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A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry

RATIONALE: For the characterization of the chemical composition of complex matrices such as tobacco smoke, containing more than 6000 constituents, several analytical approaches have to be combined to increase compound coverage across the chemical space. Furthermore, the identification of unknown mol...

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Autores principales: Arndt, Daniel, Wachsmuth, Christian, Buchholz, Christoph, Bentley, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050541/
https://www.ncbi.nlm.nih.gov/pubmed/31479554
http://dx.doi.org/10.1002/rcm.8571
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author Arndt, Daniel
Wachsmuth, Christian
Buchholz, Christoph
Bentley, Mark
author_facet Arndt, Daniel
Wachsmuth, Christian
Buchholz, Christoph
Bentley, Mark
author_sort Arndt, Daniel
collection PubMed
description RATIONALE: For the characterization of the chemical composition of complex matrices such as tobacco smoke, containing more than 6000 constituents, several analytical approaches have to be combined to increase compound coverage across the chemical space. Furthermore, the identification of unknown molecules requiring the implementation of additional confirmatory tools in the absence of reference standards, such as tandem mass spectrometry spectra comparisons and in silico prediction of mass spectra, is a major bottleneck. METHODS: We applied a combination of four chromatographic/ionization techniques (reversed‐phase (RP) – heated electrospray ionization (HESI) in both positive (+) and negative (−) modes, RP – atmospheric pressure chemical ionization (APCI) in positive mode, and hydrophilic interaction liquid chromatography (HILIC) – HESI positive) using a Thermo Q Exactive™ liquid chromatography/high‐resolution accurate mass spectrometry (LC/HRAM‐MS) platform for the analysis of 3R4F‐derived smoke. Compound identification was performed by using mass spectral libraries and in silico predicted fragments from multiple integrated databases. RESULTS: A total of 331 compounds with semi‐quantitative estimates ≥100 ng per cigarette were identified, which were distributed within the known chemical space of tobacco smoke. The integration of multiple LC/HRAM‐MS‐based chromatographic/ionization approaches combined with complementary compound identification strategies was key for maximizing the number of amenable compounds and for strengthening the level of identification confidence. A total of 50 novel compounds were identified as being present in tobacco smoke. In the absence of reference MS(2) spectra, in silico MS(2) spectra prediction gave a good indication for compound class and was used as an additional confirmatory tool for our integrated non‐targeted screening (NTS) approach. CONCLUSIONS: This study presents a powerful chemical characterization approach that has been successfully applied for the identification of novel compounds in cigarette smoke. We believe that this innovative approach has general applicability and a huge potential benefit for the analysis of any complex matrices.
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spelling pubmed-70505412020-03-09 A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry Arndt, Daniel Wachsmuth, Christian Buchholz, Christoph Bentley, Mark Rapid Commun Mass Spectrom Research Articles RATIONALE: For the characterization of the chemical composition of complex matrices such as tobacco smoke, containing more than 6000 constituents, several analytical approaches have to be combined to increase compound coverage across the chemical space. Furthermore, the identification of unknown molecules requiring the implementation of additional confirmatory tools in the absence of reference standards, such as tandem mass spectrometry spectra comparisons and in silico prediction of mass spectra, is a major bottleneck. METHODS: We applied a combination of four chromatographic/ionization techniques (reversed‐phase (RP) – heated electrospray ionization (HESI) in both positive (+) and negative (−) modes, RP – atmospheric pressure chemical ionization (APCI) in positive mode, and hydrophilic interaction liquid chromatography (HILIC) – HESI positive) using a Thermo Q Exactive™ liquid chromatography/high‐resolution accurate mass spectrometry (LC/HRAM‐MS) platform for the analysis of 3R4F‐derived smoke. Compound identification was performed by using mass spectral libraries and in silico predicted fragments from multiple integrated databases. RESULTS: A total of 331 compounds with semi‐quantitative estimates ≥100 ng per cigarette were identified, which were distributed within the known chemical space of tobacco smoke. The integration of multiple LC/HRAM‐MS‐based chromatographic/ionization approaches combined with complementary compound identification strategies was key for maximizing the number of amenable compounds and for strengthening the level of identification confidence. A total of 50 novel compounds were identified as being present in tobacco smoke. In the absence of reference MS(2) spectra, in silico MS(2) spectra prediction gave a good indication for compound class and was used as an additional confirmatory tool for our integrated non‐targeted screening (NTS) approach. CONCLUSIONS: This study presents a powerful chemical characterization approach that has been successfully applied for the identification of novel compounds in cigarette smoke. We believe that this innovative approach has general applicability and a huge potential benefit for the analysis of any complex matrices. John Wiley and Sons Inc. 2020-01-10 2020-01-30 /pmc/articles/PMC7050541/ /pubmed/31479554 http://dx.doi.org/10.1002/rcm.8571 Text en © 2019 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Arndt, Daniel
Wachsmuth, Christian
Buchholz, Christoph
Bentley, Mark
A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title_full A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title_fullStr A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title_full_unstemmed A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title_short A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
title_sort complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non‐targeted liquid chromatography with high‐resolution mass spectrometry
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7050541/
https://www.ncbi.nlm.nih.gov/pubmed/31479554
http://dx.doi.org/10.1002/rcm.8571
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