Abstract
Food authenticity is extremely important and widely targeted bi-omics is a promising pipeline attributing to incorporating metabolomics and peptidomics. Colla Corii Asini (CCA, Ejiao) is one of the most popular tonic edible materials, with counterfeit and adulterated products being widespread. An attempt was devoted to develop a high-throughput and reliable DI–MRM3 program facilitating widely targeted bi-omics of CCA. Firstly, predictive MRM program captured metabolites and peptides in trypsin-digestive gelatins. After data alignment and structure annotation, primary parameters such as Q1 → Q3 → QLIT, CE, and EE were optimized for all 17 metabolites and 34 peptides by online ER-MS. Though a single run merely consumed 6.5 min, great selectivity was reached for each analyte. Statistical results showed that nine peptides contributed to distinguish CCA from other gelatins. After cross-validation with LC–MRM, DI–MRM3 was justified to be reproducible and high-throughput for widely targeted bi-omics of CCA, suggesting a meaningful tool for food authenticity.
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