Selection and generation of waveforms for differential mobility spectrometry

Application and integration of deep learning in FAIMS for identifying acetone concentration

In practical applications, analytical instruments are used for both qualitative and quantitative analysis. However, for high-field asymmetric-waveform ion mobility spectrometry (FAIMS), most studies to date have been focused on the qualitative analysis of substances, with limited research on quantitative analysis. Explored here is the feasibility of using deep learning in FAIMS for quantitative analysis, aided by redesigning the FAIMS upper computer. Integrating spectrum creation and deep learning analysis into the FAIMS upper computer boosts the processing and analysis of FAIMS data, laying a foundation for applying FAIMS practically. For analysis using image processing, multiple FAIMS spectral lines obtained under different conditions are converted into a three-dimensional thermodynamic map known as a FAIMS spectrum, and multiple FAIMS spectrum are preprocessed to obtain the data set of this experiment. The principles of partial-least-squares regression and the XGBoost and ResNeXt models are introduced in detail, and the data are analyzed using these models, while exploring the effects of different model parameters and determining their optimal values. The experimental results show that the pre-trained ResNeXt deep learning model performs the best on the test set, with a root mean square error of 0.86 mg/mL, indicating the potential of deep learning in realizing quantitative analysis of substances in FAIMS.

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

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

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.

Kinetics in DMS: Modeling Clustering and Declustering Reactions

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

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.

Identification of Specific Substances in the FAIMS Spectra of Complex Mixtures Using Deep Learning

High-field asymmetric ion mobility spectrometry (FAIMS) spectra of single chemicals are easy to interpret but identifying specific chemicals within complex mixtures is difficult. This paper demonstrates that the FAIMS system can detect specific chemicals in complex mixtures. A homemade FAIMS system is used to analyze pure ethanol, ethyl acetate, acetone, 4-methyl-2-pentanone, butanone, and their mixtures in order to create datasets. An EfficientNetV2 discriminant model was constructed, and a blind test set was used to verify whether the deep-learning model is capable of the required task. The results show that the pre-trained EfficientNetV2 model completed convergence at a learning rate of 0.1 as well as 200 iterations. Specific substances in complex mixtures can be effectively identified using the trained model and the homemade FAIMS system. Accuracies of 100%, 96.7%, and 86.7% are obtained for ethanol, ethyl acetate, and acetone in the blind test set, which are much higher than conventional methods. The deep learning network provides higher accuracy than traditional FAIMS spectral analysis methods. This simplifies the FAIMS spectral analysis process and contributes to further development of FAIMS systems.

Identification and quantification of amino acids and related compounds based on Differential Mobility Spectrometry

A new metabolite descriptor allowing fast quantification for the diagnosis of metabolic diseases.

A First Principle Model of Differential Ion Mobility: the Effect of Ion-Solvent Clustering

The use of differential mobility spectrometry (DMS) as a separation tool prior to mass analysis has increased in popularity over the years. However, the fundamental principles behind the difference between high- and low-field mobility is still a matter of debate-especially regarding the strong impact of solvent molecules added to the gas phase in chemically modified DMS environments. In this contribution, we aim to present a thorough model for the determination of the ion mobility over a wide range of field strengths and subsequent calculation of DMS dispersion plots. Our model relies on first principle calculations only, incorporating the modeling of the "hard-sphere" mobility, the change in CCS with field strength, and the degree of clustering of solvent molecules to the ion. We show that all three factors have to be taken into account to qualitatively predict dispersion plots. In particular, type A behavior (i.e., strong clustering) in DMS can only be explained by a significant change of the mean cluster size with field strengths. The fact that our model correctly predicts trends between differently strong binding solvents, as well as the solvent concentration and the background gas temperature, highlights the importance of clustering for differential mobility.

Quantitation of Cyclosporin A in Cell Culture Media by Differential Mobility Mass Spectrometry (DMS-MS/MS)

Cell permeability is an important factor in determining the bioavailability of therapeutics that is usually measured by cell culture testing. The concentration of pharmaceutical in a medium such as Hank's Balanced Salt Solution with HEPES organic buffer (HBSS-HEPES) is measured at a series of time points, making simplicity and high throughput of the analytical method important characteristics. We report an electrospray differential mobility spectrometry mass spectrometry method (nanoESI-DMS-MS) for the rapid determination of cyclosporin A (CsA, cyclosporine) concentration in such a buffer. DMS technology provides gas phase atmospheric pressure ion filtration for small-molecule bioanalytical methods that suppresses interfering ions and reduces chemical noise, without the use of chromatography. This allows simplified sample preparation, fast calibration curve development, and shortened analysis times. It has also been noted that the DMS prefilter can reduce contamination of the mass spectrometer by salts, thereby extending mass spectrometer system uptime.In the application described here, DMS-MS/MS is applied to cyclosporine A (CsA) in cell medium. Sample preparation is limited to dilution with an ammonium acetate-methanol-water mobile phase and the addition of CsA-d4 internal standard. The isotope ratio data are obtained in DMS-MS MRM mode observing NH₃ loss from the ammonium adduct of the two species. A calibration curve with high linearity (R² = 0.998) is rapidly obtained with nearly zero intercept, while it was found that a liquid chromatography LC-MS method required a preliminary SPE step to obtain a linear calibration curve. The time for data acquisition in the DMS-MS MRM method with flow injection (FIA) or infusion introduction at ESI flow of 400 nL/min is typically 30 s leading to a cycle time of less than 1 min.

Machine Vision Methods, Natural Language Processing, and Machine Learning Algorithms for Automated Dispersion Plot Analysis and Chemical Identification from Complex Mixtures

Gas-phase trace chemical detection techniques such as ion mobility spectrometry (IMS) and differential mobility spectrometry (DMS) can be used in many settings, such as evaluating the health condition of patients or detecting explosives at airports. These devices separate chemical compounds in a mixture and provide information to identify specific chemical species of interest. Further, these types of devices operate well in both controlled lab environments and in-field applications. Frequently, the commercial versions of these devices are highly tailored for niche applications (e.g., explosives detection) because of the difficulty involved in reconfiguring instrumentation hardware and data analysis software algorithms. In order for researchers to quickly adapt these tools for new purposes and broader panels of chemical targets, it is critical to develop new algorithms and methods for generating libraries of these sensor responses. Microelectromechanical system (MEMS) technology has been used to fabricate DMS devices that miniaturize the platforms for easier deployment; however, concurrent advances in advanced data analytics are lagging. DMS generates complex three-dimensional dispersion plots for both positive and negative ions in a mixture. Although simple spectra of single chemicals are straightforward to interpret (both visually and via algorithms), it is exceedingly challenging to interpret dispersion plots from complex mixtures with many chemical constituents. This study uses image processing and computer vision steps to automatically identify features from DMS dispersion plots. We used the bag-of-words approach adapted from natural language processing and information retrieval to cluster and organize these features. Finally, a support vector machine (SVM) learning algorithm was trained using these features in order to detect and classify specific compounds in these represented conceptualized data outputs. Using this approach, we successfully maintain a high level of correct chemical identification, even when a gas mixture increases in complexity with interfering chemicals present.

Ultra-high-resolution ion mobility spectrometry-current instrumentation, limitations, and future developments

With recent advances in ionization sources and instrumentation, ion mobility spectrometers (IMS) have transformed from a detector for chemical warfare agents and explosives to a widely used tool in analytical and bioanalytical applications. This increasing measurement task complexity requires higher and higher analytical performance and especially ultra-high resolution. In this review, we will discuss the currently used ion mobility spectrometers able to reach such ultra-high resolution, defined here as a resolving power greater than 200. These instruments are drift tube IMS, traveling wave IMS, trapped IMS, and field asymmetric or differential IMS. The basic operating principles and the resulting effects of experimental parameters on resolving power are explained and compared between the different instruments. This allows understanding the current limitations of resolving power and how ion mobility spectrometers may progress in the future. Graphical abstract.

DMS as an orthogonal separation to LC/ESI/MS/MS for quantifying isomeric cerebrosides in plasma and cerebrospinal fluid

Cerebrosides, including glucosylceramides (GlcCers) and galactosylceramides (GalCers), are important membrane components of animal cells with deficiencies resulting in devastating lysosomal storage disorders. Their quantification is essential for disease diagnosis and a better understanding of disease mechanisms. The simultaneous quantification of GlcCer and GalCer isomers is, however, particularly challenging due to their virtually identical structures. To address this challenge, we developed a new LC/MS-based method using differential ion mobility spectrometry (DMS) capable of rapidly and reproducibly separating and quantifying isomeric cerebrosides in a single run. We show that this LC/ESI/DMS/MS/MS method exhibits robust quantitative performance within an analyte concentration range of 2.8-355 nM. We further report the simultaneous quantification of nine GlcCers (16:0, 18:0, 20:0, 22:0, 23:0, 24:1, 24:0, 25:0, and 26:0) and five GalCers (16:0, 22:0, 23:0, 24:1, and 24:0) molecular species in human plasma, as well as six GalCers (18:0, 22:0, 23:0, 24:1, 24:0 and 25:0) and two GlcCers (24:1 and 24:0) in human cerebrospinal fluid. Our method expands the potential of DMS technology in the field of glycosphingolipid analysis for both biomarker discovery and drug screening by enabling the unambiguous assignment and quantification of cerebroside lipid species in biological samples.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Variables Affecting the Internal Energy of Peptide Ions During Separation by Differential Ion Mobility Spectrometry

Differential ion mobility spectrometry (DIMS) devices separate ions on the basis of differences in ion mobility in low and high electric fields, and can be used as a stand-alone analytical method or as a separation step before further analysis. As with other ion mobility separation techniques, the ability of DIMS separations to retain the structural characteristics of analytes has been of concern. For DIMS separations, this potential loss of ion structure originates from the fact that the separations occur at atmospheric pressure and the ions, during their transit through the device, undergo repeated collisions with the DIMS carrier gas while being accelerated by the electric field. These collisions have the ability to increase the internal energy distribution of the ions, which can cause isomerization or fragmentation. The increase in internal energy of the ions is based on a number of variables, including the dispersion field and characteristics of the carrier gas such as temperature and composition. The effects of these parameters on the intra-DIMS fragmentation of multiply charged ions of the peptides bradykinin (RPPGFSPFR) and GLISH are discussed herein. Furthermore, similarities and differences in the internal energy deposition that occur during collisional activation in tandem mass spectrometry experiments are discussed, as the fragmentation pathways accessed by both are similar. Graphical Abstract ᅟ.

Maximizing Ion Transmission in Differential Mobility Spectrometry

We provide modeling and experimental data describing the dominant ion-loss mechanisms for differential mobility spectrometry (DMS). Ion motion is considered from the inlet region of the mobility analyzer to the DMS exit, and losses resulting from diffusion to electrode surfaces, insufficient effective gap, ion fragmentation, and fringing field effects are considered for a commercial DMS system with 1-mm gap height. It is shown that losses due to diffusion and radial oscillations can be minimized with careful consideration of residence time, electrode spacing, gas flow rate, and waveform frequency. Fragmentation effects can be minimized by limitation of the separation field. When these parameters were optimized, fringing field effects at the DMS inlet contributed the most to signal reduction. We also describe a new DMS cell configuration that improves the gas dynamics at the mobility cell inlet. The new cell provides a gas jet that decreases the residence time for ions within the fringing field region, resulting in at least twofold increase in ion signal as determined by experimental data and simulations. Graphical Abstract ᅟ.

Increased Ion Transmission for Differential Ion Mobility Combined with Mass Spectrometry by Implementation of a Flared Inlet Capillary

Differential ion mobility spectrometry (DIMS) is capable of separating components of complex mixtures prior to mass spectrometric analysis, thereby increasing signal-to-noise and signal-to-background ratios on millisecond timescales. However, adding a DIMS device to the front end of a mass spectrometer can reduce the signal intensity of subsequent mass spectrometric analysis. This is a result, in part, of ions lost due to inefficient transfer of ions from the DIMS device through the aperture leading into the mass spectrometer. This problem of transferring ions can be at least partially corrected by modifying the front end of the inlet capillary leading to the vacuum of the mass spectrometer. The inner diameter of the ion-sampling end of the inlet capillary was enlarged by drilling into the face. This results in a conical flare at the front end of the capillary, while the other end of the capillary remains unmodified. These flared capillaries allow for a greater number of ions from the DIMS device to be sampled relative to the unmodified standard capillary. Four flare dimensions were tested, differing by the angle between the wall of the flare and the outer wall of the inlet capillary. All flared capillaries showed greater signal intensity than the standard capillary with a DIMS device present without reducing the resolving power. It was also observed that the signal intensity increased as the flare angle decreased. The flared capillary with the smallest flare angle showed greater than a fivefold increase in signal intensity compared with the standard capillary. Graphical Abstract ᅟ.

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure. Graphical Abstract ᅟ.

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

This review of differential mobility spectrometry focuses primarily on mass spectrometry coupling, starting with the history of the development of this technique in the Soviet Union. Fundamental principles of the separation process are covered, in addition to efforts related to design optimization and advancements in computer simulations. The flexibility of differential mobility spectrometry design features is explored in detail, particularly with regards to separation capability, speed, and ion transmission. 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:687-737, 2016.

Supervised Semi-Automated Data Analysis Software for Gas Chromatography / Differential Mobility Spectrometry (GC/DMS) Metabolomics Applications

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

Lifetimes and stabilities of familiar explosive molecular adduct complexes during ion mobility measurements

Trapped ion mobility spectrometry coupled to mass spectrometry (TIMS-MS) was utilized for the separation and identification of familiar explosives in complex mixtures. For the first time, molecular adduct complex lifetimes, relative stability, binding energies and candidate structures are reported for familiar explosives. Experimental and theoretical results showed that the adduct size and reactivity, complex binding energy and the explosive structure tailor the stability of the molecular adduct complex. The flexibility of TIMS to adapt the mobility separation as a function of the molecular adduct complex stability (i.e., short or long IMS experiments/low or high IMS resolution) permits targeted measurements of explosives in complex mixtures with high confidence levels.

Improved Differential Ion Mobility Separations Using Linked Scans of Carrier Gas Composition and Compensation Field

Differential ion mobility spectrometry (DIMS) separates ions based on differences in their mobilities in low and high electric fields. When coupled to mass spectrometric analyses, DIMS has the ability to improve signal-to-background by eliminating isobaric and isomeric compounds for analytes in complex mixtures. DIMS separation power, often measured by resolution and peak capacity, can be improved through increasing the fraction of helium in the nitrogen carrier gas. However, because the mobility of ions is higher in helium, a greater number of ions collide with the DIMS electrodes or housing, yielding losses in signal intensity. To take advantage of the benefits of helium addition on DIMS separations and reduce ion losses, linked scans were developed. In a linked scan the helium content of the carrier gas is reduced as the compensation field is increased. Linked scans were compared with conventional compensation field scans with constant helium content for the protein ubiquitin and a tryptic digest of bovine serum albumin (BSA). Linked scans yield better separation of ubiquitin charge states and enhanced peak capacities for the analysis of BSA compared with compensation field scans with constant helium carrier gas percentages. Linked scans also offer improved signal intensity retention in comparison to compensation field scans with constant helium percentages in the carrier gas.

Review on ion mobility spectrometry. Part 2: hyphenated methods and effects of experimental parameters

Ion Mobility Spectrometry (IMS) is a widely used and 'well-known' technique of ion separation in the gaseous phase based on the differences of ion mobilities under an electric field. This technique has received increased interest over the last several decades as evidenced by the pace and advances of new IMS devices available. In this review we explore the hyphenated techniques that are used with IMS, specifically mass spectrometry as an identification approach and a multi-capillary column as a pre-separation approach. Also, we will pay special attention to the key figures of merit of the ion mobility spectrum and how data sets are treated, and the influences of the experimental parameters on both conventional drift time IMS (DTIMS) and miniaturized IMS also known as high Field Asymmetric IMS (FAIMS) in the planar configuration. The present review article is preceded by a companion review article which details the current instrumentation and contains the sections that configure both conventional DTIMS and FAIMS devices. These reviews will give the reader an insightful view of the main characteristics and aspects of the IMS technique.

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.

Differential ion mobility spectrometry coupled to tandem mass spectrometry enables targeted leukemia antigen detection

Differential ion mobility spectrometry (DIMS) can be used as a filter to remove undesired background ions from reaching the mass spectrometer. The ability to use DIMS as a filter for known analytes makes DIMS coupled to tandem mass spectrometry (DIMS-MS/MS) a promising technique for the detection of cancer antigens that can be predicted by computational algorithms. In experiments using DIMS-MS/MS that were performed without the use of high-performance liquid chromatography (HPLC), a predicted model antigen, GLR (FLSSANEHL), was detected at a concentration of 10 pM (20 amol) in a mixture containing 94 competing model peptide antigens, each at a concentration of 1 μM. Without DIMS filtering, the GLR peptide was undetectable in the mixture even at 100 nM. Again, without using HPLC, DIMS-MS/MS was used to detect 2 of 3 previously characterized antigens produced by the leukemia cell line U937.A2. Because of its sensitivity, a targeted DIMS-MS/MS methodology can likely be used to probe for predicted cancer antigens from cancer cell lines as well as human tumor samples.

Description of gas-phase ion/neutral interactions in differential ion mobility spectrometry: CV prediction using calibration runs

Differential ion mobility spectrometry (DMS) coupled to mass spectrometry is increasingly used in both quantitative analyses of biological samples and as a means of removing background interferences for enhanced selectivity and improved quality of mass spectra. However, DMS separation efficiency using dry inert gases often lacks the required selectivity to achieve baseline separation. Polar gas-phase modifiers such as alcohols are therefore frequently employed to improve selectivity via clustering/declustering processes. The choice of an optimal modifier currently relies on trial and error experiments, making method development a tedious activity. It was the goal of this study to establish a means of CV prediction for compounds using a homologous series of alcohols as gas-phase modifiers. This prediction was based on linear regression of compensation voltages of two calibration runs for the alcohols with the lowest and the highest molecular weights and readily available descriptors such as proton affinity and gas phase acidity of the modifier molecules. All experiments were performed on a commercial quadrupole linear ion trap mass spectrometer equipped with a DMS device between electrospray ionization source and entrance quadrupole lens. We evaluated our approach using a homologous series of 4-alkylbenzoic acids and a selection of 23 small molecules of high chemical diversity. Predicted CV values typically deviated from the experimentally determined values by less than 0.5 V. Several test compounds changed their ion mobility behavior for the investigated gas phase modifiers (e.g., from type B to type A) and thus could thus not be evaluated.

Ion-molecule clustering in differential mobility spectrometry: lessons learned from tetraalkylammonium cations and their isomers

Differential mobility spectrometry (DMS) can distinguish ions based upon the differences in their high- and low-field ion mobilities as they experience the asymmetric waveform applied to the DMS cell. These mobilities are known to be influenced by the ions' structure, m/z, and charge distribution (i.e., resonance structures) within the ions themselves, as well as by the gas-phase environment of the DMS cell. While these associations have been developed over time through empirical observations, the exact role of ion structures or their interactions with clustering molecules remains generally unknown. In this study, that relationship is explored by observing the DMS behaviors of a series of tetraalkylammonium ions as a function of their structures and the gas-phase environment of the DMS cell. To support the DMS experiments, the basin-hopping search strategy was employed to identify candidate cluster structures for density functional theory treatment. More than a million cluster structures distributed across 72 different ion-molecule cluster systems were sampled to determine global minimum structures and cluster binding energies. This joint computational and experimental approach suggests that cluster geometry, in particular ion-molecule intermolecular separation, plays a critical role in DMS.

Understanding gas phase modifier interactions in rapid analysis by differential mobility-tandem mass spectrometry

A systematic study involving the use and optimization of gas-phase modifiers in quantitative differential mobility-mass spectrometry (DMS-MS) analysis is presented using nucleoside-adduct biomarkers of DNA damage as an important reference point for analysis in complex matrices. Commonly used polar protic and polar aprotic modifiers have been screened for use against two deoxyguanosine adducts of DNA: N-(deoxyguanosin-8-yl)-4-aminobiphenyl (dG-C8-4-ABP) and N-(deoxyguanosin-8-y1)-2-amino-l-methyl-6-phenylimidazo[4,5-b]pyridine (dG-C8-PhIP). Particular attention was paid to compensation voltage (CoV) shifts, peak shapes, and product ion signal intensities while optimizing the DMS-MS conditions. The optimized parameters were then applied to rapid quantitation of the DNA adducts in calf thymus DNA. After a protein precipitation step, adduct levels corresponding to less than one modification in 10(6) normal DNA bases were detected using the DMS-MS platform. Based on DMS fundamentals and ab initio thermochemical results, we interpret the complexity of DMS modifier responses in terms of thermal activation and the development of solvent shells. At very high bulk gas temperature, modifier dipole moment may be the most important factor in cluster formation and cluster geometry, but at lower temperatures, multi-neutral clusters are important and less predictable. This work provides a useful protocol for targeted DNA adduct quantitation and a basis for future work on DMS modifier effects.

Ion dynamics in a trapped ion mobility spectrometer

In the present paper, theoretical simulations and experimental observations are used to describe the ion dynamics in a trapped ion mobility spectrometer. In particular, the ion motion, ion transmission and mobility separation are discussed as a function of the bath gas velocity, radial confinement, analysis time and speed. Mobility analysis and calibration procedure are reported for the case of sphere-like molecules for positive and negative ion modes. Results showed that a maximal mobility resolution can be achieved by optimizing the gas velocity, radial confinement (RF amplitude) and ramp speed (voltage range and ramp time). The mobility resolution scales with the electric field and gas velocity and R = 100-250 can be routinely obtained at room temperature.

The expanding universe of mass analyzer configurations for biological analysis

Mass spectrometry (MS) is an analytical technique that measures the mass-to-charge ratio of electrically charged gas-phase particles. All mass spectrometers combine ion formation, mass analysis, and ion detection. Although mass analyzers can be regarded as sophisticated devices that manipulate ions in space and time, the rich diversity of possible ways to combine ion separation, focusing, and detection in dynamic mass spectrometers accounts for the large number of instrument designs. A historical perspective of the progress in mass spectrometry that since 1965 until today have contributed to position this technique as an indispensable tool for biological research has been recently addressed by a privileged witness of this golden age of MS (Gelpí J. Mass Spectrom 43:419-435, 2008; Gelpí J. Mass Spectrom 44:1137-1161, 2008). The aim of this chapter is to highlight the view that the operational principles of mass spectrometry can be understood by a simple mathematical language, and that an understanding of the basic concepts of mass spectrometry is necessary to take the most out of this versatile technique.

Extending the dynamic range of the ion trap by differential mobility filtration

A miniature, planar, differential ion mobility spectrometer (DMS) was interfaced to an LCQ classic ion trap to conduct selective ion filtration prior to mass analysis in order to extend the dynamic range of the trap. Space charge effects are known to limit the functional ion storage capacity of ion trap mass analyzers and this, in turn, can affect the quality of the mass spectral data generated. This problem is further exacerbated in the analysis of mixtures where the indiscriminate introduction of matrix ions results in premature trap saturation with non-targeted species, thereby reducing the number of parent ions that may be used to conduct MS/MS experiments for quantitation or other diagnostic studies. We show that conducting differential mobility-based separations prior to mass analysis allows the isolation of targeted analytes from electrosprayed mixtures preventing the indiscriminate introduction of matrix ions and premature trap saturation with analytically unrelated species. Coupling these two analytical techniques is shown to enhance the detection of a targeted drug metabolite from a biological matrix. In its capacity as a selective ion filter, the DMS can improve the analytical performance of analyzers such as quadrupole (3D or linear) and ion cyclotron resonance (FT-ICR) ion traps that depend on ion accumulation.

A differential mobility spectrometry/mass spectrometry platform for the rapid detection and quantitation of DNA adduct dG-ABP

RATIONALE

There is continued interest in exploring new analytical technologies for the detection and quantitation of DNA adducts, biomarkers which provide direct evidence of exposure and genetic damage in cells. With the goal of reducing clean-up steps and improving sample throughput, a Differential Mobility Spectrometry/Mass Spectrometry (DMS/MS) platform has been introduced for adduct analysis.

METHODS

A DMS/MS platform has been utilized for the analysis of dG-ABP, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl (4-ABP). After optimization of the DMS parameters, each sample was analyzed in just 30 s following a simple protein precipitation step of the digested DNA.

RESULTS

A detection limit of one modification in 10^6 nucleosides has been achieved using only 2 µg of DNA. A brief comparison (quantitative and qualitative) with liquid chromatography/mass spectrometry is also presented highlighting the advantages of using the DMS/MS method as a high-throughput platform.

CONCLUSIONS

The data presented demonstrate the successful application of a DMS/MS/MS platform for the rapid quantitation of DNA adducts using, as a model analyte, the deoxyguanosine adduct of the bladder carcinogen 4-aminobiphenyl.

Differential mobility spectrometry with nanospray ion source as a compact detector for small organics and inorganics

Electrospray ionization (ESI) is an important tool in chemical and biochemical survey and targeted analysis in many applications. For chemical detection and identification electrospray is usually used with mass spectrometry (MS). However, for screening and monitoring of chemicals of interest in light, low power field-deployable instrumentation, an alternative detection technology with chemical selectivity would be highly useful, especially since small, lightweight, chip-based gas and liquid chromatographic technologies are being developed. Our initial list of applications requiring portable instruments includes chemical surveys on Mars, medical diagnostics based on metabolites in biological samples, and water quality analysis. In this report, we evaluate ESI-Differential Mobility Spectrometry (DMS) as a compact, low-power alternative to MS detection. Use of DMS for chemically-selective detection of ESI suffers in comparison with mass spectrometry because portable MS peak capacity is greater than that of DMS by 10X or more, but the development of light, fast chip chromatography offers compensating resolution. Standalone DMS provides the chemical selectivity familiar from DMS-MS publications, and exploits the sensitivity of ion detection. We find that sub-microliter-per-minute flows and a correctly-designed interface prepare a desolvated ion stream that enables DMS to act as an effective ion filter. Results for a several small organic biomarkers and metabolites, including citric acid, azelaic acid, n-hexanoylglycine, thymidine, and caffeine, as well as compounds such as dinitrotoluene and others, have been characterized and demonstrate selective detection. Water-quality-related halogen-containing anions, fluoride through bromate, contained in liquid samples are also isolated by DMS. A reaction-chamber interface is highlighted as most practical for portable ESI-DMS instrumentation.

High-field asymmetric waveform ion mobility spectrometry for mass spectrometry-based proteomics

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve the detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, the authors review recent developments in LC-FAIMS-MS and its application to MS-based proteomics.

Transversal Modulation Ion Mobility Spectrometry (TM-IMS), a new mobility filter overcoming turbulence related limitations

The analysis of ions according to their mobility is a technique that is attracting increasing interest. The new technology presented here, which we have termed Transversal Modulation Ion Mobility Spectrometry (TM-IMS), utilizes only electric fields, operates at atmospheric pressure, produces a continuous output of mobility selected ions (according to their true mobility and not to nonlinear effects), and has a very accessible inlet and outlet. These features would make it an ideal choice for tandem IMS-MS analysis in combination with most commercial Atmospheric Pressure Interface MS (API-MS) systems. We modeled and evaluated two different TM-IMS configurations (TM-IMS, and multistage TM-IMS), and we concluded that the most promising configuration would be a two-stage TM-IMS. We developed and tested a TM-IMS, and the measured resolving power is R = 55. The TM-IMS behaves similarly to the planar Differential Mobility Analyzer, but the TM-IMS utilizes only electric fields, and no fragile flow with high Reynolds numbers is required. We tested the robustness of the TM-IMS, which proves to be a very robust and reliable analyzer: the required voltage accuracy is 5 V in 10 kV, and the mechanical precision is 1 mm in 5 cm.

Development of rapid methodologies for the isolation and quantitation of drug metabolites by differential mobility spectrometry - mass spectrometry

Clinical and forensic toxicology laboratories are inundated with thousands of samples requiring lengthy chromatographic separations prior to mass spectrometry. Here, we employ differential mobility spectrometry (DMS) interfaced to nano-electrospray ionization-mass spectrometry to provide a rapid ion filtration technique for the separation of ions in gas phase media prior to mass spectral analysis on a DMS-integrated AB SCIEX API 3000 triple-quadrupole mass spectrometer. DMS is efficient at the rapid separation of ions under ambient conditions and provides many advantages when used as an ion filtration technique in tandem with mass spectrometry (MS) and MS/MS. Our studies evaluated DMS-MS/MS as a rapid, quantitative platform for the analysis of drug metabolites isolated from urine samples. In targeted applications, five metabolites of common drugs of abuse were effectively and rapidly separated using isopropanol and ethyl acetate as transport gas modifiers, eliminating the gas chromatography or liquid chromatography-based separations commonly employed in clinical and forensic toxicology laboratories. Calibration curves were prepared for the selected drug metabolites utilizing deuterated internal standards for quantitative purposes. The feasibility of separating and quantitating drug metabolites in a rapid fashion was evaluated by compensation voltage stepping followed by multiple reaction monitoring (MRM) detection. Rapid profiling of clinical and forensic toxicology samples could help to address an urgent need within the scientific community by developing high-throughput analytical methodologies, which could reduce significant case backlogs present within these laboratories.

Radiation metabolomics and its potential in biodosimetry

PURPOSE

Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. This review provides an overview of radiation signalling and metabolism, of metabolomic approaches used in the discovery phase, and of instrumentation with the potential to assess radiation injury in the field.

APPROACH

Recent developments in fast, high-resolution chromatography and mass spectrometry and new data analysis methods allow the quantitative assessment of thousands of metabolites based on biofluids obtained non-invasively. This complex analysis leads to the discovery-phase identification of groups of metabolites useful for screening and biodosimetry by targeted quantitative measurement. Instrumentation for target analysis can be simpler than that used for discovery, so we examine current technologies based on ion mobility.

CONCLUSIONS

Recent published results and ongoing studies examine the complex changes in the levels of many metabolites caused by radiation exposure, and identify groups of small-molecule biomarkers for radiation biodosimetry. Based on results showing separation orthogonal to mass, chemical noise suppression, and high sensitivity, differential mobility mass spectrometry (DMS-MS) ion mobility spectrometry appears highly promising for the development of deployable instrumentation.

Planar differential mobility spectrometer as a pre-filter for atmospheric pressure ionization mass spectrometry

Ion filters based on planar DMS can be integrated with the inlet configuration of most mass spectrometers, and are able to enhance the quality of mass analysis and quantitative accuracy by reducing chemical noise, and by pre-separating ions of similar mass. This paper is the first in a series of three papers describing the optimization of DMS / MS instrumentation. In this paper the important physical parameters of a planar DMS-MS interface including analyzer geometry, analyzer coupling to a mass spectrometer, and transport gas flow control are considered. The goal is to optimize ion transmission and transport efficiency, provide optimal and adjustable resolution, and produce stable operation under conditions of high sample contamination. We discuss the principles of DMS separations and highlight the theoretical underpinnings. The main differences between planar and cylindrical geometries are presented, including a discussion of the advantages and disadvantages of RF ion focusing. In addition, we present a description of optimization of the frequency and amplitude of the DMS fields for resolution and ion transmission, and a discussion of the influence and importance of ion residence time in DMS. We have constructed a mass spectrometer interface for planar geometries that takes advantage of atmospheric pressure gas dynamic principles, rather than ion focusing, to minimize ion losses from diffusion in the analyzer and to maximize total ion transport into the mass spectrometer. A variety of experimental results has been obtained that illustrate the performance of this type of interface, including tests of resistance to high contamination levels, and the separation of stereoisomers. In a subsequent publication the control of the chemical interactions that drive the separation process of a DMS / MS system will be considered. In a third publication we describe novel electronics designed to provide the high voltages asymmetric waveform fields (SV) required for these devices as well as the effects of different waveforms.

Detection of Radiation-Exposure Biomarkers by Differential Mobility Prefiltered Mass Spectrometry (DMS-MS)

Technology to enable rapid screening for radiation exposure has been identified as an important need, and, as a part of a NIH / NIAD effort in this direction, metabolomic biomarkers for radiation exposure have been identified in a recent series of papers. To reduce the time necessary to detect and measure these biomarkers, differential mobility spectrometry - mass spectrometry (DMS-MS) systems have been developed and tested. Differential mobility ion filters preselect specific ions and also suppress chemical noise created in typical atmospheric-pressure ionization sources (ESI, MALDI, and others). Differential-mobility-based ion selection is based on the field dependence of ion mobility, which, in turn, depends on ion characteristics that include conformation, charge distribution, molecular polarizability, and other properties, and on the transport gas composition which can be modified to enhance resolution. DMS-MS is able to resolve small-molecule biomarkers from nearly-isobaric interferences, and suppresses chemical noise generated in the ion source and in the mass spectrometer, improving selectivity and quantitative accuracy. Our planar DMS design is rapid, operating in a few milliseconds, and analyzes ions before fragmentation. Depending on MS inlet conditions, DMS-selected ions can be dissociated in the MS inlet expansion, before mass analysis, providing a capability similar to MS/MS with simpler instrumentation. This report presents selected DMS-MS experimental results, including resolution of complex test mixtures of isobaric compounds, separation of charge states, separation of isobaric biomarkers (citrate and isocitrate), and separation of nearly-isobaric biomarker anions in direct analysis of a bio-fluid sample from the radiation-treated group of a mouse-model study. These uses of DMS combined with moderate resolution MS instrumentation indicate the feasibility of field-deployable instrumentation for biomarker evaluation.