ABSTRACT
Multiple reaction monitoring (MRM) is a powerful and popular technique used for metabolite quantification in targeted metabolomics. Accurate and consistent quantitation of metabolites from the MRM data is essential for subsequent analyses. Here, we developed an automated tool, MRMQuant, for targeted metabolomic quantitation using high-throughput liquid chromatography-tandem mass spectrometry MRM data to provide users with an easy-to-use tool for accurate MRM data quantitation with minimal human intervention. This tool has many user-friendly functions and features to inspect and correct the quantitation results as required. MRMQuant possesses the following features to ensure accurate quantitation: (1) dynamic signal smoothing, (2) automatic deconvolution of coeluted peaks, (3) absolute quantitation via standard curves and/or internal standards, (4) visualized inspection and correction, (5) corrections applicable to multiple samples, and (6) batch-effect correction.
Subject(s)
Metabolomics , Tandem Mass Spectrometry , Metabolomics/methods , Tandem Mass Spectrometry/methods , Humans , Automation , Chromatography, Liquid/methods , SoftwareABSTRACT
Plasma lipid levels are commonly measured using traditional methods such as triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and cholesterol (CH). However, the use of newer technologies, such as nuclear magnetic resonance (NMR) with post-analysis platforms, has made it easier to assess lipoprotein profiles in research. In this study involving ApoE-deficient mice that were fed high-fat diets, significant changes were observed in TG, CH, free cholesterol (FC), and phospholipid (PL) levels within the LDL fraction. The varied proportions of TG in wild-type mice and CH, FC, and PL in ApoE-/- mice were strikingly different in very low-density lipoproteins (VLDL), LDL, intermediate-density lipoprotein (IDL), and HDL. This comprehensive analysis expands our understanding of lipoprotein subfractions and the impacts of the APOE protein and high-fat diet in mouse models. The new testing method allows for a complete assessment of plasma lipids and their correlation with genetic background and diet in mice.