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Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions
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 spec...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314751/ https://www.ncbi.nlm.nih.gov/pubmed/32581242 http://dx.doi.org/10.1038/s41467-020-17026-6 |
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author | Sarvin, Boris Lagziel, Shoval Sarvin, Nikita Mukha, Dzmitry Kumar, Praveen Aizenshtein, Elina Shlomi, Tomer |
author_facet | Sarvin, Boris Lagziel, Shoval Sarvin, Nikita Mukha, Dzmitry Kumar, Praveen Aizenshtein, Elina Shlomi, Tomer |
author_sort | Sarvin, Boris |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7314751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73147512020-06-26 Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions Sarvin, Boris Lagziel, Shoval Sarvin, Nikita Mukha, Dzmitry Kumar, Praveen Aizenshtein, Elina Shlomi, Tomer Nat Commun Article 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. Nature Publishing Group UK 2020-06-24 /pmc/articles/PMC7314751/ /pubmed/32581242 http://dx.doi.org/10.1038/s41467-020-17026-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Sarvin, Boris Lagziel, Shoval Sarvin, Nikita Mukha, Dzmitry Kumar, Praveen Aizenshtein, Elina Shlomi, Tomer Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title | Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title_full | Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title_fullStr | Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title_full_unstemmed | Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title_short | Fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
title_sort | fast and sensitive flow-injection mass spectrometry metabolomics by analyzing sample-specific ion distributions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314751/ https://www.ncbi.nlm.nih.gov/pubmed/32581242 http://dx.doi.org/10.1038/s41467-020-17026-6 |
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