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建立并应用一种 LC-MS/MS 非靶向暴露组学方法,该方法采用了独立混合的质控策略。

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy.

机构信息

Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, L-4367 Belvaux, Luxembourg.

Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy.

出版信息

Molecules. 2022 Apr 16;27(8):2580. doi: 10.3390/molecules27082580.

Abstract

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

摘要

通常在非靶向方法中实施合并质量控制(QC),以通过去除未检测到或不可重现的特征来提高数据集的质量。然而,在针对暴露和未暴露组的暴露组进行的暴露组研究中,这种方法可能会受到限制,因为仅在暴露组中存在的低水平化合物可能会被稀释,从而在合并的 QC 中无法检测到。本工作旨在开发并应用一种用于尿液样本中人体生物监测的非靶向工作流程,实施一种新的分离方法来制备合并的质量控制。开发并应用了一种 LC-MS/MS 工作流程来对吸烟和不吸烟的研究对象进行案例研究。制备了三种不同的合并质量控制:从每个样本的等分试样混合(QC-T),仅从不吸烟者(QC-NS),仅从吸烟者(QC-S)。分别使用 QC-T(T 特征列表)、QC-S 和 QC-NS 过滤特征表。最后两个特征列表合并(SNS-特征列表)。与 T-特征列表相比,SNS-特征列表获得了更多的特征,从而鉴定出更多具有生物学意义的化合物。实施的分离合并 QC 策略可以提高针对暴露和未暴露组的非靶向人体生物监测。

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