Recent progress in metabolomics using ion mobility-mass spectrometry

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

INTRODUCTION

2,3-dinor 11β-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.

Metabolomics approach to understand molecular mechanisms involved in fungal pathogen-citrus pathosystems

Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host-pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen-citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen-host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.

Association of Blood Metabolomics Biomarkers with Brain Metabolites and Patient-Reported Outcomes as a New Approach in Individualized Diagnosis of Schizophrenia

Given its polygenic nature, there is a need for a personalized approach to schizophrenia. The aim of the study was to select laboratory biomarkers from blood, brain imaging, and clinical assessment, with an emphasis on patients' self-report questionnaires. Metabolomics studies of serum samples from 51 patients and 45 healthy volunteers, based on the liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS), led to the identification of 3 biochemical indicators (cortisol, glutamate, lactate) of schizophrenia. These metabolites were sequentially correlated with laboratory tests results, imaging results, and clinical assessment outcomes, including patient self-report outcomes. The hierarchical cluster analysis on the principal components (HCPC) was performed to identify the most homogeneous clinical groups. Significant correlations were noted between blood lactates and 11 clinical and 10 neuroimaging parameters. The increase in lactate and cortisol were significantly associated with a decrease in immunological parameters, especially with the level of reactive lymphocytes. The strongest correlations with the level of blood lactate and cortisol were demonstrated by brain glutamate, N-acetylaspartate and the concentrations of glutamate and glutamine, creatine and phosphocreatine in the prefrontal cortex. Metabolomics studies and the search for associations with brain parameters and self-reported outcomes may provide new diagnostic evidence to specific schizophrenia phenotypes.

Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics

The analysis of the brain extracellular metabolome is of interest for numerous subdomains within neuroscience. Not only does it provide information about normal physiological functions, it is even more of interest for biomarker discovery and target discovery in disease. The extracellular analysis of the brain is particularly interesting as it provides information about the release of mediators in the brain extracellular fluid to look at cellular signaling and metabolic pathways through the release, diffusion and re-uptake of neurochemicals. In vivo samples are obtained through microdialysis, cerebral open-flow microperfusion or solid-phase microextraction. The analytes of potential interest are typically low in concentration and can have a wide range of physicochemical properties. Liquid chromatography coupled to mass spectrometry has proven its usefulness in brain metabolomics. It allows sensitive and specific analysis of low sample volumes, obtained through different approaches. Several strategies for the analysis of the extracellular fluid have been proposed. The most widely used approaches apply sample derivatization, specific stationary phases and/or hydrophilic interaction liquid chromatography. Miniaturization of these methods allows an even higher sensitivity. The development of chiral metabolomics is indispensable, as it allows to compare the enantiomeric ratio of compounds and provides even more challenges. Some limitations continue to exist for the previously developed methods and the development of new, more sensitive methods remains needed. This review provides an overview of the methods developed for sampling and liquid chromatography-mass spectrometry analysis of the extracellular metabolome.

Ultra-high Performance Liquid Chromatography-Ion Mobility-High-Resolution Mass Spectrometry to Evaluate the Metabolomic Response of Durum Wheat to Sustainable Treatments

Sustainable agriculture aims at achieving a healthy food production while reducing the use of fertilizers and greenhouse gas emissions using biostimulants and soil amendments. Untargeted metabolomics by ultra-high performance liquid chromatography-ion mobility-high-resolution mass spectrometry, operating in a high-definition MSE mode, was applied to investigate the metabolome of durum wheat in response to sustainable treatments, i.e., the addition of biochar, commercial plant growth promoting microbes, and their combination. Partial least squares-discriminant analysis provided a good discrimination among treatments with sensitivity, specificity, and a non-error rate close to 1. A total of 88 and 45 discriminant compounds having biological, nutritional, and technological implications were tentatively identified in samples grown in 2020 and 2021. The addition of biochar-biostimulants produced the highest up-regulation of lipids and flavonoids, with the glycolipid desaturation being the most impacted pathway, whereas carbohydrates were mostly down-regulated. The findings achieved suggest the safe use of the combined biochar-biostimulant treatment for sustainable wheat cultivation.

Characterization of Bile Acid Isomers and the Implementation of High-Resolution Demultiplexing with Ion Mobility-Mass Spectrometry

Bile acids (BAs) are a complex suite of clinically relevant metabolites that include many isomers. Liquid chromatography coupled to mass spectrometry (LC-MS) is an increasingly popular technique due to its high specificity and sensitivity; nonetheless, acquisition times are generally 10-20 min, and isomers are not always resolved. In this study, the application of ion mobility (IM) spectrometry coupled to MS was investigated to separate, characterize, and measure BAs. A subset of 16 BAs was studied, including three groups of isomers belonging to unconjugated, glycine-conjugated, and taurine-conjugated BA classes. A variety of strategies were explored to increase BA isomer separation such as changing the drift gas, measuring different ionic species (i.e., multimers and cationized species), and enhancing the instrumental resolving power. In general, Ar, N₂, and CO₂ provided the best peak shape, resolving power (R_p), and separation, especially CO₂; He and SF₆ were less preferable. Furthermore, measuring dimers versus monomers improved isomer separation due to enhanced gas-phase structural differences. A variety of cation adducts other than sodium were characterized. Mobility arrival times and isomer separation were affected by the choice of adduct, which was shown to be used to target certain BAs. Finally, a novel workflow that involves high-resolution demultiplexing in combination with dipivaloylmethane ion-neutral clusters was implemented to improve R_p dramatically. A maximum R_p increase was observed with lower IM field strengths to obtain longer drift times, increasing R_p from 52 to 187. A combination of these separation enhancement strategies demonstrates great potential for rapid BA analysis.

Spatial single cell metabolomics: Current challenges and future developments

Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell-cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.

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.

Lipidomics Profiling of HepG2 Cells and Interference by Mycotoxins Based on UPLC-TOF-IMS

Discovering the fungus-infected or mycotoxin-contaminated biomarkers is significant for systems biology since the metabolites in biological samples have significant polarity differences in both stochastic gene expression and microenvironmental change. Here, we aim to establish a comprehensive method for a lipidome by ion mobility mass spectrometry (IMS) merged with chemometrics to accurately find out the more scientific markers of cell interference by mycotoxins and for pathogenesis exploration and drug development. The differences in the abundances of several small molecules found in these metabolites were explored through multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), to further screen biomarkers. Good applicability and predictability were demonstrated by R²(X) and Q² (R² = 0.959, Q² = 0.999). Five compounds with m/z values of 512.502 8, 540.5343, 722.525 8, 787.667 5, and 813.683 0 were selected as markers, and four of them were further confirmed by chemical standards (i.e., MSMS of m/z 813.683 0 covering m/z 86.0978, 125.0008, 184.0745, and 185.0781). In summary, we demonstrated the integration of UPLC-TOF-IMS and the chemometrics approach to elucidate identified biomarkers, which also provides a new way of thinking for covering lipid biomarkers or prognostic indicators for mycotoxins.

Recent Analytical Approaches for the Study of Bioavailability and Metabolism of Bioactive Phenolic Compounds

The study of the bioavailability of bioactive compounds is a fundamental step for the development of applications based on them, such as nutraceuticals, functional foods or cosmeceuticals. It is well-known that these compounds can undergo metabolic reactions before reaching therapeutic targets, which may also affect their bioactivity and possible applications. All recent studies that have focused on bioavailability and metabolism of phenolic and terpenoid compounds have been developed because of the advances in analytical chemistry and metabolomics approaches. The purpose of this review is to show the role of analytical chemistry and metabolomics in this field of knowledge. In this context, the different steps of the analytical chemistry workflow (design study, sample treatment, analytical techniques and data processing) applied in bioavailability and metabolism in vivo studies are detailed, as well as the most relevant results obtained from them.

Lipid analysis by ion mobility spectrometry combined with mass spectrometry: A brief update with a perspective on applications in the clinical laboratory

Ion mobility spectrometry (IMS) is an analytical technique where ions are separated in the gas phase based on their mobility through a buffer gas in the presence of an electric field. An ion passing through an IMS device has a characteristic collisional cross section (CCS) value that depends on the buffer gas used. IMS can be coupled with mass spectrometry (MS), which characterizes an ion based on a mass-to-charge ratio (m/z), to increase analytical specificity and provide further physicochemical information. In particular, IMS-MS is of ever-increasing interest for the analysis of lipids, which can be problematic to accurately identify and quantify in bodily fluids by liquid chromatography (LC) with MS alone due to the presence of isomers, isobars, and structurally similar analogs. IMS provides an additional layer of separation when combined with front-end LC approaches, thereby, enhancing peak capacity and analytical specificity. CCS (and also ion mobility drift time) can be plotted against m/z ion intensity and/or LC retention time in order to generate in-depth molecular profiles of a sample. Utilization of IMS-MS for routine clinical laboratory testing remains relatively unexplored, but areas do exist for potential implementation. A brief update is provided here on lipid analysis using IMS-MS with a perspective on some applications in the clinical laboratory.

Insights and prospects for ion mobility-mass spectrometry in clinical chemistry

INTRODUCTION

Ion mobility-mass spectrometry is an emerging technology in the clinical setting for high throughput and high confidence molecular characterization from complex biological samples. Ion mobility spectrometry can provide isomer separations on the basis of molecular structure, the ability of which is increasing through technological developments that afford enhanced resolving power. Integrating multiple separation dimensions, such as liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) provide dramatic enhancements in the mitigation of molecular interferences for high accuracy clinical measurements.

AREAS COVERED

Multidimensional separations with LC-IM-MS provide better selectivity and sensitivity in molecular analysis. Mass spectrometry imaging of tissues to inform spatial molecular distribution is improved by complementary ion mobility analyses. Biomarker identification in surgical environments is enhanced by intraoperative biochemical analysis with mass spectrometry and holds promise for integration with ion mobility spectrometry. New prospects in high resolving power ion mobility are enhancing analysis capabilities, such as distinguishing isomeric compounds.

EXPERT OPINION

Ion mobility-mass spectrometry holds many prospects for the field of isomer identification, molecular imaging, and intraoperative tumor margin delineation in clinical settings. These advantages are afforded while maintaining fast analysis times and subsequently high throughput. High resolving power ion mobility will enhance these advantages further, in particular for analyses requiring high confidence isobaric selectivity and detection.

Advanced tandem mass spectrometry in metabolomics and lipidomics-methods and applications

Metabolomics and lipidomics are new drivers of the omics era as molecular signatures and selected analytes allow phenotypic characterization and serve as biomarkers, respectively. The growing capabilities of untargeted and targeted workflows, which primarily rely on mass spectrometric platforms, enable extensive charting or identification of bioactive metabolites and lipids. Structural annotation of these compounds is key in order to link specific molecular entities to defined biochemical functions or phenotypes. Tandem mass spectrometry (MS), first and foremost collision-induced dissociation (CID), is the method of choice to unveil structural details of metabolites and lipids. But CID fragment ions are often not sufficient to fully characterize analytes. Therefore, recent years have seen a surge in alternative tandem MS methodologies that aim to offer full structural characterization of metabolites and lipids. In this article, principles, capabilities, drawbacks, and first applications of these "advanced tandem mass spectrometry" strategies will be critically reviewed. This includes tandem MS methods that are based on electrons, photons, and ion/molecule, as well as ion/ion reactions, combining tandem MS with concepts from optical spectroscopy and making use of derivatization strategies. In the final sections of this review, the first applications of these methodologies in combination with liquid chromatography or mass spectrometry imaging are highlighted and future perspectives for research in metabolomics and lipidomics are discussed.

The maternal serum metabolome by multisegment injection-capillary electrophoresis-mass spectrometry: a high-throughput platform and standardized data workflow for large-scale epidemiological studies

A standardized data workflow is described for large-scale serum metabolomic studies using multisegment injection-capillary electrophoresis-mass spectrometry. Multiplexed separations increase throughput (<4 min/sample) for quantitative determination of 66 polar/ionic metabolites in serum filtrates consistently detected (coefficient of variance (CV) <30%) with high frequency (>75%) from a multi-ethnic cohort of pregnant women (n = 1,004). We outline a validated protocol implemented in four batches over a 7-month period that includes details on preventive maintenance, sample workup, data preprocessing and metabolite authentication. We achieve stringent quality control (QC) and robust batch correction of long-term signal drift with good mutual agreement for a wide range of metabolites, including serum glucose as compared to a clinical chemistry analyzer (mean bias = 11%, n = 668). Control charts for a recovery standard (mean CV = 12%, n = 2,412) and serum metabolites in QC samples (median CV = 13%, n = 202) demonstrate acceptable intermediate precision with a median intraclass coefficient of 0.87. We also report reference intervals for 53 serum metabolites from a diverse population of women in their second trimester of pregnancy.

The Role of High-Resolution Analytical Techniques in the Development of Functional Foods

The approaches based on high-resolution analytical techniques, such as nuclear magnetic resonance or mass spectrometry coupled to chromatographic techniques, have a determining role in several of the stages necessary for the development of functional foods. The analyses of botanical extracts rich in bioactive compounds is one of the fundamental steps in order to identify and quantify their phytochemical composition. However, the compounds characterized in the extracts are not always responsible for the bioactive properties because they generally undergo metabolic reactions before reaching the therapeutic targets. For this reason, analytical techniques are also applied to analyze biological samples to know the bioavailability, pharmacokinetics and/or metabolism of the compounds ingested by animal or human models in nutritional intervention studies. In addition, these studies have also been applied to determine changes of endogenous metabolites caused by prolonged intake of compounds with bioactive potential. This review aims to describe the main types and modes of application of high-resolution analytical techniques in all these steps for functional food development.

Review: Metabolomics as a prediction tool for plants performance under environmental stress

Metabolomics as a diagnosis tool for plant performance has shown good features for breeding and crop improvement. Additionally, due to limitations in land area and the increasing climate changes, breeding projects focusing on abiotic stress tolerance are becoming essential. Nowadays no universal method is available to identify predictive metabolic markers. As a result, research aims must dictate the best method or combination of methods. To this end, we will introduce the key aspects to consider regarding growth scenarios and sampling strategies and discuss major analytical and data treatment approaches that are available to find metabolic markers of plant performance.

Recent applications of ion mobility spectrometry in natural product research

Ion mobility spectrometry (IMS) is a rapid separation technique capable of extracting complementary structural information to chromatography and mass spectrometry (MS). IMS, especially in combination with MS, has experienced inordinate growth in recent years as an analytical technique, and elicited intense interest in many research fields. In natural product analysis, IMS shows promise as an additional tool to enhance the performance of analytical methods used to identify promising drug candidates. Potential benefits of the incorporation of IMS into analytical workflows currently used in natural product analysis include the discrimination of structurally similar secondary metabolites, improving the quality of mass spectral data, and the use of mobility-derived collision cross-section (CCS) values as an additional identification criterion in targeted and untargeted analyses. This review aims to provide an overview of the application of IMS to natural product analysis over the last six years. Instrumental aspects and the fundamental background of IMS will be briefly covered, and recent applications of the technique for natural product analysis will be discussed to demonstrate the utility of the technique in this field.

Identification of new, very long-chain polyunsaturated fatty acids in fish by gas chromatography coupled to quadrupole/time-of-flight mass spectrometry with atmospheric pressure chemical ionization

The characterization of very long-chain (>C24) polyunsaturated fatty acids (VLC-PUFAs), which are essential in the vision, neural function, and reproduction of vertebrates, is challenging because of the lack of reference standards and their very low concentrations in certain lipid classes. In this research, we have developed a new methodology for VLC-PUFA identification based on gas chromatography coupled to quadrupole/time-of-flight mass spectrometry with an atmospheric pressure chemical ionization source (GC-APCI-QTOF MS). The mass accuracy attainable with the innovative QTOF instrument, together with the soft ionization of the APCI source, provides valuable information on the intact molecule, traditionally lost with electron ionization sources due to the extensive fragmentation suffered. We have identified, for the first time, VLC-PUFAs with chains up to 44 carbons in eyes, brain, and gonads of gilthead sea bream, a commercially important fish in the Mediterranean. The added value of ion mobility-mass spectrometry (IMS), recently developed in combination with GC-QTOF MS, and the contribution of the collisional cross section (CCS) parameter in the characterization of novel VLC-PUFAs (for which reference standards are not available) have been also evaluated. The methodology developed has allowed assessing qualitative differences between farmed and wild fish, and opens new perspectives in a still scarcely known field of research.

Recent advances in analytical strategies for mass spectrometry-based lipidomics

Lipids are vital biological molecules and play multiple roles in cellular function of mammalian organisms such as cellular membrane anchoring, signal transduction, material trafficking and energy storage. Driven by the biological significance of lipids, lipidomics has become an emerging science in the field of omics. Lipidome in biological systems consists of hundreds of thousands of individual lipid molecules that possess complex structures, multiple categories, and diverse physicochemical properties assembled by different combinations of polar headgroups and hydrophobic fatty acyl chains. Such structural complexity poses a huge challenge for comprehensive lipidome analysis. Thanks to the great innovations in chromatographic separation techniques and the continuous advances in mass spectrometric detection tools, analytical strategies for lipidomics have been highly diversified so that the depth and breadth of lipidomics have been greatly enhanced. This review will present the current state of mass spectrometry-based analytical strategies including untargeted, targeted and pseudotargeted lipidomics. Recent typical applications of lipidomics in biomarker discovery, pathogenic mechanism and therapeutic strategy are summarized, and the challenges facing to the field of lipidomics are also discussed.

Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples

The human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts. Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.

Spatial Metabolomics and Imaging Mass Spectrometry in the Age of Artificial Intelligence

Spatial metabolomics is an emerging field of omics research that has enabled localizing metabolites, lipids, and drugs in tissue sections, a feat considered impossible just two decades ago. Spatial metabolomics and its enabling technology-imaging mass spectrometry-generate big hyper-spectral imaging data that have motivated the development of tailored computational methods at the intersection of computational metabolomics and image analysis. Experimental and computational developments have recently opened doors to applications of spatial metabolomics in life sciences and biomedicine. At the same time, these advances have coincided with a rapid evolution in machine learning, deep learning, and artificial intelligence, which are transforming our everyday life and promise to revolutionize biology and healthcare. Here, we introduce spatial metabolomics through the eyes of a computational scientist, review the outstanding challenges, provide a look into the future, and discuss opportunities granted by the ongoing convergence of human and artificial intelligence.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.