Transmission-Mode Maldi Mass Spectrometry Imaging Of Single Cells: Optimizing Sample Preparation Protocols

ANALYTICAL CHEMISTRY(2021)

引用 30|浏览5
暂无评分
摘要
Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) makes it possible to simultaneously visualize the spatial distribution of dozens to hundreds of different biomolecules (e.g., phospho- and glycolipids) in tissue sections and in cell cultures. The implementation of novel desorption and (post-)ionization techniques has recently pushed the pixel size of this imaging technique to the low micrometer scale and below and thus to a cellular and potentially sub-cellular level. However, to fully exploit this potential for cell biology and biomedicine, sample preparation becomes highly demanding. Here, we investigated the effect of several key parameters on the quality of the sample preparation and achievable spatial resolution, that include the washing, drying, chemical fixation, and matrix coating steps. The incubation of cells with formalin for about 5 min in combination with isotonic washing and mild drying produced a robust protocol that largely preserved not only cell morphologies, but also the molecular integrities of amine group-containing cell membrane phospholipids (phosphatidylethanolamines and -serines). A disadvantage of the chemical fixation is an increased permeabilization of cell membranes, resulting in leakage of cytosolic compounds. We demonstrate the pros and cons of the protocols with four model cell lines, cultured directly on indium tin oxide (ITO)-coated glass slides. Transmission (t-)mode MALDI-2-MSI enabled on a Q Exactive plus Orbitrap mass spectrometer was used to analyze the cultures at a pixel size of 2 mu m. Phase contrast light microscopy and scanning electron microscopy were used as complementary methods. The protocols described could prove to be an important contribution to the advancement of single-cell MALDI imaging, especially for the characterization of cell-to-cell heterogeneities at a molecular level.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要