Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA.
Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
Nat Methods. 2021 Jul;18(7):779-787. doi: 10.1038/s41592-021-01195-3. Epub 2021 Jul 8.
Chimeric MS/MS spectra contain fragments from multiple precursor ions and therefore hinder compound identification in metabolomics. Historically, deconvolution of these chimeric spectra has been challenging and relied on specific experimental methods that introduce variation in the ratios of precursor ions between multiple tandem mass spectrometry (MS/MS) scans. DecoID provides a complementary, method-independent approach where database spectra are computationally mixed to match an experimentally acquired spectrum by using LASSO regression. We validated that DecoID increases the number of identified metabolites in MS/MS datasets from both data-independent and data-dependent acquisition without increasing the false discovery rate. We applied DecoID to publicly available data from the MetaboLights repository and to data from human plasma, where DecoID increased the number of identified metabolites from data-dependent acquisition data by over 30% compared to direct spectral matching. DecoID is compatible with any user-defined MS/MS database and provides automated searching for some of the largest MS/MS databases currently available.
嵌合 MS/MS 谱包含来自多个前体离子的碎片，因此会阻碍代谢组学中化合物的鉴定。从历史上看，这些嵌合谱的解卷积一直具有挑战性，并且依赖于特定的实验方法，这些方法会导致多个串联质谱 (MS/MS) 扫描之间的前体离子比例发生变化。DecoID 提供了一种互补的、不依赖于方法的方法，其中数据库谱通过使用 LASSO 回归进行计算混合，以匹配实验获得的谱。我们验证了 DecoID 增加了来自数据非依赖性和数据依赖性采集的 MS/MS 数据集的鉴定代谢物的数量，而不会增加假阳性率。我们将 DecoID 应用于来自 MetaboLights 存储库的公开可用数据和来自人类血浆的数据，与直接光谱匹配相比，DecoID 使数据依赖性采集数据中鉴定的代谢物数量增加了 30%以上。DecoID 与任何用户定义的 MS/MS 数据库兼容，并为一些当前可用的最大 MS/MS 数据库提供自动化搜索。
