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AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry
MOTIVATION: Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion’s collision cross section (CCS), which reflects its s...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502155/ https://www.ncbi.nlm.nih.gov/pubmed/34145874 http://dx.doi.org/10.1093/bioinformatics/btab429 |
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author | Lee, Joon-Yong Bilbao, Aivett Conant, Christopher R Bloodsworth, Kent J Orton, Daniel J Zhou, Mowei Wilson, Jesse W Zheng, Xueyun Webb, Ian K Li, Ailin Hixson, Kim K Fjeldsted, John C Ibrahim, Yehia M Payne, Samuel H Jansson, Christer Smith, Richard D Metz, Thomas O |
author_facet | Lee, Joon-Yong Bilbao, Aivett Conant, Christopher R Bloodsworth, Kent J Orton, Daniel J Zhou, Mowei Wilson, Jesse W Zheng, Xueyun Webb, Ian K Li, Ailin Hixson, Kim K Fjeldsted, John C Ibrahim, Yehia M Payne, Samuel H Jansson, Christer Smith, Richard D Metz, Thomas O |
author_sort | Lee, Joon-Yong |
collection | PubMed |
description | MOTIVATION: Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion’s collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required. RESULTS: We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing. AVAILABILITY AND IMPLEMENTATION: https://github.com/PNNL-Comp-Mass-Spec/AutoCCS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979). |
format | Online Article Text |
id | pubmed-9502155 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-95021552022-09-26 AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry Lee, Joon-Yong Bilbao, Aivett Conant, Christopher R Bloodsworth, Kent J Orton, Daniel J Zhou, Mowei Wilson, Jesse W Zheng, Xueyun Webb, Ian K Li, Ailin Hixson, Kim K Fjeldsted, John C Ibrahim, Yehia M Payne, Samuel H Jansson, Christer Smith, Richard D Metz, Thomas O Bioinformatics Original Papers MOTIVATION: Ion mobility spectrometry (IMS) separations are increasingly used in conjunction with mass spectrometry (MS) for separation and characterization of ionized molecular species. Information obtained from IMS measurements includes the ion’s collision cross section (CCS), which reflects its size and structure and constitutes a descriptor for distinguishing similar species in mixtures that cannot be separated using conventional approaches. Incorporating CCS into MS-based workflows can improve the specificity and confidence of molecular identification. At present, there is no automated, open-source pipeline for determining CCS of analyte ions in both targeted and untargeted fashion, and intensive user-assisted processing with vendor software and manual evaluation is often required. RESULTS: We present AutoCCS, an open-source software to rapidly determine CCS values from IMS-MS measurements. We conducted various IMS experiments in different formats to demonstrate the flexibility of AutoCCS for automated CCS calculation: (i) stepped-field methods for drift tube-based IMS (DTIMS), (ii) single-field methods for DTIMS (supporting two calibration methods: a standard and a new enhanced method) and (iii) linear calibration for Bruker timsTOF and non-linear calibration methods for traveling wave based-IMS in Waters Synapt and Structures for Lossless Ion Manipulations. We demonstrated that AutoCCS offers an accurate and reproducible determination of CCS for both standard and unknown analyte ions in various IMS-MS platforms, IMS-field methods, ionization modes and collision gases, without requiring manual processing. AVAILABILITY AND IMPLEMENTATION: https://github.com/PNNL-Comp-Mass-Spec/AutoCCS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Demo datasets are publicly available at MassIVE (Dataset ID: MSV000085979). Oxford University Press 2021-06-19 /pmc/articles/PMC9502155/ /pubmed/34145874 http://dx.doi.org/10.1093/bioinformatics/btab429 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Lee, Joon-Yong Bilbao, Aivett Conant, Christopher R Bloodsworth, Kent J Orton, Daniel J Zhou, Mowei Wilson, Jesse W Zheng, Xueyun Webb, Ian K Li, Ailin Hixson, Kim K Fjeldsted, John C Ibrahim, Yehia M Payne, Samuel H Jansson, Christer Smith, Richard D Metz, Thomas O AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title_full | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title_fullStr | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title_full_unstemmed | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title_short | AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
title_sort | autoccs: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9502155/ https://www.ncbi.nlm.nih.gov/pubmed/34145874 http://dx.doi.org/10.1093/bioinformatics/btab429 |
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