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.
Acetaminophen
Animals
Brain
/ metabolism
Chemical and Drug Induced Liver Injury
Discriminant Analysis
High-Throughput Screening Assays
Humans
Liver
/ metabolism
Liver Diseases
/ diagnosis
Male
Meningioma
/ diagnosis
Mice
Mice, Inbred ICR
Principal Component Analysis
Software
Spectrometry, Mass, Electrospray Ionization
Tandem Mass Spectrometry
Journal
Analytical chemistry
ISSN: 1520-6882
Titre abrégé: Anal Chem
Pays: United States
ID NLM: 0370536
Informations de publication
Date de publication:
16 06 2020
16 06 2020
Historique:
pubmed:
8
5
2020
medline:
16
2
2021
entrez:
8
5
2020
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 32375466
doi: 10.1021/acs.analchem.0c01271
doi:
Substances chimiques
Acetaminophen
362O9ITL9D
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM