EGUCHI SEIICHIRO    Department   School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine    Position   Assistant Professor
Article types	Original article
Language	English
Peer review	Peer reviewed
Title	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.
Journal	Formal name：Analytical chemistry Abbreviation：Anal Chem ISSN code：15206882/00032700
Domestic / Foregin	Foregin
Volume, Issue, Page	92(12),pp.8514-8522
Author and coauthor	Zaitsu Kei†*, Eguchi Seiichiro, Ohara Tomomi, Kondo Kenta, Ishii Akira, Tsuchihashi Hitoshi, Kawamata Takakazu, Iguchi Akira
Publication date	2020/06
Summary	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 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 projection 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-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 posthoc data analysis within ca. 1 min. Thus, it would be a universal platform to perform rapid metabolic profiling of biological samples.
DOI	10.1021/acs.analchem.0c01271
PMID	32375466