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制备型超临界流体色谱法进行脂质类别分离 - 基于高分辨率质谱脂质组学的新策略。

Preparative supercritical fluid chromatography for lipid class fractionation-a novel strategy in high-resolution mass spectrometry based lipidomics.

机构信息

Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringer Strasse 38, 1090, Vienna, Austria.

Vienna Metabolomics Center (VIME), University of Vienna, Althanstrasse 14, 1090, Vienna, Austria.

出版信息

Anal Bioanal Chem. 2020 Apr;412(10):2365-2374. doi: 10.1007/s00216-020-02463-5. Epub 2020 Mar 4.

DOI:10.1007/s00216-020-02463-5
PMID:32130438
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7118041/
Abstract

In this work, a lipidomics workflow based on offline semi-preparative lipid class-specific fractionation by supercritical fluid chromatography (SFC) followed by high-resolution mass spectrometry was introduced. The powerful SFC approach offered separation of a wide polarity range for lipids, enabled enrichment (up to 3 orders of magnitude) of lipids, selective fractionation of 14 lipid classes/subclasses, and increased dynamic range enabling in-depth characterization. A significantly increased coverage of low abundant lipids improving lipid identification by numbers and degree (species and molecular level) was obtained in Pichia pastoris when comparing high-resolution mass spectrometry based lipidomics with and without prior fractionation. Proof-of-principle experiments using a standard reference material (SRM 1950, NIST) for human plasma showed that the proposed strategy enabled quantitative lipidomics. Indeed, for 70 lipids, the consensus values available for this sample could be met. Thus, the novel workflow is ideally suited for lipid class-specific purification/isolation from milligram amounts of sample while not compromising on omics type of analysis (identification and quantification). Finally, compared with established fractionation/pre-concentration approaches, semi-preparative SFC is superior in terms of versatility, as it involved only volatile modifiers and salt additives facilitating any follow-up use such as qualitative or quantitate analysis or further purification down to the single lipid species level. Graphical Abstract.

摘要

在这项工作中,引入了一种基于超临界流体色谱(SFC)离线半制备脂质类别特异性分级的脂质组学工作流程,然后进行高分辨率质谱分析。强大的 SFC 方法提供了广泛的极性范围的脂质分离,能够实现脂质的富集(高达 3 个数量级)、14 种脂质类别/亚类的选择性分级以及动态范围的增加,从而实现深入的特征描述。与未经分级的高分辨率质谱脂质组学相比,毕赤酵母中低丰度脂质的覆盖度显著增加,从而提高了脂质的鉴定数量和程度(物种和分子水平)。使用人血浆标准参考物质(SRM 1950,NIST)进行的原理验证实验表明,所提出的策略能够实现定量脂质组学。实际上,对于 70 种脂质,可以满足该样品的共识值。因此,这种新型工作流程非常适合从毫克量的样品中进行脂质类别特异性的纯化/分离,而不会影响组学类型的分析(鉴定和定量)。最后,与已建立的分级/预浓缩方法相比,半制备 SFC 在多功能性方面具有优势,因为它只涉及挥发性修饰剂和盐添加剂,便于进行任何后续使用,如定性或定量分析或进一步纯化到单个脂质种类水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/aebc98d04f2b/216_2020_2463_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/a5782e056ae6/216_2020_2463_Figa_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/699b7856bf53/216_2020_2463_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/dc4a5ad7c2ec/216_2020_2463_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/e8d527f71354/216_2020_2463_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/223c0b4578d2/216_2020_2463_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/189ec4b43d43/216_2020_2463_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/aebc98d04f2b/216_2020_2463_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/a5782e056ae6/216_2020_2463_Figa_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/699b7856bf53/216_2020_2463_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/dc4a5ad7c2ec/216_2020_2463_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/e8d527f71354/216_2020_2463_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/223c0b4578d2/216_2020_2463_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/189ec4b43d43/216_2020_2463_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4407/7118041/aebc98d04f2b/216_2020_2463_Fig6_HTML.jpg

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