Post-acquisition spectral stitching. An alternative approach for data processing in untargeted metabolomics by UHPLC-ESI(−)-HRMS.

Introduction In the case of the MS-based metabolomics, the large number of false positives remains a fundamental issue. Objective The aim of this study was to develop a new strategy, which highlights the number of the reliable features i.e. the detected features that correspond to a consistent peak according to chromatographic and mass spectrometric criteria. Method For the analysis blood samples from 20 chickens, which were administrated with naringin and 9 samples from control, were analyzed by UHPLC-HRMS (Orbitrap Velos). Two methodologies have been compared for data processing. In the first one (classical approach), all data in the 100–900  m/z mass-to charge range were included for the data processing procedure whereas for the newly developed methodology, the data were shred in 100 Da slices generating 8 datasets, which have been then subjected to the downstream MS data processing. Each dataset was treated separately and the m/z _t R features obtained by either VIP’s or t -test values were merged and used as the input for the construction of the general model. Results The new methodology resulted to a 4-fold increase of the peaks that could be considered chromatographically and mass spectrometrically valid. Conclusion A new strategy was reported on the detection of chromatographically reliable features during a metabolomic approach. The shredding of the LC–MS chromatograms into multiple m/z ranges increased the number of the identified chromatographically reliable features. [ABSTRACT FROM AUTHOR]