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通过离线高效薄层层析-基质辅助激光解吸电离飞行时间质谱分析干细胞脂质。

Analysis of stem cell lipids by offline HPTLC-MALDI-TOF MS.

作者信息

Fuchs Beate, Schiller Jürgen, Süss Rosmarie, Zscharnack Matthias, Bader Augustinus, Müller Peter, Schürenberg Martin, Becker Michael, Suckau Detlev

机构信息

Faculty of Medicine, Institute of Medical Physics and Biophysics, University of Leipzig, Härtelstrasse 16-18, 04107, Leipzig, Germany.

出版信息

Anal Bioanal Chem. 2008 Nov;392(5):849-60. doi: 10.1007/s00216-008-2301-8. Epub 2008 Aug 5.

DOI:10.1007/s00216-008-2301-8
PMID:18679659
Abstract

MALDI-TOF MS is traditionally used for "proteomics", but is also a useful tool for lipid analysis. Depending on the applied matrix, however, some lipid classes are more sensitively detected than other ones and this may even lead to suppression effects if complex mixtures are analyzed. Therefore, a previous separation into the individual lipid classes is necessary. Using artificial lipid mixtures or easily available tissue extracts, it has been already shown that HPTLC-(High Performance Thin-Layer Chromatography)-separated lipids can be conveniently analyzed by MALDI-TOF MS directly on the TLC plate. Here we present an initial TLC-MALDI study of the lipid composition of ovine mesenchymal stem cells. Due to the complex composition of these cells, data are also compared to lipids extracted from human erythrocytes. It will be shown that even very minor lipid classes can be easily detected and with much higher sensitivity than by common staining protocols. Additionally, MS images of the developed TLC plates will be shown and potential applications, new methods of data analysis as well as problems discussed.

摘要

基质辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)传统上用于“蛋白质组学”,但也是脂质分析的有用工具。然而,根据所应用的基质,某些脂质类别比其他类别更能被灵敏地检测到,如果分析复杂混合物,这甚至可能导致抑制效应。因此,事先将脂质分离成各个类别是必要的。使用人工脂质混合物或容易获得的组织提取物,已经表明,通过MALDI-TOF MS可以直接在薄层色谱(TLC)板上方便地分析经高效薄层色谱(HPTLC)分离的脂质。在此,我们展示了对绵羊间充质干细胞脂质组成的初步TLC-MALDI研究。由于这些细胞的组成复杂,数据也与从人红细胞中提取的脂质进行了比较。结果将表明,即使是非常微量的脂质类别也能很容易地被检测到,并且比通过常规染色方法具有更高的灵敏度。此外,还将展示展开后的TLC板的质谱图像,并讨论潜在应用、新的数据分析方法以及存在的问题。

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