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Plant Genome-Scale Modeling and Implementation

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Plant Metabolic Flux Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1090))

Abstract

Considerable progress has been made in plant genome-scale metabolic reconstruction and modeling in recent years. Such reconstructions made it possible to explore metabolic phenotypes through appropriate model formulation and optimization methods. As a result, plant genome-scale modeling has increasingly attracted interest from the plant research community. In this chapter, the first generation of plant genome-scale metabolic reconstructions is presented, along with the important concepts behind model and constraint formulation. A brief protocol describing the use of constraint-based reconstruction and analysis (COBRA) Toolbox in flux simulation and model modification is provided. This is followed by a presentation of metabolic constraints required to generate fluxes in AraGEM using COBRA that describe photosynthesis, photorespiration, and respiration, respectively. Overall, plant genome-scale modeling is a powerful approach that is accessible and readily adopted.

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References

  1. Durot M, Bourguignon PY, Schachter V (2009) Genome-scale models of bacterial metabolism: reconstruction and applications. FEMS Microbiol Rev 33(1):164–190

    Article  PubMed  CAS  Google Scholar 

  2. Feist AM, Herrgard MJ, Thiele I et al (2009) Reconstruction of biochemical networks in microorganisms. Nat Rev Microbiol 7(2):129–143

    Article  PubMed  CAS  Google Scholar 

  3. Jang YS, Lee J, Malaviya A et al (2012) Butanol production from renewable biomass: rediscovery of metabolic pathways and metabolic engineering. Biotechnol J 7(2):186–198

    Article  PubMed  CAS  Google Scholar 

  4. Park JM, Kim TY, Lee SY (2011) Genome-scale reconstruction and in silico analysis of the Ralstonia eutropha H16 for polyhydroxyalkanoate synthesis, lithoautotrophic growth, and 2-methyl citric acid production. BMC Syst Biol 5:101

    Article  PubMed  CAS  Google Scholar 

  5. Edwards JS, Ibarra RU, Palsson BO (2001) In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat Biotechnol 19(2):125–130

    Article  PubMed  CAS  Google Scholar 

  6. Werner E (2007) Systems biology: properties of reconstructed networks. Nature 446(7135):493–494

    Article  CAS  Google Scholar 

  7. Edwards JS, Palsson BO (1999) Systems properties of the Haemophilus influenzae Rd metabolic genotype. J Biol Chem 274(25):17410–17416

    Article  PubMed  CAS  Google Scholar 

  8. Covert MW, Schilling CH, Famili I et al (2001) Metabolic modeling of microbial strains in silico. Trends Biochem Sci 26(3):179–186

    Article  PubMed  CAS  Google Scholar 

  9. Fong SS, Marciniak JY, Palsson BO (2003) Description and interpretation of adaptive evolution of Escherichia coli K-12 MG1655 by using a genome-scale in silico metabolic model. J Bacteriol 185(21):6400–6408

    Article  PubMed  CAS  Google Scholar 

  10. Felst AM, Henry CS, Reed JL et al (2007) A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol 3:121

    Google Scholar 

  11. Gonzalez O, Gronau S, Falb M et al (2008) Reconstruction, modeling & analysis of Halobacterium salinarum R-1 metabolism. Mol Biosyst 4(2):148–159

    Article  PubMed  CAS  Google Scholar 

  12. Famili I, Forster J, Nielson J et al (2003) Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network. Proc Natl Acad Sci U S A 100(23):13134–13139

    Article  PubMed  CAS  Google Scholar 

  13. Boyle NR, Morgan J (2009) Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Syst Biol 3:32

    Article  Google Scholar 

  14. Huthmacher C, Hoppe A, Bulik S, Holzhütter H-G (2010) Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis. BMC Syst Biol 4:120

    Article  PubMed  Google Scholar 

  15. Vanee N, Roberts SB, Fong SS et al (2010) A genome-scale metabolic model of cryptosporidium hominis. Chem Biodivers 7(5):1026–1039

    Article  PubMed  CAS  Google Scholar 

  16. Zhang P, Dreher K, Karthikeyan A et al (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(4):1479–1491

    Article  PubMed  CAS  Google Scholar 

  17. de Oliveira Dal’Molin CGD, Quek L-E, Palfreyman RW, Nielsen LK (2011) AlgaGEM - a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome. BMC Genomics 12(Suppl 4):S5

    Article  Google Scholar 

  18. Caspeta L, Shoaie S, Agren R, Nookaew I, Jens NJ (2012) Genome-scale metabolic reconstructions of Pichia stipitis and Pichia pastoris and in silico evaluation of their potentials. BMC Syst Biol 6:24

    Article  PubMed  CAS  Google Scholar 

  19. Sohn SB, Kim TY, Lee JH, Lee SY (2012) Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth. BMC Syst Biol 6:49

    Article  PubMed  Google Scholar 

  20. Quek L, Nielsen LK (2008) On the reconstruction of the Mus musculus genome-scale metabolic network model. Genome Inform 21:89–100

    Article  PubMed  CAS  Google Scholar 

  21. Duarte NC, Becker SA, Jamshidi N et al (2007) Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc Natl Acad Sci U S A 104(6):1777–1782

    Article  PubMed  CAS  Google Scholar 

  22. de Oliveira Dal’Molin CG, Quek LE, Palfreyman RW et al (2010) AraGEM, a genome-scale reconstruction of the primary metabolic network in Arabidopsis. Plant Physiol 152(2):579–589

    Article  PubMed  Google Scholar 

  23. Mintz-Oron S, Meir S, Malitsky S et al (2012) Reconstruction of Arabidopsis metabolic network models accounting for subcellular compartmentalization and tissue-specificity. Proc Natl Acad Sci U S A 109(1):339–344

    Article  PubMed  CAS  Google Scholar 

  24. Poolman MG, Miguet L, Sweetlove LJ, Fell DA (2009) A genome-scale metabolic model of arabidopsis and some of its properties. Plant Physiol 151(3):1570–1581

    Article  PubMed  CAS  Google Scholar 

  25. Saha R, Suthers PF, Maranas CD (2011) Zea mays iRS1563: a comprehensive genome-scale metabolic reconstruction of maize metabolism. PLoS One 6(7):e21784

    Article  PubMed  CAS  Google Scholar 

  26. de Oliveira Dal’Molin CG, Quek LE, Palfreyman RW et al (2010) C4GEM, a genome-scale metabolic model to study C4 plant metabolism. Plant Physiol 154(4):1871–1885

    Article  Google Scholar 

  27. Thiele I, Palsson BO (2010) A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 5(1):93–121

    Article  PubMed  CAS  Google Scholar 

  28. Henry CS, DeJongh M, Best AA et al (2010) High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol 28(9):977–982

    Article  PubMed  CAS  Google Scholar 

  29. de Oliveira Dal’Molin CG, Nielsen LK (2012) Plant genome-scale metabolic reconstruction and modelling. Curr Opin Biotechnol 24:271–277

    Article  PubMed  Google Scholar 

  30. Livingston DP, Henson CA (1998) Apoplastic sugars, fructans, fructan exohydrolase, and invertase in winter oat: respones to second-phase cold hardening. Plant Physiol 116(1):403–408

    Article  CAS  Google Scholar 

  31. Gowik U, Westhoff P (2011) The path from C3 to C4 photosynthesis. Plant Physiol 155(1):56–63

    Article  PubMed  CAS  Google Scholar 

  32. Segre D, Vitkup D, Church GM (2002) Analysis of optimality in natural and perturbed metabolic networks. Proc Natl Acad Sci U S A 99(23):15112–15117

    Article  PubMed  CAS  Google Scholar 

  33. Shlomi T, Berkman O, Ruppin E (2005) Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc Natl Acad Sci U S A 102(21):7695–7700

    Article  PubMed  CAS  Google Scholar 

  34. Lonien J, Schwender J (2009) Analysis of metabolic flux phenotypes for two Arabidopsis mutants with severe impairment in seed storage lipid synthesis. Plant Physiol 151(3):1617–1634

    Article  PubMed  CAS  Google Scholar 

  35. Schellenberger J, Que R, Fleming RM et al (2011) Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0. Nat Protoc 6(9):1290–1307

    Article  PubMed  CAS  Google Scholar 

  36. Lam HM, Coschigano K, Schultz C et al (1995) Use of arabidopsis mutants and genes to study amide amino-acid biosynthesis. Plant Cell 7(7):887–898

    PubMed  CAS  Google Scholar 

  37. Hess JL, Tolbert NE (1967) Glycolate pathway in algae. Plant Physiol 42(3):371–379

    Article  PubMed  CAS  Google Scholar 

  38. Miller RM, Meyer CM, Tanner HA (1963) Glycolate excretion & uptake by chlorella. Plant Physiol 38(2):184–188

    Article  PubMed  CAS  Google Scholar 

  39. Moroney JV, Wilson BJ, Tolbert NE (1986) Glycolate metabolism and excretion by chlamydomonas reinhardtii. Plant Physiol 82(3):821–826

    Article  PubMed  CAS  Google Scholar 

  40. Schellenberger J, Lewis NE, Palsson BO (2011) Elimination of thermodynamically infeasible loops in steady-state metabolic models. Biophys J 100(3):544–553

    Article  PubMed  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, Australia

    Cristiana G. O. Dal’Molin, Lake-Ee Quek, Robin W. Palfreyman & Lars K. Nielsen

Authors
  1. Cristiana G. O. Dal’Molin
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  2. Lake-Ee Quek
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  3. Robin W. Palfreyman
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  4. Lars K. Nielsen
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Editor information

Editors and Affiliations

  1. INRA Bordeaux Université Bordeaux Segalen, Villenave d'Ornon, France

    Martine Dieuaide-Noubhani

  2. Department of Molecular Genetics, The Ohio State University, Columbus, Ohio, USA

    Ana Paula Alonso

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Dal’Molin, C.G.O., Quek, LE., Palfreyman, R.W., Nielsen, L.K. (2014). Plant Genome-Scale Modeling and Implementation. In: Dieuaide-Noubhani, M., Alonso, A. (eds) Plant Metabolic Flux Analysis. Methods in Molecular Biology, vol 1090. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-688-7_19

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  • DOI: https://doi.org/10.1007/978-1-62703-688-7_19

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-687-0

  • Online ISBN: 978-1-62703-688-7

  • eBook Packages: Springer Protocols

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