Matrix-assisted laser desorption/ionization imaging mass spectrometry

Journal Article (2026)
Author(s)

Jeffrey M. Spraggins (Vanderbilt University Medical Center, VanderBilt University)

Amanda B. Hummon (The Ohio State University)

Shane R. Ellis (University of Wollongong)

Lingjun Li (University of Wisconsin-Madison)

Boone M. Prentice (University of Florida)

Martina Marchetti-Deschmann (University of Veterinary Medicine, Technische Universität Wien)

Raf Van de Plas (VanderBilt University, TU Delft - Mechanical Engineering)

Richard M. Caprioli (VanderBilt University)

Research Group
Team Raf Van de Plas
DOI related publication
https://doi.org/10.1038/s43586-026-00492-5 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Team Raf Van de Plas
Journal title
Nature Reviews Methods Primers
Issue number
1
Volume number
6
Article number
44
Downloads counter
10
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Abstract

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a transformative molecular imaging technology capable of mapping diverse chemical classes, from small metabolites, neurotransmitters and lipids to N-glycans and proteins, at cellular resolution. The field has rapidly matured, offering a range of mass analysers, including axial time-of-flight, quadrupole (or orthogonal) time-of-flight, and high-resolution Orbitrap and Fourier-transform ion cyclotron resonance systems, each with distinct characteristics in terms of spatial resolution, chemical specificity and throughput. In practice, MALDI IMS involves applying a light-absorbing chemical matrix onto a tissue section, followed by automated laser irradiation at discrete coordinates (like pixels) to desorb and ionize endogenous molecules for mass analysis. This label-free approach preserves spatial context, providing a molecular map that links highly multiplexed molecular distributions to distinct anatomical regions, functional tissue units and cell types in situ. This Primer includes an overview of basic imaging MALDI IMS concepts, instrumentation, data processing approaches and advanced applications. We also address key challenges and considerations, with an eye towards optimizing instrumentation and methods to overcome issues in spatial resolution, sensitivity and specificity. Finally, we look towards the future of the technology, including its integration with other spatial omics modalities and its potential as a tool for precision medicine.

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