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基于微波辅助萃取/超高效液相色谱-四极杆-轨道阱质谱联用技术的脂质组学工作流程用于软质奶酪脂质的综合研究

Microwave-Assisted Extraction/UHPLC-Q-Orbitrap-MS-Based Lipidomic Workflow for Comprehensive Study of Lipids in Soft Cheese.

作者信息

Campaniello Maria, Nardelli Valeria, Zianni Rosalia, Tomaiuolo Michele, Miedico Oto, Iammarino Marco, Mentana Annalisa

机构信息

Istituto Zooprofilattico Sperimentale della Puglia e della Basilicata, Via Manfredonia, 20-71121 Foggia, Italy.

出版信息

Foods. 2024 Mar 28;13(7):1033. doi: 10.3390/foods13071033.

DOI:10.3390/foods13071033
PMID:38611340
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11012187/
Abstract

In this work, Microwave-Assisted Extraction (MAE) was proposed as an alternative and environmentally friendly technique in lipidomics to study the lipid fingerprint of soft cheeses, such as mozzarella. For method development, a first step concerning an evaluation of extraction solvents was carried out via testing three different mixtures, including methanol/ethyl acetate, isopropanol/ethyl acetate, and ethanol/ethyl acetate, at a 1:2 / ratio. The latter was chosen as a solvent mixture for subsequent method optimization. MAE conditions, in terms of solvent volume, time, and temperature, were explored to define their effects on extraction capability through a full factorial experimental design. The best compromise to extract more lipids at the same time was obtained with 24 mL g for solvent-to-solid ratio, 65 °C for temperature, and 18 min for time. Lipid analyses were conducted by UHPLC-Q-Orbitrap-MS associated with multivariate statistics. The developed lipidomic workflow allowed for the extraction of over 400 lipids grouped into 18 different subclasses. The results confirmed that MAE is a suitable technique for lipid extraction in the omics approach with high efficiency, even using low-cost and less toxic solvents. Moreover, a comprehensive structure characterization of extracted lipids, in terms of fatty acid composition and regiochemistry, was carried out.

摘要

在本研究中,提出将微波辅助萃取(MAE)作为脂质组学中一种替代的、环境友好的技术,用于研究软质奶酪(如马苏里拉奶酪)的脂质指纹图谱。为了开展方法开发,第一步是通过测试三种不同的混合物(甲醇/乙酸乙酯、异丙醇/乙酸乙酯和乙醇/乙酸乙酯,比例为1:2)来评估萃取溶剂。选择后者作为溶剂混合物用于后续的方法优化。通过全因子实验设计探索了MAE在溶剂体积、时间和温度方面的条件,以确定它们对萃取能力的影响。在溶剂与固体比例为24 mL/g、温度为65℃、时间为18分钟的条件下,获得了在同一时间内萃取更多脂质的最佳折中方案。脂质分析通过超高效液相色谱-四极杆-轨道阱质谱联用多元统计方法进行。所开发的脂质组学工作流程能够萃取400多种脂质,这些脂质被分为18个不同的亚类。结果证实,MAE是一种适用于组学方法中脂质萃取的高效技术,即使使用低成本、低毒性的溶剂也是如此。此外,还对萃取脂质的脂肪酸组成和区域化学等方面进行了全面的结构表征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/3ddd2991b838/foods-13-01033-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/a145d0d0a4c5/foods-13-01033-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/997fa30169f9/foods-13-01033-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/5d0f5890fd43/foods-13-01033-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/3ddd2991b838/foods-13-01033-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/a145d0d0a4c5/foods-13-01033-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/997fa30169f9/foods-13-01033-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/5d0f5890fd43/foods-13-01033-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aa05/11012187/3ddd2991b838/foods-13-01033-g004.jpg

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