Efficient Transformation Product Identification and Structural Elucidation Using an Integrated Bottom-Up HRMS Workflow with Pyhrms and Transformapy

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.