Analysis of proteinogenic amino acid and starch labeling by 2D NMR

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 [ 1 H, 13 C] Nuclear Magnetic Resonance (2D NMR) spectroscopy. From 13 C-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. © Springer Science+Business Media New York 2014.