Altered metabolic pathways elucidated via untargeted in vivo toxicometabolomics in rat urine and plasma samples collected after controlled application of a human equivalent amphetamine dose

Amphetamine is widely consumed as drug of abuse due to its stimulating and cognitive enhancing effects. Since amphetamine has been on the market for quite a long time and it is one of the most commonly used stimulants worldwide, to date there is still limited information on its effects on the metabolome. In recent years, untargeted toxicometabolomics have been increasingly used to study toxicity-related pathways of such drugs of abuse to find and identify important endogenous and exogenous biomarkers. In this study, the acute effects of amphetamine intake on plasma and urinary metabolome in rats were investigated. For this purpose, samples of male Wistar rats after a single dose of amphetamine (5 mg/kg) were compared to a control group using an untargeted metabolomics approach. Analysis was performed using normal and reversed phase liquid chromatography coupled to high-resolution mass spectrometry using positive and negative ionization mode. Statistical evaluation was performed using Welch’s two-sample t test, hierarchical clustering, as well as principal component analysis. The results of this study demonstrate a downregulation of amino acids in plasma samples after amphetamine exposure. Furthermore, four new potential biomarkers N-acetylamphetamine, N-acetyl-4-hydroxyamphetamine, N-acetyl-4-hydroxyamphetamine glucuronide, and amphetamine succinate were identified in urine. The present study complements previous data and shows that several studies are necessary to elucidate altered metabolic pathways associated with acute amphetamine exposure

Method development for quantitative determination of seven statins including four active metabolites by means of high-resolution tandem mass spectrometry applicable for adherence testing and therapeutic drug monitoring

Background: Statins are used to treat and prevent cardiovascular diseases (CVDs) by reducing the total serum cholesterol concentration. Unfortunately, dose-related side effects and sub-optimal response, attributed to non-adherence amongst others, were described. Therefore, a fast and sensitive liquid chromatography-high-resolution tandem mass spectrometry (LC-HRMS/MS) method for adherence testing and therapeutic drug monitoring of all currently marketed statins and their active metabolites in human blood plasma should be developed, validated and tested for applicability. Methods:Atorvastatin, fluvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, and simvastatin, as well as ortho- and para-hydroxy-atorvastatin, lovastatin hydroxy acid and simvastatin hydroxy acid were included and several internal standards (IS) tested. Validation was performed according to the guideline of the European Medicines Agency including selectivity, carry-over, accuracy, precision, matrix effects, dilution integrity and analyte stability. Finally, applicability was tested using 14 patient samples submitted for regular toxicological analysis. Results: Due to an analytical interference of atorvastatin-d5, diazepam-d5 and pentobarbital-d5 were chosen as IS for positive and negative ionization mode, respectively. All statins and metabolites fulfilled the validation acceptance criteria except for fluvastatin, which could not be quantified reliably and reproducibly, most probably due to instability. Analyses of human plasma samples revealed concentrations of statins and metabolites below the reference plasma concentrations in the case of eight patients. However, nothing was known concerning patients’ adherence and time between intake and sampling. Conclusions: An LC-HRMS/MS method for identification and quantification of atorvastatin, lovastatin, pitavastatin, pravastatin, rosuvastatin, simvastatin and four active metabolites was successfully developed and applicability demonstrated

In Vitro and In Vivo Toxicometabolomics of the Synthetic Cathinone PCYP Studied by Means of LC-HRMS/MS

Synthetic cathinones are one important group amongst new psychoactive substances (NPS) and limited information is available regarding their toxicokinetics and -dynamics. Over the past few years, nontargeted toxicometabolomics has been increasingly used to study compound-related effects of NPS to identify important exogenous and endogenous biomarkers. In this study, the effects of the synthetic cathinone PCYP (2-cyclohexyl-1-phenyl-2-(1-pyrrolidinyl)-ethanone) on in vitro and in vivo metabolomes were investigated. Pooled human-liver microsomes and blood and urine of male Wistar rats were used to generate in vitro and in vivo data, respectively. Samples were analyzed by liquid chromatography and high-resolution mass spectrometry using an untargeted metabolomics workflow. Statistical evaluation was performed using univariate and multivariate statistics. In total, sixteen phase I and one phase II metabolite of PCYP could be identified as exogenous biomarkers. Five endogenous biomarkers (e.g., adenosine and metabolites of tryptophan metabolism) related to PCYP intake could be identified in rat samples. The present data on the exogenous biomarker of PCYP are crucial for setting up analytical screening procedures. The data on the endogenous biomarker are important for further studies to better understand the physiological changes associated with cathinone abuse but may also serve in the future as additional markers for an intake

Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data

The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normaland reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions

Addendum: Hemmer, S., et al. Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data. Metabolites 2020, 10, 378

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Evaluation of extraction methods for untargeted metabolomic studies for future applications in zebrafish larvae infection models

Sample preparation in untargeted metabolomics should allow reproducible extractions of as many molecules as possible. Thus, optimizing sample preparation is crucial. This study compared six diferent extraction procedures to fnd the most suitable for extracting zebrafsh larvae in the context of an infection model. Two one-phase extractions employing methanol (I) and a single miscible phase of methanol/acetonitrile/water (II) and two two-phase methods using phase separation between chloroform and methanol/water combinations (III and IV) were tested. Additional bead homogenization was used for methods III and IV (III_B and IV_B). Nine internal standards and 59 molecules of interest (MoInt) related to mycobacterial infection were used for method evaluation. Two-phase methods (III and IV) led to a lower feature count, higher peak areas of MoInt, especially amino acids, and higher coefcients of variation in comparison to one-phase extractions. Adding bead homogenization increased feature count, peak areas, and CVs. Extraction I showed higher peak areas and lower CVs than extraction II, thus being the most suited one-phase method. Extraction III and IV showed similar results, with III being easier to execute and less prone to imprecisions. Thus, for future applications in zebrafsh larvae metabolomics and infection models, extractions I and III might be chosen

Accessing the strong interaction between Λ baryons and charged kaons with the femtoscopy technique at the LHC

The interaction between Λ baryons and kaons/antikaons is a crucial ingredient for the strangeness S=0 and S=-2 sector of the meson–baryon interaction at low energies. In particular, the Lambda-Kbar might help in understanding the origin of states such as the Csi(1620), whose nature and properties are still under debate. Experimental data on Lambda-K and Lambda-Kbar systems are scarce, leading to large uncertainties and tension between the available theoretical predictions constrained by such data. In this Letter we present the measurements of Λ–KK− and Λ–KK+ correlations obtained in the high-multiplicity triggered data sample in pp collisions at sqrt(s) = 13 TeV recorded by ALICE at the LHC. The correlation function for both pairs is modeled using the Lednický–Lyuboshits analytical formula and the corresponding scattering parameters are extracted. The Λ–KK+ correlations show the presence of several structures at relative momenta k* above 200 MeV/c, compatible with the Ω baryon, the , and resonances decaying into Λ–K− pairs. The low k* region in the Λ–KK+ also exhibits the presence of the state, expected to strongly couple to the measured pair. The presented data allow to access the ΛK+ and ΛK− strong interaction with an unprecedented precision and deliver the first experimental observation of the decaying into ΛK−

Optimization and application of in vitro and in vivo toxicometabolomics studies

To improve the identification of new drug metabolites and to elucidate changes in the endogenous metabolism after drug consumption, several untargeted metabolomics techniques were investigated and optimized. Initially, a suitable sample preparation for urine samples was investigated. Subsequently, the analytical method was optimized for different matrices with respect to the used liquid chromatography columns. To obtain reliable information from the raw data and to ensure a meaningful biological interpretation, different data processing workflows were compared. Finally, two substances of interest due to their potential for abuse were investigated both in vitro and in vivo using untargeted toxicometabolomics. The optimization of various techniques demonstrated that parameters from sample collection to biological interpretation should be adapted to the research question and carefully considered beforehand, as each parameter has an influence on the outcome of the study. The two untargeted metabolomics studies indicated that the use of toxicometabolomics studies can provide both toxicokinetic data and information on the mode of action of drugs of abuse. Furthermore, toxicometabolomics studies can circumvent conventional screening methods by identifying both metabolites and endogenous biomarkers that would not have been expected.Im Hinblick auf einen besseren Nachweis neuer Drogenmetabolite und Veränderungen des Stoffwechsels nach dem Konsum von Drogen, wurden verschiedene ungezielte Metabolomik-Techniken untersucht und optimiert. Zunächst wurde eine geeignete Probenaufarbeitung für Urinproben untersucht. Nachfolgend wurde die analytische Methode in Bezug auf die verwendeten Flüssigkeitschromatographie Säulen unter Berücksichtigung verschiedener Matrizes optimiert. Zur Gewinnung verwertbarer Informationen aus Rohdaten und Sicherstellung einer aussagekräftigen biologischen Interpretation, wurden im Anschluss verschiedene Arbeitsabläufe zur Datenprozessierung verglichen. Im letzten Schritt wurden zwei Substanzen aufgrund ihres Missbrauchspotentials mithilfe der ungezielten Toxikometabolomik in vitro und in vivo untersucht. Die Optimierung der verschiedenen Techniken ergab, dass alle Parameter von der Probenentnahme bis zur biologischen Interpretation an die Fragestellung angepasst und zuvor sorgfältig untersucht werden sollten, da jeder Parameter einen Einfluss auf das Ergebnis der Studie hatte. Die beiden nicht-zielgerichteten Metabolom-Studien ergaben, dass Toxikometabolomik-Studien toxikokinetische Daten und Informationen über die Wirkungsweise von Missbrauchsdrogen liefern können. Toxikometabolomik-Studien ermöglichen es, herkömmliche Screening-Methoden zu umgehen, indem sie sowohl Metabolite als auch endogene Biomarker identifizieren können, die nicht zu erwarten gewesen wären

In Vitro and In Vivo Toxicometabolomics of the Synthetic Cathinone PCYP Studied by Means of LC-HRMS/MS

Synthetic cathinones are one important group amongst new psychoactive substances (NPS) and limited information is available regarding their toxicokinetics and -dynamics. Over the past few years, nontargeted toxicometabolomics has been increasingly used to study compound-related effects of NPS to identify important exogenous and endogenous biomarkers. In this study, the effects of the synthetic cathinone PCYP (2-cyclohexyl-1-phenyl-2-(1-pyrrolidinyl)-ethanone) on in vitro and in vivo metabolomes were investigated. Pooled human-liver microsomes and blood and urine of male Wistar rats were used to generate in vitro and in vivo data, respectively. Samples were analyzed by liquid chromatography and high-resolution mass spectrometry using an untargeted metabolomics workflow. Statistical evaluation was performed using univariate and multivariate statistics. In total, sixteen phase I and one phase II metabolite of PCYP could be identified as exogenous biomarkers. Five endogenous biomarkers (e.g., adenosine and metabolites of tryptophan metabolism) related to PCYP intake could be identified in rat samples. The present data on the exogenous biomarker of PCYP are crucial for setting up analytical screening procedures. The data on the endogenous biomarker are important for further studies to better understand the physiological changes associated with cathinone abuse but may also serve in the future as additional markers for an intake

Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data

The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normal- and reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions