Potential of ion mobility-mass spectrometry for both targeted and non-targeted analysis of phase II steroid metabolites in urine

Improved separation of fentanyl isomers using metal cation adducts and high-resolution ion mobility-mass spectrometry

Fentanyl is a potent synthetic opioid that has attracted significant attention due to its illegal production and distribution, resulting in misuse, overdose, and fatalities. Because numerous fentanyl analogs, including structural isomers, with different potency have been discovered in the field, there is a critical need to continue developing analytical methodologies capable of accurate identification in forensic and clinical laboratories. This study aimed to develop a rapid method for detecting and separating fentanyl isomers based on ion mobility-mass spectrometry (IM-MS), where IM separates gas-phase ions based on differences in their size, shape, and charge. Several strategies for improved differentiation were implemented, including using unconventional cation adducts (e.g., alkali and transition metals) and data post-processing by high-resolution demultiplexing. A collection of collision cross section (CCS) values for the various metal ion adducts was gathered, which can be used to improve confidence of identification in future samples. Notable examples, such as [M + Cu]+ and [M + Ag]+ adducts, contributed to significant improvement of resolution between isomers. Furthermore, the addition of high-resolution post-processing provided resolving power of >150, which constitutes a significant increase in comparison with the normal 50-60 obtained with low-resolution drift tube instruments. Collectively, these improved separation strategies allowed for confident detection and subsequent quantitative analysis. The optimized IM-MS method resulted in quantification of fentanyl in human urine with limits of detection and quantification of 13 pg/mL and 40 pg/mL, respectively.

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen (DTCCSN2) and traveling wave CCS in nitrogen (TWCCSN2). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

Improved analysis of derivatized steroid hormone isomers using ion mobility-mass spectrometry (IM-MS)

Over the last decade, applications of ion mobility-mass spectrometry (IM-MS) have exploded due primarily to the widespread commercialization of robust instrumentation from several vendors. Unfortunately, the modest resolving power of many of these platforms (~40-60) has precluded routine separation of constitutional and stereochemical isomers. While instrumentation advances have pushed resolving power to >150 in some cases, chemical approaches offer an alternative for increasing resolution with existing IM-MS instrumentation. Herein we explore the utility of two reactions, derivatization by Girard's reagents and 1,1-carbonyldiimidazole (CDI), for improving IM separation of steroid hormone isomers. These reactions are fast (≤30 min), simple (requiring only basic lab equipment/expertise), and low-cost. Notably, these reactions are structurally selective in that they target carbonyl and hydroxyl groups, respectively, which are found in all naturally occurring steroids. Many steroid hormone isomers differ only in the number, location, and/or stereochemistry of these functional groups, allowing these reactions to "amplify" subtle structural differences and improve IM resolution. Our results show that resolution was significantly improved amongst CDI-derivatized isomer groups of hydroxyprogesterone (two-peak resolution of Rpp = 1.10 between 21-OHP and 11B-OHP), deoxycortisone (Rpp = 1.47 between 11-DHC and 21-DOC), and desoximetasone (Rpp = 1.98 between desoximetasone and fluocortolone). Moreover, characteristic collision cross section (DTCCSN2) measurements can be used to increase confidence in the identification of these compounds in complex biological mixtures. To demonstrate the feasibility of analyzing the derivatized steroids in complex biological matrixes, the reactions were performed following steroid extraction from urine and yielded similar results. Additionally, we applied a software-based approach (high-resolution demultiplexing) that further improved the resolving power (>150). Overall, our results suggest that targeted derivatization reactions coupled with IM-MS can significantly improve the resolution of challenging isomer groups, allowing for more accurate and efficient analysis of complex mixtures.

New Approach for the Identification of Isobaric and Isomeric Metabolites

The structural elucidation of metabolite molecules is important in many branches of the life sciences. However, the isomeric and isobaric complexity of metabolites makes their identification extremely challenging, and analytical standards are often required to confirm the presence of a particular compound in a sample. We present here an approach to overcome these challenges using high-resolution ion mobility spectrometry in combination with cryogenic vibrational spectroscopy for the rapid separation and identification of metabolite isomers and isobars. Ion mobility can separate isomeric metabolites in tens of milliseconds, and cryogenic IR spectroscopy provides highly structured IR fingerprints for unambiguous molecular identification. Moreover, our approach allows one to identify metabolite isomers automatically by comparing their IR fingerprints with those previously recorded in a database, obviating the need for a recurrent introduction of analytical standards. We demonstrate the principle of this approach by constructing a database composed of IR fingerprints of eight isomeric/isobaric metabolites and use it for the identification of these isomers present in mixtures. Moreover, we show how our fast IR fingerprinting technology allows to probe the IR fingerprints of molecules within just a few seconds as they elute from an LC column. This approach has the potential to greatly improve metabolomics workflows in terms of accuracy, speed, and cost.

Comparability of Steroid Collision Cross Sections Using Three Different IM-HRMS Technologies: An Interplatform Study

Steroids play key roles in various biological processes and are characterized by many isomeric variants, which makes their unambiguous identification challenging. Ion mobility-mass spectrometry (IM-MS) has been proposed as a suitable platform for this application, particularly using collision cross section (CCS) databases obtained from different commercial IM-MS instruments. CCS is seen as an ideal additional identification parameter for steroids as long-term repeatability and interlaboratory reproducibility of this measurand are excellent and matrix effects are negligible. While excellent results were demonstrated for individual IM-MS technologies, a systematic comparison of CCS derived from all major commercial IM-MS technologies has not been performed. To address this gap, a comprehensive interlaboratory comparison of 142 CCS values derived from drift tube (DTIM-MS), traveling wave (TWIM-MS), and trapped ion mobility (TIM-MS) platforms using a set of 87 steroids was undertaken. Besides delivering three instrument-specific CCS databases, systematic comparisons revealed excellent interlaboratory performance for 95% of the ions with CCS biases within ±1% for TIM-MS and within ±2% for TWIM-MS with respect to DTIM-MS values. However, a small fraction of ions (<1.5%) showed larger biases of up to 7% indicating that differences in the ion conformation sampled on different instrument types need to be further investigated. Systematic differences between CCS derived from different IM-MS analyzers and implications on the applicability for nontargeted analysis are critically discussed. To the best of our knowledge, this is the most comprehensive interlaboratory study comparing CCS from three different IM-MS technologies for analysis of steroids and small molecules in general.

Evaluation of Metabolism of a Defined Pesticide Mixture through Multiple In Vitro Liver Models

The evaluation of exposure to multiple contaminants in a mixture presents a number of challenges. For example, the characterization of chemical metabolism in a mixture setting remains a research area with critical knowledge gaps. Studies of chemical metabolism typically utilize suspension cultures of primary human hepatocytes; however, this model is not suitable for studies of more extended exposures and donor-to-donor variability in a metabolic capacity is unavoidable. To address this issue, we utilized several in vitro models based on human-induced pluripotent stem cell (iPSC)-derived hepatocytes (iHep) to characterize the metabolism of an equimolar (1 or 5 µM) mixture of 20 pesticides. We used iHep suspensions and 2D sandwich cultures, and a microphysiological system OrganoPlate^® 2-lane 96 (Mimetas^TM) that also included endothelial cells and THP-1 cell-derived macrophages. When cell culture media were evaluated using gas and liquid chromatography coupled to tandem mass spectrometry methods, we found that the parent molecule concentrations diminished, consistent with metabolic activity. This effect was most pronounced in iHep suspensions with a 1 µM mixture, and was lowest in OrganoPlate^® 2-lane 96 for both mixtures. Additionally, we used ion mobility spectrometry-mass spectrometry (IMS-MS) to screen for metabolite formation in these cultures. These analyses revealed the presence of five primary metabolites that allowed for a more comprehensive evaluation of chemical metabolism in vitro. These findings suggest that iHep-based suspension assays maintain higher metabolic activity compared to 2D sandwich and OrganoPlate^® 2-lane 96 model. Moreover, this study illustrates that IMS-MS can characterize in vitro metabolite formation following exposure to mixtures of environmental contaminants.

Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

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

Critical evaluation of the role of external calibration strategies for IM-MS

The major benefits of integrating ion mobility (IM) into LC-MS methods for small molecules are the additional separation dimension and especially the use of IM-derived collision cross sections (CCS) as an additional ion-specific identification parameter. Several large CCS databases are now available, but outliers in experimental interplatform IM-MS comparisons are identified as a critical issue for routine use of CCS databases for identity confirmation. We postulate that different routine external calibration strategies applied for traveling wave (TWIM-MS) in comparison to drift tube (DTIM-MS) and trapped ion mobility (TIM-MS) instruments is a critical factor affecting interplatform comparability. In this study, different external calibration approaches for IM-MS were experimentally evaluated for 87 steroids, for which ^TWCCS_N2, ^DTCCS_N2 and ^TIMCCS_N2 are available. New reference CCS_N2 values for commercially available and class-specific calibrant sets were established using DTIM-MS and the benefit of using consolidated reference values on comparability of CCS_N2 values assessed. Furthermore, use of a new internal correction strategy based on stable isotope labelled (SIL) internal standards was shown to have potential for reducing systematic error in routine methods. After reducing bias for CCS_N2 between different platforms using new reference values (95% of ^TWCCS_N2 values fell within 1.29% of ^DTCCS_N2 and 1.12% of ^TIMCCS_N2 values, respectively), remaining outliers could be confidently classified and further studied using DFT calculations and CCS_N2 predictions. Despite large uncertainties for in silico CCS_N2 predictions, discrepancies in observed CCS_N2 values across different IM-MS platforms as well as non-uniform arrival time distributions could be partly rationalized.

Androgens, sports, and detection strategies for anabolic drug use

For decades, anabolic androgenic agents have represented the substance class most frequently observed in doping control samples. They comprise synthetic and pseudoendogenous anabolic androgenic steroids and other, mostly non-steroidal compounds with (presumed) positive effects on muscle mass and function. While exogenous substances can easily be detected by gas/liquid chromatography and mass spectrometry, significantly more complex methodologies including the longitudinal monitoring of individual urinary steroid concentrations/ratios and isotope ratio mass spectrometry are required to provide evidence for the exogenous administration of endogenous compounds. This narrative review summarizes the efforts made within the last 5 years to further improve the detection of anabolic agents in doping control samples. Different approaches such as the identification of novel metabolites and biomarkers, the acquisition of complementary mass spectrometric data, and the development of new analytical strategies were employed to increase method sensitivity and retrospectivity while simultaneously reducing method complexity to facilitate a higher and faster sample throughput.

Current Role of Mass Spectrometry in the Determination of Pesticide Residues in Food

The extensive use of pesticides represents a risk to human health. Consequently, legal frameworks have been established to ensure food safety, including control programs for pesticide residues. In this context, the performance of analytical methods acquires special relevance. Such methods are expected to be able to determine the largest number of compounds at trace concentration levels in complex food matrices, which represents a great analytical challenge. Technical advances in mass spectrometry (MS) have led to the development of more efficient analytical methods for the determination of pesticides. This review provides an overview of current analytical strategies applied in pesticide analysis, with a special focus on MS methods. Current targeted MS methods allow the simultaneous determination of hundreds of pesticides, whereas non-targeted MS methods are now applicable to the identification of pesticide metabolites and transformation products. New trends in pesticide analysis are also presented, including approaches for the simultaneous determination of pesticide residues and other food contaminants (i.e., mega-methods), or the recent application of techniques such as ion mobility–mass spectrometry (IM–MS) for this purpose.

Toward Routine Analysis of Anabolic Androgenic Steroids in Urine Using Ion Mobility-Mass Spectrometry

Anabolic androgenic steroids (AAS) make up one of the most prevalent classes of performance-enhancing drugs banned by the World Anti-Doping Agency (WADA) due to the competitive advantage they can afford athletes. Mass spectrometry-based methods coupled with chromatographic separations have become the gold standard for AAS analysis because of the superior sensitivity and selectivity provided. However, emerging analytical techniques including ion mobility spectrometry (IMS) have been demonstrated in recent applications as a means to further characterize and identify potential unknowns while simultaneously delivering improved sensitivity by filtering noise. Herein we outline the next crucial steps in bringing IMS to the routine drug testing workflow by combining it with established chromatographic and mass spectrometry methods (i.e., LC-IM-MS) for the detection of AAS in human urine. In addition to robust measurement of collision cross sections which can be used for identification purposes, functional group microtrends provide a structural basis on which to elucidate the structure of future novel anabolic agents. Lastly, the developed workflow is tested by analysis of testosterone in a realistic matrix (human urine) and demonstrates a limit of detection of 524 pg/mL, which surpasses the WADA Minimum Required Performance Levels for anabolic steroids. This work is expected to pave the way toward routine incorporation of IMS into analytical drug testing workflows to augment both qualitative and quantitative measure of performance enhancing drugs in the future.

Development of a high-throughput differential mobility separation-tandem mass spectrometry (DMS-MS/MS) method for clinical urine drug testing

INTRODUCTION

Differential mobility separation (DMS) is an analytical technique used for rapid separation of ions and isomers based on gas phase mobility prior to entering a mass spectrometer for analysis. The entire DMS process is accomplished in fewer than 20 ms and can be used as a rapid alternative to chromatographic separation.

OBJECTIVE

The primary objective was to evaluate the utility of DMS-tandem mass spectrometry (DMS-MS/MS) as a replacement for immunoassay-based clinical toxicology testing.

METHODS

A sensitive DMS-MS/MS method was developed and validated for simultaneous identification of 33 drugs and metabolites in human urine samples. After DMS optimization, the method was validated and used to screen 56 clinical urine samples. These results were compared to results obtained by immunoassay.

RESULTS

The DMS-MS/MS method achieved limits of detection ranging from 5 to 100 ng/mL. Moreover, the total analysis time was 2 min per sample. For the method performance evaluation, DMS-MS/MS results were compared with previously obtained urine toxicology immunoassay results. DMS-MS/MS showed higher sensitivity and identified 20% more drugs in urine, which were confirmed by LC-MS/MS.

CONCLUSION

The DMS-MS/MS as applied in our lab demonstrated the capability for rapid drug screening and provided better analytical performance than immunoassay.

Trapped Ion Mobility Incorporated in LC-HRMS Workflows as an Integral Analytical Platform of High Sensitivity: Targeted and Untargeted 4D-Metabolomics in Extra Virgin Olive Oil

Trapped ion mobility spectrometry (TIMS) is a promising technique for the separation of isomers based on their mobility. In the present work, TIMS coupled to liquid chromatography (LC) and high-resolution mass spectrometry (HRMS) was applied as a comprehensive analytical platform to address authenticity challenges, focusing on extra virgin olive oil (EVOO). Isomers detected in EVOO's phenolic fraction, classified into secoiridoids group, were successfully separated. Thanks to parallel accumulation serial fragmentation (PASEF) acquisition mode, high-quality spectra were obtained, facilitating identification. Moreover, a four-dimensional (4D) untargeted metabolomics approach was implemented to evaluate EVOO's global profile in cases of both variety and geographical origin discrimination. Potential authenticity markers, attributed to isomers, were successfully identified through the proposed workflow that incorporates ion mobility information along with LC-HRMS analytical evidence (i.e., mass accuracy, retention time, isotopic pattern, MS/MS fragmentation). Our study establishes LC-TIMS-HRMS in food authenticity and highlights mobility-enhanced metabolomics in four dimensions.

Bioanalytical strategies in drug discovery and development

A reliable, rapid, and effective bioanalytical method is essential for the determination of the pharmacokinetic, pharmacodynamic, and toxicokinetic parameters that inform the safety and efficacy profile of investigational drugs. The overall goal of bioanalytical method development is to elucidate the procedure and operating conditions under which a method can sufficiently extract, qualify, and/or quantify the analyte(s) of interest and/or their metabolites for the intended purpose. Given the difference in the physicochemical properties of small and large molecule drugs, different strategies need to be adopted for the development of an effective and efficient bioanalytical method. Herein, we provide an overview of different sample preparation strategies, analytical platforms, as well as procedures for achieving high throughput for bioanalysis of small and large molecule drugs.

Metabolomic Profiling of Human Urine Samples Using LC-TIMS-QTOF Mass Spectrometry

The identification of metabolites in biological samples is challenging due to their chemical and structural diversity. Ion mobility spectrometry (IMS) separates ionized molecules based on their mobility in a carrier buffer gas giving information about the ionic shape by measuring the rotationally averaged collision cross-section (CCS) value. This orthogonal descriptor, in combination with the m/z, isotopic pattern distribution, and MS/MS spectrum, has the potential to improve the identification of molecular molecules in complex mixtures. Urine metabolomics can reveal metabolic differences, which arise as a result of a specific disease or in response to therapeutic intervention. It is, however, complicated by the presence of metabolic breakdown products derived from a wide range of lifestyle and diet-related byproducts, many of which are poorly characterized. In this study, we explore the use of trapped ion mobility spectrometry (TIMS) via LC parallel accumulation with serial fragmentation (PASEF) for urine metabolomics. A total of 362 urine metabolites were characterized from 80 urine samples collected from healthy volunteers using untargeted metabolomics employing HILIC and RP chromatography. Additionally, three analytes (Trp, Phe, and Tyr) were selected for targeted quantification. Both the untargeted and targeted data was highly reproducible and reported CCS measurements for identified metabolites were robust in the presence of the urine matrix. A comparison of CCS values among different laboratories was also conducted, showing less than 1.3% ΔCCS values across different platforms. This is the first report of a human urine metabolite database compiled with CCS values experimentally acquired using an LC-PASEF TIMS-qTOF platform.

Investigation into Small Molecule Isomeric Glucuronide Metabolite Differentiation Using In Silico and Experimental Collision Cross-Section Values

Identifying isomeric metabolites remains a challenging and time-consuming process with both sensitivity and unambiguous structural assignment typically only achieved through the combined use of LC-MS and NMR. Ion mobility mass spectrometry (IMMS) has the potential to produce timely and accurate data using a single technique to identify drug metabolites, including isomers, without the requirement for in-depth interpretation (cf. MS/MS data) using an automated computational pipeline by comparison of experimental collision cross-section (CCS) values with predicted CCS values. An ion mobility enabled Q-Tof mass spectrometer was used to determine the CCS values of 28 (14 isomeric pairs of) small molecule glucuronide metabolites, which were then compared to two different in silico models; a quantum mechanics (QM) and a machine learning (ML) approach to test these approaches. The difference between CCS values within isomer pairs was also assessed to evaluate if the difference was large enough for unambiguous structural identification through in silico prediction. A good correlation was found between both the QM- and ML-based models and experimentally determined CCS values. The predicted CCS values were found to be similar between ML and QM in silico methods, with the QM model more accurately describing the difference in CCS values between isomer pairs. Of the 14 isomeric pairs, only one (naringenin glucuronides) gave a sufficient difference in CCS values for the QM model to distinguish between the isomers with some level of confidence, with the ML model unable to confidently distinguish the studied isomer pairs. An evaluation of analyte structures was also undertaken to explore any trends or anomalies within the data set.

Multidimensional Separations of Intact Phase II Steroid Metabolites Utilizing LC-Ion Mobility-HRMS

The detection and unambiguous identification of anabolic-androgenic steroid metabolites are essential in clinical, forensic, and antidoping analyses. Recently, sulfate phase II steroid metabolites have received increased attention in steroid metabolism and drug testing. In large part, this is because phase II steroid metabolites are excreted for an extended time, making them a potential long-term chemical marker of choice for tracking steroid misuse in sports. Comprehensive analytical methods, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS), have been used to detect and identify glucuronide and sulfate steroids in human urine with high sensitivity and reliability. However, LC-MS/MS identification strategies can be hindered by the fact that phase II steroid metabolites generate nonselective ion fragments across the different metabolite markers, limiting the confidence in metabolite identifications that rely on exact mass measurement and MS/MS information. Additionally, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is sometimes insufficient at fully resolving the analyte peaks from the sample matrix (commonly urine) chemical noise, further complicating accurate identification efforts. Therefore, we developed a liquid chromatography-ion mobility-high resolution mass spectrometry (LC-IM-HRMS) method to increase the peak capacity and utilize the IM-derived collision cross section (CCS) values as an additional molecular descriptor for increased selectivity and to improve identifications of intact steroid analyses at low concentrations.

Application of Predicted Collisional Cross Section to Metabolome Databases to Probabilistically Describe the Current and Future Ion Mobility Mass Spectrometry

Metabolomics is a powerful phenotyping platform with potential for high-throughput analyses. The primary technology for metabolite profiling is mass spectrometry. In recent years, the coupling of mass spectrometry with ion mobility spectrometry (IMS) has offered the promise of faster analysis time and greater resolving power. Our understanding of the potential impact of IMS on the field of metabolomics is limited by availability of comprehensive experimental data. In this analysis, we use a probabilistic approach to enumerate the strengths and limitations, the present and future, of this technology. This is accomplished through use of "model" metabolomes, predicted physicochemical properties, and probabilistic descriptions of resolving power. This analysis advances our understanding of the importance of orthogonality in resolving (separation) dimensions, describes the impact of the metabolome composition on resolution demands, and offers a system resolution landscape that may serve to guide practitioners in the coming years.

Improved Identification of Isomeric Steroids Using the Paternò-Büchi Reaction with Ion Mobility-Mass Spectrometry

The Paternò-Büchi (PB) reaction is a common organic reaction in which a carbonyl radical formed by exposure to UV radiation reacts with an alkene to form an oxetane ring. Recent analytical applications of this reaction have included the determination of C═C bond position in lipid fatty acyl tails using tandem mass spectrometry. Our group has recently investigated methods for structurally modifying steroid isomers to improve their identification and resolution using ion mobility spectrometry. Herein, we report the first application of the Paternò-Büchi reaction to form steroid oxetanes using a simple, low-cost, and high efficiency method with a low pressure mercury lamp. This methodology is performed on several endogenous steroid isomers, resulting in unique ion mobility spectra that provide a unique fingerprint for each. These fingerprint spectra can add confidence in identification of those compounds, especially in complex biological matrixes. Testosterone and epitestosterone, an epimer pair commonly interrogated in a number of applications such as for their use as performance enhancing drugs, displayed one and three unique ion mobility peaks, respectively. These spectra and their measured collision cross sections (CCS) allow for unambiguous differentiation of these and several other steroid isomer groups analyzed in this work. Finally, multiple anabolic androgenic steroids prohibited by the World Anti-Doping Agency were tested with this method and resulted in unique CCS for their PB reaction products. This approach can offer improved confidence in their identification as well as for many other banned substances.

Interlaboratory and Interplatform Study of Steroids Collision Cross Section by Traveling Wave Ion Mobility Spectrometry

Collision cross section (CCS) databases based on single-laboratory measurements must be cross-validated to extend their use in peak annotation. This work addresses the validation of the first comprehensive ^TWCCS_N2 database for steroids. First, its long-term robustness was evaluated (i.e., a year and a half after database generation; Synapt G2-S instrument; bias within ±1.0% for 157 ions, 95.7% of the total ions). It was further cross-validated by three external laboratories, including two different TWIMS platforms (i.e., Synapt G2-Si and two Vion IMS QToF; bias within the threshold of ±2.0% for 98.8, 79.9, and 94.0% of the total ions detected by each instrument, respectively). Finally, a cross-laboratory ^TWCCS_N2 database was built for 87 steroids (142 ions). The cross-laboratory database consists of average ^TWCCS_N2 values obtained by the four TWIMS instruments in triplicate measurements. In general, lower deviations were observed between ^TWCCS_N2 measurements and reference values when the cross-laboratory database was applied as a reference instead of the single-laboratory database. Relative standard deviations below 1.5% were observed for interlaboratory measurements (<1.0% for 85.2% of ions) and bias between average values and ^TWCCS_N2 measurements was within the range of ±1.5% for 96.8% of all cases. In the context of this interlaboratory study, this threshold was also suitable for ^TWCCS_N2 measurements of steroid metabolites in calf urine. Greater deviations were observed for steroid sulfates in complex urine samples of adult bovines, showing a slight matrix effect. The implementation of a scoring system for the application of the CCS descriptor in peak annotation is also discussed.

Current developments in LC-MS for pharmaceutical analysis

Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades.

Ion Mobility Spectrometry in Food Analysis: Principles, Current Applications and Future Trends

In the last decade, ion mobility spectrometry (IMS) has reemerged as an analytical separation technique, especially due to the commercialization of ion mobility mass spectrometers. Its applicability has been extended beyond classical applications such as the determination of chemical warfare agents and nowadays it is widely used for the characterization of biomolecules (e.g., proteins, glycans, lipids, etc.) and, more recently, of small molecules (e.g., metabolites, xenobiotics, etc.). Following this trend, the interest in this technique is growing among researchers from different fields including food science. Several advantages are attributed to IMS when integrated in traditional liquid chromatography (LC) and gas chromatography (GC) mass spectrometry (MS) workflows: (1) it improves method selectivity by providing an additional separation dimension that allows the separation of isobaric and isomeric compounds; (2) it increases method sensitivity by isolating the compounds of interest from background noise; (3) and it provides complementary information to mass spectra and retention time, the so-called collision cross section (CCS), so compounds can be identified with more confidence, either in targeted or non-targeted approaches. In this context, the number of applications focused on food analysis has increased exponentially in the last few years. This review provides an overview of the current status of IMS technology and its applicability in different areas of food analysis (i.e., food composition, process control, authentication, adulteration and safety).