The biomass composition of soybeans is fundamental in establishing its market price. Soy proteins have a huge market as raw material for animal feed, other food products and industrial non-food applications. Soybean oil is used in cooking, in making margarine and in industrial applications, particularly biodiesel and lubricants. It has additionally been observed that there is an inverse relationship between the protein and oil content in soybeans. However, the underlying physiology causing this inverse relationship remains unclear.

¹³C metabolic flux analysis (MFA) is an effective tool for elucidating underlying physiology of a biological system. This study involved comparison of intracellular fluxes of three different soybean genotypes with considerable difference in protein contents to investigate the changes in the pathway interactions. BC3-128 genotype, a back crossed line created from High PI and Evans, produced more protein than Evans and less than High PI. Further, Evans had the maximum lipid content, followed by BC3-128 and then High PI. The starch content was highest in Evans, then High PI, followed by BC3-128. It was additionally observed that the BC3-128 was also nearly isogenic to Evans and as a plant, grew as well as Evans in the fields.

¹³C MFA was performed on soybeans of the above three genotypes during early stages of development (21 days after flowering) to analyze the central carbon metabolism. The ¹³C labeling pattern, which is reflected in the proteinogenic amino acids and starch, was analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy using 2-dimensional (2D) HSQC (¹H, ¹³C Heteronuclear single quantum correlated spectroscopy) to evaluate the extent of carbon-carbon bond coupling. Extracellular measurements coupled with NMR analysis were employed to quantify the fluxes in the pathways of the three genotypes, using a generic mathematical framework developed in our lab, NMR2Flux.

Comparisons of the intracellular fluxes between the three genotypes enable the development of hypotheses of important metabolic nodes in protein/oil partitioning. We will present metabolic maps for the three soybean genotypes with quantitative values of the intracellular fluxes, as well as summaries of highly flexible and rigid nodes in the metabolic network.