Molecular Biogeochemistry, Department of Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745 Jena, Germany.
Chair for Bioinformatics, Faculty of Mathematics and Computer Science, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.
Environ Sci Technol. 2022 Aug 2;56(15):11027-11040. doi: 10.1021/acs.est.2c01332. Epub 2022 Jul 14.
Ultrahigh-resolution Fourier transform mass spectrometry (FTMS) has revealed unprecedented details of natural complex mixtures such as dissolved organic matter (DOM) on a molecular formula level, but we lack approaches to access the underlying structural complexity. We here explore the hypothesis that every DOM precursor ion is potentially linked with all emerging product ions in FTMS experiments. The resulting mass difference (Δ) matrix is deconvoluted to isolate individual precursor ion Δ profiles and matched with structural information, which was derived from 42 Δ features from 14 in-house reference compounds and a global set of 11 477 Δ features with assigned structure specificities, using a dataset of ∼18 000 unique structures. We show that Δ matching is highly sensitive in predicting potential precursor ion identities in terms of molecular and structural composition. Additionally, the approach identified unresolved precursor ions and missing elements in molecular formula annotation (P, Cl, F). Our study provides first results on how Δ matching refines structural annotations in van Krevelen space but simultaneously demonstrates the wide overlap between potential structural classes. We show that this effect is likely driven by chemodiversity and offers an explanation for the observed ubiquitous presence of molecules in the center of the van Krevelen space. Our promising first results suggest that Δ matching can both unfold the structural information encrypted in DOM and assess the quality of FTMS-derived molecular formulas of complex mixtures in general.
超高分辨率傅里叶变换质谱(FTMS)在分子水平上揭示了天然复杂混合物(如溶解有机物(DOM))前所未有的细节,但我们缺乏揭示潜在结构复杂性的方法。我们在这里探索了这样一个假设,即每个 DOM 前体离子都可能与 FTMS 实验中出现的所有产物离子相关联。由此产生的质量差(Δ)矩阵被反卷积以分离出各个前体离子Δ谱,并与结构信息进行匹配,这些结构信息来自 14 种内部参考化合物中的 42 个Δ特征以及一个具有指定结构特异性的全球数据集的 11477 个Δ特征,该数据集使用了约 18000 个独特结构。我们表明,在预测分子和结构组成方面,Δ 匹配在潜在前体离子身份方面具有高度敏感性。此外,该方法还确定了分子公式注释中未解析的前体离子和缺失元素(P、Cl、F)。我们的研究首次提供了关于 Δ 匹配如何在范·克里夫伦空间中细化结构注释的结果,但同时也证明了潜在结构类之间的广泛重叠。我们表明,这种效应可能是由化学多样性驱动的,并为观察到的范·克里夫伦空间中心普遍存在的分子提供了一种解释。我们有希望的初步结果表明,Δ 匹配既可以展开 DOM 中加密的结构信息,又可以评估一般复杂混合物的 FTMS 衍生分子公式的质量。