当前位置: X-MOL 学术Anal. Bioanal. Chem. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Evaluation of lipid quantification accuracy using HILIC and RPLC MS on the example of NIST® SRM® 1950 metabolites in human plasma.
Analytical and Bioanalytical Chemistry ( IF 3.8 ) Pub Date : 2020-04-02 , DOI: 10.1007/s00216-020-02576-x
Mike Lange 1, 2 , Maria Fedorova 1, 2
Affiliation  

Lipidomics analysis for large-scale studies aiming at the identification and quantification of natural lipidomes is often performed using LC-MS-based data acquisition. However, the choice of suitable LC-MS method for accurate lipid quantification remains a matter of debate. Here, we performed the systematic comparison between two HRAM-MS-based quantification workflows based on HILIC and RPLC MS by quantifying 191 lipids from five lipid classes in human blood plasma using deuterated standards in the "one ISTD-per-lipid class" approach. Lipid quantification was performed considering all necessary isotopic corrections, and obtained correction factors are illustrated. Concentrations of lipids in NIST® SRM® 1950 human blood plasma determined by the two methods were comparable for most of the studied lipid species except for highly unsaturated phosphatidylcholines (PC). A comparison of lipid concentrations to consensus values determined in a previously published multi-laboratory study illustrated possible "overestimation" of concentrations for these highly unsaturated lipids by HILIC MS. We evaluated the influence of lipid loading amounts as well as the difference between quantified lipid and internal standard concentrations on the HILIC MS quantification results. We conclude that both HILIC and RPLC HRAM-MS workflows can be equally used for accurate lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and sphingomyelin (SM) lipid quantification, despite significant differences in the concentration of highly unsaturated PC lipids which need to be addressed by establishing response factors to account for the differences in degree of lipid unsaturation. Graphical.

中文翻译:

以人血浆中的 NIST® SRM® 1950 代谢物为例,使用 HILIC 和 RPLC MS 评估脂质定量准确性。

旨在鉴定和定量天然脂质组的大规模研究的脂质组学分析通常使用基于 LC-MS 的数据采集进行。然而,选择合适的 LC-MS 方法来准确定量脂质仍然存在争议。在这里,我们通过使用“每个脂质类别一个 ISTD”方法中的氘化标准品对人血浆中五个脂质类别的 191 种脂质进行定量,对两种基于 HILIC 和 RPLC MS 的基于 HRAM-MS 的定量工作流程进行了系统比较。考虑所有必要的同位素校正进行脂质定量,并说明了获得的校正因子。通过这两种方法测定的 NIST® SRM® 1950 人血浆中的脂质浓度对于大多数研究的脂质种类具有可比性,但高度不饱和磷脂酰胆碱 (PC) 除外。将脂质浓度与先前发表的多实验室研究中确定的共识值进行比较,表明 HILIC MS 对这些高度不饱和脂质的浓度可能“高估”。我们评估了脂质加载量以及定量脂质和内标浓度之间的差异对 HILIC MS 定量结果的影响。我们得出的结论是,HILIC 和 RPLC HRAM-MS 工作流程都可以同样用于准确的溶血磷脂酰胆碱 (LPC)、溶血磷脂酰乙醇胺 (LPE)、磷脂酰胆碱 (PC)、磷脂酰乙醇胺 (PE) 和鞘磷脂 (SM) 脂质定量,尽管两者的差异显着高度不饱和 PC 脂质的浓度,需要通过建立响应因子来解决脂质不饱和程度的差异。图形化。
更新日期:2020-04-02
down
wechat
bug