Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
24 06 2020
Historique:
received: 10 09 2019
accepted: 02 06 2020
entrez: 26 6 2020
pubmed: 26 6 2020
medline: 28 8 2020
Statut: epublish

Résumé

Mass spectrometry based metabolomics is a widely used approach in biomedical research. However, current methods coupling mass spectrometry with chromatography are time-consuming and not suitable for high-throughput analysis of thousands of samples. An alternative approach is flow-injection mass spectrometry (FI-MS) in which samples are directly injected to the ionization source. Here, we show that the sensitivity of Orbitrap FI-MS metabolomics methods is limited by ion competition effect. We describe an approach for overcoming this effect by analyzing the distribution of ion m/z values and computationally determining a series of optimal scan ranges. This enables reproducible detection of ~9,000 and ~10,000 m/z features in metabolomics and lipidomics analysis of serum samples, respectively, with a sample scan time of ~15 s and duty time of ~30 s; a ~50% increase versus current spectral-stitching FI-MS. This approach facilitates high-throughput metabolomics for a variety of applications, including biomarker discovery and functional genomics screens.

Identifiants

pubmed: 32581242
doi: 10.1038/s41467-020-17026-6
pii: 10.1038/s41467-020-17026-6
pmc: PMC7314751
doi:

Substances chimiques

Ions 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3186

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Auteurs

Boris Sarvin (B)

Faculty of Biology, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Shoval Lagziel (S)

Faculty of Computer Science, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Nikita Sarvin (N)

Faculty of Biology, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Dzmitry Mukha (D)

Faculty of Biology, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Praveen Kumar (P)

Faculty of Biology, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Elina Aizenshtein (E)

Lokey Center for Life Science and Engineering, Technion-Israel Institute of Technology, 32000, Haifa, Israel.

Tomer Shlomi (T)

Faculty of Biology, Technion-Israel Institute of Technology, 32000, Haifa, Israel. tomersh@cs.technion.ac.il.
Faculty of Computer Science, Technion-Israel Institute of Technology, 32000, Haifa, Israel. tomersh@cs.technion.ac.il.
Lokey Center for Life Science and Engineering, Technion-Israel Institute of Technology, 32000, Haifa, Israel. tomersh@cs.technion.ac.il.

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