Abstract
Lipids play crucial roles in human biology, serving as energy stores, cell membranes, hormone production, and signaling molecules. Accordingly, their study under lipidomics has advanced the study of living organisms. 1-Dimensional (D) and 2D NMR methods, particularly 1D (1)H and 2D (1)H-(1)H Total Correlation Spectroscopy (TOCSY), are commonly used in lipidomics for quantification and structural identification. However, these NMR methods suffer from low sensitivity, especially in cases of low concentrated molecules such as protons attached to hydroxy, esters, aliphatic, or aromatic unsaturated carbons. Such molecules are common in complex mixtures such as dairy products and plant oils. On the other hand, lipids have highly populated fractions of methyl and methylene groups that result in intense peaks that overwhelm lower peaks and cause inhomogeneities in 2D TOCSY spectra. In this study, we applied a method of suppression to suppress these intense peaks of methyl and methylene groups to detect weaker peaks. The suppression method was investigated on samples of cheese, butter, a mixture of lipids, coconut oil, and olive oil. A significant improvement in peak sensitivity and visibility of cross-peaks was observed, leading to enhanced comparative quantification and structural identification of a greater number of lipids. Additionally, the enhanced sensitivity reduced the time required for the qualitative and comparative quantification of other lipid compounds and components. This, in turn, enables faster and more reliable structural identification and comparative quantification of a greater number of lipids. Additionally, it reduces the time required for the qualitative, and comparative quantification due to the enhancement of sensitivity.