Lipidomics Profiling of HepG2 Cells and Interference by Mycotoxins Based on UPLC-TOF-IMS

Discovering the fungus-infected or mycotoxin-contaminated biomarkers is significant for systems biology since the metabolites in biological samples have significant polarity differences in both stochastic gene expression and microenvironmental change. Here, we aim to establish a comprehensive method for a lipidome by ion mobility mass spectrometry (IMS) merged with chemometrics to accurately find out the more scientific markers of cell interference by mycotoxins and for pathogenesis exploration and drug development. The differences in the abundances of several small molecules found in these metabolites were explored through multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), to further screen biomarkers. Good applicability and predictability were demonstrated by R²(X) and Q² (R² = 0.959, Q² = 0.999). Five compounds with m/z values of 512.502 8, 540.5343, 722.525 8, 787.667 5, and 813.683 0 were selected as markers, and four of them were further confirmed by chemical standards (i.e., MSMS of m/z 813.683 0 covering m/z 86.0978, 125.0008, 184.0745, and 185.0781). In summary, we demonstrated the integration of UPLC-TOF-IMS and the chemometrics approach to elucidate identified biomarkers, which also provides a new way of thinking for covering lipid biomarkers or prognostic indicators for mycotoxins.