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用于气相色谱/质谱半定量代谢组学的校准曲线锁定数据库

Calibration-Curve-Locking Database for Semi-Quantitative Metabolomics by Gas Chromatography/Mass Spectrometry.

作者信息

Hata Kosuke, Soma Yuki, Yamashita Toshiyuki, Takahashi Masatomo, Sugitate Kuniyo, Serino Takeshi, Miyagawa Hiromi, Suzuki Kenichi, Yamada Kayoko, Kawamukai Takatomo, Shiota Teruhisa, Izumi Yoshihiro, Bamba Takeshi

机构信息

Division of Metabolomics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.

Agilent Technologies Japan Ltd., 9-1 Takakuramachi, Hachioji-shi, Tokyo 192-8510, Japan.

出版信息

Metabolites. 2021 Mar 30;11(4):207. doi: 10.3390/metabo11040207.

DOI:10.3390/metabo11040207
PMID:33808182
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8065573/
Abstract

Calibration-Curve-Locking Databases (CCLDs) have been constructed for automatic compound search and semi-quantitative screening by gas chromatography/mass spectrometry (GC/MS) in several fields. CCLD felicitates the semi-quantification of target compounds without calibration curve preparation because it contains the retention time (RT), calibration curves, and electron ionization (EI) mass spectra, which are obtained under stable apparatus conditions. Despite its usefulness, there is no CCLD for metabolomics. Herein, we developed a novel CCLD and semi-quantification framework for GC/MS-based metabolomics. All analytes were subjected to GC/MS after derivatization under stable apparatus conditions using (1) target tuning, (2) RT locking technique, and (3) automatic derivatization and injection by a robotic platform. The RTs and EI mass spectra were obtained from an existing authorized database. A quantifier ion and one or two qualifier ions were selected for each target metabolite. The calibration curves were obtained as plots of the peak area ratio of the target compounds to an internal standard versus the target compound concentration. These data were registered in a database as a novel CCLD. We examined the applicability of CCLD for analyzing human plasma, resulting in time-saving and labor-saving semi-qualitative screening without the need for standard substances.

摘要

校准曲线锁定数据库(CCLDs)已被构建用于多个领域中通过气相色谱/质谱联用(GC/MS)进行自动化合物搜索和半定量筛选。CCLD有助于在无需制备校准曲线的情况下对目标化合物进行半定量分析,因为它包含在稳定仪器条件下获得的保留时间(RT)、校准曲线和电子电离(EI)质谱。尽管其有用性,但代谢组学领域尚无CCLD。在此,我们开发了一种基于GC/MS的代谢组学新型CCLD和半定量框架。所有分析物在稳定仪器条件下经衍生化后进行GC/MS分析,采用(1)目标调谐、(2)保留时间锁定技术和(3)通过机器人平台进行自动衍生化和进样。保留时间和EI质谱取自现有的授权数据库。为每个目标代谢物选择一个定量离子和一或两个定性离子。校准曲线通过目标化合物与内标物的峰面积比相对于目标化合物浓度作图获得。这些数据作为新型CCLD登记在数据库中。我们检验了CCLD在分析人血浆方面的适用性,结果表明无需标准物质即可实现省时省力的半定性筛选。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/0d7a8e3160f5/metabolites-11-00207-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/1f192087e498/metabolites-11-00207-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/6c1d2c98b980/metabolites-11-00207-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/0d7a8e3160f5/metabolites-11-00207-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/1f192087e498/metabolites-11-00207-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/6c1d2c98b980/metabolites-11-00207-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5c69/8065573/0d7a8e3160f5/metabolites-11-00207-g003.jpg

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