Identification of Phospholipids Relevant to Cancer Tissue Using Differential Ion Mobility Spectrometry.

Phospholipids are the main building components of cell membranes and are also used for cell signaling and as energy storages. Cancer cells alter their lipid metabolism, which ultimately leads to an increase in phospholipids in cancer tissue. Surgical energy instruments use electrical or vibrational energy to heat tissues, which causes intra- and extracellular water to expand rapidly and degrade cell structures, bursting the cells, which causes the formation of a tissue aerosol or smoke depending on the amount of energy used. This gas phase analyte can then be analyzed via gas analysis methods. Differential mobility spectrometry (DMS) is a method that can be used to differentiate malignant tissue from benign tissues in real time via the analysis of surgical smoke produced by energy instruments. Previously, the DMS identification of cancer tissue was based on a 'black box method' by differentiating the 2D dispersion plots of samples. This study sets out to find datapoints from the DMS dispersion plots that represent relevant target molecules. We studied the ability of DMS to differentiate three subclasses of phospholipids (phosphatidylcholine, phosphatidylinositol, and phosphatidylethanolamine) from a control sample using a bovine skeletal muscle matrix with a 5 mg addition of each phospholipid subclass to the sample matrix. We trained binary classifiers using linear discriminant analysis (LDA) and support vector machines (SVM) for sample classification. We were able to identify phosphatidylcholine, -inositol, and -ethanolamine with SVM binary classification accuracies of 91%, 73%, and 66% and with LDA binary classification accuracies of 82%, 74%, and 72%, respectively. Phosphatidylcholine was detected with a reliable classification accuracy, but ion separation setups should be adjusted in future studies to reliably detect other relevant phospholipids such as phosphatidylinositol and phosphatidylethanolamine and improve DMS as a microanalysis method and identify other phospholipids relevant to cancer tissue.

Development of a rapid simultaneous assay of two urinary tetrasaccharide metabolites using differential ion mobility and tandem mass spectrometry and its application to patients with glycogen storage disease (type Ib and II).

Glucose tetrasaccharide (Glc4) and maltotetraose (M4) are important biomarkers for Pompe disease and other glycogen storage diseases (GSDs). With the development of new treatments for GSDs, more specific and sensitive bioanalytical methods are needed to determine biomarkers. In recent years, differential mobility spectrometry (DMS) has become an effective analytical technique with high selectivity and specificity. This study aimed to develop an efficient analytical method for the two urinary tetrasaccharide metabolites using DMS and apply it to patients with GSDs (type Ib and II). Urine samples were directly diluted and injected into liquid chromatography-differential mobility spectrometry tandem mass spectrometry (LC-DMS-MS/MS). Chromatographic separation was performed on an Acquity™ UPLC BEH Amide column (2.1 × 50 mm, 1.7 µm) with a short gradient elution of 2.6 min. DMS-MS/MS was used to detect two urinary tetrasaccharide metabolites in a negative multiple reaction monitoring mode with isopropanol as a modifier. A total of 20 urine samples from 6 healthy volunteers and 10 patients with GSDs (type Ib and II) were collected for analysis. The method was linear over a concentration range of 0.5~100.0 µg/mL for each urinary tetrasaccharide (r≥0.99). The intra- and inter-day precision RSD% were less than 14.3%, and the accuracy RE% were in the range of -14.3~13.4%. The relative matrix effect was between 86.6 and 114.3%. No carryover or interference was observed. Patients with GSDs (type Ib and II) had significantly higher median urinary Glc4 (P=0.001) and M4 (P=0.012) excretion than healthy subjects. The developed method was simple, rapid, sensitive, and specific. It was successfully applied to healthy volunteers and patients with GSDs (type Ib and II). DMS technology greatly improved analysis efficiency and provided high sensitivity and specificity.

Liquid chromatography and differential mobility spectrometry-data-independent mass spectrometry for comprehensive multidimensional separations in metabolomics.

The benefits of combining drift time ion mobility (DTIMS) with liquid chromatography-high-resolution mass spectrometry (HRMS) have been reported for metabolomics but the use of differential time mobility spectrometry (DMS) is less obvious due to the need for rapid scanning of the DMS cell. Drift DTIMS provides additional precursor ion selectivity and collisional cross-section information but the separation resolution between analytes remains cell- and component-dependent. With DMS, the addition of 2-propanol modifier can improve the selectivity but on cost of analyte MS response. In the present work, we investigate the liquid chromatography-mass spectrometry (LC-MS) analysis of a mix of 50 analytes, representative for urine and plasma metabolites, using scanning DMS with the single modifiers cyclohexane (Ch), toluene (Tol), acetonitrile (ACN), ethanol (EtOH), and 2-propanol (IPA), and a binary modifier mixture (cyclohexane/2-propanol) with emphasis on selectivity and signal sensitivity. 1.5% IPA in the N2 stream was found to suppress the signal of 50% of the analytes which could be partially recovered with the use of IPA to 0.05% as a Ch/IPA mixture. The potential to use the separation voltage/compensation voltage/modifier (SV/CoV/Mod) feature as an additional analyte identifier for qualitative analysis is also presented and applied to a data-independent LCxDMS-SWATH-MS workflow for the analysis of endogenous metabolites and drugs of abuse in human urine samples from traffic control.

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.

Laser desorption tissue imaging with Differential Mobility Spectrometry.

Pathological gross examination of breast carcinoma samples is sometimes laborious. A tissue pre-mapping method could indicate neoplastic areas to the pathologist and enable focused sampling. Differential Mobility Spectrometry (DMS) is a rapid and affordable technology for complex gas mixture analysis. We present an automated tissue laser analysis system for imaging approaches (iATLAS), which utilizes a computer-controlled laser evaporator unit coupled with a DMS gas analyzer. The system is demonstrated in the classification of porcine tissue samples and three human breast carcinomas. Tissue samples from eighteen landrace pigs were classified with the system based on a pre-designed matrix (spatial resolution 1-3 mm). The smoke samples were analyzed with DMS, and tissue classification was performed with several machine learning approaches. Porcine skeletal muscle (n = 1030), adipose tissue (n = 1329), normal breast tissue (n = 258), bone (n = 680), and liver (n = 264) were identified with 86% cross-validation (CV) accuracy with a convolutional neural network (CNN) model. Further, a panel tissue that comprised all five tissue types was applied as an independent validation dataset. In this test, 82% classification accuracy with CNN was achieved. An analogous procedure was applied to demonstrate the feasibility of iATLAS in breast cancer imaging according to 1) macroscopically and 2) microscopically annotated data with 10-fold CV and SVM (radial kernel). We reached a classification accuracy of 94%, specificity of 94%, and sensitivity of 93% with the macroscopically annotated data from three breast cancer specimens. The microscopic annotation was applicable to two specimens. For the first specimen, the classification accuracy was 84% (specificity 88% and sensitivity 77%). For the second, the classification accuracy was 72% (specificity 88% and sensitivity 24%). This study presents a promising method for automated tissue imaging in an animal model and lays foundation for breast cancer imaging.

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

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

Enhancing Top-Down Proteomics of Brain Tissue with FAIMS.

Proteomic investigations of Alzheimer's and Parkinson's disease have provided valuable insights into neurodegenerative disorders. Thus far, these investigations have largely been restricted to bottom-up approaches, hindering the degree to which one can characterize a protein's "intact" state. Top-down proteomics (TDP) overcomes this limitation; however, it is typically limited to observing only the most abundant proteoforms and of a relatively small size. Therefore, fractionation techniques are commonly used to reduce sample complexity. Here, we investigate gas-phase fractionation through high-field asymmetric waveform ion mobility spectrometry (FAIMS) within TDP. Utilizing a high complexity sample derived from Alzheimer's disease (AD) brain tissue, we describe how the addition of FAIMS to TDP can robustly improve the depth of proteome coverage. For example, implementation of FAIMS with external compensation voltage (CV) stepping at -50, -40, and -30 CV could more than double the mean number of non-redundant proteoforms, genes, and proteome sequence coverage compared to without FAIMS. We also found that FAIMS can influence the transmission of proteoforms and their charge envelopes based on their size. Importantly, FAIMS enabled the identification of intact amyloid beta (Aß) proteoforms, including the aggregation-prone Aß1-42 variant which is strongly linked to AD. Raw data and associated files have been deposited to the ProteomeXchange Consortium via the MassIVE data repository with data set identifier PXD023607.

Enhancing signal and mitigating up-front peptide fragmentation using controlled clustering by gas-phase modifiers.

Up-front CID fragmentation is a phenomenon where molecular ions are activated and fragment as they enter the atmosphere-to-vacuum region of the mass spectrometer, and consequently can complicate the mass spectra and their analysis. This phenomenon can be minimized by controlling the voltages on lens/optic elements where ions are sampled from the atmospheric region, but this approach can also have a negative effect on overall ion sensitivity. In this study, we introduce gas-phase modifiers (acetonitrile, acetone, cyclohexane, water, and methanol) to the curtain gas to mitigate up-front CID fragmentation. These modifiers cluster with incoming ions, increasing the energy barrier to fragmentation and consequently reducing the complexity of mass spectra. The clustering is monitored by differential mobility spectrometry-mass spectrometry (DMS-MS) and precursor mass spectrum-scanning. Unlike typical singly charged species, peptide ion-modifier clusters were found to survive through the atmosphere-to-vacuum interface of the mass spectrometer, showing that highly charged peptides cluster most strongly with acetonitrile and acetone. In addition, when peptides cluster with acetonitrile, they produce a large increase in signal intensity for the most highly charged and fragile ions. This results in a significant reduction, up to 90% with some modifiers, in up-front CID fragmentation for these fragile highly charged peptides, increasing the overall analytical sensitivity and decreasing the limits of detection by up to 82% depending on the analyte. The proposed technique has no significant detrimental effect on the peptide mass fingerprinting of a BSA or mAb protein digest, but it does reduce the amount of redundant and data-deficient spectra needed to produce adequate sequence coverage using information-dependent acquisition methods by ~ 40%. We propose that this technique could have a benefit in the fields of proteomics and peptidomics where up-front CID fragmentation and chemical noise routinely mask targets of biological importance. Graphical abstract.

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.

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.

High-throughput liquid chromatography differential mobility spectrometry mass spectrometry for bioanalysis: determination of reduced and oxidized form of glutathione in human blood.

Currently, the measure of the oxidative stress, from oxidized and reduced glutathione (GSSG and GSH respectively), for large cohorts of samples, is generally limited to spectrometric methods. In this study, a high-throughput assay for GSH after derivatization with N-ethylmaleimide and GSSG in blood sample was developed with an analysis time of 1.5 min. The method combines protein precipitation and a short LC (10-mm length) column where compounds were trapped in front-flush mode and eluted in back-flush mode. This setup is combined with modifier-assisted differential ion mobility spectrometry (DMS, SelexIon) and detection is performed in the selected reaction monitoring mode using positive electrospray ionization. In DMS, various modifiers were investigated including N2, methanol, toluene, ethanol, acetonitrile, and isopropanol to improve assay selectivity. Using EtOH as modifier, the limit of quantification (LOQ) was found to be 0.4 µM for GSSG and 3.2 µM for GS-N-ethylmaleimide (NEM) using a blood volume of 60 µL. The method is linear over a wide dynamic concentration range of 0.4 to 400 µM for GSSG and from 3.2 to 3200 µM for GS-NEM. The inter-assay precision of QC samples were ≤ 6.7%, with accuracy values between 98.3 and 103%. The method was further cross-validated with a LC Hypercarb-DMS-MS/MS method by the analysis of human blood samples. The bias between both assays ranged from - 0.3 to 0.2%. Graphical abstract ᅟ.

In vitro detection of common rhinosinusitis bacteria by the eNose utilising differential mobility spectrometry.

Acute rhinosinusitis (ARS) is a sudden, symptomatic inflammation of the nasal and paranasal mucosa. It is usually caused by respiratory virus infection, but bacteria complicate for a small number of ARS patients. The differential diagnostics between viral and bacterial pathogens is difficult and currently no rapid methodology exists, so antibiotics are overprescribed. The electronic nose (eNose) has shown the ability to detect diseases from gas mixtures. Differential mobility spectrometry (DMS) is a next-generation device that can separate ions based on their different mobility in high and low electric fields. Five common rhinosinusitis bacteria (Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pseudomonas aeruginosa) were analysed in vitro with DMS. Classification was done using linear discriminant analysis (LDA) and k-nearest neighbour (KNN). The results were validated using leave-one-out cross-validation and separate train and test sets. With the latter, 77% of the bacteria were classified correctly with LDA. The comparative figure with KNN was 79%. In one train-test set, P. aeruginosa was excluded and the four most common ARS bacteria were analysed with LDA and KNN; the correct classification rate was 83 and 85%, respectively. DMS has shown its potential in detecting rhinosinusitis bacteria in vitro. The applicability of DMS needs to be studied with rhinosinusitis patients.

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.

Differential mobility spectrometry tandem mass spectrometry with multiple ion monitoring for the bioanalysis of liraglutide.

Liraglutide is a glucagon-like peptide-1 analog for the treatment of type 2 diabetes. Major interference in plasma of human and animals and low fragment signal in tandem mass spectrometry are the main difficulties encountered in the bioanalysis of liraglutide. In this study, by combining differential mobility spectrometry (DMS) with multiple ion monitoring detection (MIM), a liquid chromatography differential mobility spectrometry tandem mass spectrometry with multiple ion monitoring detection (LC-DMS-MIM) method was developed for the quantitation of liraglutide in dog plasma. Mixed anion-exchange solid-phase extraction was used for sample preparation. The parameters of DMS were meticulously optimized to increase the signal-to-noise ratio of the analyte. The assay was linear in the range 1-100 ng/mL with good accuracy and precision. The lower limit of quantitation (LLOQ, the lowest standard on the calibration curve) of this method was 1 ng/mL. The research reveals that DMS is an effective tool for the elimination of interference in bioanalysis and that LC-DMS-MIM has better specificity and higher signal-to-noise ratio than classical liquid chromatography-tandem mass spectrometry (LC-MS/MS) for the bioanalysis of liraglutide. Graphical abstract Process for the bioanalysis of liraglutide by liquid chromatography differential mobility spectrometry tandem mass spectrometry with multiple ion monitoring detection.

Elucidating the chemical structure of native 1-deoxysphingosine.

The 1-deoxysphingolipids (1-deoxySLs) are formed by an alternate substrate usage of the enzyme, serine-palmitoyltransferase, and are devoid of the C1-OH-group present in canonical sphingolipids. Pathologically elevated 1-deoxySL levels are associated with the rare inherited neuropathy, HSAN1, and diabetes type 2 and might contribute to ß cell failure and the diabetic sensory neuropathy. In analogy to canonical sphingolipids, it was assumed that 1-deoxySLs also bear a (4E) double bond, which is normally introduced by sphingolipid delta(4)-desaturase 1. This, however, was never confirmed. We therefore supplemented HEK293 cells with isotope-labeled D3-1-deoxysphinganine and compared the downstream formed D3-1-deoxysphingosine (1-deoxySO) to a commercial synthetic SPH m18:1(4E)(3OH) standard. Both compounds showed the same m/z, but differed in their RPLC retention time and atmospheric pressure chemical ionization in-source fragmentation, suggesting that the two compounds are structural isomers. Using dimethyl disulfide derivatization followed by MS(2) as well as differential-mobility spectrometry combined with ozone-induced dissociation MS, we identified the carbon-carbon double bond in native 1-deoxySO to be located at the (Δ14) position. Comparing the chromatographic behavior of native 1-deoxySO to chemically synthesized SPH m18:1(14Z) and (14E) stereoisomers assigned the native compound to be SPH m18:1(14Z). This indicates that 1-deoxySLs are metabolized differently than canonical sphingolipids.

Characterization of acyl chain position in unsaturated phosphatidylcholines using differential mobility-mass spectrometry.

Glycerophospholipids (GPs) that differ in the relative position of the two fatty acyl chains on the glycerol backbone (i.e., sn-positional isomers) can have distinct physicochemical properties. The unambiguous assignment of acyl chain position to an individual GP represents a significant analytical challenge. Here we describe a workflow where phosphatidylcholines (PCs) are subjected to ESI for characterization by a combination of differential mobility spectrometry and MS (DMS-MS). When infused as a mixture, ions formed from silver adduction of each phospholipid isomer {e.g., [PC (16:0/18:1) + Ag](+) and [PC (18:1/16:0) + Ag](+)} are transmitted through the DMS device at discrete compensation voltages. Varying their relative amounts allows facile and unambiguous assignment of the sn-positions of the fatty acyl chains for each isomer. Integration of the well-resolved ion populations provides a rapid method (< 3 min) for relative quantification of these lipid isomers. The DMS-MS results show excellent agreement with established, but time-consuming, enzymatic approaches and also provide superior accuracy to methods that rely on MS alone. The advantages of this DMS-MS method in identification and quantification of GP isomer populations is demonstrated by direct analysis of complex biological extracts without any prior fractionation.

Insights into modifiers effects in differential mobility spectrometry: A data science approach for metabolomics and peptidomics.

Utilizing a data-driven approach, this study investigates modifier effects on compensation voltage in differential mobility spectrometry-mass spectrometry (DMS-MS) for metabolites and peptides. Our analysis uncovers specific factors causing signal suppression in small molecules and pinpoints both signal suppression mechanisms and the analytes involved. In peptides, machine learning models discern a relationship between molecular weight, topological polar surface area, peptide charge, and proton transfer-induced signal suppression. The models exhibit robust performance, offering valuable insights for the application of DMS to metabolites and tryptic peptides analysis by DMS-MS.

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.

High-throughput liquid chromatography-vacuum differential mobility spectrometry-mass spectrometry for the analysis of isomeric drugs of abuse in human urine.

The use of differential mobility spectrometry at low pressure coupled to liquid chromatography-mass spectrometry (LC-vDMS-MS) was investigated for the analysis of 13 drugs of abuse (DoA) including the following: cocaine, ecgonine methyl ester, cocaethylene, benzoylecgonine, norcocaine, tramadol, isomeric pairs of metabolites; O-desmethyl-cis-tramadol and N-desmethyl-cis-tramadol, and cannabinoids: Δ9-tetrahydrocannabinol, Δ9-tetrahydrocannabidiol, 11-hydroxy-Δ9-tetrahydrocannabinol, 11-nor-9carboxy-Δ9-tetrahydrocannabinol, and 11-nor-9carboxy-Δ9-tetrahydrocannabinol glucuronide. Different parameters were optimized for isomeric separation, such as LC mobile phase composition (20%-100% methanol acetonitrile and isopropanol, flow rate: 8-100 µL/min) and DMS separation voltage. Methanol and acetonitrile significantly affected the compensation voltage of the analytes and improved DMS separation. A short trap/elute LC-vDMS-SIM/MS screening method of 1 min was developed to quantify 11 drugs of abuse (except THC/CBD), in addition to a 4-min LC-vDMS-SIM/MS method to identify and quantify five cannabinoids including the isomers THC/CBD and three THC metabolites. THC is the principal psychoactive constituent of cannabis and is a controlled substance in comparison to its isomeric counterpart CBD; this highlights the importance and challenges to resolve these isomeric pairs by analytical techniques. The signal responses were linear over a concentration range of 0.005-10 µg/mL for the DoA and 1-1000 ng/mL for cannabinoids. The intraday and interday precision were better than 12.2% and accuracy better than 115%. Urine samples from subjects who tested positive for THC and/or cocaine during roadside drug testing were evaluated to assess the performance of the methods LC-vDMS-SIM/MS and LC-MRM/MS. Results show that the developed LC-vDMS-SIM/MS method presents similar performance to LC-MRM/MS with improved sample throughput.

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

INTRODUCTION: 2,3-dinor 11ß-Prostaglandin F2α (BPG) is an arachidonic acid derivative and the most abundant metabolic byproduct of prostaglandin D2, which is released during mast cell activation. Therefore, measurements of BPG in urine using liquid chromatography-tandem mass spectrometry (LC-MS/MS) provide a noninvasive method for evaluation and management of mast cell disorders. Measurements obtained by LC-MS/MS exhibit a high prevalence of chromatographic interferences resulting in challenges with optimal determination of BGP. In this investigation, differential mobility spectrometry (DMS) is utilized to overcome the limitations of current testing. METHODS: Urine samples were extracted using an automated solid-phase extraction method. Samples were then analyzed with and without DMS devices installed on two commercially available mass spectrometry platforms to assess the benefits of DMS. Following promising results from a preliminary analytical evaluation, LC-DMS-MS/MS measurements of BPG in urine were fully validated to assess the analytical implications of using this technology. RESULTS AND DISCUSSION: The addition of DMS devices to the LC-MS/MS systems evaluated in this investigation significantly reduced interferences observed in the chromatograms. Concomitantly, DMS reduced the number of discordant quantifier/qualifier fragment ion results that significantly exceeded the ± 20 % limits, suggesting greater analytical specificity. The validation studies yielded low interday imprecision, with %CVs less than 6.5 % across 20 replicate measurements. Validation studies assessing other aspects of analytical performance also met acceptance criteria. CONCLUSIONS: Incorporating DMS devices greatly improved the specificity of BPG measurements by LC-MS/MS, as evidenced by the comparison of chromatograms and fragment ion results. Validation studies showed exceptional performance for established analytical metrics, indicating that this technology can be used to minimize the impact of interferences without adversely impacting other aspects of analytical or clinical performance.