Application Of Metabolomic Techniques Research Articles

Metabolomics-Based Mechanistic Insights into Revealing the Adverse Effects of Pesticides on Plants: An Interactive Review.

In plant biology, metabolomics is often used to quantitatively assess small molecules, metabolites, and their intermediates in plants. Metabolomics has frequently been applied to detect metabolic alterations in plants exposed to various biotic and abiotic stresses, including pesticides. The widespread use of pesticides and agrochemicals in intensive crop production systems is a serious threat to the functionality and sustainability of agroecosystems. Pesticide accumulation in soil may disrupt soil-plant relationships, thereby posing a pollution risk to agricultural output. Application of metabolomic techniques in the assessment of the biological consequences of pesticides at the molecular level has emerged as a crucial technique in exposome investigations. State-of-the-art metabolomic approaches such as GC-MS, LC-MS/MS UHPLC, UPLC-IMS-QToF, GC/EI/MS, MALDI-TOF MS, and 1H-HR-MAS NMR, etc., investigating the harmful effects of agricultural pesticides have been reviewed. This updated review seeks to outline the key uses of metabolomics related to the evaluation of the toxicological impacts of pesticides on agronomically important crops in exposome assays as well as bench-scale studies. Overall, this review describes the potential uses of metabolomics as a method for evaluating the safety of agricultural chemicals for regulatory applications. Additionally, the most recent developments in metabolomic tools applied to pesticide toxicology and also the difficulties in utilizing this approach are discussed.

Finding CYP2D6 activity biomarkers by correlating MDMA pharmacokinetic parameters to untargeted metabolomics data

Cytochrome P450 (CYP) enzymes play a major role in drug metabolism. Many of these enzymes exhibit a huge inter-individual variation in activity, not only attributable to the individual's genotype. Such environmental influences are hardly measurable, let alone their outcome predictable. The actual phenotype is usually determined through administration of well-studied CYP probe substrates – an approach that is obviously unsuitable for forensic investigations, particularly postmortem. Therefore, we aimed at finding alternative biomarkers of the CYP phenotype. Application of metabolomics techniques in theory should reveal endogenous metabolites processed by CYP isoenzymes, which in turn could be indicative for a person's phenotype for particular CYP isoenzymes (e.g. 2D6). In a standard metabolomics approach, features (unidentified metabolites) could be compared between different known CYP genotype/phenotypes. While this approach is most promising, a controlled study needs to be conducted including genotyping and probe-substrate phenotyping. Instead of a new phenotyping study, we aimed to explore the intended approach with a previous crossover study with a typical CYP2D6 substrate (MDMA) and a known inhibitor of CYP2D6 (bupropion) for the general suitability to find endogenous correlates of CYP2D6 activity. Plasma samples of a controlled MDMA/bupropion crossover study with four experimental test sessions (pretreatment – study day as follows: placebo-placebo, bupropion – placebo, placebo-MDMA, and bupropion-MDMA, n = 16 each), initially intended to study pharmacological questions, were reused. Plasma from timepoint 9 from the placebo-placebo and bupropion-placebo session were worked-up by simple protein precipitation and measured with a previously published untargeted metabolomics method (Boxler. Drug Test Anal 2019;11(5):678–696). Briefly, LC-qTOF-MS (Sciex 6600) with reversed-phase (RP) and HILIC chromatography was used in both positive and negative ESI mode. Untargeted data was analysed using msDial 4.8 and a pre-release version of SIRIUS (5.4.1) for structure elucidation and comparison to common databases. Feature peak areas were correlated (spearman) with the ratio of the area under the curve (AUC) of MDMA metabolites/AUC MDMA as determined as the best CYP2D6 correlate in a former targeted analysis (Steuer. Plos One 2016;11:e0150955). Further filter criteria were: fold change between groups of > 2 or < 0.5 and mean S/N > 150. Out of 24858 features found in RP positive mode, by correlation analysis, 27 features with a spearman correlation greater than 0.55 and with assigned MS/MS and 109 features without MS/MS information were found, respectively. As expected, 3 of the features could be unambiguously identified to be bupropion and its known metabolites. Further 10 features indicated a chlorine cluster, not expected endogenously, which pointed to further fragments/metabolites or artifacts of bupropion. The remaining 14 features could be considered as promising biomarker candidates not related to bupropion and as such as tentative indicators of the respective CYP2D6 phenotype. Using the pharmacokinetic parameters of MDMA, acting as a CYP2D6 substrate, with and without CYP2D6 inhibition by bupropion and corresponding metabolomics data, we could show, that the metabolome approach is able to find potential biomarkers for actual CYP2D6 status. As unfortunately typical for untargeted metabolomics, final identification of features still remains the bottleneck and requires further investigation. In addition, the applicability of the found biomarkers of course needs to be tested in a larger independent cohort. Ideally, a ratio of features that are substrate and product of the enzyme could be formed to increase the predictive power of this approach.

Metabolic Syndrome and PCOS: Pathogenesis and the Role of Metabolites.

Polycystic ovary syndrome (PCOS) is one of the most common endocrine diseases among women of reproductive age and is associated with many metabolic manifestations, such as obesity, insulin resistance (IR) and hyperandrogenism. The underlying pathogenesis of these metabolic symptoms has not yet been fully elucidated. With the application of metabolomics techniques, a variety of metabolite changes have been observed in the serum and follicular fluid (FF) of PCOS patients and animal models. Changes in metabolites result from the daily diet and occur during uncommon physiological routines. However, some of these metabolite changes may provide evidence to explain possible mechanisms and new approaches for prevention and therapy. This article reviews the pathogenesis of PCOS metabolic symptoms and the relationship between metabolites and the pathophysiology of PCOS. Furthermore, the potential clinical application of some specific metabolites will be discussed.

Toxicometabolomics of the new psychoactive substances \u03b1-PBP and \u03b1-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.

Simplifying the complex: metabolomics approaches in chemical ecology.

Chemical signals are important mediators of organismal interactions. These interactions significantly influence ecosystem structure and thus are crucial to understand. Ecologists and analytical chemists work closely together to identify the specific molecules regulating ecological interactions. However, limitations in the analytical techniques on the one hand and time-demanding bioassays on the other have been restraining chemical ecology research. Application of metabolomics techniques has recently led to significant advancement of the field. Here, we discuss modifications to the traditional bioassay-guided fractionation approach with metabolomics techniques. We focus on two challenging topics within chemical ecology, waterborne cues and single-cell investigations, to highlight how metabolomics techniques can succeed where traditional approaches have failed. Graphical abstract ᅟ.

Crop metabolomics: from diagnostics to assisted breeding.

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding. We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality. Translational metabolomics applied to crop breeding programs.