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

Analytical chemistry
ISSN: 1520-6882
Titre abrégé: Anal Chem
Pays: United States
ID NLM: 0370536

Informations de publication

Date de publication:
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

Pagination

8514-8522

Auteurs

Kei Zaitsu (K)

In Vivo Real-Time Omics Laboratory, Institute for Advanced Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan.
Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

Seiichiro Eguchi (S)

Department of Neurosurgery, Neurological Institute, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo 162-8666, Japan.

Tomomi Ohara (T)

Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

Kenta Kondo (K)

Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

Akira Ishii (A)

Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

Hitoshi Tsuchihashi (H)

Department of Legal Medicine & Bioethics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8550, Japan.

Takakazu Kawamata (T)

Department of Neurosurgery, Neurological Institute, Tokyo Women's Medical University, 8-1 Kawada-cho, Shinjuku-ku, Tokyo 162-8666, Japan.

Akira Iguchi (A)

Marine Geo-Environment Research Group, Institute of Geology and Geoinformation, National Institute of Advanced Industrial Science and Technology (AIST), AIST Tsukuba Central 7, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8567, Japan.

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Classifications MeSH