Metabolites In Biological Samples Research Articles

Feature-Based Molecular Network for New Psychoactive Substance Identification: The Case of Synthetic Cannabinoids in a Seized e-Liquid and Biological Samples.

The comprehensive detection of new psychoactive substances, including synthetic cannabinoids along with their associated metabolites in biological samples, remains an analytical challenge. To detect these chemicals, untargeted approaches using appropriate bioinformatic tools such as molecular networks are useful, albeit it necessitates as a prerequisite the identification of a node of interest within the cluster. To illustrate it, we reported in this study the identification of synthetic cannabinoids and some of their metabolites in seized e-liquid, urine, and hair collected from an 18-year-old poisoned patient hospitalized for neuropsychiatric disorders. A comprehensive analysis of the seized e-liquid was performed using gas chromatography coupled with electron ionization mass spectrometry, 1H NMR, and liquid chromatography coupled with high resolution tandem mass spectrometry combined with data processing based on molecular network strategy. It allowed researchers to detect in the e-liquid known synthetic cannabinoids including MDMB-4en-PINACA, EDMB-4en-PINACA, MMB-4en-PINACA, and MDMB-5F-PICA. Compounds corresponding to transesterification of MDMB-4en-PINACA with pentenol, glycerol, and propylene glycol were also identified. Regarding the urine sample of the patient, metabolites of MDMB-4en-PINACA were detected, including MDMB-4en-PINACA butanoic acid, dihydroxylated MDMB-4en-PINACA butanoic acid, and glucurono-conjugated MDMB-4en-PINACA butanoic acid. Hair analysis of the patient allowed the detection of MDMB-4en-PINACA and MDMB-5F-PICA in the two investigated hair segments. This untargeted analysis of seized materials and biological samples demonstrates the utility of the molecular network strategy in identifying closely related compounds and metabolites of synthetic cannabinoids. It also emphasizes the need for developing strategies to anchor molecular networks, especially for new psychoactive substances.

Preparation of a multiple interacting magnetic fluid for rapid and sensitive simultaneous extraction of β-nicotinamide mononucleotide metabolites in biological samples

Backgroundβ-nicotinamide mononucleotide stands out as an essential breakthrough in “anti-aging” and consistently leads the list of top-selling nutritional supplements in terms of quantity. As the metabolites of β-nicotinamide mononucleotide, the detection of nicotinamide and N1-methylnicotinamide is of great significance for evaluating the nutritional effect of dietary supplements of β-nicotinamide mononucleotide. However, due to the extremely low concentration of nicotinamide and N1-methylnicotinamide in vivo and the serious matrix interference in biological samples, there is an increasing demand for materials and methods of pre-treatment. ResultsIn this study, Fe3O4@hydroxypropyl methyl cellulose@dodecylbenzenesulfonic acid magnetic fluid was synthesized for the first time, and it was used as pretreatment material to detect nicotinamide and N1- methylnicotinamide in urine samples by high performance liquid chromatography. Compared with other adsorption materials, Fe3O4@hydroxypropyl methyl cellulose@dodecylbenzenesulfonic acid nanoparticles are a kind of uniform magnetic fluid. Furthermore, they have more types and quantities of interaction sites (electrostatic interactions, hydrophobic interactions, hydrogen bonding interactions, and π-π interactions), so they own greater adsorption capacity. When the pH of the solution is 4, they can be adsorbed quickly within 10 s. The method successfully detected trace nicotinamide and N1-methylnicotinamide in urine samples in the linear range of 0.1–80 μg mL−1, the low detection limits were 0.30 ng mL−1 and 1.5 ng mL−1 respectively, and the quantification limits were 1.0 ng mL−1 and 5.0 ng mL−1, respectively. At the same time, the standard urine samples of nicotinamide and N1-methylnicotinamide showed satisfactory recovery rate 94.50–109.1 %. The results indicated that the established method can accurately and quantitatively determine trace nicotinamide and N1-methylnicotinamide in urine samples. SignificanceConsequently, low concentration of β-nicotinamide mononucleotide metabolites can be detected simultaneously, and the interference can be eliminated during the detection process, which provides an efficient and convenient pretreatment method and a rapid and sensitive detection method for the analysis of β-nicotinamide mononucleotide metabolites. What's more, it has a wide application prospect in the analysis of other similar metabolites in biological samples.

Poprhyrinoids Based Sensors for Volatilomics

Metabolomics can be defined as the systematic study of the unique chemical fingerprints that specific cellular and physiological processes leave behind. For the scope, it encompasses a set of analytical methods to detect low molecular weight metabolites in biological samples that are linked to specific health or disease conditions. The collections of compounds form the so-called metabolic profiles usually containing hundreds of different compounds. Ultimately, metabolomics studies are aimed at finding the alteration of the metabolic profile due to specific conditions or diverse pathologies from cancer, to infective diseases.The volatilomics is the case of metabolomics concerned with the small metabolites that are volatile or semi-volatile. The human volatilome can be studied in different human samples such as breath, skin, urines, saliva, and feces.The study of volatile compounds is an important topic of analytical chemistry. Thus, several analytical instruments and methods are available for the investigation of the volatilome5. In general, the scope of the analysis is the detection of the quality and the quantity of the molecules contained in a sample. To achieve this scope these instruments are made by a step of separation and a detector.Analytical machines are generally bulky, costly, and they require specialized staff to be operated and to interpret the data. For these reasons, volatilomics is greatly fascinated by the possibility to replace the analytical machines with sensors. Sensors are devices small enough to be directly connected to electronic platforms.In sensors the separation stage of the analytical instruments is replaced by the affinity of the sensor respect to the molecules composing the sample. however, differently form mass spectrometers. sensors always produce a signal that is related to the totality of the molecules at which it is exposed. Thus, sensors may be selective, when the affinity towards one molecular species overcome the affinity towards all the others, or non-selective when the affinities are comparable. Thus, in principle to replace a GC, an ensemble of sensors each selective to a different species is necessary.The development of sensors for volatilomics found an unexpected inspiration from nature, and more specifically, from olfaction. One of the most striking characteristics of olfaction is the capability to sense many different odors with a limited set of different receptors. It has been surmised that human, with only 388 different receptors, can detect more than one trillion of odor stimuli. The principle of odor identification in olfaction is ruled by the so-called combinatorial selectivity. since a single compound may be sensed by more receptors and more receptors may sense the same compound, the identification of an odor is accomplished by the pattern of responses of the whole set of receptors.Porphyrinoids have been found to be an exceptional material for electronic noses because theie molecular structure made of modular blocks such as the central metal atom, the aromatic ring, and the peripheral motifs can be modified giving rise to a large variety of sensitivity patterns.Porphyrins have been extensivelly used in volatilomics, in the first implementation, as the functional layer of quartz microbalances. In 2003 an array made of porphyrins and corroles demonstrated that lung cancer could be diagnosed from the analysis of breath. This first evidence was followed by other applications aimed at diagnosis tuberculosisfrom breath, lung cancerand kidney cancerfrom urines and COVID-19 from serum. Additionally, these sensors were used to study malariaand stem cellsproliferation in murine models.Recently, quartz microbalance sensors were challenged by the possibility to develop porphyrins-based impedance sensors. The introduction of these sensors is expected to reduce the costs of production and to result into more simple and widely usable devices. For instance, a capacitive sensor array made of porphyrinoids coated silica particles was used to detect COVID-19 from the VOCs released by serum, and Porphyrins-doped PEDOT was implemented in facemasksand used to diagnose chronic kidney diseases.In the presentation, the rationale of these developments will be presented, and somne noteworthy case studies will be discussed.

Chemical Isotope Labeling and Dual-Filtering Strategy for Comprehensive Profiling of Urinary Glucuronide Conjugates.

Glucuronidation, a crucial process in phase II metabolism, plays a vital role in the detoxification and elimination of endogenous substances and xenobiotics. A comprehensive and confident profiling of glucuronate-conjugated metabolites is imperative to understanding their roles in physiological and pathological processes. In this study, a chemical isotope labeling and dual-filtering strategy was developed for global profiling of glucuronide metabolites in biological samples. N,N-Dimethyl ethylenediamine (DMED-d0) and its deuterated counterpart DMED-d6 were used to label carboxylic acids through an amidation reaction. First, carboxyl-containing compounds were extracted based on a characteristic mass difference (Δm/z, 6.037 Da) observed in MS between light- and heavy-labeled metabolites (filter I). Subsequently, within the pool of carboxyl-containing compounds, glucuronides were identified using two pairs of diagnostic ions (m/z 247.1294/253.1665 and 229.1188/235.1559 for DMED-d0/DMED-d6-labeled glucuronides) originating from the fragmentation of the derivatized glucuronic acid group in MS/MS (filter II). Compared with non-derivatization, DEMD labeling significantly enhanced the detection sensitivity of glucuronides, as evidenced by a 3- to 55-fold decrease in limits of detection for representative standards. The strategy was applied to profiling glucuronide metabolites in urine samples from colorectal cancer (CRC) patients. A total of 685 features were screened as potential glucuronides, among which 181 were annotated, mainly including glucuronides derived from lipids, organic oxygen, and phenylpropanoids. Enzymatic biosynthesis was employed to accurately identify unknown glucuronides without standards, demonstrating the reliability of the dual-filtering strategy. Our strategy exhibits great potential for profiling the glucuronide metabolome with high coverage and confidence to reveal changes in CRC and other diseases.

Substantial benefits of an inert biphenyl column for the analysis of steroids and their phase II metabolites in biological samples.

Steroids can be used as biomarkers in clinical metabolomics and other fields related to human toxicology. This chemical group is known for its complexity, considering its number of isobaric compounds and the wide variety of phases I and II metabolic pathways that parent compounds can undergo. For a successful analysis of steroids in biological samples, liquid chromatography separation must be finely tuned. It is especially challenging for glucuronidated and sulfated steroids derivatives that bear polar heads and can be affected by non-specific adsorption. The benefits of a biphenyl stationary phase chemistry for the selectivity of the separation of steroids and their phase II metabolites and the extent to which nonspecific adsorption phenomena could degrade chromatographic performance were investigated. Replacing a conventional hardware by a passivated hardware allowed to considerably reduce peaks width and asymmetry of sulfated species. The addition of weak ion pairing agents in the mobile phase could also help to reduce non-specific adsorption but are detrimental to mass spectrometry detection. As confirmed by the successful detection of 52 steroids in plasma, the use of a biphenyl stationary phase complemented by a passivated column hardware is of great help for a successful biomedical analysis of steroids and their phase II metabolites.

Electrochemical Sensors, Biosensors, and Optical Sensors for the Detection of Opioids and Their Analogs: Pharmaceutical, Clinical, and Forensic Applications

Pharmaceutical opioids are intravenously or orally administered analgesics. While they are effective in relieving chronic and acute pain, their narrow window of therapeutic use contributes to the high occurrence of abuse. The associated abuse of this family of drugs can be correlated to the increase in dependency, overdose, and death of users. The negative effects of opioids extend beyond the physical and psychological effects experienced by the user to their unregulated synthesis and sale, which contribute to socioeconomic challenges and are a biproduct of this global public health epidemic. From clinical to point-of-care applications, the detection and real-time monitoring of this family of drug is critical in the fight to decrease abuse and improve use in clinical settings. Chromatographic separations and chromatography–mass spectrometry are traditional methods of opioid analyses, but the high cost, long analysis time, and absence of portability highlight the need for the development of fast, in situ, point-of-care analysis, or of community drug monitoring services. This review highlights recent electrochemical and optical (FTIR, Raman, colorimetric, and fluorescent) advances and biosensors for pharmaceutical and illicit opioid analysis. Specifically, an emphasis is placed on the detection of opioids and their metabolites in biological samples and in vitro cellular assays for clinical diagnosis and forensic applications. The challenges and prospects of the role of electrochemical sensors, biosensors, and optical sensors for opioid analysis in promoting clinical diagnosis, forensic study, point-of-care, and community drug monitoring services to reduce harm are also provided.

Application of Metabolomics across the Spectrum of Pulmonary and Critical Care Medicine.

In recent years, metabolomics, the systematic study of small-molecule metabolites in biological samples, has yielded fresh insights into the molecular determinants of pulmonary diseases and critical illness. The purpose of this article is to orient the reader to this emerging field by discussing the fundamental tenets underlying metabolomics research, the tools and techniques that serve as foundational methodologies, and the various statistical approaches to analysis of metabolomics datasets. We present several examples of metabolomics applied to pulmonary and critical care medicine to illustrate the potential of this avenue of research to deepen our understanding of pathophysiology. We conclude by reviewing recent advances in the field and future research directions that stand to further the goal of personalizing medicine to improve patient care.

Analysis of vitamin D and its metabolites in biological samples – Part I: Optimization and comparison of UHPSFC-MS/MS and UHPLC-MS/MS methods

Fat-soluble vitamin D is an essential bioactive compound important for human health. Insufficient vitamin D levels can result not only in bone disease but also in other disorders, such as cancer, metabolic disorders, and diseases related to poor immune function. The current methods commonly used for vitamin D analysis are often applied to determine the levels of the most abundant metabolite in plasma, i.e., 25-OH-D2/D3. These methods do not consider the presence of other hydroxylated and esterified metabolites, including isomers and epimers, which are typically found in low concentrations.In this study, we developed a fast and selective ultra-high performance supercritical fluid chromatography (UHPSFC) method using a 150 mm long 1-amino anthracene (1-AA) column and a mobile phase consisting of carbon dioxide and methanol/isopropanol (1/1, v/v) mixed with 8 % water. After thorough optimization of column temperature and back pressure, the separation of four vitamin D3 esters, vitamin D3 and D2, and eight mono- and di-hydroxylated metabolites, including three groups of isomers, was achieved in 10 min. Two ion sources, atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization optimized within this study, were compared in tandem mass spectrometry (MS/MS) detection. No significant sensitivity differences were observed. Subsequently, the same 1-AA column chemistry was examined in ultra-high performance liquid chromatography (UHPLC) as the stationary phase that could hypothetically bring different selectivity in the separation of vitamin D and its metabolites. However, this hypothesis was rejected, and C18 was used as a stationary phase in the final optimized UHPLC-MS/MS method. Despite detailed optimization, the final 15 min UHPLC method was not able to separate di-hydroxylated isomers of vitamin D3, while it enabled better resolution of esterified forms compared to UHPSFC.Optimized methods provided similar repeatability of retention times and peak areas, with RSD < 2 % and 10 %, respectively. The lowest limits of quantification were in the range of 1.2 – 4.9 ng/mL for UHPSFC-APCI-MS/MS, while for UHPLC-APCI-MS/MS, they were typically in the range of 2.6 – 9.6 ng/mL. Based on the obtained results, the UHPSFC-APCI-MS/MS method was the most promising approach for fast, selective, and sensitive analysis that could be applied in the analysis of biological samples with emphasis on the separation of both hydroxylated and esterified metabolites, including isomeric forms.

Analysis of vitamin D and its metabolites in biological samples – Part II: Optimization of a sample preparation method for liver tissue

Extraction of vitamin D, including its hydroxylated and esterified metabolites, from soft tissues such as the liver is challenging due to the lipophilic character of matrix and analytes that are expected in very low concentration levels.In this study, we aimed at the optimization of two-step extraction using solid–liquid extraction as the first step, followed by solid-phase extraction. Various solvents, including ethanol, acetonitrile, methanol, acetone, heptane, and heptane with isopropanol, were investigated to isolate vitamin D compounds from liver tissue in the first step. Acetone was finally selected as the most suitable solvent for the solid–liquid extraction, with the highest recovery in the range of 67 – 98% for polar hydroxylated forms and 3 – 28% for lipophilic vitamin D and esters. Two solid phase extraction (SPE) based on the (i) “bind and elute strategy” and (ii) “removal strategy” using hydrophilic-lipophilic balanced SPE sorbent were optimized as a proceeding step for acetone extracts to increase the method selectivity. Finally, two optimized methods, combining solid–liquid extraction and individual SPE strategy, were examined in terms of sensitivity, recovery, matrix effect, accuracy, and precision.The limits of quantification were in the range of 1 – 10 ng/mL and 3 – 20 ng/mL analyzed by ultra-high performance supercritical fluid chromatography and ultra-high performance liquid chromatography hyphenated a with tandem mass spectrometer, respectively. The absolute recovery determined for the “bind and elute strategy” protocol was in the range of 3 – 24 %. Nevertheless, this method was free of matrix effects, which were determined to be in the 73 – 120 % range. On the contrary, the “removal strategy” approach provided higher recovery values for all compounds (47 – 123 %), but the results for nonpolar vitamin D and esters were strongly affected by signal suppression (matrix effects 3 – 51 %). Both methods fulfilled the criteria for accuracy and precision requested by the European Medicine Agency Guideline on Bioanalysis.“Removal strategy” SPE with decreased manual intervention and lower solvent consumption was finally applied to mouse liver tissue to determine vitamin D and its hydroxylated and esterified metabolites for the first time. The results, i.e., vitamin D esters detected in liver tissue, supported the notion that esters of vitamin D can be stored in lipophilic tissues to release vitamin D.

Novel LC-MS/MS Method for Simultaneous Determination of Monoamine Neurotransmitters and Metabolites in Human Samples.

For the simultaneous determination of monoamine neurotransmitters (NTs) like dopamine, serotonin, noradrenaline, and epinephrine, and their metabolites (metanephrine, normetanephrine, 3-methoxytyramine, vanillylmandelic acid, 3,4-dihydroxyphenylacetic acid, homovanillic acid, and 5-hydroxyindoleacetic acid), a robust liquid chromatography method coupled with tandem mass spectrometry (LC-MS/MS) was introduced as the analytical method. This analytical method proved to be accurate for the simultaneous measurement of the amounts of 11 NTs and their metabolites in biological samples. The method proved to be more efficient and better than the previously reported method in terms of precision, recovery, sample requirement, and extraction procedure. The reported method requires only 100 μL of blood and 200 μL of urine, and the extraction procedure requires acetonitrile precipitation, filtration, drying, and reconstitution in water. The separation of all analytes was performed on an C18 column (4.6 mm × 150 mm and 1.8 μm). A 10 min gradient elution program with a mobile phase consisting of phase A (0.2% formic acid in water) and phase B (methanol) was used. The positive ionization mode was used for the detection of all analytes in multiple reaction monitoring (MRM). The proposed method was validated with an internal standard and yielded lower limits of detection and quantification ranges of 0.0182-0.0797 ng/mL and 0.0553-0.2415 ng/mL, respectively, with a good linearity (R2) between 0.9959 and 0.9994. The recoveries ranged from 73.37% to 116.63% in blood and from 80.9% to 115.33% in urine. For the NTs and metabolites, the intra- and interday % CV were 0.24-9.36 and 0.85-9.67, respectively. The developed LC-MS/MS method was successfully used for the determination of trace amounts of endogenous compounds in human blood and urine samples.

Metabolomics: a review of liquid chromatography mass spectrometry-based methods and clinical applications

Abstract Introduction Metabolomics is a rapidly growing field that aims to understand the complex metabolic pathways involved in health and disease. Liquid chromatography mass spectrometry (LC-MS) based untargeted metabolomics has emerged as a powerful tool for investigating the metabolic changes associated with various diseases, and for identifying potential biomarkers for early disease detection and treatment monitoring. This review provides a comprehensive overview of LC-MS based untargeted metabolomics and its clinical applications. Content The advantages and challenges of untargeted metabolomics are discussed, encompassing sample preparation, data processing, sample storage, acquisition mode selection, column strategy, and annotation. The latest advancements in LC-MS technology and data analysis techniques are reviewed, which have facilitated the more accurate and sensitive detection of metabolites in biological samples. The clinical applications of untargeted metabolomics are emphasized, including its utilization in disease diagnosis, treatment monitoring, and personalized medicine. Examples are provided of how biomarkers for various diseases, such as cancer, coronary heart disease, and infectious disease, have been identified through the application of untargeted metabolomics. Summary and outlook Overall, LC-MS based untargeted metabolomics is a powerful tool for investigating the complex metabolic changes associated with various diseases, and has the potential to transform clinical diagnosis, treatment, and personalized medicine.

Analytical methods for detecting butane, propane, and their metabolites in biological samples: Implications for inhalant abuse detection

Worldwide, various inhalants are widely abused for recreational purposes, with butane and propane emerging as among the most commonly misused volatile substances, posing a significant risk of sudden death. The rapid elimination and oxidation of these highly volatile compounds upon inhalation necessitate the identification of butane and propane along with their metabolites in biological samples. Hence, the primary objective of this study is twofold: firstly, to establish a method for analyzing butane, propane, and metabolites, and secondly, to demonstrate the detection window and exposure indicators associated with the inhalation of butane and propane. In pursuit of this objective, we developed analytical methods for the determination of isobutane, n-butane, propane, and their nine metabolites in both blood and urine. Headspace-gas chromatography–mass spectrometry (GC–MS) and solid-phase microextraction-GC–MS were employed for the analyses, demonstrating acceptable precision and accuracy. An animal study revealed that isobutane and n-butane were only detectable below the limit of quantification (LOQ) in rat blood 5 min after exposure. Meanwhile, the three major metabolites—2-methyl-2-propanol, 2-butanol, and 2-butanone—were observed 5 min after exposure but persisted in rat urine even 5 h post-exposure. Additionally, human urine samples identified other metabolites, including acetone, acetoin, and 2,3-butanediol isomers. The presence of specific metabolites corresponding to each inhalant confirmed the abuse of butane and propane. This comprehensive approach provides valuable insights into the detection and assessment of inhalation to these volatile substances.

Recent findings and advancements in the detection of designer benzodiazepines: a brief review.

This review article takes a closer look at a new class of psychoactive substances called designer benzodiazepines (DBZs) and the challenges of their detection. These are adinazolam, clonazolam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, phenazepam, and pyrazolam. They are central nervous system depressants and sedatives that can cause psychomotor impairment and increase the overdose risk when combined with other sedatives. DBZs undergo phase I and II metabolism similar to traditional benzodiazepines, but their specific metabolic pathways and the influence of genetic polymorphisms are yet to be clarified. Advances in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enhanced the method's sensitivity for DBZs and their metabolites in biological samples and coupled with improved blood sampling methods require less blood for drug monitoring. Further research should focus on elucidating their pharmacokinetic properties and metabolism in humans, especially in view of genetic polymorphisms and drug interactions that could inform clinical treatment choices. Even though we have witnessed important advances in DBZ detection and measurement, further refinements are needed to expand the scope of detectable DBZs and their metabolites. All this should help toxicological research to better identify and characterise the risks of chronic and polydrug abuse and facilitate clinical, forensic, and regulatory responses to this growing issue.

Profiling Analysis of Tryptophan Metabolites in the Urine of Patients with Parkinson's Disease Using LC-MS/MS.

Although Parkinson's disease (PD) is a representative neurodegenerative disorder and shows characteristic motor impediments, the pathophysiological mechanisms and treatment targets for PD have not yet been clearly identified. Since several tryptophan metabolites produced by gut microbiota could pass the blood-brain barrier and, furthermore, might influence the central nervous system, tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways might be the most potent targets for PD development. Furthermore, most metabolites are circulated via the blood, play roles in and/or are metabolized via the host organs, and finally are excreted into the urine. Therefore, profiling the overall tryptophan metabolic pathways in urine samples of patients with PD is important to understanding the pathological mechanisms, finding biomarkers, and discovering therapeutic targets for PD. However, the development of profiling analysis based on tryptophan metabolism pathways in human urine samples is still challenging due to the wide physiological ranges, the varied signal response, and the structural diversity of tryptophan metabolites in complicated urine matrices. In this study, an LC-MS/MS method was developed to profile 21 tryptophan metabolites within the indole, kynurenine, and serotonin metabolic pathways in human urine samples using ion-pairing chromatography and multiple reaction monitoring determination. The developed method was successfully applied to urine samples of PD patients (n = 41) and controls (n = 20). Further, we investigated aberrant metabolites to find biomarkers for PD development and therapeutic targets based on the quantitative results. Unfortunately, most tryptophan metabolites in the urine samples did not present significant differences between control and PD patients, except for indole-3-acetic acid. Nonetheless, indole-3-acetic acid was reported for the first time for its aberrant urinary levels in PD patients and tentatively selected as a potential biomarker for PD. This study provides accurate quantitative results for 21 tryptophan metabolites in biological samples and will be helpful in revealing the pathological mechanisms of PD development, discovering biomarkers for PD, and further providing therapeutic targets for various PD symptoms. In the near future, to further investigate the relationship between gut microbial metabolites and PD, we will employ studies on microbial metabolites using plasma and stool samples from control and PD patients.

SPA-STOCSY: an automated tool for identifying annotated and non-annotated metabolites in high-throughput NMR spectra.

Nuclear magnetic resonance spectroscopy (NMR) is widely used to analyze metabolites in biological samples, but the analysis requires specific expertise, it is time-consuming, and can be inaccurate. Here, we present a powerful automate tool, SPatial clustering Algorithm-Statistical TOtal Correlation SpectroscopY (SPA-STOCSY), which overcomes challenges faced when analyzing NMR data and identifies metabolites in a sample with high accuracy. As a data-driven method, SPA-STOCSY estimates all parameters from the input dataset. It first investigates the covariance pattern among datapoints and then calculates the optimal threshold with which to cluster datapoints belonging to the same structural unit, i.e. the metabolite. Generated clusters are then automatically linked to a metabolite library to identify candidates. To assess SPA-STOCSY's efficiency and accuracy, we applied it to synthesized spectra and spectra acquired on Drosophila melanogaster tissue and human embryonic stem cells. In the synthesized spectra, SPA outperformed Statistical Recoupling of Variables (SRV), an existing method for clustering spectral peaks, by capturing a higher percentage of the signal regions and the close-to-zero noise regions. In the biological data, SPA-STOCSY performed comparably to the operator-based Chenomx analysis while avoiding operator bias, and it required <7min of total computation time. Overall, SPA-STOCSY is a fast, accurate, and unbiased tool for untargeted analysis of metabolites in the NMR spectra. It may thus accelerate the use of NMR for scientific discoveries, medical diagnostics, and patient-specific decision making. The codes of SPA-STOCSY are available at https://github.com/LiuzLab/SPA-STOCSY.

Immobilized Enzymes on Magnetic Beads for Separate Mass Spectrometric Investigation of Human Phase II Metabolite Classes.

The human body has evolved to remove xenobiotics through a multistep clearance process. Non-endogenous metabolites are converted through a series of phase I and different phase II enzymes into compounds with higher hydrophilicity. These compounds are important for diverse research fields such as toxicology, nutrition, biomarker discovery, doping control, and microbiome metabolism. One of the challenges in these research fields has been the investigation of the two major phase II modifications, sulfation and glucuronidation, and the corresponding unconjugated aglycon independently. We have now developed a new methodology utilizing an immobilized arylsulfatase and an immobilized β-glucuronidase to magnetic beads for treatment of human urine samples. The enzyme activities remained the same compared to the enzyme in solution. The separate mass spectrometric investigation of each metabolite class in a single sample was successfully applied to obtain the dietary glucuronidation and sulfation profile of 116 compounds. Our new chemical biology strategy provides a new tool for the investigation of metabolites in biological samples with the potential for broad-scale application in metabolomics, nutrition, and microbiome studies.

Quantitative Metabolomic Dataset of Avian Eye Lenses

Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics may help to reveal the molecular basis of a disease, make a diagnosis, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lenses from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrating with other “-omics” data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing, with the final table containing information on the abundance of 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. The data were obtained using the bird specimens collected in compliance with ethical standards and revealed potential differences in metabolic pathways due to phylogenetic differences or environmental exposure.

Profiling of Amino Metabolites in Biological Samples without Protein Precipitation Using a Solid-Phase-Supported Phenyl Isothiocyanate-Based Chemoselective Probe.

Amino metabolites are essential for life activities and can be used clinically as biomarkers for disease diagnosis and treatment. Solid-phase-supported chemoselective probes can simplify sample handling and enhance detection sensitivity. However, the low efficiency and complicated preparation of traditional probes limit their further application. In this work, a novel solid-phase-supported probe Fe3O4-SiO2-polymers-phenyl isothiocyanate (FSP-PITC) was developed by immobilizing phenyl isothiocyanate on magnetic beads with disulfide as an orthogonal cleavage site, which can couple amino metabolites directly regardless of whether proteins and other matrixes were removed. After purification, the targeted metabolites were released by dithiothreitol and detected by high-resolution mass spectrometry. The simplified processing steps shorten the analysis time, and the introduction of polymers results in a 100-1000-fold increase in probe capacity. With high stability and specificity, FSP-PITC pretreatment allows accurate qualitative and quantitative (R2 > 0.99) analysis, facilitating the detection of metabolites in subfemtomole quantities. Using this strategy, 4158 metabolite signals were detected in negative ion mode. Among them, 352 amino metabolites including human cells (226), serum (227), and mouse samples (274) were searched from the Human Metabolome Database. These metabolites participate in metabolic pathways of amino acids, biogenic amine, and the urea cycle. All these results indicate that FSP-PITC is a promising probe for novel metabolite discovery and high-throughput screening.

Quantitative plasma profiling by 1H NMR-based metabolomics: impact of sample treatment.

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.

Comparison of serum metabolomics in women with breast Cancer Prior to Chemotherapy and at 1 year: cardiometabolic implications

ObjectiveEarly-stage breast cancer (BC) is the second most common malignancy in women, worldwide. Early-detection and treatment advances have led to 5-year survival rates of 90% for early-stage breast cancer. However, the long-term morbidity of breast cancer remains high, with a majority of survivors facing increased risk of cardiometabolic conditions as well as secondary cancers. In particular, African American women with breast cancer experience higher morbidity and mortality than other women. Metabolomics is the comprehensive study of metabolites in biological samples to elucidate the role of monosaccharides, amino acids, and their respective metabolic pathways. Although some studies have found differential metabolites in women with breast cancer compared to normal controls, there has been little study of women with breast cancer across time and the active treatment trajectory. This study examines and compares the serum metabolomic profile of women with BC, prior to initial chemotherapy and at 1 year after inception of chemotherapy.MethodsThis study examined serum metabolites through a secondary analysis of a longitudinal parent study (EPIGEN) of women diagnosed with early-stage BC. Participants were evaluated across 5 time points: prior to their receipt of chemotherapy (T1), at the time of their 4th chemotherapy treatment (T2), 6 months after the initiation of chemotherapy (T3), one year after the initiation of chemotherapy (T4) and two years after the initiation of chemotherapy (T5). This analysis focused on the metabolomic data from 70 participants from T1 to T4. Using ultra high-pressure liquid chromatography high resolution mass spectrometry (UHPLC-HRMS), we performed Friedman Rank Sum Test followed by Nemenyi post-hoc pairwise tests to identify which metabolite levels differed between time points, focusing on metabolites with a Benjamini-Hochberg false discovery rate (FDR) from the overall Friedman test < 0.05 and then specifically examined the p-values from the T1 vs. T4 pairwise comparison.ResultsThe untargeted serum metabolomics yielded a total of 2,395 metabolites identified on the basis of the accurate mass and MS/MS fragmentation, 1,264 of which were significant after Friedman’s test (FDR < 0.05). The analysis then focused on the levels of 124 metabolites from the T1 vs. T4 post-hoc comparison that had a combined FDR < 0.05 and fold change (FC) > 2.0. Metabolite set enrichment analysis (MSEA) as part of Metaboanalyst 3.0 was performed to identify pathways that were significantly altered. The known metabolites identified from the functional analysis were used to evaluate the up and down regulated pathways. The 40metabolites from the Functional Analysis were mainly attributed to amino acids (specifically lysine regulation), fatty acids (particularly unsaturated) and steroid hormone synthesis (lysophosphatidic acid).ConclusionThere were multiple significant changes in the serum metabolomic profile of women with breast cancer at one-year post inception of chemotherapy compared to pre-chemotherapy, most notably associated with lysine degradation, branched-chain amino acid synthesis, linoleic acid metabolism, tyrosine metabolism and biosynthesis of unsaturated fatty acids as the top 5 metabolic pathways. Some of these changes could be associated with metabolic perturbations that are consistent with heightened risk of cardiometabolic morbidity. Our results provide new insights into the mechanisms underlying potential heightened cardiovascular health risks in this population.