Issue 20, 2023

Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging

Abstract

In this study, we conducted a direct comparison of water-assisted laser desorption ionization (WALDI) and matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging, with MALDI serving as the benchmark for label-free molecular tissue analysis in biomedical research. Specifically, we investigated the lipidomic profiles of several biological samples and calculated the similarity of detected peaks and Pearson's correlation of spectral profile intensities between the two techniques. We show that, overall, MALDI MS and WALDI MS present very close lipidomic analyses and that the highest similarity is obtained for the norharmane MALDI matrix. Indeed, for norharmane in negative ion mode, the lipidomic spectra revealed 100% similarity of detected peaks and over 0.90 intensity correlation between both technologies for five samples. The MALDI-MSI positive ion lipid spectra displayed more than 83% similarity of detected peaks compared to those of WALDI-MSI. However, we observed a lower percentage (77%) of detected peaks when comparing WALDI-MSI with MALDI-MSI due to the rich WALDI-MSI lipid spectra. Despite this difference, the global lipidomic spectra showed high consistency between the two technologies, indicating that they are governed by similar processes. Thanks to this similarity, we can increase datasets by including data from both modalities to either co-train classification models or obtain cross-interrogation.

Graphical abstract: Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging

Supplementary files

Article information

Article type
Communication
Submitted
30 Jun 2023
Accepted
15 Sep 2023
First published
15 Sep 2023
This article is Open Access
Creative Commons BY-NC license

Analyst, 2023,148, 4982-4986

Comparing MS imaging of lipids by WALDI and MALDI: two technologies for evaluating a common ground truth in MS imaging

L. Ledoux, Y. Zirem, F. Renaud, L. Duponchel, M. Salzet, N. Ogrinc and I. Fournier, Analyst, 2023, 148, 4982 DOI: 10.1039/D3AN01096A

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