Mahadevan R. Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data. J Biol Chem 2007, 282(39):28791-28799.
13. Senger RS, Papoutsakis ET. Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis. Biotechnol Bioeng 2008, 101(5):1036-1052.
14. Schilling CH, Covert MW, Famili I, Church GM, Edwards JS, et al. Genome-scale metabolic model of Helicobacter pylori 26695. J Bacteriol 2002, 184(16):4582-4593.
15. Oliveira AP, Nielsen J, Forster J. Modeling Lactococcus lactis using a genome-scale flux model. BMC Microbiol 2005, 5:39.
16. Beste DJ, Hooper T, Stewart G, Bonde B, Avignone-Rossa C, et al. GSMN-TB: a web-based genomescale network model of Mycobacterium tuberculosis metabolism. Genome Biol 2007, 8(5):R89.
17. Oberhardt MA, Puchalka J, Fryer KE, Martins dos Santos VA, Papin JA. Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. J Bacteriol 2008, 190(8):2790-2803.
18. Chavali AK, Whittemore JD, Eddy JA, Williams KT, Papin JA. Systems analysis of metabolism in the pathogenic trypanosomatid Leishmania major. Mol Syst Biol 2008, 4:177.
19. BoyleNR, Morgan JA. Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Syst Biol 2009, 3:4.
20. Shastri AA, Morgan JA. Flux balance analysis of photoautotrophic metabolism. Biotechnol Prog 2005, 21(6):1617-1626.
21. Luo RY, Liao S, Tao GY, Li YY, Zeng S, et al. Dynamic analysis of optimality in myocardial energy metabolism under normal and ischemic conditions. Mol Syst Biol 2006, 2:2006.0031.
22. Teusink B, Wiersma A, Molenaar D, Francke C, de Vos WM, et al. Analysis of growth of Lactobacillus plantarum WCFS1 on a complex medium using a genome-scale metabolic model. J Biol Chem 2006, 281(52):40041-40048.
23. Ramakrishna R, Edwards JS, McCulloch A, Palsson BO. Flux-balance analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints. Am J Physiol Regul Integr Comp Physiol 2001, 280(3):R695-R704.
24. Vo TD, Greenberg HJ, Palsson BO. Reconstruction and functional characterization of the human mitochondrial metabolic network based on proteomic and biochemical data. J Biol Chem 2004, 279(38):39532-39540.
25. Varma A, Boesch BW, Palsson BO. Biochemical production capabilities of Escherichia coli. Biotechnol Bioeng 1993, 42(1):59-73.
26. Blank LM, Ebert BE, Buhler B, Schmid A. Metabolic capacity estimation of Escherichia coli as a platform for redox biocatalysis: constraint-based modeling and experimental verification. Biotechnol Bioeng 2008, 100(6):1050-1065.
27. Portnoy VA, Herrgard MJ, Palsson BO. Aerobic fermentation of D-glucose by an evolved cytochrome oxidase-deficient Escherichia coli strain. Appl Environ Microbiol 2008, 74(24):7561-7569.
28. Lee KH, Park JH, Kim TY, Kim HU, Lee SY. Systems metabolic engineering of Escherichia coli for L-threonine production. Mol Syst Biol 2007, 3:149.
29. Schwender J. Metabolic flux analysis as a tool in metabolic engineering of plants. Curr Opin Biotechnol 2008, 19(2):131-137.
30. Izallalen M, Mahadevan R, Burgard A, Postier B, Didonato R Jr, et al. Geobacter sulfurreducens strain engineered for increased rates of respiration. Metab Eng 2008, 10(5):267-275.
31. Cakir T, Efe C, Dikicioglu D, Hortacsu A, Kirdar B, et al. Flux balance analysis of a genome-scale yeast model constrained by exometabolomic data allows metabolic system identification of genetically different strains. Biotechnol Prog 2007, 23(2):320-326.
32. Kim TY, Kim HU, Park JM, Song H, Kim JS, et al. Genome-scale analysis of Mannheimia succiniciproducens metabolism. Biotechnol Bioeng 2007, 97(4):657-671.
33. Edwards JS, Palsson BO. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc Natl Acad Sci U S A 2000, 97(10):5528-5533.
34. Beard DA, Liang SD, Qian H. Energy balance for analysis of complex metabolic networks. Biophys J 2002, 83(1):79-86.
35. Balabanian N, Bickart TA. Electrical Network Theory. Malabar, FL: R.E. Krieger Pub. Co.; 1983.
36. Covert MW, Schilling CH, Palsson B. Regulation of gene expression in flux balance models of metabolism. J Theor Biol 2001, 213(1):73-88.
37. Covert MW, Palsson BO. Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J Biol Chem 2002, 277(31):28058-28064.
38. Covert MW, Palsson BO. Constraints-based models: regulation of gene expression reduces the steady-state solution space. J Theor Biol 2003, 221(3):309-325.
39. Herrgard MJ, Lee BS, Portnoy V, Palsson BO. Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Res 2006, 16(5):627-635.
40. Gianchandani EP, Papin JA, Price ND, Joyce AR, Palsson BO. Matrix formalism to describe functional states of transcriptional regulatory systems. PLoS Comput Biol 2006, 2(8):e101.
41. Gianchandani EP, Joyce AR, Palsson BO, Papin JA. Functional states of the genome-scale Escherichia coli transcriptional regulatory system. PLoS Comput Biol 2009, 5(6):e1000403.
42. Min Lee J, Gianchandani EP, Eddy JA, Papin JA. Dynamic analysis of integrated signaling, metabolic, and regulatory networks. PLoS Comput Biol 2008, 4(5):e1000086.
43. Gerdtzen ZP, Daoutidis P, Hu WS. Non-linear reduction for kinetic models of metabolic reaction networks. Metab Eng 2004, 6(2):140-154.
44. Segre D, Vitkup D, Church GM. Analysis of optimality in natural and perturbed metabolic networks. Proc Natl Acad Sci U S A 2002, 99(23):15112-15117.
45. Stephanopoulos G, Alper H, Moxley J. Exploiting biological complexity for strain improvement through systems biology. Nat Biotechnol 2004, 22(10):1261-1267.
46. Mahadevan R, Edwards JS, Doyle FJ III. Dynamic flux balance analysis of diauxic growth in Escherichia coli. Biophys J 2002, 83(3):1331-1340.
47. Gianchandani EP, Oberhardt MA, Burgard AP, Maranas CD, Papin JA. Predicting biological system objectives de novo from internal state measurements. BMC Bioinform 2008, 9:43.
48. Gombert AK, Moreira dos Santos M, Christensen B, Nielsen J. Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression. J Bacteriol 2001, 183(4):1441-1451.
49. Burgard AP, Maranas CD. Optimization-based framework for inferring and testing hypothesized metabolic objective functions. Biotechnol Bioeng 2003, 82(6):670-677.
50. Nolan RP, Fenley AP, Lee K. Identification of distributed metabolic objectives in the hypermetabolic liver by flux and energy balance analysis. Metab Eng 2006, 8(1):30-45.
51. Knorr AL, Jain R, Srivastava R. Bayesian-based selection of metabolic objective functions. Bioinformatics 2007, 23(3):351-357.
52. Schuetz R, Kuepfer L, Sauer U. Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. Mol Syst Biol 2007, 3:119.
53. Wiechert W. An introduction to 13C metabolic flux analysis. Genet Eng 2002, 24:215-238.
54. Weckwerth W. Metabolomics in systems biology. Annu Rev Plant Biol 2003, 54:669-689.
55. Fiehn O. Metabolomics-the link between genotypes and phenotypes. Plant Mol Biol 2002, 48(1-2):155-171.
56. Sauer U. High-throughput phenomics: experimental methods for mapping fluxomes. Curr Opin Biotechnol 2004, 15(1):58-63.
57. HellersteinMK. In vivo measurement of fluxes through metabolic pathways: the missing link in functional genomics and pharmaceutical research. Annu Rev Nutr 2003, 23:379-402.
58. Smedsgaard J, Nielsen J. Metabolite profiling of fungi and yeast: from phenotype to metabolome by MS and informatics. J Exp Bot 2005, 56(410):273-286.
59. Fischer E, Zamboni N, Sauer U. High-throughput metabolic flux analysis based on gas chromatographymass spectrometry derived 13C constraints. Anal Biochem 2004, 325(2):308-316.
60. Fischer E, Sauer U. Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur J Biochem. 2003, 270(5):880-891.
61. Blank LM, Sauer U. TCA cycle activity in Saccharomyces cerevisiae is a function of the environmentally determined specific growth and glucose uptake rates. Microbiology 2004, 150(Pt 4):1085-1093.
62. Blank LM, Kuepfer L, Sauer U. Large-scale 13C-flux analysis reveals mechanistic principles of metabolic network robustness to null mutations in yeast. Genome Biol 2005, 6(6):R49.
63. Blank LM, Lehmbeck F, Sauer U. Metabolic-flux and network analysis in fourteen hemiascomycetous yeasts. FEMS Yeast Res 2005, 5(6-7):545-558.
64. Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, et al. Metabolite profiling for plant functional genomics. Nat Biotechnol 2000, 18(11):1157-1161.
65. Roessner U, Wagner C, Kopka J, Trethewey RN, Willmitzer L. Technical advance: simultaneous analysis of metabolites in potato tuber by gas chromatographymass spectrometry. Plant J 2000, 23(1):131-142.
66. Jansen JJ, Hoefsloot HC, Boelens HF, van der Greef J, Smilde AK. Analysis of longitudinal metabolomics data. Bioinformatics 2004, 20(15):2438-2446.
67. Landau BR, Wahren J, Chandramouli V, Schumann WC, Ekberg K, et al. Use of 2H2O for estimating rates of gluconeogenesis. Application to the fasted state. J Clin Invest 1995, 95(1):172-178.
68. Zamboni N, Sauer U. Model-independent fluxome profiling from 2H and 13C experiments for metabolic variant discrimination. Genome Biol 2004, 5(12): R99.
69. AntoniewiczMR, Aleman J, Kelleher JK, Stephanopoulos GN, eds. Comprehensive Analysis of the Gluconeogenesis Pathways through the Use of Multiple Isotopic Tracers. The 2006 Annual Meeting of the American Institute for Chemical Engineers (AIChE). San Francisco, CA: American Institute for Chemical Engineers; 2006.
70. AntoniewiczMR, Aleman J, Kelleher JK, Stephanopoulos GN, eds. High Resolution Flux Estimation of Gluconeogenesis Using A Novel [U-13C,2H8]Glycerol Tracer in Mice. The 2007 AnnualMeeting of the American Institute for Chemical Engineers (AIChE). Salt Lake City, UT: American Institute for Chemical Engineers; 2007.
71. Antoniewicz MR, Kelleher JK, Stephanopoulos G. Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions. Metab Eng 2007, 9(1):68-86.
72. McConville MJ, de Souza D, Saunders E, Likic VA, Naderer T. Living in a phagolysosome; metabolism of Leishmania amastigotes. Trends Parasitol 2007, 23(8):368-375.
73. Becker SA, Palsson BO. Context-specific metabolic networks are consistent with experiments. PLoS Comput Biol 2008, 4(5):e1000082.
74. Shlomi T, Cabili MN, Herrgard MJ, Palsson BO, Ruppin E. Network-based prediction of human tissue-specific metabolism. Nat Biotechnol 2008, 26(9):1003-1010.
75. Raman K, Rajagopalan P, Chandra N. Flux balance analysis of mycolic acid pathway: targets for antitubercular drugs. PLoS Comput Biol 2005, 1(5):e46.
76. Manichaikul A, Ghamsari L, Hom EFY, Lin C, Murray RR, et al. Metabolic network analysis integrated with transcript verification for sequenced genomes. Nat Methods 2009, 6(8):589-592.
77. Park JH, Lee KH, Kim TY, Lee SY.Metabolic engineering of Escherichia coli for the production of L-valine based on transcriptome analysis and in silico gene knockout simulation. Proc Natl Acad Sci U S A 2007, 104(19):7797-7802.
78. Fong SS, Burgard AP, Herring CD, Knight EM, Blattner FR, et al. In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol Bioeng 2005, 91(5):643-648.
79. Lee SJ, Lee DY, Kim TY, Kim BH, Lee J, et al. Metabolic engineering of Escherichia coli for enhanced production of succinic acid, based on genome comparison and in silico gene knockout simulation. Appl Environ Microbiol 2005, 71(12):7880-7887.