LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling.

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of 1H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, 1H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative 1H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by 1H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Unravelling and Quantifying the "NMR-Invisible" Metabolites Interacting with Human Serum Albumin by Binding Competition and T2 Relaxation-Based Decomposition Analysis.

Quantitative profiling of low-molecular-weight metabolites (LMWMs) by 1H NMR is routinely used in high-throughput serum metabolomics. First, the protein background is attenuated using a T2 filter; then, the LMWM signals are resolved by line-shape fitting. However, protein-binding modifies the motional properties of LMWM, and their signal partially attenuates with the T2 filter, along with the protein background. Consequently, the quantified LMWM signals do not reflect the total concentration in serum but the nonbinding part. Here we present a novel strategy based on binding competition to promote the release of the "NMR-invisible" metabolites from serum proteins and achieve quantifications closer to total concentrations. The study focuses on five clinically relevant amino acids with different binding properties (valine, isoleucine, leucine, tyrosine, and phenylalanine). We analyzed their binding affinity to human serum albumin (HSA) in serum mimic samples and promoted the release of their bound fraction by TSP titration. Furthermore, we used a novel combination of pseudo-2D CPMG and multivariate curve resolution analysis, allowing the separation of LMWM and protein signals and providing LMWM quantifications corrected for transverse relaxation effects. We found that TSP concentrations larger than 3 mM released most of the bound fraction and validated these findings in real serum/plasma samples.

Lipid Profiling Using 1H NMR Spectroscopy.

Lipid profiling, which includes fatty acids, phospholipids, glycerides, and cholesterols is extremely important because of the essential role lipids play in the regulation of metabolism in animals. 1H-NMR-based protocols for high-throughput lipid analysis in complex mixtures have been developed and applied to biological systems. Many classes of lipids can be quantitatively analyzed in many sample matrices including serum, cells, and tissues using a simple 1H NMR experiment. In this chapter, we provide protocols for NMR-based lipid profiling including sample preparation, NMR experiments, and quantification using the LipSpin software tool.