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Updated: Jan 12, 2026

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS

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Published on: May 20, 2013

在非目标的LC-MS代谢学中矩阵效应:从创建到补偿,通过对标准的后列输入进行补偿

Pingping Zhu¹, Amy C Harms¹, Pascal Maas¹

¹Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, the Netherlands.

Journal of chromatography. A

|November 8, 2025

概括

这项研究引入了一种使用人工矩阵效应 (MEart) 选择合适的列后输液标准 (PCIS) 来纠正非目标代谢学中的矩阵效应的新方法. 这种方法可以提高LC-ESI-MS分析的准确性和可重复性.

科学领域:

分析化学分析化学
代谢学代谢学代谢学
质谱测量质量谱测量

背景情况:

矩阵效应显著影响LC-ESI-MS代谢学中的准确性和可重复性.
后列注入标准 (PCIS) 是一种减轻矩阵效应的策略,但在选择适合非目标研究的标准方面面临挑战.
确定合适的PCIS对于可靠的矩阵效应补偿至关重要.

研究的目的:

提出一种新的方法来选择合适的PCIS用于使用人工矩阵效应 (MEart) 的矩阵效应补偿.
评估MEart在识别PCIS以纠正LC-PCIS-MS中的生物矩阵效应 (MEbio) 的有效性.
为了证明MEart在非目标代谢学应用中的潜力.

主要方法:

开发了一种基于MEart的方法,通过注入破坏电喷射电离 (ESI) 的化合物来产生.
在血,尿液和便中使用19个稳定同位素标记 (SIL) 标准评估了该方法.
基于MEart与MEbio的PCIS选择进行了比较,并评估了MEart选择的PCIS对MEbio校正的影响.

主要成果:

基于MEart的PCIS选择显示出高一致性 (89%) 与跨多种生物矩阵的MEbio选择.
应用MEart选择的PCIS有效地纠正了MEbio对大多数受影响的SIL标准.
该方法对没有发生矩阵效应的标准保持了MEbio,表明性能强.

结论:

MEart是一种有效的策略,用于在LC-PCIS-MS中选择合适的PCIS进行矩阵效应校正.
这种方法通过改进矩阵效应补偿来提高非向代谢物质的可靠性.
对于在非目标代谢学中检测到的任何特征,MEart方法可以广泛地用于识别PCIS.

关键词:

人工矩阵是一个人工矩阵.这就是LC-MS.矩阵效应纠正纠正矩阵效应纠正在后列输液后进行输液.没有针对性的代谢组分.

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