Evaluation of lipid coverage and high spatial resolution MALDI-imaging capabilities of oversampling combined with laser post-ionisation
Evaluation of lipid coverage and high spatial resolution MALDI-imaging capabilities of oversampling combined with laser post-ionisation
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DOI：
10.1007/s00216-019-02290-3
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发表时间：
2019-12-26
影响因子：
4.3
通讯作者：
Ellis, Shane R.
中科院分区：
文献类型：
--
作者：
Bowman, Andrew P.;Bogie, Jeroen F. J.;Ellis, Shane R.
基质辅助激光解吸/电离质谱成像（MALDI-MSI）是一种强大的技术，用于可视化生物组织中脂质的空间位置。然而，在解释使用MALDI-MSI检测的局部脂质组成和分布的生物学意义方面的主要挑战是难以将光谱与组织内的细胞脂质代谢相关联。总的来说，这是由于MALDI-MSI的空间分辨率通常有限（30-100 μ m），这意味着单个光谱代表从多个相邻细胞获得的平均光谱，每个细胞可能具有独特的脂质组成和生物功能。过采样技术是一种有效的减小采样面积、提高空间分辨率的方法，但其灵敏度会大大降低。在这项工作中，我们克服了这些挑战，通过耦合过采样MALDI-MSI与激光后电离（MALDI-2）。我们证明了从像素小至6 μ m，相当于或小于典型的哺乳动物细胞的大小获取丰富的脂质光谱的能力。再加上自动脂质识别的方法，它表明，MALDI-2结合过采样在6 μ m的像素大小可以检测到高达三倍以上的脂质和更多的脂质类甚至比传统的MALDI在20 μ m的分辨率在正离子模式。将其应用于含有活动性多发性硬化病变的小鼠肾脏和人脑组织，其中分别鉴定出74和147种独特的脂质，脂质信号定位于肾脏内的个体微管和具有病变特异性巨噬细胞的脂滴。
Matrix-assisted laser desorption/ionisation-mass spectrometry imaging (MALDI-MSI) is a powerful technique for visualising the spatial locations of lipids in biological tissues. However, a major challenge in interpreting the biological significance of local lipid compositions and distributions detected using MALDI-MSI is the difficulty in associating spectra with cellular lipid metabolism within the tissue. By-and-large this is due to the typically limited spatial resolution of MALDI-MSI (30-100 mu m) meaning individual spectra represent the average spectrum acquired from multiple adjacent cells, each potentially possessing a unique lipid composition and biological function. The use of oversampling is one promising approach to decrease the sampling area and improve the spatial resolution in MALDI-MSI, but it can suffer from a dramatically decreased sensitivity. In this work we overcome these challenges through the coupling of oversampling MALDI-MSI with laser post-ionisation (MALDI-2). We demonstrate the ability to acquire rich lipid spectra from pixels as small as 6 mu m, equivalent to or smaller than the size of typical mammalian cells. Coupled with an approach for automated lipid identification, it is shown that MALDI-2 combined with oversampling at 6 mu m pixel size can detect up to three times more lipids and many more lipid classes than even conventional MALDI at 20 mu m resolution in the positive-ion mode. Applying this to mouse kidney and human brain tissue containing active multiple sclerosis lesions, where 74 and 147 unique lipids are identified, respectively, the localisation of lipid signals to individual tubuli within the kidney and lipid droplets with lesion-specific macrophages is demonstrated.