Review of applications of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and differential mobility spectrometry (DMS)

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.

Characterization of Pharmaceutical Transformation Products by High-Field Asymmetric Waveform Ion Mobility and Infrared Ion Spectroscopy Coupled to Mass Spectrometry

The identification of drug degradation products is crucial for pharmaceutical development and quality control, as drug transformation products can significantly affect therapeutic efficacy and patient safety. Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and tandem mass spectrometry (MS/MS), often require reference standards for accurate identification and may be unsuitable for resolving isomeric and isobaric degradation products. This study explores the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) and infrared multiple photon dissociation (IRMPD) spectroscopy coupled with mass spectrometry (MS) as an effective alternative for identifying drug degradation products without the need for previous chromatographic stages or the use of reference standards. Cyclophosphamide, a widely used DNA-alkylating agent in cancer and autoimmune therapies, is employed as a model system for this study. FAIMS enabled the separation of species based on their differential mobility, while IRMPD provided distinctive spectral data, allowing precise reference-standard-free structural elucidation. This integrated approach offers a robust solution for the identification of complex degradation products, advancing stability studies, formulation development, and quality control in pharmaceutical analysis.

Decoding Sugars: Mass Spectrometric Advances in the Analysis of the Sugar Alphabet

Monosaccharides play a central role in metabolic networks and in the biosynthesis of glycomolecules, which perform essential functions across all domains of life. Thus, identifying and quantifying these building blocks is crucial in both research and industry. Routine methods have been established to facilitate the analysis of common monosaccharides. However, despite the presence of common metabolites, most organisms utilize distinct sets of monosaccharides and derivatives. These molecules therefore display a large diversity, potentially numbering in the hundreds or thousands, with many still unknown. This complexity presents significant challenges in the study of glycomolecules, particularly in microbes, including pathogens and those with the potential to serve as novel model organisms. This review discusses mass spectrometric techniques for the isomer-sensitive analysis of monosaccharides, their derivatives, and activated forms. Although mass spectrometry allows for untargeted analysis and sensitive detection in complex matrices, the presence of stereoisomers and extensive modifications necessitates the integration of advanced chromatographic, electrophoretic, ion mobility, or ion spectroscopic methods. Furthermore, stable-isotope incorporation studies are critical in elucidating biosynthetic routes in novel organisms.

Differential Mobility Spectrometry Authenticates the Botanical Origins of Five Monofloral Honeys

Differential mobility spectrometry (DMS) enables the detection and separation of volatile organic compounds, exploiting differences in ion mobility under varying electric fields, which enhance the resolution of complex mixtures. In this study, DMS, upon integration with chemometrics, enabled the differentiation of the botanical origins of Italian honeys. Utilizing a benchtop differential mobility spectrometer connected to pure air, 219 monofloral honeys of five different botanical origins (acacia, chestnut, citrus, eucalyptus, and linden) were simultaneously analyzed in positive and negative ion modes and with the analysis duration of less than 2 min. Repeatability of the resultant volatilomic fingerprints was verified by cosine similarity with the subsequent elimination of the nonrepeatable data. Afterward, the data for both polarities were concatenated, and an exploratory investigation was carried out into the discrimination capabilities of DMS by principal component analysis. The merged data were then submitted to a statistical analysis for classification. The performance of the resultant random forest (RF) classifier was evaluated by repeated cross-validation and resubstitution into the training set, and finally, this classifier was validated on a withheld subset of data. The performances of the classification model for each test were evaluated by calculating the contingency table-derived parameters of accuracy, Matthew's correlation coefficient (MCC), sensitivity, and specificity. The RF classifier produced high-performance values when predicting the botanical origin of the honey in both training (MCC 84.8%, accuracy 88.0%, sensitivity 87.5%, and specificity 96.9%) and validation subsets (MCC 82.6%, accuracy 86.3%, sensitivity 85.7%, and specificity 96.5%). Some limitations, expected to be mitigated by further research, were encountered in the correct classification of acacia honey.

Overcoming the challenge of potent endogenous interferences in limaprost quantification: An innovative methodology combining differential mobility spectrometry with LC-MS/MS for ultra-high sensitivity, selectivity and significantly enhanced throughput

Limaprost, an orally administered analogue of prostaglandin E1, possesses potent vasodilatory, antiplatelet, and cytoprotective properties. Due to its extremely low therapeutic doses and exceedingly low plasma concentrations, the pharmacokinetic and bioequivalence studies of limaprost necessitate a highly sensitive quantitative method with a sub-pg/mL level of lower limit of quantification. Moreover, the intensity of endogenous interferences can even exceed the maximum concentration level of limaprost in human plasma, presenting further challenge to the quantification of limaprost. As a result, existing methods have not yet met the necessary level of sensitivity, selectivity, and throughput needed for the quantitative analysis of limaprost in pharmacokinetic and bioequivalence investigations. This study presents a new methodology that combines differential mobility spectrometry (DMS) with liquid chromatography-tandem mass spectrometry (LC-MS/MS) and utilizes a distinctive strategy to achieve more accurate DMS conditions. This integration yields a method that is currently the most sensitive and features the shortest analytical time, making it the sole technique capable of meeting the requirements for limaprost pharmacokinetic and bioequivalence investigations. This method demonstrates robustness and is successfully employed in a pharmacokinetic investigation of limaprost in human subjects, underscoring that the combination of DMS with LC-MS/MS serves as an efficacious strategy for overcoming the challenges inherent in analyzing biological samples afflicted by multiple interferences.

Racetrack FAIMS for High-Resolution and High-Sensitivity Characterization of Peptide Conformers

A racetrack field asymmetric waveform ion mobility spectrometry (r-FAIMS) device, which consists of both cylindrical FAIMS (c-FAIMS) and planar FAIMS (p-FAIMS) sections with a 1 mm gap width, was developed and applied for high-resolution and high-sensitivity exploration of conformational diversity for peptides. The optimal operating conditions of r-FAIMS were systemically studied, and the performance of the fully optimized r-FAIMS was compared to a previously developed p-FAIMS in detail by using pure nitrogen as the FAIMS carrier gas. Relying on the ion focusing effect in the c-FAIMS section, the intensity of the FAIMS spectrum for doubly charged bradykinin ions acquired by using r-FAIMS is ∼8.5-fold higher than that acquired by using p-FAIMS under the same resolving power/resolution condition, implying about an order of magnitude better sensitivity of r-FAIMS. In addition, the peak separation resolution of r-FAIMS was ∼1.70-fold higher than p-FAIMS under a similar sensitivity condition for doubly charged bradykinin ions. Due to a reduced gap width of the newly designed r-FAIMS (1 mm) as compared to the previously developed p-FAIMS (1.88 mm), r-FAIMS can operate at a much higher separation field with a similar FAIMS dispersion voltage (DV) to gain significantly higher resolving power. For triply charged syntide 2 ions, the resolving power of r-FAIMS can easily exceed 120 at -3.5 kV DV by using pure nitrogen as the FAIMS carrier gas as compared to 44.2 resolving power obtained by using p-FAIMS at -4.0 kV DV. All of the experimental results have confirmed that r-FAIMS can perform structural characterization of biomolecules with both high resolution and high sensitivity.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

Dual ionization sources high-field asymmetric waveform ion mobility spectrometry with combined ultraviolet lamp source and corona discharge source

Dual ionization sources combining an ultraviolet (UV) lamp source and a corona discharge (CD) source were first used as ionization sources for high-field asymmetric waveform ion mobility spectrometry (FAIMS) to switch ionization modes without changing hardware. The CD source was manufactured using a tungsten needle and a copper ring and its usability was verified. The UV source and the CD source were combined into the FAIMS sensor and multiple ionization modes were attempted by controlling their on-off status. The optimal flow rate, quantitative and qualitative capabilities of the system were investigated, and the experiments on the impact of humidity and interferent on the system were conducted. The experimental results indicated that the flow rate of 3-4 L/min could ensure sufficient sensitivity and resolution of the system. The dual ionization sources configuration provided richer qualitative and quantitative information for FAIMS. This platform could operate in three ionization modes and had the potential to expand the analyzable compounds of UV-FAIMS. In summary, the research demonstrates that the dual ionization sources could be used as ionization sources for FAIMS, and the combined system provided convenience for chemical analysis.

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.

Structural Elucidation of Intact Rough-type Lipopolysaccharides Using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots

Lipopolysaccharides (LPSs) are a hallmark virulence factor of Gram-negative bacteria. They are complex, structurally heterogeneous mixtures due to variations in number, type, and position of their simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of an intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas-phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas-phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [Na-H] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families, i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 181 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA

A major limitation when undertaking quantitative proteomic time-course experimentation is the tradeoff between depth-of-analysis and speed-of-analysis. In high complexity and high dynamic range sample types, such as plant extracts, balance between resolution and time is especially apparent. To address this, we evaluate multiple compensation voltage (CV) high field asymmetric waveform ion mobility spectrometry (FAIMSpro) settings using the latest label-free single-shot Orbitrap-based DIA acquisition workflows for their ability to deeply quantify the Arabidopsis thaliana seedling proteome. Using a BoxCarDIA acquisition workflow with a -30 -50 -70 CV FAIMSpro setting, we were able to consistently quantify >5000 Arabidopsis seedling proteins over a 21-min gradient, facilitating the analysis of ∼42 samples per day. Utilizing this acquisition approach, we then quantified proteome-level changes occurring in Arabidopsis seedling shoots and roots over 24 h of salt and osmotic stress, to identify early and late stress response proteins and reveal stress response overlaps. Here, we successfully quantify >6400 shoot and >8500 root protein groups, respectively, quantifying nearly ∼9700 unique protein groups in total across the study. Collectively, we pioneer a short gradient, multi-CV FAIMSpro BoxCarDIA acquisition workflow that represents an exciting new analysis approach for undertaking quantitative proteomic time-course experimentation in plants.

Stationary Explosive Trace Detection System Using Differential Ion Mobility Spectrometry (DMS)

Detecting trace amounts of explosives is important for maintaining national security due to the growing threat of terror attacks. Particularly challenging is the increasing use of homemade explosives. Therefore, there is a constant need to improve existing technologies for detecting trace amounts of explosives. This paper describes the design of a stationary device (a gate) for detecting trace amounts of explosives and explosive taggants and the design of differential ion mobility spectrometers with a focus on the gas system. Nitromethane (NM), trimeric acetone peroxide (TATP), hexamine peroxide (HMTD), and explosive taggants 2,3-dimethyl-2,3-dinitrobutane (DMDNB) and 4-nitrotoluene (4NT) were used in this study. Gate measurements were carried out by taking air from the hands, pocket area, and shoes of the tested person. Two differential ion mobility spectrometers operating in two different modes were used as explosive detectors: a mode with a semi-permeable membrane to detect explosives with high vapor pressures (such as TATP) and a mode without a semi-permeable membrane (using direct introduction of the sample into the measuring chamber) to detect explosives with low vapor pressures (such as HMTD). The device was able to detect trace amounts of selected explosives/explosive taggants in 5 s.

Optimum collision energies for proteomics: The impact of ion mobility separation

Ion mobility spectrometry (IMS) is a widespread separation technique used in various research fields. It can be coupled to liquid chromatography-mass spectrometry (LC-MS/MS) methods providing an additional separation dimension. During IMS, ions are subjected to multiple collisions with buffer gas, which may cause significant ion heating. The present project addresses this phenomenon from the bottom-up proteomics point of view. We performed LC-MS/MS measurements on a cyclic ion mobility mass spectrometer with varied collision energy (CE) settings both with and without IMS. We investigated the CE dependence of identification score, using Byonic search engine, for more than 1000 tryptic peptides from HeLa digest standard. We determined the optimal CE values-giving the highest identification score-for both setups (i.e., with and without IMS). Results show that lower CE is advantageous when IMS separation is applied, by 6.3 V on average. This value belongs to the one-cycle separation configuration, and multiple cycles may supposedly have even larger impact. The effect of IMS is also reflected in the trends of optimal CE values versus m/z functions. The parameters suggested by the manufacturer were found to be almost optimal for the setup without IMS; on the other hand, they are obviously too high with IMS. Practical consideration on setting up a mass spectrometric platform hyphenated to IMS is also presented. Furthermore, the two CID (collision induced dissociation) fragmentation cells of the instrument-located before and after the IMS cell-were also compared, and we found that CE adjustment is needed when the trap cell is used for activation instead of the transfer cell. Data have been deposited in the MassIVE repository (MSV000090944).

High-Field Asymmetric Waveform Ion Mobility Spectrometry Analysis of Carcinogenic Aromatic Amines in Tobacco Smoke with an Orbitrap Tribrid Mass Spectrometer

Smoking is a risk factor for bladder cancer (BC), although the specific chemicals responsible for BC remain uncertain. Considerable research has focused on aromatic amines (AAs), including o-toluidine (o-tol), o-anisidine (o-anis), 2-naphthylamine (2-NA), and 4-aminobiphenyl (4-ABP), which are linked to human BC based on elevated BC incidence in occupationally exposed factory workers. These AAs arise at nanogram levels per combusted cigarette. The unambiguous identification of AAs, particularly low-molecular-weight monocyclic AAs in tobacco smoke extracts, by liquid chromatography-mass spectrometry (LC-MS) is challenging due to their poor performance on reversed-phase columns and co-elution with isobaric interferences from the complex tobacco smoke matrix. We employed a tandem liquid-liquid and solid-phase extraction method to isolate AAs from the basic fraction of tobacco smoke condensate (TSC) and utilized high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to high-resolution accurate mass (HRAM) Orbitrap LC-MS2 to assay AAs in TSC. The employment of FAIMS greatly reduced sample complexity by removing precursor co-isolation interfering species at the MS1 scan stage, resulting in dramatically improved signal-to-noise of the precursor ions and cleaner, high-quality MS2 spectra for unambiguous identification and quantification of AAs in TSC. We demonstrate the power of LC/FAIMS/MS2 by characterizing and quantifying two low-molecular-weight carcinogenic AAs, o-tol and o-anis, in TSC, using stable isotopically labeled internal standards. These results demonstrate the power of FAIMS in trace-level analyses of AA carcinogens in the complex tobacco smoke matrix.

Structural Elucidation of Intact Rough-Type Lipopolysaccharides using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots

Lipopolysaccharide (LPS) is a hallmark virulence factor of Gram-negative bacteria. It is a complex, structurally heterogeneous mixture due to variations in number, type, and position of its simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [NaH] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families; i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 179 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

Simplified Liquid Chromatography-Mass Spectrometry Methods for Gestagen Analysis in Animal Fat and Liver

Gestagens, a class of veterinary drugs also called progestogens, are synthetic hormones used to increase feed efficiency and rate of gain in heifers. The Canadian Food Inspection Agency analyzes progestogens melengestrol acetate (MGA), megestrol acetate, and chlormadinone acetate using liquid chromatography-mass spectrometry (LC-MS). Our conventional gestagen method for kidney fat has many time-consuming steps, including solid-phase extraction. A sample preparation procedure having fewer clean-up steps was developed for routine diagnostic analysis of kidney fat and provided similar results faster, and at lower cost. A confirmatory liver method for gestagens, developed using salt-assisted extraction, employed minimal clean-up steps that resulted in high chemical background at the desired lower limit of quantification (LLOQ). Differential ion mobility spectrometry, specifically high-field asymmetric waveform ion mobility spectrometry (FAIMS), was used to filter chemical background in the gas phase. The effect of the ionization probe position on FAIMS parameters, including sensitivity, is described. With LC-FAIMS-MS, chemical background for each gestagen was virtually eliminated, resulting in a quantitative liver method having the desired 0.6 ng/g LLOQ and estimated limits of detection (LODs) up to 140 times lower than LC-MS. Incurred MGA samples, analyzed using kidney fat and liver methods from the same animal, show levels within the quantitative ranges of both methods.

Differential Mobility Spectrometry-Tandem Mass Spectrometry with Multiple Ion Monitoring Coupled with in Source-Collision Induced Dissociation: A New Strategy for the Quantitative Analysis of Pharmaceutical Polymer Excipients in Rat Plasma

Polylactic acids (PLAs) are synthetic polymers composed of repeating lactic acid subunits. For their good biocompatibility, PLAs have been approved and widely applied as pharmaceutical excipients and scaffold materials. Liquid chromatography-tandem mass spectrometry is a powerful analytical tool not only for pharmaceutical ingredients but also for pharmaceutical excipients. However, the characterization of PLAs presents particular problems for mass spectrometry techniques. In addition to their high molecular weights and wide polydispersity, multiple charging and various adductions are intrinsic features of electrospray ionization. In the present study, a strategy combining of differential mobility spectrometry (DMS), multiple ion monitoring (MIM) and in-source collision-induced dissociation (in source-CID) has been developed and applied to the characterization and quantitation of PLAs in rat plasma. First, PLAs will be fragmented into characteristic fragment ions under high declustering potential in the ionization source. The specific fragment ions are then screened twice by quadrupoles to ensure a high signal intensity and low interference for mass spectrometry detection. Subsequently, DMS technique has been applied to further reduce the background noise. The appropriately chosen surrogate specific precursor ions could be utilized for the qualitative and quantitative analysis of PLAs, which provided results with the advantages of low endogenous interference, sufficient sensitivity and selectivity for bioassay. The linearity of the method was evaluated over the concentration range 3-100 μg/mL (r² = 0.996) for PLA 20,000. The LC-DMS-MIM coupled with in source-CID strategy may contribute to the pharmaceutical studies of PLAs and the possible prospects of other pharmaceutical excipients.

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).

Development of a Rapid and Accurate Vapor Generation System for Real-Time Monitoring of a Chemical Warfare Agent (CWA) by Coupling Fourier Transform Infrared (FT-IR) Spectroscopy

Developing an accurate chemical warfare agent (CWA) vapor generator is critical for homeland security because it enables real-time monitoring of target agent concentration for testing and evaluation. We designed and built an elaborate CWA vapor generator that offers reliable long-term stability and real-time monitoring capabilities by coupling it with Fourier transform infrared (FT-IR) spectroscopy. We evaluated the reliability and stability of the vapor generator using a gas chromatography-flame ion detector (GC-FID) and conducted a comparison between the experimental and theoretical results of sulfur mustard (HD, bis-2-chloroethylsulfide), a real CWA, at concentrations ranging from 1 to 5 ppm. Our FT-IR-coupled vapor generation system showed real-time monitoring ability, which enables rapid and accurate evaluation of chemical detectors. The vapor generation system was able to generate CWA vapor continuously for over 8 h, demonstrating its long-term vapor generation capability. In addition, we vaporized another representative CWA, viz., GB (Sarin, propan-2-yl ethylphosphonofluoridate), and conducted real-time monitoring of GB vapor concentration with high accuracy. This versatile vapor generator approach can enable the rapid and accurate evaluation of CWAs for homeland security against chemical threats and can be used in constructing a versatile real-time monitoring vapor generation system for CWAs.

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.

Hydrogen-Deuterium-Exchange-Based Mass Distribution Shifts in High-Resolution Cyclic Ion Mobility Separations

The mass distribution of ions influences separations in ion mobility spectrometry-mass spectrometry (IMS-MS). Herein, we introduce a method to induce mass distribution shifts for various analytes using hydrogen-deuterium exchange (HDX) immediately prior to ionization using a dual syringe approach. By replacing labile hydrogens on analytes with deuteriums, we were able to differentiate isomers using separations of isotopologues. For each analyte studied, every possible level of deuteration (from undeuterated to fully deuterated) was generated and then separated using cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS). The information gained from such separations (relative arrival times; t_Rel. values) was found to be orthogonal to conventional IMS-MS separations. Additionally, the observed shifts were linearly additive with increasing deuteration, suggesting that this methodology could be extended to analytes with a larger number of labile hydrogens. For one isomer pair, as few as two deuteriums were able to produce a large enough mass distribution shift to differentiate isomers. In another experiment, we found that the mass distribution shift was large enough to overcome the reduced mass contribution, resulting in a "flipped" arrival time where the heavier deuterated isotopologue arrived before the lighter one. In this work, we present a proof-of-concept demonstration that mass-distribution-based shifts, t_Rel. values, could potentially act as an added dimension to characterize molecules in IMS-MS. We anticipate, along with future work in this area, that mass-distribution-based shifts could enable the identification of unknown molecules through a database-driven approach in an analogous fashion to collision cross section (CCS) measurements.

Understanding of protomers/deprotomers by combining mass spectrometry and computation

Multifunctional compounds may form different prototropic isomers under different conditions, which are known as protomers/deprotomers. In biological systems, these protomer/deprotomer isomers affect the interaction modes and conformational landscape between compounds and enzymes and thus present different biological activities. Study on protomers/deprotomers is essentially the study on the acidity/basicity of each intramolecular functional group and its effect on molecular structure. In recent years, the combination of mass spectrometry (MS) and computational chemistry has been proven to be a powerful and effective means to study prototropic isomers. MS-based technologies are developed to discriminate and characterize protomers/deprotomers to provide structural information and monitor transformations, showing great superiority than other experimental methods. Computational chemistry is used to predict the thermodynamic stability of protomers/deprotomers, provide the simulated MS/MS spectra, infrared spectra, and calculate collision cross-section values. By comparing the theoretical data with the corresponding experimental results, the researchers can not only determine the protomer/deprotomer structure, but also investigate the structure-activity relationship in a given system. This review covers various MS methods and theoretical calculations and their devotion to isomer discrimination, structure identification, conformational transformation, and phase transition investigation of protomers/deprotomers.

MALDI TIMS IMS of Disialoganglioside Isomers─GD1a and GD1b in Murine Brain Tissue

Gangliosides are acidic glycosphingolipids, containing ceramide moieties and oligosaccharide chains with one or more sialic acid residue(s) and are highly diverse isomeric structures with distinct biological roles. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) enables the untargeted spatial analysis of gangliosides, among other biomolecules, directly from tissue sections. Integrating trapped ion mobility spectrometry with MALDI IMS allows for the analysis of isomeric lipid structures in situ. Here, we demonstrate the gas-phase separation and identification of disialoganglioside isomers GD1a and GD1b that differ in the position of a sialic acid residue, in multiple samples, including a standard mixture of both isomers, a biological extract, and directly from thin tissue sections. The unique spatial distributions of GD1a/b (d36:1) and GD1a/b (d38:1) isomers were determined in rat hippocampus and spinal cord tissue sections, demonstrating the ability to structurally characterize and spatially map gangliosides based on both the carbohydrate chain and ceramide moieties.

Ambient Ionization Mass Spectrometry: Application and Prospective

Mass spectrometry (MS) is a formidable analytical tool for the analysis of non-polar to polar compounds individually and/or from mixtures, providing information on the molecular weights and chemical structures of the analytes. During the last more than one-decade, ambient ionization mass spectrometry (AIMS) has developed quickly, producing a wide range of platforms and proving scientific improvements in a variety of domains, from biological imaging to quick quality control. These methods have made it possible to detect target analytes in real time without sample preparation in an open environment, and they can be connected to any MS system with an atmospheric pressure interface. They also have the ability to analyze explosives, illicit drugs, disease diagnostics, drugs in biological samples, adulterants in food and agricultural products, reaction progress, and environmental monitoring. The development of novel ambient ionization techniques, such as probe electrospray ionization, paper spray ionization, and fiber spray ionization, employed even at picolitre to femtolitre solution levels to provide femtogram to attogram levels of the target analytes. The special characteristic of this ambient ion source, which has been extensively used, is the noninvasive property of PESI of examination of biological real samples. The results in the current review supports the idea that AIMS has emerged as a pioneer in MS-based approaches and that methods will continue to be developed along with improvements to existing ones in the near future.

A deep learning approach for detecting liver cirrhosis from volatolomic analysis of exhaled breath

Liver disease such as cirrhosis is known to cause changes in the composition of volatile organic compounds (VOC) present in patient breath samples. Previous studies have demonstrated the diagnosis of liver cirrhosis from these breath samples, but studies are limited to a handful of discrete, well-characterized compounds. We utilized VOC profiles from breath samples from 46 individuals, 35 with cirrhosis and 11 healthy controls. A deep-neural network was optimized to discriminate between healthy controls and individuals with cirrhosis. A 1D convolutional neural network (CNN) was accurate in predicting which patients had cirrhosis with an AUC of 0.90 (95% CI: 0.75, 0.99). Shapley Additive Explanations characterized the presence of discrete, observable peaks which were implicated in prediction, and the top peaks (based on the average SHAP profiles on the test dataset) were noted. CNNs demonstrate the ability to predict the presence of cirrhosis based on a full volatolomics profile of patient breath samples. SHAP values indicate the presence of discrete, detectable peaks in the VOC signal.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

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

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.

Femtoliter-Droplet Mass Spectrometry Interface Utilizing Nanofluidics for Ultrasmall and High-Sensitivity Analysis

In the fields of biology and medicine, comprehensive protein analysis at the single-cell level utilizing mass spectrometry (MS) with pL sample volumes and zmol to amol sensitivity is required. Our group has developed nanofluidic analytical pretreatment methods that exploit nanochannels for downsizing chemical unit operations to fL-pL volumes. In the field of analytical instruments, mass spectrometers have advanced to achieve ultrahigh sensitivity. However, a method to interface between fL-pL pretreatments and mass spectrometers without sample loss and dispersion is still challenging. In this study, we developed an MS interface utilizing nanofluidics to achieve high-sensitivity detection. After charging analyte molecules by an applied voltage through an electrode, the liquid sample was converted to fL droplets by a nanofluidic device. Considering the inertial force that acts on the droplets, the droplets were carried with a controlled trajectory, even in turbulent air flow, and injected into a mass spectrometer with 100% efficiency. A module for heat transfer was designed and constructed, by which all of the injected droplets were vaporized to produce gas-phase ions. The detection of caffeine ions was achieved at a limit of detection of 1.52 amol, which was 290 times higher than a conventional MS interface by electrospray ionization with sample dispersion combined with a similar mass spectrometer. Therefore, sensitivity that was 2 orders of magnitude higher could be realized due to the 100% sample injection rate. The present study provides a new methodology for the analysis of ultrasmall samples with high-sensitivity, such as protein molecules produced from a single cell.

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.

Two-Dimensional FAIMS-IMS Characterization of Peptide Conformers with Resolution Exceeding 1000

A high-performance field asymmetric waveform ion mobility spectrometry (FAIMS)-IMS-MS platform was developed and applied to explore the conformational diversity of the singly and doubly charged bradykinin (BK + H⁺)⁺ and (BK + 2H⁺)²⁺ ions. With pure N₂ as the FAIMS carrier gas, more than ten conformers of (BK + H⁺)⁺ can be resolved using FAIMS-IMS, as compared to only four conformers resolved using either FAIMS or IMS alone. Interestingly, multiple conformers of (BK + H⁺)⁺ were found to have completely different values of FAIMS compensation voltage (CV), while their IMS drift times were essentially the same, which were also proven experimentally to not result from the structural annealing by the collisional heating in the ion funnel. The separations in the FAIMS and IMS dimensions are substantially orthogonal, and the overall resolving power of two-dimensional FAIMS-IMS separation is largely proportional to the product of the separation resolving powers of FAIMS and IMS. Using a gas mixture of N₂/He to further improve the resolving power of the FAIMS separation, the total resolving powers of the combined FAIMS and IMS separation were estimated to be about 1020 and 1400 for (BK + H⁺)⁺ and (BK + 2H⁺)²⁺ ions, respectively, which are significantly higher than the resolving power of any ion mobility-based separation techniques demonstrated so far. The combined FAIMS-IMS can thus be a much more powerful technique to explore the structural diversity of biomolecules.

Drone-Mountable Gas Sensing Platform Using Graphene Chemiresistors for Remote In-Field Monitoring

We present the design, fabrication, and testing of a drone-mountable gas sensing platform for environmental monitoring applications. An array of graphene-based field-effect transistors in combination with commercial humidity and temperature sensors are used to relay information by wireless communication about the presence of airborne chemicals. We show that the design, based on an ESP32 microcontroller combined with a 32-bit analog-to-digital converter, can be used to achieve an electronic response similar, within a factor of two, to state-of-the-art laboratory monitoring equipment. The sensing platform is then mounted on a drone to conduct field tests, on the ground and in flight. During these tests, we demonstrate a one order of magnitude reduction in environmental noise by reducing contributions from humidity and temperature fluctuations, which are monitored in real-time with a commercial sensor integrated to the sensing platform. The sensing device is controlled by a mobile application and uses LoRaWAN, a low-power, wide-area networking protocol, for real-time data transmission to the cloud, compatible with Internet of Things (IoT) applications.

Enhanced Top-Down Protein Characterization with Electron Capture Dissociation and Cyclic Ion Mobility Spectrometry

Tandem mass spectrometry of denatured, multiply charged high mass protein precursor ions yield extremely dense spectra with hundreds of broad and overlapping product ion isotopic distributions of differing charge states that yield an elevated baseline of unresolved "noise" centered about the precursor ion. Development of mass analyzers and signal processing methods to increase mass resolving power and manipulation of precursor and product ion charge through solution additives or ion-ion reactions have been thoroughly explored as solutions to spectral congestion. Here, we demonstrate the utility of electron capture dissociation (ECD) coupled with high-resolution cyclic ion mobility spectrometry (cIMS) to greatly increase top-down protein characterization capabilities. Congestion of protein ECD spectra was reduced using cIMS of the ECD product ions and "mobility fractions", that is, extracted mass spectra for segments of the 2D mobiligram (m/z versus drift time). For small proteins, such as ubiquitin (8.6 kDa), where mass resolving power was not the limiting factor for characterization, pre-IMS ECD and mobility fractions did not significantly increase protein sequence coverage, but an increase in the number of identified product ions was observed. However, a dramatic increase in performance, measured by protein sequence coverage, was observed for larger and more highly charged species, such as the +35 charge state of carbonic anhydrase (29 kDa). Pre-IMS ECD combined with mobility fractions yielded a 135% increase in the number of annotated isotope clusters and a 75% increase in unique product ions compared to processing without using the IMS dimension. These results yielded 89% sequence coverage for carbonic anhydrase.

Mapping Protein Structural Evolution upon Unfolding

In the past, many intensive attempts failed to capture or underestimated the copopulated intermediate conformers from the protein folding/unfolding reaction. We report a promising approach to kinetically trap, resolve, and quantify protein conformers that evolve during unfolding in solution. We conducted acid-induced unfolding of three model proteins (cytochrome c, myoglobin, and lysozyme), and the corresponding reaction aliquots upon decreasing the pH were electrosprayed for high field asymmetric waveform ion mobility spectrometry (FAIMS) measurements. The copopulated conformers were resolved, visualized, and quantified by a two-dimensional mapping of the FAIMS output. Contrary to expectations, all the above proteins appeared metamorphic (multiple-folded conformations) at the physiological pH, and cytochrome c exhibited an unusual "conformational shuttling" before forming the molten globule state. Thus, in contrast to many previous studies, a wide variety of thermodynamically stable intermediate conformers, including compact, molten globule, and partially unfolded forms, was trapped from solution, probing the unfolding mechanism in detail.

Getting more out of FLAG-Tag co-immunoprecipitation mass spectrometry experiments using FAIMS

Co-immunoprecipitation of proteins coupled to mass spectrometry is critical for the understanding of protein interaction networks. In instances where a suitable antibody is not available, it is common to graft synthetic tags onto a target protein sequence thereby allowing the use of commercially available antibodies for affinity purification. A common approach is through FLAG-Tag co-immunoprecipitation. To allow the selective elution of protein complexes, competitive displacement using a large molar excess of the tag peptides is often carried out. Yet, this creates downstream challenges for the mass spectrometry analysis due to the presence of large quantities of these peptides. Here, we demonstrate that Field Asymmetric Ion Mobility Spectrometry (FAIMS), a gas phase ion separation device prior to mass spectrometry analysis can be applied to FLAG-Tag co-immunoprecipitation experiments to increase the depth of protein coverage. By excluding these abundant tag peptides, we were able to observe deeper coverage of interacting proteins and as a result, deeper biological insights, without the need for additional sample handling or altering sample preparation protocols. SIGNIFICANCE: We have shown that application of FAIMS separation in the gas phase can increase the proteome coverage of Flag-Tagged co-immunoprecipitation mass spectrometry experiments versus one without FAIMS. We were able to observe deeper coverage of interacting proteins and as a result, deeper biological insights, without additional sample handling, fractionation, machine run time or modifying the sample preparation protocol.

Application of zero-phase digital filtering for effective denoising of field asymmetric waveform ion mobility spectrometry signal

RATIONALE

Field asymmetric waveform ion mobility spectrometry (FAIMS) has a great potential to become a portable technology for rapid detection of chemical and biological agents. However, the ion current signals, measured at the exit of the planar FAIMS directly, may contain different types of noises. The peak information in the FAIMS spectrum, such as the compensation voltage (CV) value at the maximum peak intensity (CV_P ) and the peak width at half maximum (W_h ), could not be accurately determined under the weak signal condition, which significantly limits the achievable instrument sensitivity, and there are no existing solutions to the problem.

METHODS

This study analyzed the noise type of FAIMS signal in detail, and three different signal processing algorithms, such as median filtering (MF), discrete wavelet transform (DWT), and zero-phase digital filtering (ZDF), were evaluated for their performance in denoising the FAIMS signal.

RESULTS

The results show that the standard deviation of CV_p obtained from the signal denoised using ZDF algorithm is at least 31.82% smaller as compared to using MF and DWT algorithms. The standard deviation of W_h is at least 45.45% smaller using ZDF algorithm. Moreover, only ZDF algorithm can keep the percentage error for the CV value of the denoised signal to be within 0.50 ± 0.47% of the true CV value, implying the effectiveness of ZDF algorithm in denoising while retaining the integrity of the signal.

CONCLUSIONS

The ZDF algorithm greatly reduces the analyte peak extraction error and improves the limit of detection in FAIMS measurements.

Molecular Mapping of Neutral Lipids Using Silicon Nanopost Arrays and TIMS Imaging Mass Spectrometry

We demonstrate the utility of combining silicon nanopost arrays (NAPA) and trapped ion mobility imaging mass spectrometry (TIMS IMS) for high spatial resolution and specificity mapping of neutral lipid classes in tissue. Ionization of neutral lipid species such as triglycerides (TGs), cholestryl esters (CEs), and hexosylceramides (HexCers) from biological tissues has remained a challenge for imaging applications. NAPA, a matrix-free laser desorption ionization substrate, provides enhanced ionization efficiency for the above-mentioned neutral lipid species, providing complementary lipid coverage to matrix-assisted laser desorption ionization (MALDI). The combination of NAPA and TIMS IMS enables imaging of neutral lipid species at 20 μm spatial resolution while also increasing molecular coverage greater than 2-fold using gas-phase ion mobility separations. This is a significant improvement with respect to sensitivity, specificity, and spatial resolution compared to previously reported imaging studies using NAPA alone. Improved specificity for neutral lipid analysis using TIMS IMS was shown using rat kidney tissue to separate TGs, CEs, HexCers, and phospholipids into distinct ion mobility trendlines. Further, this technology allowed for the separation of isomeric species, including mobility resolved isomers of Cer(d42:2) (m/z 686.585) with distinct spatial localizations measured in rat kidney tissue section.

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.

UVPD spectroscopy of differential mobility-selected prototropic isomers of protonated adenine

Two prototropic isomers of adenine are formed in an electrospray ion source and are resolved spatially in a differential mobility spectrometer before detection in a triple quadrupole mass spectrometer. Each isomer is gated in CV space before being trapped in the linear ion trap of the modified mass spectrometer, where they are irradiated by the tuneable output of an optical parametric oscillator and undergo photodissociation to form charged fragments with m/z 119, 109, and 94. The photon-normalised intensity of each fragmentation channel is measured and the action spectra for each DMS-gated tautomer are obtained. Our analysis of the action spectra, aided by calculated vibronic spectra and thermochemical data, allow us to assign the two signals in our measured ionograms to specific tautomers of protonated adenine.

Current status and future prospects for ion-mobility mass spectrometry in the biopharmaceutical industry

Detailed characterization of protein reagents and biopharmaceuticals is key in defining successful drug discovery campaigns, aimed at bringing molecules through different discovery stages up to development and commercialization. There are many challenges in this process, with complex and detailed analyses playing paramount roles in modern industry. Mass spectrometry (MS) has become an essential tool for characterization of proteins ever since the onset of soft ionization techniques and has taken the lead in quality assessment of biopharmaceutical molecules, and protein reagents, used in the drug discovery pipeline. MS use spans from identification of correct sequences, to intact molecule analyses, protein complexes and more recently epitope and paratope identification. MS toolkits could be incredibly diverse and with ever evolving instrumentation, increasingly novel MS-based techniques are becoming indispensable tools in the biopharmaceutical industry. Here we discuss application of Ion Mobility MS (IMMS) in an industrial setting, and what the current applications and outlook are for making IMMS more mainstream.

Detection of Triacetone Triperoxide (TATP) and Hexamethylene Triperoxide Diamine (HMTD) from the Gas Phase with Differential Ion Mobility Spectrometry (DMS)

One of the significant problems in the modern world is the detection of improvised explosives made of materials synthesized at home. Such compounds include triacetone triperoxide (TATP) and hexamethylene triperoxide diamine (HMTD). An attempt was made to construct an instrument allowing for the simultaneous detection of both compounds despite the large difference of vapor pressure: very high for TATP and very low for HMTD. The developed system uses differential ion mobility spectrometry (DMS) in combination with a specially designed gas sample injection system. The created system of detectors allowed for the detection of a high concentration of TATP and a very low concentration of HMTD. TATP detection was possible despite the presence of impurities—acetone remaining from the technological process and formed as a coproduct of diacetone diperoxide (DADP) synthesis. Ammonia added to the carrier gas improved the possibility of detecting the abovementioned explosives, reducing the intensity of the acetone signal. The obtained results were then compared with the detection capabilities of drift tube ion mobility spectrometer (DT-IMS), which has not made possible such detection as DMS.

The Effect of Soil Moisture on the Ability to Detect TNT Pairs from the Sand Layer in Order to Prevent Environmental Pollution and Groundwater

The aim of the study was to investigate the influence of sand bed moisture on TNT transport from under the sand layer. The MO-2M explosive vapor detector was used, the detection mechanism of which is based on the FAIMS method. In addition, it was determined after what time the detector alarm appears, signaling the presence of TNT vapors, and how it affects the thickness of the sand layer. The performed work allowed us to assess the suitability and possibly adapt the MO-2M detector to detect non-metal mines, which will help develop new application possibilities for this device. These tests can also be used to eliminate environmental contamination resulting from the deposition of explosives in the ground and the migration of harmful compounds to groundwater.

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.

Reaction Monitoring and Structural Characterisation of Coordination Driven Self-Assembled Systems by Ion Mobility-Mass Spectrometry

Nature creates exquisite molecular assemblies, required for the molecular-level functions of life, via self-assembly. Understanding and harnessing these complex processes presents an immense opportunity for the design and fabrication of advanced functional materials. However, the significant industrial potential of self-assembly to fabricate highly functional materials is hampered by a lack of knowledge of critical reaction intermediates, mechanisms, and kinetics. As we move beyond the covalent synthetic regime, into the domain of non-covalent interactions occupied by self-assembly, harnessing and embracing complexity is a must, and non-targeted analyses of dynamic systems are becoming increasingly important. Coordination driven self-assembly is an important subtype of self-assembly that presents several wicked analytical challenges. These challenges are "wicked" due the very complexity desired confounding the analysis of products, intermediates, and pathways, therefore limiting reaction optimisation, tuning, and ultimately, utility. Ion Mobility-Mass Spectrometry solves many of the most challenging analytical problems in separating and analysing the structure of both simple and complex species formed via coordination driven self-assembly. Thus, due to the emerging importance of ion mobility mass spectrometry as an analytical technique tackling complex systems, this review highlights exciting recent applications. These include equilibrium monitoring, structural and dynamic analysis of previously analytically inaccessible complex interlinked structures and the process of self-sorting. The vast and largely untapped potential of ion mobility mass spectrometry to coordination driven self-assembly is yet to be fully realised. Therefore, we also propose where current analytical approaches can be built upon to allow for greater insight into the complexity and structural dynamics involved in self-assembly.

Predicting lecithin concentration from differential mobility spectrometry measurements with linear regression models and neural networks

Differential mobility spectrometry (DMS) analysis of electrosurgical smoke can be used to distinguish cancerous and healthy tissues. Mass spectrometry studies of surgical smoke have revealed phospholipids as the key compounds enabling this discrimination. Lecithin is a mixture of phospholipids encountered in tissues. We hypothesized that DMS is capable of detecting and quantifying lecithin from water solution in headspace chamber, paving way for analysis of surgical smoke. We measured different lecithin concentrations in a biologically relevant range considering healthy and cancerous tissues with DMS and trained regression models to predict the analyte concentration. The models were internally cross-validated and externally validated. The best cross-validation results were obtained with convolutional neural networks, with root mean square error (RMSE) = 0.38 mg/ml. This is the first demonstration of estimation of analyte concentration from DMS measurements with neural networks. The best external validation results were acquired with sparse linear regression methods, with RMSE varying from 0.40 mg/ml to 0.41 mg/ml. The results demonstrate that DMS is sufficiently sensitive to detect biologically relevant changes in phospholipid concentration, potentially explaining its ability to detect cancerous tissue. In the future, we aim to reproduce the results by using surgical smoke as the medium. In this scenario, the complex background of surgical smoke will be the main challenge to overcome. Predicting concentration with neural networks also lays the foundation for wider analytical usage of DMS.

Recent technical progress in sample preparation and liquid-phase separation-mass spectrometry for proteomic analysis of mass-limited samples

Mass spectrometry (MS)-based proteomics has enabled the identification and quantification of thousands of proteins from complex proteomes in a single experiment. However, its performance for mass-limited proteome samples (e.g., single cells and tissue samples from laser capture microdissection) is still not satisfying. The development of novel proteomic methodologies with better overall sensitivity is vital. During the last several years, substantial technical progress has been achieved for the preparation and liquid-phase separation-MS characterization of mass-limited proteome samples. In this review, we summarize recent technological progress of sample preparation, liquid chromatography (LC)-MS, capillary zone electrophoresis (CZE)-MS and MS instrumentation for bottom-up proteomics of trace biological samples, highlight some exciting applications of the novel techniques for single-cell proteomics, and provide a very brief perspective about the field at the end.

Recent developments in the characterization of nucleic acids by liquid chromatography, capillary electrophoresis, ion mobility, and mass spectrometry (2010-2020)

The development of new strategies for the analysis of nucleic acids has gained momentum due to the increased interest in using these biomolecules as drugs or drug targets. The application of new mass spectrometry ion activation techniques and the optimization of separation methods including liquid chromatography, capillary electrophoresis, and ion mobility have allowed more detailed characterization of nucleic acids and oligonucleotide therapeutics including confirmation of sequence, localization of modifications and interaction sites, and structural analysis as well as identification of failed sequences and degradation products. This review will cover tandem mass spectrometry methods as well as the recent developments in liquid chromatography, capillary electrophoresis, and ion mobility coupled to mass spectrometry for the analysis of nucleic acids and oligonucleotides.

Multimodal Imaging Mass Spectrometry: Next Generation Molecular Mapping in Biology and Medicine

Imaging mass spectrometry has become a mature molecular mapping technology that is used for molecular discovery in many medical and biological systems. While powerful by itself, imaging mass spectrometry can be complemented by the addition of other orthogonal, chemically informative imaging technologies to maximize the information gained from a single experiment and enable deeper understanding of biological processes. Within this review, we describe MALDI, SIMS, and DESI imaging mass spectrometric technologies and how these have been integrated with other analytical modalities such as microscopy, transcriptomics, spectroscopy, and electrochemistry in a field termed multimodal imaging. We explore the future of this field and discuss forthcoming developments that will bring new insights to help unravel the molecular complexities of biological systems, from single cells to functional tissue structures and organs.