Ion Mobility-Mass Spectrometry in Metabolomic, Lipidomic, and Proteomic Analyses

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Ion Mobility-Mass Spectrometry in Metabolomic, Lipidomic, and Proteomic Analyses Christopher D. Chouinard2, Gabe Nagy, Richard D. Smith, Erin S. Baker1 Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States 1 Corresponding author: e-mail address: [email protected]

Contents 1. Introduction 2. Ion Mobility-Mass Spectrometry in Metabolomics and Lipidomics 2.1 Identification and Quantitation of Metabolites 2.2 Lipidomics: A Structurally Challenging Class of Molecules 3. Ion Mobility-Mass Spectrometry in Proteomics 3.1 Bottom-up Proteomics Approaches 3.2 The Role of IMS-MS in Structural Proteomics 4. The Future Outlook for IMS-MS in the Omics 4.1 Improving CCS Measurements and Populating Databases 4.2 Potential Use of IMS-MS in Clinical Applications 4.3 Tandem Techniques and Instrumentation Advances for Improving IMS-MS 5. Conclusions References

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ABBREVIATIONS CCS CID CIU DMS DTIMS ECD EDD EHSS

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collision cross section collision-induced dissociation collision-induced unfolding differential mobility spectrometry drift tube ion mobility spectrometry electron capture dissociation electron detachment dissociation exact hard sphere scattering

Current address: Florida Institute of Technology, Melbourne, FL, United States.

Comprehensive Analytical Chemistry ISSN 0166-526X https://doi.org/10.1016/bs.coac.2018.11.001

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2018 Elsevier B.V. All rights reserved.

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ESI ETD ExD FAIMS FTICR GC HCD HDX HRMS IDP IMS IMS-MS IR IRMPD LC m/z MALDI MCC-IMS MS OzID PA PC PTM QQQ QTOF RT SLIM TG TIMS TM TOFMS TWIMS UPLC UVPD

electrospray ionization electron transfer dissociation electron-activated dissociation methods high-field asymmetric waveform ion mobility spectrometry Fourier transform ion cyclotron resonance mass spectrometry gas chromatography higher energy collisional dissociation hydrogen deuterium exchange high-resolution mass spectrometry intrinsically disordered proteins ion mobility spectrometry ion mobility-mass spectrometry infrared infrared multiple photon dissociation liquid chromatography mass-to-charge matrix-assisted laser desorption/ionization multicapillary column ion mobility spectrometry mass spectrometry ozone-induced dissociation projection approximation phosphatidylcholine posttranslational modification triple quadrupole mass spectrometry quadrupole time-of-flight retention time structures for lossless ion manipulations triacylglycerol trapped ion mobility spectrometry trajectory method time-of-flight mass spectrometry travelling wave ion mobility spectrometry ultrahigh-performance liquid chromatography ultraviolet photodissociation

1. INTRODUCTION Ion mobility spectrometry (IMS) has historically been used in defence and environmental monitoring [1,2]. While many IMS devices are now used around the world for differentiating small molecules such as explosives, pesticides, and gunshot residue, the full capability of IMS has been limited by the discrete detection methods often employed. Charge collectors or Faraday plate current detectors are often used in these systems but neither provides any additional chemical information to the IMS assays. Thus, coupling IMS with mass spectrometry (IMS-MS) is attractive for obtaining both

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structural and mass information in one assay, and also providing an opportunity to explore systems that cannot be fully understood with current techniques [3,4]. MS has been utilized for several decades to characterize, identify, and quantify biomolecules in complex samples ranging from urine to blood plasma, as well as a multitude of other matrices [5,6]. Advances in sensitivity and resolution, in addition to improvements in more practical considerations, such as instrument size, cost, and availability, have prompted the widespread implementation of mass spectrometers in research labs, hospital/clinical facilities, and even portable/field testing applications [7]. The increasing utilization of tandem MS (MS/MS or MSn) in such applications has further improved sensitivity and specificity by allowing mass-to-charge (m/z) selection and fragmentation to reduce chemical noise and improve analysis sensitivity and selectivity. MS/MS has also paved the road for better structural characterization of biomolecules by increasing the amount of chemical information achievable. Moreover, the successful coupling of front end separations (e.g. gas or liquid chromatography, GC/LC) and a range of biomolecule-amenable ionization sources (e.g. electrospray ionization, ESI; matrix-assisted laser desorption/ionization, MALDI; etc.) have significantly expanded the capabilities of MS-based methodologies in the –omics fields. However, there is a great need to attain additional chemical information for a given sample on a faster timescale than is feasible with conventional separations. IMS-MS has shown the potential for addressing this need by providing a rapid (<100 ms), gas-phase separation capable of differentiating important biological isomers while simultaneously adding a distinctive molecular descriptor, the collision cross section (CCS) [8,9]. Since the earliest implementations, several forms of IMS have been coupled with various mass spectrometers. These IMS methods have been reviewed extensively, but briefly include drift tube IMS (DTIMS) [10–13]; travelling wave IMS (TWIMS) [14]; trapped IMS (TIMS) [15]; and differential mobility spectrometry (DMS) [16–18] also referred to as high-field asymmetric waveform IMS (FAIMS), all of which are now available in commercial implementations. Other types of IMS, including novel instrumentation and/or modifications, have also been coupled to mass spectrometers and will also be discussed throughout the chapter as relevant. Time-of-flight (TOF) and quadrupole TOF (QTOF) mass spectrometers have historically been the choice for time-dispersive IMS methods, such as DTIMS and TWIMS, due to the time nesting possible for the two, particularly with additional up-front (e.g. GC or LC) separations [3]. Since TOF MS typically acquire spectra on the order of
104 s1, while IMS

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normally operates at 10–100 spectra/s, the collection of individual mass spectra at each point across the mobility spectrum is possible. Other types of mass spectrometers have also been implemented (triple quadrupole, QQQ; ion trap; Fourier transform ion cyclotron resonance; or Orbitrapbased analyzers; etc.), especially with non-time-dispersive IMS (i.e. DMS/FAIMS) [19–21]. However, drift-time slicing, scanning, multiplexing, and other “tricks” are often utilized to accommodate the rapid IMS separations with the slower MS analysis [19]. The timescale marriage for IMS-MS also extends one step further, as it is easily coupled with conventional separation techniques that operate on the order of minutes or longer. These methods (e.g. LC-IMS-MS) often provide significant improvements in orthogonality, peak capacity, and sensitivity in the characterization of biological samples, without sacrificing throughput. IMS-MS has been increasingly explored for –omics applications, and this chapter will focus on its uses in metabolomics, lipidomics, and proteomics. In this review, the utility of IMS-MS in metabolomics will be covered in terms of identification and quantitation of small molecule metabolites such as glycans and steroids, and specific lipidomic applications will also be illustrated. The strategies for both metabolomics and lipidomics will be divided between “global” untargeted discovery-based methods and targeted assays. The utility of IMS-MS in proteomics will also be covered briefly, including the historical use of IMS for protein structural characterization, and the currently dominant “bottom-up” (i.e. peptide-based) methodologies. Finally, the future outlook of IMS-MS will be examined with regard to novel advances in tandem methods and instrumentation, as well as yet unrealized application avenues, such as in clinical testing.

2. ION MOBILITY-MASS SPECTROMETRY IN METABOLOMICS AND LIPIDOMICS 2.1 Identification and Quantitation of Metabolites Metabolomics is the study of small molecule metabolites and their role in various regulatory pathways within the human body [22]. Global, or untargeted, metabolomics is challenged by the abundance of unidentified “features” (i.e. detected species). Features are often defined as deisotoped signals for species having a separation retention time (RT) and/or MS determined m/z, but no known identity. In hypothesis-free measurements, multidimensional IMS-MS and LC-IMS-MS can improve both selectivity and coverage of the metabolome by providing additional structural information

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compared to standard MS or LC-MS-based methods [23]. In IMS, compounds of different sizes, shapes, and charges are separated as they travel through the mobility cell (Fig. 1). The measured IMS drift or arrival time for species of known mass can then be converted into a rotationally averaged CCS [24,25], which is a useful descriptor of an ion’s three-dimensional gasphase structure under given experimental conditions. Although CCS and m/z are not truly orthogonal identifiers, due to a correlation between the two measures, different molecular classes have differing relationships and exhibit distinct “trend lines”. Thus, potential insight can be garnered on the class of an unknown analyte based on its position on an m/z vs their CCS trendline [26]. CCS can be measured directly using a static field drift tube instrument, based on measured drift time and experimental instrumental parameters such as drift length, gas pressure and temperature, and field strength. With dynamic field instrumentation, such as those using travelling wave (TW) separations, CCS can be determined using known calibrants. CCS can then be used for added confidence in identification by comparison with libraries of known values, similar to RT and m/z matching with GC- or LC-MS methods, or potentially compared to theoretically derived CCS values. Fig. 2A demonstrates a typical IMS-MS metabolomics workflow in which metabolomic features (CCS and m/z) can be matched to a library or database to reduce the number of false positives, in comparison with m/z matching alone. In addition to increased confidence of identification afforded by CCS measurement and trend line analysis, the hyphenation of IMS with other pre-MS separations (e.g. sample preparation/extractions, gas/liquid/supercritical fluid chromatography, capillary

Fig. 1 IMS operates by separating ions based on their size, shape, and charge as they traverse a drift cell under the influence of an electric field. Different molecular classes (e.g. carbohydrates, peptides, and lipids) can be separated in drift time, and ions within each class can be further separated by relative differences in size. Reproduced with permission from E.S. Baker, K.E. Burnum-Johnson, Y.M. Ibrahim, D.J. Orton, M.E. Monroe, R.T. Kelly, R.J. Moore, X. Zhang, R. Theberge, C.E. Costello, R.D. Smith, Enhancing bottom-up and top-down proteomic measurements with ion mobility separations, Proteomics 15 (16) (2015) 2766–2776.

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Fig. 2 (A) IMS-MS allows for features to be identified based on their CCS and m/z. By matching these values with known databases, the false positive rate can be significantly reduced in comparison with MS-only identification. (B) The addition of LC and MS/MS (LC-IMS-MS/MS) can further improve confidence in identification by inclusion of retention time and fragmentation spectra. Reproduced with permission from Z. Zhou, J. Tu, Z.J. Zhu, Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era, Curr. Opin. Chem. Biol. 42 (2018) 34–41.

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electrophoresis, etc.) [1,27,28] and/or tandem MS can significantly improve the achievable peak capacity, and the ability to deal with highly complex mixtures. By including both RT and fragmentation spectra (Fig. 2B) with CCS and parent m/z, confidence in identification is further increased [29–31]. One current limitation to global IMS-MS protocols is the traditional use of time-of-flight mass spectrometers as the MS of choice. TOFs couple well with IMS due to the ideal nesting of timescales, but even the highest resolution TOFs will not match the identification capabilities of ultra-high-resolution mass spectrometers such as FTICR or Orbitrap-based MS platforms. While DT- or TW-based IMS systems provide a full range of mobilities in a single separation (analogous to time-of-flight MS), high-field asymmetric waveform IMS (FAIMS) and DMS are alternative techniques that function more as a mobility filter (analogous to a quadrupole MS). As such, FAIMS has been utilized in several applications for targeted metabolomics, in which given experimental conditions (dispersion and compensation voltages) allow the selective transmission of a targeted species to reduce chemical noise and improve sensitivity and limits of detection. FAIMS/DMS can also be implemented on slower acquisition/ higher resolution mass spectrometers. IMS-MS has been applied to the study of metabolomics for improved compound identification across a range of metabolite classes including steroids, glycans, and lipids [1,26–28,32–45]. For example, steroids comprise a class of largely nonpolar, structurally rigid molecules that can be difficult to differentiate with GC- or LC-MS methods. Minor variations in hydroxyl/ ketone group location, stereochemistry, and double bond position within the ring structure complicate separation and identification of these compounds. However, IMS-MS has shown great promise in separation of these components (Fig. 3) [46–50]. Another major structural class within the field of metabolomics is that of glycans/carbohydrates. The major challenge in their analysis, termed glycomics, is the huge abundance of isomeric species resulting from: (1) isomeric monosaccharides (glucose, galactose, mannose, etc.); (2) anomericity (α- vs β-linkages); (3) glycosidic linkage position (α [1-4] linkage vs α [1-6] linkage vs β [1-4]); and (4) branching vs linear glycan forms, in which the monosaccharide composition is identical, but the connectivity along the monosaccharide chain differs (Fig. 4). Because of the abundance of structural variability, IMS-MS has emerged as a potential solution [51,52]. The earliest applications involved separation and CCS measurement of small oligosaccharides, such as tetrasaccharides, hexasaccharides, and cyclic oligosaccharides (cyclodextrins) [53,54]. More challenging glycans successfully resolved using IMS-MS include anomeric

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Fig. 3 Steroids can be challenging to separate by conventional methods like LC, but (A) many common steroid hormones are easily resolved with IMS-MS. (B) IMS even shows promise for separating the structurally similar isomers testosterone/dehydroepiandrosterone (DHEA) and pregnenolone/5α-dihydroprogesterone (5α-DHP). Reproduced with permission from C.D. Chouinard, C.R. Beekman, R.H.J. Kemperman, H.M. King, R.A. Yost, Ion mobility-mass spectrometry separation of steroid structural isomers and epimers, Int. J. Ion Mobil. Spectrom. 20 (1–2) (2016) 31–39.

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Fig. 4 Glycans differ in (A) isomeric monomer composition, linkage orientation and position, and core/branch configuration. (B) However, IMS-MS can resolve many of these different isomers. Reproduced with permission from Z. Chen, M.S. Glover, L. Li, Recent advances in ion mobility-mass spectrometry for improved structural characterization of glycans and glycoconjugates, Curr. Opin. Chem. Biol. 42 (2018) 1–8.

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trisaccharides [55], high mannose N-glycans [56], and even glycopeptides [57–59]. Despite the improvements in resolution, some challenging separations have still required alternative strategies. In contrast to typical MS ionization forms such as [M + H]+, [M + Na]+, and [M  H], the addition of various metal salts (e.g. silver chloride) can form adducts with different gas-phase structures. These different adducts have been shown to often provide improved separation of glycan isomers [60–62]. Another method for augmenting structural differences is preseparation derivatization, in which the target analytes are chemically modified with a chosen derivatizing agent. These modifications can amplify minor structural differences to improve separation and tease apart very structurally similar isomers [63,64]. Finally, addition of other enantiopure molecules (typically in the solution-phase) produces noncovalent complexes that can be more readily differentiated [65,66]. The complexation strategy has even been effectively applied to the separation of enantiomeric glucose isomers [67]. Because enantiomers have identical CCS values, the primary IMS method by which they are readily resolved is by complexation with chiral modifiers. Due to the immense structural diversity of glycans, several groups have begun compiling databases of glycan CCS values [68].

2.2 Lipidomics: A Structurally Challenging Class of Molecules Lipids comprise a biologically important molecular class that are studied for their relevance to disease state and development. However, characterization of lipids by traditional methods (i.e. GC- and LC-MS/MS) is complicated by the significant structural variation, including different head groups; tail position isomers (sn-1/sn-2 vs sn-2/sn-1); backbone stereoconfiguration differences in sn chain connectivity; double bond isomers (positional and conformational); tail isomers (16:0/16:0 vs 18:0/14:0); and S vs R orientation (Fig. 5). Although many of these isomer groups can be separated using optimized chromatographic methods, huge variability in chemical properties such as polarity can complicate analysis of global lipidomics samples. Furthermore, LC parameter optimization can be very time consuming and not straightforward as care is needed in selecting the correct stationary phases, mobile phases, flow rates and temperatures. IMS-MS only requires buffer gas optimization and is amenable to a range of preseparation techniques and ionization methods, making it an ideal complement to existing methods (Fig. 6).

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Fig. 5 Lipids comprise a structurally diverse class with differences that include (A) sn-1/ sn-2 vs sn-2/sn-1; (B) sn-backbone differences; (C) cis vs trans orientation; and (D) S vs R orientation. IMS-MS has been demonstrated to separate isomers with each of these structural differences. Reproduced with permission from J.E. Kyle, X. Zhang, K.K. Weitz, M.E. Monroe, Y.M. Ibrahim, R.J. Moore, J. Cha, X. Sun, E.S. Lovelace, J. Wagoner, S.J. Polyak, T.O. Metz, S.K. Dey, R.D. Smith, K.E. Burnum-Johnson, E.S. Baker, Uncovering biologically significant lipid isomers with liquid chromatography, ion mobility spectrometry and mass spectrometry, Analyst 41 (5) (2016) 1649–1659.

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Fig. 6 IMS is amenable to several preseparation techniques (chromatography) and ionization methods (electrospray ionization, desorption electrospray ionization) to create plots of CCS vs m/z (and RT) and can also be used for improvements in mass spectrometric imaging (MSI). Reproduced with permission from G. Paglia, B. Shrestha, G. Astarita, Ion-mobility mass spectrometry for lipidomics applications, Humana Press, New York, NY, 2017.

In lipid analyses, isomeric lipids with different head groups are easily be distinguished in IMS by their difference in their three-dimensional structures. Similarly, double-bond isomers that are increasingly difficult to resolve with chromatography and even MS/MS strategies can be resolved with IMS. In fact, during global studies, lipids are often identified simply by their class, number of fatty acyl carbons and number of double bonds (e.g. PC 32:2, indicating a phosphatidylcholine with 32 total tail carbons and 2 double bonds). The two fatty acyl chains can be identified with MS/MS; however, determining the exact location and conformation of the double bonds is considerably more difficult. Various IMS studies have demonstrated capabilities in separation of these isomers in two important ways. First, studies have shown that in general lipids with trans double bonds will have smaller CCS values than those with cis double bonds. This effect is due to the cis double bond creating a “kink” in the tail and increasing the overall gas-phase size of the ion. Second, the position of the double bond relative to the head group is correlated to the overall size of the ion. This is however difficult to determine just with structural measurements and

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additional chemical analysis such as ozone-induced fragmentation is needed [69]. To date, numerous instances of IMS-MS have been published demonstrating improvements in lipid identification. In one study IMS-MS/MS analyses were utilized to provide a high level of structural information for phosphatidylcholines (PCs), including differentiation of fatty acyl substituents at the sn-1 vs sn-2 position, and location of fatty acyl double bond(s) for PCs in plasma [70]. A different evaluation showed that glycero- and phospholipid isomers can be separated using high-resolution FAIMS-MS/ MS with
75% success when forming silver adducts with the target lipids [71,72]. Saturated and unsaturated triacylglycerol (TG) regioisomers (sn-1/3 vs sn-2) from porcine adipose tissue were also resolved as their silver adducts using FAIMS with 1-butanol or 1-propanol dopants [73]. Most importantly in previous studies, IMS-MS strategies have been implemented to directly evaluate various disease states and several biological matrices. LC-IMS-MSE (alternating low- and high-energy fragmentation) was used to perform quantitative and qualitative analysis with deeper structural insight for lipids in human plasma extracts [74]. UPLC-IMS-MSE was used to characterize new specific lipid markers in cardiovascular risk [75]. Furthermore, many other lipid derivatives have been studied using IMSMS. p-Toluenesulfonyl isocyanate-derivatized oxysterol isomers were successfully resolved in fibroblast cells with UPLC-IMS-MS [76]. Separation of eicosanoids (mono- and dihydroxy arachidonate metabolites) was performed in conjunction with CCS measurements and theoretical modelling. Prostanoids were separated with LC-FAIMS and selected reaction monitoring (LC-FRM) [77]. Gangliosides, a class of glycosphingolipids important in neurogenesis and synaptic transmission, were characterized from human foetal hippocampus, which led to the discovery of 25 novel structures [78]. Although it can be difficult to fully identify unknown lipids even with the combination of RT, CCS, MS, and MS/MS, several approaches are being undertaken to tackle this lofty goal. First, CCS libraries are becoming readily available to the public allowing researchers the ability to compare unknowns with previously identified standards, in a manner analogous to any other LC-MS/MS library database search [79–81]. Many groups have even begun to compile their own libraries for lipids, and these CCS values are being collected under different experimental conditions, including various IMS types (DT, TW, etc.), buffer gas compositions (nitrogen vs helium), and adducts (sodiated, potassiated, ammoniated, etc.). To date

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publications have illustrated greatly improved specificity and selectivity in various lipidomics approaches, including LC-IMS-MS workflows and “shotgun” approaches [82]. Machine-learning algorithm-based CCS prediction has also been implemented to generate large-scale CCS libraries in support of lipidomics [83]. These approaches are utilizing modelling knowledge from small molecules/metabolites and peptides/proteins calculations which have been performed for decades with methods such as the projection approximation (PA), exact hard sphere scattering (EHSS), and the trajectory method (TM) [84–86], and with various software programs such as MOBCAL and IMOS [87–89]. Although the combination of experimental CCS measurement with theoretical modelling and CCS prediction has been utilized extensively [49,90–96], even with increased computational power the accurate prediction of CCS is rarely better than 2%. Since experimental uncertainty alone is often much less than 1%, many structurally similar isomers can be separated, but if their identity is unknown, the 2% theoretical matching error means that very minor differences in CCS (i.e. structural isomers) may not be distinguished even with the best present modelling approaches. Thus, future work is still necessary in this area.

3. ION MOBILITY-MASS SPECTROMETRY IN PROTEOMICS 3.1 Bottom-up Proteomics Approaches Over the last few decades, the field of proteomics has established its role in monitoring various disease states. Proteomics is typically divided between the “bottom-up” and “top-down” approaches. In the bottom-up strategy, proteins are digested and then identified based on their characteristic peptides, whereas the top-down approach detects and identifies intact, undigested proteins. However, even with these two approaches, modern mass spectrometry-based proteomics still suffers from a major limitation in its lack of component resolution within complex biological samples. With the bottom-up approach, extensive chromatographic times (often >100 min) and high-resolution mass spectrometers with tandem MS capabilities for distinguishing multiply charged and isobaric species are typically required. However, even these LC-MS/MS methodologies still lack the ability to fully resolve all peptide components, especially when many of these important components are at low abundance. The inclusion of IMS, which couples with many existing LC-MS protocols, provides obvious benefits in improving proteomics component resolution without sacrificing analysis

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time and even the capability to speed up front-end separations [97,98]. The improvement from IMS is a result of (1) mobility separation based on charge state trend lines effectively reducing chemical noise from +1 charge state interferents; (2) separation of different classes of peptides, such as those containing posttranslational modifications (PTMs) like methylation or phosphorylation [99,100]; and (3) the ability to separate isomeric peptides based on differences in their gas-phase conformations (amino acid residue or sequence isomers) even if they have identical LC RTs [101]. These improvements are illustrated in Fig. 7, where LC-IMS-MS analyses of a plasma digest were able to provide over an order of magnitude improvement

Fig. 7 Global proteomic studies benefit from a third dimension of separation and the LC-IMS-MS analyses are able to provide over an order of magnitude improvement in the identification of peptides vs LC-MS alone due to greater peak capacity. Reproduced with permission from S.J. Valentine, M.D. Plasencia, X. Liu, M. Krishnan, S. Naylor, H.R. Udseth, R.D. Smith, D.E. Clemmer, Toward plasma proteome profiling with ion mobility-mass spectrometry, J. Proteome Res. 5 (2006) 2977–2984.

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in the identification of peptides compared to LC-MS alone due to increased peak capacity. These massive improvements in peak capacity have been demonstrated not only for DT- and TWIMS platforms, but also with FAIMS and TIMS. The earliest applications of IMS-MS in proteomics primarily aimed to measure CCS for structural characterization of peptides, such as those performed by the Bowers group involving bradykinin [102]. Soon thereafter, several groups began utilizing the technique to separate peptide isomers based on minor structural differences, and to measure CCS for a wide range of peptides [97,101,103–109], with some studies including CCS values for over 600 peptides from a tryptic digest of 34 common proteins [110]. These early capabilities led to more extensive profiling studies of plasma tryptic digests. Historically, bottom-up assays have been separated into targeted and discovery-based (global, untargeted, etc.) methods, although recently many approaches have been implemented to simultaneously increase coverage and throughput by combining these methods into a discovery and targeted monitoring (DTM) approach [111,112]. Using LC-DTIMS-MS, this approach utilizes heavy-labelled peptide standards, spiked into a tryptic digest for relative quantitation of target peptides, while unknown peptides are also characterized based on their RTs, CCS values, and accurate masses. This strategy provides better overall peptide/protein sequence coverage and can detect lower abundance peptides. Higher resolution TIMS (R ¼ 150–250) has been employed with this strategy, providing peptide biomarker detection (based on heavy-labelled analogues) at concentrations as low as 10 nM in xenograft tumour tissue, while also measuring untargeted peptides from other proteins [112]. Fig. 8 demonstrates the ability to resolve a target peptide TTILQSTGK from a nearly identical mass interference, based on differences in CCS, while also providing relative quantitation based on a heavy-labelled standard. IMS-MS also increases the breadth of coverage in a bottom-up proteomics workflow. One examples is the use of IMS-MS for the analysis of isomeric peptides which are difficult to separate with conventional methods such as LC. Isomeric peptides occur when the amino acid composition is identical but the sequence is different (i.e. ABCD vs ABDC); isomeric amino acids are substituted for each other (i.e. aspartate and isoaspartate; leucine and isoleucine; etc.); PTMs are localization at different sites; or stereochemical differences occur (i.e. amino acid is in either the D- or L-configuration). The most common bottom-up proteomics methods have included targeted LC-MS/MS methods, typically performed used a triple

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Fig. 8 A new proteomics paradigm involves simultaneous discovery and targeted monitoring (DTM) in which IMS is used (A) to identify peptides following separation of isobaric/isomeric species by differences in their CCS. (B) Furthermore, the use of heavy-labelled analogues (with identical CCS) can be used for relative quantitation of targeted peptides. Reproduced with permission from A. Garabedian, P. Benigni, C.E. Ramirez, E.S. Baker, T. Liu, R.D. Smith, F. Fernandez-Lima, Toward discovery and targeted peptide biomarker detection using nanoESI-TIMS-TOF MS, J. Am. Soc. Mass Spectrom. 29 (5) (2018) 817–826.

quadrupole MS or LC-HRMS methods performed with a high-resolution instrument such as an FTICR or Orbitrap-based MS. However, these proteomics analyses are extremely time consuming with chromatographic times in excess of an hour. Furthermore, even with such extensive chromatographic separations, the aforementioned isomers remain difficult to separate due to their physicochemical similarity and thus similar chromatographic behaviour. Single stage MS (and even HRMS) is not useful, as it cannot differentiate between identical m/z isomers, and even many MS/MS procedures (especially ergodic methods like collision-induced dissociation (CID) and HCD) will not fragment the parent ions in a way that provides useful sequence coverage. Although novel fragmentation methods such as electron capture dissociation (ECD), electron transfer dissociation (ETD), and ultraviolet photodissociation (UVPD) have been investigated for their increased sequence coverage, these methods suffer from a variety of limitations including minimal commercial availability and poor efficiency. In these cases, IMS-MS provides the potential to overcome pitfalls of conventional techniques without drawbacks in additional analysis time.

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3.2 The Role of IMS-MS in Structural Proteomics The relationship between structure and function in biology has formed the fundamental foundation for the utility of IMS in structural biology and proteomics. Because IMS-MS provides relative structural information not easily obtained using mass spectrometry alone, the earliest biological implementations revolved around structural characterization of biomolecules. Work performed in the 1990s displayed the utility for investigating gross structural changes (e.g. misfolding, aggregation, etc.), which researchers soon realized could be studied used for correlation to various disease states [11,53,95,102,113–115]. One interesting example of IMS-MS applied to structural biology and intact proteomics is the study of intrinsically disordered proteins (IDPs) [116–118], especially due to their implications in neurodegenerative diseases like Alzheimer’s (amyloid-β protein) and Parkinson’s (α-synuclein protein) [119–129]. In diseases such as these, where protein misfolding causes aggregation, IMS-MS can be used to aid in elucidation of disease progression. A more recent advent in native/intact proteomics is the development of collision-induced unfolding (CIU), a technique that utilizes collision voltage to impart energy on proteins or complexes and measure changes in overall size based on their stability [130]. With CIU, the collision voltage is sequentially increased prior to IMS separation, allowing for generation of arrival time spectra at each voltage. Under the gentlest of conditions (lowest energy), proteins tend to adopt compact conformations, resulting in relatively short IMS arrival times. However, as the energy is increased these proteins/complexes slowly begin an unfolding processing which leads to longer arrival times, and thus larger CCS. Plotting IMS drift time vs collision voltage produces graphs that reveal characteristic unfolding events. While this field is still in its infancy and interpreting these transitions is difficult, new information is being deemed about the structural elucidation of these macromolecules. Depending on the tertiary and quaternary structure, these proteins/complexes may undergo several discrete unfolding events, such as those shown in Fig. 9, in which a protein with several α-helix regions is slowly unfolded into different higher energy, more extended conformations. Early instances of CIU included the study of unfolding cytochrome c and apomyoglobin [95,131,132]. More recent examples have probed the conformational stability of protein complexes and protein–ligand interactions [133–135]. Especially when combined with specialized data analysis software [136] and theoretical modelling of protein structure, CIU may become an invaluable tool in the repertoire of structural biology techniques.

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Collision voltage (V)

Collision voltage (V)

Fig. 9 Collision-induced unfolding (CIU) is a tool used in native proteomics to measure structural changes as a function of energy. (A) Compact, folded proteins will gradually unfold and become larger (with longer drift time) as collision voltage is increased. (B) Plots of drift time vs collision voltage clearly show discrete unfolding events that can be useful in elucidation of protein structure. (C) The CIU comparison plot depicting an apo- and doubly bound protein–ligand complex (red and green oval) with collision voltage on x-axis, arrival time on y-axis, and colour scheme representing the differential intensities of the apo- (red) and ligand-bound (blue) states. (D) A scaled deviation score analysis depicting a comparison of two different ligand-bound states with CIU data acquired for the apo protein. Reproduced with permission from S.M. Dixit, D.A. Polasky, B.T. Ruotolo, Collision induced unfolding of isolated proteins in the gas phase: past, present, and future, Curr. Opin. Chem. Biol. 42 (2018) 93–100.

4. THE FUTURE OUTLOOK FOR IMS-MS IN THE OMICS 4.1 Improving CCS Measurements and Populating Databases An important step in advancing the routine use of IMS-MS for both targeted and untargeted studies across the –omics, is maximizing the robustness of CCS determination and compiling databases for improved identification of unknowns. Numerous interlaboratory studies have been undertaken to

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compare values measured for the same group of standard compounds during different days and in different laboratories with the same instrumentation, with some studies achieving precision as low as 0.29% (RSD) [137]. Agreement in these studies generally falls within 2%, a figure that allows routine differentiation of compounds with fairly different CCS, but many compounds with exceedingly similar three-dimensional structures (e.g. stereoisomers) may still not be reliably differentiated in complex mixtures. Many groups have begun compiling CCS libraries for lipids [26,82,83,138], glycans [68], metabolites [80,139,140], steroids [48,50], amino acids [139,141], and peptides [110]. In addition, computational modelling and machine-learning-based approaches have been attempted to predict CCS on a large-scale basis [83,139,141,142]. A full discussion of the steps necessary to improve upon this agreement is outside of the scope of this chapter, but briefly includes better control and measurement of experimental and instrumental conditions (pressure, temperature, gas purity, etc.) and agreed upon methods for CCS calibrants and calibration procedures (especially in the case of TWIMS). There remains a general lack of agreement on adequate standards for CCS calibration with the most common options being polyalanine peptides and other mixed solutions [143]. However, other studies have shown that use of calibrants in different molecular class or charge state than the target analyte(s) can create significant error in measurement and could potentially elucidate misidentification of unknown compounds of interest [144].

4.2 Potential Use of IMS-MS in Clinical Applications As the expanded study of the –omics leads to the discovery of biomarkers for various disease states, clinical assays are slowly being developed to improve upon the speed, sensitivity, selectivity, and cost of testing for targeted analytes. LC-MS/MS methods are now utilized in clinical chemistry for assays ranging from vitamin D metabolites to proteins, yet IMS offers a potentially attractive addition to the clinical LC-MS/MS workflow due primarily to its speed and ability to separate isomers/isobars in a manner that is complementary to chromatography [93,145]. As such, this coupling provides tremendous potential for increasing the speed of clinical methods, while also providing separation based on structure. Direct sampling methods such as breath analysis have also shown great promise with preliminary results indicating the presence of sarcoidosis [146], lung cancer [147], airway inflammation/asthma [148], and chronic obstructive pulmonary disorder

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(COPD) [149]. Specialized forms of IMS have also been tested for breath analysis (multicapillary column IMS, MCC-IMS) [150] and for the analysis of lipoproteins based on their size [151]. Routine implementation of IMS-based clinical methods has been extremely minimal, but improving technology and breadth of applications will ultimately lead to extensive clinical use.

4.3 Tandem Techniques and Instrumentation Advances for Improving IMS-MS The huge surge in commercially available IMS-MS instrumentation has led to significant advances in the –omics, but challenges remain and must be addressed to continue advancing the technology. Major limitations include the lack of chemical information attainable with IMS (CCS data provide limited chemical and structural information for target analytes); poor IMS resolution for commercial instruments (generally <100) which limits the separation power for compounds with very similar structure; poor IMS duty cycle; and relatively low MS resolution with TOFs. The first current limitation to IMS-based methods is the relative lack of chemical information possible from an IMS measurement as a measured CCS can only provide information regarding the overall molecular size and shape of a target analyte, but very little about its chemistry (molecular class, functional groups, etc.). In addition to previously discussed MS/MS methods such as CID/HCD, other tandem techniques have demonstrated utility. Examples include electron-activated dissociation methods (ExD) such as ECD, ETD, and electron detachment dissociation (EDD) [152–159]; optical fragmentation methods such as infrared multiple photon dissociation (IRMPD) and UVPD [159–163]; spectroscopic methods such as infrared (IR) spectroscopy [164–172]; hydrogen-deuterium exchange (HDX) [173–175]; and ion/ion or ion/molecule reactions such as OzID [176,177]. These methods have been applied to several chemical classes including glycans [160,162,166,172] and lipids. For example, online LC-IMS-MS with rapid (<10 ms) ozonolysis (OzID) allowed the identification of unsaturated lipids across 11 classes in positive/negative modes, including double bond positions identified based on fragments, and geometric configuration of double bonds by IMS (and OzID product ratios) within human plasma [176]. Coupling methods such as these with current IMS-MS based workflows will provide even more chemical information to improve the identification of unknowns.

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Next, the development of higher resolving power IMS instruments will allow for the separation of more structurally similar compounds and expand the already impressive peak capacity, especially when coupled with other preseparation techniques like chromatography. The resolution of drift tube-based instruments is ultimately limited by the length of the separation cell. Improved resolving power can be achieved with longer separation paths, but this creates increased instrument footprint and complexity/cost of electronics. Trapped ion mobility (TIMS) is a recently developed commercial option that can provide >250 resolving power, separating ions based on mobility differences when exposed to opposing gas flow and electric field [178]. This approach eliminates the resolution dependence on geometric length, and separation is instead determined by the precision with which the electric fields can be tuned [15,179–182]. Several approaches to longer drift path have been investigated, ranging from 2 m to several kilometres. The Clemmer group designed a cyclotron geometry drift tube that allowed for ions to undergo multiple cycles through the device for longer path length separations, but was limited by the relatively short path of one cycle (
2 m) that resulted in ions lapping [183–185]. Perhaps the most notable of these new technologies for gains in achievable IMS resolving power is that of structures for lossless ion manipulations (SLIM) [186]. SLIM utilize travelling wave (TW)-based separations, which enables much longer achievable path lengths as compared to DTIMS instruments due to their higher voltage constraints [187,188]. In SLIM, ions can be routed through serpentine paths created by the application of various DC and RF potentials. Significant capabilities of SLIM include the implementation of a path switching region, which routes ions either to the mass spectrometer for detection or back to the beginning of the serpentine path for additional passes throughout the SLIM module. These serpentine ultralong paths with extended routing (SUPER) separations have demonstrated achievable resolving powers of
2000 after 500 m of separation [189]. As a result of these ultralong path length separations, ion peaks will inherently become diffuse in nature (i.e. broader), and thus this approach can significantly benefit from narrowing their mobility peak widths if accomplished without sacrificing overall resolution. Compression ratio ion mobility programming (CRIMP) can accomplish this in SLIM by utilizing an intermittently applied travelling wave (i.e. a stuttering TW) to compress ions as they pass through the interface between the nonstuttering (i.e. operating in separation conditions) and stuttering regions [190]. The application of CRIMP has already demonstrated promise for increasing the resolution

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of various isomers, and was specifically illustrated for bile acid isomers with only small structural changes [191]. An additional feature of SLIM involves ions being introduced and accumulated “in-SLIM” as opposed to an external region, such as an ion funnel trap [192]. This mechanism is accomplished by completely stopping ions from entering the second region of the SLIM so that ions are accumulated in the first TW region (
9 m in the initial design used). To date, in-SLIM ion accumulation has allowed over 109 ions to be introduced in the MS platform, illustrating two to three orders of magnitude higher charge capacity than an ion funnel trap [192]. This higher accumulation capacity has already shown benefits in achieving comparable sensitivity for phosphoproteomics experiments as conventional SRM measurements and allowing the detection of ions at very low concentrations [193]. Overall, SLIM-based approaches have shown improved separations of many different types of molecules including carbohydrates, lipids, bile acids, and peptides [187–189,194,195]. Future SLIM work is underway to further improve the ion accumulation process, potentially by altering the TW conditions between accumulation and separation, as well as the development of a new SLIM module to permit concurrent ion accumulation and separation, ultimately increasing measurement duty cycle. Another method that is being explored with SLIM is multiplexing, in which successive ion packets are injected prior to completion of the preceding separation. This approach requires deconvolution of the resulting spectra (e.g. Hadamard transformation) due to overlap of the separations, potentially providing significant increases in resolution and sensitivity compared to DTIMS analyses and due to the long path lengths possible in SLIM [196–203]. A final direction to increase the utility of current IMS measurements is their coupling to higher resolution mass spectrometers. Historically, most IMS-MS instruments have utilized TOFs due to the ideal nesting of the timescales (ms for IMS, μs for TOF). This has presented a practical limitation on the resolution in the MS domain with current TOF technology only providing resolution <100,000. Alternative MS platforms, such as Fourier transform ion cyclotron resonance (FTICR) and Orbitrap-based instruments, are routinely capable of providing resolution >100,000, even exceeding 1 M in some cases. Coupling IMS with these higher resolution MS techniques presents a challenge with timescale, as acquisition of mass spectra from such high resolution can require hundreds of milliseconds to seconds. To date, several groups have designed prototype time-dispersive instrumentation (e.g. DTIMS and TWIMS) on FTICR and Orbitrap

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platforms [19,204–206], while others have explored alternative IMS modes (e.g. TIMS and FAIMS) [152,207–210]. Further developments in this area are expected in the future, including the combination of TW-based SLIM and high-resolution MS instruments.

5. CONCLUSIONS Once characterized as an “emerging” technique in the –omics, IMSMS has now proven to be a cornerstone in modern metabolomics, lipidomic and proteomic measurements. The accurate and precise measurement of CCS and compilation of databases are slowly leading to the routine use of this descriptor in molecular identification for small molecules and peptides. Previously challenging small molecule analyses such as those for glycans and lipids are now regularly being performed where isomers with only minor differences are being differentiated by their respective mobilities. Computational methods such as theoretical modelling of structures and machine-based approaches to CCS prediction are also making use of more accessible computing power to aid in molecular elucidation. Higher resolution IMS and MS instrumentation is also providing even more confidence in global measurements of complex biological samples. While, undoubtedly the increasing utility of IMS-MS hinges on its successful coupling with other preseparation, fragmentation, and characterization tools, it has clearly carved out a role in the –omics toolbox and its future in –omic measurements looks extremely optimistic.

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