化学计量学
化学
脂类学
代谢组学
主成分分析
脂质体
计算生物学
真菌毒素
偏最小二乘回归
色谱法
质谱法
生物标志物发现
飞镖离子源
代谢组
环境化学
食品科学
生物化学
蛋白质组学
基因
生物
人工智能
统计
离子
计算机科学
有机化学
数学
电离
电子电离
作者
Lan Chen,Fengming Chen,Tong Liu,Feng Feng,Wei Guo,Yuan Zhang,Xiaojun Feng,Jin‐Ming Lin,Feng Zhang
标识
DOI:10.1021/acs.analchem.1c05543
摘要
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.
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