Direct analysis in real time mass spectrometry (DART-MS/MS) for rapid urine opioid detection in a clinical setting.

BACKGROUND AND AIMS: Current laboratory methods for opioid detection involve an initial screening with immunoassays which offers efficient but non-specific results and a subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) confirmation which offers accurate results but requires extensive sample preparation and turnaround time. Direct Analysis in Real Time (DART) tandem mass spectrometry is evaluated as an alternative approach for accurate opioid detection with efficient sample preparation and turnaround time. MATERIALS AND METHODS: DART-MS/MS was optimized by testing the method with varying temperatures, operation modes, extraction methods, hydrolysis times, and vortex times. The method was evaluated for 12 opioids by testing the analytical measurement range, percent carryover, precision studies, stability, and method-to-method comparison with LC-MS/MS. RESULTS: DART-MS/MS shows high sensitivity and specificity for the detection of 6-acetylmorphine, codeine, hydromorphone, oxymorphone, hydrocodone, naloxone, buprenorphine, norfentanyl, and fentanyl in urine samples. However, its performance was suboptimal for norbuprenorphine, morphine and oxycodone. CONCLUSION: In this proof-of-concept study, DART-MS/MS is evaluated for its rapid quantitative definitive testing of opioids drugs in urine. Further research is needed to expand its application to other areas of drug testing.

Modular, Scalable, and Customizable LC-HRMS for Exposomics.

In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

(Pre)Clinical Metabolomics Analysis.

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Stable Isotope Tracing Experiments Using LC-MS.

Metabolomics has emerged as a pivotal field in understanding cellular function, particularly in the context of disease. In numerous diseases, including cancer, alterations in metabolism play an essential role in disease progression and drug response. Hence, unraveling the metabolic rewiring is of importance to find novel diagnostic and therapeutic strategies. Isotope tracing is a powerful technique for delving deeper into the metabolic wiring of cells. By tracking an isotopically labeled substrate through biochemical reactions in the cell, this technique provides a dynamic understanding of cellular metabolism. This chapter outlines a robust isotope tracing protocol utilizing high-resolution mass spectrometry coupled to liquid chromatography in cell culture-based models. We cover essential aspects of experimental design and analyses, providing a valuable resource for researchers aiming to employ isotopic tracing.

Quantification of Total Ketone Bodies in Biological Matrices Using Stable Isotope-Labeled Internal Standards and RP-UHPLC-MS/MS.

Acetoacetate (AcAc) and D-beta-hydroxybutyrate (D-ßOHB), the two major ketone bodies found in circulation, are linked to multiple physiological and pathophysiological states. Therefore, analytical methodologies surrounding the quantification of total ketone body (TKB) concentrations in biological matrices are paramount. Traditional methods to quantify TKBs relied on indirect spectrophotometric assays with narrow dynamic ranges, which have been significantly improved upon by modern mass spectrometry (MS)-based approaches. However, the lack of stable isotope-labeled internal standards (ISs) for AcAc and the need to distinguish D-ßOHB from its closely related structural and enantiomeric isomers pose significant obstacles. Here, we provide a protocol to synthesize and quantify a [13C] stable isotope-labeled IS for AcAc, which, in conjunction with a commercially available [2H] stable isotope-labeled IS for ßOHB, allows TKBs to be measured across multiple biological matrices. This rapid (7 min) analysis employs reverse phase ultra-high performance liquid chromatography (RP-UHPLC) coupled to tandem MS (MS/MS) to distinguish ßOHB from three structural isomers using parallel reaction monitoring (PRM), providing excellent specificity and selectivity. Finally, a method is provided that distinguishes D-ßOHB from L-ßOHB using a simple one-step derivatization to produce the corresponding diastereomers, which can be chromatographically resolved using the same rapid RP-UHPLC separation with new PRM transitions. In summary, this method provides a rigorous analytical pipeline for the analysis of TKBs in biological matrices via leveraging two authentic stable isotope-labeled ISs and RP-UHPLC-MS/MS.

A Method for Analysis of Oxidized Phospholipids from Biological Samples Using Mass Spectrometry.

Oxidized phospholipids (oxPLs) are generated during innate immunity and inflammation, where they play a variety of biological roles, including regulation of autoimmunity and coagulation. Some are generated by enzymatic reactions, leading to stereo- and regiospecificity, while many others can be formed through nonenzymatic oxidation and truncation and can be used as biomarkers of oxidative stress. Mass spectrometry methods have been developed over many years for oxPL analysis, which can provide robust estimations of molecular species and amounts, where standards are available. Here we present a method used for the analysis of enzymatically-generated oxPL (eoxPL), which allows quantification of mono-hydroxy oxylipin-containing species. We also show profiling of many other partially characterized structures in tissue samples and provide typical chromatograms obtained.

Reversed-Phase Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry Method for High-Throughput Lipidomic Quantitation.

Reversed-phase ultrahigh-performance liquid chromatography-mass spectrometry (RP-UHPLC/MS) method is optimized for the quantitation of a large number of lipid species in biological samples, primarily in human plasma and serum. The method uses a C18 bridged ethylene hybrid (BEH) column (150 × 2.1 mm; 1.7 µm) for the separation of lipids from 23 subclasses with a total run time of 25 min. Lipid species separation allows the resolution of isobaric and isomeric lipid forms. A triple quadrupole mass spectrometer is used for targeted lipidomic analysis using multiple reaction monitoring (MRM) in the positive ion mode. Data are evaluated by Skyline software, and the concentrations of analytes are determined using internal standards per each individual lipid class.

Long Chain Base Profiling with Multiple Reaction Monitoring Mass Spectrometry.

Sphingolipids (SLs) are essential lipids with important functions in membrane formation and cell signaling. The presence of a long chain base (LCB) structure is common to all SLs. De novo SL synthesis is initiated by the enzyme serine-palmitoyltransferase (SPT), which forms an LCB by the conjugation from serine and fatty acyl-CoAs. SPT can metabolize a variety of acyl-CoA substrates, which form diverse LCB structures within and across species. The LCB then undergoes further metabolic modifications resulting in an extraordinarily diverse spectrum of sphingolipids formed. SL analysis, using liquid chromatography-mass spectrometry (LC-MS)-based methods, poses challenges due to the diverse range of frequently isobaric species. This complexity complicates the identification of underlying LCB structures using standard lipidomics approaches. Here, we describe a simplified method to analyze the LCB profile in cells, tissue, and blood. The procedure involves chemical hydrolysis to remove the conjugated headgroups and N-acyl chains, allowing to specifically resolve the underlying LCB structures by LC-MS. This method can also be combined with an isotope labeling approach to determine in vivo SPT activity and total SL de novo synthesis over time.

Sphingolipid Analysis in Clinical Research.

Sphingolipids are the most diverse class of lipids due to the numerous variations in their structural components. This diversity is also reflected in their extremely different functions. Sphingolipids are not only constituents of cell membranes but have emerged as key signaling molecules involved in a variety of cellular functions, such as cell growth and differentiation, proliferation and apoptotic cell death. Lipidomic analyses in clinical research have identified pathways and products of sphingolipid metabolism that are altered in several human pathologies. In this article, we describe how to properly design a lipidomic experiment in clinical research, how to handle plasma and serum samples for this purpose, and how to measure sphingolipids using liquid chromatography-mass spectrometry.

Nonenzymatic Oxidized Polyunsaturated Fatty Acid Products in Human Plasma and Urine Samples by LC-QTOF-MS/MS.

Oxidative stress induces autooxidation of polyunsaturated fatty acids, producing numerous isoprostanoids and isofuranoids. These oxidized products are measurable in human plasma and urine and serve as oxidative stress biomarkers for chronic diseases. This chapter details the preparation and measurement of α-linolenic acid-derived phytoprostanes and phytofurans in human samples using liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-QToF-MS/MS).

Quantification of Octadecanoids in Human Plasma Using Chiral Supercritical Fluid Chromatography-Tandem Mass Spectrometry.

Octadecanoids are a subset of oxylipins derived from 18-carbon fatty acids. These compounds have historically been understudied but have more recently attracted attention to their purported biological activity. One obstacle to the study of octadecanoids has been a lack of specific analytical methods for their measurement. A particular limitation has been the need for chiral-based methods that enable separation and quantification of individual stereoisomers. The use of chirality provides an additional dimension for distinguishing analytes produced enzymatically from those formed through autoxidation. In this chapter, we describe a comprehensive method using chiral supercritical fluid chromatography-tandem mass spectrometry (SFC-MS/MS) for the quantification of octadecanoids in human plasma. This method stands as an effective approach for quantifying octadecanoids and is applicable to diverse research applications including clinical research.

Recommendations for Accurate Lipid Annotation and Semi-absolute Quantification from LC-MS/MS Datasets.

Recent developments in LC-MS instrumentation and analytical technologies together with bioinformatics tools supporting high-throughput processing of large omics datasets significantly enhanced our capabilities and efficiency of identification and quantification of lipids in diverse biological materials. However, each biological matrix is characterized by its unique lipid composition, thus requiring optimization of analytical and bioinformatics workflows for each studied lipidome. Here, we describe an integrated workflow for deep lipidome profiling, accurate annotation, and semi-absolute quantification of complex lipidomes based on reversed phase chromatography and high resolution mass spectrometry. This chapter provides details on selection of the optimal extraction protocol, acquisition of LC-MS/MS data for accurate annotation of lipid molecular species, and design of lipidome-specific mixtures of internal standards to assist quantitative analysis of complex, native lipidomes.

Ultrahigh-Performance Supercritical Fluid Chromatography-Mass Spectrometry in the Clinical Lipidomic Analysis.

Ultrahigh-performance supercritical fluid chromatography-mass spectrometry (UHPSFC/MS) method is optimized for the high-throughput quantitation of lipids in human serum and plasma with an emphasis on robustness and accurate quantitation. Bridged ethylene hybrid (BEH) silica column (100 × 3 mm; 1.7 µm) is used for the separation of 17 nonpolar and polar lipid classes in 4.4 min using the positive ion electrospray ionization mode. The lipid class separation approach in UHPSFC/MS results in the coelution of all lipid species within one lipid class in one chromatographic peak, including two exogenous internal standards (IS) per lipid class, which provides the optimal conditions for robust quantitation. The method was validated according to European Medicines Agency and Food and Drug Administration recommendations. UHPSFC/MS combined with LipidQuant software allows a semiautomated process to determine lipid concentrations with a total run time of only 8 min including column equilibration, which enables the analysis of 160 samples per day.

Rapid Analysis of Sterols in Blood-Derived Samples.

Dysregulations of cholesterol biosynthesis are known to be associated with several pathologies. Due to the rapid growth of clinical investigations in this research area, a specific, fast, and valid method for analyzing cholesterol, its precursors, and metabolites is required. Here, we describe a rapid method for sample preparation, separation, and quantification of sterols in blood-derived samples using polymeric solid phase extraction followed by gas chromatography-mass spectrometry. The validated method demonstrates a reliable quantification of cholesterol, its precursors, and metabolites.

Differential Mobility Spectrometry-Based Cardiolipin Analysis.

Cardiolipins (CL) are special lipids in many respects. First of all, CL are composed of four fatty acids linked by two phosphatidic acids, which provide CL a unique molecular structure. Secondly, in eukaryotic cells they are specific to a single organelle, mitochondria, where they are also synthetized. CL are one of the most abundant lipid classes in mitochondria, mainly localized in the inner membrane. They are key determinants of mitochondrial health and homeostasis by modulating membrane integrity and fluidity, mitochondrial shapes, and metabolic pathways. Disturbances in mitochondrial CL composition can lead to tissue malfunction and diseases. It is therefore important to develop analytical tools to study the mitochondrial lipidome, and more particularly the CL. The method described here allows the quantification of cardiolipins at the sum composition level in isolated mitochondria or in liver tissue by flow injection analysis coupled to differential mobility spectrometry (FIA-DMS), also known as DMS-based shotgun lipidomics.

Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies.

Assessing potential alterations of metabolic pathways using large-scale approaches plays today a central role in clinical research. Because several thousands of mass features can be measured for each sample with separation techniques hyphenated to mass spectrometry (MS) detection, adapted strategies have to be implemented to detect altered pathways and help to elucidate the mechanisms of pathologies. These procedures include peak detection, sample alignment, normalization, statistical analysis, and metabolite annotation. Interestingly, considerable advances have been made over the last years in terms of analytics, bioinformatics, and chemometrics to help massive and complex metabolomic data to be more adequately handled with automated processing and data analysis workflows. Recent developments and remaining challenges related to MS signal processing, metabolite annotation, and biomarker discovery based on statistical models are illustrated in this chapter in light of their application to clinical research.

Application of a Computational Metabolomics Workflow for the Diagnosis of Inborn Errors of Metabolism in a Laboratory Setting.

Inborn errors of metabolism constitute a set of hereditary diseases that impose severe medical and physical challenges in the affected individual, in particular, for the pediatric patient population. Timely diagnosis is crucial for these patients, as any delay could result in irreversible health damage, underscoring the importance of early initiation of personalized treatment. Current routine diagnostic screening for inborn errors of metabolism relies on various targeted analyses of established biomarkers. However, this approach is time-consuming, focuses on a limited number of tests (based on clinical information) with a relatively small number of biomarkers, and does not facilitate the identification of new markers. In contrast, untargeted metabolomics-based screening offers a more efficient diagnostic solution, by assessing thousands of metabolites across multiple metabolic pathways in a single test. This not only saves time but also conserves resources for clinicians, the diagnostic laboratory, and for patients.This chapter describes the computational workflow of our "Next Generation Metabolic Screening" approach, which is a metabolomics-based method that is currently applied at the Translational Metabolic Laboratory of the Radboud University Medical Center (the Netherlands) for the diagnosis of inborn errors of metabolism.

In Situ Isotope Tracing at Single-Cell Resolution Using Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) allows for label-free spatial molecular interrogation of tissues. With advances in the field over recent years, the spatial resolution at which MSI data can be recorded has reached the single-cell level. This makes MSI complementary to other single-cell omics technologies. As metabolism is a highly dynamic process, capturing the metabolic turnover adds a valuable layer of information. Here, we describe how to set up in situ stable isotope tracing followed by MSI-enabled spatial metabolomics to perform dynamic metabolomics at the single-cell level.

Enhanced protection for interfacial lipid ozonolysis by sulfur-containing amino acids.

Sulfur-containing amino acids have been proposed as drugs for lipid oxidation associated with diseases for a long time, but the molecular-level mechanism on the effectiveness of sulfur-containing amino acids against lipid oxidation remains elusive. In this work, with the interfacial sensitivity mass spectrometry method, oxidation of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylglycerol (POPG), a widely used model lipid, was significantly inhibited on hung droplet surface in presence of sulfur-containing amino acids, such as cysteine (Cys) and methionine (Met). Both the Cys and Met showed a self-sacrificing protection. The amino acids with -S-R tails (R referring to methyl or t-butyl group) showed more effective against POPG oxidation than those with -SH tails, and this process was not related to the conformations of amino acids. The low effectiveness of Cys during the interfacial chemistry was proved to arise from the formation of disulfide bond. This study extends the current understanding of chemistry of sulfur-containing amino acids and provides insights to aid the sulfur-containing amino acids against cell oxidation.

Seasonal changes of chemodiversity along with microbial succession in a municipal wastewater treatment plant.

The relationship between chemodiversity and microbial succession in wastewater treatment plants (WWTPs) is highly intricate and bidirectional. The specific contribution of the microbial community to changes in the composition of dissolved organic matter (DOM) within different biological treatment units remains unclear, as does the reciprocal influence of DOM composition on microbial succession. In this study, spectroscopy ((Excitation-emission matrix) EEM-PARAFAC, Ultraviolet (UV)-spectrum, Fourier transform infrared spectrometer (FT-IR)), Liquid chromatograph mass spectrometer (LC‒MS) and Fourier transform ion cyclotron resonance (FT-ICR) MS along with high-throughput sequencing technology were used to explore the relationship between chemodiversity and microbial succession in WWTPs concerning seasonal changes. The results showed that WWTPs with anaerobic/anoxic/oxic (A2O) processes can metabolize and transform most of the wastewater DOM, and the anaerobic unit has the highest removal rate for fluorescence DOM (FDOM, 14.07%-64.43%); the anaerobic unit increased aliphatic/proteins and lignin-like molecules but decreased relative intensity, while the anoxic unit removed unsaturated hydrocarbons, aromatic structures, and lignin-like substances. The impact of seasonal changes on the composition and removal of FDOM and DOM in wastewater treatment is significant, and the variations that occur during different seasons affect microbial activity, as well as the production, degradation, and transformation of organic compounds throughout the wastewater treatment process. Network analysis shows that Parcubacteria_genera_incertae_sedis plays a crucial role in DOM chemodiversity, highlighting the crucial contribution of microbial communities to both the structure and operation of the entire DOM network. The results in this study could provide some theoretical and practical basis for guiding the process optimization of WWTPs.