72 research outputs found

    Single-Step Extraction Coupled with Targeted HILIC-MS/MS Approach for Comprehensive Analysis of Human Plasma Lipidome and Polar Metabolome.

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    Expanding metabolome coverage to include complex lipids and polar metabolites is essential in the generation of well-founded hypotheses in biological assays. Traditionally, lipid extraction is performed by liquid-liquid extraction using either methyl-tert-butyl ether (MTBE) or chloroform, and polar metabolite extraction using methanol. Here, we evaluated the performance of single-step sample preparation methods for simultaneous extraction of the complex lipidome and polar metabolome from human plasma. The method performance was evaluated using high-coverage Hydrophilic Interaction Liquid Chromatography-ESI coupled to tandem mass spectrometry (HILIC-ESI-MS/MS) methodology targeting a panel of 1159 lipids and 374 polar metabolites. The criteria used for method evaluation comprised protein precipitation efficiency, and relative MS signal abundance and repeatability of detectable lipid and polar metabolites in human plasma. Among the tested methods, the isopropanol (IPA) and 1-butanol:methanol (BUME) mixtures were selected as the best compromises for the simultaneous extraction of complex lipids and polar metabolites, allowing for the detection of 584 lipid species and 116 polar metabolites. The extraction with IPA showed the greatest reproducibility with the highest number of lipid species detected with the coefficient of variation (CV) < 30%. Besides this difference, both IPA and BUME allowed for the high-throughput extraction and reproducible measurement of a large panel of complex lipids and polar metabolites, thus warranting their application in large-scale human population studies

    Sex-specific alterations in NAD+ metabolism in 3xTg Alzheimer's disease mouse brain assessed by quantitative targeted LC-MS.

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    Levels of nicotinamide adenine dinucleotide (NAD+) are known to decline with age and have been associated with impaired mitochondrial function leading to neurodegeneration, a key facet of Alzheimer's disease (AD). NAD+synthesis is sustained via tryptophan-kynurenine (Trp-Kyn) pathway as de novo synthesis route, and salvage pathways dependent on the availability of nicotinic acid and nicotinamide. While being currently investigated as a multifactorial disease with a strong metabolic component, AD remains without curative treatment and important sex differences were reported in relation to disease onset and progression. The aim of this study was to reveal the potential deregulation of NAD+metabolism in AD with the direct analysis of NAD+precursors in the mouse brain tissue (wild type (WT) versus triple transgenic (3xTg) AD), using a sex-balanced design. To this end, we developed a quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) method, which allowed for the measurement of the full spectrum of NAD+precursors and intermediates in all three pathways. In brain tissue of mice with developed AD symptoms, a decrease in kynurenine (Kyn) versus increase in kynurenic acid (KA) levels were observed in both sexes with a significantly higher increment of KA in males. These alterations in Trp-Kyn pathway might be a consequence of neuroinflammation and a compensatory production of neuroprotective kynurenic acid. In the NAD+ salvage pathway, significantly lower levels of nicotinamide mononucleotide (NMN) were measured in the AD brain of males and females. Depletion of NMN implies the deregulation of salvage pathway critical for maintaining optimal NAD+ levels and mitochondrial and neuronal function

    Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models.

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    Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems

    Metabolic View on Human Healthspan: A Lipidome-Wide Association Study.

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    As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied 'omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level

    LC-HRMS data as a result of untargeted metabolomic profiling of human cerebrospinal fluid.

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    Cerebrospinal fluid (CSF) is a key body fluid that maintains the homeostasis in central nervous system (CNS). As a biofluid whose content reflects the brain metabolic activity, the CSF is analyzed in the context of neurological diseases and is rarely collected from healthy subjects. For this reason, the metabolite variation associated with general phenotypic characteristics such as gender and age have hardly ever been studied. Here we present the hydrophilic interaction liquid chromatography-high resolution mass spectrometry (HILIC-HRMS) data as a result of untargeted metabolomics analysis of a cohort of elderly cognitively healthy volunteers ( <i>n</i>  = 32). 146 unambiguously identified water soluble metabolites (using accurate mass, retention time and MS/MS matching against spectral libraries) were measured and their abundances across all the subjects depending on their gender are provided in this article. Data tables are available at https://data.mendeley.com/datasets/c73xtsd4s5/1. it's published on mendeley, the DOI is DOI:10.17632/c73xtsd4s5.1. The data presented in this article are related to the research article entitled "A global HILIC-MS approach to measure polar human cerebrospinal fluid metabolome: Exploring gender-associated variation in a cohort of elderly cognitively healthy subjects" (Gallart-Ayala et al., 2018, In press)

    New trends in fast liquid chromatography for food and environmental analysis

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    Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study

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    Introduction Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. Methods Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12–18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. Results A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10−20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10−4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. Conclusions This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma

    Advances in structure elucidation of small molecules using mass spectrometry

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    The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules
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