Efficient Transformation Product Identification and Structural Elucidation Using an Integrated Bottom-Up HRMS...

Transformation products (TPs) have attracted increasing attention due to their widespread occurrence and potential adverse effects, and high-resolution mass spectrometry (HRMS) has been widely applied for their detection and characterization. However, the identification and structural elucidation of TPs from massive HRMS data sets remain challenging due to the limited availability of reference standards and the substantial manual effort required for data interpretation. In this study, we present a bottom-up workflow that integrates two open-source tools, Pyhrms and Transformapy, encompassing HRMS data deconvolution and prioritization, molecular formula assignment and verification, as well as parent-structure-guided structure elucidation, enabling systematic TP identification and structural characterization from HRMS data sets. This workflow was successfully applied to both controlled single-parent systems and complex environmental matrices such as wastewater treatment plants (WWTPs). Its broad applicability was further demonstrated using published data, in which 97.2% of 599 reported TPs could be annotated by assigning either tentative structures (n = 454), structure-inference steps (n = 119), or molecular formulas (n = 9). This approach provides a practical and extensible foundation for achieving more comprehensive and efficient TP elucidation, reducing manual interpretation efforts, and improving the assessment of transformation processes and environmental risks associated with emerging contaminants.