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Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3...

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Autores principales: van der Laan, Tom, Boom, Isabelle, Maliepaard, Joshua, Dubbelman, Anne-Charlotte, Harms, Amy C., Hankemeier, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766927/
https://www.ncbi.nlm.nih.gov/pubmed/33353236
http://dx.doi.org/10.3390/metabo10120514
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author van der Laan, Tom
Boom, Isabelle
Maliepaard, Joshua
Dubbelman, Anne-Charlotte
Harms, Amy C.
Hankemeier, Thomas
author_facet van der Laan, Tom
Boom, Isabelle
Maliepaard, Joshua
Dubbelman, Anne-Charlotte
Harms, Amy C.
Hankemeier, Thomas
author_sort van der Laan, Tom
collection PubMed
description A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MS(ALL)) were used to evaluate the performance of DIA. Our results show that fast chromatography and MS(ALL) often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.
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spelling pubmed-77669272020-12-28 Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma van der Laan, Tom Boom, Isabelle Maliepaard, Joshua Dubbelman, Anne-Charlotte Harms, Amy C. Hankemeier, Thomas Metabolites Article A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MS(ALL)) were used to evaluate the performance of DIA. Our results show that fast chromatography and MS(ALL) often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis. MDPI 2020-12-18 /pmc/articles/PMC7766927/ /pubmed/33353236 http://dx.doi.org/10.3390/metabo10120514 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
van der Laan, Tom
Boom, Isabelle
Maliepaard, Joshua
Dubbelman, Anne-Charlotte
Harms, Amy C.
Hankemeier, Thomas
Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title_full Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title_fullStr Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title_full_unstemmed Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title_short Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma
title_sort data-independent acquisition for the quantification and identification of metabolites in plasma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766927/
https://www.ncbi.nlm.nih.gov/pubmed/33353236
http://dx.doi.org/10.3390/metabo10120514
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