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

Prediction of Collision Cross Section Values: Application to Non-Intentionally Added Substance Identification in Food Contact Materials

The synthetic chemicals in food contact materials can migrate into food and endanger human health. In this study, the traveling wave collision cross section in nitrogen values of more than 400 chemicals in food contact materials were experimentally derived by traveling wave ion mobility spectrometry. A support vector machine-based collision cross section (CCS) prediction model was developed based on CCS values of food contact chemicals and a series of molecular descriptors. More than 92% of protonated and 81% of sodiated adducts showed a relative deviation below 5%. Median relative errors for protonated and sodiated molecules were 1.50 and 1.82%, respectively. The model was then applied to the structural annotation of oligomers migrating from polyamide adhesives. The identification confidence of 11 oligomers was improved by the direct comparison of the experimental data with the predicted CCS values. Finally, the challenges and opportunities of current machine-learning models on CCS prediction were also discussed.

Geometric Analysis of Shapes in Ion Mobility-Mass Spectrometry

Experimental ion mobility-mass spectrometry (IM-MS) results are often correlated to three-dimensional structures based on theoretical chemistry calculations. The bottleneck of this approach is the need for accurate values, both experimentally and theoretically predicted. Here, we continue the development of the trend-based analyses to extract structural information from experimental IM-MS data sets. The experimental collision cross-sections (CCSs) of synthetic systems such as homopolymers and small ionic clusters are investigated in terms of CCS trends as a function of the number of repetitive units (e.g., degree of polymerization (DP) for homopolymers) and for each detected charge state. Then, we computed the projected areas of expanding but perfectly defined geometric objects using an in-house software called MoShade. The shapes were modeled using computer-aided design software where we considered only geometric factors: no atoms, mass, chemical potentials, or interactions were taken into consideration to make the method orthogonal to classical methods for 3D shape assessments using time-consuming computational chemistry. Our modeled shape evolutions favorably compared to experimentally obtained CCS trends, meaning that the apparent volume or envelope of homogeneously distributed mass effectively modeled the ion-drift gas interactions as sampled by IM-MS. The CCSs of convex shapes could be directly related to their surface area. More importantly, this relationship seems to hold even for moderately concave shapes, such as those obtained by geometry-optimized structures of ions from conventional computational chemistry methods. Theoretical sets of expanding beads-on-a-string shapes allowed extracting accurate bead and string dimensions for two homopolymers, without modeling any chemical interactions.

Separation of phosphorothioated oligonucleotide diastereomers using multiplexed drift tube ion mobility mass spectrometry

Hydrophilic interaction liquid chromatography (HILIC) coupled to drift tube ion mobility spectrometry (DTIMS) was used to separate diastereomers of five-unit oligonucleotides containing 0, 1, 2 or 3 phosphorothioate (PS) linkages. Multiplexed DTIMS (where ions are pulsed into the drift tube according to a pre-encoded sequence) and post-acquisition processing using an innovative demultiplexing tool were investigated. The electric field inside the drift tube was optimized to achieve the highest resolving power. The entrance voltage providing the best two-peak resolution was -1000V with 3-bit multiplexing. Under optimized conditions, the eight diastereomers of an oligonucleotide with three PS linkages (5'-TC∗G∗T∗G-3') could be separated unambiguously. Indeed, those diastereomers differed in their collision cross section (CCS) values. The minimal CCS values difference between two adjacent diastereomers was 0.9% with maximal RSD on CCS values of 0.3%. The use of multiplexed ion mobility and the novel high-resolution demultiplexing tool represents a real breakthrough for resolution enhancement of diastereomers in linear DTIMS.

Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity

The implication of lipid dysregulation in diseases, toxic exposure outcomes, and inflammation has brought great interest to lipidomic studies. However, lipids have proven to be analytically challenging due to their highly isomeric nature and vast concentration ranges in biological matrices. Therefore, multidimensional techniques such as those integrating liquid chromatography, ion mobility spectrometry, collision-induced dissociation, and mass spectrometry (LC-IMS-CID-MS) have been implemented to separate lipid isomers as well as provide structural information and increased identification confidence. These data sets are however extremely large and complex, resulting in challenges for data processing and annotation. Here, we have overcome these challenges by developing sample-specific multidimensional lipid libraries using the freely available software Skyline. Specifically, the human plasma library developed for this work contains over 500 unique lipids and is combined with adapted Skyline functions such as indexed retention time (iRT) for retention time prediction and IMS drift time filtering for enhanced selectivity. For comparison with other studies, this database was used to annotate LC-IMS-CID-MS data from a NIST SRM 1950 extract. The same workflow was then utilized to assess plasma and bronchoalveolar lavage fluid (BALF) samples from patients with varying degrees of smoke inhalation injury to identify lipid-based patient prognostic and diagnostic markers.

Systematic Optimization of Ambient Ionization Ion Mobility Mass Spectrometry for Rapid Separation of Isomers

Current methods typically used for metabolite screening and disease diagnosis often require extensive sample preparation, which increases analysis time and associated costs. While ambient ionization techniques enable the analysis of various samples in complex matrices with little or no sample preparation in a short time (typically within a minute), their reduced selectivity, even when coupled with high-resolution mass spectrometers, limits their application in certain fields. In this study, we have optimized the coupling of paper spray (PS) and leaf spray (LS) ambient ionization techniques with a commercially available ion mobility mass spectrometer (IM-MS) and demonstrated the separation of geometric and constitutional isomers. Ambient ionization techniques allow simultaneous introduction and ionization of samples, while background noise and matrix interference from paper and leaf substrates are filtered out by IM separation, resulting in high sensitivity and selectivity of the PS-IM-MS and LS-IM-MS workflows. In addition, we introduced a novel approach to perform single-field collision cross section (CCS) measurements, which resulted in CCS values that differ by 0.15% and 0.25% from traditional stepped-field and single-field methods, respectively. In addition, we used advanced computational tools to confidently identify analyte structures by comparing CCS values from experimental IM measurements and theoretical calculations. These results suggest that the coupling of ambient ionization methods with ion mobility techniques enables rapid, sensitive, and highly selective analysis that can be used in different fields, such as agrochemical screening and disease diagnostics.

Toward Routine Analysis of Anabolic Androgenic Steroids in Urine Using Ion Mobility-Mass Spectrometry

Anabolic androgenic steroids (AAS) make up one of the most prevalent classes of performance-enhancing drugs banned by the World Anti-Doping Agency (WADA) due to the competitive advantage they can afford athletes. Mass spectrometry-based methods coupled with chromatographic separations have become the gold standard for AAS analysis because of the superior sensitivity and selectivity provided. However, emerging analytical techniques including ion mobility spectrometry (IMS) have been demonstrated in recent applications as a means to further characterize and identify potential unknowns while simultaneously delivering improved sensitivity by filtering noise. Herein we outline the next crucial steps in bringing IMS to the routine drug testing workflow by combining it with established chromatographic and mass spectrometry methods (i.e., LC-IM-MS) for the detection of AAS in human urine. In addition to robust measurement of collision cross sections which can be used for identification purposes, functional group microtrends provide a structural basis on which to elucidate the structure of future novel anabolic agents. Lastly, the developed workflow is tested by analysis of testosterone in a realistic matrix (human urine) and demonstrates a limit of detection of 524 pg/mL, which surpasses the WADA Minimum Required Performance Levels for anabolic steroids. This work is expected to pave the way toward routine incorporation of IMS into analytical drug testing workflows to augment both qualitative and quantitative measure of performance enhancing drugs in the future.

Utilizing liquid chromatography, ion mobility spectrometry, and mass spectrometry to assess INLIGHT™ derivatized N-linked glycans in biological samples

Glycosylation is a ubiquitous co- and post-translational modification involved in the sorting, folding, and trafficking of proteins in biological systems; in humans, >50% of gene products are glycosylated with the cellular machinery of glycosylation compromising ~2% of the genome. Perturbations in glycosylation have been implicated in a variety of diseases including neurodegenerative diseases and certain types of cancer. However, understanding the relationship between a glycan and its biological role is often difficult due to the numerous glycan isomers that exist. To address this challenge, nanoflow liquid chromatography, ion mobility spectrometry, and mass spectrometry (nLC-IMS-MS) were combined with the Individuality Normalization when Labeling with the Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy to study a series of glycan standards and those enzymatically released from the glycoproteins horseradish peroxidase, fetuin, and pooled human plasma. The combination of IMS and the natural (NAT) and stable-isotope label (SIL) in the INLIGHT™ strategy provided additional confidence for each glycan identification due to the mobility aligned NAT- and SIL-labeled glycans and further capabilities for isomer examinations. Additionally, molecular trend lines based on the IMS and MS dimensions were investigated for the INLIGHT™ derivatized glycans, facilitating rapid identification of putative glycans in complex biological samples.

Utilizing ion mobility spectrometry-mass spectrometry for the characterization and detection of persistent organic pollutants and their metabolites

Persistent organic pollutants (POPs) are xenobiotic chemicals of global concern due to their long-range transport capabilities, persistence, ability to bioaccumulate, and potential to have negative effects on human health and the environment. Identifying POPs in both the environment and human body is therefore essential for assessing potential health risks, but their diverse range of chemical classes challenge analytical techniques. Currently, platforms coupling chromatography approaches with mass spectrometry (MS) are the most common analytical methods employed to evaluate both parent POPs and their respective metabolites and/or degradants in samples ranging from d rinking water to biofluids. Unfortunately, different types of analyses are commonly needed to assess both the parent and metabolite/degradant POPs from the various chemical classes. The multiple time-consuming analyses necessary thus present a number of technical and logistical challenges when rapid evaluations are needed and sample volumes are limited. To address these challenges, we characterized 64 compounds including parent per- and polyfluoroalkyl substances (PFAS), pesticides, polychlorinated biphenyls (PCBs), industrial chemicals, and pharmaceuticals and personal care products (PPCPs), in addition to their metabolites and/or degradants, using ion mobility spectrometry coupled with MS (IMS-MS) as a potential rapid screening technique. Different ionization sources including electrospray ionization (ESI) and atmospheric pressure photoionization (APPI) were employed to determine optimal ionization for each chemical. Collectively, this study advances the field of exposure assessment by structurally characterizing the 64 important environmental pollutants, assessing their best ionization sources, and evaluating their rapid screening potential with IMS-MS.

Lipid analysis by ion mobility spectrometry combined with mass spectrometry: A brief update with a perspective on applications in the clinical laboratory

Ion mobility spectrometry (IMS) is an analytical technique where ions are separated in the gas phase based on their mobility through a buffer gas in the presence of an electric field. An ion passing through an IMS device has a characteristic collisional cross section (CCS) value that depends on the buffer gas used. IMS can be coupled with mass spectrometry (MS), which characterizes an ion based on a mass-to-charge ratio (m/z), to increase analytical specificity and provide further physicochemical information. In particular, IMS-MS is of ever-increasing interest for the analysis of lipids, which can be problematic to accurately identify and quantify in bodily fluids by liquid chromatography (LC) with MS alone due to the presence of isomers, isobars, and structurally similar analogs. IMS provides an additional layer of separation when combined with front-end LC approaches, thereby, enhancing peak capacity and analytical specificity. CCS (and also ion mobility drift time) can be plotted against m/z ion intensity and/or LC retention time in order to generate in-depth molecular profiles of a sample. Utilization of IMS-MS for routine clinical laboratory testing remains relatively unexplored, but areas do exist for potential implementation. A brief update is provided here on lipid analysis using IMS-MS with a perspective on some applications in the clinical laboratory.

Insights and prospects for ion mobility-mass spectrometry in clinical chemistry

INTRODUCTION

Ion mobility-mass spectrometry is an emerging technology in the clinical setting for high throughput and high confidence molecular characterization from complex biological samples. Ion mobility spectrometry can provide isomer separations on the basis of molecular structure, the ability of which is increasing through technological developments that afford enhanced resolving power. Integrating multiple separation dimensions, such as liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) provide dramatic enhancements in the mitigation of molecular interferences for high accuracy clinical measurements.

AREAS COVERED

Multidimensional separations with LC-IM-MS provide better selectivity and sensitivity in molecular analysis. Mass spectrometry imaging of tissues to inform spatial molecular distribution is improved by complementary ion mobility analyses. Biomarker identification in surgical environments is enhanced by intraoperative biochemical analysis with mass spectrometry and holds promise for integration with ion mobility spectrometry. New prospects in high resolving power ion mobility are enhancing analysis capabilities, such as distinguishing isomeric compounds.

EXPERT OPINION

Ion mobility-mass spectrometry holds many prospects for the field of isomer identification, molecular imaging, and intraoperative tumor margin delineation in clinical settings. These advantages are afforded while maintaining fast analysis times and subsequently high throughput. High resolving power ion mobility will enhance these advantages further, in particular for analyses requiring high confidence isobaric selectivity and detection.

Trapped Ion Mobility Incorporated in LC-HRMS Workflows as an Integral Analytical Platform of High Sensitivity: Targeted and Untargeted 4D-Metabolomics in Extra Virgin Olive Oil

Trapped ion mobility spectrometry (TIMS) is a promising technique for the separation of isomers based on their mobility. In the present work, TIMS coupled to liquid chromatography (LC) and high-resolution mass spectrometry (HRMS) was applied as a comprehensive analytical platform to address authenticity challenges, focusing on extra virgin olive oil (EVOO). Isomers detected in EVOO's phenolic fraction, classified into secoiridoids group, were successfully separated. Thanks to parallel accumulation serial fragmentation (PASEF) acquisition mode, high-quality spectra were obtained, facilitating identification. Moreover, a four-dimensional (4D) untargeted metabolomics approach was implemented to evaluate EVOO's global profile in cases of both variety and geographical origin discrimination. Potential authenticity markers, attributed to isomers, were successfully identified through the proposed workflow that incorporates ion mobility information along with LC-HRMS analytical evidence (i.e., mass accuracy, retention time, isotopic pattern, MS/MS fragmentation). Our study establishes LC-TIMS-HRMS in food authenticity and highlights mobility-enhanced metabolomics in four dimensions.

Improving the Speed and Selectivity of Newborn Screening Using Ion Mobility Spectrometry-Mass Spectrometry

Detection and diagnosis of congenital disorders is the principal aim of newborn screening (NBS) programs worldwide. Mass spectrometry (MS) has become the preferred primary testing method for high-throughput NBS sampling because of its speed and selectivity. However, the ever-increasing list of NBS biomarkers included in expanding panels creates unique analytical challenges for multiplexed MS assays due to isobaric/isomeric overlap and chimeric fragmentation spectra. Since isobaric and isomeric systems limit the diagnostic power of current methods and require costly follow-up exams due to many false-positive results, here, we explore the utility of ion mobility spectrometry (IMS) to enhance the accuracy of MS assays for primary (tier 1) screening. Our results suggest that ∼400 IMS resolving power would be required to confidently assess most NBS biomarkers of interest in dried blood spots (DBSs) that currently require follow-up testing. While this level of selectivity is unobtainable with most commercially available platforms, the separations detailed here for a commercially available drift tube IMS (Agilent 6560 with high-resolution demultiplexing, HRdm) illustrate the unique capabilities of IMS to separate many diagnostic NBS biomarkers from interferences. Furthermore, to address the need for increased speed of NBS analyses, we utilized an automated solid-phase extraction (SPE) system for ∼10 s sampling of simulated NBS samples prior to IMS-MS. This proof-of-concept work demonstrates the unique capabilities of SPE-IMS-MS for high-throughput sample introduction and enhanced separation capacity conducive for increasing speed and accuracy for NBS.

A Miniature Multilevel Structures for Lossless Ion Manipulations Ion Mobility Spectrometer with Wide Mobility Range Separation Capabilities

Ion mobility spectrometry employing structures for lossless ion manipulations (SLIM-IMS) is an attractive gas-phase separation technique due to its ability to achieve unprecedented effective ion path lengths (>1 km) and IMS resolving powers in a small footprint. The emergence of multilevel SLIM technology, where ions are transferred between vertically stacked SLIM electrode surfaces, has subsequently allowed for ultralong single-pass path lengths (>40 m) to be achieved, enabling ultrahigh resolution IMS measurements to be performed over the entire mobility range in a single experiment. Here, we report on the development of a 1 m path length miniature SLIM module (miniSLIM) based on multilevel SLIM technology. Ion trajectory simulations were used to optimize SLIM board spacings and SLIM board thicknesses, and a new method of efficiently transferring ions between SLIM levels using asymmetric traveling waves (TWs) was demonstrated. We experimentally characterized the performance of the miniSLIM IMS-MS relative to a drift tube IMS-MS using Agilent tuning mixture cations and tetraalkylammonium cations. The miniSLIM achieved a resolving power of up to 131 (CCS/ΔCCS), which is ∼1.5× higher than achievable with a 78 cm path length drift tube IMS. Additionally, the entire ion mobility range was successfully transmitted in a single separation. We also demonstrated the miniSLIM's performance as a standalone IMS system (i.e., without MS), which showed baseline separation between all AgTM cations and a clear differentiation between different charge states of a standard peptide mixture. Overall, the miniSLIM provides a compact alternative to high performance IMS instruments possessing similar path lengths.

Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals

The presence of pharmaceutical compounds in the aquatic environment is a significant environmental health concern, which is exacerbated by recent evidence of the contribution of drug metabolites to the overall pharmaceutical load. In light of a recent report of the occurrence of metabolites of antiretroviral drugs (ARVDs) in wastewater, we investigate in the present work the occurrence of further ARVD metabolites in samples obtained from a domestic wastewater treatment plant in the Western Cape, South Africa. Pharmacokinetic data indicate that ARVDs are biotransformed into several positional isomeric metabolites, only two of which have been reported wastewater samples. Given the challenges associated with the separation and identification of isomeric species in complex wastewater samples, a method based on liquid chromatography hyphenated to ion mobility spectrometry-high resolution mass spectrometry (LC-IMS-HR-MS) was implemented. Gradient LC separation was achieved on a sub-2 µm reversed phase column, while the quadrupole-time-of-flight MS was operated in data independent acquisition (DIA) mode to increase spectral coverage of detected features. A mass defect filter (MDF) template was implemented to detect ARVD metabolites with known phase I and phase II mass shifts and fractional mass differences and to filter out potential interferents. IMS proved particularly useful in filtering the MS data for co-eluting species according to arrival time to provide cleaner mass spectra. This approach allowed us to confirm the presence of two known hydroxylated efavirenz and nevirapine metabolites using authentic standards, and to tentatively identify a carboxylate metabolite of abacavir previously reported in literature. Furthermore, three hydroxylated-, two sulphated and one glucuronidated metabolite of efavirenz, two hydroxylated metabolites of nevirapine and one hydroxylated metabolite of ritonavir were tentatively or putatively identified in wastewater samples for the first time. Assignment of the metabolites is discussed in terms of high resolution fragmentation data, while collisional cross section (CCS) values measured for the detected analytes are reported to facilitate further work in this area.

Toward High-Throughput Cryogenic IR Fingerprinting of Mobility-Separated Glycan Isomers

Infrared (IR) spectroscopy is a powerful tool used to infer detailed structural information on molecules, often in conjunction with quantum-chemical calculations. When applied to cryogenically cooled ions, IR spectra provide unique fingerprints that can be used for biomolecular identification. This is particularly important in the analysis of isomeric biopolymers, which are difficult to distinguish using mass spectrometry. However, IR spectroscopy typically requires laser systems that need substantial user attention and measurement times of tens of minutes, which limits its analytical utility. We report here the development of a new high-throughput instrument that combines ultrahigh-resolution ion-mobility spectrometry with cryogenic IR spectroscopy and mass spectrometry, and we apply it to the analysis of isomeric glycans. The ion mobility step, which is based on structures for lossless ion manipulations (SLIM), separates glycan isomers, and an IR fingerprint spectrum identifies them. An innovative cryogenic ion trap allows multiplexing the acquisition of analyte IR fingerprints following mobility separation, and using a turn-key IR laser, we can obtain spectra and identify isomeric species in less than a minute. This work demonstrates the potential of IR fingerprinting methods to impact the analysis of isomeric biomolecules and more specifically glycans.

Large-Scale Evaluation of Collision Cross Sections to Investigate Blood-Brain Barrier Permeation of Drugs

Successful drug administration to the central nervous system requires accurate adjustment of the drugs’ molecular properties. Therefore, structure-derived descriptors of potential brain therapeutic agents are essential for an early evaluation of pharmacokinetics during drug development. The collision cross section (CCS) of molecules was recently introduced as a novel measurable parameter to describe blood-brain barrier (BBB) permeation. This descriptor combines molecular information about mass, structure, volume, branching and flexibility. As these chemical properties are known to influence cerebral pharmacokinetics, CCS determination of new drug candidates may provide important additional spatial information to support existing models of BBB penetration of drugs. Besides measuring CCS, calculation is also possible; but however, the reliability of computed CCS values for an evaluation of BBB permeation has not yet been fully investigated. In this work, prediction tools based on machine learning were used to compute CCS values of a large number of compounds listed in drug libraries as negative or positive with respect to brain penetration (BBB⁺ and BBB⁻ compounds). Statistical evaluation of computed CCS and several other descriptors could prove the high value of CCS. Further, CCS-deduced maximum molecular size of BBB⁺ drugs matched the dimensions of BBB pores. A threshold for transcellular penetration and possible permeation through pore-like openings of cellular tight-junctions is suggested. In sum, CCS evaluation with modern in silico tools shows high potential for its use in the drug development process.

Optimization of a liquid chromatography-ion mobility-high resolution mass spectrometry platform for untargeted lipidomics and application to HepaRG cell extracts

Analytical methods to evaluate the lipidome of biological samples need to provide high data quality to ensure comprehensive profiling and reliable structural elucidation. In this perspective, liquid chromatography-high resolution mass spectrometry (LC-HRMS) is the state-of-the-art technique for lipidomic analysis of biological samples. There are thousands of lipids in most biological samples, and therefore separation methods before introduction to the mass spectrometer is key for relative quantitation and identification. Chromatographic methods differ across laboratories, without any consensus on the best methodologies. Therefore, we designed an experiment to determine the optimal LC methodology, and assessed the value of ion mobility for an additional dimension of separation. To apply an untargeted method for hypothesis generation focused on lipidomics, LC-HRMS parameters were optimized based on the measurement of 50 panel lipids covering key human metabolic pathways. Reversed-phase liquid chromatography columns were compared based on a quality scoring system considering the signal-to-noise ratio, peak shape, and retention factor. Furthermore, drift tube ion mobility spectrometry (DTIMS) was implemented to increase peak capacity and confidence during annotation by providing collision cross section (CCS) values for the analytes under investigation. However, hyphenating DTIMS to LC-HRMS may result in a reduced sensitivity due to impaired duty cycles. To increase the signal intensity, a Box-Behnken design (BBD) was used to optimize four key factors, i.e. drift entrance voltage, drift exit voltage, rear funnel entrance, and rear funnel exit voltages. Application of a maximized desirability function provided voltages for the above-mentioned parameters resulting in higher signal intensity compared to each combination of parameters used during the BBD. In addition, the influence of single pulse and Hadamard 4-bit multiplexed modes on signal intensity was explored and different trap filling and release times of ions were evaluated. The optimized LC-DTIM-HRMS platform was applied to extracts from HepaRG cells and resulted in 3912 high-quality features (<30% median relative standard deviation; n = 6, t = 24 h). From these features, 436 lipid species could be annotated (i.e., matching based on accurate mass <5 ppm, isotopic pattern, in-silico MS/MS fragmentation, and in-silico CCS database matching <3%). The application of LC-DTIM-HRMS for untargeted analysis workflows is growing and the platform optimization, as described here, can be used to guide the method development and CCS database comparison for high confidence lipid annotation.

Tandem-trapped ion mobility spectrometry/mass spectrometry coupled with ultraviolet photodissociation

RATIONALE

Tandem-ion mobility spectrometry/mass spectrometry methods have recently gained traction for the structural characterization of proteins and protein complexes. However, ion activation techniques currently coupled with tandem-ion mobility spectrometry/mass spectrometry methods are limited in their ability to characterize structures of proteins and protein complexes.

METHODS

Here, we describe the coupling of the separation capabilities of tandem-trapped ion mobility spectrometry/mass spectrometry (tTIMS/MS) with the dissociation capabilities of ultraviolet photodissociation (UVPD) for protein structure analysis.

RESULTS

We establish the feasibility of dissociating intact proteins by UV irradiation at 213 nm between the two TIMS devices in tTIMS/MS and at pressure conditions compatible with ion mobility spectrometry (2-3 mbar). We validate that the fragments produced by UVPD under these conditions result from a radical-based mechanism in accordance with prior literature on UVPD. The data suggest stabilization of fragment ions produced from UVPD by collisional cooling due to the elevated pressures used here ("UVnoD2"), which otherwise do not survive to detection. The data account for a sequence coverage for the protein ubiquitin comparable to recent reports, demonstrating the analytical utility of our instrument in mobility-separating fragment ions produced from UVPD.

CONCLUSIONS

The data demonstrate that UVPD carried out at elevated pressures of 2-3 mbar yields extensive fragment ions rich in information about the protein and that their exhaustive analysis requires IMS separation post-UVPD. Therefore, because UVPD and tTIMS/MS each have been shown to be valuable techniques on their own merit in proteomics, our contribution here underscores the potential of combining tTIMS/MS with UVPD for structural proteomics.

Collision Cross Sections for Native Proteomics: Challenges and Opportunities

Recent advancements place a comprehensive catalog of protein structure, oligomeric state, sequence, and modification status tentatively within reach, thus providing an unprecedented roadmap to therapies for many human diseases. To achieve this goal, revolutionary technologies capable of bridging key gaps in our ability to simultaneously measure protein composition and structure must be developed. Much of the current progress in this area has been catalyzed by mass spectrometry (MS) tools, which have become an indispensable resource for interrogating the structural proteome. For example, methods associated with native proteomics seek to comprehensively capture and quantify the endogenous assembly states for all proteins within an organism. Such technologies have often been partnered with ion mobility (IM) separation, from which collision cross section (CCS) information can be rapidly extracted to provide protein size information. IM technologies are also being developed that utilize CCS values to enhance the confidence of protein identification workflows derived from liquid chromatography-IM-MS analyses of enzymatically produced peptide mixtures. Such parallel advancements in technology beg the question: can CCS values prove similarly useful for the identification of intact proteins and their complexes in native proteomics? In this perspective, I examine current evidence and technology trends to explore the promise and limitations of such CCS information for the comprehensive analysis of multiprotein complexes from cellular mixtures.

High-resolution imaging and identification of biomolecules using Nano-DESI coupled to ion mobility spectrometry

Simultaneous spatial localization and structural characterization of molecules in complex biological samples currently represents an analytical challenge for mass spectrometry imaging (MSI) techniques. In this study, we describe a novel experimental platform, which substantially expands the capabilities and enhances the depth of chemical information obtained in high spatial resolution MSI experiments performed using nanospray desorption electrospray ionization (nano-DESI). Specifically, we designed and constructed a portable nano-DESI MSI platform and coupled it with a drift tube ion mobility (IM) spectrometer-mass spectrometer. We demonstrate imaging of drift time-separated ions with a high spatial resolution of better than ∼25 μm using uterine tissues on day 4 of pregnancy in mice. Collision cross-section measurements provide unique molecular descriptors of molecules observed in nano-DESI-IM-MSI necessary for their unambiguous identification by comparison with databases. Meanwhile, isomer-specific imaging reveals variations in the isomeric composition across the tissue. Furthermore, IM separation efficiently eliminates isobaric and isomeric interferences originating from solvent peaks, overlapping isotopic peaks of endogenous molecules extracted from the tissue, and products of in-source fragmentation, which is critical to obtaining accurate concentration gradients in the sample using MSI. The structural information provided by the IM separation substantially expands the molecular specificity of high-resolution MSI necessary for unraveling the complexity of biological systems.

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

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).

Intrinsic Structure and Electronic Spectrum of Deprotonated Biliverdin: Cryogenic Ion Spectroscopy and Ion Mobility

We investigated the structural and spectroscopic properties of singly deprotonated biliverdin anions in vacuo, using a combination of cryogenic ion spectroscopy, ion mobility spectrometry, and density functional theory. The ion mobility results show that at least two conformers are populated, with the dominant conformer at 75-90% relative abundance. The vibrational NH stretching signatures are sensitive to the tetrapyrrole structure, and they indicate that the tetrapyrrole system is in a helical conformation, consistent with simulated ion mobility collision cross sections. The vibrational spectrum in the fingerprint region of this singly deprotonated species shows that the two propionate groups share the remaining acidic proton. The S₁ band of the electronic spectrum in vacuo is broad, despite ion trap temperatures of 20 K during ion preparation, with a congested Franck-Condon envelope showing partially resolved vibrational features. The vertical transition exhibits a small solvatochromic red shift (-320 cm^-1) in aqueous solution.

The relevant role of ion mobility separation in LC-HRMS based screening strategies for contaminants of emerging concern in the aquatic environment

Ion mobility separation (IMS) coupled to high resolution mass spectrometry (IMS-HRMS) is a promising technique for (non-)target/suspect analysis of micropollutants in complex matrices. IMS separates ionized compounds based on their charge, shape and size facilitating the removal of co-eluting isomeric/isobaric species. Additionally, IMS data can be translated into collision cross-section (CCS) values, which can be used to increase the identification reliability. However, IMS-HRMS for the screening of contaminants of emerging concern (CECs) have been scarcely explored. In this study, the role of IMS-HRMS for the identification of CECs in complex matrices is highlighted, with emphasis on when and with which purpose is of use. The utilization of IMS can result in much cleaner mass spectra, which considerably facilitates data interpretation and the obtaining of reliable identifications. Furthermore, the robustness of IMS measurements across matrices permits the use of CCS as an additional relevant parameter during the identification step even when reference standards are not available. Moreover, an effect on the number of true and false identifications could be demonstrated by including IMS restrictions within the identification workflow. Data shown in this work is of special interest for environmental researchers dealing with the detection of CECs with state-of-the-art IMS-HRMS instruments.

Discovery and Characterization of Phenolic Compounds in Bearberry (Arctostaphylos uva-ursi) Leaves Using Liquid Chromatography-Ion Mobility-High-Resolution Mass Spectrometry

The characterization and quantification of phenolic compounds in bearberry leaves were performed using hyphenated ion mobility spectroscopy (IMS) and a quadrupole time-of-flight mass spectrometer. A higher identification confidence level was obtained by comparing the measured collision cross section (^TWCCS_N2) with predicted values using a machine learning algorithm. A total of 88 compounds were identified, including 14 arbutin derivatives, 33 hydrolyzable tannins, 6 flavanols, 26 flavonols, 9 saccharide derivatives, and glycosidic compounds. Those most reliably reproduced in all samples were quantified against respective standards. Arbutin (47-107 mg/g), 1,2,3,4,6-pentagalloylglucose (6.6-12.9 mg/g), and quercetin 3-galactoside/quercetin 3-glucoside (2.7-5.7 mg/g) were the most abundant phenolic components in the leaves. Quinic acid and ellagic acid were also detected at relatively high concentrations. The antioxidant activity of the most abundant compounds was evaluated. A critical view of the advantages and limitations of traveling wave IMS and CCS for the discovery of natural products is given.

Investigation into Small Molecule Isomeric Glucuronide Metabolite Differentiation Using In Silico and Experimental Collision Cross-Section Values

Identifying isomeric metabolites remains a challenging and time-consuming process with both sensitivity and unambiguous structural assignment typically only achieved through the combined use of LC-MS and NMR. Ion mobility mass spectrometry (IMMS) has the potential to produce timely and accurate data using a single technique to identify drug metabolites, including isomers, without the requirement for in-depth interpretation (cf. MS/MS data) using an automated computational pipeline by comparison of experimental collision cross-section (CCS) values with predicted CCS values. An ion mobility enabled Q-Tof mass spectrometer was used to determine the CCS values of 28 (14 isomeric pairs of) small molecule glucuronide metabolites, which were then compared to two different in silico models; a quantum mechanics (QM) and a machine learning (ML) approach to test these approaches. The difference between CCS values within isomer pairs was also assessed to evaluate if the difference was large enough for unambiguous structural identification through in silico prediction. A good correlation was found between both the QM- and ML-based models and experimentally determined CCS values. The predicted CCS values were found to be similar between ML and QM in silico methods, with the QM model more accurately describing the difference in CCS values between isomer pairs. Of the 14 isomeric pairs, only one (naringenin glucuronides) gave a sufficient difference in CCS values for the QM model to distinguish between the isomers with some level of confidence, with the ML model unable to confidently distinguish the studied isomer pairs. An evaluation of analyte structures was also undertaken to explore any trends or anomalies within the data set.

Multidimensional Separations of Intact Phase II Steroid Metabolites Utilizing LC-Ion Mobility-HRMS

The detection and unambiguous identification of anabolic-androgenic steroid metabolites are essential in clinical, forensic, and antidoping analyses. Recently, sulfate phase II steroid metabolites have received increased attention in steroid metabolism and drug testing. In large part, this is because phase II steroid metabolites are excreted for an extended time, making them a potential long-term chemical marker of choice for tracking steroid misuse in sports. Comprehensive analytical methods, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS), have been used to detect and identify glucuronide and sulfate steroids in human urine with high sensitivity and reliability. However, LC-MS/MS identification strategies can be hindered by the fact that phase II steroid metabolites generate nonselective ion fragments across the different metabolite markers, limiting the confidence in metabolite identifications that rely on exact mass measurement and MS/MS information. Additionally, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is sometimes insufficient at fully resolving the analyte peaks from the sample matrix (commonly urine) chemical noise, further complicating accurate identification efforts. Therefore, we developed a liquid chromatography-ion mobility-high resolution mass spectrometry (LC-IM-HRMS) method to increase the peak capacity and utilize the IM-derived collision cross section (CCS) values as an additional molecular descriptor for increased selectivity and to improve identifications of intact steroid analyses at low concentrations.

Predicting differential ion mobility behaviour in silico using machine learning

Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicting differential ion mobility would benefit practitioners by significantly reducing the time associated with method development. Here, we report a machine learning (ML) approach that predicts dispersion curves in an N2 environment, which are the compensation voltages (CVs) required for optimal ion transmission across a range of separation voltages (SVs) between 1500 to 4000 V. After training a random-forest based model using the DMS information of 409 cationic analytes, dispersion curves were reproduced with a mean absolute error (MAE) of ≤ 2.4 V, approaching typical experimental peak FWHMs of ±1.5 V. The predictive ML model was trained using only m/z and ion-neutral collision cross section (CCS) as inputs, both of which can be obtained from experimental databases before being extensively validated. By updating the model via inclusion of two CV datapoints at lower SVs (1500 V and 2000 V) accuracy was further improved to MAE ≤ 1.2 V. This improvement stems from the ability of the "guided" ML routine to accurately capture Type A and B behaviour, which was exhibited by only 2% and 17% of ions, respectively, within the dataset. Dispersion curve predictions of the database's most common Type C ions (81%) using the unguided and guided approaches exhibited average errors of 0.6 V and 0.1 V, respectively.

A new approach for identifying positional isomers of glycans cleaved from monoclonal antibodies

Glycosylation patterns in monoclonal antibodies (mAbs) can vary significantly between different host cell types, and these differences may affect mAbs safety, efficacy, and immunogenicity. Recent studies have demonstrated that glycan isomers with the terminal galactose position on either the Man α1-3 arm or the Man α1-6 arm have an impact on the effector functions and dynamic structure of mAbs. The development of a robust method to distinguish positional isomers of glycans is thus critical to guarantee mAb quality. In this work, we apply high-resolution ion mobility combined with cryogenic infrared spectroscopy to distinguish isomeric glycans with different terminal galactose positions, using G1F as an example. Selective enzymatic synthesis of the G1(α1-6)F isomer allows us to assign the peaks in the arrival-time distributions and the infrared spectra to their respective isomeric forms. Moreover, we demonstrate the impact of the host cell line (CHO and HEK-293) on the IgG G1F gycan profile at the isomer level. This work illustrates the potential of our approach for glycan analysis of mAbs.

Modular Ion Mobility Calibrants for Organometallic Anions Based on Tetraorganylborate Salts

Organometallics are widely used in catalysis and synthesis. Their analysis relies heavily on mass spectrometric methods, among which traveling-wave ion mobility spectrometry (TWIMS) has gained increasing importance. Collision cross sections (CCS) obtainable by TWIMS significantly aid the structural characterization of ions in the gas phase, but for organometallics, their accuracy has been limited by the lack of appropriate calibrants. Here, we propose tetraorganylborates and their alkali-metal bound oligomers [M_n-1(BR₄)_n]^- (M = Li, Na, K, Rb, Cs; R = aryl, Et; n = 1-6) as calibrants for electrospray ionization (ESI) TWIMS. These species chemically resemble typical organometallics and readily form upon negative-ion mode ESI of solutions of alkali-metal tetraorganylborates. By combining different tetraorganylborate salts, we have generated a large number of anions in a modular manner and determined their CCS values by drift-tube ion mobility spectrometry (DTIMS) (^DTCCS_He = 81-585, ^DTCCS_N2 = 130-704 Ų). In proof-of-concept experiments, we then applied these ^DTCCS values to the calibration of a TWIMS instrument and analyzed phenylcuprate and argentate anions, [Li_n-1M_nPh_2n]^- and [M_nPh_n+1]^- (M = Cu, Ag), as prototypical reactive organometallics. The ^TWCCS_N2 values derived from TWIMS measurements are in excellent agreement with those determined by DTIMS (<2% relative difference), demonstrating the effectiveness of the proposed calibration scheme. Moreover, we used theoretical methods to predict the structures and CCS values of the anions considered. These predictions are in good agreement with the experimental results and give further insight into the trends governing the assembly of tetraorganylborate, cuprate, and argentate oligomers.

Data Processing Workflow to Identify Structurally Related Compounds in Petroleum Substances Using Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry coupled with mass spectrometry (IMS-MS) is a post-ionization separation technique that can be used for rapid multidimensional analyses of complex samples. IMS-MS offers untargeted analysis, including ion-specific conformational data derived as collisional cross section (CCS) values. Here, we combine nitrogen gas drift tube CCS (^DTCCS_N2) and Kendrick mass defect (KMD) analyses based on CH2 and H functional units to enable compositional analyses of petroleum substances. First, polycyclic aromatic compound standards were analyzed by IMS-MS to demonstrate how CCS assists the identification of isomeric species in homologous series. Next, we used case studies of a gasoline standard previously characterized for paraffin, isoparaffin, aromatic, naphthene, and olefinic (PIANO) compounds, and a crude oil sample to demonstrate the application of the KMD analyses and CCS filtering. Finally, we propose a workflow that enables confident molecular formula assignment to the IMS-MS-derived features in petroleum samples. Collectively, this work demonstrates how rapid untargeted IMS-MS analysis and the proposed data processing workflow can be used to provide confident compositional characterization of hydrocarbon-containing substances.

Sequence-Specific Model for Predicting Peptide Collision Cross Section Values in Proteomic Ion Mobility Spectrometry

The contribution of peptide amino acid sequence to collision cross section values (CCS) has been investigated using a dataset of ∼134 000 peptides of four different charge states (1+ to 4+). The migration data were acquired using a two-dimensional liquid chromatography (LC)/trapped ion mobility spectrometry/quadrupole/time-of-flight mass spectrometry (MS) analysis of HeLa cell digests created using seven different proteases and was converted to CCS values. Following the previously reported modeling approaches using intrinsic size parameters (ISP), we extended this methodology to encode the position of individual residues within a peptide sequence. A generalized prediction model was built by dividing the dataset into eight groups (four charges for both tryptic/nontryptic peptides). Position-dependent ISPs were independently optimized for the eight subsets of peptides, resulting in prediction accuracy of ∼0.981 for the entire population of peptides. We find that ion mobility is strongly affected by the peptide's ability to solvate the positively charged sites. Internal positioning of polar residues and proline leads to decreased CCS values as they improve charge solvation; conversely, this ability decreases with increasing peptide charge due to electrostatic repulsion. Furthermore, higher helical propensity and peptide hydrophobicity result in a preferential formation of extended structures with higher than predicted CCS values. Finally, acidic/basic residues exhibit position-dependent ISP behavior consistent with electrostatic interaction with the peptide macrodipole, which affects the peptide helicity. The MS raw data files have been deposited with the ProteomeXchange Consortium via the jPOST partner repository (http://jpostdb.org) with the dataset identifiers PXD021440/JPST000959, PXD022800/JPST001017, and PXD026087/ JPST001176.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry

The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (m/z: 86-683 Da and CCS 110-236 Å2) was measured in a N2 environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's m/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform.

Plate-height model of ion mobility-mass spectrometry: Part 2-Peak-to-peak resolution and peak capacity

In a previous work, we explored zone broadening and the achievable plate numbers in linear drift tube ion mobility-mass spectrometry through developing a plate-height model [1]. On the basis of these findings, the present theoretical study extends the model by exploring peak-to-peak resolution and peak capacity in ion mobility separations. The first part provides a critical overview of chromatography-influenced resolution equations, including refinement of existing formulae. Furthermore, we present exact resolution equations for drift tube ion mobility spectrometry based on first principles. Upon implementing simple modifications, these exact formulae could be readily extended to traveling wave ion mobility separations and to cases when ion mobility spectrometry is coupled to mass spectrometry. The second part focuses on peak capacity. The well-known assumptions of constant plate number and constant peak width form the basis of existing approximate solutions. To overcome their limitations, an exact peak capacity equation is derived for drift tube ion mobility spectrometry. This exact solution is rooted in a suitable physical model of peak broadening, accounting for the finite injection pulse and subsequent diffusional spreading. By borrowing concepts from the theoretical toolbox of chromatography, we believe that the present study will help in integrating ion mobility spectrometry into the unified language of separation science.

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.

Immunomodulation of T Helper Cells by Tumor Microenvironment in Oral Cancer Is Associated With CCR8 Expression and Rapid Membrane Vitamin D Signaling Pathway

The immune system plays a key role in the protective response against oral cancer; however, the tumor microenvironment (TME) impairs this anti-cancer response by modulating T helper (Th) responses and promoting an anti-inflammatory environment. Regulatory T cells (Tregs) and Th2 effector cells (Teff) are associated with poor prognosis in oral squamous cell carcinoma (OSCC). However, the main immunomodulatory mechanisms associated with the enrichment of these subsets in OSCC remain unknown. We characterized Th-like lineages in Tregs and Teff and evaluated immunomodulatory changes induced by the TME in OSCC. Our phenotypic data revealed a higher distribution of tumour-infiltrating CCR8⁺ and Th2-like Treg in OSCC compared with non-malignant samples, whereas the percentages of Th1 cells were reduced in cancer. We then analyzed the direct effect of the TME by exposing T cell subsets to cancer secretomes and observed the OSCC secretome induced CCR8 expression and reduced cytokine production from both subsets. Transcriptomic analysis showed that the co-culture with OSCC secretome induced several gene changes associated with the vitamin D (VitD) signaling pathway in T cells. In addition, proteomic analysis identified the presence of several proteins associated with prostaglandin E2 (PGE2) production by rapid membrane VitD signaling and a reduced presence of the VitD binding protein. Thus, we analyzed the effect of VitD and PGE2 and observed that VitD promotes a regulatory Th2-like response with CCR8 expression whilst PGE2 also modulated CCR8 but inhibited cytokine production in combination with VitD. Finally, we evaluated the presence of CCR8 ligand in OSCC and observed increased chemokine CCL18, which was also able to upregulate CCR8 in activated Th cells. Overall, our data showed the immunomodulatory changes induced by the TME involving CCR8 expression and regulatory Th2 phenotypes, which are associated with PGE2 mediated VitD signaling pathway and CCL18 expression in OSCC.

Comprehensive Screening of Polycyclic Aromatic Hydrocarbons and Similar Compounds Using GC-APLI-TIMS-TOFMS/GC-EI-MS

In the present work, a novel workflow based on complementary gas-phase separations for the identification of isomeric PAHs from complex mixtures is described. This is the first report on the coupling of gas chromatography (GC), atmospheric pressure laser ionization (APLI), and trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) for the characterization of polycyclic aromatic hydrocarbons. Over a hundred known unknowns are uniquely identified based on the molecular ion retention indices I (5%), mobility (RSD < 0.6% and R = 50-90 with S_r = 0.18 V/ms), mobility-based theoretical candidate assignment (<3%), accurate mass chemical formula assignment (<2 ppm), and electron impact fragmentation pattern and database search. The advantages of theoretical modeling of PAHs and similar compounds were evaluated using candidate structures ranked by retention indices and fragmentation pattern from GC-EI-MS data sets. Over 20 PAH isomeric and deuterated standards were utilized for the GC-APLI-TIMS-TOF MS workflow validation. Noteworthy is the analytical capability for untargeted screening of isomeric and isobaric compounds with additional characterization metrics not available in traditional GC-EI-MSⁿ workflows.

Novel acquisition strategies for metabolomics using drift tube ion mobility-quadrupole resolved all ions time-of-flight mass spectrometry (IM-QRAI-TOFMS)

The focus of this work was the implementation of ion mobility (IM) and a prototype quadrupole driver within data independent acquisition (DIA) using a drift tube IM-QTOFMS aiming to improve the level of confidence in identity confirmation workflows for non-targeted metabolomics. In addition to conventional all ions (IM-AI) acquisition, quadrupole resolved all ions (IM-QRAI) acquisition allows a drift time-directed precursor ion isolation in DIA using sequential isolation of precursor ions using mass windows of up to 100 Da which can be rapidly ramped across single ion mobility transients (i.e., <100 ms) according to the arrival times of precursor ions. Both IM-AI and IM-QRAI approaches were used for identity confirmation and relative quantification of metabolites in cellular extracts of the cell factory host Pichia pastoris. Samples were spiked with a uniformly ¹³C-labeled (U¹³C) internal standard and LC with low-field drift tube IM separation was used in combination with IM-AI and IM-QRAI. Combining excellent hardware performance and correlation of IM arrival times of natural (^natC) and U¹³C metabolites enabled alignment of signals in the arrival time domain (^DTCCS_N2 differences ≤0.3%), and, in the case of IM-QRAI operation, maintenance of quantitative signals in comparison to IM-AI. The combination of tailored IM-QRAI methods for precursor ion isolation and IM separation also minimized the occurrence of spectral interferences in complex DIA datasets. Combined use of the software tools MS-DIAL, MS-Finder and Skyline for peak picking, feature alignment, reconciliation of ^natC and U¹³C isotopologue pairs, deconvolution of fragment spectra from DIA data, identity confirmation (including ^DTCCS_N2) and targeted re-extraction of datafiles were employed for the data processing workflow. Overall, the combined new acquisition and data processing approaches enabled 87 metabolites to be identified between Level 1 (identified by standard compound) and Level 3.2 (accurate mass spectrum and number of carbons confirmed). The developed methods constitute promising metabolomics discovery tools and can be used to elucidate the number of carbon atoms present in unknown metabolites in stable isotope-supported metabolomics.

Ion Mobility-High-Resolution Mass Spectrometry (IM-HRMS) for the Analysis of Contaminants of Emerging Concern (CECs): Database Compilation and Application to Urine Samples

Ion mobility mass spectrometry (IM-MS)-derived collision cross section (CCS) values can serve as a valuable additional identification parameter within the analysis of compounds of emerging concern (CEC) in human matrices. This study introduces the first comprehensive database of ^DTCCS_N2 values of 148 CECs and their metabolites including bisphenols, alternative plasticizers (AP), organophosphate flame retardants (OP), perfluoroalkyl chemicals (PFAS), and others. A total of 311 ions were included in the database, whereby the ^DTCCS_N2 values for 113 compounds are reported for the first time. For 105 compounds, more than one ion is reported. Moreover, the ^DTCCS_N2 values of several isomeric CECs and their metabolites are reported to allow a distinction between isomers. Comprehensive quality assurance guidelines were implemented in the workflow of acquiring ^DTCCS_N2 values to ensure reproducible experimental conditions. The reliability and reproducibility of the complied database were investigated by analyzing pooled human urine spiked with 30 AP and OP metabolites at two concentration levels. For all investigated metabolites, the ^DTCCS_N2 values measured in urine showed a percent error of <1% in comparison to database values. ^DTCCS_N2 values of OP metabolites showed an average percent error of 0.12% (50 ng/mL in urine) and 0.15% (20 ng/mL in urine). For AP metabolites, these values were 0.10 and 0.09%, respectively. These results show that the provided database can be of great value for enhanced identification of CECs in environmental and human matrices, which can advance future suspect screening studies on CECs.

Dynamic Time-Warping Correction for Shifts in Ultrahigh Resolving Power Ion Mobility Spectrometry and Structures for Lossless Ion Manipulations

Detection of arrival time shifts between ion mobility spectrometry (IMS) separations can limit achievable resolving power (Rp), particularly when multiple separations are summed or averaged, as commonly practiced in IMS. Such variations can be apparent in higher Rp measurements and are particularly evident in long path length traveling wave structures for lossless ion manipulations (SLIM) IMS due to their typically much longer separation times. Here, we explore data processing approaches employing single value alignment (SVA) and nonlinear dynamic time warping (DTW) to correct for variations between IMS separations, such as due to pressure fluctuations, to enable more effective spectrum summation for improving Rp and detection of low-intensity species. For multipass SLIM IMS separations, where narrow mobility range measurements have arrival times that can extend to several seconds, the SVA approach effectively corrected for such variations and significantly improved Rp for summed separations. However, SVA was much less effective for broad mobility range separations, such as obtained with multilevel SLIM IMS. Changes in ions' arrival times were observed to be correlated with small pressure changes, with approximately 0.6% relative arrival time shifts being common, sufficient to result in a loss of Rp for summed separations. Comparison of the approaches showed that DTW alignment performed similarly to SVA when used over a narrow mobility range but was significantly better (providing narrower peaks and higher signal intensities) for wide mobility range data. We found that the DTW approach increased Rp by as much as 115% for measurements in which 50 IMS separations over 2 s were summed. We conclude that DTW is superior to SVA for ultra-high-resolution broad mobility range SLIM IMS separations and leads to a large improvement in effective Rp, correcting for ion arrival time shifts regardless of the cause, as well as improving the detectability of low-abundance species. Our tool is publicly available for use with universal ion mobility format (.UIMF) and text (.txt) files.

Resolving Power and Collision Cross Section Measurement Accuracy of a Prototype High-Resolution Ion Mobility Platform Incorporating Structures for Lossless Ion Manipulation

A production prototype structures for lossless ion manipulation ion mobility (SLIM IM) platform interfaced to a commercial high-resolution mass spectrometer (MS) is described. The SLIM IM implements the traveling wave ion mobility technique across a ∼13m path length for high-resolution IM (HRIM) separations. The resolving power (CCS/ΔCCS) of the SLIM IM stage was benchmarked across various parameters (traveling wave speeds, amplitudes, and waveforms), and results indicated that resolving powers in excess of 200 can be accessed for a broad range of masses. For several cases, resolving powers greater than 300 were achieved, notably under wave conditions where ions transition from a nonselective "surfing" motion to a mobility-selective ion drift, that corresponded to ion speeds approximately 30-70% of the traveling wave speed. The separation capabilities were evaluated on a series of isomeric and isobaric compounds that cannot be resolved by MS alone, including reversed-sequence peptides (SDGRG and GRGDS), triglyceride double-bond positional isomers (TG 3, 6, 9 and TG 6, 9, 12), trisaccharides (melezitose, raffinose, isomaltotriose, and maltotriose), and ganglioside lipids (GD1b and GD1a). The SLIM IM platform resolved the corresponding isomeric mixtures, which were unresolvable using the standard resolution of a drift-tube instrument (∼50). In general, the SLIM IM-MS platform is capable of resolving peaks separated by as little as ∼0.6% without the need to target a specific separation window or drift time. Low CCS measurement biases <0.5% were obtained under high resolving power conditions. Importantly, all the analytes surveyed are able to access high-resolution conditions (>200), demonstrating that this instrument is well-suited for broadband HRIM separations important in global untargeted applications.

Mass spectrometry based untargeted metabolomics for plant systems biology

Untargeted metabolomics enables the identification of key changes to standard pathways, but also aids in revealing other important and possibly novel metabolites or pathways for further analysis. Much progress has been made in this field over the past decade and yet plant metabolomics seems to still be an emerging approach because of the high complexity of plant metabolites and the number one challenge of untargeted metabolomics, metabolite identification. This final and critical stage remains the focus of current research. The intention of this review is to give a brief current state of LC–MS based untargeted metabolomics approaches for plant specific samples and to review the emerging solutions in mass spectrometer hardware and computational tools that can help predict a compound's molecular structure to improve the identification rate.

Reevaluating the Role of Polarizability in Ion Mobility Spectrometry

With the expanding commercial availability of gas-phase separation systems that incorporate gas-phase mobility, there is a concurrent rise in efforts to cast the gas-phase mobility coefficient in terms of an ion-neutral collision cross-section (CCS). The motivating factors for this trend are varied, but many aim to complement experimental results with computationally generated CCS values from in silico structural approximations. Unfortunately, the current paradigm for relating experimental mobility results to computationally derived structures relies upon empirical approaches, including a myriad of variables that do not realistically bound the comparison. In this Critical Insight, we advocate for the development of a self-consistent experimental and computational framework that uses laboratory results to constrain the scope of the modeling effort. This paper aims to prompt discussion, challenge assumptions, and promote the development of more efficient, accurate computational techniques within the gas-phase ion measurement community. Specifically, we postulate whether experimental deviations from Langevin's polarization limit (K_pol) are suitable to estimate the relative contributions of hard-sphere collisions and long-range interactions within CCS values. Not surprisingly, different molecule classes exhibit different trends in the K/K_pol ratio when normalized for reduced mass, and the most common IMS calibrants (e.g., tune mix, polyalanine, tetraalkylammonium salts) follow different polarizability trends than many of the analytes probed in the literature. Succinctly, if gas-phase ion structure is largely invariant based upon the colliding neutral and newly developed experimental efforts can quantitatively capture ion polarizability, then modeling efforts describing a target analyte must be self-consistent as the collision neutral is changed in silico.

Discrimination of Aminobiphenyl Isomers in the Gas Phase and Investigation of Their Complex Conformations

The analysis of positional isomers is of great significance because their different chemical properties but similar structures make separation difficult. In this work, a simple method for simultaneously discriminating three positional isomers of 2-aminobiphenyl (2-ABP), 3-ABP, and 4-ABP was studied by ion mobility spectrometry (IMS) and quantum mechanical calculations at the molecular level. In the experiments, three ABP isomers were mixed with α-, β-, and γ-cyclodextrins (CD), and the IMS results show that the three ABP isomers were clearly recognized by the formed complex of [α-CD + ABP + H]⁺ via measuring their IMS, in which the different ion mobilities of 1.515, 1.544, 1.585 V·s·com^-2 with the collision cross sections (CCS) of 307.3, 312.5, 320.8 Ų were obtained for [α-CD + 2-ABP + H]⁺, [α-CD + 3-ABP + H]⁺, and [α-CD + 4-ABP + H]⁺, respectively. Collision induced dissociation analysis of the three [α-CD + ABP + H]⁺ isomer complexes were further studied, indicating that the same fragmentation process required different collisional energies, and the greater the CCS for the [α-CD + ABP + H]⁺ with looser structure and the smaller energy required. Besides, the favorable conformation and the CCS value of the different [CD + ABP + H]⁺ isomer complexes were measured via quantum mechanical calculations to detail their intermolecular interactions. It revealed that the intermolecular binding between 2-ABP and α-CD is different from that of 3- and 4-ABP, resulting in different molecular conformations and CCS, and the interaction modes of ABP with β-CD are similar to that with γ-CD, which are very consistent with the experimental observations. Finally, relative quantification of the method was performed, and satisfactory linearity with correlation coefficients (R²) greater than 0.99 was obtained. This method for isomer discrimination and conformation analysis possesses the advantages of simplicity, sensitivity, cost-effectiveness, and as such it may be widely applied in chemistry and pharmaceutical sciences.

Exploring the Impacts of Conformer Selection Methods on Ion Mobility Collision Cross Section Predictions

The prediction of structure dependent molecular properties, such as collision cross sections as measured using ion mobility spectrometry, are crucially dependent on the selection of the correct population of molecular conformers. Here, we report an in-depth evaluation of multiple conformation selection techniques, including simple averaging, Boltzmann weighting, lowest energy selection, low energy threshold reductions, and similarity reduction. Generating 50 000 conformers each for 18 molecules, we used the In Silico Chemical Library Engine (ISiCLE) to calculate the collision cross sections for the entire data set. First, we employed Monte Carlo simulations to understand the variability between conformer structures as generated using simulated annealing. Then we employed Monte Carlo simulations to the aforementioned conformer selection techniques applied on the simulated molecular property: the ion mobility collision cross section. Based on our analyses, we found Boltzmann weighting to be a good trade-off between precision and theoretical accuracy. Combining multiple techniques revealed that energy thresholds and root-mean-squared deviation-based similarity reductions can save considerable computational expense while maintaining property prediction accuracy. Molecular dynamic conformer generation tools like AMBER can continue to generate new lowest energy conformers even after tens of thousands of generations, decreasing precision between runs. This reduced precision can be ameliorated and theoretical accuracy increased by running density functional theory geometry optimization on carefully selected conformers.

Bioanalysis of erlotinib, its O-demethylated metabolites OSI-413 and OSI-420, and other metabolites by liquid chromatography-tandem mass spectrometry with additional ion mobility identification

Erlotinib is a first-generation epithelial growth factor receptor inhibitor used in the treatment of non-small cellular lung cancers. Our previously published method on a Thermo TSQ Quantum Ultra triple quadrupole mass spectrometer for the quantitation of erlotinib, OSI-420, and OSI-413 and some other kinase inhibitors was transferred to a more sensitive Sciex QTRAP5500 system. Both methods showed comparable performance in the previous range (5-5000 and 1-1000 ng/mL for erlotinib and OSI-420) with comparable accuracies and precisions (98.9-106.2 vs 98.7.0-104.0, and 3.7-13.4 vs 4.6-13.2), and a high level of agreement between the methods (R² = 0.9984 and 0.9951) for the quality control samples. The new system however was also capable of quantifying lower concentrations of both erlotinib and OSI-420 (0.5 and 0.1 ng/mL) with sufficient accuracy and precision. Along with the increased sensitivity we included the semi-quantitative determination of additional erlotinib metabolites M2, M3, M5, M6, M7, M8, M9, M10, M11, M12, M16 (hydroxy-erlotinib), M17, M18, M19, M20, M21 in a 0.1-1000 ng/mL range to the method. With a simple crash, dilute, and shoot sample preparation with acetonitrile and a 4.5 min analytical run time the method outperformed most other published methods in speed and simplicity and was suitable for TDM. Further, enhancement of the understanding of the pharmacokinetics of erlotinib and its metabolites was demonstrated.

Utilizing Ion Mobility-Mass Spectrometry to Investigate the Unfolding Pathway of Cu/Zn Superoxide Dismutase

Native mass spectrometry has emerged as a powerful tool for structural biology as it enables the evaluation of molecules as they occur in their physiological conditions. Ion mobility spectrometry-mass spectrometry (IMS-MS) has shown essential in these analyses as it allows the measurement of the shape of a molecule, denoted as its collision cross section (CCS), and mass. The structural information garnered from native IMS-MS provides insight into the tertiary and quaternary structure of proteins and can be used to validate NMR or crystallographic X-ray structures. Additionally, due to the rapid nature (millisecond measurements) and ability of IMS-MS to analyze heterogeneous solutions, it can be used to address structural questions not possible with traditional structural approaches. Herein, we applied multiple solution conditions to systematically denature bovine Cu/Zn-superoxide dismutase (SOD1) and assess its unfolding pathway from the holo-dimer to the holo-monomer, single-metal monomer, and apo-monomer. Additionally, we compared and noted 1–2% agreement between CCS values from both drift tube IMS and trapped IMS for the SOD1 holo-monomer and holo-dimer. The observed CCS values were in excellent agreement with computational CCS values predicted from the homo-dimer crystal structure, showcasing the ability to use both IMS-MS platforms to provide valuable structural information for molecular modeling of protein interactions and structural assessments.

Detection of acacia honey adulteration with high fructose corn syrup through determination of targeted α‑Dicarbonyl compound using ion mobility-mass spectrometry coupled with UHPLC-MS/MS

High-value acacia honey is often adulterated with inexpensive high fructose corn syrup (HFCS), due to their similar color and sugar composition. α‑Dicarbonyl compounds formed by Maillard reaction or caramelization during heat treatment or storage, differ between HFCS and honey due to differences in starting materials and processing methods. In this study, we compared α-dicarbonyl compounds in acacia honey and HFCS by Ion Mobility-Mass Spectrometry and multivariate statistical analysis. Through α-dicarbonyl compound derivatization with o-phenylenediamine, we screened a marker with 189.1023 m/z and 139.3 Å² Collision Cross-Section that can distinguish HFCS from acacia honey. Nuclear magnetic resonance spectra identified this marker compound as 3,4-dideoxypentosulose. We then used chromatography-coupled tandem mass spectrometry to quantitate 3,4-dideoxypentosulose in market samples of honey and HFCS and found that 3,4-dideoxypentosulose was negligible (<0.098 mg/kg) in honey, but prevalent in HFCS (≧1.174 mg/kg), indicating 3,4-dideoxypentosulose can serve as an alternative indicator of HFCS adulteration of acacia honey.

Deep learning the collisional cross sections of the peptide universe from a million experimental values

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV < 1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools peptides validate the model within a 1.4% median relative error (R > 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.

Proteomics has been advanced by algorithms that can predict different peptide features, but predicting peptide collisional cross sections (CCS) has remained challenging. Here, the authors measure over one million CCS values of tryptic peptides and develop a deep learning model for peptide CCS prediction.

UHPLC-IM-Q-ToFMS analysis of maradolipids, found exclusively in Caenorhabditis elegans dauer larvae

Lipid identification is one of the current bottlenecks in lipidomics and lipid profiling, especially for novel lipid classes, and requires multidimensional data for correct annotation. We used the combination of chromatographic and ion mobility separation together with data-independent acquisition (DIA) of tandem mass spectrometric data for the analysis of lipids in the biomedical model organism Caenorhabditis elegans. C. elegans reacts to harsh environmental conditions by interrupting its normal life cycle and entering an alternative developmental stage called dauer stage. Dauer larvae show distinct changes in metabolism and morphology to survive unfavorable environmental conditions and are able to survive for a long time without feeding. Only at this developmental stage, dauer larvae produce a specific class of glycolipids called maradolipids. We performed an analysis of maradolipids using ultrahigh performance liquid chromatography-ion mobility spectrometry-quadrupole-time of flight-mass spectrometry (UHPLC-IM-Q-ToFMS) using drift tube ion mobility to showcase how the integration of retention times, collisional cross sections, and DIA fragmentation data can be used for lipid identification. The obtained results show that combination of UHPLC and IM separation together with DIA represents a valuable tool for initial lipid identification. Using this analytical tool, a total of 45 marado- and lysomaradolipids have been putatively identified and 10 confirmed by authentic standards directly from C. elegans dauer larvae lipid extracts without the further need for further purification of glycolipids. Furthermore, we putatively identified two isomers of a lysomaradolipid not known so far.