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Analysis of Proteinogenic Amino Acid and Starch Labeling by 2D NMR

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Book cover Plant Metabolic Flux Analysis

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

Abstract

Comprehensive analysis of isotopic labeling patterns of metabolites in proteinogenic amino acids and starch for plant systems lay in the powerful tool of 2-Dimensional [1H, 13C] Nuclear Magnetic Resonance (2D NMR) spectroscopy. From 13C-labeling experiments, 2D NMR provides information on the labeling of particular carbon positions, which contributes to the quantification of positional isotope isomers (isotopomer). 2D Heteronuclear Single Quantum Correlation (HSQC) NMR distinguishes particularly between the labeling patterns of adjacent carbon atoms, and leads to a characteristic enrichment of each carbon atom of amino acids and glucosyl and mannosyl units present in hydrolysates of glycosylated protein. Furthermore, this technique can quantitatively classify differences in glucosyl units of starch hydrolysate and of protein hydrolysate of plant biomass. Therefore, the 2D HSQC NMR method uses proteinogenic amino acids and starch to provide an understanding of carbon distribution of compartmentalization in the plant system. NMR has the advantage of minimal sample handle without separate individual compounds prior to analysis, for example multiple isotopomers can be detected, and their distribution extracted quantitatively from a single 2D HSQC NMR spectrum. The peak structure obtained from the HSQC experiment show multiplet patterns, which are directly related to isotopomer balancing. These abundances can be translated to maximum information on the metabolic flux analysis. Detailed methods for the extractions of protein, oil, soluble sugars, and starch, hydrolysis of proteinogenic amino acid and starch, and NMR preparation using soybean embryos cultured in vitro as a model plant systems are reported in this text. In addition, this chapter includes procedures to obtain the relative intensity of 16 amino acids and glucosyl units from protein hydrolysate and the glucosyl units of starch hydrolysate of soybean embryos in 2D HSQC NMR spectra.

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References

  1. Wiechert W (2001) C-13 metabolic flux analysis. Metab Eng 3(3):195–206

    Article  PubMed  CAS  Google Scholar 

  2. Massou S, Nicolas C, Letisse F, Portais JC (2007) NMR-based fluxomics: Quantitative 2D NMR methods for isotopomers analysis. Phytochemistry 68:2330–2340

    Article  PubMed  CAS  Google Scholar 

  3. Kruger NJ, Masakapalli SK, Ratcliffe RG (2012) Strategies for investigating the plant metabolic network with steady-state metabolic flux analysis: lessons from an Arabidopsis cell culture and other systems. J Exp Bot 63:2309–2323

    Article  PubMed  CAS  Google Scholar 

  4. Szyperski T (1995) Biosynthetically directed fractional C-13-labeling of proteinogenic amino-acids—an efficient analytical tool to investigate intermediary metabolism. Eur J Biochem 232:433–448

    Article  PubMed  CAS  Google Scholar 

  5. Schmidt K, Nielsen J, Villadsen J (1999) Quantitative analysis of metabolic fluxes in escherichia coli, using two-dimensional NMR spectroscopy and complete isotopomer models. J Biotechnol 71(1–3):175–189

    Article  PubMed  CAS  Google Scholar 

  6. van Winden WA, Heijnen JJ, Verheijen PJT (2002) Cumulative bondomers: a new concept in flux analysis from 2D C-13, H-1 COSYNMR data. Biotechnol Bioeng 80(7):731–745

    Article  PubMed  Google Scholar 

  7. Yang C, Hua Q, Shimizu K (2002) Quantitative analysis of intracellular metabolic fluxes using GC-MS and two-dimensional NMR spectroscopy. J Biosci Bioeng 93(1):78–87

    PubMed  CAS  Google Scholar 

  8. Bodenhausen G, Ruben DJ (1980) Natural abundance nitrogen-15 NMR by enhanced heteronuclear spectroscopy. Chemical Physics Letters 69(1):185–189

    Article  CAS  Google Scholar 

  9. Last RL, Jones AD, Shachar-Hill Y (2007) Towards the plant metabolome and beyond. Nat Rev Mol Cell Biol 8(2):167–174

    Article  PubMed  CAS  Google Scholar 

  10. Sriram G, Iyer VV, Fulton DB, Shanks JV (2007) Identification of hexose hydrolysis products in metabolic flux analytes: a case study of levulinic acid in plant protein hydrolysate. Metab Eng 9:442–451

    Article  PubMed  CAS  Google Scholar 

  11. Sriram G, Fulton DB, Iyer VV, Peterson JM, Zhou RL, Westgate ME, Spalding MH, Shanks JV (2004) Quantification of compartmented metabolic fluxes in developing soybean embryos by employing Biosynthetic ally directed fractional C-13 labeling, C-13, H-1 two-dimensional nuclear magnetic resonance, and comprehensive isotopomer balancing. Plant Physiol 136:3043–3057

    Article  PubMed  CAS  Google Scholar 

  12. Masakapalli SK, Le Lay P, Huddleston JE, Pollock NL, Kruger NJ, Ratcliffe RG (2010) Subcellular flux analysis of central metabolism in a heterotrophic arabidopsis cell suspension using steady-state stable isotope labeling. Plant Physiol 152:602–619

    Article  PubMed  CAS  Google Scholar 

  13. Williams TCR, Miguet L, Masakapalli SK, Kruger NJ, Sweetlove LJ, Ratcliffe RG (2008) Metabolic network fluxes in heterotrophic arabidopsis cells: stability of the flux distribution under different oxygenation conditions. Plant Physiol 148(2):704–718

    Article  PubMed  CAS  Google Scholar 

  14. 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 

  15. Libourel IGL, Shachar-Hill Y (2008) Metabolic flux analysis in plants: from intelligent design to rational engineering. Annu Rev Plant Biol 59:625–650

    Article  PubMed  CAS  Google Scholar 

  16. Stephanopoulos G, Vallino JJ (1991) Network rigidity and metabolic engineering in metabolite overproduction. Science 252(5013):1675–1681

    Article  PubMed  CAS  Google Scholar 

  17. Ratcliffe RG, Shachar-Hill Y (2006) Measuring multiple fluxes through plant metabolic networks. Plant J 45(4):490–511

    Article  PubMed  CAS  Google Scholar 

  18. Schwender J (2008) Metabolic flux analysis as a tool in metabolic engineering of plants. Curr Opin Biotechnol 19(2):131–137

    Article  PubMed  CAS  Google Scholar 

  19. Allen DK, Ohlrogge JB, Shachar-Hill Y (2009) The role of light in soybean seed filling metabolism. Plant J 58(2):220–234

    Article  PubMed  CAS  Google Scholar 

  20. Iyer VV, Sriram G, Fulton DB, Zhou R, Westgate ME, Shanks JV (2008) Metabolic flux maps comparing the effect of temperature on protein and oil biosynthesis in developing soybean cotyledons. Plant Cell Environ 31(4):506–517

    Article  PubMed  CAS  Google Scholar 

  21. Alonso AP, Dale VL, Shachar-Hill Y (2010) Understanding fatty acid synthesis in developing maize embryos using metabolic flux analysis. Metab Eng 12(5):488–497

    Article  PubMed  Google Scholar 

  22. Alonso AP, Val DL, Shachar-Hill Y (2011) Central metabolic fluxes in the endosperm of developing maize seeds and their implications for metabolic engineering. Metab Eng 13(1):96–107

    Article  PubMed  CAS  Google Scholar 

  23. Alonso AP, Goffman FD, Ohlrogge JB, Shachar-Hill Y (2007) Carbon conversion efficiency and central metabolic fluxes in developing sunflower (Helianthus annuus L.) embryos. Plant J 52(2):296–308

    Article  PubMed  CAS  Google Scholar 

  24. Hay J, Schwender J (2011) Computational analysis of storage synthesis in developing Brassica napus L. (oilseed rape) embryos: flux variability analysis in relation to (13)C metabolic flux analysis. Plant J 67(3):513–525

    Article  PubMed  CAS  Google Scholar 

  25. Schwender J, Ohlrogge JB, Shachar-Hill Y (2003) A flux model of glycolysis and the oxidative pentosephosphate pathway in developing Brassica napus embryos. J Biol Chem 278(32):29442–29453

    Article  PubMed  CAS  Google Scholar 

  26. Schwender J, Shachar-Hill Y, Ohlrogge JB (2006) Mitochondrial metabolism in developing embryos of Brassica napus. J Biol Chem 281(45):34040–34047

    Article  PubMed  CAS  Google Scholar 

  27. Stepansky A, Leustek T (2006) Histidine biosynthesis in plants. Amino Acids 30(2):127–142

    Article  PubMed  CAS  Google Scholar 

  28. Bradford MM (1976) Rapid and sensitive method for quantitation of microgram quantities of protein utilizing principle of protein-Dye binding. Anal Biochem 72(1–2):248–254

    Article  PubMed  CAS  Google Scholar 

  29. Cohen SA (2000) Amino acid analysis using precolumn derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate. Methods Mol Biol 159:39–47

    PubMed  CAS  Google Scholar 

  30. Johnson BA, Blevins RA (1994) NMR view—a computure-program for the visualization and analysis of NMR data. J Biomol Nmr 4(5):603–614

    Article  PubMed  CAS  Google Scholar 

  31. Wuthrich K (1976) NMR in biological research: peptides and proteins. North Holland, Amsterdam

    Google Scholar 

  32. Harris RK (1983) Nuclear magnetic resonance spectroscopy: a physiochemical view. Pitman Books, London

    Google Scholar 

  33. Krivdin LB, Kalabin GA (1989) Structural applications of One-bond carbon-carbon spin-spin coupling-constants. Prog Nucl Magn Reson Spectrosc 21:293–448

    Article  CAS  Google Scholar 

  34. Brown LR (1984) Differential scaling along omega-1 in COSY experiments. J Magn Reson 57(3):513–518

    CAS  Google Scholar 

  35. Willker W, Flogel U, Leibfritz D (1997) Ultra-high-resolved HSQC spectra of multiple-C-13-labeled biofluids. J Magn Reson 125(1):216–219

    Article  PubMed  CAS  Google Scholar 

  36. van Winden W, Schipper D, Verheijen P, Heijnen J (2001) Innovations in generation and analysis of 2D C-13, H-1 COSYNMR spectra for metabolic flux analysis purposes. Metab Eng 3(4):322–343

    Article  PubMed  Google Scholar 

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Truong, Q., Shanks, J.V. (2014). Analysis of Proteinogenic Amino Acid and Starch Labeling by 2D NMR. 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_6

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  • DOI: https://doi.org/10.1007/978-1-62703-688-7_6

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-687-0

  • Online ISBN: 978-1-62703-688-7

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