PiTMaP: A New Analytical Platform for High-Throughput Direct Metabolome Analysis by Probe Electrospray Ionization/Tandem Mass Spectrometry Using an R Software-Based Data Pipeline

Abstract

A new analytical platform called PiTMaP was developed for high-throughput direct metabolome analysis by probe electrospray ionization/tandem mass spectrometry (PESI/MS/MS) using an R software-based data pipeline. PESI/MS/MS was used as the data acquisition technique, applying a scheduled-selected reaction monitoring method to expand the targeted metabolites. Seventy-two metabolites mainly related to the central energy metabolism were selected; data acquisition time was optimized using mouse liver and brain samples, indicating that the 2.4 min data acquisition method had a higher repeatability than the 1.2 min and 4.8 min methods. A data pipeline was constructed using the R software, and it was proven that it can i) automatically generate box-and-whisker plots for all metabolites, ii) perform multivariate analyses such as principal component analysis (PCA) and projections to latent structures-discriminant analysis (PLS-DA), iii) generate score and loading plots of PCA and PLS-DA, iv) calculate variable importance of projection (VIP) values, v) determine a statistical family by VIP value criterion, vi) perform tests of significance with the false discovery rate (FDR) correction method, and vii) draw box-and-whisker plots only for significantly changed metabolites. These tasks could be completed within ca. 1 min. Finally, PiTMaP was applied to two cases: 1) an acetaminophen (APAP)-induced acute liver injury model and control mice and 2) human meningioma samples with different grades (G1–G3), demonstrating the feasibility of PiTMaP. PiTMaP was found to perform data acquisition without tedious sample preparation and a post-hoc data analysis within ca. 1 min. Thus, it would be a universal platform to perform rapid metabolic profiling of biological samples.