PDF(Pubmed)
Abstract：
Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.
摘要：
基于反相LC-MS（RPLC-MS）的非靶向代谢组学在生理和疾病状态的生物标志物发现中起着至关重要的作用。规范非目标方法的开发过程需要注意讨论中或容易忽略的关键因素，如注射参数，绩效评估，和矩阵效应评价。在这项研究中,通过优化和评估这些因素,我们开发了一种针对血浆和粪便样本的非靶向代谢组学方法.我们的结果表明，优化重建溶剂和样品注射量对于实现代谢物覆盖和信号线性之间的平衡至关重要。具有代表性的稳定同位素标记标准（SIL）的方法验证提供了对我们方法的分析性能评估的见解。为了解决矩阵效应的问题，我们采用柱后输注(PCI)方法监测总体绝对基质效应(AME)和相对基质效应(RME).监测显示血浆和粪便中不同的AME和RME谱。将通过提取后加标获得的SIL的RME数据与使用PCI化合物监测的数据进行比较，证明了这两种RME评估方法的可比性。因此,我们应用PCI方法来预测我们内部图书馆覆盖的305个目标化合物的RME，并发现在负极性检测到的目标更容易受到RME的影响。无论样本矩阵如何。鉴于这种PCI方法在确定我们方法在矩阵效应方面的优势和劣势方面的价值，我们建议在方法开发期间实施PCI方法,并将其常规应用于非靶向代谢组学.
