Data-Independent Acquisition for Improved Compound Annotation in MALDI MS Imaging

High Resolution Image Download MS PowerPoint Slide Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) enables spatial mapping of biomolecules within biological tissues, where conventional MS 1 -based workflows often result in ambiguous compound annotations. Data-dependent acquisition (DDA) can improve annotation specificity but is biased toward high-abundant ions and lacks reproducibility. Here, we present a novel MALDI MSI workflow integrating data-independent acquisition (DIA) to obtain both spatial and fragmentation information. In this approach, MS 1 and DIA MS 2 spectra are acquired alternately across the sample without prior knowledge of compound localization. Each image pixel consists of one MS 1 and several DIA MS 2 subpixels, providing both high spatial resolution for MS 1 data and broad m / z coverage. Using small, randomized m / z isolation windows reduces spectral overlap and improves fragment-ion specificity. Data were processed using an extended Compound Discoverer, integrating mzCloud and LipidSearch for compound annotation. Applied to tissue of the parasitic worm Fasciola hepatica, this workflow produced detailed lipid maps and improved annotation confidence by combining precursor-mass, DIA MS 2, and spatial-correlation information. Our results demonstrate that DIA offers a flexible strategy to integrate fragmentation information into MALDI MSI, expanding its capabilities for spatial metabolomics.