Differential mobility spectrometry/mass spectrometry history, theory, design optimization, simulations, and applications

Using differential mobility spectrometry to improve the specificity of targeted measurements of 2,3-dinor 11β-Prostaglandin F2α

INTRODUCTION

2,3-dinor 11β-Prostaglandin F2α (BPG) is an arachidonic acid derivative and the most abundant metabolic byproduct of prostaglandin D2, which is released during mast cell activation. Therefore, measurements of BPG in urine using liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a noninvasive method for evaluation and management of mast cell disorders. Measurements obtained by LC-MS/MS exhibit a high prevalence of chromatographic interferences resulting in challenges with optimal determination of BGP. In this investigation, differential mobility spectrometry (DMS) is utilized to overcome the limitations of current testing.

METHODS

Urine samples were extracted using an automated solid-phase extraction method. Samples were then analyzed with and without DMS devices installed on two commercially available mass spectrometry platforms to assess the benefits of DMS. Following promising results from a preliminary analytical evaluation, LC-DMS-MS/MS measurements of BPG in urine were fully validated to assess the analytical implications of using this technology.

RESULTS AND DISCUSSION

The addition of DMS devices to the LC-MS/MS systems evaluated in this investigation significantly reduced interferences observed in the chromatograms. Concomitantly, DMS reduced the number of discordant quantifier/qualifier fragment ion results that significantly exceeded the ± 20 % limits, suggesting greater analytical specificity. The validation studies yielded low interday imprecision, with %CVs less than 6.5 % across 20 replicate measurements. Validation studies assessing other aspects of analytical performance also met acceptance criteria.

CONCLUSIONS

Incorporating DMS devices greatly improved the specificity of BPG measurements by LC-MS/MS, as evidenced by the comparison of chromatograms and fragment ion results. Validation studies showed exceptional performance for established analytical metrics, indicating that this technology can be used to minimize the impact of interferences without adversely impacting other aspects of analytical or clinical performance.

Comparison of high-resolution mass spectrometry acquisition methods for the simultaneous quantification and identification of per- and polyfluoroalkyl substances (PFAS)

Simultaneous identification and quantification of per- and polyfluoroalkyl substances (PFAS) were evaluated for three quadrupole time-of-flight mass spectrometry (QTOF) acquisition methods. The acquisition methods investigated were MS-Only, all ion fragmentation (All-Ions), and automated tandem mass spectrometry (Auto-MS/MS). Target analytes were the 25 PFAS of US EPA Method 533 and the acquisition methods were evaluated by analyte response, limit of quantification (LOQ), accuracy, precision, and target-suspect screening identification limit (IL). PFAS LOQs were consistent across acquisition methods, with individual PFAS LOQs within an order of magnitude. The mean and range for MS-Only, All-Ions, and Auto-MS/MS are 1.3 (0.34-5.1), 2.1 (0.49-5.1), and 1.5 (0.20-5.1) pg on column. For fast data processing and tentative identification with lower confidence, MS-Only is recommended; however, this can lead to false-positives. Where high-confidence identification, structural characterisation, and quantification are desired, Auto-MS/MS is recommended; however, cycle time should be considered where many compounds are anticipated to be present. For comprehensive screening workflows and sample archiving, All-Ions is recommended, facilitating both quantification and retrospective analysis. This study validated HRMS acquisition approaches for quantification (based upon precursor data) and exploration of identification workflows for a range of PFAS compounds.

Integrating Post-Ionization Separation via Differential Mobility Spectrometry into Direct Analysis in Real Time Mass Spectrometry for Toy Safety Screening

Direct analysis in real time (DART) enables direct desorption and ionization of analytes, bypassing the time-consuming chromatographic separation traditionally required for mass spectrometry (MS) analysis. However, DART-MS suffers from matrix interference of complex samples, resulting in compromised detection sensitivity and quantitation accuracy. In this study, DART-MS was combined with differential mobility spectrometry (DMS) to provide an additional dimension of post-ionization ion mobility separation within a millisecond time scale, compensating for the lack of separation in DART-MS analysis. As proof-of-concept, primary aromatic amines (PAAs), a class of potentially hazardous chemicals, were analyzed in various toy products, including bubble solutions, finger paints, and plush toys. In addition to commercial Dip-it glass rod and metal mesh sampling tools, a customized rapid extractive evaporation device was designed for the accelerated extraction and sensitive analysis of solid toy samples. The incorporation of DMS in DART-MS analysis enabled the rapid separation and differentiation of isomeric analytes, leading to improved accuracy and reliability. The developed protocols were optimized and validated, achieving good linearity with correlation coefficients greater than 0.99 and acceptable repeatability with relative standard deviations less than 10%. Moreover, satisfactory sensitivity was realized with limits of detection and quantitation ranges of 0.2-5 and 1-20 μg/kg (μg/L) for the 11 PAA analytes. The established methodology was applied for the analysis of real toy samples (n = 18), which confirmed its appealing potential for toy safety screening and consumer health protection.

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.

Detection of Triacetone Triperoxide by High Kinetic Energy Ion Mobility Spectrometry

High Kinetic Energy Ion Mobility Spectrometry (HiKE-IMS) is a versatile technique for the detection of gaseous target molecules that is particularly useful in complex chemical environments, while the instrumental effort is low. Operating HiKE-IMS at reduced pressures from 10 to 60 mbar results in fewer ion-neutral collisions than at ambient pressure, reducing chemical cross-sensitivities and eliminating the need for a preceding separation dimension, e.g., by gas chromatography. In addition, HiKE-IMS allows operation over a wide range of reduced electric field strengths E/N up to 120 Td, allowing separation of ions by low-field ion mobility and exploiting the field dependence of ion mobility, potentially allowing separation of ion species at high E/N despite similar low-field ion mobilities. Given these advantages, HiKE-IMS can be a useful tool for trace gas analysis such as triacetone triperoxide (TATP) detection. In this study, we employed HiKE-IMS to detect TATP. We explore the ionization of TATP and the field-dependent ion mobilities, providing a database of the ion mobilities depending on E/N. Confirming the literature results, ionization of TATP by proton transfer with H3O+ in HiKE-IMS generates fragments, but using NH4+ as the primary reactant ion leads to the TATP·NH4+ adduct. This adduct fragments at high E/N, which could provide additional information for reliable detection of TATP. Thus, operating HiKE-IMS at variable E/N in the drift region generates a unique fingerprint of TATP made of all ion species related to TATP and their ion mobilities depending on E/N, potentially reducing the rate of false positives.

Vacuum differential mobility spectrometry combined with column-switching liquid chromatography- mass spectrometry for the analysis of pyrrolizidine alkaloids in tea samples

The benefit of combining liquid chromatography (LC), supercritical fluid chromatography (SFC) and vacuum Differential Mobility Spectrometry - Mass Spectrometry (vDMS-MS) was investigated for the analysis of fourteen diastereomeric pyrrolizidine alkaloids (PA); intermedine, echinatine, lycopsamine, indicine, intermedine-N-oxide, echinatine-N-oxide, indicine-N-oxide, lycopsamine-N-oxide, senecivernine, senecionine, jacobine, senecivernine-N-oxide, senecionine-N-oxide, retrorsine. The mobile phase composition (15-100% MeOH and ACN), flow rate (8-100 µL/min), vDMS cell pressure, and F value showed an effect on the mobility behavior of the analytes. At 15% MeOH with a flow rate of 100 µL/min and 33 mbar vDMS pressure, 8 out 14 PA could be partially or totally separated by vDMS-MS. As well as providing an additional separation dimension vDMS improved the selectivity and a 5-minute assay method was developed for the quantification of 10 out of 14 single diastereomeric PA in tea samples, using a short LC column-switching and hyphenated to vDMS-MS in the selected ion monitoring mode. The performance of the method was found to be comparable with a 12-minute standard LC-MS/MS method using detection in the selected reaction monitoring mode. Additionally, the combination of vDMS and SFC-MS was investigated and suggests that the mixture of CO2/MeOH influences the CV shifting of the PA to more negative compensation voltage, and the signal-to-noise ratio is improved by a factor of three compared to SFC-MS without vDMS.

Bridging the Gap between Differential Mobility, Log S, and Log P Using Machine Learning and SHAP Analysis

Aqueous solubility, log S, and the water-octanol partition coefficient, log P, are physicochemical properties that are used to screen the viability of drug candidates and to estimate mass transport in the environment. In this work, differential mobility spectrometry (DMS) experiments performed in microsolvating environments are used to train machine learning (ML) frameworks that predict the log S and log P of various molecule classes. In lieu of a consistent source of experimentally measured log S and log P values, the OPERA package was used to evaluate the aqueous solubility and hydrophobicity of 333 analytes. With ion mobility/DMS data (e.g., CCS, dispersion curves) as input, we used ML regressors and ensemble stacking to derive relationships with a high degree of explainability, as assessed via SHapley Additive exPlanations (SHAP) analysis. The DMS-based regression models returned scores of R² = 0.67 and RMSE = 1.03 ± 0.10 for log S predictions and R² = 0.67 and RMSE = 1.20 ± 0.10 for log P after 5-fold random cross-validation. SHAP analysis reveals that the regressors strongly weighted gas-phase clustering in log P correlations. The addition of structural descriptors (e.g., # of aromatic carbons) improved log S predictions to yield RMSE = 0.84 ± 0.07 and R² = 0.78. Similarly, log P predictions using the same data resulted in an RMSE of 0.83 ± 0.04 and R² = 0.84. The SHAP analysis of log P models highlights the need for additional experimental parameters describing hydrophobic interactions. These results were achieved with a smaller dataset (333 instances) and minimal structural correlation compared to purely structure-based models, underscoring the value of employing DMS data in predictive models.

MobCal-MPI 2.0: an accurate and parallelized package for calculating field-dependent collision cross sections and ion mobilities

Ion mobility spectrometry (IMS), which can be employed as either a stand-alone instrument or coupled to mass spectrometry, has become an important tool for analytical chemistry. Because of the direct relation between an ion's mobility and its structure, which is intrinsically related to its collision cross section (CCS), IMS techniques can be used in tandem with computational tools to elucidate ion geometric structure. Here, we present MobCal-MPI 2.0, a software package that demonstrates excellent accuracy (RMSE 2.16%) and efficiency in calculating low-field CCSs via the trajectory method (≤30 minutes on 8 cores for ions with ≤70 atoms). MobCal-MPI 2.0 expands on its predecessor by enabling the calculation of high-field mobilities through the implementation of the 2^nd order approximation to two-temperature theory (2TT). By further introducing an empirical correction to account for deviations between 2TT and experiment, MobCal-MPI 2.0 can compute accurate high-field mobilities that exhibit a mean deviation of <4% from experimentally measured values. Moreover, the velocities used to sample ion-neutral collisions were updated from a weighted to a linear grid, enabling the near-instantaneous evaluation of mobility/CCS at any effective temperature from a single set of N₂ scattering trajectories. Several enhancements made to the code are also discussed, including updates to the statistical analysis of collision event sampling and benchmarking of overall performance.

Chemical Transformations Can Occur during DMS Separations: Lessons Learned from Beer's Bittering Compounds

While developing a DMS-based separation method for beer's bittering compounds, we observed that the argentinated forms of humulone tautomers (i.e., [Hum + Ag]⁺) were partially resolvable in a N₂ environment seeded with 1.5 mol % of isopropyl alcohol (IPA). Attempting to improve the separation by introducing resolving gas unexpectedly caused the peaks for the cis-keto and trans-keto tautomers of [Hum + Ag]⁺ to coalesce. To understand why resolution loss occurred, we first confirmed that each of the tautomeric forms (i.e., dienol, cis-keto, and trans-keto) responsible for the three peaks in the [Hum + Ag]⁺ ionogram were assigned to the correct species by employing collision-induced dissociation, UV photodissociation spectroscopy, and hydrogen-deuterium exchange (HDX). The observation of HDX indicated that proton transfer was stimulated by dynamic clustering processes between IPA and [Hum + Ag]⁺ during DMS transit. Because IPA accretion preferentially occurs at Ag⁺, which can form pseudocovalent bonds with a suitable electron donor, solvent clustering also facilitated the formation of exceptionally stable microsolvated ions. The exceptional stability of these microsolvated configurations disproportionately impacted the compensation voltage (CV) required to elute each tautomer when the temperature within the DMS cell was varied. The disparity in CV response caused the peaks for the cis- and trans-keto species to merge when a temperature gradient was induced by the resolving gas. Moreover, simulations showed that microsolvation with IPA mediates dienol to trans-keto tautomerization during DMS transit, which, to the best of our knowledge, is the first observation of keto/enol tautomerization occurring within an ion-mobility device.

Validation of Field-Dependent Ion-Solvent Cluster Modeling via Direct Measurement of Cluster Size Distributions

Ion mobility spectrometry is widely used in analytical chemistry, either as a stand-alone technique or coupled to mass spectrometry. Ions in the gas phase tend to form loosely bound clusters with surrounding solvent vapors, artificially increasing the collisional cross section and the mass of the ion. This, in turn, affects ion mobility and influences separation. Further, ion-solvent clusters play an important role in most ionization mechanisms occurring in the gas phase. Consequently, a deeper understanding of ion-solvent cluster association and dissociation processes is desirable to guide experimental design and interpretation. A few computational models exist, which aim to describe the amount of clustering as a function of the reduced electric field strength, bath gas pressure and temperature, and the chemical species probed. It is especially challenging to model ion mobility under high reduced electrical field strengths due to the nonthermal conditions created by the field. In this work, we aim to validate a recently proposed first-principles model by comparing its predictions with direct measurements of cluster size distributions over a range of 20-120 Td as observed using a High Kinetic Energy Ion Mobility Spectrometer coupled to a mass spectrometer (HiKE-IMS-MS). By studying H⁺(H₂O)_n, [MeOH + H + n(H₂O)]⁺, [ACE + H + n(H₂O)]⁺, and [PhNH₂ + H + n(H₂O)]⁺ as test systems, we find very good agreement between model and experiment, supporting the validity of the computational workflow. Further, the detailed information gained from the modeling yields important insights into the cluster dynamics within the HiKE-IMS, allowing for better interpretation of the measured ion mobility spectra.

First-Principles Modeling of Preferential Solvation in Mixed-Modifier Differential Mobility Spectrometry

Differential mobility spectrometry (DMS) separates ions based on mobility differences between high and low electric field conditions. To enhance resolution, solvents such as water and acetonitrile are often used to modify the collision environment and take advantage of differing dynamic clustering behavior between analytes that coelute in hard-sphere environments (e.g., N₂). When binary solvent mixtures are used to modify the DMS environment, one solvent can have a dominant influence over the other with respect to ion trajectories. For example, for quinoline derivatives, a 9:1 water:acetonitrile solvent mixture exhibited identical behavior to an environment containing only acetonitrile as a modifier. It was hypothesized that this effect arises due to the significantly different binding strengths of the two solvents. Here, we utilize a first-principles model of DMS to study analytes in single and binary solvent mixtures and explore the effects governing the dominance of one solvent over the other. Computed DMS dispersion curves of quinoline derivatives are in excellent agreement with those measured experimentally. For mixed-modifier environments, the predicted cluster populations show a clear preferential solvation of ions with the stronger binding solvent. The influence of ion-solvent binding energies, solvent concentration, and solvent molecule size is discussed in the context of the observed DMS behavior. This work can guide the usage of binary solvent mixtures for improving ion separations in cases where compounds coelute in pure N₂ and in single-solvent modifier environments. Moreover, our results indicate that binary solvent mixtures can be used to create a relative scale for solvent binding energies.

Argentination: A Silver Bullet for Cannabinoid Separation by Differential Mobility Spectrometry

As the legality of cannabis continues to evolve globally, there is a growing demand for methods that can accurately quantitate cannabinoids found in commercial products. However, the isobaric nature of many cannabinoids, along with variations in extraction methods and product formulations, makes cannabinoid quantitation by mass spectrometry (MS) challenging. Here, we demonstrate that differential mobility spectrometry (DMS) and tandem-MS can distinguish a set of seven cannabinoids, five of which are isobaric: Δ⁹-tetrahydrocannabinol (Δ⁹-THC), Δ⁸-THC, exo-THC, cannabidiol, cannabichromene, cannabinol, and cannabigerol. Analytes were detected as argentinated species ([M + Ag]⁺), which, when subjected to collision-induced dissociation, led to the unexpected discovery that argentination promotes distinct fragmentation patterns for each cannabinoid. The unique fragment ions formed were rationalized by discerning fragmentation mechanisms that follow each cannabinoid's MS³ behavior. The differing fragmentation behaviors between species suggest that argentination can distinguish cannabinoids by tandem-MS, although not quantitatively as some cannabinoids produce small amounts of a fragment ion that is isobaric with the major fragment generated by another cannabinoid. By adding DMS to the tandem-MS workflow, it becomes possible to resolve each cannabinoid in a pure N₂ environment by deconvoluting the contribution of each cannabinoid to a specific fragmentation channel. To this end, we used DMS in conjunction with a multiple reaction monitoring workflow to assess cannabinoid levels in two cannabis extracts. Our methodology exhibited excellent accuracy, limits of detection (10-20 ppb depending on the cannabinoid), and linearity during quantitation by standard addition (R² > 0.99).

Investigation of Zero-/High-Field Ion Mobility Orthogonal Separation Using a Hyphenated DMA-FAIMS System and Validation of the Two-Temperature Theory at Arbitrary Field for Tetraalkylammonium Salts in Nitrogen

Toward greater separation techniques for ions, a differential mobility analyzer (DMA) has been coupled with field asymmetric waveform ion mobility spectrometry (FAIMS) to take advantage of two mobility-related but different methods of separation. The filtering effect of the DMA allows ions to be selected individually based on low-field mobility and studied in FAIMS at variable electric field, yielding mobility separations in two dimensions. Because spectra fully describe ion mobility at variable field strength, results are then compared with a two-temperature theory-predicted mobility up to the fourth-order approximation. The comparison yields excellent results up to at least 100 Td, beyond which the theory deviates from experiments. This is attributed to two effects, the enlargement of the structure due to ion heating and the inelasticity of the collisions with the nitrogen bath gas. The corrected mobility can then be used to predict the dispersion plot through a newly developed implicit equation that circumvents the possible issues related to the more elaborate Buryakov equation. Our results simultaneously show that the DMA-FAIMS coupling yields complete information on ion mobility versus the field-strength to gas-density ratio and works toward predicting such spectra from ion structures and gas properties.

Development and application of lipidomics for food research

Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.

CaptiveSpray Differential Ion Mobility Spectrometry Device with Enhanced Ion Transmission and Improved Resolving Power

A performance enhanced CaptiveSpray differential ion mobility device was designed and constructed by incorporating a circular channel and a gas flow homogenizing channel (GFHC) between the CaptiveSpray ion source and planar differential ion mobility spectrometry (DMS). The GFHC was used to reduce gas flow heterogeneity prior to the entrance of the DMS device. The optimal flared entrance greatly reduces gas flow velocity at the inlet region owing to its relatively large gas inlet interface, which assists in reducing disparities between the minimum and maximum gas velocity along the x-axis. The circular electrode was machined with channels along the x- and y-axis for the passage of auxiliary gas and was applied with a potential to focus the incoming ions from the CaptiveSpray source into the DMS channel. Using reserpine as a reference standard, substantial signal enhancement was achieved with a concomitant reduction of the peak width in the ionogram.

Omic-Scale High-Throughput Quantitative LC-MS/MS Approach for Circulatory Lipid Phenotyping in Clinical Research

Lipid analysis at the molecular species level represents a valuable opportunity for clinical applications due to the essential roles that lipids play in metabolic health. However, a comprehensive and high-throughput lipid profiling remains challenging given the lipid structural complexity and exceptional diversity. Herein, we present an 'omic-scale targeted LC-MS/MS approach for the straightforward and high-throughput quantification of a broad panel of complex lipid species across 26 lipid (sub)classes. The workflow involves an automated single-step extraction with 2-propanol, followed by lipid analysis using hydrophilic interaction liquid chromatography in a dual-column setup coupled to tandem mass spectrometry with data acquisition in the timed-selective reaction monitoring mode (12 min total run time). The analysis pipeline consists of an initial screen of 1903 lipid species, followed by high-throughput quantification of robustly detected species. Lipid quantification is achieved by a single-point calibration with 75 isotopically labeled standards representative of different lipid classes, covering lipid species with diverse acyl/alkyl chain lengths and unsaturation degrees. When applied to human plasma, 795 lipid species were measured with median intra- and inter-day precisions of 8.5 and 10.9%, respectively, evaluated within a single and across multiple batches. The concentration ranges measured in NIST plasma were in accordance with the consensus intervals determined in previous ring-trials. Finally, to benchmark our workflow, we characterized NIST plasma materials with different clinical and ethnic backgrounds and analyzed a sub-set of sera (n = 81) from a clinically healthy elderly population. Our quantitative lipidomic platform allowed for a clear distinction between different NIST materials and revealed the sex-specificity of the serum lipidome, highlighting numerous statistically significant sex differences.

Autoxidation Kinetics of Tetrahydrobiopterin-Giving Quinonoid Dihydrobiopterin the Consideration It Deserves

In humans, tetrahydrobiopterin (H4Bip) is the cofactor of several essential hydroxylation reactions which dysfunction cause very serious diseases at any age. Hence, the determination of pterins in biological media is of outmost importance in the diagnosis and monitoring of H4Bip deficiency. More than half a century after the discovery of the physiological role of H4Bip and the recent advent of gene therapy for dopamine and serotonin disorders linked to H4Bip deficiency, the quantification of quinonoid dihydrobiopterin (qH2Bip), the transient intermediate of H4Bip, has not been considered yet. This is mainly due to its short half-life, which goes from 0.9 to 5 min according to previous studies. Based on our recent disclosure of the specific MS/MS transition of qH2Bip, here, we developed an efficient HPLC-MS/MS method to achieve the separation of qH2Bip from H4Bip and other oxidation products in less than 3.5 min. The application of this method to the investigation of H4Bip autoxidation kinetics clearly shows that qH2Bip's half-life is much longer than previously reported, and mostly longer than that of H4Bip, irrespective of the considered experimental conditions. These findings definitely confirm that an accurate method of H4Bip analysis should include the quantification of qH2Bip.

Kinetics in DMS: Modeling Clustering and Declustering Reactions

Differential mobility spectrometry (DMS) uses high-frequency oscillating electrical fields to harness the differential mobility of ions for separating complex sample mixtures prior to detection. To increase the resolving power, a dynamic microsolvation environment is often created by introducing solvent vapors. Here, relatively large clusters are formed at low-field conditions which then evaporate to form smaller clusters at high-field conditions. The kinetics of these processes as the electrical field strength oscillates are not well studied. Here, we develop a computational framework to investigate how the different reactions (cluster association, cluster dissociation, and fast conformational changes) behave at different field strengths. We aim to better understand these processes, their effect on experimental outcomes, and whether DMS model accuracy is improved via incorporating their description. We find that cluster association and dissociation reactions for typical ion-solvent pairs are fast compared to the time scale of the varying separation fields usually used. However, low solvent concentration, small dipole moments, and strong ion-solvent binding can result in reaction rates small enough that a lag is observed in the ion's DMS response. This can yield differences of several volts in the compensation voltages required to correct ion trajectories for optimal transmission. We also find that the proposed kinetic approach yields generally better agreement with experiment than using a modified Boltzmann weighting scheme. Thus, this work provides insights into the chemical dynamics occurring within the DMS cell while also increasing the accuracy of dispersion plot predictions.

Food metabolomics: Latest hardware-developments for nontargeted food authenticity and food safety testing

The analytical requirements for food testing have increased significantly in recent years. On the one hand, because food fraud is becoming an ever-greater challenge worldwide, and on the other hand because food safety is often difficult to monitor due to the far-reaching trade chains. In addition, the expectations of consumers on the quality of food have increased, and they are demanding extensive information. Cutting-edge analytical methods are required to meet these demands. In this context, non-targeted metabolomics strategies using mass and nuclear magnetic resonance spectrometers (mass spectrometry [MS]) have proven to be very suitable. MS-based approaches are of particular importance as they provide a comparatively high analytical coverage of the metabolome. Accordingly, the efficiency to address even challenging issues is high. A variety of hardware developments, which are explained in this review, have contributed to these advances. In addition, the potential of future developments is highlighted, some of which are currently not yet commercially available or only used to a comparatively small extent but are expected to gain in importance in the coming years.

Multianalytical Approach for Deciphering the Specific MS/MS Transition and Overcoming the Challenge of the Separation of a Transient Intermediate, Quinonoid Dihydrobiopterin

Despite recent technological developments in analytical chemistry, separation and direct characterization of transient intermediates remain an analytical challenge. Among these, separation and direct characterization of quinonoid dihydrobiopterin (qH2Bip), a transient intermediate of tetrahydrobiopterin (H4Bip)-dependent hydroxylation reactions, essential in living organisms, with important and varied human pathophysiological impacts, are a clear illustration. H4Bip regeneration may be impaired by competitive nonenzymatic autoxidation reactions, such as isomerization of qH2Bip into a more stable 7,8-H2Bip (H2Bip) isomer, and subsequent nonenzymatic oxidation reactions. The quinonoid qH2Bip intermediate thus plays a key role in H4Bip-dependent hydroxylation reactions. However, only a few experimental results have indirectly confirmed this finding while revealing the difficulty of isolating qH2Bip from H4Bip-containing solutions. As a result, no current H4Bip assay method allows this isomer to be quantified even by liquid chromatography-tandem mass spectrometry (MS/MS). Here, we report isolation, structural characterization, and abundance of qH2Bip formed upon H4Bip autoxidation using three methods integrated into MS/MS. First, we characterized the structure of the two observed H2B isomers using IR photodissociation spectroscopy in conjunction with quantum chemical calculations. Then, we used differential ion mobility spectrometry to fully separate all oxidized forms of H4Bip including qH2Bip. These data are consistent and show that qH2Bip can also be unambiguously identified thanks to its specific MS/MS transition. This finding paves the way for the quantification of qH2Bip with MS/MS methods. Most importantly, the half-life value of this intermediate is nearly equivalent to that of H4Bip (tens of minutes), suggesting that an accurate method of H4Bip analysis should include the quantification of qH2Bip.

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.

The hitchhiker's guide to dynamic ion-solvent clustering: applications in differential ion mobility spectrometry

This article highlights the fundamentals of ion-solvent clustering processes that are pertinent to understanding an ion's behaviour during differential mobility spectrometry (DMS) experiments. We contrast DMS with static-field ion mobility, where separation is affected by mobility differences under the high-field and low-field conditions of an asymmetric oscillating electric field. Although commonly used in mass spectrometric (MS) workflows to enhance signal-to-noise ratios and remove isobaric contaminants, the chemistry and physics that underpins the phenomenon of differential mobility has yet to be fully fleshed out. Moreover, we are just now making progress towards understanding how the DMS separation waveform creates a dynamic clustering environment when the carrier gas is seeded with the vapour of a volatile solvent molecule (e.g., methanol). Interestingly, one can correlate the dynamic clustering behaviour observed in DMS experiments with gas-phase and solution-phase molecular properties such as hydrophobicity, acidity, and solubility. However, to create a generalized, global model for property determination using DMS data one must employ machine learning. In this article, we provide a first-principles description of differential ion mobility in a dynamic clustering environment. We then discuss the correlation between dynamic clustering propensity and analyte physicochemical properties and demonstrate that analytes exhibiting similar ion-solvent interactions (e.g., charge-dipole) follow well-defined trends with respect to DMS clustering behaviour. Finally, we describe how supervised machine learning can be used to create predictive models of molecular properties using DMS data. We additionally highlight open questions in the field and provide our perspective on future directions that can be explored.

Effects of the LC mobile phase in vacuum differential mobility spectrometry-mass spectrometry for the selective analysis of antidepressant drugs in human plasma

The effect of LC mobile phase composition and flow rate (2–50 µL/min) on mobility behavior in vacuum differential mobility spectrometry (vDMS) was investigated for electrosprayed isobaric antidepressant drugs (AD); amitriptyline, maprotiline, venlafaxine; and structurally related antidepressants nortriptyline, imipramine, and desipramine. While at 2 µL/min, no difference in compensation voltage was observed with methanol and acetonitrile, at 50 µL/min, acetonitrile used for LC elution of analytes enabled the selectivity of the mobility separation to be improved. An accurate and sensitive method could be developed for the quantification of six AD drugs in human plasma using trap/elute micro-LC setup hyphenated to vDMS with mass spectrometric detection in the selected ion monitoring mode. The assay was found to be linear over three orders of magnitude, and the limit of quantification was of 25 ng/mL for all analytes. The LC-vDMS-SIM/MS method was compared to a LC-MRM/MS method, and in both cases, inter-assay precisions were lower than 12.5 and accuracies were in the range 91.5–110%, but with a four times reduced analysis time (2 min) for the LC-vDMS-SIM/MS method. This work illustrates that with vDMS, the LC mobile phase composition can be used to tune the ion mobility separation and to improve assay selectivity without additional hardware.

Current Role of Mass Spectrometry in the Determination of Pesticide Residues in Food

The extensive use of pesticides represents a risk to human health. Consequently, legal frameworks have been established to ensure food safety, including control programs for pesticide residues. In this context, the performance of analytical methods acquires special relevance. Such methods are expected to be able to determine the largest number of compounds at trace concentration levels in complex food matrices, which represents a great analytical challenge. Technical advances in mass spectrometry (MS) have led to the development of more efficient analytical methods for the determination of pesticides. This review provides an overview of current analytical strategies applied in pesticide analysis, with a special focus on MS methods. Current targeted MS methods allow the simultaneous determination of hundreds of pesticides, whereas non-targeted MS methods are now applicable to the identification of pesticide metabolites and transformation products. New trends in pesticide analysis are also presented, including approaches for the simultaneous determination of pesticide residues and other food contaminants (i.e., mega-methods), or the recent application of techniques such as ion mobility–mass spectrometry (IM–MS) for this purpose.

Sensoproteomic Discovery of Taste-Modulating Peptides and Taste Re-engineering of Soy Sauce

Soy sauce, one of the most common Asian fermented foods, exhibits a distinctive savory taste profile. In the present study, targeted quantitation of literature-known taste compounds, calculation of dose-over-threshold factors, and taste re-engineering experiments enabled the identification of 34 key tastants. Following the sensoproteomics approach, 14 umami-, kokumi-, and salt-enhancing peptides were identified for the first time, with intrinsic taste threshold concentrations in the range of 166-939 μmol/L and taste-modulating threshold concentrations ranging from 42 to 420 μmol/L. The lowest taste-modulating threshold concentrations were found for the leucyl peptide LDYY with an umami- and salt-enhancing threshold of 42 μmol/L. Addition of the 14 newly identified peptides to the taste recombinate (aRec_Dipeptides) increased the overall taste intensity and mouthfulness of the recombinate, and comparison with the authentic soy sauce confirmed the identification of all key tastants. Finally, these data as well as the quantitative profiling of several (non)-fermented foods highlight the importance of fermentation with respect to taste formation. On the basis of this knowledge, microorganisms with specific digestion patterns may be used to tailor the taste profile and especially the salt taste sensation of soy sauces.

Method for the Intraoperative Detection of IDH Mutation in Gliomas with Differential Mobility Spectrometry

Isocitrate dehydrogenase (IDH) mutation status is an important factor for surgical decision-making: patients with IDH-mutated tumors are more likely to have a good long-term prognosis, and thus favor aggressive resection with more survival benefit to gain. Patients with IDH wild-type tumors have generally poorer prognosis and, therefore, conservative resection to avoid neurological deficit is favored. Current histopathological analysis with frozen sections is unable to identify IDH mutation status intraoperatively, and more advanced methods are therefore needed. We examined a novel method suitable for intraoperative IDH mutation identification that is based on the differential mobility spectrometry (DMS) analysis of the tumor. We prospectively obtained tumor samples from 22 patients, including 11 IDH-mutated and 11 IDH wild-type tumors. The tumors were cut in 88 smaller specimens that were analyzed with DMS. With a linear discriminant analysis (LDA) algorithm, the DMS was able to classify tumor samples with 86% classification accuracy, 86% sensitivity, and 85% specificity. Our results show that DMS is able to differentiate IDH-mutated and IDH wild-type tumors with good accuracy in a setting suitable for intraoperative use, which makes it a promising novel solution for neurosurgical practice.

Improved Thyreostatic Drug Detection in Animal Tissues Using Liquid Chromatography-High-Field Asymmetric Waveform Ion Mobility Spectrometry-Mass Spectrometry

Thyreostatic drugs (thyreostats) interfere with thyroid function and have been used illegally in animals slaughtered for food. Thyreostat use leads to poorer quality meat, and the drug residues can cause adverse effects in humans. These drugs, with the exception of thiouracil, do not occur naturally and require sensitive methodologies for their detection in animal tissues. Because thyreostats are low-molecular-weight polar analytes, liquid chromatography-mass spectrometry (LC-MS) is typically used for detection and, in particular, triple quadrupole mass spectrometry with selective reaction monitoring (i.e., LC-SRM). However, LC-SRM thyreostat methods suffer from chemical background noise and endogenous interferences arising from the complex tissue matrix. An improved high-field asymmetric waveform ion mobility spectrometry interface (FAIMS Pro), which separates ions based on differential ion mobility, was combined with LC-SRM to minimize these interferences. Using the same samples and conditions, LC-FAIMS-SRM showed improvements in the signal-to-noise ratio (S/N) of up to 50 times compared with our validated LC-SRM method. In addition, wider linear ranges, including substantial improvements in the lower limit of quantification (approximately an order of magnitude for tapazole and methylthiouracil), were observed with LC-FAIMS-SRM.

Microflow Liquid Chromatography Coupled to Mass Spectrometry (μLC-MS) Workflow for O-Glycopeptides Isomers Analysis Combining Differential Mobility Spectrometry and Collision Induced and Electron Capture Dissociation

Peptide and protein O-glycosylation can occur mostly on any serine or threonine and could generate several positional isomers, which may coelute during liquid chromatography (LC) separation, challenging their characterization. Ion mobility has emerged as a technique of interest to separate isomeric compounds. In the different ion mobility techniques, differential ion mobility (DMS) includes the particular interest to tune ion separation by the possible addition of an organic modifier. Different microflow liquid chromatography coupled to mass spectrometry (μLC-MS) workflows were investigated for the analysis of a set of four model peptides made of three isomeric glycopeptides and a corresponding nonglycosylated peptide using differential mobility spectrometry (DMS), collision induced dissociation (CID), and electron capture dissociation (ECD). Neither DMS nor LC provided sufficient separation of the three isomeric O-glycopeptides while the nonmodified one was clearly separated by LC. The hyphenation of LC with DMS led to differentiating the three glycopeptides, and further detection and characterization (ECD/CID) with a chimeric collision cell were achieved in a single LC run. The position of the modification was determined from ECD data, while CID data characterized the sugar through its distinctive oxoniums ions in the low mass range.

Evaluation of Ion Mobility Spectrometry for Improving Constitutional Assignment in Natural Product Mixtures

The comprehensive chemical characterization of biological samples remains a central challenge in the field of natural products. Conventional workflows using liquid chromatography (LC)-coupled high-resolution tandem mass spectrometry (MS/MS or MS2) allow the detection of relevant small molecules while providing diagnostic fragment ions for their structural assignment. Still, many natural product extracts are of a molecular complexity that challenges the resolving power of modern LC-MS2 pipelines. In this study, we examined the effect of integrating ion mobility spectrometry (IMS) to our LC-MS2 platform for the characterization of natural product mixtures. IMS provides an additional axis of separation in the gas phase as well as experimental collision cross-sectional (CCS) values. We analyzed a mixture of 20 commercial standards at 2 concentration ranges, either solubilized in solvent or spiked into an actinobacterial extract. Data were acquired in positive ion mode using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) MS2 fragmentation approaches and assessed for both chemical coverage and spectral quality. IMS-DIA identified the largest number of standards in the spiked extract at the lower concentration of standards (17), followed by IMS-DDA (10), DDA (8), and DIA (6). In addition, we examined how these data sets performed in the Global Natural Products Social Molecular Networking (GNPS) platform. Overall, integrating IMS increased both metabolite detection and the quality of MS2 spectra, particularly for samples analyzed in DIA mode.

Improved First-Principles Model of Differential Mobility Using Higher Order Two-Temperature Theory

Differential mobility spectrometry is a separation technique that may be applied to a variety of analytes ranging from small molecule drugs to peptides and proteins. Although rudimentary theoretical models of differential mobility exist, these models are often only applied to small molecules and atomic ions without considering the effects of dynamic microsolvation. Here, we advance our theoretical description of differential ion mobility in pure N₂ and microsolvating environments by incorporating higher order corrections to two-temperature theory (2TT) and a pseudoequilibrium approach to describe ion-neutral interactions. When comparing theoretical predictions to experimentally measured dispersion plots of over 300 different compounds, we find that higher order corrections to 2TT reduce errors by roughly a factor of 2 when compared to first order. Model predictions are accurate especially for pure N₂ environments (mean absolute error of 4 V at SV = 4000 V). For strongly clustering environments, accurate thermochemical corrections for ion-solvent clustering are likely required to reliably predict differential ion mobility behavior. Within our model, general trends associated with clustering strength, solvent vapor concentration, and background gas temperature are well reproduced, and fine structure visible in some dispersion plots is captured. These results provide insight into the dynamic ion-solvent clustering process that underpins the phenomenon of differential ion mobility.

Recent advances in metabolomics analysis for early drug development

The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quantitative biochemical technology. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics analysis assists in the definition of the physiological response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

A novel, differential mobility spectrometry tandem mass spectrometric method for the in vivo quantitation of ursolic acid

Ursolic acid (UA) is a naturally occurring pentacyclic triterpene widely distributed in fruits and plants. It is pharmacologically active and has the potential to be a useful therapeutic compound. To date, bioanalysis of UA has been limited by biomatrix interference and poor collision induced dissociation (CID) efficiency in tandem mass spectrometry. In this study, we developed a method based on liquid chromatography differential mobility spectrometry tandem mass spectrometry LC-DMS-MS/MS with multiple ion monitoring (MIM) for quantitation of UA in rat plasma. The method involves efficient sample preparation by solid phase extraction and requires only a limited volume of plasma (40 μL) to achieve linearity in the 1-100 ng/mL range with good accuracy and precision. The method was successfully applied to a pharmacokinetic study of orally administered UA in rat. The results indicate that LC-DMS-MS/MS with MIM is a useful strategy for the bioassay of UA suitable for high throughput analysis.

Recognition of Cis-Trans and Chiral Proline and Its Derivatives by Ion Mobility Measurement of Their Complexes with Natamycin and Metal Ion

Discrimination of isomers is an important and valuable feature in many analytical applications, and the identification of chiral isomers and cis-trans isomers is the current research focus. In this work, a simple method for direct, simultaneous recognition of d-/l-proline (P), d-/l-/cis-/trans-4-hydroxyproline (4-HP), and d-/l-/cis-/trans-N-tert-butoxycarbony (N-Boc-4-HP) was investigated by means of trapped ion mobility spectrometry-mass spectrometry (TIMS-MS). The isomers with cis-/trans-/d-/l-configuration can be directly recognized based on their mobility upon reaction with natamycin (Nat) and metal ions through noncovalent interactions. The results indicate that the recognition of the enantiomers has certain specificity, and the structural difference of the enantiomers was increased in a complex with Nat and metal ions. Herein, d-/l-P can be recognized through the ternary complexes [P + Nat + Mg - H]⁺, [P + 2Nat + Ca - H]⁺, [P + 2Nat + Mn - H]⁺, and [P + Nat + Cu - H]⁺. Similarly, c-4-HP_L, c-4-HP_D, t-4-HP_L, and t-4-HP_D can be recognized by [4-HP + Nat + Ca - H]⁺, [4-HP + 2Nat + Ca - H]⁺, and [4-HP + Nat + Cu - H]⁺, while N-Boc-c-4-HP_L, N-Boc-c-4-HP_D, N-Boc-t-4-HP_L, and N-Boc-t-4-HP_D were recognized through the enantiomer complexes [N-Boc-4-HP + Nat + Li]⁺, [N-Boc-4-HP + Nat + 2Na - H]⁺, [N-Boc-4-HP + Nat + K]⁺, [N-Boc-4-HP + Nat + Mn - H]⁺, and [N-Boc-4-HP + Nat + Ba - H]⁺. Moreover, tandem mass spectrometry (MS/MS) results indicated that different collision energies were obtained for the same fragment ions, which implied that the enantiomer complexes that contributed to their mobility separation shared identical interaction mode but had different gas-phase rigid geometries. Furthermore, the relative quantification for the enantiomers was performed, and the results were supported by a satisfactory coefficient (R² > 0.99). The developed method can provide a promising and powerful strategy for the separation of chiral proline and its d-/l-/cis-/trans derivatives, bearing the advantages of higher speed, better accuracy, high selectivity, and no need for chemical derivatization and chromatographic separation.

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.

Detection and Identification of VOCs Using Differential Ion Mobility Spectrometry (DMS)

The article presents a technique of differential ion mobility spectrometry (DMS) applicable to the detection and identification of volatile organic compounds (VOCs) from such categories as n-alkanes, alcohols, acetate esters, ketones, botulinum toxin, BTX, and fluoro- and chloro-organic compounds. A possibility of mixture identification using only the DMS spectrometer is analyzed, and several examples are published for the first time. An analysis of different compounds and their mechanisms of fragmentation, influence on effective ion temperature, and high electric field intensity is discussed.

Protonation-Induced Chirality Drives Separation by Differential Ion Mobility Spectrometry

Upon development of a workflow to analyze (±)-Verapamil and its metabolites using differential mobility spectrometry (DMS), we noticed that the ionogram of protonated Verapamil consisted of two peaks. This was inconsistent with its metabolites, as each exhibited only a single peak in the respective ionograms. The unique behaviour of Verapamil was attributed to protonation at its tertiary amino moiety, which generated a stereogenic quaternary amine. The introduction of additional chirality upon N-protonation of Verapamil renders four possible stereochemical configurations for the protonated ion: ( R,R ), ( S,S ), ( R,S ), or ( S,R ). The ( R,R )/( S,S ) and ( R,S )/( S,R ) enantiomeric pairs are diastereomeric and thus exhibit unique conformations that are resolvable by linear and differential ion mobility techniques.  Protonation-induced chirality appears to be a general phenomenon, as N -protonation of 12 additional chiral amines generated diastereomers that were readily resolved by DMS.

UVPD Spectroscopy of Differential Mobility-Selected Prototropic Isomers of Rivaroxaban

Two ion populations of protonated Rivaroxaban, [C₁₉H₁₈ClN₃O₅S + H]⁺, are separated under pure N₂ conditions using differential mobility spectrometry prior to characterization in a hybrid triple quadrupole linear ion trap mass spectrometer. These populations are attributed to bare protonated Rivaroxaban and to a proton-bound Rivaroxaban-ammonia complex, which dissociates prior to mass-selecting the parent ion. Ultraviolet photodissociation (UVPD) and collision-induced dissociation (CID) studies indicate that both protonated Rivaroxaban ion populations are comprised of the computed global minimum prototropic isomer. Two ion populations are also observed when the collision environment is modified with 1.5% (v/v) acetonitrile. In this case, the protonated Rivaroxaban ion populations are produced by the dissociation of the ammonium complex and by the dissociation of a proton-bound Rivaroxaban-acetonitrile complex prior to mass selection. Again, both populations exhibit a similar CID behavior; however, UVPD spectra indicate that the two ion populations are associated with different prototropic isomers. The experimentally acquired spectra are compared with computed spectra and are assigned to two prototropic isomers that exhibit proton sharing between distal oxygen centers.

Electrospray Ionization Ion Mobility Mass Spectrometry

Electrospray ionization ion mobility mass spectrometry (ESI-IMS-MS) is a rapidly progressing analytical technique for the examination of complex compounds in the gas phase. ESI-IMS-MS separates isomers, provides structural information, and quantitatively identifies peptides, lipids, carbohydrates, polymers, and metabolites in biological samples. ESI-IMS-MS has pharmaceutical, environmental, and manufacturing applications quickly characterizing drugs, petroleum products, and metal macromolecules. This review provides the history of ESI-IMS-MS development and applications to date.

Non-Targeted Screening Approaches for Profiling of Volatile Organic Compounds Based on Gas Chromatography-Ion Mobility Spectroscopy (GC-IMS) and Machine Learning

Due to its high sensitivity and resolving power, gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful technique for the separation and sensitive detection of volatile organic compounds. It is a robust and easy-to-handle technique, which has recently gained attention for non-targeted screening (NTS) approaches. In this article, the general working principles of GC-IMS are presented. Next, the workflow for NTS using GC-IMS is described, including data acquisition, data processing and model building, model interpretation and complementary data analysis. A detailed overview of recent studies for NTS using GC-IMS is included, including several examples which have demonstrated GC-IMS to be an effective technique for various classification and quantification tasks. Lastly, a comparison of targeted and non-targeted strategies using GC-IMS are provided, highlighting the potential of GC-IMS in combination with NTS.

Mass spectrometry based high-throughput bioanalysis of low molecular weight compounds: are we ready to support personalized medicine?

Liquid chromatography coupled to mass spectrometry (LC-MS) is the gold standard in bioanalysis for the development of quantitative assays to support drug development or therapeutic drug monitoring. High-throughput and low-cost gene sequencing have enabled a paradigm shift from one treatment fits all to personalized medicine (PM). However, gene monitoring provides only partial information about the health state. The full picture requires the combination of gene monitoring with the screening of exogenous compounds, metabolites, lipids, and proteins. This critical review discusses how mass spectrometry–based technologies and approaches including separation sciences, ambient ionization, and ion mobility are/could be used to support high-throughput bioanalysis of endogenous end exogenous low molecular weight compounds. It includes also various biological sample types (from blood to expired air), and various sample preparation techniques.

Quantification and Bitter Taste Contribution of Lipids and Their Oxidation Products in Pea-Protein Isolates (Pisum sativum L.)

An ultra-high-performance liquid chromatography-differential ion mobility (DMS)-tandem mass spectrometry method was developed to quantify 14 bitter-tasting lipids in 17 commercial pea-protein isolates (Pisum sativum L.). The DMS technology enabled the simultaneous quantification of four hydroxyoctadecadienoic acid isomers, namely, (10E,12Z)-9-hydroxyoctadeca-10,12-dienoic acid (5), (10E,12E)-9-hydroxyoctadeca-10,12-dienoic acid (6), (9Z,11E)-13-hydroxyoctadeca-9,11-dienoic acid (7), and (9E,11E)-13-hydroxyoctadeca-9,11-dienoic acid (8). Based on quantitative data and human bitter taste recognition thresholds, dose-over-threshold factors were determined to evaluate the individual lipids' bitter impact and compound classes. The free fatty acids α-linolenic acid (10) and linoleic acid (13), as well as the trihydroxyoctadecenoic acids, especially 9,10,11-trihydroxyoctadec-12-enoic (3), and 11,12,13-trihydroxyoctadec-9-enoic acids (4), were shown to be key inducers to bitterness in the isolates. Additionally, the impact of 1-linoleoyl glycerol (9) on the bitter taste could be shown for 14 of the 17 tested pea-protein isolates.

Ion Guide for Improved Atmosphere to Mass Spectrometer Vacuum Ion Transfer

Various approaches for transmitting ions from atmosphere to the deep vacuum required for mass analysis have been developed with the goal to increase the ion to gas ratio while maintaining high ion transmission efficiency. Since the vast majority of ion losses occurs in the atmospheric pressure ion source, an effective way to improve sampling of those ions is to increase the atmosphere to vacuum aperture diameter. However, as the aperture diameter is increased, the resulting intense free jet gas expansion and subsequent gas beam can scatter ions in the first vacuum region. The interface described here provides an optimized flow field to the second vacuum stage, with a unique geometry to counter the ion losses from scattering collisions with the gas. Two additional differentially pumped quadrupole ion guides are used to further improve the ion to gas ratio, resulting in an ion transfer efficiency improvement of 5-6× over a two-stage differentially pumped interface with quadrupole ion guides. The interface also demonstrates efficient declustering and fragmentation capabilities beneficial for reducing background chemical noise.

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.

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.

Clustering and Nonclustering Modifier Mixtures in Differential Mobility Spectrometry for Multidimensional Liquid Chromatography Ion Mobility-Mass Spectrometry Analysis

Modifiers provide fast and reliable tuning of separation in differential mobility spectrometry (DMS). DMS selectivity for separating isomeric molecules depends on the clustering modifier concentration, which is typically 1.5-3 mol % ratio of isopropanol or ethanol in nitrogen. Low concentrations (0.1%) of isopropanol were found to improve resolution and sensitivity but at the cost of practicality and robustness. Replacing the single-channel DMS pump with a binary high-performance liquid chromatography (HPLC) pump enabled the generation of modifier mixtures at a constant flow rate using an isocratic or gradient mode, and the analytical benefits of the system were investigated considering cyclohexane, n-hexane, or n-octane as nonclustering modifiers and isopropanol or ethanol as clustering modifiers. It was found that clustering and nonclustering modifier mixtures enable optimization of selectivity, resolution, and sensitivity for different positional isomers and diastereoisomers. Data further suggested different ion separation mechanisms depending on the modifier ratios. For 85 analytes, the absolute difference in compensation voltages (CoVs) between pure nitrogen and cyclohexane at 1.5 mol % ratio was below 4 V, demonstrating its potential as a nonclustering modifier. Cyclohexane's nonclustering behavior was further supported by molecular modeling using density functional theory (DFT) and calculated cluster binding energies, showing positive ΔG values. The ability to control analyte CoVs by adjusting modifier concentrations in isocratic and gradient modes is beneficial for optimizing multidimensional LCxDMS-MS. It is fast and effective for manipulating the DMS scanning window size to realize shorter mass spectrometry (MS) acquisition cycle times while maintaining a sufficient number of CoV steps and without compromising DMS separation performance.

The Charge-State and Structural Stability of Peptides Conferred by Microsolvating Environments in Differential Mobility Spectrometry

The presence of solvent vapor in a differential mobility spectrometry (DMS) cell creates a microsolvating environment that can mitigate complications associated with field-induced heating. In the case of peptides, the microsolvation of protonation sites results in a stabilization of charge density through localized solvent clustering, sheltering the ion from collisional activation. Seeding the DMS carrier gas (N₂) with a solvent vapor prevented nearly all field-induced fragmentation of the protonated peptides GGG, AAA, and the Lys-rich Polybia-MP1 (IDWKKLLDAAKQIL-NH₂). Modeling the microsolvation propensity of protonated n-propylamine [PrNH₃]⁺, a mimic of the Lys side chain and N-terminus, with common gas-phase modifiers (H₂O, MeOH, EtOH, iPrOH, acetone, and MeCN) confirms that all solvent molecules form stable clusters at the site of protonation. Moreover, modeling populations of microsolvated clusters indicates that species containing protonated amine moieties exist as microsolvated species with one to six solvent ligands at all effective ion temperatures (T_eff) accessible during a DMS experiment (ca. 375-600 K). Calculated T_eff of protonated GGG, AAA, and Polybia-MPI using a modified two-temperature theory approach were up to 86 K cooler in DMS environments seeded with solvent vapor compared to pure N₂ environments. Stabilizing effects were largely driven by an increase in the ion's apparent collision cross section and by evaporative cooling processes induced by the dynamic evaporation/condensation cycles incurred in the presence of an oscillating electric separation field. When the microsolvating partner was a protic solvent, abstraction of a proton from [MP1 + 3H]³⁺ to yield [MP1 + 2H]²⁺ was observed. This result was attributed to the proclivity of protic solvents to form hydrogen-bond networks with enhanced gas-phase basicity. Collectively, microsolvation provides analytes with a solvent "air bag," whereby charge reduction and microsolvation-induced stabilization were shown to shelter peptides from the fragmentation induced by field heating and may play a role in preserving native-like ion configurations.

A concise review on lipidomics analysis in biological samples

Lipids are a complex and critical heterogeneous molecular entity, playing an intricate and key role in understanding biological activities and disease processes. Lipidomics aims to quantitatively define the lipid classes, including their molecular species. The analysis of the biological tissues and fluids are challenging due to the extreme sample complexity and occurrence of the molecular species as isomers or isobars. This review documents the overview of lipidomics workflow, beginning from the approaches of sample preparation, various analytical techniques and emphasizing the state-of-the-art mass spectrometry either by shotgun or coupled with liquid chromatography. We have considered the latest ion mobility spectroscopy technologies to deal with the vast number of structural isomers, different imaging techniques. All these techniques have their pitfalls and we have discussed how to circumvent them after reviewing the power of each technique with examples..