Issue 6, 2023

Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Abstract

Mass spectrometry imaging (MSI) is an effective technique for visualizing the distribution of lipids in tissues. The direct extraction-ionization methods using minute volumes of solvent for local components have the advantage of rapid measurement without any sample pretreatment. For effective MSI of tissues, it is necessary to understand the effect of solvent physicochemical properties on ion images. In this study, we report solvent effects on the lipid imaging of mouse brain tissue by tapping-mode scanning probe electrospray ionization (t-SPESI) which is capable of extraction-ionization using sub-pL solvents. To precisely measure lipid ions, we developed a measurement system incorporating a quadrupole-time-of-flight mass spectrometer. The differences in signal intensity and spatial resolution of lipid ion images were investigated using N,N-dimethylformamide (non-protic polar solvent), methanol (protic polar solvent) and their mixture. The mixed solvent was suitable for the protonation of lipids, and it provided high spatial resolution MSI. Results indicate that the mixed solvent improves the extractant transfer efficiency and minimizes charged droplets from an electrospray. The solvent selectivity study revealed the importance of solvent selection based on physicochemical properties for the advancement of MSI by t-SPESI.

Graphical abstract: Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Supplementary files

Article information

Article type
Paper
Submitted
30 Nov 2022
Accepted
16 Feb 2023
First published
20 Feb 2023
This article is Open Access
Creative Commons BY license

Analyst, 2023,148, 1275-1284

Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Y. Otsuka, N. Ote, M. Sun, S. Shimma, O. Urakawa, S. Yamaguchi, T. Kudo and M. Toyoda, Analyst, 2023, 148, 1275 DOI: 10.1039/D2AN01953A

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