Differential mobility spectrometry: a valuable technology for analyzing challenging biological samples

Non-destructive method to classify walnut kernel freshness from volatile organic compound (VOC) emissions using gas chromatography-differential mobility spectrometry (GC-DMS) and machine learning analysis

Analysis of volatile organic compounds (VOCs) can be an effective strategy to inspect the quality of horticultural commodities and following their degradation. In this work, we report that VOCs emitted by walnuts can be studied using gas chromatography-differential mobility spectrometry (GC-DMS), and those GC-DMS data can be analyzed to predict the rancidity of walnuts, i.e., classify walnuts into grades of freshness. Walnut kernels were assigned a class n depending on their level of freshness as determined by a peroxide assay. VOC samples were analyzed using GC-DMS. From these VOC data, a partial least square regression (PLSR) model provided a freshness prediction value m , which corresponded to the rancid class n when m = n ± 0.5 . The PLSR model had an accuracy of 80% to predict walnut grade and demonstrated a minimal root mean squared error of 0.42 for the m response variables (representative of walnut grade) with the GC-DMS data. We also conducted gas chromatography-mass spectrometry (GC-MS) experiments to identify volatiles that emerged or were enhanced with more rancid walnuts. The findings of the GC-MS study of walnut VOCs align excellently with the GC-DMS study. Based on our results, we conclude that a GC-DMS device deployed with a pre-trained machine learning model can be a very effective device for classifying walnut grades in the industry.

Investigating Performance of the SLIM-Based High Resolution Ion Mobility Platform for Separation of Isomeric Phosphatidylcholine Species

Lipids are structurally diverse molecules that play a pivotal role in a plethora of biological processes. However, deciphering the biological roles of the specific lipids is challenging due to the existence of numerous isomers. This high chemical complexity of the lipidome is one of the major challenges in lipidomics research, as the traditional liquid chromatography-mass spectrometry (LC-MS) based approaches are often not powerful enough to resolve these isomeric and isobaric nuances within complex samples. Thus, lipids are uniquely suited to the benefits provided by multidimensional liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) analysis. However, many forms of lipid isomerism, including double-bond positional isomers and regioisomers, are structurally similar such that their collision cross section (CCS) differences are unresolvable via conventional IM approaches. Here we evaluate the performance of a high resolution ion mobility (HRIM) system based on structures for lossless ion manipulation (SLIM) technology interfaced to a high resolution quadrupole time-of-flight (QTOF) analyzer to address the noted lipidomic isomerism challenge. SLIM implements the traveling wave ion mobility technique along an ∼13 m ion path, providing longer path lengths to enable improved separation of isomeric features. We demonstrate the power of HRIM-MS to dissect isomeric PC standards differing only in double bond (DB) and stereospecific number (SN) positions. The partial separation of protonated DB isomers is significantly enhanced when they are analyzed as metal adducts. For sodium adducts, we achieve close to baseline separation of three different PC 18:1/18:1 isomers with different cis-double bond locations. Similarly, PC 18:1/18:1 (cis-9) can be resolved from the corresponding PC 18:1/18:1 (trans-9) form. The separation capacity is further enhanced when using silver ion doping, enabling the baseline separation of regioisomers that cannot be resolved when measured as sodium adducts. The sensitivity and reproducibility of the approach were assessed, and the performance for more complex mixtures was benchmarked by identifying PC isomers in total brain and liver lipid extracts.

Machine learning and signal processing assisted differential mobility spectrometry (DMS) data analysis for chemical identification

Differential mobility spectrometry (DMS)-based detectors are being widely studied to detect chemical warfare agents, explosives, chemicals, drugs and analyze volatile organic compounds (VOCs). The dispersion plots from DMS devices are complex to effectively analyze through visual inspection. In the current work, we adopted machine learning to differentiate pure chemicals and identify chemicals in a mixture. In particular, we observed the convolutional neural network algorithm exhibits excellent accuracy in differentiating chemicals in their pure forms while also identifying chemicals in a mixture. In addition, we propose and validate the magnitude-squared coherence (msc) between the DMS data of known chemical composition and that of an unknown sample can be sufficient to inspect the chemical composition of the unknown sample. We have shown that the msc-based chemical identification requires the least amount of experimental data as opposed to the machine learning approach.

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.

Rapid separation of cannabinoid isomer sets using differential mobility spectrometry and mass spectrometry

With legalization and decriminalization of cannabis in many parts of the world comes the need for rapid separation and quantitation of the psychoactive ingredients.

Meta-proteomic analysis of two mammoth's trunks by EVA technology and high-resolution mass spectrometry for an indirect picture of their habitat and the characterization of the collagen type I, alpha-1 and alpha-2 sequence

The recent paleoproteomic studies, including paleo-metaproteomic analyses, improved our understanding of the dietary of ancient populations, the characterization of past human diseases, the reconstruction of the habitat of ancient species, but also provided new insights into the phylogenetic relationships between extant and extinct species. In this respect, the present work reports the results of the metaproteomic analysis performed on the middle part of a trunk, and on the portion of a trunk tip tissue of two different woolly mammoths some 30,000 years old. In particular, proteins were extracted by applying EVA (Ethylene-Vinyl Acetate studded with hydrophilic and hydrophobic resins) films to the surface of these tissues belonging to two Mammuthus primigenus specimens, discovered in two regions located in the Russian Far East, and then investigated via a shotgun MS-based approach. This approach allowed to obtain two interesting results: (i) an indirect description of the habitat of these two mammoths, and (ii) an improved characterization of the collagen type I, alpha-1 and alpha-2 chains (col1a1 and col1a2). Sequence characterization of the col1a1 and col1a2 highlighted some differences between M. primigenius and other Proboscidea together with the identification of three (two for col1a1, and one for col1a2) potentially diagnostic amino acidic mutations that could be used to reliably distinguish the Mammuthus primigenius with respect to the other two genera of elephantids (i.e., Elephas and Loxodonta), and the extinct American mastodon (i.e., Mammut americanum). The results were validated through the level of deamidation and other diagenetic chemical modifications of the sample peptides, which were used to discriminate the "original" endogenous peptides from contaminant ones. The data have been deposited to the ProteomeXchange with identifier < PXD029558 > .

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.

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.

MASS SPECTROMETRY IN VIROLOGICAL SCIENCES

Virology, as a branch of the life sciences, discovered mass spectrometry (MS) to be the pivotal tool around two decades ago. The technique unveiled the complex network of interactions between the living world of pro- and eukaryotes and viruses, which delivered "a piece of bad news wrapped in protein" as defined by Peter Medawar, Nobel Prize Laureate, in 1960. However, MS is constantly evolving, and novel approaches allow for a better understanding of interactions in this micro- and nanoworld. Currently, we can investigate the interplay between the virus and the cell by analyzing proteomes, interactomes, virus-cell interactions, and search for the compounds that build viral structures. In addition, by using MS, it is possible to look at the cell from the broader perspective and determine the role of viral infection on the scale of the organism, for example, monitoring the crosstalk between infected tissues and the immune system. In such a way, MS became one of the major tools for the modern virology, allowing us to see the infection in the context of the whole cell or the organism. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Quantitation of Urinary Acylcarnitines by DMS-MS/MS Uncovers the Effects of Total Body Irradiation in Cancer Patients

Acylcarnitines have been identified in human and animal metabolomic-profiling studies as urinary markers of radiation exposure, a result which is consistent with their cytoprotective effects and roles in energy metabolism. In the present work, a rapid method for quantitation of the more abundant acylcarnitines in human urine is developed using a valuable set of samples from cancer patients who received total body irradiation (TBI) at Memorial Sloan Kettering Cancer Center. The method uses solid-phase extraction (SPE) processing followed by differential mobility spectrometry (DMS with ethyl acetate modifier) tandem mass spectrometry (ESI-DMS-MS/MS) with deuterated internal standards. The analyzed human urine samples were collected from 38 individual patients at three time points over 24 h during and after the course of radiation treatment, a design allowing each patient to act as their own control and creatinine normalization. Creatinine-normalized concentrations for nine urinary acylcarnitine (acyl-CN) species are reported. Six acyl-CN species were reduced at the 6 h point. Acetylcarnitine (C2:0-CN) and valerylcarnitine (C5:0-CN) showed recovery at 24 h, but none of the other acyl-CN species showed recovery at that point. Levels of three acyl-CN species were not significantly altered by radiation. This rapid quantitative method for clinical samples covers the short- and medium-chain acylcarnitines and has the flexibility to be expanded to cover additional radiation-linked metabolites. The human data presented here indicates the utility of the current approach as a rapid, quantitative technique with potential applications by the medical community, by space research laboratories concerned with radiation exposure, and by disaster response groups.

Differential mobility spectrometry classification of bacteria

Aim: Rapid identification of bacteria would facilitate timely initiation of therapy and improve cost–effectiveness of treatment. Traditional methods (culture, PCR) require reagents, consumables and hours to days to complete the identification. In this study, we examined whether differential mobility spectrometry could classify most common bacterial species, genera and between Gram status within minutes. Materials & methods: Cultured bacterial sample gaseous headspaces were measured with differential mobility spectrometry and data analyzed using k-nearest-neighbor and leave-one-out cross-validation. Results: Differential mobility spectrometry achieved a correct classification rate 70.7% for all bacterial species. For bacterial genera, the rate was 77.6% and between Gram status, 89.1%. Conclusion: Largest difficulties arose in distinguishing bacteria of the same genus. Future improvement of the sensor characteristics may improve the classification accuracy.

Integration of flux measurements and pharmacological controls to optimize stable isotope-resolved metabolomics workflows and interpretation

Stable isotope-resolved metabolomics (SIRM) provides information regarding the relative activity of numerous metabolic pathways and the contribution of nutrients to specific metabolite pools; however, SIRM experiments can be difficult to execute, and data interpretation is challenging. Furthermore, standardization of analytical procedures and workflows remain significant obstacles for widespread reproducibility. Here, we demonstrate the workflow of a typical SIRM experiment and suggest experimental controls and measures of cross-validation that improve data interpretation. Inhibitors of glycolysis and oxidative phosphorylation as well as mitochondrial uncouplers serve as pharmacological controls, which help define metabolic flux configurations that occur under well-controlled metabolic states. We demonstrate how such controls and time course labeling experiments improve confidence in metabolite assignments as well as delineate metabolic pathway relationships. Moreover, we demonstrate how radiolabeled tracers and extracellular flux analyses integrate with SIRM to improve data interpretation. Collectively, these results show how integration of flux methodologies and use of pharmacological controls increase confidence in SIRM data and provide new biological insights.

Application of differential mobility-mass spectrometry for untargeted human plasma metabolomic analysis

Differential mobility spectrometry (DMS) has been gaining popularity in small molecule analysis over the last few years due to its selectivity towards a variety of isomeric compounds. While DMS has been utilized in targeted liquid chromatography-mass spectrometry (LC-MS), its use in untargeted discovery workflows has not been systematically explored. In this contribution, we propose a novel workflow for untargeted metabolomics based solely on DMS separation in a clinically relevant chronic kidney disease (CKD) patient population. We analyzed ten plasma samples from early- and late-stage CKD patients. Peak finding, alignment, and filtering steps performed on the DMS-MS data yielded a list of 881 metabolic features (unique mass-to-charge and migration time combinations). Differential analysis by CKD patient group revealed three main features of interest. One of them was putatively identified as bilirubin based on high-accuracy MS data and comparison of its optimum compensation voltage (COV) with that of an authentic standard. The DMS-MS analysis was four times faster than a typical HPLC-MS run, which suggests a potential for the utilization of this technique in screening studies. However, its lower separation efficiency and reduced signal intensity make it less suitable for low-abundant features. Fewer features were detected by the DMS-based platform compared with an HPLC-MS-based approach, but importantly, the two approaches resulted in different features. This indicates a high degree of orthogonality between HPLC- and DMS-based approaches and demonstrates the need for larger studies comparing the two techniques. The workflow described here can be adapted for other areas of metabolomics and has a value as a prescreening method to develop semi-targeted workflows and as a faster alternative to HPLC in large biomedical studies.

Quadrupole Time-of-Flight Mass Spectrometry: A Paradigm Shift in Toxicology Screening Applications

The screening of biological samples for the presence of illicit or legal substances is an important frontline tool in both clinical and forensic toxicology. In the clinical setting, drug screening is a useful tool for the clinician in improving patient care and guiding treatment. Analytical approaches for the screening of drugs in biological samples are extensive and well documented, though many rapid screening techniques often lack appropriate sensitivity and specificity, requiring careful clinical interpretation. The continuous emergence of new psychoactive substances presents a considerable analytical challenge in maintaining up-to-date methods for the detection of relevant drugs. Adapting and validating methods for the detection of new substances can be a complicated and costly undertaking. There is also a considerable lag time between the emergence of new drugs and the release of commercial assays for detection. Quadrupole time-of-flight mass spectrometry (Q-TOF-MS) has gained considerable attention over the last decade as an analytical technique that is capable of meeting the challenges of a rapidly changing drug landscape. Exhibiting both high sensitivity and specificity in drug detection, Q-TOF-MS also allows methods to be rapidly updated for newly emerging psychoactive agents. The coupling of Q-TOF-MS with techniques such as liquid or gas chromatography can provide both rapid and comprehensive screening solutions that are gaining popularity in the clinical laboratory setting.

Addressing Complex Matrix Interference Improves Multiplex Food Allergen Detection by Targeted LC-MS/MS

The frequent use of precautionary food allergen labeling (PAL) such as "may contain" frustrates allergic individuals who rely on such labeling to determine whether a food is safe to consume. One technique to study whether foods contain allergens is targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) employing scheduled multiple reaction monitoring (MRM). However, the applicability of a single MRM method to many commercial foods is unknown as complex and heterogeneous interferences derived from the unique composition of each food matrix can hinder quantification of trace amounts of allergen contamination. We developed a freely available, open source software package MAtrix-Dependent Interference Correction (MADIC) to identify interference and applied it with a method targeting 14 allergens. Among 84 unique food products, we found patterns of allergen contamination such as wheat in grains, milk in chocolate-containing products, and soy in breads and corn flours. We also found additional instances of contamination in products with and without PAL as well as highly variable soy content in foods containing only soybean oil and/or soy lecithin. These results demonstrate the feasibility of applying LC-MS/MS to a variety of food products with sensitive detection of multiple allergens in spite of variable matrix interference.

Recommendations for reporting ion mobility Mass Spectrometry measurements

Here we present a guide to ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties of mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K0 ) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N; (ii) ion mobility does not measure molecular surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model; (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort toward establishing primary standards and reference materials for ion mobility, and provides recommendations to do so. © 2019 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Differential mobility spectrometry (DMS) reveals the elevation of urinary acetylcarnitine in non-human primates (NHPs) exposed to radiation

Acetylcarnitine has been identified as one of several urinary biomarkers indicative of radiation exposure in adult rhesus macaque monkeys (non-human primates, NHPs). Previous work has demonstrated an up-regulated dose-response profile in a balanced male/female NHP cohort. As a contribution toward the development of metabolomics-based radiation biodosimetry in human populations and other applications of acetylcarnitine screening, we have developed a quantitative, high-throughput method for the analysis of acetylcarnitine. We employed the Sciex SelexIon DMS-MS/MS QTRAP 5500 platform coupled to flow injection analysis (FIA), thereby allowing for fast analysis times of less than 0.5 minutes per injection with no chromatographic separation. Ethyl acetate is used as a DMS modifier to reduce matrix chemical background. We have measured NHP urinary acetylcarnitine from the male cohorts that were exposed to the following radiation levels: control, 2, 4, 6, 7, and 10 Gy. Biological variability, along with calibration accuracy of the FIA-DMS-MS/MS method, indicates LOQ of 20 μM, with observed biological levels on the order of 600 μM and control levels near 10 μM. There is an apparent onset of intensified response in the transition from 6 to 10 Gy. The results demonstrate that FIA-DMS-MS/MS is a rapid, quantitative technique that can be utilized for the analysis of urinary biomarker levels for radiation biodosimetry.

Integration of paper spray ionization high-field asymmetric waveform ion mobility spectrometry for forensic applications

RATIONALE

Paper spray ionization (PSI) is an attractive ambient ionization source for mass spectrometry (MS) since it allows the combination of surface sampling and ionization. The minimal sample preparation inherent in this approach greatly reduces the time needed for analysis. However, the ions generated from interfering compounds in the sample and the paper substrate may interfere with the analyte ions. Therefore, the integration of PSI with high-field asymmetric ion mobility spectrometry (FAIMS) is of significant interest since it should reduce the background ions entering the mass analyzer without complicating the analysis or increasing analysis time. Here we demonstrate the integration of PSI with FAIMS/MS and its potential for analysis of samples of forensic interest.

METHODS

In this work, the parameters that can influence the integration, including sampling and ionization by paper spray, the FAIMS separation of analytes from each other and background interferences, and the length of time that a usable signal can be observed for explosives on paper, were evaluated with the integrated system.

RESULTS

In the negative ion analysis of 2,4,6-trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), and 1,3,5-trinitroperhydro-1,3,5-triazine (RDX), amounts as low as 1 ng on paper were readily observed. The successful positive ion separation of a set of illicit drugs including heroin, methamphetamine, and cocaine was also achieved. In addition, the positive ion analysis of the chemical warfare agent simulants dimethyl methylphosphonate (DMMP) and diisopropyl methylphosphonate (DIMP) was evaluated.

CONCLUSIONS

The integration of PSI-FAIMS/MS was demonstrated for the analyses of explosives in negative ion mode and for illicit drugs and CW simulants in positive mode. Paper background ions that could interfere with these analyses were separated by FAIMS. The compensation voltage of an ion obtained by FAIMS provided an additional identification parameter to be combined with the mass spectrum for each analyte.

Probing the application range and selectivity of a differential mobility spectrometry-mass spectrometry platform for metabolomics

Metabolomics applications of differential mobility spectrometry (DMS)-mass spectrometry (MS) have largely concentrated on targeted assays and the removal of isobaric or chemical interferences from the signals of a small number of analytes. In the work reported here, we systematically investigated the application range of a DMS-MS method for metabolomics using more than 800 authentic metabolite standards as the test set. The coverage achieved with the DMS-MS platform was comparable to that achieved with chromatographic methods. High orthogonality was observed between hydrophilic interaction liquid chromatography and the 2-propanol-mediated DMS separation, and previously observed similarities were confirmed for the DMS platform and reversed-phase liquid chromatography. We describe the chemical selectivity observed for selected subsets of the metabolite test set, such as lipids, amino acids, nucleotides, and organic acids. Furthermore, we rationalize the behavior and separation of isomeric aromatic acids, bile acids, and other metabolites. Graphical abstract Differential mobility spectrometry-mass spectrometry (DMS-MS) facilitates rapid separation of metabolites of similar mass-to-charge ratio by distributing them across the compensation voltage range on the basis of their different molecular structures.

Optimization of a New Aerodynamic Cylindrical FAIMS Device for Small Molecule Analysis

The implementation of an aerodynamic mechanism to improve ion sampling between nanoelectrospray (n-ESI) and FAIMS was recently reported for proteomic analyses. This investigation explores the new FAIMS interface for small molecule analysis at high liquid flow rates and includes an examination of key differences in ionization between heated-ESI (HESI) and n-ESI. The sheath gas, critical for desolvation with HESI, affects FAIMS operation as higher FAIMS gas flow rates are required to achieve sufficient desolvation. Gas flow rate experiments also uncovered m/z discrimination with the conventional design as larger (slower moving) m/z ions experienced larger signal intensity losses than smaller m/z ions due to the desolvation gas flow having a greater drag effect on slower moving ions. The modified inlet in new FAIMS dampens the gas drag, making the HESI source more amenable as less m/z bias and significantly lower %RSD values were observed. Furthermore, a larger radius inner electrode in new FAIMS enables significantly higher E/N (electric field/number gas density) to be achieved using the existing waveform generator. Thus, new FAIMS signal intensities using only nitrogen improved 1.25- to 2-fold compared with the conventional design and 50% helium. Adding helium to the new FAIMS gave no significant improvements. The larger inner electrode also decreased ion focusing capabilities, and the effect on peak separation and ion intensity was examined in detail. The peak capacity of new FAIMS was approximately double that of conventional FAIMS; separation of seven low m/z ions gave a peak capacity of 37.7 using the gas additive 2-propanol. Graphical Abstract ᅟ.

Determination of triacylglycerol regioisomers using differential mobility spectrometry

RATIONALE

Triacylglycerols (TG) contain three fatty acyls attached to the glycerol backbone in stereochemically numbered positions sn-1, 2 and 3. Isobaric TG with exchanged fatty acyl chains in positions sn-1/3 vs. sn-2 are referred to as regioisomers and the determination of their regioisomeric ratios is important for nutrition purposes.

METHODS

Differential mobility spectrometry (DMS) coupled to electrospray ionization mass spectrometry (ESI-MS) is applied for the separation of simple unsaturated TG regioisomers extracted from porcine adipose tissue using their silver-ion molecular adducts.

RESULTS

Four pairs of TG regioisomers containing combinations of unsaturated and saturated fatty acyl chains are successfully separated using DMS with 1-butanol or 1-propanol as the chemical modifier. Various experimental parameters are carefully optimized, such as the separation and compensation voltages applied to DMS electrodes, the type and flow rate of chemical modifier and the dwell time of analyte ions in the DMS cell. The optimized DMS approach is used for the characterization of TG regioisomers in less than one minute, compared to tens of minutes typical for silver-ion or reversed-phase high-performance liquid chromatography/mass spectrometry approaches.

CONCLUSIONS

The application of this method for the characterization of TG regioisomers in porcine adipose tissue shows the method suitability for analyses of other animal fats.

Using differential mobility spectrometry to measure ion solvation: an examination of the roles of solvents and ionic structures in separating quinoline-based drugs

Understanding the mechanisms and energetics of ion solvation using differential mobility spectrometry.