Current Situation of the Metabolomics Techniques Used for the Metabolism Studies of New Psychoactive Substances

Metabolic profiling of a new synthetic cannabinoid receptor agonist, ADMB-FUBIATA, with human liver microsomes, human primary hepatocytes and human recombinant CYP450 enzymes using LC-quadrupole-orbitrap MS

A novel synthetic cannabinoid receptor agonist (SCRA), ADMB-FUBIATA, featuring an acetamide-linked structure, has emerged on the illicit drug market. To provide dependable verification of its consumption and identify reliable biomarkers, we investigated an in vitro metabolism study of ADMB-FUBIATA incubated with human primary hepatocytes (HPHs) for the first time and correlated our findings with those from human liver microsomes (HLMs). In this work, ADMB-FUBIATA (10 μM) was incubated with HLM and HPH for 1 and 5 h, respectively, and then subjected to LC-quadrupole-orbitrap MS. A total of 25 metabolites across 8 metabolic pathways were identified after incubation with HLM and HPH, respectively. Monohydroxylation and N-dealkylation were the major metabolic pathways, and formation to ketone was first identified. In addition, the metabolism of ADMB-FUBIATA were found to be mediated by multiple CYP450 enzymes, predominantly CYP2C19, 2D6, and 3A4. This research also initially characterized the fragmentation patterns of the metabolites of ADMB-FUBIATA, elaborating on their structural relationship with ADMB-FUBIATA analogs. To effectively monitor ADMB-FUBIATA abuse, metabolites M4 and M1 were proposed as reliable biomarkers by cross-validating the HLM and HPH incubation results.

Impact of three different peak picking software tools on the quality of untargeted metabolomics data

Data quality and control parameters are becoming more important in metabolomics. For peak picking, open-source or commercial solutions are used. Other publications consider different software solutions or data acquisition types for peak picking, a combination, including proposed and new quality parameters for the process of peak picking, does not exist. This study tries to examine the performance of three different software in terms of reproducibility and quality of their output while also considering new quality parameters to gain a better understanding of resulting feature lists in metabolomics data. We saw best recovery of spiked analytes in MS-DIAL. Reproducibility over multiple projects was good among all software. The total number of features found was consistent for DDA and full scan acquisition in MS-DIAL but full scan data leading to considerably more features in MZmine and Progenesis Qi. Feature linearity proved to be a good quality parameter. Features in MS-DIAL and MZmine, showed good linearity while Progenesis Qi produced large variation, especially in full scan data. Peak width proved to be a very powerful filtering criteria revealing many features in MZmine and Progenesis Qi to be of questionable peak width. Additionally, full scan data appears to produce a disproportionally higher number of short features. This parameter is not yet available in MS-DIAL. Finally, the manual classification of true positive features proved MS-DIAL to perform significantly better in DDA data (62 % true positive) than the two other software in either mode. We showed that currently popular solutions MS-DIAL and MZmine perform well in targeted analysis of spiked analytes as well as in classic untargeted analysis. The commercially available solution Progenesis Qi does not hold any advantage over the two in terms of quality parameters, of which we proposed peak width as a new parameter and showed that already proposed parameters such as feature linearity in samples of increasing concentration are advisable to use.

The metabolic recovery of marathon runners: an untargeted 1H-NMR metabolomics perspective

Introduction: Extreme endurance events may result in numerous adverse metabolic, immunologic, and physiological perturbations that may diminish athletic performance and adversely affect the overall health status of an athlete, especially in the absence of sufficient recovery. A comprehensive understanding of the post-marathon recovering metabolome, may aid in the identification of new biomarkers associated with marathon-induced stress, recovery, and adaptation, which can facilitate the development of improved training and recovery programs and personalized monitoring of athletic health/recovery/performance. Nevertheless, an untargeted, multi-disciplinary elucidation of the complex underlying biochemical mechanisms involved in recovery after such an endurance event is yet to be demonstrated. Methods: This investigation employed an untargeted proton nuclear magnetic resonance metabolomics approach to characterize the post-marathon recovering metabolome by systematically comparing the pre-, immediately post, 24, and 48 h post-marathon serum metabolite profiles of 15 athletes. Results and Discussion: A total of 26 metabolites were identified to fluctuate significantly among post-marathon and recovery time points and were mainly attributed to the recovery of adenosine triphosphate, redox balance and glycogen stores, amino acid oxidation, changes to gut microbiota, and energy drink consumption during the post-marathon recovery phase. Additionally, metabolites associated with delayed-onset muscle soreness were observed; however, the mechanisms underlying this commonly reported phenomenon remain to be elucidated. Although complete metabolic recovery of the energy-producing pathways and fuel substrate stores was attained within the 48 h recovery period, several metabolites remained perturbed throughout the 48 h recovery period and/or fluctuated again following their initial recovery to pre-marathon-related levels.

Metabolomics during the spontaneous fermentation in cocoa (Theobroma cacao L.): An exploraty review

Spontaneous fermentation is a process that depends on substrates' physical characteristics, crop variety, and postharvest practices; it induces variations in the metabolites that are responsible for the taste, aroma, and quality. Metabolomics makes it possible to detect key metabolites using chemometrics and makes it possible to establish patterns or identify biomarker behaviors under certain conditions at a given time. Therefore, sensitive and highly efficient analytical techniques allow for studying the metabolomic fingerprint changes during fermentation; which identify and quantify metabolites related to taste and aroma formation of an adequate processing time. This review shows that studying metabolomics in spontaneous fermentation permits the characterization of spontaneous fermentation in different stages. Also, it demonstrates the possibility of modulating the quality of cocoa by improving the spontaneous fermentation time (because of volatile aromatic compounds formation), thus standardizing the process to obtain attributes and quality that will later impact the chocolate quality.

Towards Extending the Detection Window of Gamma-Hydroxybutyric Acid-An Untargeted Metabolomics Study in Serum and Urine Following Controlled Administration in Healthy Men

In forensic toxicology, gamma-hydroxybutyrate (GHB) still represents one of the most challenging drugs of abuse in terms of analytical detection and interpretation. Given its rapid elimination, the detection window of GHB in common matrices is short (maximum 12 h in urine). Additionally, the differentiation from naturally occurring endogenous GHB, is challenging. Thus, novel biomarkers to extend the detection window of GHB are urgently needed. The present study aimed at searching new potential biomarkers of GHB use by means of mass spectrometry (MS) metabolomic profiling in serum (up to 16.5 h) and urine samples (up to 8 h after intake) collected during a placebo-controlled crossover study in healthy men. MS data acquired by different analytical methods (reversed phase and hydrophilic interaction liquid chromatography; positive and negative electrospray ionization each) were filtered for significantly changed features applying univariate and mixed-effect model statistics. Complementary to a former study, conjugates of GHB with glycine, glutamate, taurine, carnitine and pentose (ribose) were identified in urine, with particularly GHB-pentose being promising for longer detection. None of the conjugates were detectable in serum. Therein, mainly energy metabolic substrates were identified, which may be useful for more detailed interpretation of underlying pathways but are too unspecific as biomarkers.

Hyphenated high-resolution mass spectrometry-the "all-in-one" device in analytical toxicology?

This trend article reviews papers with hyphenated high-resolution mass spectrometry (HRMS) approaches applied in analytical toxicology, particularly in clinical and forensic toxicology published since 2016 and referenced in PubMed. The article focuses on the question of whether HRMS has or will become the all-in-one device in these fields as supposed by the increasing number of HRMS presentations at scientific meetings, corresponding original papers, and review articles. Typical examples for the different application fields are discussed such as targeted or untargeted drug screening, quantification, drug metabolism studies, and metabolomics approaches. Considering the reviewed papers, HRMS is currently the only technique that fulfills the criteria of an all-in-one device for the various applications needed in analytical toxicology.

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Toxicometabolomics of the new psychoactive substances α-PBP and α-PEP studied in HepaRG cell incubates by means of untargeted metabolomics revealed unexpected amino acid adducts

Toxicometabolomics, essentially applying metabolomics to toxicology of endogenous compounds such as drugs of abuse or new psychoactive substances (NPS), can be investigated by using different in vitro models and dedicated metabolomics techniques to enhance the number of relevant findings. The present study aimed to study the toxicometabolomics of the two NPS α-pyrrolidinobutiophenone (1-phenyl-2-(pyrrolidin-1-yl)butan-1-one, α-PBP) and α-pyrrolidinoheptaphenone (1-phenyl-2-(pyrrolidin-1-yl)heptan-1-one, α-PEP, PV8) in HepaRG cell line incubates. Evaluation was performed using reversed-phase and normal-phase liquid chromatography coupled with high-resolution mass spectrometry in positive and negative ionization mode, respectively, to analyze cells and cell media. Statistical evaluation was performed using one-way ANOVA, principal component discriminant function analysis, as well as hierarchical clustering. In general, the analysis of cells did not mainly reveal any features, but the parent compounds of the drugs of abuse. For α-PBP an increase in N-methylnicotinamide was found, which may indicate hepatotoxic potential of the substance. After analysis of cell media, significant features led to the identification of several metabolites of both compounds. Amino acid adducts with glycine and alanine were found, and these have not been described in any study before and are likely to appear in vivo. Additionally, significant changes in the metabolism of cholesterol were revealed after incubation with α-PEP. In summary, the application of metabolomics techniques after HepaRG cells exposure to NPS did not lead to an increased number of identified drug metabolites compared to previously published studies, but gave a wider perspective on the physiological effect of the investigated compounds on human liver cells.