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

Determination of Collisional Cross Section Using Microscale High-Field Asymmetric Waveform ion Mobility Spectroscopy-Mass Spectrometry (FAIMS-MS)

RATIONALE

Collisional cross sections (CCS) are an important characteristic of gas-phase ions that are measured using ion mobility-mass spectrometry (IMS). Typically, CCS measurements are performed with drift-tube IMS or travelling-wave IMS. However. in a high-field asymmetric waveform ion mobility (FAIMS) device, ion heating effects make CCS determination more challenging. This research explores whether CCS can be predicted with microscale FAIMS by using known CCS standards.

METHODS

An Owlstone ultraFAIMS microscale FAIMS spectrometer was coupled to an Orbitrap Exactive mass spectrometer. Two different CCS standard mixtures (tetraalkylammonium halides [TAAHs] and poly-DL-alanine oligomers) were used to evaluate the system's potential to determine CCS. Test peptide bradykinin acetate and substance P were used to evaluate CCS determination accuracy for singly and doubly charged peptide species using external calibration with a series of poly-DL-alanine peptides for +1, +2 charge states.

RESULTS

Calibrations with excellent correlation coefficients (R2 = 0.99) for both TAAHs and poly-DL-alanine were obtained. Good accuracy of determination was achieved for bradykinin [M + 2H]2+ with a ± 0.5% difference between experimental and published CCS at a dispersion field (DF) strength of 250 Td; the model proved less accurate for bradykinin [M + H]+ (±1.4% at 240 Td). The accuracy of determination for the [M + H]+ and [M + 2H]2+ ions of substance P was within ± 5% and ± 3% at 250 Td, respectively, while at higher DF values, accuracy decreased to approximately 5%.

CONCLUSIONS

Distinct relationships were observed between CCS and transmission CF with both calibrants. Optimum accuracy was obtained at DF 240-260 Td. At lower DF, accuracy is reduced by insufficient resolution of analyte ions from solvent cluster adducts, while at higher DF values, poor transmission becomes a factor. Nevertheless, these data suggest microscale FAIMS can conduct CCS measurements with reasonable accuracy when the compound being measured has similar structural features to the CCS standards used.

Towards Generalizable In Silico Predictions of Differential Ion Mobility Using Machine Learning and Customized Fingerprint Engineering

Differential mobility spectrometry (DMS), a tool for separating chemically similar species (including isomers), is readily coupled to mass spectrometry to improve selectivity in analytical workflows. DMS dispersion curves, which describe the dynamic mobility experienced by an ion in a gaseous environment, show the maximum ion transmission for an analyte through the DMS instrument as a function of the separation voltage (SV) and compensation voltage (CV) conditions. To date, there exists no fast, general prediction tool for the dispersion behavior of ions. Here, we demonstrate a machine learning (ML) model that achieves generalized dispersion prediction using an in silico feature addition pipeline. We employ a data set containing 1141 dispersion curve measurements of anions and cations recorded in pure N2 environments and in N2 environments doped with 1.5% methanol (MeOH). Our feature addition pipeline can compute 1591 RDKit and Mordred descriptors using only SMILES codes, which are then normalized to sampled molecular distributions (n = 100 000) using cumulative density functions (CDFs). This tool can be thought of as a "learned" feature fingerprint generation pipeline, which could be applied to almost any molecular (bio)cheminformatics tasks. Our best performing model, which for the first time considers solvent-modified environments, has a mean absolute error (MAE) of 2.1 ± 0.2 V for dispersion curve prediction, a significant improvement over the previous state-of-the-art work. We use explainability techniques (e.g., SHAP analysis) to show that this feature addition pipeline is a semideterministic process for feature sets, and we discuss "best practices" to understand feature sets and maximize model performance. We expect that this tool could be used for prescreening to accelerate or even automate the use of DMS in complex analytical workflows (e.g., 2D LC×DMS separation) and perform automated identification of transmission windows and increase the "self-driving" potential of the instrument. We make our models available as a free and accessible tool at https://github.com/HopkinsLaboratory/DispersionCurveGUI.

Superior Differential Ion Mobility Spectrometry of Pendular Macromolecules Using Low-Frequency Rectangular Waveforms

Ion mobility spectrometry (IMS) can delineate gas-phase ions and probe their geometries. Coupling with electrospray ionization and MS has brought IMS to structural biology, revealing the macromolecular folding and subunit connectivity. However, the orientational averaging of ion-molecule collision cross sections (Ω) in the linear and field asymmetric waveform IMS (FAIMS) diminishes the resolution and structural specificity. In the novel low-field differential (LOD) IMS, a field too weak for ion heating (and thus FAIMS) aligns strong macrodipoles, capturing their magnitudes and directional Ω across the dipole (Ω⊥). However, the bisinusoidal waveforms (from FAIMS) have compromised the resolution, measurement accuracy, and correlation to the ion properties. Large ions amenable to LODIMS have low mobility and diffuse slowly, allowing the waveform frequencies down to ∼10 kHz. The low field and frequency permit generating the ideal rectangular waveforms with a flexible frequency and duty cycle by direct switching (impractical for FAIMS) in a miniature low-power format. This new IMS stage is evaluated for the exemplary large protein albumin (66 kDa) previously studied using the bisinusoidal waveform. The flat voltages and greater form factor initiate the differential IMS effect at lower fields, expand the separation space, and enable the quantification of Ω⊥ values by varying the duty cycle.

Acoustic ejection mass spectrometry: the potential for personalized medicine

INTRODUCTION

The emergence of personalized medicine (PM) has shifted the focus of healthcare from the traditional 'one-size-fits-all' approach to strategies tailored to individual patients, accounting for genetic, environmental, and lifestyle factors. Acoustic ejection mass spectrometry (AEMS) is a novel technology that offers a robust and scalable platform for high-throughput MS readout. AEMS achieves analytical speeds of one sample per second while maintaining high data quality, broad compound coverage, and minimal sample preparation, making it an invaluable tool for PM.

AREAS COVERED

This article explores the potential of AEMS in critical PM applications, including therapeutic drug monitoring (TDM), proteomics, metabolomics, and mass spectrometry imaging. AEMS simplifies conventional workflows by minimizing sample preparation, enhancing automation compatibility, and enabling direct analysis of complex biological matrices.

EXPERT OPINION

Integrating AEMS with orthogonal separation techniques such as differential mobility spectrometry (DMS) further addresses challenges in isomer discrimination, expanding the platform's analytical capabilities. Additionally, the development of high-throughput data processing tools could further enable AEMS to accelerate the development of personalized medicine.

Differential Mobility Spectrometry Acoustic Ejection Mass Spectrometer System for Screening Isomerization-Mediating Enzyme Drug Targets

We report the first implementation of ion mobility mass spectrometry combined with an ultrahigh throughput sample introduction technology for high-throughput screening (HTS). The system integrates differential mobility spectrometry (DMS) with acoustic ejection mass spectrometry (AEMS), termed DAEMS, enabling the simultaneous quantitation of structural isomers that are the substrates and products of isomerase-mediated reactions in intermediary metabolism. We demonstrate this potential by comparing DAEMS to a luminescence assay for the isoform of phosphoglycerate mutase (iPGM) distinctively present in pathogens, offering an opportunity as a drug target for a variety of microbial and parasite borne diseases. The metabolome consists of many structural isomers that require for separation a mobility resolving power of more than 300. Resolving powers measured in collision cross-section space of 1588 and 1948 for 2- and 3-phosphoglycerate and the citrate/isocitrate isomeric pairs, respectively, are shown. These are the highest reported ion mobility resolving powers for molecules from the metabolome reported to date. The potential for DAEMS as a generalized screening tool is demonstrated with the separation of the substrates and products of two additional isomerases that present as potential therapeutic targets, chorismate mutase and triosephosphate isomerase. The separations are achieved at speeds compatible with the sample introduction rates of AEMS providing sufficient data points to integrate the peaks for quantitation without the use of internal standards. DMS hyphenated with acoustic sample ejection MS provides a unique solution to high-throughput mass spectrometry applications where separation of isomers and other types of isobaric overlaps are required.

High Resolution Ion Mobility Enables the Structural Characterization of Atropisomers of GDC-6036, a KRAS G12C Covalent Inhibitor

GDC-6036 is a covalent KRAS G12C inhibitor that demonstrates high potency and selectivity. Structurally, GDC-6036 consists of several motifs that make the analytical characterization of this molecule challenging, including a highly basic pyrrolidine motif bonded to a quinazoline ring via an ether bond and an atropisomeric carbon-carbon bond between functionalized pyridine and quinazoline groups. Structurally, the desired atropisomer was synthesized via an atroposelective Negishi coupling with very high yield. However, having a direct way to analyze and confirm the presence of the atropisomeric species remained challenging in routine analytical workflows. In this study, both variable temperature nuclear magnetic resonance (VT-NMR) and two different approaches of in-line ion mobility coupled to liquid chromatography mass spectrometry (LC-MS) workflows were evaluated for the characterization of GDC-6036 and its undesired atropisomer (Compound B) to support synthetic route development. Briefly, both VT-NMR and traveling wave ion mobility spectrometry (TWIMS) enabled by structures for lossless ion manipulation (SLIM) technology coupled to high resolution MS (HRMS) are able to elucidate the structures of the atropisomers in a complex mixture. Drift tube IMS (DTIMS) was also evaluated, but lacked the resolving power to demonstrate separation between the two species in a mixture, but did show slight differences in their arrival times when multiplexed and injected separately. The determined resolving power (Rp) by multiplexing the ions via DTIMS was 67.3 and 60.5 for GDC-6036 and Compound B, respectively, while the two peak resolving power (Rpp) was determined to be 0.41, indicating inadequate resolution between the two species. Alternatively, the SLIM-IM studies showed Rp of 103.8 and 99.4, with a Rpp of 2.64, indicating good separation between the atropisomers. Furthermore, the CCS/z for GDC-6036 and Compound B was determined to be 231.2 Å2/z and 235.0 Å2/z, respectively. Quantitative experiments demonstrate linearity (R2 >0.99) for both GDC-6036 and Compound B while maintaining separation via SLIM-IM. Spike recoveries of one atropisomer relative to the other yielded strong recoveries (98.7% to 102.5%) while maintaining reproducibility (<7% RSD). The study herein describes the analytical process for evaluating new technologies and strategies for implementation in routine biopharmaceutical characterization workflows.

Identifying viral infections through analysis of head space volatile organic compounds

Volatile organic compounds (VOCs) produced by human respiratory cells reflect metabolic and pathophysiological processes which can be detected with the use of modern technology. Analysis of exhaled breath or indoor air may potentially play an important role in screening of upper respiratory tract infections such as COVID-19 or influenza in the future. In this experimental study, air samples were collected and analyzed from the headspace of anin vitrocell culture infected by selected pathogens (influenza A H1N1 and seasonal coronaviruses OC43 and NL63). VOCs were measured with a real-time proton-transfer-reaction time-of-flight mass spectrometer and a differential mobility spectrometer. Measurements were performed every 12 h for 7 d. Non-infected cells and cell culture media served as references. In H1N1 and OC43 we observed four different VOCs which peaked during the infection. Different, individual VOCs were also observed in both infections. Activity began to clearly increase after 2 d in all analyses. We did not see increased VOC production in cells infected with NL63. VOC analysis seems to be suitable to differentiate the infected cells from those which are not infected as well as different viruses, from another. In the future, this could have practical value in both individual diagnostics and indoor environment screening.

Metal Polycation Adduction to Lipids Enables Superior Ion Mobility Separations with Ultrafast Ozone-Induced Dissociation

Specific lipid isomers are functionally critical, but their structural rigidity and usually minute geometry differences make separating them harder than other biomolecules. Such separations by ion mobility spectrometry (IMS) were recently enabled by new high-definition methods using dynamic electric fields, but major resolution gains are needed. Another problem of identifying many isomers with no unique fragments in ergodic collision-induced dissociation (CID) was partly addressed by the direct ozone-induced dissociation (OzID) that localizes the double bonds, but a low reaction efficiency has limited the sensitivity, dynamic range, throughput, and compatibility with other tools. Typically lipids are analyzed by MS as singly charged protonated, deprotonated, or ammoniated ions. Here, we explore the differential IMS (FAIMS) separations with OzID for exemplary lipids cationized by polyvalent metals. These multiply charged adducts have much greater FAIMS compensation voltages (UC) than the 1+ ions, with up to 10-fold resolution gain enabling baseline isomer separations even at a moderate resolving power of the SelexION stage. Concomitantly OzID speeds up by many orders of magnitude, producing a high yield of diagnostic fragments already in 1 ms. These capabilities can be ported to the superior high-definition FAIMS and high-pressure OzID systems to take lipidomic analyses to the next level.

A Differential Ion Mobility Acoustic Ejection Mass Spectrometer System for Screening Isomerization-Mediating Enzyme Drug Targets

We report the first implementation of ion mobility mass spectrometry combined with an ultra-high throughput sample introduction technology for high throughput screening (HTS). The system integrates differential ion mobility (DMS) with acoustic ejection mass spectrometry (AEMS), termed DAEMS, enabling the simultaneous quantitation of structural isomers that are the sub-strates and products of isomerase mediated reactions in intermediary metabolism. We demonstrate this potential by comparing DAEMS to a luminescence assay for the isoform of phosphoglycerate mutase (iPGM) distinctively present in pathogens offering an opportunity as a drug target for a variety of microbial and parasite borne diseases. The metabolome consists of many structural isomers that require for separation a mobility resolving power of more than 300. Resolving powers measured in collision cross section space of 1588 and 1948 for 2- and 3-phosphoglycerate and the citrate/isocitrate isomeric pairs respectively are shown. These are the highest reported ion mobility resolving powers for molecules from the metabolome reported to date. The potential for DAEMS as a generalized screening tool is demonstrated with the separation of the substrates and products of two additional isomerases that present as potential therapeutic targets, chorismate mutase and triosephosphate isomerase. The separations are achieved at speeds compatible with the sample introduction rates of AEMS providing sufficient data points to integrate the peaks for quantitation without the use of internal standards. DMS hyphenated with acoustic sample ejection MS provides a unique solution to high throughput mass spectrom-etry applications where isomer and other types of separations are required.

The Role of Mass Spectrometry in Protecting Public Health and the Environment from Synthetic Chemicals

Mass spectrometry (MS) has dramatically transformed environmental protection by facilitating the precise quantification and identification of pollutants. This review charts the evolution of environmental chemistry, intertwining it with advancements in analytical chemistry and MS technologies. It specifically focuses on the role of MS in studying persistent organic pollutants like organochlorine pesticides, polychlorinated biphenyls (PCBs), brominated fire retardants (BFRs), and perfluoroalkyl and polyfluoroalkyl substances (PFAS), marking significant milestones and their implications. Notably, the adoption of gas chromatography with MS in the 1970s and liquid chromatography with MS in the late 1990s profoundly expanded scientists' ability to detect complex pollutant mixtures. Over the past 50 years, the proliferation of potential pollutants has surged, necessitating more sophisticated analysis techniques, such as high-resolution mass spectrometry-nontargeted analysis (HRMS-NTA) and suspect screening. While HRMS promises to enhance the characterization of new environmental pollutants, a significant shift in chemical management strategies remains imperative. Despite technological advances, MS alone is insufficient to mitigate the risks from the continuous emergence of novel chemicals, with many potentially already present in the environment and bioaccumulating in humans.

Reliable Detection of Chemical Warfare Agents Using High Kinetic Energy Ion Mobility Spectrometry

High Kinetic Energy Ion Mobility Spectrometers (HiKE-IMS) ionize and separate ions at reduced pressures of 10-40 mbar and over a wide range of reduced electric field strengths E/N of up to 120 Td. Their reduced operating pressure is distinct from that of conventional drift tube ion mobility spectrometers that operate at ambient pressure for trace compound detection. High E/N can lead to a field-induced fragmentation pattern that provides more specific structural information about the analytes. In addition, operation at high E/N values adds the field dependence of ion mobility as an additional separation dimension to low-field ion mobility, making interfering compounds less likely to cause a false positive alarm. In this work, we study the chemical warfare agents tabun (GA), sarin (GB), soman (GD), cyclosarin (GF) and sulfur mustard (HD) in a HiKE-IMS at variable E/N in both the reaction and the drift region. The results show that varying E/N can lead to specific fragmentation patterns at high E/N values combined with molecular signals at low E/N. Compared to the operation at a single E/N value in the drift region, the variation of E/N in the drift region also provides the analyte-specific field dependence of ion mobility as additional information. The accumulated data establish a unique fingerprint for each analyte that allows for reliable detection of chemical warfare agents even in the presence of interfering compounds with similar low-field ion mobilities, thus reducing false positives.

On the Arrival Time Distribution of Reacting Systems in Ion Mobility Spectrometry

Ion mobility spectrometry (IMS) is a widely used gas-phase separation technique, particularly when coupled with mass spectrometry (MS). Modern IMS instruments often apply elevated reduced field strengths for improved ion separation and ion focusing. These alter the collision dynamics and further drive ion reaction processes that can change the analyte's structure. As a result, the measured arrival time distribution (ATD) can change with the applied reduced field strengths. In this work, we systematically study how the ion collision dynamics and the ion reaction dynamics, as a function of the reduced field strength, can alter the ATD. To this end, we investigate 2,6-di-tert-butylpyridine, methanol, and ethyl acetate using a home-built drift tube IMS coupled to a home-built MS and extensive first-principles Monte Carlo modeling. We show how elevated reduced field strengths can actually lower resolving power through increased ion diffusion and how the field dependency of the ion mobility can introduce uncertainties to collision cross sections (CCS) calculated from the measured mobilities. On top of the collision dynamics, we show how chemical transformation processes that alter the analyte's CCS, e.g., dynamic clustering or fragmentation, can lead to broadened, shifted, or non-Gaussian ATDs and how sensitive these processes are to the applied field strengths. We highlight how first-principles ion dynamics simulations can help to understand and even harness the mentioned effects.

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.