2026-03-27 理化学研究所,慶應義塾大学,科学技術振興機構
新手法SMASH imagingによって脂質分布の空間地図（リピドームアトラス）を構築
＜関連情報＞
- https://www.riken.jp/press/2026/20260327_1/index.html
- https://pubs.acs.org/doi/10.1021/acs.analchem.5c03738
SMASHイメージング：高解像度イメージングのための連続マトリックス支援レーザー脱離イオン化質量分析戦略により、単一組織切片上でのデュアル極性およびMS2空間リピドミクスが可能になる SMASH Imaging: A Serial Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Strategy for High-Resolution Imaging Facilitates Dual-Polarity and MS2 Spatial Lipidomics on a Single Tissue Section
Haruki UchinoHiroshi Tsugawa,and Makoto Arita
Analytical Chemistry Published: March 26, 2026
DOI:https://doi.org/10.1021/acs.analchem.5c03738
Abstract
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is a key technology in spatial lipidomics that provides high sensitivity and spatial resolution. Because of the ionization preference of lipid classes and the lack of detailed structural information without MS2 data, dual-polarity analyses and the acquisition of MS/MS spectra are essential to improve coverage and annotation accuracy. Multitime MSI analyses of the same tissue section can provide seamless integration of multimodal spatial data. However, the feasibility of performing serial MALDI-MSI for the same pixels with high spatial resolution has not been fully evaluated. Here, we present SMASH imaging for dual-polarity and MS2 spatial lipidomics in a single tissue section. We estimated two characteristic matrix compounds, 2,5-dihydroxyacetophenone and trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene]malononitrile, for dual-polarity analyses and defined the feasible number of layers of SMASH imaging via the coefficient of determination (R2). SMASH imaging successfully visualized over 400 lipid species on average with a 30 μm resolution, with annotation criteria S/N ≥ 50, m/z ≤ 10 mDa, and collision cross section ≤ 20 Å2. In four layers of SMASH imaging, the molecular species of 18 lipids were characterized based on MS2 spectra evidence using parallel accumulation-serial fragmentation on a single mouse brain section. Moreover, eight layers of SMASH imaging with a 5 μm spatial resolution annotated 25 lipid species, supported by a spatial correlation metric between multimodal data. Our approach provides multimodal spatial lipidomics to create a lipidome atlas with accurate annotation and high spatial resolution on a single tissue section.
