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Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools †
Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317224/ https://www.ncbi.nlm.nih.gov/pubmed/35890199 http://dx.doi.org/10.3390/ph15070901 |
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author | Shah, Syed Muhammad Zaki Ali, Arslan Khan, Muhammad Noman Khadim, Adeeba Asmari, Mufarreh Uddin, Jalal Musharraf, Syed Ghulam |
author_facet | Shah, Syed Muhammad Zaki Ali, Arslan Khan, Muhammad Noman Khadim, Adeeba Asmari, Mufarreh Uddin, Jalal Musharraf, Syed Ghulam |
author_sort | Shah, Syed Muhammad Zaki |
collection | PubMed |
description | Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids. |
format | Online Article Text |
id | pubmed-9317224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93172242022-07-27 Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † Shah, Syed Muhammad Zaki Ali, Arslan Khan, Muhammad Noman Khadim, Adeeba Asmari, Mufarreh Uddin, Jalal Musharraf, Syed Ghulam Pharmaceuticals (Basel) Article Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids. MDPI 2022-07-21 /pmc/articles/PMC9317224/ /pubmed/35890199 http://dx.doi.org/10.3390/ph15070901 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shah, Syed Muhammad Zaki Ali, Arslan Khan, Muhammad Noman Khadim, Adeeba Asmari, Mufarreh Uddin, Jalal Musharraf, Syed Ghulam Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title | Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title_full | Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title_fullStr | Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title_full_unstemmed | Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title_short | Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools † |
title_sort | sensitive detection of pharmaceutical drugs and metabolites in serum using data-independent acquisition mass spectrometry and open-access data acquisition tools † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317224/ https://www.ncbi.nlm.nih.gov/pubmed/35890199 http://dx.doi.org/10.3390/ph15070901 |
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