The Impact of the Serum Extraction Protocol on Metabolomic Profiling Using UPLC-MS/MS and FTIR Spectroscopy

Biofluid metabolomics is a very appealing tool to increasetheknowledge associated with pathophysiological mechanisms leading tobetter and new therapies and biomarkers for disease diagnosis andprognosis. However, due to the complex process of metabolome analysis,including the metabolome isolation method and the platform used toanalyze it, there are diverse factors that affect metabolomics output.In the present work, the impact of two protocols to extract the serummetabolome, one using methanol and another using a mixture of methanol,acetonitrile, and water, was evaluated. The metabolome was analyzedby ultraperformance liquid chromatography associated with tandem massspectrometry (UPLC-MS/MS), based on reverse-phase and hydrophobicchromatographic separations, and Fourier transform infrared (FTIR)spectroscopy. The two extraction protocols of the metabolome werecompared over the analytical platforms (UPLC-MS/MS and FTIR spectroscopy)concerning the number of features, the type of features, common features,and the reproducibility of extraction replicas and analytical replicas.The ability of the extraction protocols to predict the survivabilityof critically ill patients hospitalized at an intensive care unitwas also evaluated. The FTIR spectroscopy platform was compared tothe UPLC-MS/MS platform and, despite not identifying metabolites andconsequently not contributing as much as UPLC-MS/MS in terms of informationconcerning metabolic information, it enabled the comparison of thetwo extraction protocols as well as the development of very good predictivemodels of patient's survivability, such as the UPLC-MS/MS platform.Furthermore, FTIR spectroscopy is based on much simpler proceduresand is rapid, economic, and applicable in the high-throughput mode,i.e., enabling the simultaneous analysis of hundreds of samples inthe microliter range in a couple of hours. Therefore, FTIR spectroscopyrepresents a very interesting complementary technique not only tooptimize processes as the metabolome isolation but also for obtainingbiomarkers such as those for disease prognosis.