Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ross, Dylan H.; Bhotika, Harsh; Zheng, Xueyun; Smith, Richard D.; Burnum‐Johnson, Kristin E.; Bilbao, Aivett

doi:10.1002/pmic.202200436

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Journal Article · Mon Mar 04 00:00:00 EST 2024 · Proteomics

DOI:https://doi.org/10.1002/pmic.202200436· OSTI ID:2407038

^[1]; Bhotika, Harsh ^[2]; ^[1]; ^[1]; ^[2]; ^[2]

Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL)

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

View Accepted Manuscript (DOE)

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Environmental Molecular Sciences Laboratory (EMSL)

Sponsoring Organization:: National Institute of General Medical Sciences; USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 2407038

Report Number(s):: PNNL-SA--192094

Journal Information:: Proteomics, Journal Name: Proteomics Journal Issue: 12-13 Vol. 24; ISSN 1615-9853

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Review of applications of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS) Kolakowski, Beata M.; Mester, Zoltán The Analyst, Vol. 132, Issue 9 https://doi.org/10.1039/b706039d	journal	January 2007
Evaluation of drift gas selection in complex sample analyses using a high performance drift tube ion mobility-QTOF mass spectrometer Kurulugama, Ruwan. T.; Darland, Ed; Kuhlmann, Frank The Analyst, Vol. 140, Issue 20 https://doi.org/10.1039/c5an00991j	journal	January 2015
Early stages of insulin fibrillogenesis examined with ion mobility mass spectrometry and molecular modelling Cole, Harriet; Porrini, Massimiliano; Morris, Ryan The Analyst, Vol. 140, Issue 20 https://doi.org/10.1039/c5an01253h	journal	January 2015
Ion mobility coupled to native mass spectrometry as a relevant tool to investigate extremely small ligand-induced conformational changes Stojko, Johann; Fieulaine, Sonia; Petiot-Bécard, Stéphanie The Analyst, Vol. 140, Issue 21 https://doi.org/10.1039/c5an01311a	journal	January 2015
EM∩IM: software for relating ion mobility mass spectrometry and electron microscopy data Degiacomi, Matteo T.; Benesch, Justin L. P. The Analyst, Vol. 141, Issue 1 https://doi.org/10.1039/c5an01636c	journal	January 2016
New frontiers for mass spectrometry based upon structures for lossless ion manipulations Ibrahim, Yehia M.; Hamid, Ahmed M.; Deng, Liulin The Analyst, Vol. 142, Issue 7 https://doi.org/10.1039/c7an00031f	journal	January 2017
A parallelized molecular collision cross section package with optimized accuracy and efficiency Ieritano, Christian; Crouse, Jeff; Campbell, J. Larry The Analyst, Vol. 144, Issue 5 https://doi.org/10.1039/c8an02150c	journal	January 2019
Collision cross section compendium to annotate and predict multi-omic compound identities Picache, Jaqueline A.; Rose, Bailey S.; Balinski, Andrzej Chemical Science, Vol. 10, Issue 4 https://doi.org/10.1039/c8sc04396e	journal	January 2019
An improved algorithm for resolving overlapping peaks in ion mobility spectrometry and its application to the separation of glycan isomers Hu, Xiangyang; Zhou, Junfei; Li, Junhui The Analyst, Vol. 148, Issue 21 https://doi.org/10.1039/d3an01042b	journal	January 2023
Collision cross section calculations for polyatomic ions considering rotating diatomic/linear gas molecules Larriba-Andaluz, Carlos; Hogan, Christopher J. The Journal of Chemical Physics, Vol. 141, Issue 19 https://doi.org/10.1063/1.4901890	journal	November 2014
Simultaneous Proteomic Discovery and Targeted Monitoring using Liquid Chromatography, Ion Mobility Spectrometry, and Mass Spectrometry Burnum-Johnson, Kristin E.; Nie, Song; Casey, Cameron P. Molecular & Cellular Proteomics, Vol. 15, Issue 12 https://doi.org/10.1074/mcp.M116.061143	journal	September 2016
MaxQuant Software for Ion Mobility Enhanced Shotgun Proteomics Prianichnikov, Nikita; Koch, Heiner; Koch, Scarlet Molecular & Cellular Proteomics, Vol. 19, Issue 6 https://doi.org/10.1074/mcp.tir119.001720	journal	June 2020
Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant Yu, Fengchao; Haynes, Sarah E.; Teo, Guo Ci Molecular & Cellular Proteomics, Vol. 19, Issue 9 https://doi.org/10.1074/mcp.tir120.002048	journal	September 2020
AutoCCS: automated collision cross-section calculation software for ion mobility spectrometry–mass spectrometry Lee, Joon-Yong; Bilbao, Aivett; Conant, Christopher R. Bioinformatics https://doi.org/10.1093/bioinformatics/btab429	journal	June 2021
Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction Rose, Bailey S.; May, Jody C.; Picache, Jaqueline A. Bioinformatics, Vol. 38, Issue 10 https://doi.org/10.1093/bioinformatics/btac197	journal	March 2022
LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets Crowell, Kevin L.; Slysz, Gordon W.; Baker, Erin S. Bioinformatics, Vol. 29, Issue 21 https://doi.org/10.1093/bioinformatics/btt465	journal	September 2013
PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association Ma, Jian; Casey, Cameron P.; Zheng, Xueyun Bioinformatics, Vol. 33, Issue 17 https://doi.org/10.1093/bioinformatics/btx305	journal	May 2017
LipidIMMS Analyzer: integrating multi-dimensional information to support lipid identification in ion mobility—mass spectrometry based lipidomics Zhou, Zhiwei; Shen, Xiaotao; Chen, Xi Bioinformatics, Vol. 35, Issue 4 https://doi.org/10.1093/bioinformatics/bty661	journal	July 2018
Plasma Chromatography --A New Dimension for Gas Chromatography and Mass Spectrometry Cohen, M. J.; Karasek, F. W. Journal of Chromatographic Science, Vol. 8, Issue 6 https://doi.org/10.1093/chromsci/8.6.330	journal	June 1970
Structural amyloid plaque polymorphism is associated with distinct lipid accumulations revealed by trapped ion mobility mass spectrometry imaging Michno, Wojciech; Wehrli, Patrick M.; Koutarapu, Srinivas Journal of Neurochemistry, Vol. 160, Issue 4 https://doi.org/10.1111/jnc.15557	journal	December 2021
Ion Mobility in Clinical Analysis: Current Progress and Future Perspectives Chouinard, C. D.; Wei, M. S.; Beekman, C. R. Clinical Chemistry, Vol. 62, Issue 1 https://doi.org/10.1373/clinchem.2015.238840	journal	November 2015
Novel Method Based on Ion Mobility Spectrometry Combined with Machine Learning for the Discrimination of Fruit Juices Calle, José Luis P.; Vázquez-Espinosa, Mercedes; Barea-Sepúlveda, Marta Foods, Vol. 12, Issue 13 https://doi.org/10.3390/foods12132536	journal	June 2023
Generation of a Collision Cross Section Library for Multi-Dimensional Plant Metabolomics Using UHPLC-Trapped Ion Mobility-MS/MS Schroeder, Mark; Meyer, Sven W.; Heyman, Heino M. Metabolites, Vol. 10, Issue 1 https://doi.org/10.3390/metabo10010013	journal	December 2019
An Overview of Molecular Modeling for Drug Discovery with Specific Illustrative Examples of Applications Aminpour, Maral; Montemagno, Carlo; Tuszynski, Jack A. Molecules, Vol. 24, Issue 9 https://doi.org/10.3390/molecules24091693	journal	April 2019
Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry–Mass Spectrometry Lipidomics Data Ross, Dylan H.; Guo, Jian; Bilbao, Aivett Molecules, Vol. 28, Issue 8 https://doi.org/10.3390/molecules28083483	journal	April 2023
Collision Cross Section Prediction Based on Machine Learning Li, Xiaohang; Wang, Hongda; Jiang, Meiting Molecules, Vol. 28, Issue 10 https://doi.org/10.3390/molecules28104050	journal	May 2023
Full Workflows for the Analysis of Gas Chromatography—Ion Mobility Spectrometry in Foodomics: Application to the Analysis of Iberian Ham Aroma Freire, Rafael; Fernandez, Luis; Mallafré-Muro, Celia Sensors, Vol. 21, Issue 18 https://doi.org/10.3390/s21186156	journal	September 2021

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59 BASIC BIOLOGICAL SCIENCES
97 MATHEMATICS AND COMPUTING
algorithm
collision-cross section
computational tool
data processing
ion mobility spectrometry-mass spectrometry
lipidomics
metabolomics
proteomics
software

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

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