Solutions for low and high accuracy mass spectrometric data matching: a data-driven annotation strategy in nontargeted metabolomics.

Ultra high pressure liquid chromatography coupled to mass spectrometry (UHPLC-MS) has become a widespread analytical technique in metabolomics investigations, however the benefit of high-performance chromatographic separation is often blunted due to insufficient mass spectrometric accuracy. A strategy that allows for the matching of UHPLC-MS data to highly accurate direct infusion electrospray ionization (DI-ESI) Fourier transform ion cyclotron resonance/mass spectrometry (FTICR/MS) data is developed in this manuscript. Mass difference network (MDiN) based annotation of FTICR/MS data and matching to unique UHPLC-MS peaks enables the consecutive annotation of the chromatographic data set. A direct comparison of experimental m/z values provided no basis for the matching of both platforms. The matching of annotation-based exact neutral masses finally enabled the integration of platform specific multivariate statistical evaluations, minimizing the danger to compare artifacts generated on either platform. The approach was developed on a non-alcoholic fatty liver disease (NAFLD) data set.