Improvement of Sensitivity and Reproducibility for Imaging of Endogenous Metabolites by Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry

Tomomi Morikawa-Ichinose, Yoshinori Fujimura, Fusa Murayama, Yuzo Yamazaki, Takushi Yamamoto, Hiroyuki Wariishi, Daisuke Miura

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) is a powerful technique to visualize the distributions of biomolecules without any labeling. In MALDI-MSI experiments, the choice of matrix deposition method is important for acquiring favorable MSI data with high sensitivity and high reproducibility. Generally, manual or automated spray-coating and automated sublimation methods are used, but these methods have some drawbacks with respect to detection sensitivity, spatial resolution, and data reproducibility. Herein, we present an optimized matrix deposition method of sublimation coupled with recrystallization using 9-aminoacridine (9-AA) as a matrix capable of ionizing endogenous metabolites. The matrix recrystallization process after sublimation was optimized for the solvent concentration and reaction temperature for matrix–metabolite co-crystallization. This optimized method showed excellent reproducibility and spatial resolution compared to the automatic spray-coating method. Furthermore, the recrystallization step after sublimation remarkably improved the detectability of metabolites, including amino acids, nucleotide derivatives, and lipids, compared with the conventional sublimation method. To date, there have been no other reports of 9-AA-based sublimation combined with recrystallization. The present method provides an easy, sensitive, and reproducible matrix deposition method for MALDI-MSI of endogenous metabolites. [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)1512-1520
Number of pages9
JournalJournal of the American Society for Mass Spectrometry
Volume30
Issue number8
DOIs
Publication statusPublished - Aug 15 2019

All Science Journal Classification (ASJC) codes

  • Structural Biology
  • Spectroscopy

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