Ion Mobility Collision Cross Section Compendium

Automated flow injection method for the high precision determination of drift tube ion mobility collision cross sections

The field of ion mobility-based omics studies requires high-quality collision cross section (CCS) libraries to effectively utilize CCS as a molecular descriptor. Absolute CCS values with the highest precision are obtained on drift tube instruments by measuring the drift time of ions at multiple drift voltages, commonly referred to as a 'stepped field' experiment. However, generating large scale absolute CCS libraries from drift tube instruments is time consuming due to the current lack of high-throughput methods. This communication reports a fully automated stepped-field method to acquire absolute CCS on commercially available equipment. Using a drift tube ion mobility-mass spectrometer (DTIM-MS) coupled to a minimally modified liquid chromatography (LC) system, CCS values can be measured online with a carefully timed flow injection analysis (FIA) experiment. Results demonstrate that the FIA stepped-field method yields CCS values which are of high analytical precision (<0.4% relative standard deviation, RSD) and accuracy (≤0.4% difference) comparable to CCS values obtained using traditional direct-infusion stepped-field experiments. This high-throughput CCS method consumes very little sample volume (20 μL) and will expedite the generation of large-scale CCS libraries to support molecular identification within global untargeted studies.

Conformational Landscapes of Ubiquitin, Cytochrome c, and Myoglobin: Uniform Field Ion Mobility Measurements in Helium and Nitrogen Drift Gas

In this study, a commercial uniform field drift tube ion mobility-mass spectrometer (IM-MS) was utilized to measure the gas-phase conformational populations of three well-studied proteins: ubiquitin (8566 Da), cytochrome c (12,359 Da), and myoglobin in both apo and holo forms (16,951 and 17,567 Da, respectively) in order to evaluate the use of this technology for broadscale structural proteomics applications. Proteins were electrosprayed from either acidic organic (pH ~3) or aqueous buffered (pH ~6.6) solution phase conditions, which generated a wide range of cation charge states corresponding to both extended (unfolded) and compact (folded) gas-phase conformational populations. Corresponding collision cross section (CCS) measurements were compiled for significant ion mobility peak features observed at each charge state in order to map the conformational landscapes of these proteins in both helium and nitrogen drift gases. It was observed that the conformational landscapes were similar in both drift gases, with differences being attributed primarily to ion heating during helium operation due to the necessity of operating the instrument with higher pressure differentials. Higher resolving powers were observed in nitrogen, which allowed for slightly better structural resolution of closely-spaced conformer populations. The instrumentation was found to be particularly adept at measuring low abundance conformers which are only present under gentle conditions which minimize ion heating. This work represents the single largest ion mobility CCS survey published to date for these three proteins with 266 CCS values and 117 ion mobility spectra, many of which have not been previously reported.

Evaluating lipid mediator structural complexity using ion mobility spectrometry combined with mass spectrometry

AIM

Lipid mediators (LMs) are broadly defined as a class of bioactive lipophilic molecules that regulate cell-to-cell communication events with many having a strong correlation with various human diseases and conditions. LMs are usually analyzed with  LC-MS, but their numerous isomers greatly complicate the measurements with essentially identical fragmentation spectra and LC separations are not always sufficient for distinguishing the features. Results/methodology: In this work, we characterized LMs using ion mobility spectrometry (IMS) coupled with MS (IMS-MS). The collision cross-sections and m/z values from the IMS and MS analyses displayed distinct trend lines. Specifically, the structural trend lines for sodiated LMs originating from docosahexaenoic acid had the smallest collision cross-section values in relation to m/z, while those from linoleic acid had the largest. LC-IMS-MS analyses were also performed on LMs in flu infected mouse tissue samples. These multidimensional studies were able to assess known LMs while also detecting new species.

CONCLUSION

Adding IMS separations to conventional LC-MS analyses show great utility for enabling better identification and characterization of LMs in complex biological samples.

Ion Mobility Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses

Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. Graphical Abstract ᅟ.

Determining Double Bond Position in Lipids Using Online Ozonolysis Coupled to Liquid Chromatography and Ion Mobility-Mass Spectrometry

The increasing focus on lipid metabolism has revealed a need for analytical techniques capable of structurally characterizing lipids with a high degree of specificity. Lipids can exist as any one of a large number of double bond positional isomers, which are indistinguishable by single-stage mass spectrometry alone. Ozonolysis reactions coupled to mass spectrometry have previously been demonstrated as a means for localizing double bonds in unsaturated lipids. Here we describe an online, solution-phase reactor using ozone produced via a low-pressure mercury lamp, which generates aldehyde products diagnostic of cleavage at a particular double bond position. This flow-cell device is utilized in conjunction with structurally selective ion mobility-mass spectrometry. The lamp-mediated reaction was found to be effective for multiple lipid species in both positive and negative ionization modes, and the conversion efficiency from precursor to product ions was tunable across a wide range (20-95%) by varying the flow rate through the ozonolysis device. Ion mobility separation of the ozonolysis products generated additional structural information and revealed the presence of saturated species in a complex mixture. The method presented here is simple, robust, and readily coupled to existing instrument platforms with minimal modifications necessary. For these reasons, application to standard lipidomic workflows is possible and aids in more comprehensive structural characterization of a myriad of lipid species.

Improving the discovery of secondary metabolite natural products using ion mobility-mass spectrometry

Secondary metabolite discovery requires an unbiased, comprehensive workflow to detect unknown unknowns for which little to no molecular knowledge exists. Untargeted mass spectrometry-based metabolomics is a powerful platform, particularly when coupled with ion mobility for high-throughput gas-phase separations to increase peak capacity and obtain gas-phase structural information. Ion mobility data are described by the amount of time an ion spends in the drift cell, which is directly related to an ion's collision cross section (CCS). The CCS parameter describes the size, shape, and charge of a molecule and can be used to characterize unknown metabolomic species. Here, we describe current and emerging applications of ion mobility-mass spectrometry for prioritization, discovery and structure elucidation, and spatial/temporal characterization.

Adding a new separation dimension to MS and LC-MS: What is the utility of ion mobility spectrometry?

Ion mobility spectrometry is an analytical technique known for more than 100 years, which entails separating ions in the gas phase based on their size, shape, and charge. While ion mobility spectrometry alone can be useful for some applications (mostly security analysis for detecting certain classes of narcotics and explosives), it becomes even more powerful in combination with mass spectrometry and high-performance liquid chromatography. Indeed, the limited resolving power of ion mobility spectrometry alone can be tackled when combining this analytical strategy with mass spectrometry or liquid chromatography with mass spectrometry. Over the last few years, the hyphenation of ion mobility spectrometry to mass spectrometry or liquid chromatography with mass spectrometry has attracted more and more interest, with significant progresses in both technical advances and pioneering applications. This review describes the theoretical background, available technologies, and future capabilities of these techniques. It also highlights a wide range of applications, from small molecules (natural products, metabolites, glycans, lipids) to large biomolecules (proteins, protein complexes, biopharmaceuticals, oligonucleotides).

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

Here we examine the relationship among resolving power (Rp), resolution (Rpp), and collision cross section (CCS) for compounds analyzed in previous ion mobility (IM) experiments representing a wide variety of instrument platforms and IM techniques. Our previous work indicated these three variables effectively describe and predict separation efficiency for drift tube ion mobility spectrometry experiments. In this work, we seek to determine if our previous findings are a general reflection of IM behavior that can be applied to various instrument platforms and mobility techniques. Results suggest IM distributions are well characterized by a Gaussian model and separation efficiency can be predicted on the basis of the empirical difference in the gas-phase CCS and a CCS-based resolving power definition (CCS/ΔCCS). Notably traveling wave (TWIMS) was found to operate at resolutions substantially higher than a single-peak resolving power suggested. When a CCS-based Rp definition was utilized, TWIMS was found to operate at a resolving power between 40 and 50, confirming the previous observations by Giles and co-workers. After the separation axis (and corresponding resolving power) is converted to cross section space, it is possible to effectively predict separation behavior for all mobility techniques evaluated (i.e., uniform field, trapped ion mobility, traveling wave, cyclic, and overtone instruments) using the equations described in this work. Finally, we are able to establish for the first time that the current state-of-the-art ion mobility separations benchmark at a CCS-based resolving power of >300 that is sufficient to differentiate analyte ions with CCS differences as small as 0.5%.

Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era

Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics.

Recent advances in ion mobility-mass spectrometry for improved structural characterization of glycans and glycoconjugates

Glycans and glycoconjugates are involved in regulating a vast array of cellular and molecular processes. Despite the importance of glycans in biology and disease, characterization of glycans remains difficult due to their structural complexity and diversity. Mass spectrometry (MS)-based techniques have emerged as the premier analytical tools for characterizing glycans. However, traditional MS-based strategies struggle to distinguish the large number of coexisting isomeric glycans that are indistinguishable by mass alone. Because of this, ion mobility spectrometry coupled to MS (IM-MS) has received considerable attention as an analytical tool for improving glycan characterization due to the capability of IM to resolve isomeric glycans before MS measurements. In this review, we present recent improvements in IM-MS instrumentation and methods for the structural characterization of isomeric glycans. In addition, we highlight recent applications of IM-MS that illustrate the enormous potential of this technology in a variety of research areas, including glycomics, glycoproteomics, and glycobiology.

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 500 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrant ions or calibration like some other IMS techniques, they avoid calibration errors which can cause problems in distinguishing structurally similar molecules. All measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites analyzed to date have come from key metabolism pathways such as glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle, while the secondary metabolites consisted of classes such as terpenes and flavonoids, and the xenobiotics represented a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes and when urine features were matched to the database, the addition of the IMS dimension greatly reduced the possible number of candidate molecules. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added frequently.

An Interlaboratory Evaluation of Drift Tube Ion Mobility-Mass Spectrometry Collision Cross Section Measurements

Collision cross section (CCS) measurements resulting from ion mobility-mass spectrometry (IM-MS) experiments provide a promising orthogonal dimension of structural information in MS-based analytical separations. As with any molecular identifier, interlaboratory standardization must precede broad range integration into analytical workflows. In this study, we present a reference drift tube ion mobility mass spectrometer (DTIM-MS) where improvements on the measurement accuracy of experimental parameters influencing IM separations provide standardized drift tube, nitrogen CCS values (^DTCCS_N2) for over 120 unique ion species with the lowest measurement uncertainty to date. The reproducibility of these ^DTCCS_N2 values are evaluated across three additional laboratories on a commercially available DTIM-MS instrument. The traditional stepped field CCS method performs with a relative standard deviation (RSD) of 0.29% for all ion species across the three additional laboratories. The calibrated single field CCS method, which is compatible with a wide range of chromatographic inlet systems, performs with an average, absolute bias of 0.54% to the standardized stepped field ^DTCCS_N2 values on the reference system. The low RSD and biases observed in this interlaboratory study illustrate the potential of DTIM-MS for providing a molecular identifier for a broad range of discovery based analyses.

LipidCCS: Prediction of Collision Cross-Section Values for Lipids with High Precision To Support Ion Mobility-Mass Spectrometry-Based Lipidomics

The use of collision cross-section (CCS) values derived from ion mobility-mass spectrometry (IM-MS) has been proven to facilitate lipid identifications. Its utility is restricted by the limited availability of CCS values. Recently, the machine-learning algorithm-based prediction (e.g., MetCCS) is reported to generate CCS values in a large-scale. However, the prediction precision is not sufficient to differentiate lipids due to their high structural similarities and subtle differences on CCS values. To address this challenge, we developed a new approach, namely, LipidCCS, to precisely predict lipid CCS values. In LipidCCS, a set of molecular descriptors were optimized using bioinformatic approaches to comprehensively describe the subtle structure differences for lipids. The use of optimized molecular descriptors together with a large set of standard CCS values for lipids (458 in total) to build the prediction model significantly improved the precision. The prediction precision of LipidCCS was externally validated with median relative errors (MRE) of ∼1% using independent data sets across different instruments (Agilent DTIM-MS and Waters TWIM-MS) and laboratories. We also demonstrated that the improved precision in the predicted LipidCCS database (15 646 lipids and 63 434 CCS values in total) could effectively reduce false-positive identifications of lipids. Common users can freely access our LipidCCS web server for the following: (1) the prediction of lipid CCS values directly from SMILES structure; (2) database search; and (3) lipid match and identification. We believe LipidCCS will be a valuable tool to support IM-MS-based lipidomics. The web server is freely available on the Internet ( http://www.metabolomics-shanghai.org/LipidCCS/ ).

Simultaneous endo and exo Complex Formation of Pyridine[4]arene Dimers with Neutral and Anionic Guests

The formation of complexes between hexafluorophosphate (PF₆^- ) and tetraisobutyloctahydroxypyridine[4]arene has been thoroughly studied in the gas phase (ESI-QTOF-MS, IM-MS, DFT calculations), in the solid state (X-ray crystallography), and in chloroform solution (¹ H, ¹⁹ F, and DOSY NMR spectroscopy). In all states of matter, simultaneous endo complexation of solvent molecules and exo complexation of a PF₆^- anion within a pyridine[4]arene dimer was observed. While similar ternary complexes are often observed in the solid state, this is a unique example of such behavior in the gas phase.