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Optimising MALDI on PEN substrates for small molecule analysis in the context of same-section multimodal workflows

Hugo DelattreiD, Seren Piper, Ahmed Abdelhamed, Johanna von GerichteniD, Josephine BunchiD, Melanie Jane BaileyiD, Rory T. SteveniD

Abstract

Multimodal imaging workflows increasingly require multiple analytical techniques to be applied to the same tissue section to improve spatial co-registration and molecular interpretation. Polyethylene naphthalate (PEN) membrane substrates are attractive for this purpose because of their low thickness and compatibility with downstream modalities, but their use for matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI MSI) remains challenging due to low conductivity, reduced ion yield and susceptibility to laser-induced damage. In this study, MALDI MSI conditions for small-molecule analysis on PEN substrates were systematically optimised using bovine brain homogenate and mouse brain tissue using a TimsTOF flex MALDI-2 platform. Matrix selection, laser energy, pixel size (5 and 20 m), ionisation mode and PEN type were evaluated to identify acquisition conditions that balanced signal intensity with spectral quality and preservation of sample and membrane integrity. Among the matrices tested, 1,5-diaminonaphthalene (DAN) resulted in the best overall performance, providing higher ion intensities, less damage to the PEN substrates and a broader usable laser energy range than the other matrices tested. Different PEN substrate formats were also compared, showing distinct trade-offs between analytical performance and practical suitability for multimodal analysis. Under the tested conditions, glass-supported PEN (gPEN) provided the most practical overall compromise, while frame-supported PEN was not suitable for routine analysis on the instrument configuration used. Application of the optimised method to mouse brain tissue confirmed that spatially resolved metabolite imaging on PEN substrates is feasible and can support same-section multimodal workflows.

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02 /Specification & Classification

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