Abstract
Ion mobility (IM) is a gas phase separation strategy that can either supplement or serve as a high-throughput alternative to liquid chromatography (LC) in shotgun lipidomics. Incorporating the IM dimension in untargeted lipidomics workflows can help resolve isomeric lipids, and the collision cross section (CCS) values obtained from the IM measurements can provide an additional molecular descriptor to increase lipid identification confidence. This chapter provides a broad overview of an untargeted ion mobility-mass spectrometry (IM-MS) workflow using a commercial drift tube ion mobility-quadrupole-time-of-flight mass spectrometer (IM-QTOF) for high confidence lipidomics.
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References
Harris RA, Leaptrot KL, May JC et al (2019) New frontiers in lipidomics analyses using structurally selective ion mobility-mass spectrometry. TrAC Trends Anal Chem 116:316–323
Hancock SE, Poad BLJ, Batarseh A et al (2017) Advances and unresolved challenges in the structural characterization of isomeric lipids. Anal Biochem 524:45–55
Zheng X, Smith RD, Baker ES (2018) Recent advances in lipid separations and structural elucidation using mass spectrometry combined with ion mobility spectrometry, ion-molecule reactions and fragmentation approaches. Curr Opin Chem Biol 42:111–118
May JC, McLean JA (2015) Ion mobility-mass spectrometry: time-dispersive instrumentation. Anal Chem 87(3):1422–1436
Wang C, Wang M, Han X (2015) Applications of mass spectrometry for cellular lipid analysis. Mol BioSyst 11:698–713
Han X, Yang K, Gross RW (2012) Multi-dimensional mass spectrometry-based shotgun lipidomics and novel strategies for lipidomic analyses. Mass Spectrom Rev 31:134–178
Koelmel JP, Ulmer CZ, Jones CM et al (2017) Common cases of improper lipid annotation using high-resolution tandem mass spectrometry data and corresponding limitations in biological interpretation. Biochim Biophys Acta Mol Cell Biol Lipids 1862:766–770
Wishart DS, Feunang YD, Marcu A et al (2018) HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res 46:D608–D617
Kliman M, May JC, McLean JA (2011) Lipid analysis and lipidomics by structurally selective ion mobility-mass spectrometry. Biochim Biophys Acta Mol Cell Biol Lipids 1811:935–945
Paglia G, Kliman M, Claude E et al (2015) Applications of ion-mobility mass spectrometry for lipid analysis. Anal Bioanal Chem 407:4995–5007
Mason EA, McDaniel EW (1988) Transport properties of ions in gases. Wiley, New York, NY
Dodds JN, May JC, McLean JA (2017) Investigation of the complete suite of the leucine and isoleucine isomers: toward prediction of ion mobility separation capabilities. Anal Chem 89:952–959
Groessl M, Graf S, Knochenmuss R (2015) High resolution ion mobility-mass spectrometry for separation and identification of isomeric lipids. Analyst 140:6904–6911
Kyle JE, Zhang X, Weitz KK et al (2016) Uncovering biologically significant lipid isomers with liquid chromatography, ion mobility spectrometry and mass spectrometry. Analyst 141:1649–1659
Fenn LS, Kliman M, Mahsut A et al (2009) Characterizing ion mobility-mass spectrometry conformation space for the analysis of complex biological samples. Anal Bioanal Chem 394:235–244
May JC, Goodwin CR, Lareau NM et al (2014) Conformational ordering of biomolecules in the gas phase: nitrogen collision cross sections measured on a prototype high resolution drift tube ion mobility-mass spectrometer. Anal Chem 86:2107–2116
Picache JA, Rose BS, Balinski A et al (2019) Collision cross section compendium to annotate and predict multi-omic compound identities. Chem Sci 10:983–993
Leaptrot KL, May JC, Dodds JN et al (2019) Ion mobility conformational lipid atlas for high confidence lipidomics. Nat Commun 10:985
Stow SM, Causon TJ, Zheng X et al (2017) An interlaboratory evaluation of drift tube ion mobility-mass spectrometry collision cross section measurements. Anal Chem 89:9048–9055
Matyash V, Liebisch G, Kurzchalia TV et al (2008) Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. J Lipid Res 49:1137–1146
Ulmer CZ, Jones CM, Yost RA et al (2018) Optimization of Folch, Bligh-Dyer, and Matyash sample-to-extraction solvent ratios for human plasma-based lipidomics studies. Anal Chim Acta 1037:351–357
Morris CB, May JC, Leaptrot KL et al (2019) Evaluating separation selectivity and collision cross section measurement reproducibility in helium, nitrogen, argon, and carbon dioxide drift gases for drift tube ion mobility–mass spectrometry. J Am Soc Mass Spectrom 30:1059–1068
Kurulugama RT, Darland E, Kuhlmann F et al (2015) Evaluation of drift gas selection in complex sample analyses using a high performance drift tube ion mobility-QTOF mass spectrometer. Analyst 140:6834–6844
May JC, Dodds JN, Kurulugama RT et al (2015) Broadscale resolving power performance of a high precision uniform field ion mobility-mass spectrometer. Analyst 140:6824–6833
Mahieu NG, Spalding JL, Gelman SJ et al (2016) Defining and detecting complex peak relationships in mass spectral data: the Mz.unity algorithm. Anal Chem 88:9037–9046
Mahieu NG, Patti GJ (2017) Systems-level annotation of a metabolomics data set reduces 25,000 features to fewer than 1000 unique metabolites. Anal Chem 89:10397–10406
Zheng X, Aly NA, Zhou Y et al (2017) A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry. Chem Sci 8:7724–7736
Hoaglund-Hyzer CS, Li J, Clemmer DE (2000) Mobility labeling for parallel CID of ion mixtures. Anal Chem 72:2737–2740
Navas-Iglesias N, Carrasco-Pancorbo A, Cuadros-Rodríguez L (2009) From lipids analysis towards lipidomics, a new challenge for the analytical chemistry of the 21st century. Part II: analytical lipidomics. TrAC Trends Anal Chem 28:393–403
Pati S, Nie B, Arnold RD et al (2016) Extraction, chromatographic and mass spectrometric methods for lipid analysis. Biomed Chromatogr 30:695–709
Acknowledgments
This work was supported in part using the resources of the Center for Innovative Technology (CIT) at Vanderbilt University. BSR acknowledges a fellowship from the Vanderbilt Institute for Chemical Biology (VICB). Financial support was provided by the National Institutes of Health (R01GM107978) and the U.S. Environmental Protection Agency (EPA) under Assistance Agreement No. 83573601. This work has not been formally reviewed by the EPA and EPA does not endorse any products or commercial services mentioned in this document. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the EPA or the U.S. Government.
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Rose, B.S., Leaptrot, K.L., Harris, R.A., Sherrod, S.D., May, J.C., McLean, J.A. (2021). High Confidence Shotgun Lipidomics Using Structurally Selective Ion Mobility-Mass Spectrometry. In: Hsu, FF. (eds) Mass Spectrometry-Based Lipidomics. Methods in Molecular Biology, vol 2306. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1410-5_2
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DOI: https://doi.org/10.1007/978-1-0716-1410-5_2
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