Untargeted metabolomics analysis captures chemical reactions among small molecules. Common mass spectrometry-based metabolomics workflows first identify the small molecules significantly associated with the outcome of interest, then begin exploring their biochemical relationships to understand biological fate or impact. We suggest an alternative by which general chemical relationships including abiotic reactions can be directly retrieved through untargeted high-resolution paired mass distance (PMD) analysis without a priori knowledge of the identities of participating compounds. PMDs calculated from the mass spectrometry data are linked to chemical reactions obtained via data mining of small molecule and reaction databases, i.e. ‘PMD-based reactomics’. We demonstrate applications of PMD-based reactomics including PMD network analysis, source appointment of unknown compounds, and biomarker reaction discovery as complements to compound discovery analyses used in traditional untargeted workflows. An R implementation of reactomics analysis and the reaction/PMD databases is available as the pmd package.

非靶向代谢组学分析捕获小分子之间的化学反应。常见的基于质谱的代谢组学工作流程首先识别与目标结果显着相关的小分子，然后开始探索它们的生化关系以了解生物命运或影响。我们提出了一种替代方法，通过这种方法可以通过非目标高分辨率配对质量距离 (PMD) 分析直接检索包括非生物反应在内的一般化学关系，而无需事先了解参与化合物的身份。从质谱数据计算的 PMD 与通过小分子和反应数据库的数据挖掘获得的化学反应相关联，即“基于 PMD 的反应组学”。我们展示了基于 PMD 的反应组学的应用，包括 PMD 网络分析，未知化合物的来源指定和生物标志物反应发现作为对传统非靶向工作流程中使用的化合物发现分析的补充。反应组学分析和反应/PMD 数据库的 R 实现可作为 pmd 包使用。