Rapid determination of biosynthetic pathways using fractional isotope enrichment and high-resolution dynamic nuclear polarization enhanced NMR. Academic Article uri icon

abstract

  • Carbon-13 NMR has traditionally been a method of choice for the determination of metabolic pathways. Through fractional labeling, (13)C spectra allow the identification of fragments incorporated as a unit into a biosynthesized molecule. The low sensitivity of (13)C spectroscopy is an impediment to such studies, especially if compounded with an often limited availability of biosynthesized molecules. Dynamic nuclear polarization (DNP) can increase the signal-to-noise ratio in magnetic resonance by several orders of magnitude, and in combination with high-resolution spectroscopy has the potential to increase the reach of this technique for metabolic profiling. Here, we present an application of high-resolution DNP enhanced NMR to the study of the biosynthetic pathways for membrane lipids. We show that fatty acid methyl esters are readily hyperpolarized in organic solvent. The resulting spectra resolve the various structural features of the chains, including atoms near the termini, as well as unsaturated and cyclopropyl groups. Peak patterns observed in fractionally labeled samples are explained by the way feed molecules are incorporated into fatty acid chains during synthesis. Differences in multiplet intensity between samples made from glucose and acetate feedstock mixtures further reveal metabolic preferences for these precursors in the biosynthesis of the product. In addition to the present study of lipid biosynthesis, high-resolution DNP-NMR of fractionally (13)C-labeled metabolites may present itself for the rapid determination of biosynthetic pathways in various biomedical applications, especially in cases of limited availability of the products of interest.

author list (cited authors)

  • Bowen, S., Sekar, G., & Hilty, C

citation count

  • 13

complete list of authors

  • Bowen, Sean||Sekar, Giridhar||Hilty, Christian

publisher