Detection Of Endogenous Metabolites Research Articles

Development of LC-HRMS untargeted analysis methods for nasal epithelial lining fluid exposomics.

The nasal mucosa, as a primary site of entry for inhaled substances, contains both inhaled xenobiotic and endogenous biomarkers. Nasal mucosa can be non-invasively sampled (nasal epithelial lining fluid "NELF") and analyzed for biological mediators. However, methods for untargeted analysis of compounds inhaled and/or retained in the nasal mucosa are needed. This study aimed to develop a high resolution LC-MS untargeted method to analyze collected NELF. Profiling of compounds in NELF samples will also provide baseline data for future comparative studies to reference. Extracted NELF analytes were injected to LC-ESI-MS. After spectrum processing, an in-house library provided annotations with high confidence, while more tentative annotation proposals were obtained via ChemSpider database matching. The established method successfully detected unique molecular signatures within NELF. Baseline profiling of 27 samples detected 2002 unknown molecules, with 77 and 463 proposed structures by our in-house library and Chemspider matching. High confidence annotations revealed common metabolites and tentative annotations implied various environmental exposure biomarkers are also present in NELF. The experimental pipeline for analyzing NELF samples serves as simple and robust method applicable for future studies to characterize identities/effects of inhaled substances and metabolites retained in the nasal mucosa. The nasal mucosa contains exogenous and endogenous compounds. The development of an untargeted analysis is necessary to characterize the nasal exposome by deciphering the identity and influence of inhaled compounds on nasal mucosal biology. This study established a high resolution LC-MS based untargeted analysis of non-invasively collected nasal epithelial lining fluid. Baseline profiling of the nasal mucosa (n = 27) suggests the presence of environmental pollutants, along with detection of endogenous metabolites. Our results show high potential for the analytical pipeline to facilitate future respiratory health studies involving inhaled pollutants or pharmaceutical compounds and their effects on respiratory biology.

Multi‐Dimensional Organic Mass Cytometry: Simultaneous Analysis of Proteins and Metabolites on Single Cells

AbstractMass cytometry is attracting significant attention for enabling spatiotemporal high‐throughput single‐cell analysis. As the first demonstration of the simultaneous detection of single‐cell proteins and untargeted metabolites, a multi‐dimensional organic mass‐cytometry system was established by a simple microfluidic chip connected to a nanoelectrospray mass spectrometer, providing useful heterogeneous information about the cells. A series of mass probes with online‐dissociated mass tags were developed, ensuring the semi‐quantification of cell‐surface proteins and the compatibility of endogenous metabolite detection at the single‐cell level. Six cell surface antigens and ≈100 metabolites from three ovarian‐cancer cell types and two breast‐cancer cell types were successfully monitored and contributed to highly sensitive and specific cell typing. Doxorubicin‐resistant cancer‐cell analysis confirmed the applications in distinguishing rare cell phenotypes. The proposed system is simple, extensible, and promising for cell typing, drug‐resistance analysis of tumor cells, and clinical diagnosis and therapy at the single‐cell level.

Multi-Dimensional Organic Mass Cytometry: Simultaneous Analysis of Proteins and Metabolites on Single Cells.

Mass cytometry is attracting significant attention for enabling spatiotemporal high-throughput single-cell analysis. As the first demonstration of the simultaneous detection of single-cell proteins and untargeted metabolites, a multi-dimensional organic mass-cytometry system was established by a simple microfluidic chip connected to a nanoelectrospray mass spectrometer, providing useful heterogeneous information about the cells. A series of mass probes with online-dissociated mass tags were developed, ensuring the semi-quantification of cell-surface proteins and the compatibility of endogenous metabolite detection at the single-cell level. Six cell surface antigens and ≈100 metabolites from three ovarian-cancer cell types and two breast-cancer cell types were successfully monitored and contributed to highly sensitive and specific cell typing. Doxorubicin-resistant cancer-cell analysis confirmed the applications in distinguishing rare cell phenotypes. The proposed system is simple, extensible, and promising for cell typing, drug-resistance analysis of tumor cells, and clinical diagnosis and therapy at the single-cell level.

Comparative Untargeted Metabolomics Analysis of the Psychostimulants 3,4-Methylenedioxy-Methamphetamine (MDMA), Amphetamine, and the Novel Psychoactive Substance Mephedrone after Controlled Drug Administration to Humans.

Psychoactive stimulants are a popular drug class which are used recreationally. Over the last decade, large numbers of new psychoactive substances (NPS) have entered the drug market and these pose a worldwide problem to human health. Metabolomics approaches are useful tools for simultaneous detection of endogenous metabolites affected by drug use. They allow identification of pathways or characteristic metabolites, which might support the understanding of pharmacological actions or act as indirect biomarkers of consumption behavior or analytical detectability. Herein, we performed a comparative metabolic profiling of three psychoactive stimulant drugs 3,4-methylenedioxymethamphetamine (MDMA), amphetamine and the NPS mephedrone by liquid chromatography-high resolution mass spectrometry (LC-HRMS) in order to identify common pathways or compounds. Plasma samples were obtained from controlled administration studies to humans. Various metabolites were identified as increased or decreased based on drug intake, mainly belonging to energy metabolism, steroid biosynthesis and amino acids. Linoleic acid and pregnenolone-sulfate changed similarly in response to intake of all drugs. Overall, mephedrone produced a profile more similar to that of amphetamine than MDMA in terms of affected energy metabolism. These data can provide the basis for further in-depth targeted metabolome studies on pharmacological actions and search for biomarkers of drug use.

Spatially resolved endogenous improved metabolite detection in human osteoarthritis cartilage by matrix assisted laser desorption ionization mass spectrometry imaging.

Osteoarthritis (OA) is one of the most common musculoskeletal diseases, characterized by the progressive deterioration of articular cartilage. Although the disease has been well studied in the past few years, the endogenous metabolic composition and more importantly the spatial information of these molecules in cartilage is still poorly understood. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) has been previously used for the investigation of the bimolecular distribution of proteins and lipids through the in situ analysis of cartilage tissue sections. MALDI-MSI as a tool to detect metabolites remains challenging, as these species have low abundance and degrade rapidly. In this work, we present a complete methodology, from sample preparation to data analysis for the detection of endogenous metabolites on cartilage by MSI. Our results demonstrate for the first time the ability to detect small molecules in fragile, challenging tissues through an optimized protocol, and render MSI as a tool towards a better understanding of OA.

Frequency and phase correction for multiplexed edited MRS of GABA and glutathione.

Detection of endogenous metabolites using multiplexed editing substantially improves the efficiency of edited magnetic resonance spectroscopy. Multiplexed editing (i.e., performing more than one edited experiment in a single acquisition) requires a tailored, robust approach for correction of frequency and phase offsets. Here, a novel method for frequency and phase correction (FPC) based on spectral registration is presented and compared against previously presented approaches. One simulated dataset and 40 γ-aminobutyric acid-/glutathione-edited HERMES datasets acquired in vivo at three imaging centers were used to test four FPC approaches: no correction; spectral registration; spectral registration with post hoc choline-creatine alignment; and multistep FPC. The performance of each routine for the simulated dataset was assessed by comparing the estimated frequency/phase offsets against the known values, whereas the performance for the in vivo data was assessed quantitatively by calculation of an alignment quality metric based on choline subtraction artifacts. The multistep FPC approach returned corrections that were closest to the true values for the simulated dataset. Alignment quality scores were on average worst for no correction, and best for multistep FPC in both the γ-aminobutyric acid- and glutathione-edited spectra in the in vivo data. Multistep FPC results in improved correction of frequency/phase errors in multiplexed γ-aminobutyric acid-/glutathione-edited magnetic resonance spectroscopy experiments. The optimal FPC strategy is experiment-specific, and may even be dataset-specific. Magn Reson Med 80:21-28, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Distinguishing between the metabolome and xenobiotic exposome in environmental field samples analysed by direct-infusion mass spectrometry based metabolomics and lipidomics.

Environmental metabolomics is increasingly used to investigate organismal responses to complex chemical mixtures, including waste water effluent (WWE). In parallel, increasingly sensitive analytical methods are being used in metabolomics studies, particularly mass spectrometry. This introduces a considerable, yet overlooked, challenge that high analytical sensitivity will not only improve the detection of endogenous metabolites in biological specimens but also exogenous chemicals. If these often unknown xenobiotic features are not removed from the “biological” dataset, they will bias the interpretation and could lead to incorrect conclusions about the biotic response. Here we illustrate and validate a novel workflow classifying the origin of peaks detected in biological samples as: endogenous, xenobiotics, or metabolised xenobiotics. The workflow is demonstrated using direct infusion mass spectrometry-based metabolomic analysis of testes from roach exposed to different concentrations of a complex WWE. We show that xenobiotics and their metabolic products can be detected in roach testes (including triclosan, chloroxylenol and chlorophene), and that these compounds have a disproportionately high level of statistical significance within the total (bio)chemical changes induced by the WWE. Overall we have demonstrated that this workflow extracts more information from an environmental metabolomics study of complex mixture exposures than was possible previously.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-014-0693-3) contains supplementary material, which is available to authorized users.

Negative mode nanostructure-initiator mass spectrometry for detection of phosphorylated metabolites

The chemical complexity of the metabolome requires the development of new detection methods to enlarge the range of compounds detectable in a biological sample. Recently, a novel matrix-free laser desorption/ionization method called nanostructure-initiator mass spectrometry (NIMS) [Northen et al., Nature 449(7165):1033–1036, 2007] was reported. Here we investigate NIMS in negative ion mode for the detection of endogenous metabolites, namely small phosphorylated molecules. 3-Aminopropyldimethylethoxysilane was found to be suitable as initiator for the analytes studied and a limit of detection in the tens of femtomoles was reached. The detection of different endogenous cell metabolites in a yeast cell extract is demonstrated.

Clinical biochemical genetics in the twenty-first century.

Genetic disorders are recognized to play an increasing role in pediatrics. Close to 10% of diseases among hospitalized children have been ascribed to Mendelian traits inherited as single gene defects, not a surprising figure considering that approximately 1000 inborn errors of metabolism (IEM) have been identified to date, primarily through the detection of endogenous metabolites abnormally accumulated in biological fluids and tissues. The laboratory discipline that covers the biochemical diagnosis of IEM is known as clinical biochemical genetics, and is defined as one concerned with the evaluation and diagnosis of patients and families with inherited metabolic disease, monitoring of treatment, and distinguishing heterozygous carriers from non-carriers by metabolite and enzymic analysis of physiological fluids and tissues. The biochemical genetics laboratory differs from the clinical chemistry laboratory in the extent of interpretation necessary to make its results meaningful to the clinician. While dramatic advances in molecular genetics have greatly changed the landscape of diagnostic options for many genetic disorders, a biochemical approach remains the dominant force for the diagnosis and monitoring of IEM. Owing to the stereotypical clinical presentation of many of these disorders, a major role of the biochemical genetics laboratory is to analyze ever more complex metabolic profiles to reach a preliminary diagnosis, which then needs to be confirmed by enzymic and/or molecular studies in vitro. Accordingly, the role of biochemical genetics in the pediatric practice of the 21st century is to provide a multicomponent screening process that can be divided into four major components: (i) at-risk screening (prenatal diagnosis); (ii) newborn screening (testing of presymptomatic patients); (iii) high-risk screening (testing of symptomatic patients); and (iv) postmortem screening (metabolic autopsy). The focus of our laboratory is to apply state-of-the-art technology such as tandem mass spectrometry to bring as many as possible IEM within the boundaries of newborn screening programs, and to investigate the role played by individual disorders in maternal complications of pregnancy, pediatric acute/fulminant liver failure, and sudden and unexpected death in early life.