RESUMO
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.
