Liquid chromatography-high-resolution mass spectrometry-based integrated strategy combining in silico prediction and molecular networking for metabolite identification of podophyllotoxin in a fatal poisoning case.

Podophyllotoxin is an aryltetralin lignan with potent antimitotic and antiviral activities; however, its severe toxicity restricts clinical use to topical application, and systemic exposure to it can result in life-threatening poisoning. However, its metabolic profile remains largely uncharacterized, leaving a critical gap in the biomarkers available for confirming intoxication. Here, we used an integrated nontargeted screening strategy to investigate podophyllotoxin metabolism in post-mortem blood from a rare fatal case of podophyllotoxin poisoning. Two complementary nontargeted screening strategies were established using liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes. SyGMa was first used to generate a predicted metabolite list of podophyllotoxin, enabling target analysis against the acquired data. Subsequently, molecular networking was applied to cluster structurally related compounds across specimens based on high-resolution tandem mass spectrometry spectral similarity, enabling visualization and discovery of unknown metabolites and their structural relationships. By integrating these approaches, a total of 11 potential metabolites were identified, including 2 phase Ⅰ metabolites and 9 phase Ⅱ metabolites, of which 5 were previously unreported. Among these, the O-demethylenated and methylated products (m/z 416.1471) are proposed as potential biomarkers for assessing podophyllotoxin exposure. The integrated workflow demonstrated herein facilitates xenobiotic metabolite identification in biological samples, and the characterized metabolites may support future metabolite annotation and exposure assessment through incorporation into mass spectral libraries. SIGNIFICANCE STATEMENT: Human metabolic data for podophyllotoxin remain scarce despite the severe toxicity associated with systemic exposure. By analyzing post-mortem blood from a fatal poisoning case, this study expands knowledge of podophyllotoxin biotransformation and proposes previously unreported metabolites. The results further demonstrate the complementary value of combining in silico prediction with molecular networking for metabolite discovery and annotation, highlighting a practical strategy for characterizing xenobiotic metabolites in limited biological specimens.