Recent advances in data-mining techniques for measuring transformation products by high-resolution mass spectrometry

Abstract Investigation on transformation products (TPs) of environmental contaminants is important for chemical exposure risk assessments. However, the task of identifying potential TPs in complex environmental matrices is very challenging. Advanced data-mining techniques have greatly accelerated the process of TP recognition and identification, which should be included as part of an integrated analytical workflow along with robust sample preparation and data acquisition protocols. In this review, the methods for enrichment of TPs from various sample matrix and the data acquisition modes by high-resolution mass spectrometry (HRMS) are summarized. Further, advanced data-mining techniques including suspect screening by in-silico prediction, case-control strategy, stable isotope labeling, mass defect filtering, and product ion filtering are critically reviewed. The gaps in the current knowledge and future trends for the identification of TPs are also discussed.