Cholesterol, the principal zoosterol, is a key metabolite linked to several health complications. Studies have shown its potential as a metabolic biomarker for predicting various diseases and determining food origin. However, the existing INEPT (insensitive nuclei enhanced by polarization transfer) 13 C position-specific isotope analysis method of cholesterol by NMR was not suitable for very precise analysis of small quantities due to its long acquisition time and therefore is restricted to products rich in cholesterol. In this work, a symmetric and adiabatic heteronuclear single quantum coherence (HSQC) 2D NMR sequence was developed for the high-precision (few permil) analysis of small quantities of cholesterol. Adiabatic pulses were incremented for improving precision and sensitivity. Moreover, several strategies such as the use of non-uniform sampling, linear prediction, and variable recycling time were optimized to reduce the acquisition time. The number of increments and spectral range were also adjusted. The method was developed on a system with a cryogenically cooled probe and was not tested on a room-temperature system. Our new approach allowed analyzing as low as 5 mg of cholesterol in 31 min with a long-term repeatability lower than 2‰ on the 24 non-quaternary carbon atoms of the molecule comparing to 16.2 h for the same quantity using the existing INEPT method. This result makes conceivable the isotope analysis of matrices low in cholesterol.
Quantitative nuclear magnetic resonance (NMR) for isotopic
measurements,
known as irm-NMR (isotope ratio measured by NMR), is well suited for
the quantitation of 13C-isotopomers in position-specific
isotope analysis and thus for measuring the carbon isotope composition
(δ13C, mUr) in C-atom positions. Irm-NMR has already
been used with glucose after derivatization to study sugar metabolism
in plants. However, up to now, irm-NMR has exploited a “single-pulse”
sequence and requires a relatively large amount of material and long
experimental time, precluding many applications with biological tissues
or extracts. To reduce the required amount of sample, we investigated
the use of 2D-NMR analysis. We adapted and optimized the NMR sequence
so as to be able to analyze a small amount (10 mg) of a glucose derivative
(diacetonide glucofuranose, DAGF) with a precision better than 1 mUr
at each C-atom position. We also set up a method to correct raw data
and express 13C abundance on the usual δ13C scale (δ-scale). In fact, due to the distortion associated
with polarization transfer and spin manipulation during 2D-NMR analyses,
raw 13C abundance is found to be on an unusual scale. This
was compensated for by a correction factor obtained via comparative
analysis of a reference material (commercial DAGF) using both previous
(single-pulse) and new (2D) sequences. Glucose from different biological
origins (CO2 assimilation metabolisms of plants, namely,
C3, C4, and CAM) was analyzed with the two sequences
and compared. Validation criteria such as selectivity, limit of quantification,
precision, trueness, and robustness are discussed, including in the
framework of green analytical chemistry.
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