Spatialized Metabolomic Annotation Combining MALDI Imaging and Molecular Networks

Abstract

MALDI mass spectrometry imaging has gained major interest in the field of chemical imaging. This technique makes it possible to locate tens to hundreds of ionic signals on the sample surface without any a priori. One of the current challenges is still the limited ability to annotate signals in order to convert m/z values into probable chemical structures. At the same time, data obtained by LC-MS/MS have benefited from the development of numerous chemoinformatics tools, in particular molecular networks, for their efficient annotation. For the first time, we present here the combination of MALDI-FT-ICR imaging with molecular networks from MALDI-MS/MS data directly acquired on plant tissue sections. Annotation improvements are demonstrated, paving the way for new annotation pipelines for MALDI imaging.