Flux-balance modeling of plant metabolism

Frontiers in Plant Science

Volumn 2, Issue AUG, 2011, Pages

  Sweetlove, Lee J ^a   George Ratcliffe, R ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Flux; Flux balance modeling; Metabolism

Indexed keywords

EID: 84870302280     PISSN: None     EISSN: 1664462X     Source Type: Journal    
DOI: 10.3389/fpls.2011.00038     Document Type: Article

References (94)

1. Allen, D. K., Libourel, I. G. L., and Shachar-Hill, Y. (2009a). Metabolic fux analysis in plants: coping with complexity. Plant Cell Environ. 32, 1241-1257.
2. Allen, D. K., Ohlrogge, J. B., and Shachar-Hill, Y. (2009b). The role of light in soybean seed filling metabolism. Plant J. 58, 220-234.
3. Alonso, A. P., Dale, V. L., and Shachar-Hill, Y. (2010). Understanding fatty acid synthesis in developing maize embryos using metabolic flux analysis. Metab. Eng. 12, 488-497.
4. Alonso, A. P., Goffman, F. D., Ohlrogge, J. B., and Shachar-Hill, Y. (2007). Carbon conversion efficiency and central metabolic fluxes in developing sunfower (Helianthus annuus L.) embr yos. Plant J. 52, 296-308.
5. Alper, H., Jin, Y. S., Moxley, J. F., and Stephanopoulos, G. (2005). Identifying gene targets for the metabolic engineering of lycopene biosynthesis in Escherichia coli. Metab. Eng. 7, 155-164.
6. Amthor, J. S. (2000). The McCree-de Wit-Penning de Vries-Thornley respiration paradigms: 30 years later. Ann. Bot. 86, 1-20.
7. Apel, K., and Hirt, H. (2004). Reactive oxygen species: metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant Biol. 55, 373-399.
8. Araujo, W. L., Nunes-Nesi, A., Nikoloski, Z., Sweetlove, L. J., and Fernie, A. R. (2011). Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues. Plant Cell Environ. doi: 10.1111/j.1365-3040.2011.02332.x. [Epub ahead of print].
9. Armstrong, A. F., Logan, D. C., Tobin, A. K., O'Toole, P., and Atkin, O. K. (2006). Heterogeneity of plant mitochondrial responses underpinning respiratory acclimation to the cold in Arabidopsis thaliana leaves. Plant Cell Environ. 29, 940-949.
10. Averill, R. H., Bailey-Serres, J., and Kruger, N. J. (1998). Co-operation between cytosolic and plastidic oxidative pen-tose phosphate pathways revealed by 6-phosphogluconate dehydrogenase-defcient genotypes of maize. Plant J. 14, 449-457.
11. Baerenfaller, K., Grossmann, J., Grobei, M. A., Hull, R., Hirsch-Hoffmann, M., Yalovsky, S., Zimmermann, P., Grossniklaus, U., Gruissem, W., and Baginsky, S. (2008). Genome-scale proteomics reveals Arabidopsis thaliana gene models and proteome dynamics. Science 320, 938-941.
12. Bar-Even, A., Noor, E., Lewis, N. E., and Milo, R. (2010). Design and analysis of synthetic carbon fixation pathways. Proc. Natl. Acad. Sci. U.S.A. 107, 8889-8894.
13. Becker, J., Zelder, O., Hafner, S., Schroder, H., and Wittmann, C. (2011). From zero to hero-design-based systems metabolic engineering of Corynebacterium glutamicum for l-lysine production. Metab. Eng. 13, 159-168.
14. Bekaert, M., Edger, P. P., Pires, J. C., and Conant, G. C. (2011). Two-phase resolution of poly ploidy in the Arabidopsis metabolic network gives rise to r elative and absolute dosage constraints. Plant Cell 23, 1719-1728.
15. Borodina, I., and Nielsen, J. (2005). From genomes to in silico cells via metabolic networks. Curr. Opin. Biotechnol. 16, 350-355.
16. Boyle, N. R., and Morgan, J. A. (2009). Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Syst. Biol. 3, 4. doi: 10.1186/1752-0509-3-4
17. Boyle, N. R., and Morgan, J. A. (2011). Computation of metabolic fuxes and efficiencies for biological carbon dioxide fixation. Metab. Eng. 13, 150-158.
18. Brady, S. M., Orlando, D. A., Lee, J. Y., Wang, J. Y., Koch, J., Dinneny, J. R., Mace, D., Ohler, U., and Benfey, P. N. (2007). A high-resolution root spatiotemporal map reveals dominant expression patterns. Science 318, 801-806.
19. Burgard, A. P., Pharkya, P., and Maranas, C. D. (2003). OptKnock: a bilevel pro -gramming framework for identifying gene knockout strategies for micro-bial strain optimization. Biotechnol. Bioeng. 84, 647-657.
20. Butelli, E., Titta, L., Giorgio, M., Mock, H. P., Matros, A., Peterek, S., Schijlen, E. G. W. M., Hall, R. D., Bovy, A. G., Luo, J., and Martin, C. (2008). Enrichment of tomato fruit with health-promoting anthocyanins by expression of select transcription factors. Nat. Biotechnol. 26, 1301-1308.
21. Christophe, A., Letort, V., Hummel, I., Cournede, P. H., de Reffye, P., and Lecoeur, J. (2008). A model-based analysis of the dynamics of carbon balance at the whole-plant level in Arabidopsis thaliana. Funct. Plant Biol. 35, 1147-1162.
22. Cogne, G., Rugen, M., Bockmayr, A., Titica, M., Dussap, C. G., Cornet, J. F., and Legrand, J. (2011). A model-based method for investigating bioenergetic processes in autotrophically growing eukaryotic microalgae: application to the green algae Chlamydomonas rein-hardtii. Biotechnol. Prog. 27, 631-640.
23. De Oliveira Dal'Molin, C. G., Quek, L. E., Palfreyman, R. W., Brumbley, S. M., and Nielsen, L. K. (2010a). Aragem, a genome-scale reconstruction of the primary metabolic network in Arabidopsis. Plant Physiol. 152, 579-589.
24. De Oliveira Dal'Molin, C. G., Quek, L. E., Palfreyman, R. W., Brumbley, S. M., and Nielsen, L. K. (2010b). C4gem, a genome-scale metabolic model to study C4 plant metabolism. Plant Physiol. 154, 1871-1885.
25. Edwards, J. S., and Palsson, B. O. (2000). The Escherichia coli mg1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc. Natl. Acad. Sci. U.S.A. 97, 5528-5533.
26. Enfssi, E. M., Fraser, P. D., Lois, L. M., Boronat, A., Schuch, W., and Bramley, P. M. (2005). Metabolic engineering of the mevalonate and non-mevalonate isopentenyl diphosphate-forming pathways for the production of health-promoting isoprenoids in tomato. Plant Biotechnol. J. 3, 17-27.
27. Fell, D. A., Poolman, M. G., and Gevorgyan, A. (2010). Building and analysing genome-scale metabolic models. Biochem. Soc. Trans. 38, 1197-1201.
28. Fernie, A. R., and Schauer, N. (2009). Metabolomics-assisted breeding: a viable option for crop improvement? Trends Genet. 25, 39-48.
29. Fraser, P. D., Romer, S., Shipton, C. A., Mills, P. B., Kiano, J. W., Misawa, N., Drake, R. G., Schuch, W., and Bramley, P. M. (2002). Evaluation of transgenic tomato plants expressing an additional phytoene synthase in a fruit-specific manner. Proc. Natl. Acad. Sci. U.S.A. 99, 1092-1097.
30. Geigenberger, P., Stitt, M., and Fernie, A. R. (2004). Metabolic control analysis and regulation of the conversion of sucrose to starch in growing potato tubers. Plant Cell Environ. 27, 655-673.
31. Grafahrend-Belau, E., Schreiber, F., Koschutzki, D., and Junker, B. H. (2009). Flux balance analysis of barley seeds: a computational approach to study systemic properties of central metabolism. Plant Physiol. 149, 585-598.
32. Hauben, M., Haesendonckx, B., Standaert, E., Van Der Kelen, K., Azmi, A., Akpo, H., Va n Breusegem, F., Guisez, Y., Bots, M., Lambert, B., Laga, B., and De Block, M. (2009). Energy use efficiency is characterized by an epige-netic component that can be directed through artificial selection to increase yield. Proc. Natl. Acad. Sci. U.S.A. 106, 20109-20114.
33. 13C-metabolic flux analysis. Plant J. 67, 513-525.
34. Hay, J., and Schwender, J. (2011b). Metabolic network reconstruction and flux variability analysis of storage synthesis in developing oilseed rape (Brassica napus L.) embryos. Plant J. 67, 526-541.
35. Heazlewood, J. L., Tonti-Filippini, J. S., Gout, A. M., Day, D. A., Whelan, J., and Millar, A. H. (2004). Experimental analysis of the Arabidopsis mitochon-drial proteome highlights signaling and regulatory components, provides assessment of targeting prediction programs, and indicates plant-specific mitochondrial proteins. Plant Cell 16, 241-256.
36. Heazlewood, J. L., Verboom, R. E., Tonti-Filippini, J., Small, I., and Millar, A. H. (2007). SUBA: the Arabidopsis subcellular database. Nucleic Acids Res. 35, D213-D218.
37. Heinzle, E., Matsuda, F., Miyagawa, H., Wakasa, K., and Nishioka, T. (2007). Estimation of metabolic fluxes, expression levels and metabolite dynamics of a secondary metabolic pathway in potato using label pulse-feeding experiments combined with kinetic network modeling and simulation. Plant J. 50, 176-187.
38. Henry, C. S., Dejongh, M., Best, A. A., Frybarger, P. M., Linsay, B., and Stevens, R. L. (2010). High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat. Biotechnol. 28, 977-982.
39. Iyer, V. V., Sriram, G., Fulton, D. B., Zhou, R., Westgate, M. E., and Shanks, J. V. (2008). Metabolic flux maps comparing the effect of temperature on protein and oil biosynthesis in developing soybean cotyledons. Plant Cell Environ. 31, 506-517.
40. Jankowski, M. D., Henry, C. S., Broadbelt, L. J., and Hatzimanikatis, V. (2008). Group contribution method for thermody-namic analysis of complex metabolic networks. Biophys. J. 95, 1487-1499.
41. Junker, B. H., Lonien, J., Heady, L. E., Rogers, A., and Schwender, J. (2007). Parallel determination of enzyme activities and in vivo fluxes in Brassica napus embryos grown on organic or inorganic nitrogen source. Phytochemistry 68, 2232-2242.
42. Knoop, H., Zilliges, Y., Lockau, W., and Steuer, R. (2010). The metabolic network of Synechocystis sp. PCC 6803: systemic properties of autotrophic growth. Plant Physiol. 154, 410-422.
43. Kruger, N. J., and Ratcliffe, R. G. (2008). Metabolic organization in plants: a challenge for the metabolic engineer. Adv. Plant Biochem. Mol. Biol. 1, 1-27.
44. Kruger, N. J., and Ratcliffe, R. G. (2009). Insights into plant metabolic networks from steady-state metabolic flux anal -ysis. Biochimie 91, 697-702.
45. Kruger, N. J., and von Schaewen, A. (2003). The oxidative pentose phosphate pathway: structure and organization. C u r r. Opin. Plant Biol. 6, 236-246.
46. Lee, C. P., Eubel, H., O'Toole, N., and Millar, A. H. (2011). Combining pro-teomics of root and shoot mitochondria and transcript analysis to define constitutive and variable components in plant mitochondria. Phytochemistry 72 1092-1108.
47. Lee, S., Chan, P., Domach, M. M., and Grossman, I. E. (2000). Recursive MILP model for finding all the alternate optima in LP models for metabolic networks. Comput. Chem. Eng. 24, 711-716.
48. Lehmann, M., Schwarzlander, M., Obata, T., Sirikantaramas, S., Burow, M., Olsen, C. E., Tohge, T., Fricker, M. D., Moller, B. L., Fernie, A. R., Sweetlove, L. J., and Laxa, M. (2009). The metabolic response of arabidopsis roots to oxidative stress is distinct from that of heterot rophic cells in culture and high -lights a complex relationship between the levels of transcripts, metabolites, and fux. Mol. Plant 2, 390-406.
49. Lewis, N. E., Schramm, G., Bordbar, A., Schellenberger, J., Andersen, M. P., Cheng, J. K., Patel, N., Yee, A., Lewis, R. A., Eils, R., König, R., and Palsson, B. Ø. (2010). Large-scale in silico modeling of metabolic interactions between cell types in the human brain. Nat. Biotechnol. 28, 1279-1285.
50. Libourel, I. G. L., and Shachar-Hill, Y. (2008). Metabolic flux analysis in plants: from intelligent design to rational engineering. Annu. Rev. Plant Biol. 59, 625-650.
51. Lonien, J., and Schwender, J. (2009). Analysis of metabolic flux pheno-types for two Arabidopsis mutants with severe impairment in seed storage lipid synthesis. Plant Physiol. 151, 1617-1634.
52. Lunn, J. E. (2007). Compartmentation in plant metabolism. J. Exp. Bot. 58, 35-47.
53. Mahadevan, R., Edwards, J. S., and Doyle, F. J. III (2002). Dynamic fux balance analysis of diauxic growth in Escherichia coli. Biophys. J. 83, 1331-1340.
54. Mahadevan, R., and Schilling, C. H. (2003). The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab. Eng. 5, 264-276.
55. Masakapalli, S. K., Le Lay, P., Huddleston, J. E., Pollock, N. L., Kruger, N. J., and Ratcliffe, R. G. (2010). Subcellular fux analysis of central metabolism in a het -erotrophic Arabidopsis cell suspension using steady-state stable isotope labeling. Plant Physiol. 152, 602-619.
56. Memelink, J., and Gantet, P. (2007). Transcription factors involved in ter-penoid indole alkaloid biosynthesis in Catharanthus roseus. Phytochem. Rev. 6, 353-362.
57. Montagud, A., Navarro, E., Fernandez de Cordoba, P., Urchueguia, J. F., and Patil, K. R. (2010). Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium. BMC Syst. Biol. 4, 156. doi: 10.1186/1752-0509-4-156
58. Naqvi, S., Zhu, C., Farre, G., Ramessar, K., Bassie, L., Breitenbach, J., Perez Conesa, D., Ros, G., Sandmann, G., Capell, T., and Christou, P. (2009). Transgenic multivitamin corn through biofortifcation of endosperm with three vitamins representing three distinct metabolic pathways. Proc. Natl. Acad. Sci. U.S.A. 106, 7762-7767.
59. Parry, M. A., Reynolds, M., Salvucci, M. E., Raines, C., Andralojc, P. J., Zhu, X. G., Price, G. D., Condon, A. G., and Furbank, R. T. (2010). Raising yield potential of wheat. II. Increasing pho-tosynthetic capacity and effciency. J. Exp. Bot. 62, 453-467.
60. Penning de Vries, F. W. T. (1974). Substrate utilization and respiration in relation to growth and maintenance in higher plants. Neth. J. Agric. Sci. 22, 40-44.
61. Penning de Vries, F. W. T., Brunsting, A. H. M., and Van Laar, H. H. (1974). Products, requirements and efficiency of biosynthesis - quantitative approach. J. Theor. Biol. 45, 339-377.
62. Pilalis, E., Chatziioannou, A., Thomasset, B., and Kolisis, F. (2011). An in silico compartmentalized metabolic model of Brassica napus enables the systemic study of regulatory aspects of plant central metabolism. Biotechnol. Bioeng. 108, 1673-1682.
63. Poolman, M. G., Miguet, L., Sweetlove, L. J., and Fell, D. A. (2009). A genome-scale metabolic model of Arabidopsis and some of its properties. Plant Physiol. 151, 1570-1581.
64. Pramanik, J., and Keasling, J. D. (1997). Stoichiometric model of Escherichia coli metabolism: incorporation of growth-rate dependent biomass composition and mechanistic energy requirements. Biotechnol. Bioeng. 56, 398-421.
65. Radrich, K., Tsuruoka, Y., Dobson, P., Gevorgyan, A., Swainston, N., Baart, G., and Schwartz, J. M. (2010). Integration of metabolic databases for the reconstruction of genome-scale metabolic networks. BMC Syst. Biol. 4, 114. doi: 10.1186/1752-0509-4-114
66. Raines, C. A. (2003). The Calvin cycle revisited. Photosynth. Res. 75, 1-10.
67. Ratcliffe, R. G., and Shachar-Hill, Y. (2006). Measuring multiple fluxes through plant metabolic networks. Plant J. 45, 490-511.
68. Reed, J. L., and Palsson, B. O. (2003). Thirteen years of building constraint-based in silico models of Escherichia coli. J. Bacteriol. 185, 2692-2699.
69. Roscher, A., Kruger, N. J., and Ratcliffe, R. G. (2000). Strategies for metabolic fux analysis in plants using isotope labelling. J. Biotechnol. 77, 81-102.
70. Rossell, S., van der Weijden, C. C., Lindenbergh, A., van Tuijl, A., Francke, C., Bakker, B. M., and Westerhoff, H. V. (2006). Unraveling the complexity of fux regulation: a new method demonstr ated for nutrient starvation in Saccharomyces cer-evisiae. Proc. Natl. Acad. Sci. U.S.A. 103, 2166-2171.
71. Saha, R., Suthers, P., and Maranas, C. (2011). Zea mays irs1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism. PLoS ONE 6, e21784. doi: 10.1371/ journal.pone.0021784
72. Schallau, K., and Junker, B. H. (2010). Simulating plant metabolic pathways with enzyme-kinetic models. Plant Physiol. 152, 1763-1771.
73. Schuetz, R., Kuepfer, L., and Sauer, U. (2007). Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli. Mol. Syst. Biol. 3, 119.
74. Schuster, S., Pfeiffer, T., and Fell, D. A. (2008). Is maximization of molar yield in metabolic networks favored by evolution? J. Theor. Biol. 252, 497-504.
75. Schwender, J., Goffman, F., Ohlrogge, J. B., and Shachar-Hill, Y. (2004). Rubisco without the Calvin cycle improves the carbon efficiency of developing green seeds. Nature 432, 779-782.
76. Schwender, J., Ohlrogge, J. B., and Shachar-Hill, Y. (2003). A flux model of glycolysis and the oxidative pen-tosephosphate pathway in developing Brassica napus embryos. J. Biol. Chem. 278, 29442-29453.
77. Schwinn, K., Venail, J., Shang, Y., Mackay, S., Alm, V., Butelli, E., Oyama, R., Bailey, P., Davies, K., and Martin, C. (2006). A small family of myb-regulatory genes controls foral pigmentation intensity and patterning in the genus antirrhinum. Plant Cell 18, 831-851.
78. Shastri, A. A., and Morgan, J. A. (2005). Flux balance analysis of photoauto-trophic metabolism. Biotechnol. Prog. 21, 1617-1626.
79. 13C metabolic flux analysis of photoautotrophic microorganisms. Phytochemistry 68, 2302-2312.
80. Smith, A. M., and Stitt, M. (2007). Coordination of carbon supply and plant growth. Plant Cell Environ. 30, 1126-1149.
81. Soh, K. C., and Hatzimanikatis, V. (2010). DREAMS of metabolism. Trends Biotechnol. 28, 501-508.
82. 1H] nuclear magnetic resonance, and comprehensive isotopomer balancing. Plant Physiol. 136, 3043-3057.
83. Stitt, M., Sulpice, R., and Keurentjes, J. (2010). Metabolic networks: how to identify key components in the regulation of metabolism and growth. Plant Physiol. 152, 428-444.
84. Sweetlove, L. J., Beard, K. F., Nunes-Nesi, A., Fernie, A. R., and Ratcliffe, R. G. (2010). Not just a circle: flux modes in the plant TCA cycle. Trends Plant Sci. 15, 462-470.
85. Sweetlove, L. J., Fell, D., and Fernie, A. R. (2008). Getting to grips with the plant metabolic network. Biochem. J. 409, 27-41.
86. Taylor, L., Nunes-Nesi, A., Parsley, K., Leiss, A., Leach, G., Coates, S., Wingler, A., Fernie, A. R., and Hibberd, J. M. (2010). Cytosolic pyruvate, orthophosphate dikinase functions in nitrogen remobilization during leaf senescence and limits individual seed growth and nitrogen content. Plant J. 62, 641-652.
87. Taylor, N. L., Day, D. A., and Millar, A. H. (2004). Targets of stress-induced oxi-dative damage in plant mitochondria and their impact on cell carbon/nitrogen metabolism. J. Exp. Bot. 55, 1-10.
88. Thornley, J. H. M., and Johnson, I. R. (1990). Plant and Crop Modeling Oxford: Oxford University Press.
89. Torres, M. A. (2010). ROS in biotic interactions. Physiol. Plant. 138, 414-429.
90. Walton, E. F., and de Jong, T. M. (1990). Estimating the bioenergetic cost of a developing kiwifruit berry and its growth and maintenance respiration components. Ann. Bot. 66, 417-424.
91. Williams, T. C. R., Miguet, L., Masakapalli, S. K., Kruger, N. J., Sweetlove, L. J., and Ratcliffe, R. G. (2008). Metabolic network fluxes in heterotrophic Arabidopsis cells: stability of the flux distribution under different oxygenation conditions. Plant Physiol. 148, 704-718.
92. Williams, T. C. R., Poolman, M. G., Howden, A. J., Schwarzlander, M., Fell, D. A., Ratcliffe, R. G., and Sweetlove, L. J. (2010). A genome-scale metabolic model accurately predicts fluxes in central carbon metabolism under stress conditions. Plant Physiol. 154, 311-323.
93. Zhang, P., Dreher, K., Karthikeyan, A., Chi, A., Pujar, A., Caspi, R., Karp, P., Kirkup, V., Latendresse, M., Lee, C., Mueller, L. A., Muller, R., and Rhee, S. Y. (2010). Creation of a genome-wide metabolic pathway database for Populus trichocarpa using a new approach for reconstruction and curation of metabolic pathways for plants. Plant Physiol. 153, 1479-1491.
94. Zimmermann, P., Hirsch-Hoffmann, M., Hennig, L., and Gruissem, W. (2004). Genevestigator. Arabidopsis microar-ray database and analysis toolbox. Plant Physiol. 136, 2621-2632.