AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry

Journal Article · Sat Jun 19 00:00:00 EDT 2021 · Bioinformatics

DOI:https://doi.org/10.1093/bioinformatics/btab429· OSTI ID:1888830

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. ; Valencia, ed., Alfonso

Abstract 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).

• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); USDOE Advanced Research Projects Agency - Energy (ARPA-E)
• Grant/Contract Number: AC05-76RL01830; U2CES030170; 14/CJ000/09/02
• OSTI ID: 1888830
• Alternate ID(s): OSTI ID: 1804827
• Journal Information: Bioinformatics, Journal Name: Bioinformatics Vol. 37 Journal Issue: 22; ISSN 1367-4803
• Publisher: Oxford University Press
• Country of Publication: United Kingdom
• Language: English