It has been widely recognized that individual cells that exist within a large population of cells, even if they are genetically identical, can have divergent molecular makeups resulting from a variety of factors, including local environmental factors and stochastic processes within each cell. Presently, numerous approaches have been described that permit the resolution of these single-cell expression differences for RNA and protein; however, relatively few techniques exist for the study of lipids and metabolites in this manner. This study presents a methodology for the analysis of metabolite and lipid expression at the level of a single cell through the use of imaging mass spectrometry on a high-performance Fourier transform ion cyclotron resonance mass spectrometer. This report provides a detailed description of the overall experimental approach, including sample preparation as well as the data acquisition and analysis strategy for single cells. Applying this approach to the study of cultured RAW264.7 cells, we demonstrate that this method can be used to study the variation in molecular expression with cell populations and is sensitive to alterations in that expression that occurs upon lipopolysaccharide stimulation.

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众所周知，存在于大量细胞中的单个细胞，即使它们在遗传上是相同的，也可能由于多种因素而产生不同的分子组成，这些因素包括局部环境因素和每个细胞内的随机过程。目前，已经描述了许多方法，这些方法可以解决RNA和蛋白质的这些单细胞表达差异。但是，以这种方式研究脂质和代谢物的技术相对较少。这项研究提出了一种通过在高性能傅立叶变换离子回旋共振质谱仪上使用成像质谱法在单个细胞水平上分析代谢物和脂质表达的方法。该报告详细介绍了整个实验方法，包括样品制备以及单个细胞的数据采集和分析策略。将这种方法应用于培养的RAW264.7细胞的研究中，我们证明了该方法可用于研究分子表达随细胞群体的变化，并且对脂多糖刺激后发生的表达变化很敏感。

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