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气相色谱-质谱联用靶向代谢组学方法中在线衍生化的优化工作流程

Optimized Workflow for On-Line Derivatization for Targeted Metabolomics Approach by Gas Chromatography-Mass Spectrometry.

作者信息

Fritsche-Guenther Raphaela, Gloaguen Yoann, Bauer Anna, Opialla Tobias, Kempa Stefan, Fleming Christina A, Redmond Henry Paul, Kirwan Jennifer A

机构信息

Berlin Institute of Health (BIH) @ Charité-Universitätsmedizin Berlin, BIH Metabolomics Platform, 13125 Berlin, Germany.

Core Unit Bioinformatics, Berlin Institute of Health (BIH) @ Charité- Universitätsmedizin Berlin, 10117 Berlin, Germany.

出版信息

Metabolites. 2021 Dec 18;11(12):888. doi: 10.3390/metabo11120888.

DOI:10.3390/metabo11120888
PMID:34940646
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8703763/
Abstract

Using manual derivatization in gas chromatography-mass spectrometry samples have varying equilibration times before analysis which increases technical variability and limits the number of potential samples analyzed. By contrast, automated derivatization methods can derivatize and inject each sample in an identical manner. We present a fully automated (on-line) derivatization method used for targeted analysis of different matrices. We describe method optimization and compare results from using off-line and on-line derivatization protocols, including the robustness and reproducibility of the methods. Our final parameters for the derivatization process were 20 µL of methoxyamine (MeOx) in pyridine for 60 min at 30 °C followed by 80 µL -Methyl--trimethylsilyltrifluoracetamide (MSTFA) for 30 min at 30 °C combined with 4 h of equilibration time. The repeatability test in plasma and liver revealed a median relative standard deviation (RSD) of 16% and 10%, respectively. Serum samples showed a consistent intra-batch median RSD of 20% with an inter-batch variability of 27% across three batches. The direct comparison of on-line versus off-line demonstrated that on-line was fit for purpose and improves repeatability with a measured median RSD of 11% compared to 17% using the same method off-line. In summary, we recommend that optimized on-line methods may improve results for metabolomics and should be used where available.

摘要

在气相色谱 - 质谱分析中使用手动衍生化时,样品在分析前具有不同的平衡时间,这增加了技术变异性并限制了可分析的潜在样品数量。相比之下,自动衍生化方法可以以相同的方式对每个样品进行衍生化和进样。我们提出了一种用于不同基质靶向分析的全自动(在线)衍生化方法。我们描述了方法优化,并比较了离线和在线衍生化方案的结果,包括方法的稳健性和重现性。我们衍生化过程的最终参数为:在30℃下,20μL吡啶中的甲氧基胺(MeOx)反应60分钟,然后在30℃下加入80μL - 甲基 - 三甲基硅基三氟乙酰胺(MSTFA)反应30分钟,并结合4小时的平衡时间。血浆和肝脏中的重复性测试显示,相对标准偏差(RSD)中位数分别为16%和10%。血清样品在三批样品中的批内中位数RSD为20%,批间变异性为27%。在线与离线的直接比较表明,在线方法符合要求,并且提高了重现性,测得的中位数RSD为11%,而使用相同方法离线时为17%。总之,我们建议优化的在线方法可能会改善代谢组学的结果,并且在可行的情况下应予以使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/6f358e38384c/metabolites-11-00888-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/036945e5799e/metabolites-11-00888-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/2c4b023fd935/metabolites-11-00888-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/5c31cbd8429f/metabolites-11-00888-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/6f358e38384c/metabolites-11-00888-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/036945e5799e/metabolites-11-00888-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/2c4b023fd935/metabolites-11-00888-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/5c31cbd8429f/metabolites-11-00888-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c575/8703763/6f358e38384c/metabolites-11-00888-g004.jpg

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