Univ Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail)-UMR_S 1085, F-35000 Rennes, France.
Anal Chem. 2021 Jan 26;93(3):1792-1800. doi: 10.1021/acs.analchem.0c04660. Epub 2020 Dec 22.
The technological advances of cutting-edge high-resolution mass spectrometry (HRMS) have set the stage for a new paradigm for exposure assessment. However, some adjustments of the metabolomics workflow are needed before HRMS-based methods can detect the low-abundant exogenous chemicals in human matrixes. It is also essential to provide tools to speed up marker identifications. Here, we first show that metabolomics software packages developed for automated optimization of XCMS parameters can lead to a false negative rate of up to 80% for chemicals spiked at low levels in blood. We then demonstrate that manual selection criteria in open-source (XCMS, MZmine2) and vendor software (MarkerView, Progenesis QI) allow to decrease the rate of false negative up to 4% (MZmine2). We next report an MS1 automatized suspect screening workflow that allows for a rapid preannotation of HRMS data sets. The novelty of this suspect screening workflow is to combine several predictors based on /, retention time () prediction models, and isotope ratio to generate intermediate and global scorings. Several prediction models were tested and hierarchized (PredRet, Retip, retention time indices, and a log model), and a nonlinear scoring was developed to account for variations observed within individual runs. We then tested the efficiency of this suspect screening tool to detect spiked and nonspiked chemicals in human blood. Compared to other existing annotation tools, its main advantages include the use of predictors using different models, its speed, and the use of efficient scoring algorithms to prioritize preannotated markers and reduce false positives.
前沿高分辨率质谱 (HRMS) 的技术进步为暴露评估开辟了一个新的范例。然而，在基于 HRMS 的方法能够检测出人基质中低丰度外源性化学物质之前，需要对代谢组学工作流程进行一些调整。提供加速标志物鉴定的工具也是必不可少的。在这里，我们首先表明，为自动优化 XCMS 参数而开发的代谢组学软件包可能导致在血液中低水平添加的化学物质的假阴性率高达 80%。然后，我们证明开源 (XCMS、MZmine2) 和供应商软件 (MarkerView、Progenesis QI) 中的手动选择标准可以将假阴性率降低至 4%（MZmine2）。接下来，我们报告了一种 MS1 自动化可疑筛选工作流程，该工作流程可快速对 HRMS 数据集进行预注释。该可疑筛选工作流程的新颖之处在于结合了几种基于预测器的方法，包括预测器、保留时间 () 预测模型和同位素比，以生成中间和全局评分。我们测试了几种预测模型并对其进行了分类（PredRet、Retip、保留时间指数和对数模型），并开发了非线性评分以解释个体运行中观察到的差异。然后，我们测试了这种可疑筛选工具检测人血液中添加和未添加化学物质的效率。与其他现有的注释工具相比，它的主要优点包括使用不同模型的预测器、速度以及使用高效的评分算法来优先考虑预注释的标记物并减少假阳性。
