Dual-Drive Platform Combining Biotransformation Prediction and Diagnostic Ion Cluster Reveals Novel Type B Trichothecenes in Wheat

Type B trichothecenes (B-TCTs) and their metabolites pose significant risks to both human and animal health and are the most common mycotoxin found in wheat. However, the identification of unknown B-TCT metabolites remains a considerable challenge. In this study, we develop a novel dual-mode analytical platform combining a biotransformation-driven prediction database with core structural ion clusters to rapidly screen and accurately identify unknown B-TCT metabolites. The platform integrates 36 metabolic reactions to construct a database of 4321 predicted B-TCT metabolites and introduces a diagnostic ion cluster of 17 characteristic structural fragments, significantly reducing false-positive rates. This platform provides superior screening efficiency to traditional methods without compromising coverage and successfully identifies nine B-TCT metabolites in wheat samples from high-risk areas in China, including four metabolites not previously discovered in naturally contaminated wheat. This platform effectively identifies unknown B-TCT metabolites with 3-4 times less false positives and effort than traditional methods and provides a valuable methodological approach for investigating unknown metabolites of other compounds.