Mass spectrometry imaging to explore molecular heterogeneity in cell culture

被引:42
|
作者
Bien, Tanja [1 ,2 ]
Koerfer, Krischan [3 ,4 ]
Schwenzfeier, Jan [1 ]
Dreisewerd, Klaus [1 ,2 ]
Soltwisch, Jens [1 ,2 ]
机构
[1] Univ Munster, Inst Hyg, D-48149 Munster, Germany
[2] Univ Munster, Interdisciplinary Ctr Clin Res IZKF, D-48149 Munster, Germany
[3] Univ Munster, Inst Psychol, D-48149 Munster, Germany
[4] Univ Munster, Otto Creutzfeldt Ctr Cognit & Behav Neurosci, D-48149 Munster, Germany
关键词
single-cell mass spectrometry; t-MALDI-2-MSI; cellular heterogeneity; lipidomics; SINGLE CELLS; SAMPLE PREPARATION; MALDI-MS; INDIVIDUALITY; POPULATIONS; EXPRESSION; PLASTICITY; RESOLUTION; REVEALS;
D O I
10.1073/pnas.2114365119
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Molecular analysis on the single-cell level represents a rapidly growing field in the life sciences. While bulk analysis from a pool of cells provides a general molecular profile, it is blind to heterogeneities between individual cells. This heterogeneity, however, is an inherent property of every cell population. Its analysis is fundamental to understanding the development, function, and role of specific cells of the same genotype that display different phenotypical properties. Single-cell mass spectrometry (MS) aims to provide broad molecular information for a significantly large number of cells to help decipher cellular heterogeneity using statistical analysis. Here, we present a sensitive approach to single-cell MS based on high-resolution MALDI-2-MS imaging in combination with MALDI-compatible staining and use of optical microscopy. Our approach allowed analyzing large amounts of unperturbed cells directly from the growth chamber. Confident coregistration of both modalities enabled a reliable compilation of single-cell mass spectra and a straightforward inclusion of optical as well as mass spectrometric features in the interpretation of data. The resulting multimodal datasets permit the use of various statistical methods like machine learning-driven classification and multivariate analysis based on molecular profile and establish a direct connection of MS data with microscopy information of individual cells. Displaying data in the form of histograms for individual signal intensities helps to investigate heterogeneous expression of specific lipids within the cell culture and to identify subpopulations intuitively. Ultimately, t-MALDI-2-MSI measurements at 2-mu m pixel sizes deliver a glimpse of intracellular lipid distributions and reveal molecular profiles for subcellular domains.
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页数:12
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