Untargeted Molecular Discovery in Primary Metabolism: Collision Cross Section as a Molecular Descriptor in Ion Mobility-Mass Spectrometry

Impact of Source Conditions on Collision Cross Section Determination by Trapped Ion Mobility Spectrometry

Collision cross section (CCS) values determined in ion mobility-mass spectrometry (IM-MS) are increasingly employed as additional descriptors in metabolomics studies. CCS values must therefore be reproducible and the causes of deviations must be carefully known and controlled. Here, we analyzed lipid standards by trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) to evaluate the effects of solvent and flow rate in flow injection analysis (FIA), as well as electrospray source parameters including nebulizer gas pressure, drying gas flow rate, and temperature, on the ion mobility and CCS values. The stability of ion mobility experiments was studied over 10 h, which established the need for a delay-time of 20 min to stabilize source parameters (mostly pressure and temperature). Modifications of electrospray source parameters induced shifts of ion mobility peaks and even the occurrence of an additional peak in the ion mobility spectra. This behavior could be essentially explained by ion-solvent cluster formation. Changes in source parameters were also found to impact CCS value measurements, resulting in deviations up to 0.8%. However, internal calibration with the Tune Mix calibrant reduced the CCS deviations to 0.1%. Thus, optimization of source parameters is essential to achieve a good desolvation of lipid ions and avoid misinterpretation of peaks in ion mobility spectra due to solvent effects. This work highlights the importance of internal calibration to ensure interoperable CCS values, usable in metabolomics annotation.

Solvent Composition Can Have a Measurable Influence on the Ion Mobility-Derived Collision Cross Section of Small Molecules

Ion mobility (IM) is an important analytical technique for increasing identification coverage of metabolites in untargeted studies, especially when integrated into traditional liquid chromatography-mass spectrometry workflows. While there has been extensive work surrounding best practices to obtain and standardize collision cross section (CCS) measurements necessary for comparing across different IM techniques and laboratories, there has been little investigation into experimental factors beyond the mobility separation region that could potentially influence CCS measurements. The first-principles derived CCS of 15 chemical standards were evaluated across 27 aqueous:organic solvent compositions using a high-precision drift tube instrument. A small but measurable dependency of the CCS on the solvent composition was observed, with the larger analytes from this study (m/z > 400) exhibiting a characteristic increase in CCS at the intermediate (40-60%) solvent compositions. Parallels to the behavior of solvent viscosity and protonation site tautomers (protomers) were noted, although the origin of these solvent-dependent CCS trends is as yet unclear. Taken together, these findings document a solvent dependency on CCS, which, while minor (<0.5%), identifies an important need for reporting the solvent system when utilizing CCS in comparative ion mobility studies.

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen (DTCCSN2) and traveling wave CCS in nitrogen (TWCCSN2). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

Collision cross section measurement and prediction methods in omics

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

Right in two: capabilities of ion mobility spectrometry for untargeted metabolomics

This mini review focuses on the opportunities provided by current and emerging separation techniques for mass spectrometry metabolomics. The purpose of separation technologies in metabolomics is primarily to reduce complexity of the heterogeneous systems studied, and to provide concentration enrichment by increasing sensitivity towards the quantification of low abundance metabolites. For this reason, a wide variety of separation systems, from column chemistries to solvent compositions and multidimensional separations, have been applied in the field. Multidimensional separations are a common method in both proteomics applications and gas chromatography mass spectrometry, allowing orthogonal separations to further reduce analytical complexity and expand peak capacity. These applications contribute to exponential increases in run times concomitant with first dimension fractionation followed by second dimension separations. Multidimensional liquid chromatography to increase peak capacity in metabolomics, when compared to the potential of running additional samples or replicates and increasing statistical confidence, mean that uptake of these methods has been minimal. In contrast, in the last 15 years there have been significant advances in the resolution and sensitivity of ion mobility spectrometry, to the point where high-resolution separation of analytes based on their collision cross section approaches chromatographic separation, with minimal loss in sensitivity. Additionally, ion mobility separations can be performed on a chromatographic timescale with little reduction in instrument duty cycle. In this review, we compare ion mobility separation to liquid chromatographic separation, highlight the history of the use of ion mobility separations in metabolomics, outline the current state-of-the-art in the field, and discuss the future outlook of the technology. "Where there is one, you're bound to divide it. Right in two", James Maynard Keenan.

Utilization of LC-MS/MS and Drift Tube Ion Mobility for Characterizing Intact Oxidized Arachidonate-Containing Glycerophosphatidylethanolamine

Lipid peroxidation is a key component in the pathogenesis of numerous disease states, where the oxidative damage of lipids frequently leads to membrane dysfunction and subsequent cellular death. Glycerophosphoethanolamine (PE) is the second most abundant phospholipid found in cellular membranes and, when oxidized, has been identified as an executor of ferroptotic cell death. PE commonly exists in the plasmalogen form, where the presence of the vinyl ether bond and its enrichment in polyunsaturated fatty acids make it especially susceptible to oxidative degradation. This results in a multitude of oxidized products complicating identification and often requiring several analytical techniques for interpretation. In the present study, we outline an analytical approach for the structural characterization of intact oxidized products of arachidonate-containing diacyl and plasmalogen PE. Intact oxidized PE structures, including structural and positional isomers, were identified using complementary liquid chromatography techniques, drift tube ion mobility, and high-resolution tandem mass spectrometry. This work establishes a comprehensive method for the analysis of intact lipid peroxidation products and provides an important pathway to investigate how lipid peroxidation initially impacts glycerophospholipids and their role in redox biology.

Characterization of Bile Acid Isomers and the Implementation of High-Resolution Demultiplexing with Ion Mobility-Mass Spectrometry

Bile acids (BAs) are a complex suite of clinically relevant metabolites that include many isomers. Liquid chromatography coupled to mass spectrometry (LC-MS) is an increasingly popular technique due to its high specificity and sensitivity; nonetheless, acquisition times are generally 10-20 min, and isomers are not always resolved. In this study, the application of ion mobility (IM) spectrometry coupled to MS was investigated to separate, characterize, and measure BAs. A subset of 16 BAs was studied, including three groups of isomers belonging to unconjugated, glycine-conjugated, and taurine-conjugated BA classes. A variety of strategies were explored to increase BA isomer separation such as changing the drift gas, measuring different ionic species (i.e., multimers and cationized species), and enhancing the instrumental resolving power. In general, Ar, N₂, and CO₂ provided the best peak shape, resolving power (R_p), and separation, especially CO₂; He and SF₆ were less preferable. Furthermore, measuring dimers versus monomers improved isomer separation due to enhanced gas-phase structural differences. A variety of cation adducts other than sodium were characterized. Mobility arrival times and isomer separation were affected by the choice of adduct, which was shown to be used to target certain BAs. Finally, a novel workflow that involves high-resolution demultiplexing in combination with dipivaloylmethane ion-neutral clusters was implemented to improve R_p dramatically. A maximum R_p increase was observed with lower IM field strengths to obtain longer drift times, increasing R_p from 52 to 187. A combination of these separation enhancement strategies demonstrates great potential for rapid BA analysis.

Using Hadamard Transform Multiplexed IR Spectroscopy Together with a Segmented Ion Trap for the Identification of Mobility-Selected Isomers

The high isomeric complexity of glycans makes them particularly difficult to analyze. While ultra-high-resolution ion mobility spectrometry (IMS) can offer rapid baseline separation of many glycan isomers, their unambiguous identification remains a challenging task. One approach to solving this problem is to identify mobility-separated isomers by measuring their highly resolved cryogenic vibrational spectra. To be able to apply this approach to complex mixtures at high throughput, we have recently developed a Hadamard transform multiplexed spectroscopic technique that allows measuring vibrational spectra of all species separated in both IMS and mass spectrometry dimensions in a single laser scan. In the current work, we further develop the multiplexing technique using ion traps incorporated directly into the IMS device based on structures for lossless ion manipulations (SLIM). We also show that multiplexed spectroscopy using perfect sequence matrices can outperform standard multiplexing using Simplex matrices. Lastly, we show that we can increase the measurement speed and throughput further by running multiple multiplexing schemes using several SLIM ion traps in combination with simultaneous spectroscopic measurements in the segmented cryogenic ion trap.

Collision Cross Section Prediction Based on Machine Learning

Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.

A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics

Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, the high dimensionality of IM-resolved metabolomics data presents a great challenge to data processing, restricting its widespread applications. Here, we develop a mass spectrum-oriented bottom-up assembly algorithm for IM-resolved metabolomics that utilizes mass spectra to assemble four-dimensional peaks in a reverse order of multidimensional separation. We further develop the end-to-end computational framework Met4DX for peak detection, quantification and identification of metabolites in IM-resolved metabolomics. Benchmarking and validation of Met4DX demonstrates superior performance compared to existing tools with regard to coverage, sensitivity, peak fidelity and quantification precision. Importantly, Met4DX successfully detects and differentiates co-eluted metabolite isomers with small differences in the chromatographic and IM dimensions. Together, Met4DX advances metabolite discovery in biological organisms by deciphering the complex 4D metabolomics data.

Untargeted metabolomics approach using UHPLC-IMS-QTOF MS for surface body samples to identify low-volatility chemosignals related to maternal care in mice

The present study is focused on the determination of low-volatile chemosignals excreted or secreted by mouse pups in their early days of life involved in maternal care induction in mice adult females. Untargeted metabolomics was employed to differentiate between samples collected with swabs from facial and anogenital area from neonatal mouse pups receiving maternal care (first two weeks of life) and the elder mouse pups in the weaning period (4th week old). The sample extracts were analysed by ultra-high pressure liquid chromatography (UHPLC) coupled to ion mobility separation (IMS) in combination with high resolution mass spectrometry (HRMS). After data processing with Progenesis QI and multivariate statistical analysis, five markers present in the first two weeks of mouse pups life and putatively involved in materno-filial chemical communication were tentatively identified: arginine, urocanic acid, erythro-sphingosine (d17:1), sphingosine (d18:1) and sphinganine. The four-dimensional data and the tools associated to the additional structural descriptor obtained by IMS separation were of great help in the compound identification. The results demonstrated the great potential of UHPLC-IMS-HRMS based untargeted metabolomics to identity putative pheromones in mammals.

Integrating ion mobility into comprehensive multidimensional metabolomics workflows: critical considerations

BACKGROUND

Ion mobility (IM) separation capabilities are now widely available to researchers through several commercial vendors and are now being adopted into many metabolomics workflows. The added peak capacity that ion mobility offers with minimal compromise to other analytical figures-of-merit has provided real benefits to sensitivity and structural selectivity and have allowed more specific metabolite annotations to be assigned in untargeted workflows. One of the greatest promises of contemporary IM-enabled instrumentation is the capability of operating multiple analytical dimensions inline with minimal sample volumes, which has the potential to address many grand challenges currently faced in the omics fields. However, comprehensive operation of multidimensional mass spectrometry comes with its own inherent challenges that, beyond operational complexity, may not be immediately obvious to practitioners of these techniques.

AIM OF REVIEW

In this review, we outline the strengths and considerations for incorporating IM analysis in metabolomics workflows and provide a critical but forward-looking perspective on the contemporary challenges and prospects associated with interpreting IM data into chemical knowledge.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We outline a strategy for unifying IM-derived collision cross section (CCS) measurements obtained from different IM techniques and discuss the emerging field of high resolution ion mobility (HRIM) that is poised to address many of the contemporary challenges associated with ion mobility metabolomics. Whereas the LC step limits the throughput of comprehensive LC-IM-MS, the higher peak capacity of HRIM can allow fast LC gradients or rapid sample cleanup via solid-phase extraction (SPE) to be utilized, significantly improving the sample throughput.

Traveling Wave Ion Mobility-Derived Collision Cross Section Database for Plant Specialized Metabolites: An Application to Ventilago harmandiana Pierre

The combination of ion mobility mass spectrometry (IM-MS) and chromatography is a valuable tool for identifying compounds in natural products. In this study, using an ultra-performance liquid chromatography system coupled to a high-resolution quadrupole/traveling wave ion mobility spectrometry/time-of-flight MS (UPLC-TWIMS-QTOF), we have established and validated a comprehensive TWCCSN2 and MS database for 112 plant specialized metabolites. The database included 15 compounds that were isolated and purified in-house and are not commercially available. We obtained accurate m/z, retention times, fragment ions, and TWIMS-derived CCS (TWCCSN2) values for 207 adducts (ESI+ and ESI-). The database included novel 158 TWCCSN2 values from 79 specialized metabolites. In the presence of plant matrix, the CCS measurement was reproducible and robust. Finally, we demonstrated the application of the database to extend the metabolite coverage of Ventilago harmandiana Pierre. In addition to pyranonaphthoquinones, a group of known specialized metabolites in V. harmandiana, we identified flavonoids, xanthone, naphthofuran, and protocatechuic acid for the first time through targeted analysis. Interestingly, further investigation using IM-MS of unknown features suggested the presence of organonitrogen compounds and lipid and lipid-like molecules, which is also reported for the first time. Data are available on the MassIVE (https://massive.ucsd.edu, data set identifier MSV000090213).

A High-Throughput Ion Mobility Spectrometry-Mass Spectrometry Screening Method for Opioid Profiling

In 2017, the United States Department of Health and Human Services declared the widespread misuse and abuse of prescription and illicit opioids an epidemic. However, this epidemic dates back to the 1990s when opioids were extensively prescribed for pain management. Currently, opioids are still recommended for pain management, and given their abuse potential, rapid screening is imperative for patient treatment. Of particular importance is assessing pain management patient compliance, where evaluating drug use is crucial for preventing opioid abuse and potential overdoses. In this work, we utilized drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) to develop a rapid screening method for 33 target opioids and opioid urinary metabolites. Collision cross section values were determined for all target molecules using a flow-injection DTIMS-MS method, and clear differentiation of 27 out of the 33 opioids without prior chromatographic separation was observed when utilizing a high resolution demultiplexing screening approach. An automated solid phase extraction (SPE) platform was then coupled to DTIMS-MS for 10 s sample-to-sample analyses. This SPE-IMS-MS approach enabled the rapid screening of urine samples for opioids and presents a major improvement in sample throughput compared to traditional chromatographic analyses coupled with MS, which routinely take several minutes per sample. Overall, this vast reduction in analysis time facilitates a faster turn-around for patient samples, providing great benefits to clinical applications.

Applications of ion mobility-mass spectrometry in the chemical analysis in traditional Chinese medicines

离子淌度质谱(IM-MS)是一种将离子淌度分离与质谱分析相结合的新型分析技术。IM-MS的主要优势不仅是在质谱检测前提供了基于气相离子形状、大小、电荷数等因素的多一维分离,而且能够提供碰撞截面积、漂移时间等质谱信息进而辅助化合物鉴定。近年来,随着IM-MS技术的不断发展,该技术在中药化学成分分析中受到越来越多的关注。首先,IM-MS已成功应用于改善中药复杂成分尤其是同分异构体或等量异位素等成分的分离;其次,IM-MS可通过多重碎裂模式辅助高质量中药小分子质谱信息的获取;此外,IM-MS提供的高维质谱数据信息还可促进中药复杂体系多成分的整合分析。该文在对IM-MS分类和基本原理进行概述的基础上,从分离能力及分离策略、多重碎裂模式、多维质谱数据处理策略3个方面,重点综述了IM-MS在中药化学成分分析中的应用,以期为IM-MS在中药化学成分研究提供参考。

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.

Collision Cross-Section Calibration Strategy for Lipid Measurements in SLIM-Based High-Resolution Ion Mobility

Structures for lossless ion manipulation-based high-resolution ion mobility (HRIM) interfaced with mass spectrometry has emerged as a powerful tool for the separation and analysis of many isomeric systems. IM-derived collision cross section (CCS) is increasingly used as a molecular descriptor for structural analysis and feature annotation, but there are few studies on the calibration of CCS from HRIM measurements. Here, we examine the accuracy, reproducibility, and practical applicability of CCS calibration strategies for a broad range of lipid subclasses and develop a straightforward and generalizable framework for obtaining high-resolution CCS values. We explore the utility of using structurally similar custom calibrant sets as well as lipid subclass-specific empirically derived correction factors. While the lipid calibrant sets lowered overall bias of reference CCS values from ∼2-3% to ∼0.5%, application of the subclass-specific correction to values calibrated with a broadly available general calibrant set resulted in biases <0.4%. Using this method, we generated a high-resolution CCS database containing over 90 lipid values with HRIM. To test the applicability of this method to a broader class range typical of lipidomics experiments, a standard lipid mix was analyzed. The results highlight the importance of both class and arrival time range when correcting or scaling CCS values and provide guidance for implementation of the method for more general applications.

Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction

MOTIVATION

Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a highly reproducible metric for feature annotation, the collision cross-section (CCS).

RESULTS

We present a data processing workflow to increase confidence in molecular class annotations based on CCS values. This approach uses class-specific regression models built from a standardized CCS repository (the Unified CCS Compendium) in a parallel scheme that combines a new annotation filtering approach with a machine learning class prediction strategy. In a proof-of-concept study using murine brain lipid extracts, 883 lipids were assigned higher confidence identifications using the filtering approach, which reduced the tentative candidate lists by over 50% on average. An additional 192 unannotated compounds were assigned a predicted chemical class.

AVAILABILITY AND IMPLEMENTATION

All relevant source code is available at https://github.com/McLeanResearchGroup/CCS-filter.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

In Silico Collision Cross Section Calculations to Aid Metabolite Annotation

The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low or atmospheric pressure drift chamber. The sensitivity and reliability of computational prediction of CCS values depend on accurately modeling the molecular state over accessible conformations. In this work, we developed an efficient CCS computational workflow using a machine learning model in conjunction with standard DFT methods and CCS calculations. Furthermore, we have performed Traveling Wave IM-MS (TWIMS) experiments to validate the extant experimental values and assess uncertainties in experimentally measured CCS values. The developed workflow yielded accurate structural predictions and provides unique insights into the likely preferred conformation analyzed using IM-MS experiments. The complete workflow makes the computation of CCS values tractable for a large number of conformationally flexible metabolites with complex molecular structures.

Cyclic Peptide Protomer Detection in the Gas Phase: Impact on CCS Measurement and Fragmentation Patterns

With the recent improvements in ion mobility resolution, it is now possible to separate small protomeric tautomers, called protomers. In larger molecules above 1000 Da such as peptides, a few studies suggest that protomers do exist as well and may contribute to their gas-phase conformational heterogeneity. In this work, we observed a CCS distribution that can be explained by the presence of protomers of surfactin, a small lipopeptide with no basic site. Following preliminary density functional theoretical calculations, several protonation sites in the gas phase were energetically favorable in positive ionization mode. Experimentally, at least three near-resolved IM peaks were observed in positive ionization mode, while only one was detected in negative ionization mode. These results were in good agreement with the DFT predictions. CID breakdown curve analysis after IM separation showed different inflection points (CE₅₀) suggesting that different intramolecular interactions were implied in the stabilization of the structures of surfactin. The fragment ratio observed after collision-induced fragmentation was also different, suggesting different ring-opening localizations. All these observations support the presence of protomers on the cyclic peptide moieties of the surfactin. These data strongly suggest that protomeric tautomerism can still be observed on molecules above 1000 Da if the IM resolving power is sufficient. It also supports that the proton localization involves a change in the 3D structure that can affect the experimental CCS and the fragmentation channels of such peptides.

A Collision Cross Section Database for Extractables and Leachables from Food Contact Materials

The chemicals in food contact materials (FCMs) can migrate into food and endanger human health. In this study, we developed a database of traveling wave collision cross section in nitrogen (^TWCCS_N2) values for extractables and leachables from FCMs. The database contains a total of 1038 ^TWCCS_N2 values from 675 standards including those commonly used additives and nonintentionally added substances in FCMs. The ^TWCCS_N2 values in the database were compared to previously published values, and 85.7, 87.7, and 64.9% [M + H]⁺, [M + Na]⁺, and [M - H]^- adducts showed deviations <2%, with the presence of protomers, post-ion mobility spectrometry dissociation of noncovalent clusters and inconsistent calibration are possible sources of CCS deviations. Our experimental ^TWCCS_N2 values were also compared to CCS values from three prediction tools. Of the three, CCSondemand gave the most accurate predictions. The ^TWCCS_N2 database developed will aid the identification and differentiation of chemicals from FCMs in targeted and untargeted analysis.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Combining Isotopologue Workflows and Simultaneous Multidimensional Separations to Detect, Identify, and Validate Metabolites in Untargeted Analyses

While the combination of liquid chromatography and tandem mass spectrometry (LC-MS/MS) is commonly used for feature annotation in untargeted omics experiments, ensuring these prioritized features originate from endogenous metabolism remains challenging. Isotopologue workflows, such as isotopic ratio outlier analysis (IROA), mass isotopomer ratio analysis of U-¹³C labeled extracts (MIRACLE), and credentialing incorporate isotopic labels directly into metabolic precursors, guaranteeing that all features of interest are unequivocal byproducts of cellular metabolism. Furthermore, comprehensive separation and annotation of small molecules continue to challenge the metabolomics field, particularly for isomeric systems. In this paper, we evaluate the analytical utility of incorporating ion mobility spectrometry (IMS) as an additional separation mechanism into standard LC-MS/MS isotopologue workflows. Since isotopically labeled molecules codrift in the IMS dimension with their ¹²C versions, LC-IMS-CID-MS provides four dimensions (LC, IMS, MS, and MS/MS) to directly investigate the metabolic activity of prioritized untargeted features. Here, we demonstrate this additional selectivity by showcasing how a preliminary data set of 30 endogeneous metabolites are putatively annotated from isotopically labeled Escherichia coli cultures when analyzed by LC-IMS-CID-MS. Metabolite annotations were based on several molecular descriptors, including accurate mass measurement, carbon number, annotated fragmentation spectra, and collision cross section (CCS), collectively illustrating the importance of incorporating IMS into isotopologue workflows. Overall, our results highlight the enhanced separation space and increased annotation confidence afforded by IMS for metabolic characterization and provide a unique perspective for future developments in isotopically labeled MS experiments.

High-Throughput Multiplexed Infrared Spectroscopy of Ion Mobility-Separated Species Using Hadamard Transform

Coupling vibrational ion spectroscopy with high-resolution ion mobility separation offers a promising approach for detailed analysis of biomolecules in the gas phase. Improvements in the ion mobility technology have made it possible to separate isomers with minor structural differences, and their interrogation with a tunable infrared laser provides vibrational fingerprints for unambiguous database-enabled identification. Nevertheless, wide analytical application of this technique requires high-throughput approaches for acquisition of vibrational spectra of all species present in complex mixtures. In this work, we present a novel multiplexed approach and demonstrate its utility for cryogenic ion spectroscopy of peptides and glycans in mixtures. Since the method is based on Hadamard transform multiplexing, it yields infrared spectra with an increased signal-to-noise ratio compared to a conventional signal averaging approach.

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.

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.

A multifaceted approach towards understanding the peculiar behavior of (α)-hydroxyiminophosphonates

A unique multifaceted approach involving the interplay of NMR, XRD, LC, DFT and MS/IM-MS techniques toward the understanding of the peculiar isomer-selective reduction of (α)-hydroxyiminophosphonates into (α)-hydroxyaminophosphonate derivatives.

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.

Spectral entropy outperforms MS/MS dot product similarity for small-molecule compound identification

Compound identification in small-molecule research, such as untargeted metabolomics or exposome research, relies on matching tandem mass spectrometry (MS/MS) spectra against experimental or in silico mass spectral libraries. Most software programs use dot product similarity scores. Here we introduce the concept of MS/MS spectral entropy to improve scoring results in MS/MS similarity searches via library matching. Entropy similarity outperformed 42 alternative similarity algorithms, including dot product similarity, when searching 434,287 spectra against the high-quality NIST20 library. Entropy similarity scores proved to be highly robust even when we added different levels of noise ions. When we applied entropy levels to 37,299 experimental spectra of natural products, false discovery rates of less than 10% were observed at entropy similarity score 0.75. Experimental human gut metabolome data were used to confirm that entropy similarity largely improved the accuracy of MS-based annotations in small-molecule research to false discovery rates below 10%, annotated new compounds and provided the basis to automatically flag poor-quality, noisy spectra.

Online pressurized liquid extraction enables directly chemical analysis of herbal medicines: A mini review

Extraction is responsible for transferring components from solid materials into solvent. Tedious extraction procedures are usually involved in liquid chromatography-based chemical analysis of herbal medicines (HMs), resulting in extensive consumptions of organic solvents, time, energy, and materials, as well as the significant chemical degradation risks for those labile compounds. Fortunately, an emerging online pressurized liquid extraction (OLE, also known as online liquid extraction) technique has been developed for the achievement of directly chemical analysis for solid matrices in recent years, and in a short period, this versatile technique has been widely applied for the chemical analysis of HMs. In the present mini-review, we aim to briefly summarize the principles, the instrumentation, along with the application progress of this robust and flexible extraction technique in the latest six years, and the emerging challenges and future prospects are discussed as well. Special attention is paid onto the hyphenation of the versatile OLE module with LC-MS instrument. The described information is expected to introduce a promising OLE approach and to provide the guidance for the achievement of directly chemical analysis of, but not limited to, HMs.

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.

Recent advances in NMR-based metabolomics of alcoholic beverages

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NMR-based techniques can be used for establishing metabolic “fingerprint” .

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Biomarkers for discrimination of wine varietals were identified.

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COSY and DOSY techniques may aid in assigning phenolic compounds and disaccharides.

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NMR-based metabolomic studies of alcoholic beverages remain limited in Asia.

Alcoholic beverages have a complex chemistry that can be influenced by their alcoholic content, origin, fermentation process, additives, and contaminants. The complex composition of these beverages leave them susceptible to fraud, potentially compromising their authenticity, quality, and market value, thus increasing risks to consumers’ health. In recent years, intensive studies have been carried out on alcoholic beverages using different analytical techniques to evaluate the authenticity, variety, age, and fermentation processes that were used. Among these techniques, NMR-based metabolomics holds promise in profiling the chemistry of alcoholic beverages, especially in Asia where metabolomics studies on alcoholic beverages remain limited.

The Pharmacometabodynamics of Gefitinib after Intravenous Administration to Mice: A Preliminary UPLC-IM-MS Study

The effects of intravenous gefitinib (10 mg/kg), an anilinoquinazoline thymidylate kinase inhibitor (TKI), selective for the epidermal growth factor receptor (EGFR), on the urinary metabotypes of mice were studied. We hypothesized that, in response to the administration of gefitinib, there might be significant changes in the excretion of many endogenous metabolites in the urine, which could be correlated with the plasma pharmacokinetics (PK) of the drug. In order to investigate this conjecture, urine from male C57 BL6 mice was collected before IV dosing (10 mg/kg) and at 0–3, 3–8, and 8–24 h post-dose. The samples were profiled by UPLC/IM/MS and compared with the profiles obtained from undosed control mice with the data analyzed using multivariate statistical analysis (MVA). This process identified changes in endogenous metabolites over time and these were compared with drug and drug metabolite PK and excretion. While the MVA of these UPLC/IM/MS data did indeed reveal time-related changes for endogenous metabolites that appeared to be linked to drug administration, this analysis did not highlight the presence of either the drug or its metabolites in urine. Endogenous metabolites affected by gefitinib administration were identified by comparison of mass spectral, retention time and ion mobility-derived collision cross section data (compared to authentic standards wherever possible). The changes in endogenous metabolites resulting from gefitinib administration showed both increases (e.g., tryptophan, taurocholic acid, and the dipeptide lysyl-arginine) and decreases (e.g., deoxyguanosine, 8-hydroxydeoxyguanosine, and asparaginyl-histidine) relative to the control animals. By 8–24 h, the post-dose concentrations of most metabolites had returned to near control values. From these studies, we conclude that changes in the amounts of endogenous metabolites excreted in the urine mirrored, to some extent, the plasma pharmacokinetics of the drug. This phenomenon is similar to pharmacodynamics, where the pharmacological effects are related to the drug concentrations, and by analogy, we have termed this effect “pharmacometabodynamics”.

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.

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.

Ion Mobility–Mass Spectrometry for Bioanalysis

This paper aims to cover the main strategies based on ion mobility spectrometry (IMS) for the analysis of biological samples. The determination of endogenous and exogenous compounds in such samples is important for the understanding of the health status of individuals. For this reason, the development of new approaches that can be complementary to the ones already established (mainly based on liquid chromatography coupled to mass spectrometry) is welcomed. In this regard, ion mobility spectrometry has appeared in the analytical scenario as a powerful technique for the separation and characterization of compounds based on their mobility. IMS has been used in several areas taking advantage of its orthogonality with other analytical separation techniques, such as liquid chromatography, gas chromatography, capillary electrophoresis, or supercritical fluid chromatography. Bioanalysis is not one of the areas where IMS has been more extensively applied. However, over the last years, the interest in using this approach for the analysis of biological samples has clearly increased. This paper introduces the reader to the principles controlling the separation in IMS and reviews recent applications using this technique in the field of bioanalysis.

Use of ion mobility-high resolution mass spectrometry in metabolomics studies to provide near MS/MS quality data in a single injection

The use of ion mobility separations (IMSs) in metabolomics approaches has started to be deeply explored in the last years. In this work, the use of liquid chromatography (LC) coupled to IMS-quadrupole time-of-flight mass spectrometry (QTOF MS) has been evaluated in a metabolomics experiments using single injection of the samples. IMS has allowed obtaining cleaner fragmentation spectra, of nearly tandem MS quality, in data-independent acquisition mode. This is much useful in this research area as a second injection, generally applied in LC-QTOF MS workflows to obtain tandem mass spectra, is not necessary, saving time and evading possible compound degradation. As a case study, the smoke produced after combustion of herbal blends used to spray synthetic cannabinoids has been selected as study matrix. The smoke components were trapped in carbon cartridges, desorbed and analyzed by LC-IMS-QTOF MS using different separation mechanisms (reversed phase and HILIC) and acquiring in both positive and negative mode to widen the chemical domain. Partial Least Squares-Discriminant Analysis highlighted several compounds, and ratio between N-Isopropyl-3-(isoquinolinyl)-2-propen-1-amine and quinoline allowed differentiating between tobacco and herbal products. These two compounds were tentatively identified using the cleaner fragmentation spectra from a single injection in the IMS-QTOF MS, with additional confidence obtained by retention time (Rt) and collisional cross section (CCS) prediction using artificial neural networks. Data from this work show that LC-IMS-QTOF is an efficient technique in untargeted metabolomics, avoiding re-injection of the samples for elucidation purposes. In addition, the prediction models for Rt and CCS resulted of help in the elucidation process of potential biomarkers.

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.

Application of Predicted Collisional Cross Section to Metabolome Databases to Probabilistically Describe the Current and Future Ion Mobility Mass Spectrometry

Metabolomics is a powerful phenotyping platform with potential for high-throughput analyses. The primary technology for metabolite profiling is mass spectrometry. In recent years, the coupling of mass spectrometry with ion mobility spectrometry (IMS) has offered the promise of faster analysis time and greater resolving power. Our understanding of the potential impact of IMS on the field of metabolomics is limited by availability of comprehensive experimental data. In this analysis, we use a probabilistic approach to enumerate the strengths and limitations, the present and future, of this technology. This is accomplished through use of "model" metabolomes, predicted physicochemical properties, and probabilistic descriptions of resolving power. This analysis advances our understanding of the importance of orthogonality in resolving (separation) dimensions, describes the impact of the metabolome composition on resolution demands, and offers a system resolution landscape that may serve to guide practitioners in the coming years.

Identity confirmation of anthocyanins in berries by LC-DAD-IM-QTOFMS

Rugged analytical methods for the screening and identity confirmation of anthocyanins require a dedicated sample preparation, chromatographic setup, and the reliable generation of multiple identification points to confirm identity against the wide range of phenolic compounds typically present in food, beverage, and plant material samples. To this end, combinations of spectroscopic and mass spectrometric detection are frequently employed for this application to provide higher confidence in the absence of authentic standards. In the present work, low‐field drift tube ion mobility (DTIM) separation is evaluated for this task using a LC–DAD–DTIM–QTOFMS method. DTIM‐MS allows accurate determination of collision cross sections (^DTCCS) for all analysed compounds as well as a precise alignment tool for reconciling fragment and precursor ions in data independent acquisition mode. The presented approach thereby allows for an anthocyanin screening method taking true advantage of all dimensions of the analytical platform: relative retention (RPLC), UV/VIS absorption spectrum, accurate mass, ^DTCCS_N2, and confirmed high‐resolution fragment ions. From the analysis of authentic standards and several berry samples primarily from the Vaccinium genus, Level 1 confirmation data for six anthocyanins from the cyanidin family, and Level 2 confirmation for a further 29 anthocyanins confirmed in berry samples is provided. The method and accompanying dataset provided as part of this work provides a means to develop anthocyanin screening methods using the ion mobility dimension as an additional alignment and filtering parameter in data independent analysis acquisition across any LC–IM–MS platform.

Targeted Strategy to Analyze Antiepileptic Drugs in Human Serum by LC-MS/MS and LC-Ion Mobility-MS

Routine small-molecule analysis is challenging owing to the need for high selectivity and/or low limits of quantification. This work reports a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify 14 antiepileptic drugs (AEDs) in human serum. For the optimized LC-MS/MS method described herein, we applied the guidelines outlined in the Clinical and Laboratory Standards Institute (CLSI) LC-MS C62-A document and the U.S. Food and Drug Administration (FDA) Bioanalytical Method Validation Guidance for Industry to evaluate the quality of the assay. In these studies, AED linearity, analyte recovery, matrix effects, precision, and accuracy were assessed. Using liquid chromatography-drift tube ion mobility-mass spectrometry (LC-DTIM-MS), a qualitative method was also used to increase confidence in AED identification using accurate mass and collision cross section (CCS) measurements. The LC-DTIM-MS method was also used to assess the ability of drift tube CCS measurements to aid in the separation and identification of AED structural isomers and other AEDs. These data show that another dimension of information, namely CCS measurements, provides an orthogonal dimension of structural information needed for AED analysis. Multiplexed AED measurements using LC-MS/MS and LC-DTIM-MS have the potential to enable better optimization of dosing owing to the high precision capabilities available in these types of analytical studies. Taken together, these data also show the ability to increase confidence in small-molecule identification and quantification using these analytical technologies.

Probing Gas-Phase-Clustering Thermodynamics with Ion Mobility-Mass Spectrometry: Association Energies of Phenylalanine Ions with Gas-Phase Alcohols

Vapor assisted mobility shift measurements were made with atmospheric pressure drift-tube ion mobility-mass spectrometry (IM-MS) to determine the thermodynamic properties of weakly bound ion-molecule clusters formed from protonated phenylalanine and neutral vapor molecules with hydroxyl functional groups. Relative binding energies and gas-phase association energies of amino acid ions clustered with small organic molecules have been established previously using high-pressure mass spectrometry. However, the issue of volatility largely prohibits the use of high-pressure mass spectrometry for the determination of gas-phase associations of amino acid ions clustered with neutral vapor molecules in many instances. In contrast, ion mobility measurements can be made at atmospheric pressure with volatile vapor additives near and above their boiling points, providing access to clustering equilibria not possible using high-vacuum techniques. In this study, we report the gas-phase association energies, enthalpies, and entropies for a protonated phenylalanine ion clustered with three neutral vapor molecules: 2-propanol, 1-butanol, and 2-pentanol based upon measurements at temperatures ranging from 120 to 180 °C. The gas-phase enthalpy and entropy changes ranged between -4 to -7 kcal/mol and -3 to 6 cal/(mol K), respectively. We found enthalpically favored ion-neutral cluster reactions for phenylalanine with entropic barriers for the formation of phenylalanine-1-butanol and phenylalanine-2-pentanol cluster ions, while phenylalanine-2-propanol cluster ion formation is both enthalpically and (weakly) entropically favorable. Under the measurement conditions examined, phenylalanine-vapor modifier cluster ion formation is clearly observed via shifts in the drift time for the three test vapor molecules. In comparison, negligible shifts in mobility are observed for protonated arginine exposed to the same vapor modifiers.

Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics

The metabolome includes not just known but also unknown metabolites; however, metabolite annotation remains the bottleneck in untargeted metabolomics. Ion mobility - mass spectrometry (IM-MS) has emerged as a promising technology by providing multi-dimensional characterizations of metabolites. Here, we curate an ion mobility CCS atlas, namely AllCCS, and develop an integrated strategy for metabolite annotation using known or unknown chemical structures. The AllCCS atlas covers vast chemical structures with >5000 experimental CCS records and ~12 million calculated CCS values for >1.6 million small molecules. We demonstrate the high accuracy and wide applicability of AllCCS with medium relative errors of 0.5-2% for a broad spectrum of small molecules. AllCCS combined with in silico MS/MS spectra facilitates multi-dimensional match and substantially improves the accuracy and coverage of both known and unknown metabolite annotation from biological samples. Together, AllCCS is a versatile resource that enables confident metabolite annotation, revealing comprehensive chemical and metabolic insights towards biological processes.

Collision Cross Section Conformational Analyses of Bile Acids via Ion Mobility-Mass Spectrometry

Bile acids serve as one of the most important classes of biological molecules in the gastrointestinal system. Due to their structural similarity, bile acids have historically been difficult to accurately annotate in complex biological matrices using mass spectrometry. They often have identical or nominally similar mass-to-charge ratios and similar fragmentation patterns that make identification by mass spectrometry arduous, normally involving chemical derivatization and separation via liquid chromatography. Here, we demonstrate the use of drift tube ion mobility (DTIM) to derive collision cross section (CCS) values in nitrogen drift gas (DTCCSN2) for use as an additional descriptor to facilitate expedited bile acid identification. We also explore trends in DTIM measurements and detail structural characteristics for differences in DTCCSN2 values between subclasses of bile acid molecules.