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Sample records for highly-parallel metabolomics approaches

  1. Mathematical Modeling Approaches in Plant Metabolomics.

    Science.gov (United States)

    Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas

    2018-01-01

    The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.

  2. Proteomic and metabolomic approaches to biomarker discovery

    CERN Document Server

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  3. Modeling of fatigue crack induced nonlinear ultrasonics using a highly parallelized explicit local interaction simulation approach

    Science.gov (United States)

    Shen, Yanfeng; Cesnik, Carlos E. S.

    2016-04-01

    This paper presents a parallelized modeling technique for the efficient simulation of nonlinear ultrasonics introduced by the wave interaction with fatigue cracks. The elastodynamic wave equations with contact effects are formulated using an explicit Local Interaction Simulation Approach (LISA). The LISA formulation is extended to capture the contact-impact phenomena during the wave damage interaction based on the penalty method. A Coulomb friction model is integrated into the computation procedure to capture the stick-slip contact shear motion. The LISA procedure is coded using the Compute Unified Device Architecture (CUDA), which enables the highly parallelized supercomputing on powerful graphic cards. Both the explicit contact formulation and the parallel feature facilitates LISA's superb computational efficiency over the conventional finite element method (FEM). The theoretical formulations based on the penalty method is introduced and a guideline for the proper choice of the contact stiffness is given. The convergence behavior of the solution under various contact stiffness values is examined. A numerical benchmark problem is used to investigate the new LISA formulation and results are compared with a conventional contact finite element solution. Various nonlinear ultrasonic phenomena are successfully captured using this contact LISA formulation, including the generation of nonlinear higher harmonic responses. Nonlinear mode conversion of guided waves at fatigue cracks is also studied.

  4. New approaches for metabolomics by mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Vertes, Akos [George Washington Univ., Washington, DC (United States)

    2017-07-10

    Small molecules constitute a large part of the world around us, including fossil and some renewable energy sources. Solar energy harvested by plants and bacteria is converted into energy rich small molecules on a massive scale. Some of the worst contaminants of the environment and compounds of interest for national security also fall in the category of small molecules. The development of large scale metabolomic analysis methods lags behind the state of the art established for genomics and proteomics. This is commonly attributed to the diversity of molecular classes included in a metabolome. Unlike nucleic acids and proteins, metabolites do not have standard building blocks, and, as a result, their molecular properties exhibit a wide spectrum. This impedes the development of dedicated separation and spectroscopic methods. Mass spectrometry (MS) is a strong contender in the quest for a quantitative analytical tool with extensive metabolite coverage. Although various MS-based techniques are emerging for metabolomics, many of these approaches include extensive sample preparation that make large scale studies resource intensive and slow. New ionization methods are redefining the range of analytical problems that can be solved using MS. This project developed new approaches for the direct analysis of small molecules in unprocessed samples, as well as pushed the limits of ultratrace analysis in volume limited complex samples. The projects resulted in techniques that enabled metabolomics investigations with enhanced molecular coverage, as well as the study of cellular response to stimuli on a single cell level. Effectively individual cells became reaction vessels, where we followed the response of a complex biological system to external perturbation. We established two new analytical platforms for the direct study of metabolic changes in cells and tissues following external perturbation. For this purpose we developed a novel technique, laser ablation electrospray

  5. Metabolomics, a promising approach to translational research in cardiology

    Directory of Open Access Journals (Sweden)

    Martino Deidda

    2015-12-01

    In this article, we will provide a description of metabolomics in comparison with other, better known “omics” disciplines such as genomics and proteomics. In addition, we will review the current rationale for the implementation of metabolomics in cardiology, its basic methodology and the available data from human studies in this discipline. The topics covered will delineate the importance of being able to use the metabolomic information to understand the mechanisms of diseases from the perspective of systems biology, and as a non-invasive approach to the diagnosis, grading and treatment of cardiovascular diseases.

  6. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    Metabolomics is the analysis of the whole metabolome and the focus in metabolomics studies is to measure as many metabolites as possible. The use of chemometrics in metabolomics studies is widespread, but there is a clear lack of validation in the developed models. The focus in this thesis has been...... how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR...... is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...

  7. LightForce Photon-Pressure Collision Avoidance: Updated Efficiency Analysis Utilizing a Highly Parallel Simulation Approach

    Science.gov (United States)

    Stupl, Jan; Faber, Nicolas; Foster, Cyrus; Yang, Fan Yang; Nelson, Bron; Aziz, Jonathan; Nuttall, Andrew; Henze, Chris; Levit, Creon

    2014-01-01

    This paper provides an updated efficiency analysis of the LightForce space debris collision avoidance scheme. LightForce aims to prevent collisions on warning by utilizing photon pressure from ground based, commercial off the shelf lasers. Past research has shown that a few ground-based systems consisting of 10 kilowatt class lasers directed by 1.5 meter telescopes with adaptive optics could lower the expected number of collisions in Low Earth Orbit (LEO) by an order of magnitude. Our simulation approach utilizes the entire Two Line Element (TLE) catalogue in LEO for a given day as initial input. Least-squares fitting of a TLE time series is used for an improved orbit estimate. We then calculate the probability of collision for all LEO objects in the catalogue for a time step of the simulation. The conjunctions that exceed a threshold probability of collision are then engaged by a simulated network of laser ground stations. After those engagements, the perturbed orbits are used to re-assess the probability of collision and evaluate the efficiency of the system. This paper describes new simulations with three updated aspects: 1) By utilizing a highly parallel simulation approach employing hundreds of processors, we have extended our analysis to a much broader dataset. The simulation time is extended to one year. 2) We analyze not only the efficiency of LightForce on conjunctions that naturally occur, but also take into account conjunctions caused by orbit perturbations due to LightForce engagements. 3) We use a new simulation approach that is regularly updating the LightForce engagement strategy, as it would be during actual operations. In this paper we present our simulation approach to parallelize the efficiency analysis, its computational performance and the resulting expected efficiency of the LightForce collision avoidance system. Results indicate that utilizing a network of four LightForce stations with 20 kilowatt lasers, 85% of all conjunctions with a

  8. Computational Approaches for Integrative Analysis of the Metabolome and Microbiome

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    Jasmine Chong

    2017-11-01

    Full Text Available The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics to enable resolution of microbiome-conferred functionalities associated with health. However, analyzing the resulting multi-omics data remains a significant challenge in current microbiome studies. In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation analysis to metabolic network-based modeling approaches. Throughout the process, we strive to present a unified conceptual framework for multi-omics integration and interpretation, as well as point out potential future directions.

  9. Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches.

    Science.gov (United States)

    Checkley, William; Deza, Maria P; Klawitter, Jost; Romero, Karina M; Klawitter, Jelena; Pollard, Suzanne L; Wise, Robert A; Christians, Uwe; Hansel, Nadia N

    2016-12-01

    The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p  13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that serum metabolomics may represent a diagnostic tool for asthma and may be helpful for distinguishing asthma phenotypes. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Biomarker discovery in neurological diseases: a metabolomic approach

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    Afaf El-Ansary

    2009-12-01

    Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

  11. Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

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    Perrin H. Beatty

    2016-10-01

    Full Text Available A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.

  12. A LC-MS metabolomics approach to investigate the effect of raw apple intake in the rat plasma metabolome

    DEFF Research Database (Denmark)

    Rago, Daniela; Kristensen, Mette; Gürdeniz, Gözde

    2013-01-01

    Fruit and vegetable consumption has been associated with several health benefits; however the mechanisms are largely unknown at the biochemical level. Our research aims to investigate whether plasma metabolome profiling can reflect biological effects after feeding rats with raw apple by using...... an untargeted UPLC–ESI– TOF–MS based metabolomics approach in both positive and negative mode. Eighty young male rats were randomised into groups receiving daily 0, 5 or 10 g fresh apple slices, respectively, for 13 weeks. During weeks 3–6 some of the animals were receiving 4 mg/ml 1,2-dimethylhydrazine...

  13. Characterization and Discrimination of Ancient Grains: A Metabolomics Approach

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    Laura Righetti

    2016-07-01

    Full Text Available Hulled, or ancient, wheats were the earliest domesticated wheats by mankind and the ancestors of current wheats. Their cultivation drastically decreased during the 1960s; however, the increasing demand for a healthy and equilibrated diet led to rediscovering these grains. Our aim was to use a non-targeted metabolomic approach to discriminate and characterize similarities and differences between ancient Triticum varieties. For this purpose, 77 hulled wheat samples from three different varieties were collected: Garfagnana T. turgidum var. dicoccum L. (emmer, ID331 T. monococcum L. (einkorn and Rouquin T. spelta L. (spelt. The ultra high performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-QTOF metabolomics approach highlighted a pronounced sample clustering according to the wheat variety, with an excellent predictability (Q2, for all the models built. Fifteen metabolites were tentatively identified based on accurate masses, isotopic pattern, and product ion spectra. Among these, alkylresorcinols (ARs were found to be significantly higher in spelt and emmer, showing different homologue composition. Furthermore, phosphatidylcholines (PC and lysophosphatidylcholines (lysoPC levels were higher in einkorn variety. The results obtained in this study confirmed the importance of ARs as markers to distinguish between Triticum species and revealed their values as cultivar markers, being not affected by the environmental influences.

  14. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    Science.gov (United States)

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-07-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states.

  15. Metabolomics approach for discovering disease biomarkers and understanding metabolic pathway

    Directory of Open Access Journals (Sweden)

    Jeeyoun Jung

    2011-12-01

    Full Text Available Metabolomics, the multi-targeted analysis of endogenous metabolites from biological samples, can be efficiently applied to screen disease biomarkers and investigate pathophysiological processes. Metabolites change rapidly in response to physiological perturbations, making them the closest link to disease phenotypes. This study explored the role of metabolomics in gaining mechanistic insight into disease processes and in searching for novel biomarkers of human diseases

  16. Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health.

    Science.gov (United States)

    Vernocchi, Pamela; Del Chierico, Federica; Putignani, Lorenza

    2016-01-01

    The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies.

  17. Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

    Science.gov (United States)

    Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

    2017-03-01

    Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

  18. Understanding Aquatic Rhizosphere Processes Through Metabolomics and Metagenomics Approach

    Science.gov (United States)

    Lee, Yong Jian; Mynampati, Kalyan; Drautz, Daniela; Arumugam, Krithika; Williams, Rohan; Schuster, Stephan; Kjelleberg, Staffan; Swarup, Sanjay

    2013-04-01

    The aquatic rhizosphere is a region around the roots of aquatic plants. Many studies focusing on terrestrial rhizosphere have led to a good understanding of the interactions between the roots, its exudates and its associated rhizobacteria. The rhizosphere of free-floating roots, however, is a different habitat that poses several additional challenges, including rapid diffusion rates of signals and nutrient molecules, which are further influenced by the hydrodynamic forces. These can lead to rapid diffusion and complicates the studying of diffusible factors from both plant and/or rhizobacterial origins. These plant systems are being increasingly used for self purification of water bodies to provide sustainable solution. A better understanding of these processes will help in improving their performance for ecological engineering of freshwater systems. The same principles can also be used to improve the yield of hydroponic cultures. Novel toolsets and approaches are needed to investigate the processes occurring in the aquatic rhizosphere. We are interested in understanding the interaction between root exudates and the complex microbial communities that are associated with the roots, using a systems biology approach involving metabolomics and metagenomics. With this aim, we have developed a RhizoFlowCell (RFC) system that provides a controlled study of aquatic plants, observed the root biofilms, collect root exudates and subject the rhizosphere system to changes in various chemical or physical perturbations. As proof of concept, we have used RFC to test the response of root exudation patterns of Pandanus amaryllifolius after exposure to the pollutant naphthalene. Complexity of root exudates in the aquatic rhizosphere was captured using this device and analysed using LC-qTOF-MS. The highly complex metabolomic profile allowed us to study the dynamics of the response of roots to varying levels of naphthalene. The metabolic profile changed within 5mins after spiking with

  19. Profiling the metabolome changes caused by cranberry procyanidins in plasma of female rats using (1) H NMR and UHPLC-Q-Orbitrap-HRMS global metabolomics approaches.

    Science.gov (United States)

    Liu, Haiyan; Garrett, Timothy J; Tayyari, Fariba; Gu, Liwei

    2015-11-01

    The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using (1) H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Twenty-four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for three times using a 250 mg extracts/kg body weight dose. Plasma was collected 6 h after the last gavage and analyzed using (1) H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using (1) H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in the plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulphate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4'-O-methyl-(-)-epicatechin-3'-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(-)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-ϒ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  20. Profiling the Metabolome Changes Caused by Cranberry Procyanidins in Plasma of Female Rats using 1H NMR and UHPLC-Q-Orbitrap-HRMS Global Metabolomics Approaches

    Science.gov (United States)

    Liu, Haiyan; Garrett, Timothy J.; Tayyari, Fariba; Gu, Liwei

    2015-01-01

    Scope The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using 1H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Methods and results Twenty four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for 3 times using a 250 mg extracts/kg body weight dose. Plasma were collected six hours after the last gavage and analyzed using 1H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using 1H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulfate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4′-O-methyl-(−)-epicatechin-3′-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(−)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-γ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. Conclusion The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. PMID:26264887

  1. Short overview on metabolomic approach and redox changes in psychiatric disorders

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    Gordana Nedic Erjavec

    2018-04-01

    Full Text Available Schizophrenia, depression and posttraumatic stress disorder (PTSD are severe mental disorders and complicated diagnostic entities, due to their phenotypic, biological and genetic heterogeneity, unknown etiology, and poorly understood alterations in biological pathways and biological mechanisms. Disturbed homeostasis between overproduction of oxidant species, overcoming redox regulation and a lack of cellular antioxidant defenses, resulting in free radical-mediated pathology and subsequent neurotoxicity contributes to development of depression, schizophrenia and PTSD, their heterogeneous clinical presentation and resistance to treatment. Metabolomics is a discipline that combines different strategies with the aim to extract, detect, identify and quantify all metabolites that are present in a biological sample and might provide mechanistic insights into the etiology of various psychiatric disorders. Therefore, oxidative stress research combined with metabolomics might offer a novel approach in dissecting psychiatric disorders, since these data-driven but not necessarily hypothesis-driven methods might identify new targets, molecules and pathways responsible for development of schizophrenia, depression or PTSD. Findings from the oxidative research in psychiatry together with metabolomics data might facilitate development of specific and validated prognostic, therapeutic and clinical biomarkers. These methods might reveal bio-signatures of individual patients, leading to individualized treatment approach. In reviewing findings related to oxidative stress and metabolomics in selected psychiatric disorders, we have highlighted how these novel approaches might make a unique contribution to deeper understanding of psychopathological alterations underlying schizophrenia, depression and PTSD. Keywords: Schizophrenia, Depression, Posttraumatic stress disorder, Oxidative stress, Lipid peroxidation, Metabolomics, Biomarkers

  2. What Have Metabolomics Approaches Taught Us About Type 2 Diabetes?

    DEFF Research Database (Denmark)

    Gonzalez-Franquesa, Alba; Burkart, Alison M; Isganaitis, Elvira

    2016-01-01

    Type 2 diabetes (T2D) is increasing worldwide, making identification of biomarkers for detection, staging, and effective prevention strategies an especially critical scientific and medical goal. Fortunately, advances in metabolomics techniques, together with improvements in bioinformatics....... Conversely, tricarboxylic acid cycle intermediates, betaine, and other metabolites decrease. Future studies will be required to fully integrate these and other findings into our understanding of diabetes pathophysiology and to identify biomarkers of disease risk, stage, and responsiveness to specific...

  3. Chitosan and grape secondary metabolites: A proteomics and metabolomics approach

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    Bavaresco Luigi

    2017-01-01

    Full Text Available Chitosan is a polysaccharide obtained by deacetylation of chitin, and it is involved in defence mechanisms of plants toward diseases. In the present work, V. vinifera L. cv. Ortrugo, grafted on 420A rootstock was grown in pot and treated, at veraison, by 0.03% chitosan solution at cluster level. Just before the treatment (T0 and 24 hours (T1, 48 hours (T2, 72 hours (T3 and 10 days (T4 later, the concentration of stilbenic compounds was detected, and at T1 proteomics and metabolomics analyses were done. Proteomics relies on the analysis of the complete set of proteins existing in a given substrate, while metabolomics relies on the analyses of the complete set of metabolites in a given substrate. The treatment improved the stilbene concentration over the control at T1. Proteomic analysis showed that superoxide dismutase (SOD and phenylalanine ammonia-lyase (PAL were overexpressed in the treated grapes. SOD is known to be an enzyme active against reactive oxygen species (ROS while PAL is a key enzyme in the phenylpropanoids pathway. Metabolomics analysis highlighted the positive role of the treatment in improving the triperpenoid concentration (betulin, erythrodiol, uvaol, oleanolate; these compounds are known to be effective against microbes, insects and fungi.

  4. A functional genomics approach using metabolomics and in silico pathway analysis

    DEFF Research Database (Denmark)

    Förster, Jochen; Gombert, Andreas Karoly; Nielsen, Jens

    2002-01-01

    analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway...

  5. A 'Foodomic' Approach for the Evaluation of Food Quality and its Impact on the Human Metabolome

    DEFF Research Database (Denmark)

    Trimigno, Alessia

    In recent years, omic sciences have been increasingly employed in a multitude of research fields thanks to their high-throughput capabilities and holistic approach. Among the omic sciences, metabolomics and foodomics have recently emerged in the investigation of food and nutrition and their relat......In recent years, omic sciences have been increasingly employed in a multitude of research fields thanks to their high-throughput capabilities and holistic approach. Among the omic sciences, metabolomics and foodomics have recently emerged in the investigation of food and nutrition...... and their relation to the individual health and wellness status (Chapter 1). The analytical platforms used are ideal for non-targeted analysis, due to their capability of detecting and identifying a large set of variables (or metabolites) in complex biological samples. The most employed metabolomics techniques...... carried out both in Italy and in Denmark, outlines the analytical pipeline of the foodomic approach and highlights the current challenges in the field (Chapter 2.3). The thesis traces the path of modern foodomics and metabolomics from the definition and description of food quality (Chapters 3 to 6...

  6. A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism.

    Science.gov (United States)

    Jacob, Minnie; Malkawi, Abeer; Albast, Nour; Al Bougha, Salam; Lopata, Andreas; Dasouki, Majed; Abdel Rahman, Anas M

    2018-09-26

    Metabolome, the ultimate functional product of the genome, can be studied through identification and quantification of small molecules. The global metabolome influences the individual phenotype through clinical and environmental interventions. Metabolomics has become an integral part of clinical research and allowed for another dimension of better understanding of disease pathophysiology and mechanism. More than 95% of the clinical biochemistry laboratory routine workload is based on small molecular identification, which can potentially be analyzed through metabolomics. However, multiple challenges in clinical metabolomics impact the entire workflow and data quality, thus the biological interpretation needs to be standardized for a reproducible outcome. Herein, we introduce the establishment of a comprehensive targeted metabolomics method for a panel of 220 clinically relevant metabolites using Liquid chromatography-tandem mass spectrometry (LC-MS/MS) standardized for clinical research. The sensitivity, reproducibility and molecular stability of each targeted metabolite (amino acids, organic acids, acylcarnitines, sugars, bile acids, neurotransmitters, polyamines, and hormones) were assessed under multiple experimental conditions. The metabolic tissue distribution was determined in various rat organs. Furthermore, the method was validated in dry blood spot (DBS) samples collected from patients known to have various inborn errors of metabolism (IEMs). Using this approach, our panel appears to be sensitive and robust as it demonstrated differential and unique metabolic profiles in various rat tissues. Also, as a prospective screening method, this panel of diverse metabolites has the ability to identify patients with a wide range of IEMs who otherwise may need multiple, time-consuming and expensive biochemical assays causing a delay in clinical management. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. A metabolomic approach to animal vitreous humor topographical composition: a pilot study.

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    Emanuela Locci

    Full Text Available The purpose of this study was to evaluate the feasibility of a (1H-NMR-based metabolomic approach to explore the metabolomic signature of different topographical areas of vitreous humor (VH in an animal model. Five ocular globes were enucleated from five goats and immediately frozen at -80 °C. Once frozen, three of them were sectioned, and four samples corresponding to four different VH areas were collected: the cortical, core, and basal, which was further divided into a superior and an inferior fraction. An additional two samples were collected that were representative of the whole vitreous body. (1H-NMR spectra were acquired for twenty-three goat vitreous samples with the aim of characterizing the metabolomic signature of this biofluid and identifying whether any site-specific patterns were present. Multivariate statistical analysis (MVA of the spectral data were carried out, including Principal Component Analysis (PCA, Hierarchical Cluster Analysis (HCA, and Partial Least Squares Discriminant Analysis (PLS-DA. A unique metabolomic signature belonging to each area was observed. The cortical area was characterized by lactate, glutamine, choline, and its derivatives, N-acetyl groups, creatine, and glycerol; the core area was characterized by glucose, acetate, and scyllo-inositol; and the basal area was characterized by branched-chain amino acids (BCAA, betaine, alanine, ascorbate, lysine, and myo-inositol. We propose a speculative approach on the topographic role of these molecules that are mainly responsible for metabolic differences among the as-identified areas. (1H-NMR-based metabolomic analysis has shown to be an important tool for investigating the VH. In particular, this approach was able to assess in the samples here analyzed the presence of different functional areas on the basis of a different metabolite distribution.

  8. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

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    Hardy Nigel

    2006-06-01

    Full Text Available Abstract Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. Conclusion The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

  9. Metabolomic approach to human brain spectroscopy identifies associations between clinical features and the frontal lobe metabolome in multiple sclerosis

    Science.gov (United States)

    Vingara, Lisa K.; Yu, Hui Jing; Wagshul, Mark E.; Serafin, Dana; Christodoulou, Christopher; Pelczer, István; Krupp, Lauren B.; Maletić-Savatić, Mirjana

    2013-01-01

    Proton magnetic resonance spectroscopy (1H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo 1H-MRS from frontal lobe white matter of 27 patients with relapsing–remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials. PMID:23751863

  10. Short overview on metabolomics approach to study pathophysiology of oxidative stress in cancer

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    Luka Andrisic

    2018-04-01

    Full Text Available Association of oxidative stress with carcinogenesis is well known, but not understood well, as is pathophysiology of oxidative stress generated during different types of anti-cancer treatments. Moreover, recent findings indicate that cancer associated lipid peroxidation might eventually help defending adjacent nonmalignant cells from cancer invasion. Therefore, untargeted metabolomics studies designed for advanced translational and clinical studies are needed to understand the existing paradoxes in oncology, including those related to controversial usage of antioxidants aiming to prevent or treat cancer. In this short review we have tried to put emphasis on the importance of pathophysiology of oxidative stress and lipid peroxidation in cancer development in relation to metabolic adaptation of particular types of cancer allowing us to conclude that adaptation to oxidative stress is one of the main driving forces of cancer pathophysiology. With the help of metabolomics many novel findings are being achieved thus encouraging further scientific breakthroughs. Combined with targeted qualitative and quantitative methods, especially immunochemistry, further research might reveal bio-signatures of individual patients and respective malignant diseases, leading to individualized treatment approach, according to the concepts of modern integrative medicine. Keywords: Carcinogenesis, Cancer, Oxidative stress, Lipid peroxidation, 4-hydroxynonenal, Glutathione, Metabolomics, Immunochemistry, Biomarkers, Omics science

  11. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    strategy influences the patterns identified as important for the nutritional question under study. Therefore, in depth understanding of the study design and the specific effects of the analytical technology on the produced data is extremely important to achieve high quality data handling. Besides data......Metabolomics provides a holistic approach to investigate the perturbations in human metabolism with respect to a specific exposure. In nutritional metabolomics, the research question is generally related to the effect of a specific food intake on metabolic profiles commonly of plasma or urine....... Application of multiple analytical strategies may provide comprehensive information to reach a valid answer to these research questions. In this thesis, I investigated several analytical technologies and data handling strategies in order to evaluate their effects on the biological answer. In metabolomics, one...

  12. Metabolomics for laboratory diagnostics.

    Science.gov (United States)

    Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

    2015-09-10

    Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. An Ultrahigh-Performance Liquid Chromatography-Time-of-Flight Mass Spectrometry Metabolomic Approach to Studying the Impact of Moderate Red-Wine Consumption on Urinary Metabolome.

    Science.gov (United States)

    Esteban-Fernández, Adelaida; Ibañez, Clara; Simó, Carolina; Bartolomé, Begoña; Moreno-Arribas, M Victoria

    2018-04-06

    Moderate red-wine consumption has been widely described to exert several benefits in human health. This is mainly due to its unique content of bioactive polyphenols, which suffer several modifications along their pass through the digestive system, including microbial transformation in the colon and phase-II metabolism, until they are finally excreted in urine and feces. To determine the impact of moderate wine consumption in the overall urinary metabolome of healthy volunteers ( n = 41), samples from a red-wine interventional study (250 mL/day, 28 days) were investigated. Urine (24 h) was collected before and after intervention and analyzed by an untargeted ultrahigh-performance liquid chromatography-time-of-flight mass spectrometry metabolomics approach. 94 compounds linked to wine consumption, including specific wine components (tartaric acid), microbial-derived phenolic metabolites (5-(dihydroxyphenyl)-γ-valerolactones and 4-hydroxyl-5-(phenyl)-valeric acids), and endogenous compounds were identified. Also, some relationships between parallel fecal and urinary metabolomes are discussed.

  14. The metabolomic approach identifies a biological signature of low-dose chronic exposure to Cesium 137

    International Nuclear Information System (INIS)

    Grison, S.; Grandcolas, L.; Martin, J.C.

    2012-01-01

    Reports have described apparent biological effects of 137 Cs (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to 137 Cs through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a liquid chromatography coupled to mass spectrometry (LC-MS) system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P=0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated 137 Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators. (author)

  15. Metabolomics diagnostic approach to mustard airway diseases: a preliminary study

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    BiBi Fatemeh Nobakht Mothlagh Ghoochani

    2018-01-01

    Full Text Available Objective(s: This study aims to evaluate combined proton nuclear magnetic resonance (1H NMR spectroscopy and gas chromatography-mass spectrometry (GC-MS metabolic profiling approaches, for discriminating between mustard airway diseases (MADs and healthy controls and for providing biochemical information on this disease. Materials and Methods: In the present study, analysis of serum samples collected from 17 MAD subjects and 12 healthy controls was performed using NMR. Of these subjects, 14 (8 patients and 6 controls were analyzed by GC-MS. Then, their spectral profiles were subjected to principal component analysis (PCA and orthogonal partial least squares regression discriminant analysis (OPLS-DA. Results: A panel of twenty eight metabolite biomarkers was generated for MADs, sixteen  NMR-derived metabolites (3-methyl-2-oxovaleric acid, 3-hydroxyisobutyrate, lactic acid, lysine, glutamic acid, proline, hydroxyproline, dimethylamine, creatine, citrulline, choline, acetic acid, acetoacetate, cholesterol, alanine, and lipid (mainly VLDL and twelve GC-MS-derived metabolites (threonine, phenylalanine, citric acid, myristic acid, pentadecanoic acid, tyrosine, arachidonic acid, lactic acid, propionic acid, 3-hydroxybutyric acid, linoleic acid, and oleic acid. This composite biomarker panel could effectively discriminate MAD subjects from healthy controls, achieving an area under receiver operating characteristic curve (AUC values of 1 and 0.79 for NMR and GC-MS, respectively. Conclusion: In the present study, a robust panel of twenty-eight biomarkers for detecting MADs was established. This panel is involved in three metabolic pathways including aminoacyl-tRNA biosynthesis, arginine, and proline metabolism, and synthesis and degradation of ketone bodies, and could differentiate MAD subjects from healthy controls with a higher accuracy.

  16. Atmo-metabolomics: a new measurement approach for investigating aerosol composition and ecosystem functioning.

    Science.gov (United States)

    Rivas-Ubach, A.; Liu, Y.; Sardans, J.; Tfaily, M. M.; Kim, Y. M.; Bourrianne, E.; Paša-Tolić, L.; Penuelas, J.; Guenther, A. B.

    2016-12-01

    Aerosols play crucial roles in the processes controlling the composition of the atmosphere and the functioning of ecosystems. Gaining a deeper understanding of the chemical composition of aerosols is one of the major challenges for atmospheric and climate scientists and is beginning to be recognized as important for ecological research. Better comprehension of aerosol chemistry can potentially provide valuable information on atmospheric processes such as oxidation of organics and the production of cloud condensation nuclei as well as provide an approximation of the general status of an ecosystem through the measurement of certain stress biomarkers. In this study, we describe an efficient aerosol sampling method, the metabolite extraction and the analytical procedures for the chemical characterization of aerosols, namely, the atmo-metabolome. We used mass spectrometry (MS) coupled to liquid chromatography (LC-MS), gas chromatography (GC-MS) and Fourier transform ion cyclotron resonance (FT-ICR-MS) to characterize the atmo-metabolome of two marked seasons; spring and summer. Our sampling and extraction methods demonstrated to be suitable for aerosol chemical characterization with any of the analytical platforms used in this study. The atmo-metabolome between spring and summer showed overall statistically differences. We identified several metabolites that can be attributed to pollen and other plant-related aerosols. Spring aerosols exhibit higher concentrations of metabolites linked to higher plant activity while summer samples had higher concentrations of metabolites that may reflect certain oxidative stresses in primary producers. Moreover, the elemental composition of aerosols showed clear different between seasons. Summer aerosols were generally higher in molecular weight and with higher O/C ratios, indicating higher oxidation levels and condensation of compounds relative to spring. Our method represents an advanced approach for characterizing the composition of

  17. Metabolomic approach to optimizing and evaluating antibiotic treatment in the axenic culture of cyanobacterium Nostoc flagelliforme.

    Science.gov (United States)

    Han, Pei-pei; Jia, Shi-ru; Sun, Ying; Tan, Zhi-lei; Zhong, Cheng; Dai, Yu-jie; Tan, Ning; Shen, Shi-gang

    2014-09-01

    The application of antibiotic treatment with assistance of metabolomic approach in axenic isolation of cyanobacterium Nostoc flagelliforme was investigated. Seven antibiotics were tested at 1-100 mg L(-1), and order of tolerance of N. flagelliforme cells was obtained as kanamycin > ampicillin, tetracycline > chloromycetin, gentamicin > spectinomycin > streptomycin. Four antibiotics were selected based on differences in antibiotic sensitivity of N. flagelliforme and associated bacteria, and their effects on N. flagelliforme cells including the changes of metabolic activity with antibiotics and the metabolic recovery after removal were assessed by a metabolomic approach based on gas chromatography-mass spectrometry combined with multivariate analysis. The results showed that antibiotic treatment had affected cell metabolism as antibiotics treated cells were metabolically distinct from control cells, but the metabolic activity would be recovered via eliminating antibiotics and the sequence of metabolic recovery time needed was spectinomycin, gentamicin > ampicillin > kanamycin. The procedures of antibiotic treatment have been accordingly optimized as a consecutive treatment starting with spectinomycin, then gentamicin, ampicillin and lastly kanamycin, and proved to be highly effective in eliminating the bacteria as examined by agar plating method and light microscope examination. Our work presented a strategy to obtain axenic culture of N. flagelliforme and provided a method for evaluating and optimizing cyanobacteria purification process through diagnosing target species cellular state.

  18. Metabolomic Studies in Drosophila.

    Science.gov (United States)

    Cox, James E; Thummel, Carl S; Tennessen, Jason M

    2017-07-01

    Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila , often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

  19. Towards Polypharmacokinetics: Pharmacokinetics of Multicomponent Drugs and Herbal Medicines Using a Metabolomics Approach

    Directory of Open Access Journals (Sweden)

    Ke Lan

    2013-01-01

    Full Text Available Determination of pharmacokinetics (PKs of multicomponent pharmaceuticals and/or nutraceuticals (polypharmacokinetics, poly-PKs is difficult due to the vast number of compounds present in natural products, their various concentrations across a wide range, complexity of their interactions, as well as their complex degradation dynamics in vivo. Metabolomics coupled with multivariate statistical tools that focus on the comprehensive analysis of small molecules in biofluids is a viable approach to address the challenges of poly-PK. This paper discusses recent advances in the characterization of poly-PK and the metabolism of multicomponent xenobiotic agents, such as compound drugs, dietary supplements, and herbal medicines, using metabolomics strategy. We propose a research framework that integrates the dynamic concentration profile of bioavailable xenobiotic molecules that result from in vivo absorption and hepatic and gut bacterial metabolism, as well as the human metabolic response profile. This framework will address the bottleneck problem in the pharmacological evaluation of multicomponent pharmaceuticals and nutraceuticals, leading to the direct elucidation of the pharmacological and molecular mechanisms of these compounds.

  20. Expanded metabolomics approach to profiling endogenous carbohydrates in the serum of ovarian cancer patients.

    Science.gov (United States)

    Cheng, Yu; Li, Li; Zhu, Bangjie; Liu, Feng; Wang, Yan; Gu, Xue; Yan, Chao

    2016-01-01

    We applied hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry to the quantitative analysis of serum from 58 women, including ovarian cancer patients, ovarian benign tumor patients, and healthy controls. All of these ovarian cancer and ovarian benign tumor patients have elevated cancer antigen 125, which makes them clinically difficult to differentiate the malignant from the benign. All of the 16 endogenous carbohydrates were quantitatively detected in the human sera, of which, eight endogenous carbohydrates were significantly different (P-value carbohydrates in the expanded metabolomics approach after the global metabolic profiling are characterized and are potential biomarkers for the early diagnosis of ovarian cancer. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Investigation of Liver Injury of Polygonum multiflorum Thunb. in Rats by Metabolomics and Traditional Approaches

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    Yun-Xia Li

    2017-11-01

    Full Text Available Liver injury induced by Polygonum multiflorum Thunb. (PM have been reported since 2006, which aroused widespread concern. However, the toxicity mechanism of PM liver injury remained unclear. In this study, the mechanism of liver injury induced by different doses of PM after long-term administration was investigated in rats by metabolomics and traditional approaches. Rats were randomly divided into control group and PM groups. PM groups were oral administered PM of low (10 g/kg, medium (20 g/kg, high (40 g/kg dose, while control group was administered distilled water. After 28 days of continuous administration, the serum biochemical indexes in the control and three PM groups were measured and the liver histopathology were analyzed. Also, UPLC-Q-TOF-MS with untargeted metabolomics was performed to identify the possible metabolites and pathway of liver injury caused by PM. Compared with the control group, the serum levels of ALT, AST, ALP, TG, and TBA in middle and high dose PM groups were significantly increased. And the serum contents of T-Bil, D-Bil, TC, TP were significantly decreased. However, there was no significant difference between the low dose group of PM and the control group except serum AST, TG, T-Bil, and D-Bil. Nine biomarkers were identified based on biomarkers analysis. And the pathway analysis indicated that fat metabolism, amino acid metabolism and bile acid metabolism were involved in PM liver injury. Based on the biomarker pathway analysis, PM changed the lipid metabolism, amino acid metabolism and bile acid metabolism and excretion in a dose-dependent manner which was related to the mechanism of liver injury.

  2. Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies.

    Science.gov (United States)

    Zaitsu, Kei; Hayashi, Yumi; Kusano, Maiko; Tsuchihashi, Hitoshi; Ishii, Akira

    2016-02-01

    Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

  3. Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

    Science.gov (United States)

    Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

    2015-02-01

    Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides

  4. Metabolomics approaches for discovering biomarkers of drug-induced hepatotoxicity and nephrotoxicity

    International Nuclear Information System (INIS)

    Beger, Richard D.; Sun, Jinchun; Schnackenberg, Laura K.

    2010-01-01

    Hepatotoxicity and nephrotoxicity are two major reasons that drugs are withdrawn post-market, and hence it is of major concern to both the FDA and pharmaceutical companies. The number of cases of serious adverse effects (SAEs) in marketed drugs has climbed faster than the number of total drug prescriptions issued. In some cases, preclinical animal studies fail to identify the potential toxicity of a new chemical entity (NCE) under development. The current clinical chemistry biomarkers of liver and kidney injury are inadequate in terms of sensitivity and/or specificity, prompting the need to discover new translational specific biomarkers of organ injury. Metabolomics along with genomics and proteomics technologies have the capability of providing translational diagnostic and prognostic biomarkers specific for early stages of liver and kidney injury. Metabolomics has several advantages over the other omics platforms such as ease of sample preparation, data acquisition and use of biofluids collected through minimally invasive procedures in preclinical and clinical studies. The metabolomics platform is reviewed with particular emphasis on applications involving drug-induced hepatotoxicity and nephrotoxicity. Analytical platforms for metabolomics, chemometrics for mining metabolomics data and the applications of the metabolomics technologies are covered in detail with emphasis on recent work in the field.

  5. A dried blood spot mass spectrometry metabolomic approach for rapid breast cancer detection

    Directory of Open Access Journals (Sweden)

    Wang Q

    2016-03-01

    of 84.4%. Compared to the routinely used protein markers, this model exhibited distinct advantage with its higher sensitivity.Conclusion: Blood metabolites screening is a more plausible approach for BC detection. Furthermore, this direct MS analysis could be finished within few minutes, which means that its throughput is higher than the currently used imaging techniques. Keywords: breast cancer, metabolomics, dried blood spot testing

  6. A GC/MS-based metabolomic approach for reliable diagnosis of phenylketonuria.

    Science.gov (United States)

    Xiong, Xiyue; Sheng, Xiaoqi; Liu, Dan; Zeng, Ting; Peng, Ying; Wang, Yichao

    2015-11-01

    Although the phenylalanine/tyrosine ratio in blood has been the gold standard for diagnosis of phenylketonuria (PKU), the disadvantages of invasive sample collection and false positive error limited the application of this discriminator in the diagnosis of PKU to some extent. The aim of this study was to develop a new standard with high sensitivity and specificity in a less invasive manner for diagnosing PKU. In this study, an improved oximation-silylation method together with GC/MS was utilized to obtain the urinary metabolomic information in 47 PKU patients compared with 47 non-PKU controls. Compared with conventional oximation-silylation methods, the present approach possesses the advantages of shorter reaction time and higher reaction efficiency at a considerably lower temperature, which is beneficial to the derivatization of some thermally unstable compounds, such as phenylpyruvic acid. Ninety-seven peaks in the chromatograms were identified as endogenous metabolites by the National Institute of Standards and Technology (NIST) mass spectra library, including amino acids, organic acids, carbohydrates, amides, and fatty acids. After normalization of data using creatinine as internal standard, 19 differentially expressed compounds with p values of <0.05 were selected by independent-sample t test for the separation of the PKU group and the control group. A principal component analysis (PCA) model constructed by these differentially expressed compounds showed that the PKU group can be discriminated from the control group. Receiver-operating characteristic (ROC) analysis with area under the curve (AUC), specificity, and sensitivity of each PKU marker obtained from these differentially expressed compounds was used to evaluate the possibility of using these markers for diagnosing PKU. The largest value of AUC (0.987) with high specificity (0.936) and sensitivity (1.000) was obtained by the ROC curve of phenylacetic acid at its cutoff value (17.244 mmol/mol creatinine

  7. A comparative UPLC-Q/TOF-MS-based metabolomics approach for distinguishing Zingiber officinale Roscoe of two geographical origins.

    Science.gov (United States)

    Mais, Enos; Alolga, Raphael N; Wang, Shi-Lei; Linus, Loveth O; Yin, Xiaojin; Qi, Lian-Wen

    2018-02-01

    Ginger, the rhizome of Zingiber officinale Roscoe, is a popular spice used in the food, beverage and confectionary industries. In this study, we report an untargeted UPLC-Q/TOF-MS-based metabolomics approach for comprehensively discriminating between ginger from two geographical locations, Ghana in West Africa and China. Forty batches of fresh ginger from both countries were discriminated using principal component analysis and orthogonal partial least squares discrimination analysis. Sixteen differential metabolites were identified between the gingers from the two geographical locations, six of which were identified as the marker compounds responsible for the discrimination. Our study highlights the essence and predictive power of metabolomics in detecting minute differences in same varieties of plants/plant samples based on the levels and composition of their metabolites. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics

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    Ivana Blaženović

    2018-05-01

    Full Text Available The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies include the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included.

  9. Metabolomics approach for analyzing the effects of exercise in subjects with type 1 diabetes mellitus.

    Directory of Open Access Journals (Sweden)

    Laura Brugnara

    Full Text Available The beneficial effects of exercise in patients with type 1 diabetes (T1D are not fully proven, given that it may occasionally induce acute metabolic disturbances. Indeed, the metabolic disturbances associated with sustained exercise may lead to worsening control unless great care is taken to adjust carbohydrate intake and insulin dosage. In this work, pre- and post-exercise metabolites were analyzed using a (1H-NMR and GC-MS untargeted metabolomics approach assayed in serum. We studied ten men with T1D and eleven controls matched for age, body mass index, body fat composition, and cardiorespiratory capacity, participated in the study. The participants performed 30 minutes of exercise on a cycle-ergometer at 80% VO(2max. In response to exercise, both groups had increased concentrations of gluconeogenic precursors (alanine and lactate and tricarboxylic acid cycle intermediates (citrate, malate, fumarate and succinate. The T1D group, however, showed attenuation in the response of these metabolites to exercise. Conversely to T1D, the control group also presented increases in α-ketoglutarate, alpha-ketoisocaproic acid, and lipolysis products (glycerol and oleic and linoleic acids, as well as a reduction in branched chain amino acids (valine and leucine determinations. The T1D patients presented a blunted metabolic response to acute exercise as compared to controls. This attenuated response may interfere in the healthy performance or fitness of T1D patients, something that further studies should elucidate.

  10. Evaluation of 2,4-dichlorophenol exposure of Japanese medaka, Oryzias latipes, using a metabolomics approach.

    Science.gov (United States)

    Kokushi, Emiko; Shintoyo, Aoi; Koyama, Jiro; Uno, Seiichi

    2017-12-01

    In this study, the metabolic effects of waterborne exposure of medaka (Oryzias latipes) to nominal concentrations of 20 (L group) and 2000 μg/L (H group) 2,4-dichlorophenol (DCP) were examined using a gas chromatography/mass spectroscopy (GC/MS) metabolomics approach. A principal component analysis (PCA) separated the L, H, and control groups along PC1 to explain the toxic effects of DCP at 24 h of exposure. Furthermore, the L and H groups were separated along PC1 at 96 h on the PCA score plots. These results suggest that the effects of DCP depended on exposure concentration and time. Changes in tricarboxylic cycle metabolites suggested that fish exposed to 2,4-DCP require more energy to metabolize and eliminate DCP, particularly at 96 h of exposure. A time-dependent response in the fish exposed to DCP was observed in the GC/MS data, suggesting that the higher DCP concentration had greater effects at 24 h than those observed in response to the lower concentration. In addition, several essential amino acids (arginine, histidine, lysine, isoleucine, leucine, methionine, phenylalanine, threonine, tryptophan, and valine) decreased after DCP exposure in the H group, and starvation condition and high concentration exposure of DCP could consume excess energy from amino acids.

  11. Comparative Metabolomics Approach Detects Stress-Specific Responses during Coral Bleaching in Soft Corals.

    Science.gov (United States)

    Farag, Mohamed A; Meyer, Achim; Ali, Sara E; Salem, Mohamed A; Giavalisco, Patrick; Westphal, Hildegard; Wessjohann, Ludger A

    2018-06-01

    Chronic exposure to ocean acidification and elevated sea-surface temperatures pose significant stress to marine ecosystems. This in turn necessitates costly acclimation responses in corals in both the symbiont and host, with a reorganization of cell metabolism and structure. A large-scale untargeted metabolomics approach comprising gas chromatography mass spectrometry (GC-MS) and ultraperformance liquid chromatography coupled to high resolution mass spectrometry (UPLC-MS) was applied to profile the metabolite composition of the soft coral Sarcophyton ehrenbergi and its dinoflagellate symbiont. Metabolite profiling compared ambient conditions with response to simulated climate change stressors and with the sister species, S. glaucum. Among ∼300 monitored metabolites, 13 metabolites were modulated. Incubation experiments providing four selected upregulated metabolites (alanine, GABA, nicotinic acid, and proline) in the culturing water failed to subside the bleaching response at temperature-induced stress, despite their known ability to mitigate heat stress in plants or animals. Thus, the results hint to metabolite accumulation (marker) during heat stress. This study provides the first detailed map of metabolic pathways transition in corals in response to different environmental stresses, accounting for the superior thermal tolerance of S. ehrenbergi versus S. glaucum, which can ultimately help maintain a viable symbiosis and mitigate against coral bleaching.

  12. Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

    Science.gov (United States)

    Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

    2016-01-05

    The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups

  13. Metabolomics in chemical ecology.

    Science.gov (United States)

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  14. Untargeted Metabolomics Approach in Halophiles: Understanding the Biodeterioration Process of Building Materials

    Directory of Open Access Journals (Sweden)

    Justyna Adamiak

    2017-12-01

    Full Text Available The aim of the study was to explore the halophile metabolome in building materials using untargeted metabolomics which allows for broad metabolome coverage. For this reason, we used high-performance liquid chromatography interfaced to high-resolution mass spectrometry (HPLC/HRMS. As an alternative to standard microscopy techniques, we introduced pioneering Coherent Anti-stokes Raman Scattering Microscopy (CARS to non-invasively visualize microbial cells. Brick samples saturated with salt solution (KCl, NaCl (two salinity levels, MgSO4, Mg(NO32, were inoculated with the mixture of preselected halophilic microorganisms, i.e., bacteria: Halobacillus styriensis, Halobacillus naozhouensis, Halobacillus hunanensis, Staphylococcus succinus, Marinococcus halophilus, Virgibacillus halodenitryficans, and yeast: Sterigmatomyces halophilus and stored at 28°C and 80% relative humidity for a year. Metabolites were extracted directly from the brick samples and measured via HPLC/HRMS in both positive and negative ion modes. Overall, untargeted metabolomics allowed for discovering the interactions of halophilic microorganisms with buildings materials which together with CARS microscopy enabled us to elucidate the biodeterioration process caused by halophiles. We observed that halophile metabolome was differently affected by different salt solutions. Furthermore, we found indications for haloadaptive strategies and degradation of brick samples due to microbial pigment production as a salt stress response. Finally, we detected changes in lipid content related to changes in the structure of phospholipid bilayers and membrane fluidity.

  15. Metabolomics approach reveals metabolic disorders and potential biomarkers associated with the developmental toxicity of tetrabromobisphenol A and tetrachlorobisphenol A

    Science.gov (United States)

    Ye, Guozhu; Chen, Yajie; Wang, Hong-Ou; Ye, Ting; Lin, Yi; Huang, Qiansheng; Chi, Yulang; Dong, Sijun

    2016-10-01

    Tetrabromobisphenol A and tetrachlorobisphenol A are halogenated bisphenol A (H-BPA), and has raised concerns about their adverse effects on the development of fetuses and infants, however, the molecular mechanisms are unclear, and related metabolomics studies are limited. Accordingly, a metabolomics study based on gas chromatography-mass spectrometry was employed to elucidate the molecular developmental toxicology of H-BPA using the marine medaka (Oryzias melastigmas) embryo model. Here, we revealed decreased synthesis of nucleosides, amino acids and lipids, and disruptions in the TCA (tricarboxylic acid) cycle, glycolysis and lipid metabolism, thus inhibiting the developmental processes of embryos exposed to H-BPA. Unexpectedly, we observed enhanced neural activity accompanied by lactate accumulation and accelerated heart rates due to an increase in dopamine pathway and a decrease in inhibitory neurotransmitters following H-BPA exposure. Notably, disorders of the neural system, and disruptions in glycolysis, the TCA cycle, nucleoside metabolism, lipid metabolism, glutamate and aspartate metabolism induced by H-BPA exposure were heritable. Furthermore, lactate and dopa were identified as potential biomarkers of the developmental toxicity of H-BPA and related genetic effects. This study has demonstrated that the metabolomics approach is a useful tool for obtaining comprehensive and novel insights into the molecular developmental toxicity of environmental pollutants.

  16. Multi-platform metabolomics and a genetic approach support the authentication of agarwood produced by Aquilaria crassna and Aquilaria malaccensis.

    Science.gov (United States)

    Nguyen, Huy Truong; Min, Jung-Eun; Long, Nguyen Phuoc; Thanh, Ma Chi; Le, Thi Hong Van; Lee, Jeongmi; Park, Jeong Hill; Kwon, Sung Won

    2017-08-05

    Agarwood, the resinous heartwood produced by some Aquilaria species such as Aquilaria crassna, Aquilaria malaccensis and Aquilaria sinensis, has been traditionally and widely used in medicine, incenses and especially perfumes. However, up to now, the authentication of agarwood has been largely based on morphological characteristics, a method which is prone to errors and lacks reproducibility. Hence, in this study, we applied metabolomics and a genetic approach to the authentication of two common agarwood chips, those produced by Aquilaria crassna and Aquilaria malaccensis. Primary metabolites, secondary metabolites and DNA markers of agarwood were authenticated by 1 H NMR metabolomics, GC-MS metabolomics and DNA-based techniques, respectively. The results indicated that agarwood chips could be classified accurately by all the methods illustrated in this study. Additionally, the pros and cons of each method are also discussed. To the best of our knowledge, our research is the first study detailing all the differences in the primary and secondary metabolites, as well as the DNA markers between the agarwood produced by these two species. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Characterizing Dissolved Organic Matter and Metabolites in an Actively Serpentinizing Ophiolite Using Global Metabolomics Techniques

    Science.gov (United States)

    Seyler, L. M.; Rempfert, K. R.; Kraus, E. A.; Spear, J. R.; Templeton, A. S.; Schrenk, M. O.

    2017-12-01

    Environmental metabolomics is an emerging approach used to study ecosystem properties. Through bioinformatic comparisons to metagenomic data sets, metabolomics can be used to study microbial adaptations and responses to varying environmental conditions. Since the techniques are highly parallel to organic geochemistry approaches, metabolomics can also provide insight into biogeochemical processes. These analyses are a reflection of metabolic potential and intersection with other organisms and environmental components. Here, we used an untargeted metabolomics approach to characterize dissolved organic carbon and aqueous metabolites from groundwater obtained from an actively serpentinizing habitat. Serpentinites are known to support microbial communities that feed off of the products of serpentinization (such as methane and H2 gas), while adapted to harsh environmental conditions such as high pH and low DIC availability. However, the biochemistry of microbial populations that inhabit these environments are understudied and are complicated by overlapping biotic and abiotic processes. The aim of this study was to identify potential sources of carbon in an environment that is depleted of soluble inorganic carbon, and to characterize the flow of metabolites and describe overlapping biogenic and abiogenic processes impacting carbon cycling in serpentinizing rocks. We applied untargeted metabolomics techniques to groundwater taken from a series of wells drilled into the Semail Ophiolite in Oman.. Samples were analyzed via quadrupole time-of-flight liquid chromatography tandem mass spectrometry (QToF-LC/MS/MS). Metabolomes and metagenomic data were imported into Progenesis QI software for statistical analysis and correlation, and metabolic networks constructed using the Genome-Linked Application for Metabolic Maps (GLAMM), a web interface tool. Further multivariate statistical analyses and quality control was performed using EZinfo. Pools of dissolved organic carbon could

  18. Identification of Potential Biomarkers from Aconitum carmichaelii, a Traditional Chinese Medicine, Using a Metabolomic Approach.

    Science.gov (United States)

    Zhao, Dake; Shi, Yana; Zhu, Xinyan; Liu, Li; Ji, Pengzhang; Long, Chunlin; Shen, Yong; Kennelly, Edward J

    2018-04-01

    Despite their well-known toxicity, Aconitum species are important traditional medicines worldwide. Aconitum carmichaelii , known in Chinese as (fuzi), is an officially recognized traditional Chinese medicine with characteristic analgesic and anti-inflammatory activities, whose principal pharmacological ingredients are considered as aconitine-type diterpene alkaloids. Notwithstanding the long-recorded use of A. carmichaelii in traditional Chinese medicine, no single-entity aconitum alkaloid drug has been developed for clinical use. UPLC-Q-TOF-MS was used to investigate the marker compounds that can be used to differentiate A. carmichaelii from seven other Aconitum species collected in Yunnan Province. Nontargeted principle component analysis scores plots found that all the tested Aconitum species clustered into three distinct groups, and A. carmichaelii was significantly different chemically than the other seven species. Furthermore, the primary and lateral roots of A. carmichaelii also showed significant differences. Using orthogonal partial least squares discriminate analysis analysis, eight marker compounds were identified, including 14-acetylkarakoline, aconitine, carmichaeline, fuziline, hypaconitine, mesaconitine, neoline, and talatisamine. Four of these aconitum alkaloids, fuziline, hypaconitine, mesaconitine, and neoline, showed significant analgesic activity in a dose-dependent manner compared to the negative and positive controls. However, hypaconitine, mesaconitine, and neoline exhibited significant acute toxicity activity, while fuziline showed no acute toxicity in mice, suggesting the relative safety of this alkaloid. This study provides a good example of how to differentiate an authentic medicinal plant from common adulterants using a metabolomics approach, and to identify compounds that may be developed into new drugs. Georg Thieme Verlag KG Stuttgart · New York.

  19. 1H NMR- based metabolomics approaches as non- invasive tools for diagnosis of endometriosis

    Directory of Open Access Journals (Sweden)

    Negar Ghazi

    2016-01-01

    Full Text Available Background: So far, non-invasive diagnostic approaches such as ultrasound, magnetic resonance imaging, or blood tests do not have sufficient diagnostic power for endometriosis disease. Lack of a non-invasive diagnostic test contributes to the long delay between onset of symptoms and diagnosis of endometriosis. Objective: The present study focuses on the identification of predictive biomarkers in serum by pattern recognition techniques and uses partial least square discriminant analysis, multi-layer feed forward artificial neural networks (ANNs and quadratic discriminant analysis (QDA modeling tools for the early diagnosis of endometriosis in a minimally invasive manner by 1H- NMR based metabolomics. Materials and Methods: This prospective cohort study was done in Pasteur Institute, Iran in June 2013. Serum samples of 31 infertile women with endometriosis (stage II and III who confirmed by diagnostic laparoscopy and 15 normal women were collected and analyzed by nuclear magnetic resonance spectroscopy. The model was built by using partial least square discriminant analysis, QDA, and ANNs to determine classifier metabolites for early prediction risk of disease. Results: The levels of 2- methoxyestron, 2-methoxy estradiol, dehydroepiandrostion androstendione, aldosterone, and deoxy corticosterone were enhanced significantly in infertile group. While cholesterol and primary bile acids levels were decreased. QDA model showed significant difference between two study groups. Positive and negative predict value levels obtained about 71% and 78%, respectively. ANNs provided also criteria for detection of endometriosis. Conclusion: The QDA and ANNs modeling can be used as computational tools in noninvasive diagnose of endometriosis. However, the model designed by QDA methods is more efficient compared to ANNs in diagnosis of endometriosis patients.

  20. NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

    International Nuclear Information System (INIS)

    Li, Minghui; Wang, Junsong; Lu, Zhaoguang; Wei, Dandan; Yang, Minghua; Kong, Lingyi

    2014-01-01

    Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a 1 H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment

  1. NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

    Energy Technology Data Exchange (ETDEWEB)

    Li, Minghui [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Wang, Junsong, E-mail: wang.junsong@gmail.com [Center for Molecular Metabolism, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 200 Xiao Ling Wei Street, Nanjing 210094 (China); Lu, Zhaoguang; Wei, Dandan; Yang, Minghua [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Kong, Lingyi, E-mail: cpu_lykong@126.com [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China)

    2014-01-15

    Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a {sup 1}H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment.

  2. Metabolomic approach: postharvest storage stability of red radish (raphanus sativus l.)

    International Nuclear Information System (INIS)

    Jahangir, M.; Farid, J.B.A.

    2014-01-01

    Post harvest storage of vegetables at different temperature for consumption is commonly practiced that need standardization. Among vegetables, red radish (Raphanus sativus L.) is a well known and commonly consumed vegetable all over the world. Its bioactive or nutritional constituents include a wide range of metabolites including, glucosinolates, phenolics, amino acids, organic acids, and sugars. However, many of these metabolites are not stable and can easily be degraded or modified during storage. In order to investigate the metabolomic changes during post harvest storage, radish samples (intact roots and aerial parts) were subjected to four different storage temperatures above and below 0 degree C (20 degree C, 4 degree C, -20 degree C, and -80 degree C), for a maximum of 28 days. 1H-NMR and two-dimensional NMR spectra data resulting from the analysis of the different samples were subjected to principal component analysis (PCA) to investigate any possible metabolomic changes. A profound chemical alteration was observed in primary and secondary metabolites. Glucosinolates, phenylpropanoids, organic acids, amino acids, and sugars were found to be the discriminating metabolites for the storage effect. Initially, an increase in secondary metabolites (phenolics and glucosinolates) was observed, but levels of these compounds decreased in later stages, probably due to the breakdown of these products. Whereas late storage samples contained high amounts of amino acids (alanine, valine, threonine, (gama-amino-butyric acid / GABA)) and some glucosinolates (glucobrassicin, neoglucobrassicin). This phenomenon was pronounced at room temperature as compared to other storage temperatures. Interestingly even at lower and freezing temperatures metabolomic changes in these biological samples were observed. The least metabolomic changes were observed at samples stored at -80 degree C. While studying temperature dependent metabolomic changes, high levels of glucose, adenine, alanine

  3. First-Trimester Serum Acylcarnitine Levels to Predict Preeclampsia: A Metabolomics Approach

    Directory of Open Access Journals (Sweden)

    Maria P. H. Koster

    2015-01-01

    Full Text Available Objective. To expand the search for preeclampsia (PE metabolomics biomarkers through the analysis of acylcarnitines in first-trimester maternal serum. Methods. This was a nested case-control study using serum from pregnant women, drawn between 8 and 14 weeks of gestational age. Metabolites were measured using an UPLC-MS/MS based method. Concentrations were compared between controls (n=500 and early-onset- (EO- PE (n=68 or late-onset- (LO- PE (n=99 women. Metabolites with a false discovery rate <10% for both EO-PE and LO-PE were selected and added to prediction models based on maternal characteristics (MC, mean arterial pressure (MAP, and previously established biomarkers (PAPPA, PLGF, and taurine. Results. Twelve metabolites were significantly different between EO-PE women and controls, with effect levels between −18% and 29%. For LO-PE, 11 metabolites were significantly different with effect sizes between −8% and 24%. Nine metabolites were significantly different for both comparisons. The best prediction model for EO-PE consisted of MC, MAP, PAPPA, PLGF, taurine, and stearoylcarnitine (AUC = 0.784. The best prediction model for LO-PE consisted of MC, MAP, PAPPA, PLGF, and stearoylcarnitine (AUC = 0.700. Conclusion. This study identified stearoylcarnitine as a novel metabolomics biomarker for EO-PE and LO-PE. Nevertheless, metabolomics-based assays for predicting PE are not yet suitable for clinical implementation.

  4. Quantifying the Metabolome of Pseudomonas taiwanensis VLB120: Evaluation of Hot and Cold Combined Quenching/Extraction Approaches

    DEFF Research Database (Denmark)

    Wordofa, Gossa Garedew; Kristensen, Mette; Schrübbers, Lars

    2017-01-01

    Absolute quantification of free intracellular metabolites is a valuable tool in both pathway discovery and metabolic engineering. In this study, we conducted a comprehensive examination of different hot and cold combined quenching/extraction approaches to extract and quantify intracellular...... (such as cold methanol/acetonitrile/water, hot water, and boiling ethanol/water, as well as cold ethanol/water) were tested and evaluated for P. taiwanensis VLB120 metabolome analysis. In total 94 out of 107 detected intracellular metabolites were quantified using an isotope-ratio-based approach....... The quantified metabolites include amino acids, nucleotides, central carbon metabolism intermediates, redox cofactors, and others. The acquired data demonstrate that the pressure driven fast filtration approach followed by boiling ethanol quenching/extraction is the most adequate technique for P. taiwanensis VLB...

  5. Vitroprocines, new antibiotics against Acinetobacter baumannii, discovered from marine Vibrio sp. QWI-06 using mass-spectrometry-based metabolomics approach

    Science.gov (United States)

    Liaw, Chih-Chuang; Chen, Pei-Chin; Shih, Chao-Jen; Tseng, Sung-Pin; Lai, Ying-Mi; Hsu, Chi-Hsin; Dorrestein, Pieter C.; Yang, Yu-Liang

    2015-08-01

    A robust and convenient research strategy integrating state-of-the-art analytical techniques is needed to efficiently discover novel compounds from marine microbial resources. In this study, we identified a series of amino-polyketide derivatives, vitroprocines A-J, from the marine bacterium Vibrio sp. QWI-06 by an integrated approach using imaging mass spectroscopy and molecular networking, as well as conventional bioactivity-guided fractionation and isolation. The structure-activity relationship of vitroprocines against Acinetobacter baumannii is proposed. In addition, feeding experiments with 13C-labeled precursors indicated that a pyridoxal 5‧-phosphate-dependent mechanism is involved in the biosynthesis of vitroprocines. Elucidation of amino-polyketide derivatives from a species of marine bacteria for the first time demonstrates the potential of this integrated metabolomics approach to uncover marine bacterial biodiversity.

  6. Gut metabolome meets microbiome

    DEFF Research Database (Denmark)

    Lamichhane, Santosh; Sen, Partho; Dickens, Alex M

    2018-01-01

    It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We...... highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding...

  7. Towards Improving Point-of-Care Diagnosis of Non-malaria Febrile Illness: A Metabolomics Approach.

    Directory of Open Access Journals (Sweden)

    Saskia Decuypere

    2016-03-01

    Full Text Available Non-malaria febrile illnesses such as bacterial bloodstream infections (BSI are a leading cause of disease and mortality in the tropics. However, there are no reliable, simple diagnostic tests for identifying BSI or other severe non-malaria febrile illnesses. We hypothesized that different infectious agents responsible for severe febrile illness would impact on the host metabolome in different ways, and investigated the potential of plasma metabolites for diagnosis of non-malaria febrile illness.We conducted a comprehensive mass-spectrometry based metabolomics analysis of the plasma of 61 children with severe febrile illness from a malaria-endemic rural African setting. Metabolite features characteristic for non-malaria febrile illness, BSI, severe anemia and poor clinical outcome were identified by receiver operating curve analysis.The plasma metabolome profile of malaria and non-malaria patients revealed fundamental differences in host response, including a differential activation of the hypothalamic-pituitary-adrenal axis. A simple corticosteroid signature was a good classifier of severe malaria and non-malaria febrile patients (AUC 0.82, 95% CI: 0.70-0.93. Patients with BSI were characterized by upregulated plasma bile metabolites; a signature of two bile metabolites was estimated to have a sensitivity of 98.1% (95% CI: 80.2-100 and a specificity of 82.9% (95% CI: 54.7-99.9 to detect BSI in children younger than 5 years. This BSI signature demonstrates that host metabolites can have a superior diagnostic sensitivity compared to pathogen-detecting tests to identify infections characterized by low pathogen load such as BSI.This study demonstrates the potential use of plasma metabolites to identify causality in children with severe febrile illness in malaria-endemic settings.

  8. A metabolomic approach to the study of wine micro-oxygenation.

    Directory of Open Access Journals (Sweden)

    Panagiotis Arapitsas

    Full Text Available Wine micro-oxygenation is a globally used treatment and its effects were studied here by analysing by untargeted LC-MS the wine metabolomic fingerprint. Eight different procedural variations, marked by the addition of oxygen (four levels and iron (two levels were applied to Sangiovese wine, before and after malolactic fermentation. Data analysis using supervised and unsupervised multivariate methods highlighted some known candidate biomarkers, together with a number of metabolites which had never previously been considered as possible biomarkers for wine micro-oxygenation. Various pigments and tannins were identified among the known candidate biomarkers. Additional new information was obtained suggesting a correlation between oxygen doses and metal contents and changes in the concentration of primary metabolites such as arginine, proline, tryptophan and raffinose, and secondary metabolites such as succinic acid and xanthine. Based on these findings, new hypotheses regarding the formation and reactivity of wine pigment during micro-oxygenation have been proposed. This experiment highlights the feasibility of using unbiased, untargeted metabolomic fingerprinting to improve our understanding of wine chemistry.

  9. A Metabolomic Approach to the Study of Wine Micro-Oxygenation

    Science.gov (United States)

    Arapitsas, Panagiotis; Scholz, Matthias; Vrhovsek, Urska; Di Blasi, Stefano; Biondi Bartolini, Alessandra; Masuero, Domenico; Perenzoni, Daniele; Rigo, Adelio; Mattivi, Fulvio

    2012-01-01

    Wine micro-oxygenation is a globally used treatment and its effects were studied here by analysing by untargeted LC-MS the wine metabolomic fingerprint. Eight different procedural variations, marked by the addition of oxygen (four levels) and iron (two levels) were applied to Sangiovese wine, before and after malolactic fermentation. Data analysis using supervised and unsupervised multivariate methods highlighted some known candidate biomarkers, together with a number of metabolites which had never previously been considered as possible biomarkers for wine micro-oxygenation. Various pigments and tannins were identified among the known candidate biomarkers. Additional new information was obtained suggesting a correlation between oxygen doses and metal contents and changes in the concentration of primary metabolites such as arginine, proline, tryptophan and raffinose, and secondary metabolites such as succinic acid and xanthine. Based on these findings, new hypotheses regarding the formation and reactivity of wine pigment during micro-oxygenation have been proposed. This experiment highlights the feasibility of using unbiased, untargeted metabolomic fingerprinting to improve our understanding of wine chemistry. PMID:22662221

  10. Are ant feces nutrients for plants? A metabolomics approach to elucidate the nutritional effects on plants hosting weaver ants

    DEFF Research Database (Denmark)

    Vidkjær, Nanna Hjort; Wollenweber, Bernd; Gislum, René

    2015-01-01

    Weaver ants (genus Oecophylla) are tropical carnivorous ant species living in high numbers in the canopies of trees. The ants excrete copious amounts of fecal matter on leaf surfaces, and these feces may provide nutrients to host trees. This hypothesis is supported by studies of ant......-plant interactions involving other ant species that have demonstrated the transfer of nutrients from ants to plants. In this 7-months study, a GC–MS-based metabolomics approach along with an analysis of total nitrogen and carbon levels was used to study metabolic changes in ant-hosting Coffea arabica plants compared...... with control plants. The results showed elevated levels of total nitrogen, amino acids, fatty acids, caffeine, and secondary metabolites of the phenylpropanoid pathway in leaves from ant-hosting plants. Minor effects were observed for sugars, whereas little or no effect was observed for organic acids, despite...

  11. Clinical Metabolomics and Glaucoma.

    Science.gov (United States)

    Barbosa-Breda, João; Himmelreich, Uwe; Ghesquière, Bart; Rocha-Sousa, Amândio; Stalmans, Ingeborg

    2018-01-01

    Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or detect patients with a high risk of progression. Metabolomics is the study of all metabolites in an organism, and it has the potential to provide a biomarker. This review summarizes the findings of metabolomics in glaucoma patients and explains why this field is promising for new research. We identified published studies that focused on metabolomics and ophthalmology. After providing an overview of metabolomics in ophthalmology, we focused on human glaucoma studies. Five studies have been conducted in glaucoma patients and all compared patients to healthy controls. Using mass spectrometry, significant differences were found in blood plasma in the metabolic pathways that involve palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors. For nuclear magnetic resonance spectroscopy, a high glutamine-glutamate/creatine ratio was found in the vitreous and lateral geniculate body; no differences were detected in the optic radiations, and a lower N-acetylaspartate/choline ratio was observed in the geniculocalcarine and striate areas. Metabolomics can move glaucoma care towards a personalized approach and provide new knowledge concerning the pathophysiology of glaucoma, which can lead to new therapeutic options. © 2017 S. Karger AG, Basel.

  12. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

    Full Text Available Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  13. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

  14. Improving peak detection in high-resolution LC/MS metabolomics data using preexisting knowledge and machine learning approach.

    Science.gov (United States)

    Yu, Tianwei; Jones, Dean P

    2014-10-15

    Peak detection is a key step in the preprocessing of untargeted metabolomics data generated from high-resolution liquid chromatography-mass spectrometry (LC/MS). The common practice is to use filters with predetermined parameters to select peaks in the LC/MS profile. This rigid approach can cause suboptimal performance when the choice of peak model and parameters do not suit the data characteristics. Here we present a method that learns directly from various data features of the extracted ion chromatograms (EICs) to differentiate between true peak regions from noise regions in the LC/MS profile. It utilizes the knowledge of known metabolites, as well as robust machine learning approaches. Unlike currently available methods, this new approach does not assume a parametric peak shape model and allows maximum flexibility. We demonstrate the superiority of the new approach using real data. Because matching to known metabolites entails uncertainties and cannot be considered a gold standard, we also developed a probabilistic receiver-operating characteristic (pROC) approach that can incorporate uncertainties. The new peak detection approach is implemented as part of the apLCMS package available at http://web1.sph.emory.edu/apLCMS/ CONTACT: tyu8@emory.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. A novel serum metabolomics-based diagnostic approach for colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Shin Nishiumi

    Full Text Available To improve the quality of life of colorectal cancer patients, it is important to establish new screening methods for early diagnosis of colorectal cancer.We performed serum metabolome analysis using gas-chromatography/mass-spectrometry (GC/MS. First, the accuracy of our GC/MS-based serum metabolomic analytical method was evaluated by calculating the RSD% values of serum levels of various metabolites. Second, the intra-day (morning, daytime, and night and inter-day (among 3 days variances of serum metabolite levels were examined. Then, serum metabolite levels were compared between colorectal cancer patients (N = 60; N = 12 for each stage from 0 to 4 and age- and sex-matched healthy volunteers (N = 60 as a training set. The metabolites whose levels displayed significant changes were subjected to multiple logistic regression analysis using the stepwise variable selection method, and a colorectal cancer prediction model was established. The prediction model was composed of 2-hydroxybutyrate, aspartic acid, kynurenine, and cystamine, and its AUC, sensitivity, specificity, and accuracy were 0.9097, 85.0%, 85.0%, and 85.0%, respectively, according to the training set data. In contrast, the sensitivity, specificity, and accuracy of CEA were 35.0%, 96.7%, and 65.8%, respectively, and those of CA19-9 were 16.7%, 100%, and 58.3%, respectively. The validity of the prediction model was confirmed using colorectal cancer patients (N = 59 and healthy volunteers (N = 63 as a validation set. At the validation set, the sensitivity, specificity, and accuracy of the prediction model were 83.1%, 81.0%, and 82.0%, respectively, and these values were almost the same as those obtained with the training set. In addition, the model displayed high sensitivity for detecting stage 0-2 colorectal cancer (82.8%.Our prediction model established via GC/MS-based serum metabolomic analysis is valuable for early detection of colorectal cancer and has the

  16. Livestock metabolomics and the livestock metabolome: A systematic review.

    Science.gov (United States)

    Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

  17. Livestock metabolomics and the livestock metabolome: A systematic review

    Science.gov (United States)

    Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

    2017-01-01

    Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

  18. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach.

    Science.gov (United States)

    Floegel, Anna; Stefan, Norbert; Yu, Zhonghao; Mühlenbruch, Kristin; Drogan, Dagmar; Joost, Hans-Georg; Fritsche, Andreas; Häring, Hans-Ulrich; Hrabě de Angelis, Martin; Peters, Annette; Roden, Michael; Prehn, Cornelia; Wang-Sattler, Rui; Illig, Thomas; Schulze, Matthias B; Adamski, Jerzy; Boeing, Heiner; Pischon, Tobias

    2013-02-01

    Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21-0.44], factor 2 3.82 [2.64-5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.

  19. Development of Urinary Biomarkers for Internal Exposure by Cesium-137 Using a Metabolomics Approach in Mice

    Science.gov (United States)

    Goudarzi, Maryam; Weber, Waylon; Mak, Tytus D.; Chung, Juijung; Doyle-Eisele, Melanie; Melo, Dunstana; Brenner, David J.; Guilmette, Raymond A.; Fornace, Albert J.

    2014-01-01

    Cesium-137 is a fission product of uranium and plutonium in nuclear reactors and is released in large quantities during nuclear explosions or detonation of an improvised device containing this isotope. This environmentally persistent radionuclide undergoes radioactive decay with the emission of beta particles as well as gamma radiation. Exposure to 137Cs at high doses can cause acute radiation sickness and increase risk for cancer and death. The serious health risks associated with 137Cs exposure makes it critical to understand how it affects human metabolism and whether minimally invasive and easily accessible samples such as urine and serum can be used to triage patients in case of a nuclear disaster or a radiologic event. In this study, we have focused on establishing a time-dependent metabolomic profile for urine collected from mice injected with 137CsCl. The samples were collected from control and exposed mice on days 2, 5, 20 and 30 after injection. The samples were then analyzed by ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) and processed by an array of informatics and statistical tools. A total of 1,412 features were identified in ESI+ and ESI− modes from which 200 were determined to contribute significantly to the separation of metabolomic profiles of controls from those of the different treatment time points. The results of this study highlight the ease of use of the UPLC/TOFMS platform in finding urinary biomarkers for 137Cs exposure. Pathway analysis of the statistically significant metabolites suggests perturbations in several amino acid and fatty acid metabolism pathways. The results also indicate that 137Cs exposure causes: similar changes in the urinary excretion levels of taurine and citrate as seen with external-beam gamma radiation; causes no attenuation in the levels of hexanoylglycine and N-acetylspermidine; and has unique effects on the levels of isovalerylglycine and tiglylglycine. PMID

  20. Metabolomics and Personalized Medicine.

    Science.gov (United States)

    Koen, Nadia; Du Preez, Ilse; Loots, Du Toit

    2016-01-01

    Current clinical practice strongly relies on the prognosis, diagnosis, and treatment of diseases using methods determined and averaged for the specific diseased cohort/population. Although this approach complies positively with most patients, misdiagnosis, treatment failure, relapse, and adverse drug effects are common occurrences in many individuals, which subsequently hamper the control and eradication of a number of diseases. These incidences can be explained by individual variation in the genome, transcriptome, proteome, and metabolome of a patient. Various "omics" approaches have investigated the influence of these factors on a molecular level, with the intention of developing personalized approaches to disease diagnosis and treatment. Metabolomics, the newest addition to the "omics" domain and the closest to the observed phenotype, reflects changes occurring at all molecular levels, as well as influences resulting from other internal and external factors. By comparing the metabolite profiles of two or more disease phenotypes, metabolomics can be applied to identify biomarkers related to the perturbation being investigated. These biomarkers can, in turn, be used to develop personalized prognostic, diagnostic, and treatment approaches, and can also be applied to the monitoring of disease progression, treatment efficacy, predisposition to drug-related side effects, and potential relapse. In this review, we discuss the contributions that metabolomics has made, and can potentially still make, towards the field of personalized medicine. © 2016 Elsevier Inc. All rights reserved.

  1. A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops.

    Science.gov (United States)

    Martínez Bueno, María Jesús; Díaz-Galiano, Francisco José; Rajski, Łukasz; Cutillas, Víctor; Fernández-Alba, Amadeo R

    2018-04-20

    In the last decade, the consumption trend of organic food has increased dramatically worldwide. However, the lack of reliable chemical markers to discriminate between organic and conventional products makes this market susceptible to food fraud in products labeled as "organic". Metabolomic fingerprinting approach has been demonstrated as the best option for a full characterization of metabolome occurring in plants, since their pattern may reflect the impact of both endogenous and exogenous factors. In the present study, advanced technologies based on high performance liquid chromatography-high-resolution accurate mass spectrometry (HPLC-HRAMS) has been used for marker search in organic and conventional tomatoes grown in greenhouse under controlled agronomic conditions. The screening of unknown compounds comprised the retrospective analysis of all tomato samples throughout the studied period and data processing using databases (mzCloud, ChemSpider and PubChem). In addition, stable nitrogen isotope analysis (δ 15 N) was assessed as a possible indicator to support discrimination between both production systems using crop/fertilizer correlations. Pesticide residue analyses were also applied as a well-established way to evaluate the organic production. Finally, the evaluation by combined chemometric analysis of high-resolution accurate mass spectrometry (HRAMS) and δ 15 N data provided a robust classification model in accordance with the agricultural practices. Principal component analysis (PCA) showed a sample clustering according to farming systems and significant differences in the sample profile was observed for six bioactive components (L-tyrosyl-L-isoleucyl-L-threonyl-L-threonine, trilobatin, phloridzin, tomatine, phloretin and echinenone). Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Metabolomics Approach to Male Lower Urinary Tract Symptoms: Identification of Possible Biomarkers and Potential Targets for New Treatments.

    Science.gov (United States)

    Mitsui, Takahiko; Kira, Satoru; Ihara, Tatsuya; Sawada, Norifumi; Nakagomi, Hiroshi; Miyamoto, Tatsuya; Shimura, Hiroshi; Yokomichi, Hiroshi; Takeda, Masayuki

    2018-05-01

    We identified metabolites using a metabolomics approach and investigated the association between these metabolites and lower urinary tract symptoms. We used a 24-hour bladder diary and I-PSS (International Prostate Symptom Score) to assess micturition behavior and lower urinary tract symptoms in 58 male patients without apparent neurological disease. Lower urinary tract symptoms were defined as a total I-PSS score of 8 or greater. Patients with a score of 7 or less were placed in the control group. A comprehensive study of plasma metabolites was also performed by capillary electrophoresis time-of-flight mass spectrometry. Metabolites were compared between the lower urinary tract symptoms and control groups using the Mann-Whitney U test. Biomarkers of male lower urinary tract symptoms from the metabolites were analyzed using multivariable logistic regression analysis to determine the OR. Of the 58 men 32 were in the lower urinary tract symptoms group and the remaining 26 were in the control group. The 24-hour bladder diary showed that nocturnal urine volume, 24-hour micturition frequency, nocturnal micturition frequency and the nocturia index were significantly higher in the lower urinary tract symptoms group. Metabolomics analysis identified 60 metabolites from patient plasma. Multivariate analysis revealed that increased glutamate and decreased arginine, asparagine and inosine monophosphate were significantly associated with lower urinary tract symptoms in males. Decreases in citrulline and glutamine could also be associated with male lower urinary tract symptoms. Male lower urinary tract symptoms may develop due to abnormal metabolic processes in some pathways. Potential new treatments for lower urinary tract symptoms can be developed by identifying changes in the amino acid profiles. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  3. Diet-induced hyperinsulinemia differentially affects glucose and protein metabolism: a high-throughput metabolomic approach in rats.

    Science.gov (United States)

    Etxeberria, U; de la Garza, A L; Martínez, J A; Milagro, F I

    2013-09-01

    Metabolomics is a high-throughput tool that quantifies and identifies the complete set of biofluid metabolites. This "omics" science is playing an increasing role in understanding the mechanisms involved in disease progression. The aim of this study was to determine whether a nontargeted metabolomic approach could be applied to investigate metabolic differences between obese rats fed a high-fat sucrose (HFS) diet for 9 weeks and control diet-fed rats. Animals fed with the HFS diet became obese, hyperleptinemic, hyperglycemic, hyperinsulinemic, and resistant to insulin. Serum samples of overnight-fasted animals were analyzed by (1)H NMR technique, and 49 metabolites were identified and quantified. The biochemical changes observed suggest that major metabolic processes like carbohydrate metabolism, β-oxidation, tricarboxylic acid cycle, Kennedy pathway, and folate-mediated one-carbon metabolism were altered in obese rats. The circulating levels of most amino acids were lower in obese animals. Serum levels of docosahexaenoic acid, linoleic acid, unsaturated n-6 fatty acids, and total polyunsaturated fatty acids also decreased in HFS-fed rats. The circulating levels of urea, six water-soluble metabolites (creatine, creatinine, choline, acetyl carnitine, formate, and allantoin), and two lipid compounds (phosphatidylcholines and sphingomyelin) were also significantly reduced by the HFS diet intake. This study offers further insight of the possible mechanisms implicated in the development of diet-induced obesity. It suggests that the HFS diet-induced hyperinsulinemia is responsible for the decrease in the circulating levels of urea, creatinine, and many amino acids, despite an increase in serum glucose levels.

  4. Unambiguous metabolite identification in high-throughput metabolomics by hybrid 1D 1 H NMR/ESI MS 1 approach: Hybrid 1D 1 H NMR/ESI MS 1 metabolomics method

    Energy Technology Data Exchange (ETDEWEB)

    Walker, Lawrence R. [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland WA 99354 USA; Hoyt, David W. [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland WA 99354 USA; Walker, S. Michael [Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence KS 66045 USA; Ward, Joy K. [Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence KS 66045 USA; Nicora, Carrie D. [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland WA 99354 USA; Bingol, Kerem [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland WA 99354 USA

    2016-09-16

    We present a novel approach to improve accuracy of metabolite identification by combining direct infusion ESI MS1 with 1D 1H NMR spectroscopy. The new approach first applies standard 1D 1H NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in metabolomics library. This generates a list of candidate metabolites. The list contains false positive and ambiguous identifications. Next, we constrained the list with the chemical formulas derived from high-resolution direct infusion ESI MS1 spectrum of the same sample. Detection of the signals of a metabolite both in NMR and MS significantly improves the confidence of identification and eliminates false positive identification. 1D 1H NMR and direct infusion ESI MS1 spectra of a sample can be acquired in parallel in several minutes. This is highly beneficial for rapid and accurate screening of hundreds of samples in high-throughput metabolomics studies. In order to make this approach practical, we developed a software tool, which is integrated to Chenomx NMR Suite. The approach is demonstrated on a model mixture, tomato and Arabidopsis thaliana metabolite extracts, and human urine.

  5. Comparative mass spectrometry & nuclear magnetic resonance metabolomic approaches for nutraceuticals quality control analysis: a brief review.

    Science.gov (United States)

    Farag, Mohamed A

    2014-01-01

    The number of botanical dietary supplements in the market has recently increased primarily due to increased health awareness. Standardization and quality control of the constituents of these plant extracts is an important topic, particularly when such ingredients are used long term as dietary supplements, or in cases where higher doses are marketed as drugs. The development of fast, comprehensive, and effective untargeted analytical methods for plant extracts is of high interest. Nuclear magnetic resonance spectroscopy and mass spectrometry are the most informative tools, each of which enables high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in the majority of plant metabolomics applications, there is a growing interest in combining the data from both platforms to effectively unravel the complexity of plant samples. The application of combined MS and NMR in the quality control of nutraceuticals forms the major part of this review. Finally I will look at the future developments and perspectives of these two technologies for the quality control of herbal materials.

  6. Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment

    Science.gov (United States)

    Welzenbach, Julia; Neuhoff, Christiane; Looft, Christian; Schellander, Karl; Tholen, Ernst; Große-Brinkhaus, Christine

    2016-01-01

    The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators. PMID:26919205

  7. NMR-based metabolomics applications

    DEFF Research Database (Denmark)

    Iaccarino, Nunzia

    Metabolomics is the scientific discipline that identifies and quantifies endogenous and exogenous metabolites in different biological samples. Metabolites are crucial components of a biological system and they are highly informative about its functional state, due to their closeness to the organism...... focused on the analysis of various samples covering a wide range of fields, namely, food and nutraceutical sciences, cell metabolomics and medicine using a metabolomics approach. Indeed, the first part of the thesis describes two exploratory studies performed on Algerian extra virgin olive oil and apple...... juice from ancient Danish apple cultivars. Both studies revealed variety-related peculiarities that would have been difficult to detect by means of traditional analysis. The second part of the project includes four metabolomics studies performed on samples of biological origin. In particular, the first...

  8. Positional enrichment by proton analysis (PEPA). A one-dimensional "1H-NMR approach for "1"3C stable isotope tracer studies in metabolomics

    International Nuclear Information System (INIS)

    Vinaixa, Maria; Yanes, Oscar; Rodriguez, Miguel A.; Capellades, Jordi; Aivio, Suvi; Stracker, Travis H.; Gomez, Josep; Canyellas, Nicolau

    2017-01-01

    A novel metabolomics approach for NMR-based stable isotope tracer studies called PEPA is presented, and its performance validated using human cancer cells. PEPA detects the position of carbon label in isotopically enriched metabolites and quantifies fractional enrichment by indirect determination of "1"3C-satellite peaks using 1D-"1H-NMR spectra. In comparison with "1"3C-NMR, TOCSY and HSQC, PEPA improves sensitivity, accelerates the elucidation of "1"3C positions in labeled metabolites and the quantification of the percentage of stable isotope enrichment. Altogether, PEPA provides a novel framework for extending the high-throughput of "1H-NMR metabolic profiling to stable isotope tracing in metabolomics, facilitating and complementing the information derived from 2D-NMR experiments and expanding the range of isotopically enriched metabolites detected in cellular extracts. (copyright 2017 The Authors. Published by Wiley-VCH Verlag GmbH and Co. KGaA.)

  9. Positional enrichment by proton analysis (PEPA). A one-dimensional {sup 1}H-NMR approach for {sup 13}C stable isotope tracer studies in metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Vinaixa, Maria; Yanes, Oscar [Department of Electronic Engineering-Universitat Rovira i Virgili, Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Reus (Spain); Rodriguez, Miguel A.; Capellades, Jordi [Universitat Rovira i Virgili, Spanish Biomedical Research Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Reus (Spain); Aivio, Suvi; Stracker, Travis H. [Institute for Research in Biomedicine (IRB Barcelona), Barcelona Institute of Science and Technology (Spain); Gomez, Josep; Canyellas, Nicolau [Department of Electronic Engineering-, Universitat Rovira i Virgili, Tarragona (Spain)

    2017-03-20

    A novel metabolomics approach for NMR-based stable isotope tracer studies called PEPA is presented, and its performance validated using human cancer cells. PEPA detects the position of carbon label in isotopically enriched metabolites and quantifies fractional enrichment by indirect determination of {sup 13}C-satellite peaks using 1D-{sup 1}H-NMR spectra. In comparison with {sup 13}C-NMR, TOCSY and HSQC, PEPA improves sensitivity, accelerates the elucidation of {sup 13}C positions in labeled metabolites and the quantification of the percentage of stable isotope enrichment. Altogether, PEPA provides a novel framework for extending the high-throughput of {sup 1}H-NMR metabolic profiling to stable isotope tracing in metabolomics, facilitating and complementing the information derived from 2D-NMR experiments and expanding the range of isotopically enriched metabolites detected in cellular extracts. (copyright 2017 The Authors. Published by Wiley-VCH Verlag GmbH and Co. KGaA.)

  10. UHPLC-Q-TOF-MS-based metabolomics approach to compare the saponin compositions of Xueshuantong injection and Xuesaitong injection.

    Science.gov (United States)

    Yao, Changliang; Yang, Wenzhi; Zhang, Jingxian; Qiu, Shi; Chen, Ming; Shi, Xiaojian; Pan, Huiqin; Wu, Wanying; Guo, Dean

    2017-02-01

    Various traditional Chinese medicine preparations developed from Notoginseng total saponins, including Xueshuantong injection and Xuesaitong injection, are extensively used in China to treat cardiocerebrovascular diseases. However, the difference of their saponin compositions remains unknown. An ultra high performance liquid chromatography with quadrupole time-of-flight mass spectrometry based metabolomics approach was developed to probe the saponin discrimination between Xueshuantong and Xuesaitong and the related factors by large sample analysis. A highly efficient chromatographic separation was achieved on an HSS T3 column within 20 min with the holistic metabolites information recorded in the negative MS E mode. A six-step data pretreatment procedure mainly based on Progenesis QI and mass defect filtering was established. Pattern recognition chemometrics was used to discover the potential saponin markers. The saponin composition of Wuzhou Xueshuantong showed distinct discrimination from the other products. Wuzhou Xueshuantong contains more abundant protopanaxatriol-type noto-R 1 , Rg 1 , Re, and protopanaxadiol-type Rb 1 , but less Rd and other low-polarity protopanaxadiol-type ginsenosides. These differences could not directly correlate to the use of different parts of Panax notoginseng, but possibly to the different preparation techniques employed by different manufacturers. These results are beneficial to the establishment of pharmacopoeia standards and the assessment of the efficacy and adverse drug reactions for these homologous products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Changes in extra-virgin olive oil added with Lycium barbarum L. carotenoids during frying: Chemical analyses and metabolomic approach.

    Science.gov (United States)

    Blasi, F; Rocchetti, G; Montesano, D; Lucini, L; Chiodelli, G; Ghisoni, S; Baccolo, G; Simonetti, M S; Cossignani, L

    2018-03-01

    In this work, an Italian extra-virgin olive oil (EVOO) sample and the same sample added with a carotenoid-rich nutraceutical extract from Lycium barbarum L. (EVOOCar) were subjected to a frying process to comparatively assess chemical and physical changes and heat stability. Oxidation progress was monitored by measuring oil quality changes such as peroxide value, free acidity, K232, K268, and fatty acid composition as well as minor compound content, phenols, α-tocopherol, and carotenoids. An UHPLC/QTOF-MS metabolomics approach discriminated the two oil samples based on their chemical changes during frying, identifying also the phenolic classes most exposed to statistically significant variations. Partial least square discriminant analysis and volcano analysis were applied together to identify the most significant markers allowing group separation. The decrease in total phenolic content was lower in EVOOCar than in EVOO during frying. Monounsaturated and polyunsaturated fatty acids showed a significant percentage loss, 3.7% and 17.2%, respectively, in EVOO after 180min frying at 180°C, while they remained constant or slightly changed in EVOOCar. Zeaxanthin added to the oil rapidly decreased during the frying process. These findings showed that the addition of a carotenoid extract from L. barbarum can help to improve the oxidative stability of extra-virgin olive oil. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. An Innovative Approach for The Integration of Proteomics and Metabolomics Data In Severe Septic Shock Patients Stratified for Mortality.

    Science.gov (United States)

    Cambiaghi, Alice; Díaz, Ramón; Martinez, Julia Bauzá; Odena, Antonia; Brunelli, Laura; Caironi, Pietro; Masson, Serge; Baselli, Giuseppe; Ristagno, Giuseppe; Gattinoni, Luciano; de Oliveira, Eliandre; Pastorelli, Roberta; Ferrario, Manuela

    2018-04-27

    In this work, we examined plasma metabolome, proteome and clinical features in patients with severe septic shock enrolled in the multicenter ALBIOS study. The objective was to identify changes in the levels of metabolites involved in septic shock progression and to integrate this information with the variation occurring in proteins and clinical data. Mass spectrometry-based targeted metabolomics and untargeted proteomics allowed us to quantify absolute metabolites concentration and relative proteins abundance. We computed the ratio D7/D1 to take into account their variation from day 1 (D1) to day 7 (D7) after shock diagnosis. Patients were divided into two groups according to 28-day mortality. Three different elastic net logistic regression models were built: one on metabolites only, one on metabolites and proteins and one to integrate metabolomics and proteomics data with clinical parameters. Linear discriminant analysis and Partial least squares Discriminant Analysis were also implemented. All the obtained models correctly classified the observations in the testing set. By looking at the variable importance (VIP) and the selected features, the integration of metabolomics with proteomics data showed the importance of circulating lipids and coagulation cascade in septic shock progression, thus capturing a further layer of biological information complementary to metabolomics information.

  13. Gas chromatography-mass spectrometry based metabolomic approach for optimization and toxicity evaluation of earthworm sub-lethal responses to carbofuran.

    Directory of Open Access Journals (Sweden)

    Mohana Krishna Reddy Mudiam

    Full Text Available Despite recent advances in understanding mechanism of toxicity, the development of biomarkers (biochemicals that vary significantly with exposure to chemicals for pesticides and environmental contaminants exposure is still a challenging task. Carbofuran is one of the most commonly used pesticides in agriculture and said to be most toxic carbamate pesticide. It is necessary to identify the biochemicals that can vary significantly after carbofuran exposure on earthworms which will help to assess the soil ecotoxicity. Initially, we have optimized the extraction conditions which are suitable for high-throughput gas chromatography mass spectrometry (GC-MS based metabolomics for the tissue of earthworm, Metaphire posthuma. Upon evaluation of five different extraction solvent systems, 80% methanol was found to have good extraction efficiency based on the yields of metabolites, multivariate analysis, total number of peaks and reproducibility of metabolites. Later the toxicity evaluation was performed to characterize the tissue specific metabolomic perturbation of earthworm, Metaphire posthuma after exposure to carbofuran at three different concentration levels (0.15, 0.3 and 0.6 mg/kg of soil. Seventeen metabolites, contributing to the best classification performance of highest dose dependent carbofuran exposed earthworms from healthy controls were identified. This study suggests that GC-MS based metabolomic approach was precise and sensitive to measure the earthworm responses to carbofuran exposure in soil, and can be used as a promising tool for environmental eco-toxicological studies.

  14. An in vitro metabolomics approach to identify hepatotoxicity biomarkers in human L02 liver cells treated with pekinenal, a natural compound.

    Science.gov (United States)

    Shi, Jiexia; Zhou, Jing; Ma, Hongyue; Guo, Hongbo; Ni, Zuyao; Duan, Jin'ao; Tao, Weiwei; Qian, Dawei

    2016-02-01

    An in vitro cell metabolomics study was performed on human L02 liver cells to investigate the toxic biomarkers of pekinenal from the herb Euphorbia pekinensis Rupr. Pekinenal significantly induced L02 cell damage, which was characterised by necrosis and apoptosis. Metabolomics combined with data pattern recognition showed that pekinenal significantly altered the profiles of more than 1299 endogenous metabolites with variable importance in the projection (VIP) > 1. Further, screening correlation coefficients between the intensities of all metabolites and the extent of L02 cell damage (MTT) identified 12 biomarker hits: ten were downregulated and two were upregulated. Among these hits, LysoPC(18:1(9Z)/(11Z)), PC(22:0/15:0) and PC(20:1(11Z)/14:1(9Z)) were disordered, implying the initiation of inflammation and cell damage. Several fatty acids (FAs) (3-hydroxytetradecanedioic acid, pivaloylcarnitine and eicosapentaenoyl ethanolamide) decreased due to fatty acid oxidation. Dihydroceramide and Cer(d18:0/14:0) were also altered and are associated with apoptosis. Additional examination of the levels of intracellular reactive oxygen species (ROS) and two eicosanoids (PGE2, PGF2α) in the cell supernatant confirmed the fatty acid oxidation and arachidonic acid metabolism pathways, respectively. In summary, cell metabolomics is a highly efficient approach for identifying toxic biomarkers and helping understand toxicity mechanisms and predict herb-induced liver injury.

  15. New findings on the in vivo antioxidant activity of Curcuma longa extract by an integrated (1)H NMR and HPLC-MS metabolomic approach.

    Science.gov (United States)

    Dall'Acqua, Stefano; Stocchero, Matteo; Boschiero, Irene; Schiavon, Mariano; Golob, Samuel; Uddin, Jalal; Voinovich, Dario; Mammi, Stefano; Schievano, Elisabetta

    2016-03-01

    Curcuminoids possess powerful antioxidant activity as demonstrated in many chemical in vitro tests and in several in vivo trials. Nevertheless, the mechanism of this activity is not completely elucidated and studies on the in vivo antioxidant effects are still needed. Metabolomics may be used as an attractive approach for such studies and in this paper, we describe the effects of oral administration of a Curcuma longa L. extract (150 mg/kg of total curcuminoids) to 12 healthy rats with particular attention to urinary markers of oxidative stress. The experiment was carried out over 33 days and changes in the 24-h urine samples metabolome were evaluated by (1)H NMR and HPLC-MS. Both techniques produced similar representations for the collected samples confirming our previous study. Modifications of the urinary metabolome lead to the observation of different variables proving the complementarity of (1)H NMR and HPLC-MS for metabolomic purposes. The urinary levels of allantoin, m-tyrosine, 8-hydroxy-2'-deoxyguanosine, and nitrotyrosine were decreased in the treated group thus supporting an in vivo antioxidant effect of the oral administration of Curcuma extract to healthy rats. On the other hand, urinary TMAO levels were higher in the treated compared to the control group suggesting a role of curcumin supplementation on microbiota or on TMAO urinary excretion. Furthermore, the urinary levels of the sulphur containing compounds taurine and cystine were also changed suggesting a role for such constituents in the biochemical pathways involved in Curcuma extract bioactivity and indicating the need for further investigation on the complex role of antioxidant curcumin effects. Copyright © 2015 Elsevier B.V. All rights reserved.

  16. Metabolomics in Toxicology and Preclinical Research

    Science.gov (United States)

    Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

    2013-01-01

    Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

  17. A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc

    International Nuclear Information System (INIS)

    Long, Sara M.; Tull, Dedreia L.; Jeppe, Katherine J.; De Souza, David P.; Dayalan, Saravanan; Pettigrove, Vincent J.; McConville, Malcolm J.; Hoffmann, Ary A.

    2015-01-01

    Highlights: • An integrated metabolomics approach was applied to examine zinc exposure in midges. • Changes in carbohydrate and energy metabolism were observed using GC–MS. • Transsulfuration pathway is affected by zinc exposure. • Heavy metals other than zinc affect the transsulfuration pathways differently. - Abstract: Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography–mass spectrometry (GC–MS) analysis and a targeted liquid chromatography–mass spectrometry (LC–MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary

  18. A multi-platform metabolomics approach demonstrates changes in energy metabolism and the transsulfuration pathway in Chironomus tepperi following exposure to zinc

    Energy Technology Data Exchange (ETDEWEB)

    Long, Sara M., E-mail: hoskins@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); Tull, Dedreia L., E-mail: dedreia@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Jeppe, Katherine J., E-mail: k.jeppe@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, The University of Melbourne, 3010 (Australia); De Souza, David P., E-mail: desouzad@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Dayalan, Saravanan, E-mail: sdayalan@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Pettigrove, Vincent J., E-mail: vpet@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, The University of Melbourne, 3010 (Australia); McConville, Malcolm J., E-mail: malcolmm@unimelb.edu.au [Metabolomics Australia, Bio21 Molecular Science and Biotechnology Institute, 30 Flemington Road, Parkville, 3052 (Australia); Hoffmann, Ary A., E-mail: ary@unimelb.edu.au [Centre for Aquatic Pollution, Identification and Management (CAPIM), School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia); School of BioSciences, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, 30 Flemington Road, Parkville, 3052 (Australia)

    2015-05-15

    Highlights: • An integrated metabolomics approach was applied to examine zinc exposure in midges. • Changes in carbohydrate and energy metabolism were observed using GC–MS. • Transsulfuration pathway is affected by zinc exposure. • Heavy metals other than zinc affect the transsulfuration pathways differently. - Abstract: Measuring biological responses in resident biota is a commonly used approach to monitoring polluted habitats. The challenge is to choose sensitive and, ideally, stressor-specific endpoints that reflect the responses of the ecosystem. Metabolomics is a potentially useful approach for identifying sensitive and consistent responses since it provides a holistic view to understanding the effects of exposure to chemicals upon the physiological functioning of organisms. In this study, we exposed the aquatic non-biting midge, Chironomus tepperi, to two concentrations of zinc chloride and measured global changes in polar metabolite levels using an untargeted gas chromatography–mass spectrometry (GC–MS) analysis and a targeted liquid chromatography–mass spectrometry (LC–MS) analysis of amine-containing metabolites. These data were correlated with changes in the expression of a number of target genes. Zinc exposure resulted in a reduction in levels of intermediates in carbohydrate metabolism (i.e., glucose 6-phosphate, fructose 6-phosphate and disaccharides) and an increase in a number of TCA cycle intermediates. Zinc exposure also resulted in decreases in concentrations of the amine containing metabolites, lanthionine, methionine and cystathionine, and an increase in metallothionein gene expression. Methionine and cystathionine are intermediates in the transsulfuration pathway which is involved in the conversion of methionine to cysteine. These responses provide an understanding of the pathways affected by zinc toxicity, and how these effects are different to other heavy metals such as cadmium and copper. The use of complementary

  19. New approaches in systems diagnosis : combining metabolomics and ultra-weak photon emission

    NARCIS (Netherlands)

    Rossetto-Burgos, R.C.

    2017-01-01

    In recent decades, the use of a systems-based view of life has provided key insight into fundamental processes with respect to biology. In life sciences, important paradigm shifts are the way in which we approach health and disease. Although modern medicine has traditionally emphasized pathology and

  20. An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

    Science.gov (United States)

    Ruiz-Aracama, Ainhoa; Peijnenburg, Ad; Kleinjans, Jos; Jennen, Danyel; van Delft, Joost; Hellfrisch, Caroline; Lommen, Arjen

    2011-05-20

    In vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied in vitro but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on in vitro systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the in vitro model system and model toxicant, respectively. The study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD. Untargeted profiling of the polar and apolar metabolites of in vitro cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.

  1. Metabolomic approach to identifying bioactive compounds in berries: advances toward fruit nutritional enhancement.

    Science.gov (United States)

    Stewart, Derek; McDougall, Gordon J; Sungurtas, Julie; Verrall, Susan; Graham, Julie; Martinussen, Inger

    2007-06-01

    Plant polyphenolics continue to be the focus of attention with regard to their putative impact on human health. An increasing and ageing human population means that the focus on nutrition and nutritional enhancement or optimisation of our foodstuffs is paramount. Using the raspberry as a model, we have shown how modern metabolic profiling approaches can be used to identify the changes in the level of beneficial polyphenolics in fruit breeding segregating populations and how the level of these components is determined by genetic and/or environmental control. Interestingly, the vitamin C content appeared to be significantly influenced by environment (growth conditions) whilst the content of the polyphenols such as cyanidin, pelargonidin and quercetin glycosides appeared much more tightly regulated, suggesting a rigorous genetic control. Preliminary metabolic profiling showed that the fruit polyphenolic profiles divided into two gross groups segregating on the basis of relative levels of cyanidin-3-sophoroside and cyanidin-3-rutinoside, compounds implicated as conferring human health benefits.

  2. Serum metabolites and risk of myocardial infarction and ischemic stroke: a targeted metabolomic approach in two German prospective cohorts.

    Science.gov (United States)

    Floegel, Anna; Kühn, Tilman; Sookthai, Disorn; Johnson, Theron; Prehn, Cornelia; Rolle-Kampczyk, Ulrike; Otto, Wolfgang; Weikert, Cornelia; Illig, Thomas; von Bergen, Martin; Adamski, Jerzy; Boeing, Heiner; Kaaks, Rudolf; Pischon, Tobias

    2018-01-01

    Metabolomic approaches in prospective cohorts may offer a unique snapshot into early metabolic perturbations that are associated with a higher risk of cardiovascular diseases (CVD) in healthy people. We investigated the association of 105 serum metabolites, including acylcarnitines, amino acids, phospholipids and hexose, with risk of myocardial infarction (MI) and ischemic stroke in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) and Heidelberg (25,540 adults) cohorts. Using case-cohort designs, we measured metabolites among individuals who were free of CVD and diabetes at blood draw but developed MI (n = 204 and n = 228) or stroke (n = 147 and n = 121) during follow-up (mean, 7.8 and 7.3 years) and among randomly drawn subcohorts (n = 2214 and n = 770). We used Cox regression analysis and combined results using meta-analysis. Independent of classical CVD risk factors, ten metabolites were associated with risk of MI in both cohorts, including sphingomyelins, diacyl-phosphatidylcholines and acyl-alkyl-phosphatidylcholines with pooled relative risks in the range of 1.21-1.40 per one standard deviation increase in metabolite concentrations. The metabolites showed positive correlations with total- and LDL-cholesterol (r ranged from 0.13 to 0.57). When additionally adjusting for total-, LDL- and HDL-cholesterol, triglycerides and C-reactive protein, acyl-alkyl-phosphatidylcholine C36:3 and diacyl-phosphatidylcholines C38:3 and C40:4 remained associated with risk of MI. When added to classical CVD risk models these metabolites further improved CVD prediction (c-statistics increased from 0.8365 to 0.8384 in EPIC-Potsdam and from 0.8344 to 0.8378 in EPIC-Heidelberg). None of the metabolites was consistently associated with stroke risk. Alterations in sphingomyelin and phosphatidylcholine metabolism, and particularly metabolites of the arachidonic acid pathway are independently associated with risk of MI in

  3. An overview of renal metabolomics.

    Science.gov (United States)

    Kalim, Sahir; Rhee, Eugene P

    2017-01-01

    The high-throughput, high-resolution phenotyping enabled by metabolomics has been applied increasingly to a variety of questions in nephrology research. This article provides an overview of current metabolomics methodologies and nomenclature, citing specific considerations in sample preparation, metabolite measurement, and data analysis that investigators should understand when examining the literature or designing a study. Furthermore, we review several notable findings that have emerged in the literature that both highlight some of the limitations of current profiling approaches, as well as outline specific strengths unique to metabolomics. More specifically, we review data on the following: (i) tryptophan metabolites and chronic kidney disease onset, illustrating the interpretation of metabolite data in the context of established biochemical pathways; (ii) trimethylamine-N-oxide and cardiovascular disease in chronic kidney disease, illustrating the integration of exogenous and endogenous inputs to the blood metabolome; and (iii) renal mitochondrial function in diabetic kidney disease and acute kidney injury, illustrating the potential for rapid translation of metabolite data for diagnostic or therapeutic aims. Finally, we review future directions, including the need to better characterize interperson and intraperson variation in the metabolome, pool existing data sets to identify the most robust signals, and capitalize on the discovery potential of emerging nontargeted methods. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

  4. Assessment of protein modifications in liver of rats under chronic treatment with paracetamol (acetaminophen) using two complementary mass spectrometry-based metabolomic approaches.

    Science.gov (United States)

    Mast, Carole; Lyan, Bernard; Joly, Charlotte; Centeno, Delphine; Giacomoni, Franck; Martin, Jean-François; Mosoni, Laurent; Dardevet, Dominique; Pujos-Guillot, Estelle; Papet, Isabelle

    2015-04-29

    Liver protein can be altered under paracetamol (APAP) treatment. APAP-protein adducts and other protein modifications (oxidation/nitration, expression) play a role in hepatotoxicity induced by acute overdoses, but it is unknown whether liver protein modifications occur during long-term treatment with non-toxic doses of APAP. We quantified APAP-protein adducts and assessed other protein modifications in the liver from rats under chronic (17 days) treatment with two APAP doses (0.5% or 1% of APAP in the diet w/w). A targeted metabolomic method was validated and used to quantify APAP-protein adducts as APAP-cysteine adducts following proteolytic hydrolysis. The limit of detection was found to be 7ng APAP-cysteine/mL hydrolysate i.e. an APAP-Cys to tyrosine ratio of 0.016‰. Other protein modifications were assessed on the same protein hydrolysate by untargeted metabolomics including a new strategy to process the data and identify discriminant molecules. These two complementary mass spectrometry (MS)-based metabolic approaches enabled the assessment of a wide range of protein modifications induced by chronic treatment with APAP. APAP-protein adducts were detected even in the absence of glutathione depletion and hepatotoxicity, i.e. in the 0.5% APAP group, and increased by 218% in the 1% APAP group compared to the 0.5% APAP group. At the same time, the untargeted metabolomic method revealed a decrease in the binding of cysteine, cysteinyl-glycine and GSH to thiol groups of protein cysteine residues, an increase in the oxidation of tryptophan and proline residues and a modification in protein expression. This wide range of modifications in liver proteins occurred in rats under chronic treatment with APAP that did not induce hepatotoxicity. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Application of a novel metabolomic approach based on atmospheric pressure photoionization mass spectrometry using flow injection analysis for the study of Alzheimer's disease.

    Science.gov (United States)

    González-Domínguez, Raúl; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-01-01

    The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min(-1) and 40 µl min(-1), respectively) compared to positive mode (50 µl min(-1) and 20 µl min(-1)). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimer's disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. An integrated approach to the evaluation of a metabolomic fingerprint for a phytocomplex. Focus on artichoke [Cynara cardunculus subsp. scolymus] leaf.

    Science.gov (United States)

    Fodaroni, Giada; Burico, Michela; Gaetano, Anna; Maidecchi, Anna; Pagiotti, Rita; Mattoli, Luisa; Traldi, Pietro; Ragazzi, Eugenio

    2014-04-01

    The availability of reliable herbal formulations is essential in order to assure the maximal activity and to limit unwanted side-effects. The correct concentration of declared components of herbal products is a matter of health legislation and regulation, but is still a topic under debate in the field of quality control assessment. In the present work specific constituents of artichoke leaf extracts, considered as a test herbal product, were measured by standard spectrophotometric and HPLC methods (for quantitative determination of some components only), and results were correlated with the ESI-MS (showing the full metabolomic fingerprint). Phytocomplex stability over time was also investigated in batches submitted to different storage conditions. The results indicated excellent agreement between the two approaches in the measurement of total caffeoylquinic acids and chlorogenic acid contents, but the metabolomic ESI-MS method approach provides a more complete evaluation and monitoring of the composition of a herbal product, without focusing only on a single/few compound measurements. Therefore, the ESI-MS method can be proposed for the evaluation of the quality of complex matrices, such as those in a phytocomplex. Another aspect lies in the possibility to obtain a broad-spectrum stability control of herbal formulations, requiring minimal sample pre-processing procedures.

  7. Serum metabolomics of Indian women with polycystic ovary syndrome using 1H NMR coupled with a pattern recognition approach.

    Science.gov (United States)

    RoyChoudhury, Sourav; Mishra, Biswa Prasanna; Khan, Tila; Chattopadhayay, Ratna; Lodh, Indrani; Datta Ray, Chaitali; Bose, Gunja; Sarkar, Himadri S; Srivastava, Sudha; Joshi, Mamata V; Chakravarty, Baidyanath; Chaudhury, Koel

    2016-10-18

    Polycystic ovary syndrome (PCOS) is one of the most commonly occurring metabolic and endocrinological disorders affecting women of reproductive age. Metabolomics is an emerging field that holds promise in understanding disease pathophysiology. Recently, a few metabolomics based studies have been attempted in PCOS patients; however, none of them have included patients from the Indian population. The main objective of this study was to investigate the serum metabolomic profile of Indian women with PCOS and compare them with controls. Proton nuclear magnetic resonance ( 1 H NMR) was used to first identify the differentially expressed metabolites among women with PCOS from the Eastern region of India during the discovery phase and further validated in a separate cohort of PCOS and control subjects. Multivariate analysis of the binned spectra indicated 16 dysregulated bins in the sera of these women with PCOS. Out of these 16 bins, 13 identified bins corresponded to 12 metabolites including 8 amino acids and 4 energy metabolites. Amongst the amino acids, alanine, valine, leucine and threonine and amongst the energy metabolites, lactate and acetate were observed to be significantly up-regulated in women with PCOS when compared with controls. The remaining 4 amino acids, l-glutamine, proline, glutamate and histidine were down-regulated along with 2 energy metabolites: glucose and 3-hydroxybutyric acid. Our findings showed dysregulations in the expression of different metabolites in the serum of women with PCOS suggesting the involvement of multiple pathways including amino acid metabolism, carbohydrate/lipid metabolism, purine and pyrimidine metabolism and protein synthesis.

  8. An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

    International Nuclear Information System (INIS)

    Wang, Yang; Liu, Fang; Li, Peng; He, Chengwei; Wang, Ruibing; Su, Huanxing; Wan, Jian-Bo

    2016-01-01

    Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies. - Highlights: • An UHPLC/Q-TOF tsMIM MS-based pseudotargeted metabolomics was proposed. • Compared to full scan, the improved method exhibits better repeatability and a wider linear range. • The proposed method could achieve pseudotargeted analysis on one UHPLC/Q-TOF/MS instrument. • The developed method was successfully used to discover biomarkers for alcohol-induced liver injury.

  9. An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yang; Liu, Fang; Li, Peng; He, Chengwei; Wang, Ruibing; Su, Huanxing; Wan, Jian-Bo, E-mail: jbwan@umac.mo

    2016-07-13

    Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies. - Highlights: • An UHPLC/Q-TOF tsMIM MS-based pseudotargeted metabolomics was proposed. • Compared to full scan, the improved method exhibits better repeatability and a wider linear range. • The proposed method could achieve pseudotargeted analysis on one UHPLC/Q-TOF/MS instrument. • The developed method was successfully used to discover biomarkers for alcohol-induced liver injury.

  10. Multifaceted metabolomics approaches for characterization of lignocellulosic biomass degradation products formed during ammonia fiber expansion pretreatment

    Science.gov (United States)

    Vismeh, Ramin

    to 45-50 % of ammonia that is lost during the pretreatment. Methodology for identification, detection and quantification of various diferulate cross-linkers in forms of Di-Acids (Di-Ac), Acid-Amide (Ac-Am), and Di-Amides (Di-Am) in AFEX and NaOH treated corn stover using ultrahigh performance liquid chromatography/tandem mass spectrometry (LC/MS/MS) is presented. Characterization of isomeric diferulates was based on the distinguishing fragments formed upon collision induced dissociation (CID) of [M+H]+ ions of each diferulate isomer. LC separations combined with quasi-simultaneous acquisition of mass spectra at multiple collision energies provide fast spectrum acquisition using a time-of-flight (TOF) mass analyzer. This approach, called mux-CID, generates molecular and fragment ion mass information at different collision energies for molecular and adduct ions of oligosaccharides in a single analysis. Non-selective CID facilitated characterization of glucans and arabinoxylans in the AFEXTCS extracts. A LC/MS gradient based on multiplexed-CID detection was developed and applied to profile oligosaccharides in AFEXTCS extract. This method detected glucans with degree of polymerization (DP) from 2 to 22 after solid phase extraction (SPE) enrichment using porous graphitized carbon (PGC), which proved essential for recoveries of specific oligosaccharides. Arabinoxylans were also detected and partially characterized using this strategy after hydrolysis using xylanase. A relative quantification based on peak areas showed removal of almost 85% of the acetate esters of arabinoxylans after AFEX.

  11. Particle simulation on a distributed memory highly parallel processor

    International Nuclear Information System (INIS)

    Sato, Hiroyuki; Ikesaka, Morio

    1990-01-01

    This paper describes parallel molecular dynamics simulation of atoms governed by local force interaction. The space in the model is divided into cubic subspaces and mapped to the processor array of the CAP-256, a distributed memory, highly parallel processor developed at Fujitsu Labs. We developed a new technique to avoid redundant calculation of forces between atoms in different processors. Experiments showed the communication overhead was less than 5%, and the idle time due to load imbalance was less than 11% for two model problems which contain 11,532 and 46,128 argon atoms. From the software simulation, the CAP-II which is under development is estimated to be about 45 times faster than CAP-256 and will be able to run the same problem about 40 times faster than Fujitsu's M-380 mainframe when 256 processors are used. (author)

  12. Using metabolomics to evaluate food intake

    DEFF Research Database (Denmark)

    Manach, Claudine; Brennan, Lorraine; Dragsted, Lars Ove

    2015-01-01

    Improving dietary assessment is essential for modern nutritional epidemiology. This chapter discusses the potential of metabolomics for the identification of new biomarkers of intake and presents the first candidate biomarkers discovered using this approach. It then describes the challenges...

  13. Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach

    Science.gov (United States)

    Yu, Nanyang; Wei, Si; Li, Meiying; Yang, Jingping; Li, Kan; Jin, Ling; Xie, Yuwei; Giesy, John P.; Zhang, Xiaowei; Yu, Hongxia

    2016-04-01

    Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects.

  14. A metabolomics-driven approach to predict cocoa product consumption by designing a multimetabolite biomarker model in free-living subjects from the PREDIMED study.

    Science.gov (United States)

    Garcia-Aloy, Mar; Llorach, Rafael; Urpi-Sarda, Mireia; Jáuregui, Olga; Corella, Dolores; Ruiz-Canela, Miguel; Salas-Salvadó, Jordi; Fitó, Montserrat; Ros, Emilio; Estruch, Ramon; Andres-Lacueva, Cristina

    2015-02-01

    The aim of the current study was to apply an untargeted metabolomics strategy to characterize a model of cocoa intake biomarkers in a free-living population. An untargeted HPLC-q-ToF-MS based metabolomics approach was applied to human urine from 32 consumers of cocoa or derived products (CC) and 32 matched control subjects with no consumption of cocoa products (NC). The multivariate statistical analysis (OSC-PLS-DA) showed clear differences between CC and NC groups. The discriminant biomarkers identified were mainly related to the metabolic pathways of theobromine and polyphenols, as well as to cocoa processing. Consumption of cocoa products was also associated with reduced urinary excretions of methylglutarylcarnitine, which could be related to effects of cocoa exposure on insulin resistance. To improve the prediction of cocoa consumption, a combined urinary metabolite model was constructed. ROC curves were performed to evaluate the model and individual metabolites. The AUC values (95% CI) for the model were 95.7% (89.8-100%) and 92.6% (81.9-100%) in training and validation sets, respectively, whereas the AUCs for individual metabolites were cocoa consumption in free-living subjects reveals that combining different metabolites as biomarker models improves prediction of dietary exposure to cocoa. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  15. Metabolomic and high-throughput sequencing analysis—modern approach for the assessment of biodeterioration of materials from historic buildings

    Science.gov (United States)

    Gutarowska, Beata; Celikkol-Aydin, Sukriye; Bonifay, Vincent; Otlewska, Anna; Aydin, Egemen; Oldham, Athenia L.; Brauer, Jonathan I.; Duncan, Kathleen E.; Adamiak, Justyna; Sunner, Jan A.; Beech, Iwona B.

    2015-01-01

    Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar, and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II–Birkenau concentration and extermination camp in Oświecim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM), metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and nine fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus, and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of microbial

  16. Metabolomic and high-throughput sequencing analysis – modern approach for the assessment of biodeterioration of materials from historic buildings

    Directory of Open Access Journals (Sweden)

    Beata eGutarowska

    2015-09-01

    Full Text Available Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświęcim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM, metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and 9 fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of

  17. Metabolomic and high-throughput sequencing analysis-modern approach for the assessment of biodeterioration of materials from historic buildings.

    Science.gov (United States)

    Gutarowska, Beata; Celikkol-Aydin, Sukriye; Bonifay, Vincent; Otlewska, Anna; Aydin, Egemen; Oldham, Athenia L; Brauer, Jonathan I; Duncan, Kathleen E; Adamiak, Justyna; Sunner, Jan A; Beech, Iwona B

    2015-01-01

    Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar, and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświecim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM), metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and nine fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus, and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of microbial communities

  18. Metabolomics: beyond biomarkers and towards mechanisms

    Science.gov (United States)

    Johnson, Caroline H.; Ivanisevic, Julijana; Siuzdak, Gary

    2017-01-01

    Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases. PMID:26979502

  19. DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

    Science.gov (United States)

    Herrera, I.; Herrera, G. S.

    2015-12-01

    Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

  20. A novel highly parallel algorithm for linearly unmixing hyperspectral images

    Science.gov (United States)

    Guerra, Raúl; López, Sebastián.; Callico, Gustavo M.; López, Jose F.; Sarmiento, Roberto

    2014-10-01

    Endmember extraction and abundances calculation represent critical steps within the process of linearly unmixing a given hyperspectral image because of two main reasons. The first one is due to the need of computing a set of accurate endmembers in order to further obtain confident abundance maps. The second one refers to the huge amount of operations involved in these time-consuming processes. This work proposes an algorithm to estimate the endmembers of a hyperspectral image under analysis and its abundances at the same time. The main advantage of this algorithm is its high parallelization degree and the mathematical simplicity of the operations implemented. This algorithm estimates the endmembers as virtual pixels. In particular, the proposed algorithm performs the descent gradient method to iteratively refine the endmembers and the abundances, reducing the mean square error, according with the linear unmixing model. Some mathematical restrictions must be added so the method converges in a unique and realistic solution. According with the algorithm nature, these restrictions can be easily implemented. The results obtained with synthetic images demonstrate the well behavior of the algorithm proposed. Moreover, the results obtained with the well-known Cuprite dataset also corroborate the benefits of our proposal.

  1. Highly parallel translation of DNA sequences into small molecules.

    Directory of Open Access Journals (Sweden)

    Rebecca M Weisinger

    Full Text Available A large body of in vitro evolution work establishes the utility of biopolymer libraries comprising 10(10 to 10(15 distinct molecules for the discovery of nanomolar-affinity ligands to proteins. Small-molecule libraries of comparable complexity will likely provide nanomolar-affinity small-molecule ligands. Unlike biopolymers, small molecules can offer the advantages of cell permeability, low immunogenicity, metabolic stability, rapid diffusion and inexpensive mass production. It is thought that such desirable in vivo behavior is correlated with the physical properties of small molecules, specifically a limited number of hydrogen bond donors and acceptors, a defined range of hydrophobicity, and most importantly, molecular weights less than 500 Daltons. Creating a collection of 10(10 to 10(15 small molecules that meet these criteria requires the use of hundreds to thousands of diversity elements per step in a combinatorial synthesis of three to five steps. With this goal in mind, we have reported a set of mesofluidic devices that enable DNA-programmed combinatorial chemistry in a highly parallel 384-well plate format. Here, we demonstrate that these devices can translate DNA genes encoding 384 diversity elements per coding position into corresponding small-molecule gene products. This robust and efficient procedure yields small molecule-DNA conjugates suitable for in vitro evolution experiments.

  2. Highly parallel line-based image coding for many cores.

    Science.gov (United States)

    Peng, Xiulian; Xu, Jizheng; Zhou, You; Wu, Feng

    2012-01-01

    Computers are developing along with a new trend from the dual-core and quad-core processors to ones with tens or even hundreds of cores. Multimedia, as one of the most important applications in computers, has an urgent need to design parallel coding algorithms for compression. Taking intraframe/image coding as a start point, this paper proposes a pure line-by-line coding scheme (LBLC) to meet the need. In LBLC, an input image is processed line by line sequentially, and each line is divided into small fixed-length segments. The compression of all segments from prediction to entropy coding is completely independent and concurrent at many cores. Results on a general-purpose computer show that our scheme can get a 13.9 times speedup with 15 cores at the encoder and a 10.3 times speedup at the decoder. Ideally, such near-linear speeding relation with the number of cores can be kept for more than 100 cores. In addition to the high parallelism, the proposed scheme can perform comparatively or even better than the H.264 high profile above middle bit rates. At near-lossless coding, it outperforms H.264 more than 10 dB. At lossless coding, up to 14% bit-rate reduction is observed compared with H.264 lossless coding at the high 4:4:4 profile.

  3. Probabilistic Principal Component Analysis for Metabolomic Data.

    LENUS (Irish Health Repository)

    Nyamundanda, Gift

    2010-11-23

    Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

  4. Informatics for Metabolomics.

    Science.gov (United States)

    Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

    2016-01-01

    Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

  5. An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry.

    Science.gov (United States)

    Wang, Yang; Liu, Fang; Li, Peng; He, Chengwei; Wang, Ruibing; Su, Huanxing; Wan, Jian-Bo

    2016-07-13

    Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Vitamins, metabolomics, and prostate cancer.

    Science.gov (United States)

    Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

    2017-06-01

    How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms through which vitamins influence prostate cancer risk. Prostate cancer risk data related to vitamins E, A, and D and metabolomic profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have had mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomic profiling of fasting serum collected 1-20 years prior to clinical diagnoses found reduced lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with lower risk of aggressive disease. Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study.

  7. Metabolomics to study functional consequences in peroxisomal disorders

    NARCIS (Netherlands)

    Herzog, K.

    2017-01-01

    This thesis focusses on metabolomics approaches performed in cultured cells and blood samples from patients with peroxisomal disorders. By applying both targeted and untargeted metabolomics, the aim of these approaches was to study the functional consequences of the primary genetic defects causing

  8. Metabolomics and Epidemiology Working Group

    Science.gov (United States)

    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  9. A metabolomics approach to evaluate the effects of shiitake mushroom (Lentinula edodes) treatment in undernourished young rats

    International Nuclear Information System (INIS)

    Molz, Patrícia; Ellwanger, Joel Henrique; Eliete Iochims dos Santos, Carla; Dias, Johnny Ferraz; Campos, Deivis de; Corbellini, Valeriano Antonio; Prá, Daniel; Putzke, Marisa Terezinha Lopes; Franke, Silvia Isabel Rech

    2014-01-01

    Undernourishment is characterized by a decrease of the metabolic rate as a result of lack of nutrients important to life. Shiitake mushroom (Lentinula edodes) can be an alternative to reverse undernourishment. The aim of this study was to explore the metabolic changes and consequent elemental concentrations found in undernourished rats and undernourished rats treated with shiitake mushroom (n = 12 rats each group). To determine the elemental concentration, blood samples were analyzed by Particle Induced X-ray Emission (PIXE). For metabolomics, blood samples were tested under Fourier Transform Infrared Spectroscopy (FT-IR). The results indicated that the supplementation with shiitake mushroom in undernourished rats altered the composition of blood proteins, elements and volume. Several strong correlations were observed between the elemental concentrations and metabolic parameters

  10. A metabolomics approach to evaluate the effects of shiitake mushroom (Lentinula edodes) treatment in undernourished young rats

    Energy Technology Data Exchange (ETDEWEB)

    Molz, Patrícia [Nutrition Course, Department of Physical Education and Health, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Graduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Ellwanger, Joel Henrique [Biological Sciences Course, Department of Biology and Pharmacy, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Eliete Iochims dos Santos, Carla; Dias, Johnny Ferraz [Ion Implantation Laboratory, Physics Institute, Federal University of Rio Grande do Sul, Porto Alegre, RS (Brazil); Campos, Deivis de [Biological Sciences Course, Department of Biology and Pharmacy, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Corbellini, Valeriano Antonio [Graduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Prá, Daniel [Graduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Biological Sciences Course, Department of Biology and Pharmacy, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Putzke, Marisa Terezinha Lopes [Biological Sciences Course, Department of Biology and Pharmacy, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Franke, Silvia Isabel Rech, E-mail: silviafr@unisc.br [Nutrition Course, Department of Physical Education and Health, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil); Graduate Program in Health Promotion, University of Santa Cruz do Sul, Santa Cruz do Sul, RS (Brazil)

    2014-01-01

    Undernourishment is characterized by a decrease of the metabolic rate as a result of lack of nutrients important to life. Shiitake mushroom (Lentinula edodes) can be an alternative to reverse undernourishment. The aim of this study was to explore the metabolic changes and consequent elemental concentrations found in undernourished rats and undernourished rats treated with shiitake mushroom (n = 12 rats each group). To determine the elemental concentration, blood samples were analyzed by Particle Induced X-ray Emission (PIXE). For metabolomics, blood samples were tested under Fourier Transform Infrared Spectroscopy (FT-IR). The results indicated that the supplementation with shiitake mushroom in undernourished rats altered the composition of blood proteins, elements and volume. Several strong correlations were observed between the elemental concentrations and metabolic parameters.

  11. Rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry-based metabolomics approach to study the effects of jieduquyuziyin prescription on systemic lupus erythematosus.

    Science.gov (United States)

    Ding, Xinghong; Hu, Jinbo; Wen, Chengping; Ding, Zhishan; Yao, Li; Fan, Yongsheng

    2014-01-01

    Jieduquyuziyin prescription (JP), a traditional Chinese medicine (TCM) prescription, has been widely used for the clinical treatment of systemic lupus erythematosus (SLE). However, the complex chemical constituents of JP and the multifactorial pathogenesis of SLE make research on the therapeutic mechanism of JP in SLE challenging. In this paper, a serum metabolomics approach based on rapid resolution liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (RRLC-Q-TOF/MS) was employed to acquire the metabolic characteristics of serum samples obtained from mice in the SLE model group, JP-treated group, prednisone acetate (PA)-treated group and control group. The orthogonal partial least squares (OPLS) was applied to recognize metabolic patterns, and an obvious separation of groups was obtained. Thirteen metabolites, namely, phosphatidylethanolamine (PE 20:3), hepoxilin B3, lyso- phosphatidylethanolamine (lyso-PE 22:6), 12S-hydroxypentaenoic acid (12S-HEPE), traumatic acid, serotonin, platelet-activating factor (PAF), phosphatidylcholine (PC 20:5),eicosapentaenoic acid (EPA), 12(S)-hydroxyei- cosatetraenoic acid (12S-HETE), 14-hydroxy docosahexaenoic acid (14-HDOHE), lyso-phosphatidylcholine (lyso-PC 20:4), and indole acetaldehyde, were identified and characterized as differential metabolites involved in the pathogenesis of SLE. After treatment with JP, the relative content of 12(S)-HETE, PAF, 12(S)-HEPE, EPA, PE (20:3), Lyso-PE(22:6), and 14-HDOHE were effectively regulated, which suggested that the therapeutic effects of JP on SLE may involve regulating disturbances to the metabolism of unsaturated fatty acid, tryptophan and phospholipid. This research also demonstrated that metabolomics is a powerful tool for researching complex disease mechanisms and evaluating the mechanism of action of TCM.

  12. Digging Deeper: Development and evaluation of an untargeted metabolomics approach to identify biogeochemical hotspots with depth and by vegetation type in Arctic tundra soils

    Science.gov (United States)

    Ladd, M.; Wullschleger, S.; Hettich, R.

    2017-12-01

    Elucidating the chemical composition of low molecular weight (LMW) dissolved organic matter (DOM), and monitoring how this bioavailable pool varies over space and time, is critical to understanding the controlling mechanisms that underlie carbon release and storage in Arctic systems. Due to analytical challenges however, relatively little is known about how this complex mixture of small molecules varies with soil depth or how it may be influenced by vegetation. In this study, we evaluated an untargeted metabolomics approach for the characterization of LMW DOM in water extracts, and applied this approach in soil cores (10-cm diam., 30-cm depth), obtained near Barrow, Alaska (71° 16' N) from the organic-rich active layer where the aboveground vegetation was primarily either Carex aquatilis or Eriophorum angustifolium, two species commonly found in tundra systems. We hypothesized that by using a discovery-based approach, spatial patterns of chemical diversity could be identified, enabling the detection of biogeochemical hotspots across scales. LMW DOM profiles from triplicate water extracts were characterized using dual-separation, nano-liquid chromatography (LC) coupled to an electrospray Orbitrap mass spectrometer in positive and negative ion modes. Both LC separations—reversed-phase and hydrophilic interaction chromatography—were achieved with gradient elutions in 15 minutes. Using a precursor and fragment mass measurement accuracy of nutrients) impact carbon fluxes in the Arctic at the landscape-scale.

  13. The acute impact of polyphenols from Hibiscus sabdariffa in metabolic homeostasis: an approach combining metabolomics and gene-expression analyses.

    Science.gov (United States)

    Beltrán-Debón, Raúl; Rodríguez-Gallego, Esther; Fernández-Arroyo, Salvador; Senan-Campos, Oriol; Massucci, Francesco A; Hernández-Aguilera, Anna; Sales-Pardo, Marta; Guimerà, Roger; Camps, Jordi; Menendez, Javier A; Joven, Jorge

    2015-09-01

    We explored the acute multifunctional effects of polyphenols from Hibiscus sabdariffa in humans to assess possible consequences on the host's health. The expected dynamic response was studied using a combination of transcriptomics and metabolomics to integrate specific functional pathways through network-based methods and to generate hypotheses established by acute metabolic effects and/or modifications in the expression of relevant genes. Data were obtained from healthy male volunteers after 3 hours of ingestion of an aqueous Hibiscus sabdariffa extract. The data were compared with data obtained prior to the ingestion, and the overall findings suggest that these particular polyphenols had a simultaneous role in mitochondrial function, energy homeostasis and protection of the cardiovascular system. These findings suggest beneficial actions in inflammation, endothelial dysfunction, and oxidation, which are interrelated mechanisms. Among other effects, the activation of the heme oxygenase-biliverdin reductase axis, the systemic inhibition of the renin-angiotensin system, the inhibition of the angiotensin-converting enzyme, and several actions mirroring those of the peroxisome proliferator-activated receptor agonists further support this notion. We also found concordant findings in the serum of the participants, which include a decrease in cortisol levels and a significant increase in the active vasodilator metabolite of bradykinin (des-Arg(9)-bradykinin). Therefore, our data support the view that polyphenols from Hibiscus sabdariffa play a regulatory role in metabolic health and in the maintenance of blood pressure, thus implying a multi-faceted impact in metabolic and cardiovascular diseases.

  14. Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach

    Energy Technology Data Exchange (ETDEWEB)

    2016-10-18

    The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 1H-NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.

  15. Celiac Disease Genomic, Environmental, Microbiome, and Metabolomic (CDGEMM Study Design: Approach to the Future of Personalized Prevention of Celiac Disease

    Directory of Open Access Journals (Sweden)

    Maureen M. Leonard

    2015-11-01

    Full Text Available In the past it was believed that genetic predisposition and exposure to gluten were necessary and sufficient to develop celiac disease (CD. Recent studies however suggest that loss of gluten tolerance can occur at any time in life as a consequence of other environmental stimuli. Many environmental factors known to influence the composition of the intestinal microbiota are also suggested to play a role in the development of CD. These include birthing delivery mode, infant feeding, and antibiotic use. To date no large-scale longitudinal studies have defined if and how gut microbiota composition and metabolomic profiles may influence the loss of gluten tolerance and subsequent onset of CD in genetically-susceptible individuals. Here we describe a prospective, multicenter, longitudinal study of infants at risk for CD which will employ a blend of basic and applied studies to yield fundamental insights into the role of the gut microbiome as an additional factor that may play a key role in early steps involved in the onset of autoimmune disease.

  16. Metabolic regulation of trisporic acid on Blakeslea trispora revealed by a GC-MS-based metabolomic approach.

    Directory of Open Access Journals (Sweden)

    Jie Sun

    Full Text Available The zygomycete Blakeslea trispora is used commercially as natural source of â-carotene. Trisporic acid (TA is secreted from the mycelium of B. trispora during mating between heterothallic strains and is considered as a mediator of the regulation of mating processes and an enhancer of carotene biosynthesis. Gas chromatography-mass spectrometry and multivariate analysis were employed to investigate TA-associated intracellular biochemical changes in B. trispora. By principal component analysis, the differential metabolites discriminating the control groups from the TA-treated groups were found, which were also confirmed by the subsequent hierarchical cluster analysis. The results indicate that TA is a global regulator and its main effects at the metabolic level are reflected on the content changes in several fatty acids, carbohydrates, and amino acids. The carbon metabolism and fatty acids synthesis are sensitive to TA addition. Glycerol, glutamine, and ã-aminobutyrate might play important roles in the regulation of TA. Complemented by two-dimensional electrophoresis, the results indicate that the actions of TA at the metabolic level involve multiple metabolic processes, such as glycolysis and the bypass of the classical tricarboxylic acid cycle. These results reveal that the metabolomics strategy is a powerful tool to gain insight into the mechanism of a microorganism's cellular response to signal inducers at the metabolic level.

  17. A proteomic and metabolomic approach for understanding the role of the flor yeast mitochondria in the velum formation.

    Science.gov (United States)

    Moreno-García, Jaime; García-Martínez, Teresa; Moreno, Juan; Millán, M Carmen; Mauricio, Juan Carlos

    2014-02-17

    Saccharomyces cerevisiae "flor" yeast shows a strong tolerance to high ethanol concentrations and develops a velum (biofilm) on the wine surface after the alcoholic fermentation of grape must. This velum remains along several years during the so called "biological aging" process in the elaboration of some special wines carried out in specific regions around the world and it contributes to the typical organoleptic characteristics of these wines. In order to grow in this condition, flor yeast has to elaborate a response where the mitochondrial function is essential. The objective of this study is to elucidate the role of the mitochondria in the response of a flor yeast, S. cerevisiae G1, growing in a controlled velum formation condition. For this purpose, proteome and metabolome were characterized by comparing data with those from an initial fermentative condition used as reference. The obtained proteomic profiles show more mitochondrial proteins related with the ethanol resistance (13), cell respiration (18), mitochondrial genome maintenance (13), and apoptosis (2) detected under the velum formation condition. Also, the finger-printing obtained by means of the exo-metabolites directly related with the quality of fermented beverages and quantified in the velum condition shows important differences from those obtained in the reference condition. Copyright © 2013 Elsevier B.V. All rights reserved.

  18. Systematic Applications of Metabolomics in Metabolic Engineering

    Directory of Open Access Journals (Sweden)

    Robert A. Dromms

    2012-12-01

    Full Text Available The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

  19. Metabolomics investigation of whey intake

    DEFF Research Database (Denmark)

    Stanstrup, Jan

    syndrome are complex disorders and are not caused by a high-calorie diet and low exercise level alone. The specific nature of the nutrients, independent of their caloric value, also play a role. The question is which. In the quest to answer this question the qualitative intake of protein is of special...... and prevention of the metabolic syndrome related to obesity and diabetes. In this thesis the effects of whey intake on the human metabolome was investigated using a metabolomics approach. We demonstrated that intake of whey causes a decreased rate of gastric emptying compared to other protein sources....... Therefore this thesis will also present and discuss state-of-the-art tools for computer-assisted compound identification, including: annotation of adducts and fragments, determination of the molecular ion, in silico fragmentation, retention time mapping between analytical systems and de novo retention time...

  20. Metabolomics: A Primer.

    Science.gov (United States)

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

    Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    International Nuclear Information System (INIS)

    Kumar, Bhowmik Salil; Lee, Young-Joo; Yi, Hong Jae; Chung, Bong Chul; Jung, Byung Hwa

    2010-01-01

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg -1 day -1 or 250 mg kg -1 day -1 for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  2. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: jbhluck@kist.re.kr [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)

    2010-02-19

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  3. An NMR-based metabolomic approach to investigate the effects of supplementation with glutamic acid in piglets challenged with deoxynivalenol.

    Science.gov (United States)

    Wu, Miaomiao; Xiao, Hao; Ren, Wenkai; Yin, Jie; Hu, Jiayu; Duan, Jielin; Liu, Gang; Tan, Bie; Xiong, Xia; Oso, Abimbola Oladele; Adeola, Olayiwola; Yao, Kang; Yin, Yulong; Li, Tiejun

    2014-01-01

    Deoxynivalenol (DON) has various toxicological effects in humans and pigs that result from the ingestion of contaminated cereal products. This study was conducted to investigate the protective effects of dietary supplementation with glutamic acid on piglets challenged with DON. A total of 20 piglets weaned at 28 d of age were randomly assigned to receive 1 of 4 treatments (5 piglets/treatment): 1) basal diet, negative control (NC); 2) basal diet +4 mg/kg DON (DON); 3) basal diet +2% (g/g) glutamic acid (GLU); 4) basal diet +4 mg/kg DON +2% glutamic acid (DG). A 7-d adaptation period was followed by 30 days of treatment. A metabolite analysis using nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomic technology and the determination of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities for plasma, as well as the activity of Caspase-3 and the proliferation of epithelial cells were conducted. The results showed that contents of low-density lipoprotein, alanine, arginine, acetate, glycoprotein, trimethylamine-N-oxide (TMAO), glycine, lactate, and urea, as well as the glutamate/creatinine ratio were higher but high-density lipoprotein, proline, citrate, choline, unsaturated lipids and fumarate were lower in piglets of DON treatment than that of NC treatment (Pglutamic acid increased the plasma concentrations of proline, citrate, creatinine, unsaturated lipids, and fumarate, and decreased the concentrations of alanine, glycoprotein, TMAO, glycine, and lactate, as well as the glutamate/creatinine ratio (Pglutamic acid to DON treatment increased the plasma activities of SOD and GSH-Px and the proliferating cell nuclear antigen (PCNA) labeling indexes for the jejunum and ileum (Pglutamic acid has the potential to repair the injuries associated with oxidative stress as well as the disturbances of energy and amino acid metabolism induced by DON.

  4. An Untargeted Metabolomics Approach to Characterize Short-Term and Long-Term Metabolic Changes after Bariatric Surgery.

    Directory of Open Access Journals (Sweden)

    Sophie H Narath

    Full Text Available Bariatric surgery is currently one of the most effective treatments for obesity and leads to significant weight reduction, improved cardiovascular risk factors and overall survival in treated patients. To date, most studies focused on short-term effects of bariatric surgery on the metabolic profile and found high variation in the individual responses to surgery. The aim of this study was to identify relevant metabolic changes not only shortly after bariatric surgery (Roux-en-Y gastric bypass but also up to one year after the intervention by using untargeted metabolomics. 132 serum samples taken from 44 patients before surgery, after hospital discharge (1-3 weeks after surgery and at a 1-year follow-up during a prospective study (NCT01271062 performed at two study centers (Austria and Switzerland. The samples included 24 patients with type 2 diabetes at baseline, thereof 9 with diabetes remission after one year. The samples were analyzed by using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS, HILIC-QExactive. Raw data was processed with XCMS and drift-corrected through quantile regression based on quality controls. 177 relevant metabolic features were selected through Random Forests and univariate testing and 36 metabolites were identified. Identified metabolites included trimethylamine-N-oxide, alanine, phenylalanine and indoxyl-sulfate which are known markers for cardiovascular risk. In addition we found a significant decrease in alanine after one year in the group of patients with diabetes remission relative to non-remission. Our analysis highlights the importance of assessing multiple points in time in subjects undergoing bariatric surgery to enable the identification of biomarkers for treatment response, cardiovascular benefit and diabetes remission. Key-findings include different trend pattern over time for various metabolites and demonstrated that short term changes should not necessarily be used to identify

  5. [Mechanism of treatment effect of Huanglian-Huangqin herb pairs on cerebral ischemia rats based on metabolomic approach].

    Science.gov (United States)

    Cao, Hui-Ting; Zhu, Hua-Xu; Zhang, Qi-Chun; Guo, Li-Wei

    2017-06-01

    The metabolic effect of Huanglian-Huangqin herb pairs on cerebral ischemia rats was studied by using metabolomic method. The rat model of ischemia reperfusion injury induced by introduction of transient middle cerebral artery occlusion (MCAO) followed by reperfusion. Ultra high performance liquid chromatography-series four pole time of flight mass spectrometry method(UPLC-Q-TOF/MS), Markerlynx software, and principal component analysis and partial least-squares discriminant analysis were used to analyze the different endogenous metabolites among the urine samples of sham rats, cerebral ischemia model rats, Huanglian groups (HL), Huangqin groups (HQ) and Huanglian-Huangqin herb pairs groups (LQ) was achieved, combined with accurate information about the endogenous metabolites level and secondary fragment ions, retrieval and identification of possible biological markers, metabolic pathway which build in MetPA database. The 20 potential biomarkers were found in the urine of rats with cerebral ischemia, which mainly involved in the neurotransmitter regulation, amino acid metabolism, energy metabolism, lipid metabolism and so on. Those metabolic pathways were disturbed in cerebral ischemia model rats, the principal component analysis showed that the normal and cerebral ischemia model is clearly distinguished, and the compound can be given to the normal state of change after HL, HQ, LQ administration. This study index the interpretation of cerebral ischemia rat metabolism group and mechanism, the embodiment of metabonomics can reflect the physiological and metabolic state, which can better reflect the traditional Chinese medicine as a whole view, system view and the features of multi ingredient synergistic or antagonistic effects. Copyright© by the Chinese Pharmaceutical Association.

  6. Tools for the functional interpretation of metabolomic experiments.

    Science.gov (United States)

    Chagoyen, Monica; Pazos, Florencio

    2013-11-01

    The so-called 'omics' approaches used in modern biology aim at massively characterizing the molecular repertories of living systems at different levels. Metabolomics is one of the last additions to the 'omics' family and it deals with the characterization of the set of metabolites in a given biological system. As metabolomic techniques become more massive and allow characterizing larger sets of metabolites, automatic methods for analyzing these sets in order to obtain meaningful biological information are required. Only recently the first tools specifically designed for this task in metabolomics appeared. They are based on approaches previously used in transcriptomics and other 'omics', such as annotation enrichment analysis. These, together with generic tools for metabolic analysis and visualization not specifically designed for metabolomics will for sure be in the toolbox of the researches doing metabolomic experiments in the near future.

  7. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    Science.gov (United States)

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-12-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

  8. An Investigation into the Antiobesity Effects of Morinda citrifolia L. Leaf Extract in High Fat Diet Induced Obese Rats Using a 1H NMR Metabolomics Approach

    Science.gov (United States)

    Gooda Sahib Jambocus, Najla; Saari, Nazamid; Ismail, Amin; Mahomoodally, Mohamad Fawzi; Abdul Hamid, Azizah

    2016-01-01

    The prevalence of obesity is increasing worldwide, with high fat diet (HFD) as one of the main contributing factors. Obesity increases the predisposition to other diseases such as diabetes through various metabolic pathways. Limited availability of antiobesity drugs and the popularity of complementary medicine have encouraged research in finding phytochemical strategies to this multifaceted disease. HFD induced obese Sprague-Dawley rats were treated with an extract of Morinda citrifolia L. leaves (MLE 60). After 9 weeks of treatment, positive effects were observed on adiposity, fecal fat content, plasma lipids, and insulin and leptin levels. The inducement of obesity and treatment with MLE 60 on metabolic alterations were then further elucidated using a 1H NMR based metabolomics approach. Discriminating metabolites involved were products of various metabolic pathways, including glucose metabolism and TCA cycle (lactate, 2-oxoglutarate, citrate, succinate, pyruvate, and acetate), amino acid metabolism (alanine, 2-hydroxybutyrate), choline metabolism (betaine), creatinine metabolism (creatinine), and gut microbiome metabolism (hippurate, phenylacetylglycine, dimethylamine, and trigonelline). Treatment with MLE 60 resulted in significant improvement in the metabolic perturbations caused obesity as demonstrated by the proximity of the treated group to the normal group in the OPLS-DA score plot and the change in trajectory movement of the diseased group towards the healthy group upon treatment. PMID:26798649

  9. An Investigation into the Antiobesity Effects of Morinda citrifolia L. Leaf Extract in High Fat Diet Induced Obese Rats Using a 1H NMR Metabolomics Approach

    Directory of Open Access Journals (Sweden)

    Najla Gooda Sahib Jambocus

    2016-01-01

    Full Text Available The prevalence of obesity is increasing worldwide, with high fat diet (HFD as one of the main contributing factors. Obesity increases the predisposition to other diseases such as diabetes through various metabolic pathways. Limited availability of antiobesity drugs and the popularity of complementary medicine have encouraged research in finding phytochemical strategies to this multifaceted disease. HFD induced obese Sprague-Dawley rats were treated with an extract of Morinda citrifolia L. leaves (MLE 60. After 9 weeks of treatment, positive effects were observed on adiposity, fecal fat content, plasma lipids, and insulin and leptin levels. The inducement of obesity and treatment with MLE 60 on metabolic alterations were then further elucidated using a 1H NMR based metabolomics approach. Discriminating metabolites involved were products of various metabolic pathways, including glucose metabolism and TCA cycle (lactate, 2-oxoglutarate, citrate, succinate, pyruvate, and acetate, amino acid metabolism (alanine, 2-hydroxybutyrate, choline metabolism (betaine, creatinine metabolism (creatinine, and gut microbiome metabolism (hippurate, phenylacetylglycine, dimethylamine, and trigonelline. Treatment with MLE 60 resulted in significant improvement in the metabolic perturbations caused obesity as demonstrated by the proximity of the treated group to the normal group in the OPLS-DA score plot and the change in trajectory movement of the diseased group towards the healthy group upon treatment.

  10. A QC approach to the determination of day-to-day reproducibility and robustness of LC-MS methods for global metabolite profiling in metabonomics/metabolomics.

    Science.gov (United States)

    Gika, Helen G; Theodoridis, Georgios A; Earll, Mark; Wilson, Ian D

    2012-09-01

    An approach to the determination of day-to-day analytical robustness of LC-MS-based methods for global metabolic profiling using a pooled QC sample is presented for the evaluation of metabonomic/metabolomic data. A set of 60 urine samples were repeatedly analyzed on five different days and the day-to-day reproducibility of the data obtained was determined. Multivariate statistical analysis was performed with the aim of evaluating variability and selected peaks were assessed and validated in terms of retention time stability, mass accuracy and intensity. The methodology enables the repeatability/reproducibility of extended analytical runs in large-scale studies to be determined, allowing the elimination of analytical (as opposed to biological) variability, in order to discover true patterns and correlations within the data. The day-to-day variability of the data revealed by this process suggested that, for this particular system, 3 days continuous operation was possible without the need for maintenance and cleaning. Variation was generally based on signal intensity changes over the 7-day period of the study, and was mainly a result of source contamination.

  11. Toxicological effects of benzo(a)pyrene, DDT and their mixture on the green mussel Perna viridis revealed by proteomic and metabolomic approaches.

    Science.gov (United States)

    Song, Qinqin; Chen, Hao; Li, Yuhu; Zhou, Hailong; Han, Qian; Diao, Xiaoping

    2016-02-01

    Benzo(a)pyrene (BaP) and dichlorodiphenyltrichloroethane (DDT) are persistent organic pollutants and environmental estrogens (EEs) with known toxicity towards the green mussel, Perna viridis. In this study, the toxic effects of BaP (10 µg/L) and DDT (10 µg/L) and their mixture were assessed in green mussel gills with proteomic and metabolomic approaches. Metabolic responses indicated that BaP mainly caused disturbance in osmotic regulation by significantly decrease in branched chain amino acids, dimethylamine and dimethylglycine in gills of male green mussels after exposure for 7 days. DDT mainly caused disturbance in osmotic regulation and energy metabolism by differential alteration of betaine, dimethylamine, dimethylglycine, amino acids, and succinate in gills of male green mussels. However, the mixture of BaP and DDT didn't show obvious metabolite changes. Proteomic analysis showed different protein expression profiles between different treatment groups, which demonstrated that BaP, DDT and their mixture may have different modes of action. Proteomic responses revealed that BaP induced cell apoptosis, disturbance in protein digestion and energy metabolism in gills of green mussels, whereas DDT exposure altered proteins that were associated with oxidative stress, cytoskeleton and cell structure, protein digestion and energy metabolism. However, the mixture of BaP and DDT affected proteins related to the oxidative stress, cytoskeleton and cell structure, protein biosynthesis and modification, energy metabolism, growth and apoptosis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Learning to classify organic and conventional wheat - a machine-learning driven approach using the MeltDB 2.0 metabolomics analysis platform

    Directory of Open Access Journals (Sweden)

    Nikolas eKessler

    2015-03-01

    Full Text Available We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be either from conventionally grown or from organically grown samples and considering different cultivars. The motivation of our work is rather obvious on the background of nowadays increased demand for organic food in post-industrialized societies and the necessity to prove organic food authenticity. The background of our data set is given by up to eleven wheat cultivars that have been cultivated in both farming systems, organic and conventional, throughout three years. More than 300 GC-MS measurements were recorded and subsequently processed and analyzed in the MeltDB 2.0 metabolomics analysis platform, being briefly outlined in this paper. We further describe how unsupervised (t-SNE, PCA and supervised (RF, SVM methods can be applied for sample visualization and classification. Our results clearly show that years have most and wheat cultivars have second-most influence on the metabolic composition of a sample. We can also show, that for a given year and cultivar, organic and conventional cultivation can be distinguished by machine-learning algorithms.

  13. Application of Metabolomics in Thyroid Cancer Research

    Directory of Open Access Journals (Sweden)

    Anna Wojakowska

    2015-01-01

    Full Text Available Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

  14. The Human Serum Metabolome

    Science.gov (United States)

    Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

    2011-01-01

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

  15. Metabolomics in plants and humans: applications in the prevention and diagnosis of diseases.

    Science.gov (United States)

    Gomez-Casati, Diego F; Zanor, Maria I; Busi, María V

    2013-01-01

    In the recent years, there has been an increase in the number of metabolomic approaches used, in parallel with proteomic and functional genomic studies. The wide variety of chemical types of metabolites available has also accelerated the use of different techniques in the investigation of the metabolome. At present, metabolomics is applied to investigate several human diseases, to improve their diagnosis and prevention, and to design better therapeutic strategies. In addition, metabolomic studies are also being carried out in areas such as toxicology and pharmacology, crop breeding, and plant biotechnology. In this review, we emphasize the use and application of metabolomics in human diseases and plant research to improve human health.

  16. A novel approach to the simultaneous extraction and non-targeted analysis of the small molecules metabolome and lipidome using 96-well solid phase extraction plates with column-switching technology.

    Science.gov (United States)

    Li, Yubo; Zhang, Zhenzhu; Liu, Xinyu; Li, Aizhu; Hou, Zhiguo; Wang, Yuming; Zhang, Yanjun

    2015-08-28

    This study combines solid phase extraction (SPE) using 96-well plates with column-switching technology to construct a rapid and high-throughput method for the simultaneous extraction and non-targeted analysis of small molecules metabolome and lipidome based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry. This study first investigated the columns and analytical conditions for small molecules metabolome and lipidome, separated by an HSS T3 and BEH C18 columns, respectively. Next, the loading capacity and actuation duration of SPE were further optimized. Subsequently, SPE and column switching were used together to rapidly and comprehensively analyze the biological samples. The experimental results showed that the new analytical procedure had good precision and maintained sample stability (RSDmetabolome and lipidome to test the throughput. The resulting method represents a new analytical approach for biological samples, and a highly useful tool for researches in metabolomics and lipidomics. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

    Science.gov (United States)

    Miller, Marion G

    2007-02-01

    Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

  18. Linking metabolomics data to underlying metabolic regulation

    Directory of Open Access Journals (Sweden)

    Thomas eNägele

    2014-11-01

    Full Text Available The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology.Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g. LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms.Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets.Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification.Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization.As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which-if deciphered correctly-provides comprehensive insight into a metabolic system.Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation.Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of

  19. Metabolomic studies in pulmonology

    Directory of Open Access Journals (Sweden)

    R. R. Furina

    2015-01-01

    Full Text Available The review shows the results of metabolomic studies in pulmonology. The key idea of metabolomics is to detect specific biomarkers in a biological sample for the diagnosis of diseases of the bronchi and lung. Main methods for the separation and identification of volatile organic substances as biomarkers (gas chromatography, mass spectrometry, and nuclear magnetic resonance spectrometry used in metabolomics are given. A solid-phase microextraction method used to pre-prepare a sample is also covered. The results of laboratory tests for biomarkers for lung cancer, acute respiratory distress syndrome, chronic obstructive pulmonary disease, cystic fibrosis, chronic infections, and pulmonary tuberculosis are presented. In addition, emphasis is placed on the possibilities of metabolomics used in experimental medicine, including to the study of asthma. The information is of interest to both theorists and practitioners.

  20. The food metabolome

    DEFF Research Database (Denmark)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food......The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according...... by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still...

  1. Current metabolomics: technological advances.

    Science.gov (United States)

    Putri, Sastia P; Yamamoto, Shinya; Tsugawa, Hiroshi; Fukusaki, Eiichiro

    2013-07-01

    Metabolomics, the global quantitative assessment of metabolites in a biological system, has played a pivotal role in various fields of science in the post-genomic era. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression, but also form part of the regulatory system in an integrated manner. Therefore, metabolomics is often considered a powerful tool to provide an instantaneous snapshot of the physiology of a cell. The power of metabolomics lies on the acquisition of analytical data in which metabolites in a cellular system are quantified, and the extraction of the most meaningful elements of the data by using various data analysis tool. In this review, we discuss the latest development of analytical techniques and data analyses methods in metabolomics study. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  2. Metabolomics er fremtiden

    DEFF Research Database (Denmark)

    Pedersern, Birger

    2010-01-01

    Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet......Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet...

  3. Quality assurance of metabolomics.

    Science.gov (United States)

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

  4. Metabolomics: Definitions and Significance in Systems Biology.

    Science.gov (United States)

    Klassen, Aline; Faccio, Andréa Tedesco; Canuto, Gisele André Baptista; da Cruz, Pedro Luis Rocha; Ribeiro, Henrique Caracho; Tavares, Marina Franco Maggi; Sussulini, Alessandra

    2017-01-01

    Nowadays, there is a growing interest in deeply understanding biological mechanisms not only at the molecular level (biological components) but also the effects of an ongoing biological process in the organism as a whole (biological functionality), as established by the concept of systems biology. Within this context, metabolomics is one of the most powerful bioanalytical strategies that allow obtaining a picture of the metabolites of an organism in the course of a biological process, being considered as a phenotyping tool. Briefly, metabolomics approach consists in identifying and determining the set of metabolites (or specific metabolites) in biological samples (tissues, cells, fluids, or organisms) under normal conditions in comparison with altered states promoted by disease, drug treatment, dietary intervention, or environmental modulation. The aim of this chapter is to review the fundamentals and definitions used in the metabolomics field, as well as to emphasize its importance in systems biology and clinical studies.

  5. Functional Analysis of Metabolomics Data.

    Science.gov (United States)

    Chagoyen, Mónica; López-Ibáñez, Javier; Pazos, Florencio

    2016-01-01

    Metabolomics aims at characterizing the repertory of small chemical compounds in a biological sample. As it becomes more massive and larger sets of compounds are detected, a functional analysis is required to convert these raw lists of compounds into biological knowledge. The most common way of performing such analysis is "annotation enrichment analysis," also used in transcriptomics and proteomics. This approach extracts the annotations overrepresented in the set of chemical compounds arisen in a given experiment. Here, we describe the protocols for performing such analysis as well as for visualizing a set of compounds in different representations of the metabolic networks, in both cases using free accessible web tools.

  6. Changes in the Metabolome of Picea balfouriana Embryogenic Tissues That Were Linked to Different Levels of 6-BAP by Gas Chromatography-Mass Spectrometry Approach.

    Directory of Open Access Journals (Sweden)

    Q F Li

    Full Text Available Embryogenic cultures of Picea balfouriana, which is an important commercial species for reforestation in Southern China, easily lose their embryogenic ability during long-term culture. Embryogenic tissue that proliferated at lower concentrations (3.6 μM and 2.5 μM of 6-benzylaminopurine (6-BAP were more productive, and generated 113 ± 6 and 89 ± 3 mature embryos per 100 mg embryogenic tissue, respectively. A metabolomic approach was used to study the changes in metabolites linked to embryogenic competence related to three different 6-BAP concentrations (2.5 μM, 3.6 μM, and 5 μM. A total of 309 compounds were obtained, among which 123 metabolites mapped to Kyoto Encyclopedia of Genes and genomes (KEGG pathways. The levels of 35 metabolites were significantly differentially regulated among the three 6-BAP treatments, and 32 metabolites differed between the 2.5 μM and 5 μM treatments. A total of 17 metabolites appeared only once among the three comparisons. The combination of a score plot and a loading plot showed that in the samples with higher embryogenic ability (3.6 μM and 2.5 μM, up-regulated metabolites were mostly amino acids and down-regulated metabolites were mostly primary carbohydrates (especially sugars. These results suggested that 6-BAP may influence embryogenic competence by nitrogen metabolism, which could cause an increase in amino acid levels and higher amounts of aspartate, isoleucine, and leucine in tissues with higher embryogenic ability. Furthermore, we speculated that 6-BAP may affect the amount of tryptophan in tissues, which would change the indole-3-acetic acid levels and influence the embryogenic ability.

  7. Metabolomic NMR fingerprinting: an exploratory and predictive tool

    OpenAIRE

    Lauri, Ilaria

    2014-01-01

    Metabolomics is the comprehensive assessment of low molecular weight organic metabolites within biological system. The identification and characterization of several chemical species, or metabolic fingerprinting, is an emergent approach in metabolomics field that provides a valuable “snapshot” of metabolic profiles. This approach is finding an increasing number of applications in many areas including cancer research, drug discovery and food science. The combined use of NMR spectroscopy, data ...

  8. Nanoparticle-Assisted Metabolomics

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2018-03-01

    Full Text Available Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

  9. Metabolomics in the fight against malaria

    Directory of Open Access Journals (Sweden)

    Jorge L Salinas

    2014-08-01

    Full Text Available Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC, a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

  10. Updates in metabolomics tools and resources: 2014-2015.

    Science.gov (United States)

    Misra, Biswapriya B; van der Hooft, Justin J J

    2016-01-01

    Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Biochemical studies of Piper betle L leaf extract on obese treated animal using 1H-NMR-based metabolomic approach of blood serum samples.

    Science.gov (United States)

    Abdul Ghani, Zuleen Delina Fasya; Husin, Juani Mazmin; Rashid, Ahmad Hazri Ab; Shaari, Khozirah; Chik, Zamri

    2016-12-24

    Piper betle L. (PB) belongs to the Piperaceae family. The presence of a fairly large quantity of diastase in the betel leaf is deemed to play an important role in starch digestion and calls for the study of weight loss activities and metabolite profile from PB leaf extracts using metabolomics approach to be performed. PB dried leaves were extracted with 70% ethanol and the extracts were subjected to five groups of rats fed with high fat (HF) and standard diet (SD). They were then fed with the extracts in two doses and compared with a negative control group given water only according to the study protocol. The body weights and food intakes were monitored every week. At the end of the study, blood serum of the experimental animal was analysed to determine the biochemical and metabolite changes. PB treated group demonstrated inhibition of body weight gain without showing an effect on the food intake. In serum bioassay, the PB treated group (HF/PB (100mg/kg and 500mg/kg) showed an increased in glucose and cholesterol levels compared to the Standard Diet (SD/WTR) group, a decrease in LDL level and increase in HDL level when compared with High Fat Diet (HF/WTR) group. For metabolite analysis, two separation models were made to determine the metabolite changes via group activities. The best separation of PCA serum in Model 1 and 2 was achieved in principle component 1 and principle component 2. SUS-Plot model showed that HF group was characterized by high-level of glucose, glycine and alanine. Increase in the β-hydroxybutyrate level similar with SD group animals was evident in the HF/PB(500mg/kg) group. This finding suggested that the administration of 500mg/kg PB extracts leads to increase in oxidation process in the body thus maintaining the body weight and without giving an effect on the appetite even though HF was continuously consumed by the animals until the end of the studies and also a reduction in food intake, thus maintaining their body weight although they

  12. Metabolic responses of Beauveria bassiana to hydrogen peroxide-induced oxidative stress using an LC-MS-based metabolomics approach.

    Science.gov (United States)

    Zhang, Chen; Wang, Wei; Lu, Ruili; Jin, Song; Chen, Yihui; Fan, Meizhen; Huang, Bo; Li, Zengzhi; Hu, Fenglin

    2016-06-01

    The entomopathogenic fungus, Beauveria bassiana, is commonly used as a biological agent for pest control. Environmental and biological factors expose the fungus to oxidative stress; as a result, B. bassiana has adopted a number of anti-oxidant mechanisms. In this study, we investigated metabolites of B. bassiana that are formed in response to oxidative stress from hydrogen peroxide (H2O2) by using a liquid chromatography mass spectrometry (LC-MS) approach. Partial least-squares discriminant analysis (PLS-DA) revealed differences between the control and the H2O2-treated groups. Hierarchical cluster analysis (HCA) showed 18 up-regulated metabolites and 25 down-regulated metabolites in the H2O2-treated fungus. Pathway analysis indicated that B. bassiana may be able to alleviate oxidative stress by enhancing lipid catabolism and glycometabolism, thus decreasing membrane polarity and preventing polar H2O2 or ROS from permeating into fungal cells and protecting cells against oxidative injury. Meanwhile, most of the unsaturated fatty acids that are derived from glycerophospholipids hydrolysis can convert into oxylipins through autoxidation, which can prevent the reactive oxygen of H2O2 from attacking important macromolecules of the fungus. Results showed also that H2O2 treatment can enhance mycotoxins production which implies that oxidative stress may be able to increase the virulence of the fungus. In comparison to the control group, citric acid and UDP-N-acetylglucosamine were down-regulated, which suggested that metabolic flux was occurring to the TCA cycle and enhancing carbohydrate metabolism. The findings from this study will contribute to the understanding of how the molecular mechanisms of fungus respond to environmental and biological stress factors as well as how the manipulation of such metabolisms may lead to selection of more effective fungal strains for pest control. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach

    OpenAIRE

    Romero-Ibarguengoitia, Maria Elena; Vadillo-Ortega, Felipe; Caballero, Augusto Enrique; Ibarra-González, Isabel; Herrera-Rosas, Arturo; Serratos-Canales, María Fabiola; León-Hernández, Mireya; González-Chávez, Antonio; Mummidi, Srinivas; Duggirala, Ravindranath; López-Alvarenga, Juan Carlos

    2018-01-01

    Background: Structural equation modeling (SEM) can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD), family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1) If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines woul...

  14. Circadian Metabolomics in Time and Space

    Directory of Open Access Journals (Sweden)

    Kenneth A. Dyar

    2017-07-01

    Full Text Available Circadian rhythms are widely known to govern human health and disease, but specific pathogenic mechanisms linking circadian disruption to metabolic diseases are just beginning to come to light. This is thanks in part to the development and application of various “omics”-based tools in biology and medicine. Current high-throughput technologies allow for the simultaneous monitoring of multiple dynamic cellular events over time, ranging from gene expression to metabolite abundance and sub-cellular localization. These fundamental temporal and spatial perspectives have allowed for a more comprehensive understanding of how various dynamic cellular events and biochemical processes are related in health and disease. With advances in technology, metabolomics has become a more routine “omics” approach for studying metabolism, and “circadian metabolomics” (i.e., studying the 24-h metabolome has recently been undertaken by several groups. To date, circadian metabolomes have been reported for human serum, saliva, breath, and urine, as well as tissues from several species under specific disease or mutagenesis conditions. Importantly, these studies have consistently revealed that 24-h rhythms are prevalent in almost every tissue and metabolic pathway. Furthermore, these circadian rhythms in tissue metabolism are ultimately linked to and directed by internal 24-h biological clocks. In this review, we will attempt to put these data-rich circadian metabolomics experiments into perspective to find out what they can tell us about metabolic health and disease, and what additional biomarker potential they may reveal.

  15. Single cell metabolomics

    NARCIS (Netherlands)

    Heinemann, Matthias; Zenobi, Renato

    Recent discoveries suggest that cells of a clonal population often display multiple metabolic phenotypes at the same time. Motivated by the success of mass spectrometry (MS) in the investigation of population-level metabolomics, the analytical community has initiated efforts towards MS-based single

  16. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

    Directory of Open Access Journals (Sweden)

    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  17. Highly parallel algorithm for high pT physics at FAIR-CBM

    International Nuclear Information System (INIS)

    Fueloep, A; Vesztergombi, G

    2010-01-01

    The limitations of presently available data on p T range are discussed and planned future upgrades are outlined. Special attention is given to the FAIR-CBM experiment as a unique high luminosity facility for future continuation of the measurements at very high p T with emphasis on the so-called mosaic trigger system to use the highly parallel online algorithm.

  18. Integration of metabolomics data into metabolic networks.

    Science.gov (United States)

    Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

    2015-01-01

    Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.

  19. A Review of Applications of Metabolomics in Cancer

    Directory of Open Access Journals (Sweden)

    Richard D. Beger

    2013-07-01

    Full Text Available Cancer is a devastating disease that alters the metabolism of a cell and the surrounding milieu. Metabolomics is a growing and powerful technology capable of detecting hundreds to thousands of metabolites in tissues and biofluids. The recent advances in metabolomics technologies have enabled a deeper investigation into the metabolism of cancer and a better understanding of how cancer cells use glycolysis, known as the “Warburg effect,” advantageously to produce the amino acids, nucleotides and lipids necessary for tumor proliferation and vascularization. Currently, metabolomics research is being used to discover diagnostic cancer biomarkers in the clinic, to better understand its complex heterogeneous nature, to discover pathways involved in cancer that could be used for new targets and to monitor metabolic biomarkers during therapeutic intervention. These metabolomics approaches may also provide clues to personalized cancer treatments by providing useful information to the clinician about the cancer patient’s response to medical interventions.

  20. NMR-based metabolomic profiling of overweight adolescents

    DEFF Research Database (Denmark)

    Zheng, Hong; Yde, Christian C; Arnberg, Karina

    2014-01-01

    The plasma and urine metabolome of 192 overweight 12-15-year-old adolescents (BMI of 25.4 ± 2.3 kg/m(2)) were examined in order to elucidate gender, pubertal development measured as Tanner stage, physical activity measured as number of steps taken daily, and intra-/interindividual differences...... and the metabolome could be identified. The present study for the first time provides comprehensive information about associations between the metabolome and gender, pubertal development, and physical activity in overweight adolescents, which is an important subject group to approach in the prevention of obesity...... affecting the metabolome detected by proton NMR spectroscopy. Higher urinary excretion of citrate, creatinine, hippurate, and phenylacetylglutamine and higher plasma level of phosphatidylcholine and unsaturated lipid were found for girls compared with boys. The results suggest that gender differences...

  1. Metabolomics through the lens of precision cardiovascular medicine.

    Science.gov (United States)

    Lam, Sin Man; Wang, Yuan; Li, Bowen; Du, Jie; Shui, Guanghou

    2017-03-20

    Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

  2. Mass spectrometry-based metabolomics for tuberculosis meningitis.

    Science.gov (United States)

    Zhang, Peixu; Zhang, Weiguanliu; Lang, Yue; Qu, Yan; Chu, Fengna; Chen, Jiafeng; Cui, Li

    2018-04-18

    Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described. Copyright © 2018. Published by Elsevier B.V.

  3. The food metabolome: a window over dietary exposure.

    Science.gov (United States)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine; Andres-Lacueva, Cristina; Dragsted, Lars O; Draper, John; Rappaport, Stephen M; van der Hooft, Justin J J; Wishart, David S

    2014-06-01

    The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health. © 2014 American Society for Nutrition.

  4. NMR-based milk metabolomics

    DEFF Research Database (Denmark)

    Sundekilde, Ulrik; Larsen, Lotte Bach; Bertram, Hanne Christine S.

    2013-01-01

    and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining...

  5. Stable isotope-resolved metabolomics and applications for drug development

    Science.gov (United States)

    Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

    2012-01-01

    Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

  6. Quality assurance procedures for mass spectrometry untargeted metabolomics. a review.

    Science.gov (United States)

    Dudzik, Danuta; Barbas-Bernardos, Cecilia; García, Antonia; Barbas, Coral

    2018-01-05

    Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. Metabolomics in transfusion medicine.

    Science.gov (United States)

    Nemkov, Travis; Hansen, Kirk C; Dumont, Larry J; D'Alessandro, Angelo

    2016-04-01

    Biochemical investigations on the regulatory mechanisms of red blood cell (RBC) and platelet (PLT) metabolism have fostered a century of advances in the field of transfusion medicine. Owing to these advances, storage of RBCs and PLT concentrates has become a lifesaving practice in clinical and military settings. There, however, remains room for improvement, especially with regard to the introduction of novel storage and/or rejuvenation solutions, alternative cell processing strategies (e.g., pathogen inactivation technologies), and quality testing (e.g., evaluation of novel containers with alternative plasticizers). Recent advancements in mass spectrometry-based metabolomics and systems biology, the bioinformatics integration of omics data, promise to speed up the design and testing of innovative storage strategies developed to improve the quality, safety, and effectiveness of blood products. Here we review the currently available metabolomics technologies and briefly describe the routine workflow for transfusion medicine-relevant studies. The goal is to provide transfusion medicine experts with adequate tools to navigate through the otherwise overwhelming amount of metabolomics data burgeoning in the field during the past few years. Descriptive metabolomics data have represented the first step omics researchers have taken into the field of transfusion medicine. However, to up the ante, clinical and omics experts will need to merge their expertise to investigate correlative and mechanistic relationships among metabolic variables and transfusion-relevant variables, such as 24-hour in vivo recovery for transfused RBCs. Integration with systems biology models will potentially allow for in silico prediction of metabolic phenotypes, thus streamlining the design and testing of alternative storage strategies and/or solutions. © 2015 AABB.

  8. Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach.

    Science.gov (United States)

    Romero-Ibarguengoitia, Maria Elena; Vadillo-Ortega, Felipe; Caballero, Augusto Enrique; Ibarra-González, Isabel; Herrera-Rosas, Arturo; Serratos-Canales, María Fabiola; León-Hernández, Mireya; González-Chávez, Antonio; Mummidi, Srinivas; Duggirala, Ravindranath; López-Alvarenga, Juan Carlos

    2018-01-01

    Structural equation modeling (SEM) can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD), family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1) If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines would be related to non-alcoholic fatty disease that will induce insulin resistance. 2) If a positive family history of obesity and type 2 diabetes are the major determinants of the metabolomic profile, there would be higher concentration of amino acids and acylcarnitines in patients with this background that will induce obesity and NAFLD which in turn will induce insulin resistance. 137 normoglycemic subjects, mean age (SD) of 30.61 (8.6) years divided in three groups: BMI30 with absence of NAFLD (G2), n = 24; and BMI>30 with NAFLD (G3), n = 31. Family history of obesity (any) was present in 53%. Both models were adjusted in SEM. Family history of obesity predicted obesity but could not predict acylcarnitines and amino acid concentrations (effect size obesity phenotype. Family history of obesity is the major predictor of obesity, and the metabolic abnormalities on amino acids, acylcarnitines, inflammation, insulin resistance, and NAFLD.

  9. Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD. Structural equation modeling approach.

    Directory of Open Access Journals (Sweden)

    Maria Elena Romero-Ibarguengoitia

    Full Text Available Structural equation modeling (SEM can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD, family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1 If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines would be related to non-alcoholic fatty disease that will induce insulin resistance. 2 If a positive family history of obesity and type 2 diabetes are the major determinants of the metabolomic profile, there would be higher concentration of amino acids and acylcarnitines in patients with this background that will induce obesity and NAFLD which in turn will induce insulin resistance.137 normoglycemic subjects, mean age (SD of 30.61 (8.6 years divided in three groups: BMI30 with absence of NAFLD (G2, n = 24; and BMI>30 with NAFLD (G3, n = 31. Family history of obesity (any was present in 53%. Both models were adjusted in SEM. Family history of obesity predicted obesity but could not predict acylcarnitines and amino acid concentrations (effect size <0.2, but did predict obesity phenotype.Family history of obesity is the major predictor of obesity, and the metabolic abnormalities on amino acids, acylcarnitines, inflammation, insulin resistance, and NAFLD.

  10. The Human Urine Metabolome

    Science.gov (United States)

    Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

    2013-01-01

    Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing

  11. A Metabolomic Approach Applied to a Liquid Chromatography Coupled to High-Resolution Tandem Mass Spectrometry Method (HPLC-ESI-HRMS/MS): Towards the Comprehensive Evaluation of the Chemical Composition of Cannabis Medicinal Extracts.

    Science.gov (United States)

    Citti, Cinzia; Battisti, Umberto Maria; Braghiroli, Daniela; Ciccarella, Giuseppe; Schmid, Martin; Vandelli, Maria Angela; Cannazza, Giuseppe

    2018-03-01

    Cannabis sativa L. is a powerful medicinal plant and its use has recently increased for the treatment of several pathologies. Nonetheless, side effects, like dizziness and hallucinations, and long-term effects concerning memory and cognition, can occur. Most alarming is the lack of a standardised procedure to extract medicinal cannabis. Indeed, each galenical preparation has an unknown chemical composition in terms of cannabinoids and other active principles that depends on the extraction procedure. This study aims to highlight the main differences in the chemical composition of Bediol® extracts when the extraction is carried out with either ethyl alcohol or olive oil for various times (0, 60, 120 and 180 min for ethyl alcohol, and 0, 60, 90 and 120 min for olive oil). Cannabis medicinal extracts (CMEs) were analysed by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) using an untargeted metabolomics approach. The data sets were processed by unsupervised multivariate analysis. Our results suggested that the main difference lies in the ratio of acid to decarboxylated cannabinoids, which dramatically influences the pharmacological activity of CMEs. Minor cannabinoids, alkaloids, and amino acids contributing to this difference are also discussed. The main cannabinoids were quantified in each extract applying a recently validated LC-MS and LC-UV method. Notwithstanding the use of a standardised starting plant material, great changes are caused by different extraction procedures. The metabolomics approach is a useful tool for the evaluation of the chemical composition of cannabis extracts. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  12. Deconstructing the pig sex metabolome: Targeted metabolomics in heavy pigs revealed sexual dimorphisms in plasma biomarkers and metabolic pathways.

    Science.gov (United States)

    Bovo, S; Mazzoni, G; Calò, D G; Galimberti, G; Fanelli, F; Mezzullo, M; Schiavo, G; Scotti, E; Manisi, A; Samoré, A B; Bertolini, F; Trevisi, P; Bosi, P; Dall'Olio, S; Pagotto, U; Fontanesi, L

    2015-12-01

    Metabolomics has opened new possibilities to investigate metabolic differences among animals. In this study, we applied a targeted metabolomic approach to deconstruct the pig sex metabolome as defined by castrated males and entire gilts. Plasma from 545 performance-tested Italian Large White pigs (172 castrated males and 373 females) sampled at about 160 kg live weight were analyzed for 186 metabolites using the Biocrates AbsoluteIDQ p180 Kit. After filtering, 132 metabolites (20 AA, 11 biogenic amines, 1 hexose, 13 acylcarnitines, 11 sphingomyelins, 67 phosphatidylcholines, and 9 lysophosphatidylcholines) were retained for further analyses. The multivariate approach of the sparse partial least squares discriminant analysis was applied, together with a specifically designed statistical pipeline, that included a permutation test and a 10 cross-fold validation procedure that produced stability and effect size statistics for each metabolite. Using this approach, we identified 85 biomarkers (with metabolites from all analyzed chemical families) that contributed to the differences between the 2 groups of pigs ( metabolic shift in castrated males toward energy storage and lipid production. Similar general patterns were observed for most sphingomyelins, phosphatidylcholines, and lysophosphatidylcholines. Metabolomic pathway analysis and pathway enrichment identified several differences between the 2 sexes. This metabolomic overview opened new clues on the biochemical mechanisms underlying sexual dimorphism that, on one hand, might explain differences in terms of economic traits between castrated male pigs and entire gilts and, on the other hand, could strengthen the pig as a model to define metabolic mechanisms related to fat deposition.

  13. Use of Metabolomics as a Complementary Omic Approach to Implement Risk Criteria for First-Degree Relatives of Gastric Cancer Patients

    Directory of Open Access Journals (Sweden)

    Giuseppe Corona

    2018-03-01

    Full Text Available A positive family history is a strong and consistently reported risk factor for gastric cancer (GC. So far, it has been demonstrated that serum pepsinogens (PGs, and gastrin 17 (G17 are useful for screening individuals at elevated risk to develop atrophic gastritis but they are suboptimal biomarkers to screen individuals for GC. The main purpose of this study was to investigate serum metabolomic profiles to find additional biomarkers that could be integrated with serum PGs and G17 to improve the diagnosis of GC and the selection of first-degree relatives (FDR at higher risk of GC development. Serum metabolomic profiles included 188 serum metabolites, covering amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexoses. Serum metabolomic profiles were performed with tandem mass spectrometry using the Biocrates AbsoluteIDQ p180 kit. The initial cohort (training set consisted of n = 49 GC patients and n = 37 FDR. Differential metabolomic signatures among the two groups were investigated by univariate and multivariate partial least square differential analysis. The most significant metabolites were further selected and validated in an independent group of n = 22 GC patients and n = 17 FDR (validation set. Receiver operating characteristic (ROC curves were used to evaluate the diagnostic power and the optimal cut-off for each of the discriminant markers. Multivariate analysis was applied to associate the selected serum metabolites, PGs, G17 and risk factors such as age, gender and Helicobacter pylori (H. pylori infection with the GC and FDR has been performed and an integrative risk prediction algorithm was developed. In the training set, 40 metabolites mainly belonging to phospholipids and acylcarnitines classes were differentially expressed between GC and FDR. Out of these 40 metabolites, 9 were further confirmed in the validation set. Compared with FDR, GC patients were characterized by lower levels of

  14. Associations of Nasopharyngeal Metabolome and Microbiome with Severity among Infants with Bronchiolitis. A Multiomic Analysis.

    Science.gov (United States)

    Stewart, Christopher J; Mansbach, Jonathan M; Wong, Matthew C; Ajami, Nadim J; Petrosino, Joseph F; Camargo, Carlos A; Hasegawa, Kohei

    2017-10-01

    Bronchiolitis is the most common lower respiratory infection in infants; however, it remains unclear which infants with bronchiolitis will develop severe illness. In addition, although emerging evidence indicates associations of the upper-airway microbiome with bronchiolitis severity, little is known about the mechanisms linking airway microbes and host response to disease severity. To determine the relations among the nasopharyngeal airway metabolome profiles, microbiome profiles, and severity in infants with bronchiolitis. We conducted a multicenter prospective cohort study of infants (age metabolomic and metagenomic (16S ribosomal RNA gene and whole-genome shotgun sequencing) approaches to 144 nasopharyngeal airway samples collected within 24 hours of hospitalization, we determined metabolome and microbiome profiles and their association with higher severity, defined by the use of positive pressure ventilation (i.e., continuous positive airway pressure and/or intubation). Nasopharyngeal airway metabolome profiles significantly differed by bronchiolitis severity (P metabolomics to predict bronchiolitis severity and better understand microbe-host interaction.

  15. Metabolomics Workbench (MetWB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Metabolomics Program's Data Repository and Coordinating Center (DRCC), housed at the San Diego Supercomputer Center (SDSC), University of California, San Diego,...

  16. The biology of plant metabolomics

    NARCIS (Netherlands)

    Hall, R.D.

    2011-01-01

    Following a general introduction, this book includes details of metabolomics of model species including Arabidopsis and tomato. Further chapters provide in-depth coverage of abiotic stress, data integration, systems biology, genetics, genomics, chemometrics and biostatisitcs. Applications of plant

  17. LC-MS-BASED METABOLOMICS OF XENOBIOTIC-INDUCED TOXICITIES

    Directory of Open Access Journals (Sweden)

    Chi Chen

    2013-01-01

    Full Text Available Xenobiotic exposure, especially high-dose or repeated exposure of xenobiotics, can elicit detrimental effects on biological systems through diverse mechanisms. Changes in metabolic systems, including formation of reactive metabolites and disruption of endogenous metabolism, are not only the common consequences of toxic xenobiotic exposure, but in many cases are the major causes behind development of xenobiotic-induced toxicities (XIT. Therefore, examining the metabolic events associated with XIT generates mechanistic insights into the initiation and progression of XIT, and provides guidance for prevention and treatment. Traditional bioanalytical platforms that target only a few suspected metabolites are capable of validating the expected outcomes of xenobiotic exposure. However, these approaches lack the capacity to define global changes and to identify unexpected events in the metabolic system. Recent developments in high-throughput metabolomics have dramatically expanded the scope and potential of metabolite analysis. Among all analytical techniques adopted for metabolomics, liquid chromatography-mass spectrometry (LC-MS has been most widely used for metabolomic investigations of XIT due to its versatility and sensitivity in metabolite analysis. In this review, technical platform of LC-MS-based metabolomics, including experimental model, sample preparation, instrumentation, and data analysis, are discussed. Applications of LC-MS-based metabolomics in exploratory and hypothesis-driven investigations of XIT are illustrated by case studies of xenobiotic metabolism and endogenous metabolism associated with xenobiotic exposure.

  18. Untargeted metabolomics reveals specific withanolides and fatty acyl glycoside as tentative metabolites to differentiate organic and conventional Physalis peruviana fruits.

    Science.gov (United States)

    Llano, Sandra M; Muñoz-Jiménez, Ana M; Jiménez-Cartagena, Claudio; Londoño-Londoño, Julián; Medina, Sonia

    2018-04-01

    The agronomic production systems may affect the levels of food metabolites. Metabolomics approaches have been applied as useful tool for the characterization of fruit metabolome. In this study, metabolomics techniques were used to assess the differences in phytochemical composition between goldenberry samples produced by organic and conventional systems. To verify that the organic samples were free of pesticides, individual pesticides were analyzed. Principal component analysis showed a clear separation of goldenberry samples from two different farming systems. Via targeted metabolomics assays, whereby carotenoids and ascorbic acid were analyzed, not statistical differences between both crops were found. Conversely, untargeted metabolomics allowed us to identify two withanolides and one fatty acyl glycoside as tentative metabolites to differentiate goldenberry fruits, recording organic fruits higher amounts of these compounds than conventional samples. Hence, untargeted metabolomics technology could be suitable to research differences on phytochemicals under different agricultural management practices and to authenticate organic products. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Pea fiber and wheat bran fiber show distinct metabolic profiles in rats as investigated by a 1H NMR-based metabolomic approach.

    Directory of Open Access Journals (Sweden)

    Guangmang Liu

    Full Text Available This study aimed to examine the effect of pea fiber (PF and wheat bran fiber (WF supplementation in rat metabolism. Rats were assigned randomly to one of three dietary groups and were given a basal diet containing 15% PF, 15% WF, or no supplemental fiber. Urine and plasma samples were analyzed by NMR-based metabolomics. PF significantly increased the plasma levels of 3-hydroxybutyrate, and myo-inositol as well as the urine levels of alanine, hydroxyphenylacetate, phenylacetyglycine, and α-ketoglutarate. However, PF significantly decreased the plasma levels of isoleucine, leucine, lactate, and pyruvate as well as the urine levels of allantoin, bile acids, and trigonelline. WF significantly increased the plasma levels of acetone, isobutyrate, lactate, myo-inositol, and lipids as well as the urine levels of alanine, lactate, dimethylglycine, N-methylniconamide, and α-ketoglutarate. However, WF significantly decreased the plasma levels of amino acids, and glucose as well as the urine levels of acetate, allantoin, citrate, creatine, hippurate, hydroxyphenylacetate, and trigonelline. Results suggest that PF and WF exposure can promote antioxidant activity and can exhibit common systemic metabolic changes, including lipid metabolism, energy metabolism, glycogenolysis and glycolysis metabolism, protein biosynthesis, and gut microbiota metabolism. PF can also decrease bile acid metabolism. These findings indicate that different fiber diet may cause differences in the biofluid profile in rats.

  20. Nuclear Magnetic Resonance-Based Metabolomics Approach to Evaluate the Prevention Effect of Camellia nitidissima Chi on Colitis-Associated Carcinogenesis

    Directory of Open Access Journals (Sweden)

    Ming-Hui Li

    2017-07-01

    Full Text Available Colorectal cancer (CRC is one of the most common malignant tumors worldwide, occurring in the colon or rectum portion of large intestine. With marked antioxidant, anti-inflammation and anti-tumor activities, Camellia nitidissima Chi has been used as an effective treatment of cancer. The azoxymethane/dextran sodium sulfate (AOM/DSS induced CRC mice model was established and the prevention effect of C. nitidissima Chi extracts on the evolving of CRC was evaluated by examination of neoplastic lesions, histopathological inspection, serum biochemistry analysis, combined with nuclear magnetic resonance (NMR-based metabolomics and correlation network analysis. C. nitidissima Chi extracts could significantly inhibit AOM/DSS induced CRC, relieve the colonic pathology of inflammation and ameliorate the serum biochemistry, and could significantly reverse the disturbed metabolic profiling toward the normal state. Moreover, the butanol fraction showed a better efficacy than the water-soluble fraction of C. nitidissima Chi. Further development of C. nitidissima Chi extracts as a potent CRC inhibitor was warranted.

  1. Protection of Pepper Plants from Drought by Microbacterium sp. 3J1 by Modulation of the Plant's Glutamine and α-ketoglutarate Content: A Comparative Metabolomics Approach

    Directory of Open Access Journals (Sweden)

    Juan I. Vílchez

    2018-02-01

    Full Text Available Drought tolerance of plants such as tomato or pepper can be improved by their inoculation with rhizobacteria such as Microbacterium sp. 3J1. This interaction depends on the production of trehalose by the microorganisms that in turn modulate the phyto-hormone profile of the plant. In this work we describe the characterization of metabolic changes during the interaction of pepper plants with Microbacterium sp. 3J1 and of the microorganism alone over a period of drought. Our main findings include the observation that the plant responds to the presence of the microorganism by changing the C and N metabolism based on its glutamine and α-ketoglutarate content, these changes contribute to major changes in the concentration of molecules involved in the balance of the osmotic pressure. These include sugars and amino-acids; the concentration of antioxidant molecules, of metabolites involved in the production of phytohormones like ethylene, and of substrates used for lignin production such as ferulic and sinapic acids. Most of the altered metabolites of the plant when inoculated with Microbacterium sp. 3J1 in response to drought coincided with the profile of altered metabolites in the microorganism alone when subjected to drought, pointing to a response by which the plant relies on the microbe for the production of such metabolites. To our knowledge this is the first comparative study of the microbe colonized-plant and microbe alone metabolomes under drought stress.

  2. The potential biomarkers of drug addiction: proteomic and metabolomics challenges.

    Science.gov (United States)

    Wang, Lv; Wu, Ning; Zhao, Tai-Yun; Li, Jin

    2016-07-28

    Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

  3. Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks.

    Science.gov (United States)

    Fearnley, Liam G; Inouye, Michael

    2016-10-01

    Metabolomics is becoming feasible for population-scale studies of human disease. In this review, we survey epidemiological studies that leverage metabolomics and multi-omics to gain insight into disease mechanisms. We outline key practical, technological and analytical limitations while also highlighting recent successes in integrating these data. The use of multi-omics to infer reaction rates is discussed as a potential future direction for metabolomics research, as a means of identifying biomarkers as well as inferring causality. Furthermore, we highlight established analysis approaches as well as simulation-based methods currently used in single- and multi-cell levels in systems biology. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

  4. Nuclear magnetic resonance based metabolomics and liver diseases: Recent advances and future clinical applications.

    Science.gov (United States)

    Amathieu, Roland; Triba, Mohamed Nawfal; Goossens, Corentine; Bouchemal, Nadia; Nahon, Pierre; Savarin, Philippe; Le Moyec, Laurence

    2016-01-07

    Metabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an "omics" technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical "routine".

  5. Metabolomics as an emerging strategy for the investigation of yogurt components

    NARCIS (Netherlands)

    Settachaimongkon, S.; Valenberg, van H.J.F.; Smid, E.J.

    2017-01-01

    The advanced development in metabolomics allows discovery of a wide range of metabolites in complex biological systems including food matrices. This analytical approach provides opportunities to attain a global metabolite profile and discover potential biomarkers and various chemical contaminants

  6. Profiling of altered metabolomic states in Nicotiana tabacum cells induced by priming agents

    CSIR Research Space (South Africa)

    Mhlongo, MI

    2016-10-01

    Full Text Available tabacum cells. Identified biomarkers were then compared to responses induced by three phytohormones—abscisic acid, methyljasmonate, and salicylic acid. Altered metabolomes were studied using a metabolite fingerprinting approach based on liquid...

  7. Effect of sleep deprivation on the human metabolome

    NARCIS (Netherlands)

    S.K. Davies (Sarah); J.E. Ang (Joo Ern); V.L. Revell (Victoria); B. Holmes (Ben); A. Mann (Anuska); F.P. Robertson (Francesca); N. Cui (Nanyi); B. Middleton (Benita); K. Ackermann (Katrin); M.H. Kayser (Manfred); A.E. Thumser (Alfred); P. Raynaud (Philippe); D.J. Skene (Debra)

    2014-01-01

    textabstractSleep restriction and circadian clock disruption are associated with metabolic disorders such as obesity, insulin resistance, and diabetes. The metabolic pathways involved in human sleep, however, have yet to be investigatedwith the use of a metabolomics approach. Here we have used

  8. Metabolomics Society’s International Affiliations

    NARCIS (Netherlands)

    Roessner, U.; Rolin, D.; Rijswijk, van M.E.C.; Hall, R.D.; Hankemeier, T.

    2015-01-01

    In 2012 the Metabolomics Society established a more formal system for national and regional metabolomics initiatives, interest groups, societies and networks to become an International Affiliate of the Society. A number of groups (http://metabolomicssociety.org/international-affilia

  9. Role of metabolomics in TBI research

    Science.gov (United States)

    Wolahan, Stephanie M.; Hirt, Daniel; Braas, Daniel; Glenn, Thomas C.

    2016-01-01

    Synopsis Metabolomics is an important member of the omics community in that it defines which small molecules may be responsible for disease states. This article reviews the essential principles of metabolomics from specimen preparation, chemical analysis, and advanced statistical methods. Metabolomics in TBI has so far been underutilized. Future metabolomics based studies focused on the diagnoses, prognoses, and treatment effects, need to be conducted across all types of TBI. PMID:27637396

  10. ECMDB: The E. coli Metabolome Database

    OpenAIRE

    Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S.

    2012-01-01

    The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ?1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. E...

  11. Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application.

    Science.gov (United States)

    Klein, Matthias S; Shearer, Jane

    2016-01-01

    Type 2 diabetes (T2D) and its comorbidities have reached epidemic proportions, with more than half a billion cases expected by 2030. Metabolomics is a fairly new approach for studying metabolic changes connected to disease development and progression and for finding predictive biomarkers to enable early interventions, which are most effective against T2D and its comorbidities. In metabolomics, the abundance of a comprehensive set of small biomolecules (metabolites) is measured, thus giving insight into disease-related metabolic alterations. This review shall give an overview of basic metabolomics methods and will highlight current metabolomics research successes in the prediction and diagnosis of T2D. We summarized key metabolites changing in response to T2D. Despite large variations in predictive biomarkers, many studies have replicated elevated plasma levels of branched-chain amino acids and their derivatives, aromatic amino acids and α-hydroxybutyrate ahead of T2D manifestation. In contrast, glycine levels and lysophosphatidylcholine C18:2 are depressed in both predictive studies and with overt disease. The use of metabolomics for predicting T2D comorbidities is gaining momentum, as are our approaches for translating basic metabolomics research into clinical applications. As a result, metabolomics has the potential to enable informed decision-making in the realm of personalized medicine.

  12. Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application

    Directory of Open Access Journals (Sweden)

    Matthias S. Klein

    2016-01-01

    Full Text Available Type 2 diabetes (T2D and its comorbidities have reached epidemic proportions, with more than half a billion cases expected by 2030. Metabolomics is a fairly new approach for studying metabolic changes connected to disease development and progression and for finding predictive biomarkers to enable early interventions, which are most effective against T2D and its comorbidities. In metabolomics, the abundance of a comprehensive set of small biomolecules (metabolites is measured, thus giving insight into disease-related metabolic alterations. This review shall give an overview of basic metabolomics methods and will highlight current metabolomics research successes in the prediction and diagnosis of T2D. We summarized key metabolites changing in response to T2D. Despite large variations in predictive biomarkers, many studies have replicated elevated plasma levels of branched-chain amino acids and their derivatives, aromatic amino acids and α-hydroxybutyrate ahead of T2D manifestation. In contrast, glycine levels and lysophosphatidylcholine C18:2 are depressed in both predictive studies and with overt disease. The use of metabolomics for predicting T2D comorbidities is gaining momentum, as are our approaches for translating basic metabolomics research into clinical applications. As a result, metabolomics has the potential to enable informed decision-making in the realm of personalized medicine.

  13. Metabolomics: the chemistry between ecology and genetics

    NARCIS (Netherlands)

    Macel, M.; Van Dam, N.M.; Keurentjes, J.J.B.

    2010-01-01

    Metabolomics is a fast developing field of comprehensive untargeted chemical analyses. It has many applications and can in principle be used on any organism without prior knowledge of the metabolome or genome. The amount of functional information that is acquired with metabolomics largely depends on

  14. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology.

    Science.gov (United States)

    Aretz, Ina; Meierhofer, David

    2016-04-27

    Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

  15. Advantages and Pitfalls of Mass Spectrometry Based Metabolome Profiling in Systems Biology

    Directory of Open Access Journals (Sweden)

    Ina Aretz

    2016-04-01

    Full Text Available Mass spectrometry-based metabolome profiling became the method of choice in systems biology approaches and aims to enhance biological understanding of complex biological systems. Genomics, transcriptomics, and proteomics are well established technologies and are commonly used by many scientists. In comparison, metabolomics is an emerging field and has not reached such high-throughput, routine and coverage than other omics technologies. Nevertheless, substantial improvements were achieved during the last years. Integrated data derived from multi-omics approaches will provide a deeper understanding of entire biological systems. Metabolome profiling is mainly hampered by its diversity, variation of metabolite concentration by several orders of magnitude and biological data interpretation. Thus, multiple approaches are required to cover most of the metabolites. No software tool is capable of comprehensively translating all the data into a biologically meaningful context yet. In this review, we discuss the advantages of metabolome profiling and main obstacles limiting progress in systems biology.

  16. A novel approach using metabolomics coupled with hematological and biochemical parameters to explain the enriching-blood effect and mechanism of unprocessed Angelica sinensis and its 4 kinds of processed products.

    Science.gov (United States)

    Ji, Peng; Wei, Yanming; Hua, Yongli; Zhang, Xiaosong; Yao, Wanling; Ma, Qi; Yuan, Ziwen; Wen, Yanqiao; Yang, Chaoxue

    2018-01-30

    Angelica sinensis (AS), root of Angelica sinensis (Oliv.) Diels, an important kind of Chinese traditional herbal medicine, has been used for women to enrich the blood for thousands of years. It is mainly distributed in Gansu province of China. According to Traditional Chinese medicine usage, unprocessed AS (UAS) and its 4 kinds of processed products (ASs) are all used to treat different diseases or syndromes. The difference among the enriching-blood effects of ASs is unclear. And their exact mechanisms of enriching the blood are not fully understood. In this study, our aim is to compare the enriching-blood effect and explain the related mechanism of ASs, to lay the foundation for the blood deficiency diagnosis and the rational use of ASs in the clinic. ASs were used to intervene the blood deficiency syndrome model mice induced by acetyl phenylhydrazine (APH) and cyclophosphamide (CTX). A novel approach using metabolomics coupled with hematological and biochemical parameters to explain the enriching-blood effect and mechanism of ASs was established. The blood routine examination, ATPase, glucose-6-phosphate dehydrogenase, methemoglobin, glutathion peroxidase, glutathione reductase, and erythropoietin were measured. Two biofluids (plasma and urine) obtained from mice were analyzed with GC-MS. Distinct changes in metabolite patterns of the two biofluids after mice were induced by APH and CTX, and mice were intervened with ASs were analyzed using partial least squares-discriminant analysis. Potential biomarkers were found using a novel method including variable importance in the projection (VIP) >1.0, volcano plot analysis, and significance analysis of microarray. The results of hematological, biochemical parameters and the integrated metabolomics all showed the blood deficiency syndrome model was built successfully, ASs exhibited different degree of enriching-blood effect, and AS pached with alcohol (AAS) exhibited the best enriching-blood effect. 16 metabolites in

  17. Applied metabolomics in drug discovery.

    Science.gov (United States)

    Cuperlovic-Culf, M; Culf, A S

    2016-08-01

    The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

  18. Metabolomic Profiling for Identification of Novel Potential Biomarkers in Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Maria G. Barderas

    2011-01-01

    Full Text Available Metabolomics involves the identification and quantification of metabolites present in a biological system. Three different approaches can be used: metabolomic fingerprinting, metabolic profiling, and metabolic footprinting, in order to evaluate the clinical course of a disease, patient recovery, changes in response to surgical intervention or pharmacological treatment, as well as other associated features. Characteristic patterns of metabolites can be revealed that broaden our understanding of a particular disorder. In the present paper, common strategies and analytical techniques used in metabolomic studies are reviewed, particularly with reference to the cardiovascular field.

  19. Influence of a polyphenol-enriched protein powder on exercise-induced inflammation and oxidative stress in athletes: a randomized trial using a metabolomics approach.

    Directory of Open Access Journals (Sweden)

    David C Nieman

    Full Text Available Polyphenol supplementation was tested as a countermeasure to inflammation and oxidative stress induced by 3-d intensified training.Water soluble polyphenols from blueberry and green tea extracts were captured onto a polyphenol soy protein complex (PSPC. Subjects were recruited, and included 38 long-distance runners ages 19-45 years who regularly competed in road races. Runners successfully completing orientation and baseline testing (N = 35 were randomized to 40 g/d PSPC (N = 17 (2,136 mg/d gallic acid equivalents or placebo (N = 18 for 17 d using double-blinded methods and a parallel group design, with a 3-d running period inserted at day 14 (2.5 h/d, 70% VO2max. Blood samples were collected pre- and post-14 d supplementation, and immediately and 14 h after the third day of running in subjects completing all aspects of the study (N = 16 PSPC, N = 15 placebo, and analyzed using a metabolomics platform with GC-MS and LC-MS.Metabolites characteristic of gut bacteria metabolism of polyphenols were increased with PSPC and 3 d running (e.g., hippurate, 4-hydroxyhippurate, 4-methylcatechol sulfate, 1.8-, 1.9-, 2.5-fold, respectively, P<0.05, an effect which persisted for 14-h post-exercise. Fatty acid oxidation and ketogenesis were induced by exercise in both groups, with more ketones at 14-h post-exercise in PSPC (3-hydroxybutyrate, 1.8-fold, P<0.05. Established biomarkers for inflammation (CRP, cytokines and oxidative stress (protein carbonyls did not differ between groups.PSPC supplementation over a 17-d period did not alter established biomarkers for inflammation and oxidative stress but was linked to an enhanced gut-derived phenolic signature and ketogenesis in runners during recovery from 3-d heavy exertion.ClinicalTrials.gov, U.S. National Institutes of Health, identifier: NCT01775384.

  20. Food metabolomics: from farm to human.

    Science.gov (United States)

    Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

    2016-02-01

    Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. How to use MPI communication in highly parallel climate simulations more easily and more efficiently.

    Science.gov (United States)

    Behrens, Jörg; Hanke, Moritz; Jahns, Thomas

    2014-05-01

    In this talk we present a way to facilitate efficient use of MPI communication for developers of climate models. Exploitation of the performance potential of today's highly parallel supercomputers with real world simulations is a complex task. This is partly caused by the low level nature of the MPI communication library which is the dominant communication tool at least for inter-node communication. In order to manage the complexity of the task, climate simulations with non-trivial communication patterns often use an internal abstraction layer above MPI without exploiting the benefits of communication aggregation or MPI-datatypes. The solution for the complexity and performance problem we propose is the communication library YAXT. This library is built on top of MPI and takes high level descriptions of arbitrary domain decompositions and automatically derives an efficient collective data exchange. Several exchanges can be aggregated in order to reduce latency costs. Examples are given which demonstrate the simplicity and the performance gains for selected climate applications.

  2. Load balancing in highly parallel processing of Monte Carlo code for particle transport

    International Nuclear Information System (INIS)

    Higuchi, Kenji; Takemiya, Hiroshi; Kawasaki, Takuji

    1998-01-01

    In parallel processing of Monte Carlo (MC) codes for neutron, photon and electron transport problems, particle histories are assigned to processors making use of independency of the calculation for each particle. Although we can easily parallelize main part of a MC code by this method, it is necessary and practically difficult to optimize the code concerning load balancing in order to attain high speedup ratio in highly parallel processing. In fact, the speedup ratio in the case of 128 processors remains in nearly one hundred times when using the test bed for the performance evaluation. Through the parallel processing of the MCNP code, which is widely used in the nuclear field, it is shown that it is difficult to attain high performance by static load balancing in especially neutron transport problems, and a load balancing method, which dynamically changes the number of assigned particles minimizing the sum of the computational and communication costs, overcomes the difficulty, resulting in nearly fifteen percentage of reduction for execution time. (author)

  3. A Highly Parallel and Scalable Motion Estimation Algorithm with GPU for HEVC

    Directory of Open Access Journals (Sweden)

    Yun-gang Xue

    2017-01-01

    Full Text Available We propose a highly parallel and scalable motion estimation algorithm, named multilevel resolution motion estimation (MLRME for short, by combining the advantages of local full search and downsampling. By subsampling a video frame, a large amount of computation is saved. While using the local full-search method, it can exploit massive parallelism and make full use of the powerful modern many-core accelerators, such as GPU and Intel Xeon Phi. We implanted the proposed MLRME into HM12.0, and the experimental results showed that the encoding quality of the MLRME method is close to that of the fast motion estimation in HEVC, which declines by less than 1.5%. We also implemented the MLRME with CUDA, which obtained 30–60x speed-up compared to the serial algorithm on single CPU. Specifically, the parallel implementation of MLRME on a GTX 460 GPU can meet the real-time coding requirement with about 25 fps for the 2560×1600 video format, while, for 832×480, the performance is more than 100 fps.

  4. Discussion paper for a highly parallel array processor-based machine

    International Nuclear Information System (INIS)

    Hagstrom, R.; Bolotin, G.; Dawson, J.

    1984-01-01

    The architectural plant for a quickly realizable implementation of a highly parallel special-purpose computer system with peak performance in the range of 6 billion floating point operations per second is discussed. The architecture is suitable to Lattice Gauge theoretical computations of fundamental physics interest and may be applicable to a range of other problems which deal with numerically intensive computational problems. The plan is quickly realizable because it employs a maximum of commercially available hardware subsystems and because the architecture is software-transparent to the individual processors, allowing straightforward re-use of whatever commercially available operating-systems and support software that is suitable to run on the commercially-produced processors. A tiny prototype instrument, designed along this architecture has already operated. A few elementary examples of programs which can run efficiently are presented. The large machine which the authors would propose to build would be based upon a highly competent array-processor, the ST-100 Array Processor, and specific design possibilities are discussed. The first step toward realizing this plan practically is to install a single ST-100 to allow algorithm development to proceed while a demonstration unit is built using two of the ST-100 Array Processors

  5. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  6. Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

    Science.gov (United States)

    Hayton, Sarah; Maker, Garth L; Mullaney, Ian; Trengove, Robert D

    2017-12-01

    Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

  7. Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

    Science.gov (United States)

    Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

    2016-03-01

    Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. © 2016 EAN.

  8. New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report.

    Science.gov (United States)

    Bowler, Russell P; Wendt, Chris H; Fessler, Michael B; Foster, Matthew W; Kelly, Rachel S; Lasky-Su, Jessica; Rogers, Angela J; Stringer, Kathleen A; Winston, Brent W

    2017-12-01

    This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

  9. Variable selection in the explorative analysis of several data blocks in metabolomics

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Nørskov, Natalja; Yde, Christian Clement

    highly correlated data sets in one integrated approach. Due to the high number of variables in data sets from metabolomics (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need...... to be related. Tools for the handling of mental overflow minimising false discovery rates both by using statistical and biological validation in an integrative approach are needed. In this paper different strategies for variable selection were considered with respect to false discovery and the possibility...... for biological validation. The data set used in this study is metabolomics data from an animal intervention study. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using NMR and LC-MS based...

  10. A parallelization study of the general purpose Monte Carlo code MCNP4 on a distributed memory highly parallel computer

    International Nuclear Information System (INIS)

    Yamazaki, Takao; Fujisaki, Masahide; Okuda, Motoi; Takano, Makoto; Masukawa, Fumihiro; Naito, Yoshitaka

    1993-01-01

    The general purpose Monte Carlo code MCNP4 has been implemented on the Fujitsu AP1000 distributed memory highly parallel computer. Parallelization techniques developed and studied are reported. A shielding analysis function of the MCNP4 code is parallelized in this study. A technique to map a history to each processor dynamically and to map control process to a certain processor was applied. The efficiency of parallelized code is up to 80% for a typical practical problem with 512 processors. These results demonstrate the advantages of a highly parallel computer to the conventional computers in the field of shielding analysis by Monte Carlo method. (orig.)

  11. Screening of a Brassica napus bacterial artificial chromosome library using highly parallel single nucleotide polymorphism assays

    Science.gov (United States)

    2013-01-01

    Background Efficient screening of bacterial artificial chromosome (BAC) libraries with polymerase chain reaction (PCR)-based markers is feasible provided that a multidimensional pooling strategy is implemented. Single nucleotide polymorphisms (SNPs) can be screened in multiplexed format, therefore this marker type lends itself particularly well for medium- to high-throughput applications. Combining the power of multiplex-PCR assays with a multidimensional pooling system may prove to be especially challenging in a polyploid genome. In polyploid genomes two classes of SNPs need to be distinguished, polymorphisms between accessions (intragenomic SNPs) and those differentiating between homoeologous genomes (intergenomic SNPs). We have assessed whether the highly parallel Illumina GoldenGate® Genotyping Assay is suitable for the screening of a BAC library of the polyploid Brassica napus genome. Results A multidimensional screening platform was developed for a Brassica napus BAC library which is composed of almost 83,000 clones. Intragenomic and intergenomic SNPs were included in Illumina’s GoldenGate® Genotyping Assay and both SNP classes were used successfully for screening of the multidimensional BAC pools of the Brassica napus library. An optimized scoring method is proposed which is especially valuable for SNP calling of intergenomic SNPs. Validation of the genotyping results by independent methods revealed a success of approximately 80% for the multiplex PCR-based screening regardless of whether intra- or intergenomic SNPs were evaluated. Conclusions Illumina’s GoldenGate® Genotyping Assay can be efficiently used for screening of multidimensional Brassica napus BAC pools. SNP calling was specifically tailored for the evaluation of BAC pool screening data. The developed scoring method can be implemented independently of plant reference samples. It is demonstrated that intergenomic SNPs represent a powerful tool for BAC library screening of a polyploid genome

  12. Transparent Nanopore Cavity Arrays Enable Highly Parallelized Optical Studies of Single Membrane Proteins on Chip.

    Science.gov (United States)

    Diederichs, Tim; Nguyen, Quoc Hung; Urban, Michael; Tampé, Robert; Tornow, Marc

    2018-06-13

    Membrane proteins involved in transport processes are key targets for pharmaceutical research and industry. Despite continuous improvements and new developments in the field of electrical readouts for the analysis of transport kinetics, a well-suited methodology for high-throughput characterization of single transporters with nonionic substrates and slow turnover rates is still lacking. Here, we report on a novel architecture of silicon chips with embedded nanopore microcavities, based on a silicon-on-insulator technology for high-throughput optical readouts. Arrays containing more than 14 000 inverted-pyramidal cavities of 50 femtoliter volumes and 80 nm circular pore openings were constructed via high-resolution electron-beam lithography in combination with reactive ion etching and anisotropic wet etching. These cavities feature both, an optically transparent bottom and top cap. Atomic force microscopy analysis reveals an overall extremely smooth chip surface, particularly in the vicinity of the nanopores, which exhibits well-defined edges. Our unprecedented transparent chip design provides parallel and independent fluorescent readout of both cavities and buffer reservoir for unbiased single-transporter recordings. Spreading of large unilamellar vesicles with efficiencies up to 96% created nanopore-supported lipid bilayers, which are stable for more than 1 day. A high lipid mobility in the supported membrane was determined by fluorescent recovery after photobleaching. Flux kinetics of α-hemolysin were characterized at single-pore resolution with a rate constant of 0.96 ± 0.06 × 10 -3 s -1 . Here, we deliver an ideal chip platform for pharmaceutical research, which features high parallelism and throughput, synergistically combined with single-transporter resolution.

  13. The Human Blood Metabolome-Transcriptome Interface

    Science.gov (United States)

    Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

    2015-01-01

    Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

  14. The Human Blood Metabolome-Transcriptome Interface.

    Directory of Open Access Journals (Sweden)

    Jörg Bartel

    2015-06-01

    Full Text Available Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the 'human blood metabolome-transcriptome interface' (BMTI. Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.

  15. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    Science.gov (United States)

    Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    Background Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract

  16. Recent Highlights of Metabolomics in Chinese Medicine Syndrome Research

    Directory of Open Access Journals (Sweden)

    Ai-hua Zhang

    2013-01-01

    Full Text Available Chinese medicine syndrome (CMS, “ZHENG” in Chinese is an understanding of the regularity of disease occurrence and development as well as a certain stage of a comprehensive response of patients with body condition. However, because of the complexity of CMS and the limitation of present investigation method, the research for deciphering the scientific basis and systematic features of CMS is difficult to go further. Metabolomics enables mapping of early biochemical changes in disease and hence provides an opportunity to develop predictive biomarkers. Moreover, its method and design resemble those of traditional Chinese medicine (TCM which focuses on human disease via the integrity of close relationship between body and syndromes. In the systemic context, metabolomics has a convergence with TCM syndrome; therefore it could provide useful tools for exploring essence of CMS disease, facilitating personalized TCM, and will help to in-depth understand CMS. The integration of the metabolomics and CMS aspects will give promise to bridge the gap between Chinese and Western medicine and help catch the traditional features of CMS. In this paper, particular attention will be paid to the past successes in applications of robust metabolomic approaches to contribute to low-molecular-weight metabolites (biomarkers discovery in CMS research and development.

  17. The metabolomics standards initiative (MSI)

    NARCIS (Netherlands)

    Fiehn, O.; Robertson, D.; Griffin, J.; Werf, M. van der; Nikolau, B.; Morrison, N.; Sumner, L.W.; Goodacre, R.; Hardy, N.W.; Taylor, C.; Fostel, J.; Kristal, B.; Kaddurah-Daouk, R.; Mendes, P.; Ommen, B. van; Lindon, J.C.; Sansone, S.-A.

    2007-01-01

    In 2005, the Metabolomics Standards Initiative has been formed. An outline and general introduction is provided to inform about the history, structure, working plan and intentions of this initiative. Comments on any of the suggested minimal reporting standards are welcome to be sent to the open

  18. YMDB: the Yeast Metabolome Database

    Science.gov (United States)

    Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S.

    2012-01-01

    The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated ‘metabolomic’ database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

  19. Fusing metabolomics data sets with heterogeneous measurement errors

    Science.gov (United States)

    Waaijenborg, Sandra; Korobko, Oksana; Willems van Dijk, Ko; Lips, Mirjam; Hankemeier, Thomas; Wilderjans, Tom F.; Smilde, Age K.

    2018-01-01

    Combining different metabolomics platforms can contribute significantly to the discovery of complementary processes expressed under different conditions. However, analysing the fused data might be hampered by the difference in their quality. In metabolomics data, one often observes that measurement errors increase with increasing measurement level and that different platforms have different measurement error variance. In this paper we compare three different approaches to correct for the measurement error heterogeneity, by transformation of the raw data, by weighted filtering before modelling and by a modelling approach using a weighted sum of residuals. For an illustration of these different approaches we analyse data from healthy obese and diabetic obese individuals, obtained from two metabolomics platforms. Concluding, the filtering and modelling approaches that both estimate a model of the measurement error did not outperform the data transformation approaches for this application. This is probably due to the limited difference in measurement error and the fact that estimation of measurement error models is unstable due to the small number of repeats available. A transformation of the data improves the classification of the two groups. PMID:29698490

  20. The application of metabolomics in traditional Chinese medicine opens up a dialogue between Chinese and Western medicine.

    Science.gov (United States)

    Cao, Hongxin; Zhang, Aihua; Zhang, Huamin; Sun, Hui; Wang, Xijun

    2015-02-01

    Metabolomics provides an opportunity to develop the systematic analysis of the metabolites and has been applied to discovering biomarkers and perturbed pathways which can clarify the action mechanism of traditional Chinese medicines (TCM). TCM is a comprehensive system of medical practice that has been used to diagnose, treat and prevent illnesses more than 3000 years. Metabolomics represents a powerful approach that provides a dynamic picture of the phenotype of biosystems through the study of endogenous metabolites, and its methods resemble those of TCM. Recently, metabolomics tools have been used for facilitating interactional effects of both Western medicine and TCM. We describe a protocol for investigating how metabolomics can be used to open up 'dialogue' between Chinese and Western medicine, and facilitate lead compound discovery and development from TCM. Metabolomics will bridge the cultural gap between TCM and Western medicine and improve development of integrative medicine, and maximally benefiting the human. Copyright © 2014 John Wiley & Sons, Ltd.

  1. Recent advances in liquid and gas chromatography methodology for extending coverage of the metabolome.

    Science.gov (United States)

    Haggarty, Jennifer; Burgess, Karl Ev

    2017-02-01

    The metabolome is the complete complement of metabolites (small organic biomolecules). In order to comprehensively understand the effect of stimuli on a biological system, it is important to detect as many of the metabolites within that system as possible. This review briefly describes some new advances in liquid and gas chromatography to improve coverage of the metabolome, including the serial combination of two columns in tandem, column switching and different variations of two-dimensional chromatography. Supercritical fluid chromatography could provide complimentary data to liquid and gas chromatography. Although there have been many recent advancements in the field of metabolomics, it is evident that a combination, rather than a single method, is required to approach full coverage of the metabolome. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics.

    Science.gov (United States)

    Gika, Helen G; Theodoridis, Georgios A; Plumb, Robert S; Wilson, Ian D

    2014-01-01

    Based on publication and citation numbers liquid chromatography (LC-MS) has become the major analytical technology in the field of global metabolite profiling. This dominance reflects significant investments from both the research community and instrument manufacturers. Here an overview of the approaches taken for LC-MS-based metabolomics research is given, describing critical steps in the realisation of such studies: study design and its needs, specific technological problems to be addressed and major obstacles in data treatment and biomarker identification. The current state of the art for LC-MS-based analysis in metabonomics/metabolomics is described including recent developments in liquid chromatography, mass spectrometry and data treatment as these are applied in metabolomics underlining the challenges, limitations and prospects for metabolomics research. Examples of the application of metabolite profiling in the life sciences focusing on disease biomarker discovery are highlighted. In addition, new developments and future prospects are described. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Increasing rigor in NMR-based metabolomics through validated and open source tools.

    Science.gov (United States)

    Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

    2017-02-01

    The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism's phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. Copyright © 2016. Published by Elsevier Ltd.

  4. The yeast metabolome addressed by electrospray ionization mass spectrometry: Initiation of a mass spectral library and its applications for metabolic footprinting by direct infusion mass spectrometry

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul; Smedsgaard, Jørn; Nielsen, Jens

    2008-01-01

    Mass spectrometry (MS) has been a major driver for metabolomics, and gas chromatography (GC)-MS has been one of the primary techniques used for microbial metabolomics. The use of liquid chromatography (LC)-MS has however been limited, but electrospray ionization (ESI) is very well suited...... for ionization of microbial metabolites without any previous derivatization needed. To address the capabilities of ESI-MS in detecting the metabolome of Saccharomyces cerevisiae, the in silico metabolome of this organism was used as a template to present a theoretical metabolome. This showed that in combination......, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool for extraction of metabolic differences, which can guide new targeted biological...

  5. The next wave in metabolome analysis

    DEFF Research Database (Denmark)

    Nielsen, Jens; Oliver, S.

    2005-01-01

    The metabolome of a cell represents the amplification and integration of signals from other functional genomic levels, such as the transcriptome and the proteome. Although this makes metabolomics a useful tool for the high-throughput analysis of phenotypes, the lack of a direct connection...... to the genome makes it difficult to interpret metabolomic data. Nevertheless, functional genomics has produced examples of the use of metabolomics to elucidate the phenotypes of otherwise silent mutations. Despite several successes, we believe that future metabolomic studies must focus on the accurate...... measurement of the concentrations of unambiguously identified metabolites. The research community must develop databases of metabolite concentrations in cells that are grown in several well-defined conditions if metabolomic data are to be integrated meaningfully with data from the other levels of functional...

  6. Proteomics and Metabolomics: two emerging areas for legume improvement

    Directory of Open Access Journals (Sweden)

    Abirami eRamalingam

    2015-12-01

    Full Text Available The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important source of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signalling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signalling in legumes. In

  7. Optimal preprocessing of serum and urine metabolomic data fusion for staging prostate cancer through design of experiment

    International Nuclear Information System (INIS)

    Zheng, Hong; Cai, Aimin; Zhou, Qi; Xu, Pengtao; Zhao, Liangcai; Li, Chen; Dong, Baijun; Gao, Hongchang

    2017-01-01

    Accurate classification of cancer stages will achieve precision treatment for cancer. Metabolomics presents biological phenotypes at the metabolite level and holds a great potential for cancer classification. Since metabolomic data can be obtained from different samples or analytical techniques, data fusion has been applied to improve classification accuracy. Data preprocessing is an essential step during metabolomic data analysis. Therefore, we developed an innovative optimization method to select a proper data preprocessing strategy for metabolomic data fusion using a design of experiment approach for improving the classification of prostate cancer (PCa) stages. In this study, urine and serum samples were collected from participants at five phases of PCa and analyzed using a 1 H NMR-based metabolomic approach. Partial least squares-discriminant analysis (PLS-DA) was used as a classification model and its performance was assessed by goodness of fit (R 2 ) and predictive ability (Q 2 ). Results show that data preprocessing significantly affect classification performance and depends on data properties. Using the fused metabolomic data from urine and serum, PLS-DA model with the optimal data preprocessing (R 2  = 0.729, Q 2  = 0.504, P < 0.0001) can effectively improve model performance and achieve a better classification result for PCa stages as compared with that without data preprocessing (R 2  = 0.139, Q 2  = 0.006, P = 0.450). Therefore, we propose that metabolomic data fusion integrated with an optimal data preprocessing strategy can significantly improve the classification of cancer stages for precision treatment. - Highlights: • NMR metabolomic analysis of body fluids can be used for staging prostate cancer. • Data preprocessing is an essential step for metabolomic analysis. • Data fusion improves information recovery for cancer classification. • Design of experiment achieves optimal preprocessing of metabolomic data fusion.

  8. Metabolomics as a tool in the identification of dietary biomarkers.

    Science.gov (United States)

    Gibbons, Helena; Brennan, Lorraine

    2017-02-01

    Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

  9. Metabolomics Application in Maternal-Fetal Medicine

    OpenAIRE

    Fanos, Vassilios; Atzori, Luigi; Makarenko, Karina; Melis, Gian Benedetto; Ferrazzi, Enrico

    2013-01-01

    Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, prete...

  10. NMR-based metabolomics reveals urinary metabolome modifications in female Sprague-Dawley rats by cranberry procyanidins.

    Science.gov (United States)

    Liu, Haiyan; Tayyari, Fariba; Edison, Arthur S; Su, Zhihua; Gu, Liwei

    2016-08-01

    A (1)H NMR global metabolomics approach was used to investigate the urinary metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) or partially purified apple procyanidins (PPAP). After collecting 24-h baseline urine, 24 female Sprague-Dawley rats were randomly separated into two groups and gavaged with PPCP or PPAP twice using a dose of 250 mg extracts per kilogram body weight. The 24-h urine samples were collected after the gavage. Urine samples were analyzed using (1)H NMR. Multivariate analyses showed that the urinary metabolome in rats was modified after administering PPCP or PPAP compared to baseline urine metabolic profiles. 2D (1)H-(13)C HSQC NMR was conducted to assist identification of discriminant metabolites. An increase of hippurate, lactate and succinate and a decrease of citrate and α-ketoglutarate were observed in rat urine after administering PPCP. Urinary levels of d-glucose, d-maltose, 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid, formate and phenol increased but citrate, α-ketoglutarate and creatinine decreased in rats after administering PPAP. Furthermore, the NMR analysis showed that the metabolome in the urine of rats administered with PPCP differed from those gavaged with PPAP. Compared to PPAP, PPCP caused an increase of urinary excretion of hippurate but a decrease of 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid and phenol. These metabolome changes caused by cranberry procyanidins may help to explain its reported health benefits and identify biomarkers of cranberry procyanidin intake. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges.

    Science.gov (United States)

    Tokarz, Janina; Haid, Mark; Cecil, Alexander; Prehn, Cornelia; Artati, Anna; Möller, Gabriele; Adamski, Jerzy

    2017-10-01

    The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Functional metabolomics reveals novel active products in the DHA metabolome

    Directory of Open Access Journals (Sweden)

    Masakazu eShinohara

    2012-04-01

    Full Text Available Endogenous mechanisms for successful resolution of an acute inflammatory response and the local return to homeostasis are of interest because excessive inflammation underlies many human diseases. In this review, we provide an update and overview of functional metabolomics that identified a new bioactive metabolome of docosahexaenoic acid (DHA. Systematic studies revealed that DHA was converted to DHEA-derived novel bioactive products as well as aspirin-triggered (AT forms of protectins. The new oxygenated DHEA derived products blocked PMN chemotaxis, reduced P-selectin expression and platelet-leukocyte adhesion, and showed organ protection in ischemia/reperfusion injury. These products activated cannabinoid receptor (CB2 receptor and not CB1 receptors. The AT-PD1 reduced neutrophil (PMN recruitment in murine peritonitis. With human cells, AT-PD1 decreased transendothelial PMN migration as well as enhanced efferocytosis of apoptotic human PMN by macrophages. The recent findings reviewed here indicate that DHEA oxidative metabolism and aspirin-triggered conversion of DHA produce potent novel molecules with anti-inflammatory and organ-protective properties, opening the DHA metabolome functional roles.

  13. An untargeted metabolomic assessment of cocoa beans during fermentation

    OpenAIRE

    Mayorga Gross, Ana Lucía; Quirós Guerrero, Luis Manuel; Fourny, G.; Vaillant Barka, Fabrice

    2016-01-01

    Fermentation is a critical step in the processing of high quality cocoa; however, the biochemistry behind is still not well understood at a molecular level. In this research, using a non-targeted approach, the main metabolomic changes that occur throughout the fermentation process were explored. Genetically undefined cocoa varieties from Trinidad and Tobago (n = 3), Costa Rica (n = 1) and one clone IMC-67 (n = 3) were subjected to spontaneous fermentation using farm-based and pilot plant cont...

  14. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    OpenAIRE

    Hajduk, Joanna; Klupczynska, Agnieszka; Dereziński, Paweł; Matysiak, Jan; Kokot, Piotr; Nowak, Dorota; Gajęcka, Marzena; Nowak-Markwitz, Ewa; Kokot, Zenon

    2015-01-01

    The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid ...

  15. Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

    Science.gov (United States)

    Fijany, Amir; Toomarian, Benny N.

    2000-01-01

    -based architectures for highly parallel and systolic computation of signal/image processing applications, such as FFT and Wavelet and Wlash-Hadamard Transforms.

  16. Metabolomics window into diabetic complications.

    Science.gov (United States)

    Wu, Tao; Qiao, Shuxuan; Shi, Chenze; Wang, Shuya; Ji, Guang

    2018-03-01

    Diabetes has become a major global health problem. The elucidation of characteristic metabolic alterations during the diabetic progression is critical for better understanding its pathogenesis, and identifying potential biomarkers and drug targets. Metabolomics is a promising tool to reveal the metabolic changes and the underlying mechanism involved in the pathogenesis of diabetic complications. The present review provides an update on the application of metabolomics in diabetic complications, including diabetic coronary artery disease, diabetic nephropathy, diabetic retinopathy and diabetic neuropathy, and this review provides notes on the prevention and prediction of diabetic complications. © 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

  17. Metabolomics techniques for nanotoxicity investigations.

    Science.gov (United States)

    Lv, Mengying; Huang, Wanqiu; Chen, Zhipeng; Jiang, Hulin; Chen, Jiaqing; Tian, Yuan; Zhang, Zunjian; Xu, Fengguo

    2015-01-01

    Nanomaterials are commonly defined as engineered structures with at least one dimension of 100 nm or less. Investigations of their potential toxicological impact on biological systems and the environment have yet to catch up with the rapid development of nanotechnology and extensive production of nanoparticles. High-throughput methods are necessary to assess the potential toxicity of nanoparticles. The omics techniques are well suited to evaluate toxicity in both in vitro and in vivo systems. Besides genomic, transcriptomic and proteomic profiling, metabolomics holds great promises for globally evaluating and understanding the molecular mechanism of nanoparticle-organism interaction. This manuscript presents a general overview of metabolomics techniques, summarizes its early application in nanotoxicology and finally discusses opportunities and challenges faced in nanotoxicology.

  18. In vivo cardiac glucose metabolism in the high-fat fed mouse: Comparison of euglycemic–hyperinsulinemic clamp derived measures of glucose uptake with a dynamic metabolomic flux profiling approach

    International Nuclear Information System (INIS)

    Kowalski, Greg M.; De Souza, David P.; Risis, Steve; Burch, Micah L.; Hamley, Steven; Kloehn, Joachim; Selathurai, Ahrathy; Lee-Young, Robert S.; Tull, Dedreia; O'Callaghan, Sean; McConville, Malcolm J.; Bruce, Clinton R.

    2015-01-01

    resistance. • Clamp measures were compared to a dynamic metabolomics approach. • The clamp revealed the presence of cardiac insulin resistance after 3 weeks of HFD. • Cardiac glucose metabolism was not affected by HFD during an oral glucose challenge

  19. In vivo cardiac glucose metabolism in the high-fat fed mouse: Comparison of euglycemic–hyperinsulinemic clamp derived measures of glucose uptake with a dynamic metabolomic flux profiling approach

    Energy Technology Data Exchange (ETDEWEB)

    Kowalski, Greg M., E-mail: greg.kowalski@deakin.edu.au [Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria 3125 (Australia); De Souza, David P. [Metabolomics Australia, Department of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Parkville, Victoria 3010 (Australia); Risis, Steve [Cellular and Molecular Metabolism Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004 (Australia); Burch, Micah L. [Brigham and Women' s Hospital, Department of Medicine, Boston, MA (United States); Hamley, Steven [Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria 3125 (Australia); Kloehn, Joachim [Metabolomics Australia, Department of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Parkville, Victoria 3010 (Australia); Selathurai, Ahrathy [Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria 3125 (Australia); Lee-Young, Robert S. [Cellular and Molecular Metabolism Laboratory, Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004 (Australia); Tull, Dedreia; O' Callaghan, Sean; McConville, Malcolm J. [Metabolomics Australia, Department of Biochemistry and Molecular Biology, Bio21 Institute of Molecular Science and Biotechnology, University of Melbourne, Parkville, Victoria 3010 (Australia); Bruce, Clinton R. [Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Burwood, Victoria 3125 (Australia)

    2015-08-07

    insulin resistance. • Clamp measures were compared to a dynamic metabolomics approach. • The clamp revealed the presence of cardiac insulin resistance after 3 weeks of HFD. • Cardiac glucose metabolism was not affected by HFD during an oral glucose challenge.

  20. Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

    Science.gov (United States)

    Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

    2016-01-01

    Metabolomics, along with other “omics” approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data. PMID:27231903

  1. The future of metabolomics in ELIXIR

    Science.gov (United States)

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. PMID:29043062

  2. The future of metabolomics in ELIXIR.

    Science.gov (United States)

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  3. Symbiosis of chemometrics and metabolomics: past, present, and future

    NARCIS (Netherlands)

    van der Greef, J.; Smilde, A. K.

    2005-01-01

    Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the

  4. Urinary Metabolomics Identifies a Molecular Correlate of Interstitial Cystitis/Bladder Pain Syndrome in a Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP Research Network Cohort

    Directory of Open Access Journals (Sweden)

    Kaveri S. Parker

    2016-05-01

    Full Text Available Interstitial cystitis/bladder pain syndrome (IC/BPS is a poorly understood syndrome affecting up to 6.5% of adult women in the U.S. The lack of broadly accepted objective laboratory markers for this condition hampers efforts to diagnose and treat this condition. To identify biochemical markers for IC/BPS, we applied mass spectrometry-based global metabolite profiling to urine specimens from a cohort of female IC/BPS subjects from the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP Research Network. These analyses identified multiple metabolites capable of discriminating IC/BPS and control subjects. Of these candidate markers, etiocholan-3α-ol-17-one sulfate (Etio-S, a sulfoconjugated 5-β reduced isomer of testosterone, distinguished female IC/BPS and control subjects with a sensitivity and specificity >90%. Among IC/BPS subjects, urinary Etio-S levels are correlated with elevated symptom scores (symptoms, pelvic pain, and number of painful body sites and could resolve high- from low-symptom IC/BPS subgroups. Etio-S-associated biochemical changes persisted through 3–6 months of longitudinal follow up. These results raise the possibility that an underlying biochemical abnormality contributes to symptoms in patients with severe IC/BPS.

  5. Distribution patterns of flavonoids from three Momordica species by ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry: a metabolomic profiling approach

    Directory of Open Access Journals (Sweden)

    Ntakadzeni Edwin Madala

    Full Text Available ABSTRACT Plants from the Momordica genus, Curcubitaceae, are used for several purposes, especially for their nutritional and medicinal properties. Commonly known as bitter gourds, melon and cucumber, these plants are characterized by a bitter taste owing to the large content of cucurbitacin compounds. However, several reports have shown an undisputed correlation between the therapeutic activities and polyphenolic flavonoid content. Using ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry in combination with multivariate data models such as principal component analysis and hierarchical cluster analysis, three Momordica species (M. foetida Schumach., M. charantia L. and M. balsamina L. were chemo-taxonomically grouped based on their flavonoid content. Using a conventional mass spectrometric-based approach, thirteen flavonoids were tentatively identified and the three species were found to contain different isomers of the quercetin-, kaempferol- and isorhamnetin-O-glycosides. Our results indicate that Momordica species are overall very rich sources of flavonoids but do contain different forms thereof. Furthermore, to the best of our knowledge, this is a first report on the flavonoid content of M. balsamina L.

  6. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    Directory of Open Access Journals (Sweden)

    Joanna Hajduk

    2015-12-01

    Full Text Available The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18 and a matched control group (n = 13. The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44% and specificity (84.62%, as well as the total group membership classification value (90.32% calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

  7. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  8. Challenges of inversely estimating Jacobian from metabolomics data

    Directory of Open Access Journals (Sweden)

    Xiaoliang eSun

    2015-11-01

    Full Text Available Inferring dynamics of metabolic networks directly from metabolomics data provides a promising way to elucidate the underlying mechanisms of biological systems, as reported in our previous studies [1-3] by a differential Jacobian approach. The Jacobian is solved from an over-determined system of equations as JC + CJT = -2D, called Lyapunov Equation in its generic form , where J is the Jacobian, C is the covariance matrix of metabolomics data and D is the fluctuation matrix. Lyapunov Equation can be further simplified as the linear form Ax = b. Frequently, this linear equation system is ill-conditioned, i.e., a small variation in the right side b results in a big change in the solution x, thus making the solution unstable and error-prone. At the same time, inaccurate estimation of covariance matrix and uncertainties in the fluctuation matrix bring biases to the solution x. Here, we firstly reviewed common approaches to circumvent the ill-conditioned problems, including total least squares, Tikhonov regularization and truncated singular value decomposition. Then we benchmarked these methods on several in-silico kinetic models with small to large perturbations on the covariance and fluctuation matrices. The results identified that the accuracy of the reverse Jacobian is mainly dependent on the condition number of A, the perturbation amplitude of C and the stiffness of the kinetic models. Our research contributes a systematical comparison of methods to inversely solve Jacobian from metabolomics data.

  9. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

    Metabolomic analysis of plants broadens understanding of how plants may benefit humans, animals and the environment, provide sustainable food and energy, and improve current agricultural, pharmacological and medicinal practices in order to bring about healthier and longer life. The quality...... and amount of the extractible biological information is largely determined by data acquisition, data processing and analysis methodologies of the plant metabolomics studies. This PhD study focused mainly on the development and implementation of new metabolomics methodologies for improved data acquisition...... and data processing. The study mainly concerned the three most commonly applied analytical techniques in plant metabolomics, GC-MS, LC-MS and NMR. In addition, advanced chemometrics methods e.g. PARAFAC2 and ASCA have been extensively used for development of complex metabolomics data processing...

  10. A Metabolomic Perspective on Coeliac Disease

    Science.gov (United States)

    Calabrò, Antonio

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

  11. Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods

    Energy Technology Data Exchange (ETDEWEB)

    Bingol, Kerem

    2018-04-18

    Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome manual absolute quantitation step of metabolites in 1D 1H NMR spectra. This provides more consistency between inter-laboratory comparisons. Integration of 2D NMR metabolomics databases under a unified web server allowed very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry. These hybrid NMR/MS approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing to profile ever larger number of metabolites in application studies.

  12. Using next generation transcriptome sequencing to predict an ectomycorrhizal metabolome

    Directory of Open Access Journals (Sweden)

    Cseke Leland J

    2011-05-01

    Full Text Available Abstract Background Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. Results We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides roots. The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. Conclusions The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.

  13. Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow.

    Science.gov (United States)

    Volani, Chiara; Caprioli, Giulia; Calderisi, Giovanni; Sigurdsson, Baldur B; Rainer, Johannes; Gentilini, Ivo; Hicks, Andrew A; Pramstaller, Peter P; Weiss, Guenter; Smarason, Sigurdur V; Paglia, Giuseppe

    2017-10-01

    Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. In this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. The latter revealed that

  14. Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D.A. Webb) skin polyphenols.

    Science.gov (United States)

    Llorach, Rafael; Garrido, Ignacio; Monagas, Maria; Urpi-Sarda, Mireia; Tulipani, Sara; Bartolome, Begona; Andres-Lacueva, Cristina

    2010-11-05

    Almond, as a part of the nut family, is an important source of biological compounds, and specifically, almond skins have been considered an important source of polyphenols, including flavan-3-ols and flavonols. Polyphenol metabolism may produce several classes of metabolites that could often be more biologically active than their dietary precursor and could also become a robust new biomarker of almond polyphenol intake. In order to study urinary metabolome modifications during the 24 h after a single dose of almond skin extract, 24 volunteers (n = 24), who followed a polyphenol-free diet for 48 h before and during the study, ingested a dietary supplement of almond skin phenolic compounds (n = 12) or a placebo (n = 12). Urine samples were collected before ((-2)-0 h) and after (0-2 h, 2-6 h, 6-10 h, and 10-24 h) the intake and were analyzed by liquid chromatography-mass spectrometry (LC-q-TOF) and multivariate statistical analysis (principal component analysis (PCA) and orthogonal projection to latent structures (OPLS)). Putative identification of relevant biomarkers revealed a total of 34 metabolites associated with the single dose of almond extract, including host and, in particular, microbiota metabolites. As far as we know, this is the first time that conjugates of hydroxyphenylvaleric, hydroxyphenylpropionic, and hydroxyphenylacetic acids have been identified in human samples after the consumption of flavan-3-ols through a metabolomic approach. The results showed that this non-targeted approach could provide new intake biomarkers, contributing to the development of the food metabolome as an important part of the human urinary metabolome.

  15. Metabolomics enables precision medicine: "A White Paper, Community Perspective".

    Science.gov (United States)

    Beger, Richard D; Dunn, Warwick; Schmidt, Michael A; Gross, Steven S; Kirwan, Jennifer A; Cascante, Marta; Brennan, Lorraine; Wishart, David S; Oresic, Matej; Hankemeier, Thomas; Broadhurst, David I; Lane, Andrew N; Suhre, Karsten; Kastenmüller, Gabi; Sumner, Susan J; Thiele, Ines; Fiehn, Oliver; Kaddurah-Daouk, Rima

    Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.

  16. Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

    Science.gov (United States)

    Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

    2017-12-01

    Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors

    OpenAIRE

    Vázquez Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez Martínez, Miguel Ángel; Vinaixa Crevillent, Maria; Chiva Blanch, Gemma; Estruch Riba, Ramon; Correig Blanchar, Xavier; Andrés Lacueva, Ma. Cristina

    2012-01-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100m...

  18. Metabolomics in cancer biomarker discovery: current trends and future perspectives.

    Science.gov (United States)

    Armitage, Emily G; Barbas, Coral

    2014-01-01

    Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.

  19. NMR metabolomics of thrips (Frankliniella occidentalis) resistance in Senecio hybrids.

    Science.gov (United States)

    Leiss, Kirsten A; Choi, Young H; Abdel-Farid, Ibrahim B; Verpoorte, Robert; Klinkhamer, Peter G L

    2009-02-01

    Western flower thrips (Frankliniella occidentalis) has become a key insect pest of agricultural and horticultural crops worldwide. Little is known about host plant resistance to thrips. In this study, we investigated thrips resistance in F (2) hybrids of Senecio jacobaea and Senecio aquaticus. We identified thrips-resistant hybrids applying three different bioassays. Subsequently, we compared the metabolomic profiles of these hybrids applying nuclear magnetic resonance spectroscopy (NMR). The new developments of NMR facilitate a wide range coverage of the metabolome. This makes NMR especially suitable if there is no a priori knowledge of the compounds related to herbivore resistance and allows a holistic approach analyzing different chemical compounds simultaneously. We show that the metabolomes of thrips-resistant and -susceptible hybrids differed considerably. Thrips-resistant hybrids contained higher amounts of the pyrrolizidine alkaloids (PA), jacobine, and jaconine, especially in younger leaves. Also, a flavanoid, kaempferol glucoside, accumulated in the resistant plants. Both PAs and kaempferol are known for their inhibitory effect on herbivores. In resistant and susceptible F (2) hybrids, young leaves showed less thrips damage than old leaves. Consistent with the optimal plant defense theory, young leaves contained increased levels of primary metabolites such as sucrose, raffinose, and stachyose, but also accumulated jacaranone as a secondary plant defense compound. Our results prove NMR as a promising tool to identify different metabolites involved in herbivore resistance. It constitutes a significant advance in the study of plant-insect relationships, providing key information on the implementation of herbivore resistance breeding strategies in plants.

  20. Salivary microbiota and metabolome associated with celiac disease.

    Science.gov (United States)

    Francavilla, Ruggiero; Ercolini, Danilo; Piccolo, Maria; Vannini, Lucia; Siragusa, Sonya; De Filippis, Francesca; De Pasquale, Ilaria; Di Cagno, Raffaella; Di Toma, Michele; Gozzi, Giorgia; Serrazanetti, Diana I; De Angelis, Maria; Gobbetti, Marco

    2014-06-01

    This study aimed to investigate the salivary microbiota and metabolome of 13 children with celiac disease (CD) under a gluten-free diet (treated celiac disease [T-CD]). The same number of healthy children (HC) was used as controls. The salivary microbiota was analyzed by an integrated approach using culture-dependent and -independent methods. Metabolome analysis was carried out by gas chromatography-mass spectrometry-solid-phase microextraction. Compared to HC, the number of some cultivable bacterial groups (e.g., total anaerobes) significantly (P endodontalis, and Prevotella nanceiensis), together with the smallest amount of Actinobacteria. T-CD children were also characterized by decreased levels of some Actinomyces species, Atopobium species, and Corynebacterium durum. Rothia mucilaginosa was the only Actinobacteria species found at the highest level in T-CD children. As shown by multivariate statistical analyses, the levels of organic volatile compounds markedly differentiated T-CD children. Some compounds (e.g., ethyl-acetate, nonanal, and 2-hexanone) were found to be associated with T-CD children. Correlations (false discovery rate [FDR], oral dysbiosis that could affect the oral metabolome.

  1. Metabolomics to unveil and understand phenotypic diversity between pathogen populations.

    Directory of Open Access Journals (Sweden)

    Ruben t'Kindt

    Full Text Available Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.

  2. Variable selection methods in PLS regression - a comparison study on metabolomics data

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

    . The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

  3. Convergence of highly parallel stray field calculation using the fast multipole method on irregular meshes

    Science.gov (United States)

    Palmesi, P.; Abert, C.; Bruckner, F.; Suess, D.

    2018-05-01

    Fast stray field calculation is commonly considered of great importance for micromagnetic simulations, since it is the most time consuming part of the simulation. The Fast Multipole Method (FMM) has displayed linear O(N) parallelization behavior on many cores. This article investigates the error of a recent FMM approach approximating sources using linear—instead of constant—finite elements in the singular integral for calculating the stray field and the corresponding potential. After measuring performance in an earlier manuscript, this manuscript investigates the convergence of the relative L2 error for several FMM simulation parameters. Various scenarios either calculating the stray field directly or via potential are discussed.

  4. Highly parallel demagnetization field calculation using the fast multipole method on tetrahedral meshes with continuous sources

    Science.gov (United States)

    Palmesi, P.; Exl, L.; Bruckner, F.; Abert, C.; Suess, D.

    2017-11-01

    The long-range magnetic field is the most time-consuming part in micromagnetic simulations. Computational improvements can relieve problems related to this bottleneck. This work presents an efficient implementation of the Fast Multipole Method [FMM] for the magnetic scalar potential as used in micromagnetics. The novelty lies in extending FMM to linearly magnetized tetrahedral sources making it interesting also for other areas of computational physics. We treat the near field directly and in use (exact) numerical integration on the multipole expansion in the far field. This approach tackles important issues like the vectorial and continuous nature of the magnetic field. By using FMM the calculations scale linearly in time and memory.

  5. The One-node CMFD Computational Framework for Highly Parallel Reactor Analysis

    International Nuclear Information System (INIS)

    Kim, Yong Hee

    2016-01-01

    This paper presents one such possible approach named the One-Node and Two-Node Hybrid CMFD method; One-Node CMFD is used to solve the global problem, while Two-Node NEM (Nodal Expansion Method) CMFD replaces FMFD as the local problem. Rapid advancement in computing capabilities has enabled the pursuit for high-fidelity tools in analyzing the reactor configurations. One such tool that gains a lot of recent attention is the pin-by-pin core calculation via local-global iteration with nonlinear acceleration scheme. One-Node CMFD method uses two correction terms to preserve the interface current and flux, in contrast to one correction term employed by conventional nonlinear iterative method proposed. With two correction terms, One-Node CMFD can reduce computing time of local FMFD (Fine-Mesh Finite Difference) as it nonlinearly couples the CMFD and FMFD methods in global-local iterations. Nonetheless, retrieving the pinlevel information from the local FMFD is very time consuming. As such, a more flexible approach is needed to address this challenge.

  6. Metagenomic and metabolomic analysis of the toxic effects of trichloroacetamide-induced gut microbiome and urine metabolome perturbations in mice.

    Science.gov (United States)

    Zhang, Yan; Zhao, Fuzheng; Deng, Yongfeng; Zhao, Yanping; Ren, Hongqiang

    2015-04-03

    Disinfection byproducts (DBPs) in drinking water have been linked to various diseases, including colon, colorectal, rectal, and bladder cancer. Trichloroacetamide (TCAcAm) is an emerging nitrogenous DBP, and our previous study found that TCAcAm could induce some changes associated with host-gut microbiota co-metabolism. In this study, we used an integrated approach combining metagenomics, based on high-throughput sequencing, and metabolomics, based on nuclear magnetic resonance (NMR), to evaluate the toxic effects of TCAcAm exposure on the gut microbiome and urine metabolome. High-throughput sequencing revealed that the gut microbiome's composition and function were significantly altered after TCAcAm exposure for 90 days in Mus musculus mice. In addition, metabolomic analysis showed that a number of gut microbiota-related metabolites were dramatically perturbed in the urine of the mice. These results may provide novel insight into evaluating the health risk of environmental pollutants as well as revealing the potential mechanism of TCAcAm's toxic effects.

  7. Metabolomics applied to the pancreatic islet.

    Science.gov (United States)

    Gooding, Jessica R; Jensen, Mette V; Newgard, Christopher B

    2016-01-01

    Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Quartic scaling MP2 for solids: A highly parallelized algorithm in the plane wave basis

    Science.gov (United States)

    Schäfer, Tobias; Ramberger, Benjamin; Kresse, Georg

    2017-03-01

    We present a low-complexity algorithm to calculate the correlation energy of periodic systems in second-order Møller-Plesset (MP2) perturbation theory. In contrast to previous approximation-free MP2 codes, our implementation possesses a quartic scaling, O ( N 4 ) , with respect to the system size N and offers an almost ideal parallelization efficiency. The general issue that the correlation energy converges slowly with the number of basis functions is eased by an internal basis set extrapolation. The key concept to reduce the scaling is to eliminate all summations over virtual orbitals which can be elegantly achieved in the Laplace transformed MP2 formulation using plane wave basis sets and fast Fourier transforms. Analogously, this approach could allow us to calculate second order screened exchange as well as particle-hole ladder diagrams with a similar low complexity. Hence, the presented method can be considered as a step towards systematically improved correlation energies.

  9. Implementation of highly parallel and large scale GW calculations within the OpenAtom software

    Science.gov (United States)

    Ismail-Beigi, Sohrab

    The need to describe electronic excitations with better accuracy than provided by band structures produced by Density Functional Theory (DFT) has been a long-term enterprise for the computational condensed matter and materials theory communities. In some cases, appropriate theoretical frameworks have existed for some time but have been difficult to apply widely due to computational cost. For example, the GW approximation incorporates a great deal of important non-local and dynamical electronic interaction effects but has been too computationally expensive for routine use in large materials simulations. OpenAtom is an open source massively parallel ab initiodensity functional software package based on plane waves and pseudopotentials (http://charm.cs.uiuc.edu/OpenAtom/) that takes advantage of the Charm + + parallel framework. At present, it is developed via a three-way collaboration, funded by an NSF SI2-SSI grant (ACI-1339804), between Yale (Ismail-Beigi), IBM T. J. Watson (Glenn Martyna) and the University of Illinois at Urbana Champaign (Laxmikant Kale). We will describe the project and our current approach towards implementing large scale GW calculations with OpenAtom. Potential applications of large scale parallel GW software for problems involving electronic excitations in semiconductor and/or metal oxide systems will be also be pointed out.

  10. Metabolomics in Population-Based Research

    Science.gov (United States)

    Metabolomics is the study of small molecules of both endogenous and exogenous origin, such as metabolic substrates and their products, lipids, small peptides, vitamins and other protein cofactors generated by metabolism, which are downstream from genes.

  11. Metabolomics Application in Maternal-Fetal Medicine

    Directory of Open Access Journals (Sweden)

    Vassilios Fanos

    2013-01-01

    Full Text Available Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

  12. Mass Spectrometry Strategies for Clinical Metabolomics and Lipidomics in Psychiatry, Neurology, and Neuro-Oncology

    Science.gov (United States)

    Wood, Paul L

    2014-01-01

    Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed. PMID:23842599

  13. Sweat: a sample with limited present applications and promising future in metabolomics.

    Science.gov (United States)

    Mena-Bravo, A; Luque de Castro, M D

    2014-03-01

    Sweat is a biofluid with present scant use as clinical sample. This review tries to demonstrate the advantages of sweat over other biofluids such as blood or urine for routine clinical analyses and the potential when related to metabolomics. With this aim, critical discussion of sweat samplers and equipment for analysis of target compounds in this sample is made. Well established routine analyses in sweat as is that to diagnose cystic fibrosis, and the advantages and disadvantages of sweat versus urine or blood for doping control have also been discussed. Methods for analytes such as essential metals and xenometals, ethanol and electrolytes in sweat in fact constitute target metabolomics approaches or belong to any metabolomics subdiscipline such as metallomics, ionomics or xenometabolomics. The higher development of biomarkers based on genomics or proteomics as omics older than metabolomics is discussed and also the potential role of metabolomics in systems biology taking into account its emergent implementation. Normalization of the volume of sampled sweat constitutes a present unsolved shortcoming that deserves investigation. Foreseeable trends in this area are outlined. Copyright © 2013 Elsevier B.V. All rights reserved.

  14. Characterizing Alzheimer's disease through metabolomics and investigating anti-Alzheimer's disease effects of natural products.

    Science.gov (United States)

    Yi, Lunzhao; Liu, Wenbin; Wang, Zhe; Ren, Dabing; Peng, Weijun

    2017-06-01

    Alzheimer's disease (AD) is the most common cause of dementia in elderly people and is among the greatest healthcare challenges of the 21st century. However, the etiology and pathogenesis of AD remain poorly understood, and no curative treatments are available to slow down or stop the degenerative effects of AD. As a high-throughput approach, metabolomics is gaining significant attention in AD research, because it has a powerful potential to discover novel biomarkers, unravel new therapeutic targets for AD, and identify perturbed metabolic pathways involved in AD progression. Here, we systematically review metabolomics with regard to its recent advances and applications in the identification of potential biomarkers for early AD diagnosis and pathogenesis research. In addition, we illustrate the developments in metabolomics as an effective tool for understanding the anti-AD mechanisms of natural products. We believe that the insights from these advances can narrow the gap between metabolomics research and clinical applications of laboratory findings. Moreover, we discuss some limitations and perspectives of biomarker identification in metabolomics. © 2017 New York Academy of Sciences.

  15. CE-MS for metabolomics: developments and applications in the period 2012-2014.

    Science.gov (United States)

    Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

    2015-01-01

    In the field of metabolomics, CE-MS is now regarded as a useful complementary analytical technique for the profiling of (highly) polar ionogenic metabolites in biological samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolic profiling studies. This paper, which is a follow-up of three previous review papers covering the years 2000-2012 [Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65; Electrophoresis 2013, 34, 86-98], provides an update of these developments covering the scientific literature from July 2012 to June 2014. Attention will be paid to novel interfacing techniques for coupling CE to MS and their implications for metabolomics studies. The potential of CEC-MS and MEKC-MS are also considered, and CE-MS systems for high-throughput metabolic profiling are discussed. The applicability of CE-MS for metabolomics studies is demonstrated by representative examples in the fields of biomedical, clinical, microbial, plant, environmental, and food metabolomics. An overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Feline urine metabolomic signature: characterization of low-molecular-weight substances in urine from domestic cats.

    Science.gov (United States)

    Rivera-Vélez, Sol-Maiam; Villarino, Nicolas F

    2018-02-01

    Objectives This aim of this study was to characterize the composition and content of the feline urine metabolome. Methods Eight healthy domestic cats were acclimated at least 10 days before starting the study. Urine samples (~2 ml) were collected by ultrasound-guided cystocentesis. Samples were centrifuged at 1000 × g for 8 mins, and the supernatant was analyzed by gas chromatography/time-of-flight mass spectrometery. The urine metabolome was characterized using an untargeted metabolomics approach. Results Three hundred and eighteen metabolites were detected in the urine of the eight cats. These molecules are key components of at least 100 metabolic pathways. Feline urine appears to be dominated by carbohydrates, carbohydrate conjugates, organic acid and derivatives, and amino acids and analogs. The five most abundant molecules were phenaceturic acid, hippuric acid, pseudouridine phosphate and 3-(4-hydroxyphenyl) propionic acid. Conclusions and relevance This study is the first to characterize the feline urine metabolome. The results of this study revealed the presence of multiple low-molecular-weight substances that were not known to be present in feline urine. As expected, the origin of the metabolites detected in urine was diverse, including endogenous compounds and molecules biosynthesized by microbes. Also, the diet seemed to have had a relevant role on the urine metabolome. Further exploration of the urine metabolic phenotype will open a window for discovering unknown, or poorly understood, metabolic pathways. In turn, this will advance our understanding of feline biology and lead to new insights in feline physiology, nutrition and medicine.

  17. Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology.

    Science.gov (United States)

    Wood, Paul L

    2014-01-01

    Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed.

  18. Arbuscular Mycorrhizal Fungi and Plant Chemical Defence: Effects of Colonisation on Aboveground and Belowground Metabolomes.

    Science.gov (United States)

    Hill, Elizabeth M; Robinson, Lynne A; Abdul-Sada, Ali; Vanbergen, Adam J; Hodge, Angela; Hartley, Sue E

    2018-02-01

    Arbuscular mycorrhizal fungal (AMF) colonisation of plant roots is one of the most ancient and widespread interactions in ecology, yet the systemic consequences for plant secondary chemistry remain unclear. We performed the first metabolomic investigation into the impact of AMF colonisation by Rhizophagus irregularis on the chemical defences, spanning above- and below-ground tissues, in its host-plant ragwort (Senecio jacobaea). We used a non-targeted metabolomics approach to profile, and where possible identify, compounds induced by AMF colonisation in both roots and shoots. Metabolomics analyses revealed that 33 compounds were significantly increased in the root tissue of AMF colonised plants, including seven blumenols, plant-derived compounds known to be associated with AMF colonisation. One of these was a novel structure conjugated with a malonyl-sugar and uronic acid moiety, hitherto an unreported combination. Such structural modifications of blumenols could be significant for their previously reported functional roles associated with the establishment and maintenance of AM colonisation. Pyrrolizidine alkaloids (PAs), key anti-herbivore defence compounds in ragwort, dominated the metabolomic profiles of root and shoot extracts. Analyses of the metabolomic profiles revealed an increase in four PAs in roots (but not shoots) of AMF colonised plants, with the potential to protect colonised plants from below-ground organisms.

  19. RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Xu, Julia; Schrübbers, Lars

    2018-01-01

    Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated...... to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics...

  20. Conventional and Advanced Separations in Mass Spectrometry-Based Metabolomics: Methodologies and Applications

    Energy Technology Data Exchange (ETDEWEB)

    Heyman, Heino M.; Zhang, Xing; Tang, Keqi; Baker, Erin Shammel; Metz, Thomas O.

    2016-02-16

    Metabolomics is the quantitative analysis of all metabolites in a given sample. Due to the chemical complexity of the metabolome, optimal separations are required for comprehensive identification and quantification of sample constituents. This chapter provides an overview of both conventional and advanced separations methods in practice for reducing the complexity of metabolite extracts delivered to the mass spectrometer detector, and covers gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis (CE), supercritical fluid chromatography (SFC) and ion mobility spectrometry (IMS) separation techniques coupled with mass spectrometry (MS) as both uni-dimensional and as multi-dimensional approaches.

  1. Sample normalization methods in quantitative metabolomics.

    Science.gov (United States)

    Wu, Yiman; Li, Liang

    2016-01-22

    To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Metabolomics and Integrative Omics for the Development of Thai Traditional Medicine

    Science.gov (United States)

    Khoomrung, Sakda; Wanichthanarak, Kwanjeera; Nookaew, Intawat; Thamsermsang, Onusa; Seubnooch, Patcharamon; Laohapand, Tawee; Akarasereenont, Pravit

    2017-01-01

    In recent years, interest in studies of traditional medicine in Asian and African countries has gradually increased due to its potential to complement modern medicine. In this review, we provide an overview of Thai traditional medicine (TTM) current development, and ongoing research activities of TTM related to metabolomics. This review will also focus on three important elements of systems biology analysis of TTM including analytical techniques, statistical approaches and bioinformatics tools for handling and analyzing untargeted metabolomics data. The main objective of this data analysis is to gain a comprehensive understanding of the system wide effects that TTM has on individuals. Furthermore, potential applications of metabolomics and systems medicine in TTM will also be discussed. PMID:28769804

  3. An introduction to metabolomics and its potential application in veterinary science.

    Science.gov (United States)

    Jones, Oliver A H; Cheung, Victoria L

    2007-10-01

    Metabolomics has been found to be applicable to a wide range of fields, including the study of gene function, toxicology, plant sciences, environmental analysis, clinical diagnostics, nutrition, and the discrimination of organism genotypes. This approach combines high-throughput sample analysis with computer-assisted multivariate pattern-recognition techniques. It is increasingly being deployed in toxico- and pharmacokinetic studies in the pharmaceutical industry, especially during the safety assessment of candidate drugs in human medicine. However, despite the potential of this technique to reduce both costs and the numbers of animals used for research, examples of the application of metabolomics in veterinary research are, thus far, rare. Here we give an introduction to metabolomics and discuss its potential in the field of veterinary science.

  4. Parallelization of MCNP 4, a Monte Carlo neutron and photon transport code system, in highly parallel distributed memory type computer

    International Nuclear Information System (INIS)

    Masukawa, Fumihiro; Takano, Makoto; Naito, Yoshitaka; Yamazaki, Takao; Fujisaki, Masahide; Suzuki, Koichiro; Okuda, Motoi.

    1993-11-01

    In order to improve the accuracy and calculating speed of shielding analyses, MCNP 4, a Monte Carlo neutron and photon transport code system, has been parallelized and measured of its efficiency in the highly parallel distributed memory type computer, AP1000. The code has been analyzed statically and dynamically, then the suitable algorithm for parallelization has been determined for the shielding analysis functions of MCNP 4. This includes a strategy where a new history is assigned to the idling processor element dynamically during the execution. Furthermore, to avoid the congestion of communicative processing, the batch concept, processing multi-histories by a unit, has been introduced. By analyzing a sample cask problem with 2,000,000 histories by the AP1000 with 512 processor elements, the 82 % of parallelization efficiency is achieved, and the calculational speed has been estimated to be around 50 times as fast as that of FACOM M-780. (author)

  5. Integration of metabolomics and transcriptomics in nanotoxicity studies.

    Science.gov (United States)

    Shin, Tae Hwan; Lee, Da Yeon; Lee, Hyeon-Seong; Park, Hyung Jin; Jin, Moon Suk; Paik, Man-Jeong; Manavalan, Balachandran; Mo, Jung-Soon; Lee, Gwang

    2018-01-01

    Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics". [BMB Reports 2018; 51(1): 14-20].

  6. MetabR: an R script for linear model analysis of quantitative metabolomic data

    Directory of Open Access Journals (Sweden)

    Ernest Ben

    2012-10-01

    Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

  7. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

    Directory of Open Access Journals (Sweden)

    Ana Rita Lima

    2016-08-01

    Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

  8. The volatile metabolome and microbiome in pulmonary and gastro-intestinal disease

    NARCIS (Netherlands)

    van der Schee, M.P.C.

    2015-01-01

    Omics-technologies allow detailed characterization of biochemical molecular families enabling data-driven and hypothesis-generating research. In this thesis we explore potential merits and pitfalls of such an approach by studying the volatile metabolome and microbiome in disease diagnosis,

  9. A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers

    NARCIS (Netherlands)

    Vehof, Jelle; Hysi, Pirro G.; Hammond, Christopher J.

    Purpose: To test the association between serum metabolites and dry eye disease (DED) using a hypothesisfree metabolomics approach. Design: Cross-sectional association study. Participants: A total of 2819 subjects from the population-representative TwinsUK cohort in the United Kingdom, with a mean

  10. Metabolomics investigation to shed light on cheese as a possible piece in the French paradox puzzle

    DEFF Research Database (Denmark)

    Zheng, Hong; Yde, Christian C; Clausen, Morten R

    2015-01-01

    An NMR-based metabolomics approach was used to investigate the differentiation between subjects consuming cheese or milk and to elucidate the potential link to an effect on the blood cholesterol level. Fifteen healthy young men participated in a full cross-over study where they consumed three iso...

  11. Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics

    NARCIS (Netherlands)

    Wilmes, Anja; Bielow, Chris; Ranninger, Christina; Bellwon, Patricia; Aschauer, Lydia; Limonciel, Alice; Chassaigne, Hubert; Kristl, Theresa; Aiche, Stephan; Huber, Christian G; Guillou, Claude; Hewitt, Philipp; Leonard, Martin O; Dekant, Wolfgang; Bois, Frederic Y; Jennings, Paul

    2015-01-01

    Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and metabolomics coupled to

  12. Comprehensive metabolomics to evaluate the impact of industrial processing on the phytochemical composition of vegetable purees

    NARCIS (Netherlands)

    Lopez-Sanchez, P.; Vos, de R.C.H.; Jonker, H.H.; Mumm, R.; Hall, R.D.; Bialek, L.; Leenman, R.; Strassburg, K.; Vreeken, R.; Hankemeier, T.; Schumm, S.; Duynhoven, van J.P.M.

    2015-01-01

    The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC–PDA for vitamins, 1H NMR for polar metabolites, accurate

  13. Comprehensive metabolomic profiling and incident cardiovascular disease: a systematic review

    Science.gov (United States)

    Background: Metabolomics is a promising tool of cardiovascular biomarker discovery. We systematically reviewed the literature on comprehensive metabolomic profiling in association with incident cardiovascular disease (CVD). Methods and Results: We searched MEDLINE and EMBASE from inception to Janua...

  14. Plant Metabolomics : the missiong link in functional genomics strategies

    NARCIS (Netherlands)

    Hall, R.D.; Beale, M.; Fiehn, O.; Hardy, N.; Summer, L.; Bino, R.

    2002-01-01

    After the establishment of technologies for high-throughput DNA sequencing (genomics), gene expression analysis (transcriptomics), and protein analysis (proteomics), the remaining functional genomics challenge is that of metabolomics. Metabolomics is the term coined for essentially comprehensive,

  15. A 1H NMR-based metabolomics approach to evaluate the geographical authenticity of herbal medicine and its application in building a model effectively assessing the mixing proportion of intentional admixtures: A case study of Panax ginseng: Metabolomics for the authenticity of herbal medicine.

    Science.gov (United States)

    Nguyen, Huy Truong; Lee, Dong-Kyu; Choi, Young-Geun; Min, Jung-Eun; Yoon, Sang Jun; Yu, Yun-Hyun; Lim, Johan; Lee, Jeongmi; Kwon, Sung Won; Park, Jeong Hill

    2016-05-30

    Ginseng, the root of Panax ginseng has long been the subject of adulteration, especially regarding its origins. Here, 60 ginseng samples from Korea and China initially displayed similar genetic makeup when investigated by DNA-based technique with 23 chloroplast intergenic space regions. Hence, (1)H NMR-based metabolomics with orthogonal projections on the latent structure-discrimination analysis (OPLS-DA) were applied and successfully distinguished between samples from two countries using seven primary metabolites as discrimination markers. Furthermore, to recreate adulteration in reality, 21 mixed samples of numerous Korea/China ratios were tested with the newly built OPLS-DA model. The results showed satisfactory separation according to the proportion of mixing. Finally, a procedure for assessing mixing proportion of intentionally blended samples that achieved good predictability (adjusted R(2)=0.8343) was constructed, thus verifying its promising application to quality control of herbal foods by pointing out the possible mixing ratio of falsified samples. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    fusion where data from different platforms can be combined. Complex data are obtained when samples are analysed using NMR, fluorescence and GC-MS. Chemometrics methods which can be used to extract the relevant information from the obtained data are presented. Focus has been on principal component...... based on NMR data with RRV and known risk markers. The sensitivity and specificity values are 0.80 and 0.79, respectively, for a test set validated model. The second case study is based on plasma samples with verified colorectal cancer and three types of control samples analysed by fluorescence...

  17. The human plasma-metabolome: Reference values in 800 French healthy volunteers; impact of cholesterol, gender and age.

    Science.gov (United States)

    Trabado, Séverine; Al-Salameh, Abdallah; Croixmarie, Vincent; Masson, Perrine; Corruble, Emmanuelle; Fève, Bruno; Colle, Romain; Ripoll, Laurent; Walther, Bernard; Boursier-Neyret, Claire; Werner, Erwan; Becquemont, Laurent; Chanson, Philippe

    2017-01-01

    Metabolomic approaches are increasingly used to identify new disease biomarkers, yet normal values of many plasma metabolites remain poorly defined. The aim of this study was to define the "normal" metabolome in healthy volunteers. We included 800 French volunteers aged between 18 and 86, equally distributed according to sex, free of any medication and considered healthy on the basis of their medical history, clinical examination and standard laboratory tests. We quantified 185 plasma metabolites, including amino acids, biogenic amines, acylcarnitines, phosphatidylcholines, sphingomyelins and hexose, using tandem mass spectrometry with the Biocrates AbsoluteIDQ p180 kit. Principal components analysis was applied to identify the main factors responsible for metabolome variability and orthogonal projection to latent structures analysis was employed to confirm the observed patterns and identify pattern-related metabolites. We established a plasma metabolite reference dataset for 144/185 metabolites. Total blood cholesterol, gender and age were identified as the principal factors explaining metabolome variability. High total blood cholesterol levels were associated with higher plasma sphingomyelins and phosphatidylcholines concentrations. Compared to women, men had higher concentrations of creatinine, branched-chain amino acids and lysophosphatidylcholines, and lower concentrations of sphingomyelins and phosphatidylcholines. Elderly healthy subjects had higher sphingomyelins and phosphatidylcholines plasma levels than young subjects. We established reference human metabolome values in a large and well-defined population of French healthy volunteers. This study provides an essential baseline for defining the "normal" metabolome and its main sources of variation.

  18. Metabolomics applied to diabetes-lessons from human population studies.

    Science.gov (United States)

    Liggi, Sonia; Griffin, Julian L

    2017-12-01

    The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Metabolomics data normalization with EigenMS.

    Directory of Open Access Journals (Sweden)

    Yuliya V Karpievitch

    Full Text Available Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated. Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05 as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data.

  20. Towards the Fecal Metabolome Derived from Moderate Red Wine Intake

    Directory of Open Access Journals (Sweden)

    Ana Jiménez-Girón

    2014-12-01

    Full Text Available Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33. It assembles data from two analytical approaches: (1 UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis; and (2 UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis. Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota.

  1. Comparative metabolomics of drought acclimation in model and forage legumes.

    Science.gov (United States)

    Sanchez, Diego H; Schwabe, Franziska; Erban, Alexander; Udvardi, Michael K; Kopka, Joachim

    2012-01-01

    Water limitation has become a major concern for agriculture. Such constraints reinforce the urgent need to understand mechanisms by which plants cope with water deprivation. We used a non-targeted metabolomic approach to explore plastic systems responses to non-lethal drought in model and forage legume species of the Lotus genus. In the model legume Lotus. japonicus, increased water stress caused gradual increases of most of the soluble small molecules profiled, reflecting a global and progressive reprogramming of metabolic pathways. The comparative metabolomic approach between Lotus species revealed conserved and unique metabolic responses to drought stress. Importantly, only few drought-responsive metabolites were conserved among all species. Thus we highlight a potential impediment to translational approaches that aim to engineer traits linked to the accumulation of compatible solutes. Finally, a broad comparison of the metabolic changes elicited by drought and salt acclimation revealed partial conservation of these metabolic stress responses within each of the Lotus species, but only few salt- and drought-responsive metabolites were shared between all. The implications of these results are discussed with regard to the current insights into legume water stress physiology. © 2011 Blackwell Publishing Ltd.

  2. Structured plant metabolomics for the simultaneous exploration of multiple factors.

    Science.gov (United States)

    Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

    2016-11-17

    Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

  3. Fusion of mass spectrometry-based metabolomics data

    NARCIS (Netherlands)

    Smilde, Age K.; van der Werf, Mariët J.; Bijlsma, Sabina; van der Werff-van der Vat, Bianca J. C.; Jellema, Renger H.

    2005-01-01

    A general method is presented for combining mass spectrometry-based metabolomics data. Such data are becoming more and more abundant, and proper tools for fusing these types of data sets are needed. Fusion of metabolomics data leads to a comprehensive view on the metabolome of an organism or

  4. The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila.

    Science.gov (United States)

    Laye, Matthew J; Tran, ViLinh; Jones, Dean P; Kapahi, Pankaj; Promislow, Daniel E L

    2015-10-01

    Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

  5. Influence of the collection tube on metabolomic changes in serum and plasma.

    Science.gov (United States)

    López-Bascón, M A; Priego-Capote, F; Peralbo-Molina, A; Calderón-Santiago, M; Luque de Castro, M D

    2016-04-01

    Major threats in metabolomics clinical research are biases in sampling and preparation of biological samples. Bias in sample collection is a frequently forgotten aspect responsible for uncontrolled errors in metabolomics analysis. There is a great diversity of blood collection tubes for sampling serum or plasma, which are widely used in metabolomics analysis. Most of the existing studies dealing with the influence of blood collection on metabolomics analysis have been restricted to comparison between plasma and serum. However, polymeric gel tubes, which are frequently proposed to accelerate the separation of serum and plasma, have not been studied. In the present research, samples of serum or plasma collected in polymeric gel tubes were compared with those taken in conventional tubes from a metabolomics perspective using an untargeted GC-TOF/MS approach. The main differences between serum and plasma collected in conventional tubes affected to critical pathways such as the citric acid cycle, metabolism of amino acids, fructose and mannose metabolism and that of glycerolipids, and pentose and glucuronate interconversion. On the other hand, the polymeric gel only promoted differences at the metabolite level in serum since no critical differences were observed between plasma collected with EDTA tubes and polymeric gel tubes. Thus, the main changes were attributable to serum collected in gel and affected to the metabolism of amino acids such as alanine, proline and threonine, the glycerolipids metabolism, and two primary metabolites such as aconitic acid and lactic acid. Therefore, these metabolite changes should be taken into account in planning an experimental protocol for metabolomics analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Data standards can boost metabolomics research, and if there is a will, there is a way.

    Science.gov (United States)

    Rocca-Serra, Philippe; Salek, Reza M; Arita, Masanori; Correa, Elon; Dayalan, Saravanan; Gonzalez-Beltran, Alejandra; Ebbels, Tim; Goodacre, Royston; Hastings, Janna; Haug, Kenneth; Koulman, Albert; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Schober, Daniel; Smith, James; Steinbeck, Christoph; Viant, Mark R; Neumann, Steffen

    2016-01-01

    Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little "arm twisting" in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.

  7. Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease

    Directory of Open Access Journals (Sweden)

    Robert A. Quinn

    2016-08-01

    Full Text Available Background. Cystic fibrosis (CF is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS. The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable. Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

  8. Causal Genetic Variation Underlying Metabolome Differences.

    Science.gov (United States)

    Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

    2017-08-01

    An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

  9. NMR and MS Methods for Metabolomics.

    Science.gov (United States)

    Amberg, Alexander; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Dieterle, Frank; Keck, Matthias

    2017-01-01

    Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

  10. NMR-based metabolomics in human disease diagnosis: Applications, limitations, and recommendations

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2013-04-03

    Metabolomics is a dynamic and emerging research field, similar to proteomics, transcriptomics and genomics in affording global understanding of biological systems. It is particularly useful in functional genomic studies in which metabolism is thought to be perturbed. Metabolomics provides a snapshot of the metabolic dynamics that reflect the response of living systems to both pathophysiological stimuli and/or genetic modification. Because this approach makes possible the examination of interactions between an organism and its diet or environment, it is particularly useful for identifying biomarkers of disease processes that involve the environment. For example, the interaction of a high fat diet with cardiovascular disease can be studied via such a metabolomics approach by modeling the interaction between genes and diet. The high reproducibility of NMR-based techniques gives this method a number of advantages over other analytical techniques in large-scale and long-term metabolomic studies, such as epidemiological studies. This approach has been used to study a wide range of diseases, through the examination of biofluids, including blood plasma/serum, urine, blister fluid, saliva and semen, as well as tissue extracts and intact tissue biopsies. However, complicating the use of NMR spectroscopy in biomarker discovery is the fact that numerous variables can effect metabolic composition including, fasting, stress, drug administration, diet, gender, age, physical activity, life style and the subject\\'s health condition. To minimize the influence of these variations in the datasets, all experimental conditions including sample collection, storage, preparation as well as NMR spectroscopic parameters and data analysis should be optimized carefully and conducted in an identical manner as described by the local standard operating protocol. This review highlights the potential applications of NMR-based metabolomics studies and gives some recommendations to improve sample

  11. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors.

    Science.gov (United States)

    Vázquez-Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez, Miguel Ángel; Vinaixa, Maria; Chiva-Blanch, Gemma; Estruch, Ramon; Correig, Xavier; Andrés-Lacueva, Cristina

    2012-08-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis.

    Science.gov (United States)

    Veyrat-Durebex, Charlotte; Corcia, Philippe; Piver, Eric; Devos, David; Dangoumau, Audrey; Gouel, Flore; Vourc'h, Patrick; Emond, Patrick; Laumonnier, Frédéric; Nadal-Desbarats, Lydie; Gordon, Paul H; Andres, Christian R; Blasco, Hélène

    2016-12-01

    This study aims to develop a cellular metabolomics model that reproduces the pathophysiological conditions found in amyotrophic lateral sclerosis in order to improve knowledge of disease physiology. We used a co-culture model combining the motor neuron-like cell line NSC-34 and the astrocyte clone C8-D1A, with each over-expressing wild-type or G93C mutant human SOD1, to examine amyotrophic lateral sclerosis (ALS) physiology. We focused on the effects of mutant human SOD1 as well as oxidative stress induced by menadione on intracellular metabolism using a metabolomics approach through gas chromatography coupled with mass spectrometry (GC-MS) analysis. Preliminary non-supervised analysis by Principal Component Analysis (PCA) revealed that cell type, genetic environment, and time of culture influenced the metabolomics profiles. Supervised analysis using orthogonal partial least squares discriminant analysis (OPLS-DA) on data from intracellular metabolomics profiles of SOD1 G93C co-cultures produced metabolites involved in glutamate metabolism and the tricarboxylic acid cycle (TCA) cycle. This study revealed the feasibility of using a metabolomics approach in a cellular model of ALS. We identified potential disruption of the TCA cycle and glutamate metabolism under oxidative stress, which is consistent with prior research in the disease. Analysis of metabolic alterations in an in vitro model is a novel approach to investigation of disease physiology.

  13. Fish mucus metabolome reveals fish life-history traits

    Science.gov (United States)

    Reverter, M.; Sasal, P.; Banaigs, B.; Lecchini, D.; Lecellier, G.; Tapissier-Bontemps, N.

    2017-06-01

    Fish mucus has important biological and ecological roles such as defense against fish pathogens and chemical mediation among several species. A non-targeted liquid chromatography-mass spectrometry metabolomic approach was developed to study gill mucus of eight butterflyfish species in Moorea (French Polynesia), and the influence of several fish traits (geographic site and reef habitat, species taxonomy, phylogeny, diet and parasitism levels) on the metabolic variability was investigated. A biphasic extraction yielding two fractions (polar and apolar) was used. Fish diet (obligate corallivorous, facultative corallivorous or omnivorous) arose as the main driver of the metabolic differences in the gill mucus in both fractions, accounting for 23% of the observed metabolic variability in the apolar fraction and 13% in the polar fraction. A partial least squares discriminant analysis allowed us to identify the metabolites (variable important in projection, VIP) driving the differences between fish with different diets (obligate corallivores, facultative corallivores and omnivorous). Using accurate mass data and fragmentation data, we identified some of these VIP as glycerophosphocholines, ceramides and fatty acids. Level of monogenean gill parasites was the second most important factor shaping the gill mucus metabolome, and it explained 10% of the metabolic variability in the polar fraction and 5% in the apolar fraction. A multiple regression tree revealed that the metabolic variability due to parasitism in the polar fraction was mainly due to differences between non-parasitized and parasitized fish. Phylogeny and butterflyfish species were factors contributing significantly to the metabolic variability of the apolar fraction (10 and 3%, respectively) but had a less pronounced effect in the polar fraction. Finally, geographic site and reef habitat of butterflyfish species did not influence the gill mucus metabolome of butterflyfishes.

  14. Haystack, a web-based tool for metabolomics research.

    Science.gov (United States)

    Grace, Stephen C; Embry, Stephen; Luo, Heng

    2014-01-01

    Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non

  15. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    Science.gov (United States)

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Sulfites and the wine metabolome.

    Science.gov (United States)

    Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

    2017-12-15

    In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO 2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO 2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Microbiome, Metabolome and Inflammatory Bowel Disease

    Directory of Open Access Journals (Sweden)

    Ishfaq Ahmed

    2016-06-01

    Full Text Available Inflammatory Bowel Disease (IBD is a multifactorial disorder that conceptually occurs as a result of altered immune responses to commensal and/or pathogenic gut microbes in individuals most susceptible to the disease. During Crohn’s Disease (CD or Ulcerative Colitis (UC, two components of the human IBD, distinct stages define the disease onset, severity, progression and remission. Epigenetic, environmental (microbiome, metabolome and nutritional factors are important in IBD pathogenesis. While the dysbiotic microbiota has been proposed to play a role in disease pathogenesis, the data on IBD and diet are still less convincing. Nonetheless, studies are ongoing to examine the effect of pre/probiotics and/or FODMAP reduced diets on both the gut microbiome and its metabolome in an effort to define the healthy diet in patients with IBD. Knowledge of a unique metabolomic fingerprint in IBD could be useful for diagnosis, treatment and detection of disease pathogenesis.

  18. Metabolomics to Explore Impact of Dairy Intake

    Directory of Open Access Journals (Sweden)

    Hong Zheng

    2015-06-01

    Full Text Available Dairy products are an important component in the Western diet and represent a valuable source of nutrients for humans. However, a reliable dairy intake assessment in nutrition research is crucial to correctly elucidate the link between dairy intake and human health. Metabolomics is considered a potential tool for assessment of dietary intake instead of traditional methods, such as food frequency questionnaires, food records, and 24-h recalls. Metabolomics has been successfully applied to discriminate between consumption of different dairy products under different experimental conditions. Moreover, potential metabolites related to dairy intake were identified, although these metabolites need to be further validated in other intervention studies before they can be used as valid biomarkers of dairy consumption. Therefore, this review provides an overview of metabolomics for assessment of dairy intake in order to better clarify the role of dairy products in human nutrition and health.

  19. Blood transcriptomics and metabolomics for personalized medicine.

    Science.gov (United States)

    Li, Shuzhao; Todor, Andrei; Luo, Ruiyan

    2016-01-01

    Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from human immunology have infused into this area exquisite characterizations of subpopulations of blood cells. It is now possible to infer from blood transcriptomics, with fine accuracy, the contribution of immune activation and of cell subpopulations. In parallel, high-resolution mass spectrometry has brought revolutionary analytical capability, detecting > 10,000 metabolites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus, the re-examination of blood chemicals by metabolomics is in order. Transcriptomics and metabolomics can be integrated to provide a more comprehensive understanding of the human biological states. We will review these new data and methods and discuss how they can contribute to personalized medicine.

  20. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    International Nuclear Information System (INIS)

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang; Gouveia-Figueira, Sandra; Pinto, Rui; Trygg, Johan; Zivkovic, Angela M.; Nording, Malin L.

    2016-01-01

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  1. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    Energy Technology Data Exchange (ETDEWEB)

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Gouveia-Figueira, Sandra [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå (Sweden); Pinto, Rui [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Bioinformatics Infrastructure for Life Sciences (Sweden); Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Zivkovic, Angela M. [Department of Nutrition, University of California, Davis, One Shields Ave, CA 95616 (United States); Nording, Malin L., E-mail: malin.nording@umu.se [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden)

    2016-02-18

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  2. COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access

    NARCIS (Netherlands)

    Salek, R.M.; Neumann, S.; Schober, D.; Hummel, J.; Billiau, K.; Kopka, J.; Correa, E.; Reijmers, T.; Rosato, A.; Tenori, L.; Turano, P.; Marin, S.; Deborde, C.; Jacob, D.; Rolin, D.; Dartigues, B.; Conesa, P.; Haug, K.; Rocca-Serra, P.; O’Hagan, S.; Hao, J.; Vliet, M. van; Sysi-Aho, M.; Ludwig, C.; Bouwman, J.; Cascante, M.; Ebbels, T.; Griffin, J.L.; Moing, A.; Nikolski, M.; Oresic, M.; Sansone, S.A.; Viant, M.R.; Goodacre, R.; Günther, U.L.; Hankemeier, T.; Luchinat, C.; Walther, D.; Steinbeck, C.

    2015-01-01

    Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and

  3. Brain nonoxidative carbohydrate consumption is not explained by export of an unknown carbon source: evaluation of the arterial and jugular venous metabolome

    DEFF Research Database (Denmark)

    Rasmussen, Peter; Nyberg, Nils; Jaroszewski, Jerzy W.

    2010-01-01

    uptake is unknown, but it may be that brain metabolism is balanced by a yet-unidentified substance(s). This study used a nuclear magnetic resonance-based metabolomics approach to plasma samples obtained from the brachial artery and the right internal jugular vein in 16 healthy young males to identify...... be accounted for by changes in the NMR-derived plasma metabolome across the brain....

  4. Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

    Science.gov (United States)

    Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

    2016-05-01

    Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. Perinatal Asphyxia: A Review from a Metabolomics Perspective

    Directory of Open Access Journals (Sweden)

    Claudia Fattuoni

    2015-04-01

    Full Text Available Perinatal asphyxia is defined as an oxygen deprivation that occurs around the time of birth, and may be caused by several perinatal events. This medical condition affects some four million neonates worldwide per year, causing the death of one million subjects. In most cases, infants successfully recover from hypoxia episodes; however, some patients may develop HIE, leading to permanent neurological conditions or impairment of different organs and systems. Given its multifactor dependency, the timing, severity and outcome of this disease, mainly assessed through Sarnat staging, are of difficult evaluation. Moreover, although the latest newborn resuscitation guideline suggests the use of a 21% oxygen concentration or room air, such an approach is still under debate. Therefore, the pathological mechanism is still not clear and a golden standard treatment has yet to be defined. In this context, metabolomics, a new discipline that has described important perinatal issues over the last years, proved to be a useful tool for the monitoring, the assessment, and the identification of potential biomarkers associated with asphyxia events. This review covers metabolomics research on perinatal asphyxia condition, examining in detail the studies reported both on animal and human models.

  6. Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

    Science.gov (United States)

    Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

    2016-08-01

    Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  7. Comparative whole genome transcriptome and metabolome analyses of five Klebsiella pneumonia strains.

    Science.gov (United States)

    Lee, Soojin; Kim, Borim; Yang, Jeongmo; Jeong, Daun; Park, Soohyun; Shin, Sang Heum; Kook, Jun Ho; Yang, Kap-Seok; Lee, Jinwon

    2015-11-01

    The integration of transcriptomics and metabolomics can provide precise information on gene-to-metabolite networks for identifying the function of novel genes. The goal of this study was to identify novel gene functions involved in 2,3-butanediol (2,3-BDO) biosynthesis by a comprehensive analysis of the transcriptome and metabolome of five mutated Klebsiella pneumonia strains (∆wabG = SGSB100, ∆wabG∆budA = SGSB106, ∆wabG∆budB = SGSB107, ∆wabG∆budC = SGSB108, ∆wabG∆budABC = SGSB109). First, the transcriptomes of all five mutants were analyzed and the genes exhibiting reproducible changes in expression were determined. The transcriptome was well conserved among the five strains, and differences in gene expression occurred mainly in genes coding for 2,3-BDO biosynthesis (budA, budB, and budC) and the genes involved in the degradation of reactive oxygen, biosynthesis and transport of arginine, cysteine biosynthesis, sulfur metabolism, oxidoreductase reaction, and formate dehydrogenase reaction. Second, differences in the metabolome (estimated by carbon distribution, CO2 emission, and redox balance) among the five mutant strains due to gene alteration of the 2,3-BDO operon were detected. The functional genomics approach integrating metabolomics and transcriptomics in K. Pneumonia presented here provides an innovative means of identifying novel gene functions involved in 2,3-BDO biosynthesis metabolism and whole cell metabolism.

  8. Metabolomics of Hydrazine-Induced Hepatotoxicity in Rats for Discovering Potential Biomarkers

    Directory of Open Access Journals (Sweden)

    Zhuoling An

    2018-01-01

    Full Text Available Metabolic pathway disturbances associated with drug-induced liver injury remain unsatisfactorily characterized. Diagnostic biomarkers for hepatotoxicity have been used to minimize drug-induced liver injury and to increase the clinical safety. A metabolomics strategy using rapid-resolution liquid chromatography/tandem mass spectrometry (RRLC-MS/MS analyses and multivariate statistics was implemented to identify potential biomarkers for hydrazine-induced hepatotoxicity. The global serum and urine metabolomics of 30 hydrazine-treated rats at 24 or 48 h postdosing and 24 healthy rats were characterized by a metabolomics approach. Multivariate statistical data analyses and receiver operating characteristic (ROC curves were performed to identify the most significantly altered metabolites. The 16 most significant potential biomarkers were identified to be closely related to hydrazine-induced liver injury. The combination of these biomarkers had an area under the curve (AUC > 0.85, with 100% specificity and sensitivity, respectively. This high-quality classification group included amino acids and their derivatives, glutathione metabolites, vitamins, fatty acids, intermediates of pyrimidine metabolism, and lipids. Additionally, metabolomics pathway analyses confirmed that phenylalanine, tyrosine, and tryptophan biosynthesis as well as tyrosine metabolism had great interactions with hydrazine-induced liver injury in rats. These discriminating metabolites might be useful in understanding the pathogenesis mechanisms of liver injury and provide good prospects for drug-induced liver injury diagnosis clinically.

  9. Metabolomic applications to decipher gut microbial metabolic influence in health and disease

    Directory of Open Access Journals (Sweden)

    Francois-Pierre eMartin

    2012-04-01

    Full Text Available Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial mammalian cross-talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease aetiology, diagnostic stratification and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR spectroscopy and mass spectrometry (MS provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

  10. Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics

    Directory of Open Access Journals (Sweden)

    Kalle Kilk

    2018-02-01

    Full Text Available Apart from the refined management-oriented clinical stratification of chronic obstructive pulmonary disease (COPD, the molecular pathologies behind this highly prevalent disease have remained obscure. The aim of this study was the characterization of patients with COPD, based on the metabolomic profiling of peripheral blood and exhaled breath condensate (EBC within the context of defined clinical and demographic variables. Mass-spectrometry-based targeted analysis of serum metabolites (mainly amino acids and lipid species, untargeted profiles of serum and EBC of patients with COPD of different clinical characteristics (n = 25 and control individuals (n = 21 were performed. From the combined clinical/demographic and metabolomics data, associations between clinical/demographic and metabolic parameters were searched and a de novo phenotyping for COPD was attempted. Adjoining the clinical parameters, sphingomyelins were the best to differentiate COPD patients from controls. Unsaturated fatty acid-containing lipids, ornithine metabolism and plasma protein composition-associated signals from the untargeted analysis differentiated the Global Initiative for COPD (GOLD categories. Hierarchical clustering did not reveal a clinical-metabolomic stratification superior to the strata set by the GOLD consensus. We conclude that while metabolomics approaches are good for finding biomarkers and clarifying the mechanism of the disease, there are no distinct co-variate independent clinical-metabolic phenotypes.

  11. Direct infusion mass spectrometry metabolomics dataset: a benchmark for data processing and quality control

    Science.gov (United States)

    Kirwan, Jennifer A; Weber, Ralf J M; Broadhurst, David I; Viant, Mark R

    2014-01-01

    Direct-infusion mass spectrometry (DIMS) metabolomics is an important approach for characterising molecular responses of organisms to disease, drugs and the environment. Increasingly large-scale metabolomics studies are being conducted, necessitating improvements in both bioanalytical and computational workflows to maintain data quality. This dataset represents a systematic evaluation of the reproducibility of a multi-batch DIMS metabolomics study of cardiac tissue extracts. It comprises of twenty biological samples (cow vs. sheep) that were analysed repeatedly, in 8 batches across 7 days, together with a concurrent set of quality control (QC) samples. Data are presented from each step of the workflow and are available in MetaboLights. The strength of the dataset is that intra- and inter-batch variation can be corrected using QC spectra and the quality of this correction assessed independently using the repeatedly-measured biological samples. Originally designed to test the efficacy of a batch-correction algorithm, it will enable others to evaluate novel data processing algorithms. Furthermore, this dataset serves as a benchmark for DIMS metabolomics, derived using best-practice workflows and rigorous quality assessment. PMID:25977770

  12. Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

    Science.gov (United States)

    Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

    2016-05-01

    Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

  13. Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

    Science.gov (United States)

    Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

    2018-01-01

    Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

  14. Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae in a phylogenetic context.

    Directory of Open Access Journals (Sweden)

    Maria Elvira Poleti Martucci

    Full Text Available Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus. Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

  15. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    Science.gov (United States)

    Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

    2018-03-20

    The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

  16. Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

    Science.gov (United States)

    Thonusin, Chanisa; IglayReger, Heidi B; Soni, Tanu; Rothberg, Amy E; Burant, Charles F; Evans, Charles R

    2017-11-10

    In recent years, mass spectrometry-based metabolomics has increasingly been applied to large-scale epidemiological studies of human subjects. However, the successful use of metabolomics in this context is subject to the challenge of detecting biologically significant effects despite substantial intensity drift that often occurs when data are acquired over a long period or in multiple batches. Numerous computational strategies and software tools have been developed to aid in correcting for intensity drift in metabolomics data, but most of these techniques are implemented using command-line driven software and custom scripts which are not accessible to all end users of metabolomics data. Further, it has not yet become routine practice to assess the quantitative accuracy of drift correction against techniques which enable true absolute quantitation such as isotope dilution mass spectrometry. We developed an Excel-based tool, MetaboDrift, to visually evaluate and correct for intensity drift in a multi-batch liquid chromatography - mass spectrometry (LC-MS) metabolomics dataset. The tool enables drift correction based on either quality control (QC) samples analyzed throughout the batches or using QC-sample independent methods. We applied MetaboDrift to an original set of clinical metabolomics data from a mixed-meal tolerance test (MMTT). The performance of the method was evaluated for multiple classes of metabolites by comparison with normalization using isotope-labeled internal standards. QC sample-based intensity drift correction significantly improved correlation with IS-normalized data, and resulted in detection of additional metabolites with significant physiological response to the MMTT. The relative merits of different QC-sample curve fitting strategies are discussed in the context of batch size and drift pattern complexity. Our drift correction tool offers a practical, simplified approach to drift correction and batch combination in large metabolomics studies

  17. A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers.

    Science.gov (United States)

    Vehof, Jelle; Hysi, Pirro G; Hammond, Christopher J

    2017-04-01

    To test the association between serum metabolites and dry eye disease (DED) using a hypothesis-free metabolomics approach. Cross-sectional association study. A total of 2819 subjects from the population-representative TwinsUK cohort in the United Kingdom, with a mean age of 57 years (range, 17-82 years). We tested associations between 222 known serum metabolites and DED. All subjects underwent nontargeted metabolomic analysis of plasma samples using gas and liquid chromatography in combination with mass spectrometry (Metabolon Inc., Durham, NC). Dry eye disease was defined from the validated Short Questionnaire for Dry Eye Syndrome (SQDES) as a previous diagnosis of DED by a clinician or "often" or "constant" symptoms of dryness and irritation. Analyses were performed with linear mixed effect models that included age, BMI, and sex as covariates, corrected for multiple testing. Primary outcome was DED as defined by the SQDES, and secondary outcomes were symptom score of DED and a clinical diagnosis of DED. Prevalence of DED as defined by the SQDES was 15.5% (n = 436). A strong and metabolome-wide significant association with DED was found with decreased levels of the metabolites androsterone sulfate (P = 0.00030) and epiandrosterone sulfate (P = 0.00036). Three other metabolites involved in androgen metabolism, 4-androsten-3beta,17beta-diol disulfate 1 and 2, and dehydroepiandrosterone sulfate, were the next most strongly associated of the 222 metabolites, but did not reach metabolome-wide significance. Dryness and irritation symptoms, as opposed to a clinical diagnosis, were particularly strongly associated with decreased androgen steroid metabolites, with all reaching metabolome-wide significance (androsterone sulfate, P = 0.000000029; epiandrosterone sulfate, P = 0.0000040; 4-androsten-3beta,17beta-diol disulfate 1, P = 0.000016; 4-androsten-3beta,17beta-diol disulfate 2, P = 0.000064; and dehydroepiandrosterone sulfate, P = 0.00011). Of these 5

  18. The exo-metabolome in filamentous fungi

    DEFF Research Database (Denmark)

    Thrane, Ulf; Andersen, Birgitte; Frisvad, Jens Christian

    2007-01-01

    Filamentous fungi are a diverse group of eukaryotic microorganisms that have a significant impact on human life as spoilers of food and feed by degradation and toxin production. They are also most useful as a source of bulk and fine chemicals and pharmaceuticals. This chapter focuses on the exo-metabolome...

  19. Metabolome analysis of Drosophila melanogaster during embryogenesis.

    Science.gov (United States)

    An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos' metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo.

  20. Metabolomics studies in brain tissue: A review.

    Science.gov (United States)

    Gonzalez-Riano, Carolina; Garcia, Antonia; Barbas, Coral

    2016-10-25

    Brain is still an organ with a composition to be discovered but beyond that, mental disorders and especially all diseases that curse with dementia are devastating for the patient, the family and the society. Metabolomics can offer an alternative tool for unveiling new insights in the discovery of new treatments and biomarkers of mental disorders. Until now, most of metabolomic studies have been based on biofluids: serum/plasma or urine, because brain tissue accessibility is limited to animal models or post mortem studies, but even so it is crucial for understanding the pathological processes. Metabolomics studies of brain tissue imply several challenges due to sample extraction, along with brain heterogeneity, sample storage, and sample treatment for a wide coverage of metabolites with a wide range of concentrations of many lipophilic and some polar compounds. In this review, the current analytical practices for target and non-targeted metabolomics are described and discussed with emphasis on critical aspects: sample treatment (quenching, homogenization, filtration, centrifugation and extraction), analytical methods, as well as findings considering the used strategies. Besides that, the altered analytes in the different brain regions have been associated with their corresponding pathways to obtain a global overview of their dysregulation, trying to establish the link between altered biological pathways and pathophysiological conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Microbial metabolomics in open microscale platforms

    Science.gov (United States)

    Barkal, Layla J.; Theberge, Ashleigh B.; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A.; Wang, Clay C. C.; Beebe, David J.; Keller, Nancy P.; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid–liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  2. Exploring the analysis of structured metabolomics data

    NARCIS (Netherlands)

    Verouden, M.P.H.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2009-01-01

    In metabolomics research a large number of metabolites are measured that reflect the cellular state under the experimental conditions studied. In many occasions the experiments are performed according to an experimental design to make sure that sufficient variation is induced in the metabolite

  3. Analysis of metabolomics data from twin families

    NARCIS (Netherlands)

    Draisma, Hermanus Henricus Maria

    2011-01-01

    Metabolomics is the comprehensive analysis of small molecules involved in metabolism, on the basis of samples that have been obtained from organisms in a given physiological state. Data obtained from measurements of trait levels in twin families can be used to elucidate the importance of genetic and

  4. Data-processing strategies for metabolomics studies

    NARCIS (Netherlands)

    Hendriks, M.M.W.B.; Eeuwijk, van F.A.; Jellema, R.H.; Westerhuis, J.A.; Reijmers, T.H.; Hoefsloot, H.C.J.; Smilde, A.K.

    2011-01-01

    Metabolomics studies aim at a better understanding of biochemical processes by studying relations between metabolites and between metabolites and other types of information (e.g., sensory and phenotypic features). The objectives of these studies are diverse, but the types of data generated and the

  5. Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe.

    Science.gov (United States)

    Lamichhane, Santosh; Sen, Partho; Dickens, Alex M; Orešič, Matej; Bertram, Hanne Christine

    2018-04-30

    It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted. Copyright © 2018 Elsevier Inc. All rights reserved.

  6. Independent component analysis in non-hypothesis driven metabolomics

    DEFF Research Database (Denmark)

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...... information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach...... based on descriptive statistics was established to optimize ICA model. In the GC-TOF MS data set the number of principal components after whitening and the number of independent components of ICA were optimized and systematically selected by descriptive statistics. The elucidated dominating independent...

  7. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  8. Metabolomics as a tool to identify biomarkers to predict and improve outcomes in reproductive medicine: a systematic review.

    Science.gov (United States)

    Bracewell-Milnes, Timothy; Saso, Srdjan; Abdalla, Hossam; Nikolau, Dimitrios; Norman-Taylor, Julian; Johnson, Mark; Holmes, Elaine; Thum, Meen-Yau

    2017-11-01

    reproductive tract, with a summary of the current findings, promise and pitfalls in metabolomic techniques. The approaches discussed can be adapted by other metabolomic studies. A range of sophisticated modern metabolomic techniques are now more widely available and have been applied to the analysis of the female reproductive tract. However, this review has revealed the paucity of metabolomic studies in the field of fertility and the inconsistencies of findings between different studies, as well as a lack of research examining the metabolic effects of various gynecological diseases. By incorporating metabolomic technology into an increased number of well designed studies, a much greater understanding of infertility at a molecular level could be achieved. However, there is currently no evidence for the use of metabolomics in clinical practice to improve fertility outcomes. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  9. Metabolomics of Clostridial Biofuel Production

    Energy Technology Data Exchange (ETDEWEB)

    Rabinowitz, Joshua D [Princeton Univ., NJ (United States); Aristilde, Ludmilla [Cornell Univ., Ithaca, NY (United States); Amador-Noguez, Daniel [Univ. of Wisconsin, Madison, WI (United States)

    2015-09-08

    Members of the genus Clostridium collectively have the ideal set of the metabolic capabilities for fermentative biofuel production: cellulose degradation, hydrogen production, and solvent excretion. No single organism, however, can effectively convert cellulose into biofuels. Here we developed, using metabolomics and isotope tracers, basic science knowledge of Clostridial metabolism of utility for future efforts to engineer such an organism. In glucose fermentation carried out by the biofuel producer Clostridium acetobutylicum, we observed a remarkably ordered series of metabolite concentration changes as the fermentation progressed from acidogenesis to solventogenesis. In general, high-energy compounds decreased while low-energy species increased during solventogenesis. These changes in metabolite concentrations were accompanied by large changes in intracellular metabolic fluxes, with pyruvate directed towards acetyl-CoA and solvents instead of oxaloacetate and amino acids. Thus, the solventogenic transition involves global remodeling of metabolism to redirect resources from biomass production into solvent production. In contrast to C. acetobutylicum, which is an avid fermenter, C. cellulolyticum metabolizes glucose only slowly. We find that glycolytic intermediate concentrations are radically different from fast fermenting organisms. Associated thermodynamic and isotope tracer analysis revealed that the full glycolytic pathway in C. cellulolyticum is reversible. This arises from changes in cofactor utilization for phosphofructokinase and an alternative pathway from phosphoenolpyruvate to pyruvate. The net effect is to increase the high-energy phosphate bond yield of glycolysis by 150% (from 2 to 5) at the expense of lower net flux. Thus, C. cellulolyticum prioritizes glycolytic energy efficiency over speed. Degradation of cellulose results in other sugars in addition to glucose. Simultaneous feeding of stable isotope-labeled glucose and unlabeled pentose sugars

  10. High-Resolution Metabolomics: Review of the Field and Implications for Nursing Science and the Study of Preterm Birth.

    Science.gov (United States)

    Li, Shuzhao; Dunlop, Anne L; Jones, Dean P; Corwin, Elizabeth J

    2016-01-01

    Most complex health conditions do not have a single etiology but rather develop from exposure to multiple risk factors that interact to influence individual susceptibility. In this review, we discuss the emerging field of metabolomics as a means by which metabolic pathways underlying a disease etiology can be exposed and specific metabolites can be identified and linked, ultimately providing biomarkers for early detection of disease onset and new strategies for intervention. We present the theoretical foundation of metabolomics research, the current methods employed in its conduct, and the overlap of metabolomics research with other "omic" approaches. As an exemplar, we discuss the potential of metabolomics research in the context of deciphering the complex interactions of the maternal-fetal exposures that underlie the risk of preterm birth, a condition that accounts for substantial portions of infant morbidity and mortality and whose etiology and pathophysiology remain incompletely defined. We conclude by providing strategies for including metabolomics research in future nursing studies for the advancement of nursing science. © The Author(s) 2015.

  11. Metabolomics of Oxidative Stress in Recent Studies of Endogenous and Exogenously Administered Intermediate Metabolites

    Directory of Open Access Journals (Sweden)

    Jeffrey G. Pelton

    2011-09-01

    Full Text Available Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately

  12. Metabolomics of Oxidative Stress in Recent Studies of Endogenous and Exogenously Administered Intermediate Metabolites

    Science.gov (United States)

    Liu, Jia; Litt, Lawrence; Segal, Mark R.; Kelly, Mark J. S.; Pelton, Jeffrey G.; Kim, Myungwon

    2011-01-01

    Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing

  13. Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration.

    Science.gov (United States)

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2017-05-01

    Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting.

    Directory of Open Access Journals (Sweden)

    Karsten Suhre

    Full Text Available BACKGROUND: Metabolomics is the rapidly evolving field of the comprehensive measurement of ideally all endogenous metabolites in a biological fluid. However, no single analytic technique covers the entire spectrum of the human metabolome. Here we present results from a multiplatform study, in which we investigate what kind of results can presently be obtained in the field of diabetes research when combining metabolomics data collected on a complementary set of analytical platforms in the framework of an epidemiological study. METHODOLOGY/PRINCIPAL FINDINGS: 40 individuals with self-reported diabetes and 60 controls (male, over 54 years were randomly selected from the participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg study, representing an extensively phenotyped sample of the general German population. Concentrations of over 420 unique small molecules were determined in overnight-fasting blood using three different techniques, covering nuclear magnetic resonance and tandem mass spectrometry. Known biomarkers of diabetes could be replicated by this multiple metabolomic platform approach, including sugar metabolites (1,5-anhydroglucoitol, ketone bodies (3-hydroxybutyrate, and branched chain amino acids. In some cases, diabetes-related medication can be detected (pioglitazone, salicylic acid. CONCLUSIONS/SIGNIFICANCE: Our study depicts the promising potential of metabolomics in diabetes research by identification of a series of known and also novel, deregulated metabolites that associate with diabetes. Key observations include perturbations of metabolic pathways linked to kidney dysfunction (3-indoxyl sulfate, lipid metabolism (glycerophospholipids, free fatty acids, and interaction with the gut microflora (bile acids. Our study suggests that metabolic markers hold the potential to detect diabetes-related complications already under sub-clinical conditions in the general population.

  15. The metabolomic profile of umbilical cord blood in neonatal hypoxic ischaemic encephalopathy.

    Directory of Open Access Journals (Sweden)

    Brian H Walsh

    Full Text Available Hypoxic ischaemic encephalopathy (HIE in newborns can cause significant long-term neurological disability. The insult is a complex injury characterised by energy failure and disruption of cellular homeostasis, leading to mitochondrial damage. The importance of individual metabolic pathways, and their interaction in the disease process is not fully understood. The aim of this study was to describe and quantify the metabolomic profile of umbilical cord blood samples in a carefully defined population of full-term infants with HIE.The injury severity was defined using both the modified Sarnat score and continuous multichannel electroencephalogram. Using these classification systems, our population was divided into those with confirmed HIE (n = 31, asphyxiated infants without encephalopathy (n = 40 and matched controls (n = 71. All had umbilical cord blood drawn and biobanked at -80 °C within 3 hours of delivery. A combined direct injection and LC-MS/MS assay (AbsolutIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria was used for the metabolomic analyses of the samples. Targeted metabolomic analysis showed a significant alteration between study groups in 29 metabolites from 3 distinct classes (Amino Acids, Acylcarnitines, and Glycerophospholipids. 9 of these metabolites were only significantly altered between neonates with Hypoxic ischaemic encephalopathy and matched controls, while 14 were significantly altered in both study groups. Multivariate Discriminant Analysis models developed showed clear multifactorial metabolite associations with both asphyxia and HIE. A logistic regression model using 5 metabolites clearly delineates severity of asphyxia and classifies HIE infants with AUC = 0.92. These data describe wide-spread disruption to not only energy pathways, but also nitrogen and lipid metabolism in both asphyxia and HIE.This study shows that a multi-platform targeted approach to metabolomic analyses using accurately phenotyped and

  16. Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women

    DEFF Research Database (Denmark)

    Luan, Hemi; Meng, Nan; Liu, Ping

    2015-01-01

    Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were...... collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data...

  17. Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data

    Directory of Open Access Journals (Sweden)

    Kevin Schwahn

    2017-12-01

    Full Text Available Recent advances in metabolomics technologies have resulted in high-quality (time-resolved metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higher-order dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.

  18. Covering chemical diversity of genetically-modified tomatoes using metabolomics for objective substantial equivalence assessment.

    Directory of Open Access Journals (Sweden)

    Miyako Kusano

    Full Text Available As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms.

  19. Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome

    Directory of Open Access Journals (Sweden)

    Pamela eVernocchi

    2012-12-01

    Full Text Available Bacteria colonizing the human intestinal tract exhibit a high phylogenetic diversity that reflects their immense metabolic potentials. The catalytic activity of gut microbes has an important impact on gastrointestinal (GI functions and host health. The microbial conversion of carbohydrates and other food components leads to the formation of a large number of compounds that affect the host metabolome and have beneficial or adverse effects on human health. Meabolomics is a metabolic-biology system approach focused on the metabolic responses understanding of living systems to physio-pathological stimuli by using multivariate statistical data on human body fluids obtained by different instrumental techniques. A metabolomic approach based on an analytical platform could be able to separate, detect, characterize and quantify a wide range of metabolites and its metabolic pathways. This approach has been recently applied to study the metabolic changes triggered in the gut microbiota by specific diet components and diet variations, specific diseases, probiotic and synbiotic food intake.This review describes the metabolomic data obtained by analyzing human fluids by using different techniques and particularly Gas Chromatography Mass Spectrometry Solid-phase Micro Extraction (GC-MS/SPME, Proton Nuclear Magnetic Resonance (1H-NMR Spectroscopy and Fourier Transform Infrared (FTIR Spectroscopy. This instrumental approach have a good potential in the identification and detection of specific food intake and diseases biomarkers.

  20. Covering Chemical Diversity of Genetically-Modified Tomatoes Using Metabolomics for Objective Substantial Equivalence Assessment

    Science.gov (United States)

    Hirai, Tadayoshi; Oikawa, Akira; Matsuda, Fumio; Fukushima, Atsushi; Arita, Masanori; Watanabe, Shin; Yano, Megumu; Hiwasa-Tanase, Kyoko; Ezura, Hiroshi; Saito, Kazuki

    2011-01-01

    As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms. PMID:21359231

  1. Metabolomic variation of brassica rapa var. rapa (var. raapstelen) and raphanus sativus l. at different developmental stages

    International Nuclear Information System (INIS)

    Jahangir, M.; Farid, I.B.A.

    2014-01-01

    Brassica rapa (var. raapstelen) and Raphanus sativus (red radish) are being used as food and fodder while also known as model in recent plant research due to the diversity of metabolites as well as genetic resemblance to Arabidopsis. This study explains the change in metabolites (amino acids, organic acids, chlorophyll, carotenoids, tocopherols, ascorbic acid, sucrose, phenylpropanoids and glucosinolates) during plant development. In present study the metabolomic variation in relation to plant growth has been evaluated, for Brassica rapa (var. raapstelen) and red radish (Raphanus sativus) at three different developmental stages. A non-targeted and targeted metabolomic approach by NMR and HPLC in combination with Principal component analysis (PCA) of the data was used to identify phytochemicals being influenced by plant growth. The results lead to the better understanding of metabolic changes during plant development and show the importance of plant age with respect to the metabolomic profile of vegetables. (author)

  2. Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era.

    Science.gov (United States)

    Zhou, Zhiwei; Tu, Jia; Zhu, Zheng-Jiang

    2018-02-01

    Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

    Science.gov (United States)

    Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

    2018-01-01

    Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

  4. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  5. Metabolomics reveals distinct neurochemical profiles associated with stress resilience

    Directory of Open Access Journals (Sweden)

    Brooke N. Dulka

    2017-12-01

    Full Text Available Acute social defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of stress resilience, until recently, it has not been feasible to associate levels of large numbers of neurochemicals and metabolites to stress-related phenotypes. The objective of the present study was to use an untargeted metabolomics approach to identify known and unknown neurochemicals in select brain regions that distinguish susceptible and resistant individuals in two rodent models of acute social defeat. In the first experiment, male mice were first phenotyped as resistant or susceptible. Then, mice were subjected to acute social defeat, and tissues were immediately collected from the ventromedial prefrontal cortex (vmPFC, basolateral/central amygdala (BLA/CeA, nucleus accumbens (NAc, and dorsal hippocampus (dHPC. Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS was used for the detection of water-soluble neurochemicals. In the second experiment, male Syrian hamsters were paired in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 h after the last dominance encounter, animals were exposed to acute social defeat stress. Immediately after social defeat, tissue was collected from the vmPFC, BLA/CeA, NAc, and dHPC for analysis using UPLC-HRMS. Although no single biomarker characterized stress-related phenotypes in both species, commonalities were found. For instance, in both model systems, animals resistant to social defeat stress also show increased concentration of molecules to protect against oxidative stress in the NAc and vmPFC. Additionally, in both mice and hamsters, unidentified spectral features were preliminarily annotated as potential targets for future experiments. Overall, these findings

  6. Metabolomics (liver and blood profiling) in a mouse model in response to fasting: A study of hepatic steatosis

    NARCIS (Netherlands)

    Ginneken, V. van; Verhey, E.; Poelmann, R.; Ramakers, R.; Dijk, K.W. van; Ham, L.; Voshol, P.; Havekes, L.; Eck, M. van; Greef, J. van der

    2007-01-01

    A metabolomic approach was applied to a mouse model of starvation-induced hepatic steatosis. After 24 h of fasting it appears that starvation reduced the phospholipids (PL), free cholesterol (FC), and cholesterol esters (CE) content of low-density lipoproteins (LDL). In liver lipid profiles major

  7. METABOLOMICS: A Tool to Assess the Physiological Response of Pseudomonas Strains to Environmental Changes

    DEFF Research Database (Denmark)

    Wordofa, Gossa Garedew

    Qualitative and quantitative analysis of intracellular metabolites is a valuable approach for characterizing and understanding the biochemical processes in cellular systems. Their composition and level represent the molecular phenotype of an organism in response to genetic or environmental......120. These metabolites are not representative of the entire metabolome of P. taiwanensis VLB120, however, they have an essential role in central metabolism. The main chemical classification of these metabolites includes sugars phosphates, amino acids, organic acids, redox cofactors, nucleosides...

  8. Serum metabolomic profiles suggest influence of sex and oral contraceptive use

    OpenAIRE

    Ruoppolo, Margherita; Campesi, Ilaria; Scolamiero, Emanuela; Pecce, Rita; Caterino, Marianna; Cherchi, Sara; Mercuro, Giuseppe; Tonolo, Giancarlo; Franconi, Flavia

    2014-01-01

    Aim: Considering that the effects of sex and oral contraceptives (OCs) on blood metabolites have been scarcely studied and the fact that protocol designs for clinical trials emphasise the use of contraception for women of childbearing potential, we examined if OCs and sex affect the serum levels of the physiologically relevant amino acids, carnitine and acylcarnitines, using metabolomics approaches. Methods: Healthy adult men and women were enrolled. They were drug free with the exception of ...

  9. The dental calculus metabolome in modern and historic samples

    DEFF Research Database (Denmark)

    Velsko, Irina M.; Overmyer, Katherine A.; Speller, Camilla

    2017-01-01

    Introduction: Dental calculus is a mineralized microbial dental plaque biofilm that forms throughout life by precipitation of salivary calcium salts. Successive cycles of dental plaque growth and calcification make it an unusually well-preserved, long-term record of host-microbial interaction...... in the archaeological record. Recent studies have confirmed the survival of authentic ancient DNA and proteins within historic and prehistoric dental calculus, making it a promising substrate for investigating oral microbiome evolution via direct measurement and comparison of modern and ancient specimens. Objective: We...... present the first comprehensive characterization of the human dental calculus metabolome using a multi-platform approach. Methods: Ultra performance liquid chromatography-tandem mass spectrometry (UPLC–MS/MS) quantified 285 metabolites in modern and historic (200 years old) dental calculus, including...

  10. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

  11. Metabolomic analysis of three Mollicute species.

    Directory of Open Access Journals (Sweden)

    Anna A Vanyushkina

    Full Text Available We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer.

  12. Metabolomics for Quality and food security

    International Nuclear Information System (INIS)

    Diretto, Gianfranco

    2015-01-01

    By the term 'Metabolomics' means the discipline which allows you to determine the set of small molecules (metabolites) produced by an organism in a given time. The metabolomic analysis requires complex technological platforms that allow, in the first place, the separation (chromatography liquid or gaseous) of the different molecules and, subsequently, the identification of the same on the basis of characteristic ratio between their mass and charge (m / z). This study arises by estimates that, between climate change planned for the coming decades, there will also be quick increasing the concentration of Co2 in the atmosphere. In this context, it is essential to predict how these changes weather will impact on product quality plant at the base of our diet. [it

  13. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

    Science.gov (United States)

    Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

    2016-01-04

    The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. Metabolomics, peptidomics and proteomics applications of capillary electrophoresis-mass spectrometry in Foodomics: A review

    International Nuclear Information System (INIS)

    Ibáñez, Clara; Simó, Carolina; García-Cañas, Virginia; Cifuentes, Alejandro; Castro-Puyana, María

    2013-01-01

    Graphical abstract: -- Highlights: •Foodomics allows studying food and nutrition through the application of advanced omics approaches. •CE-MS plays a crucial role as analytical platform to carry out omics studies. •CE-MS applications for food metabolomics, proteomics and peptidomics are presented. -- Abstract: In the current post-genomic era, Foodomics has been defined as a discipline that studies food and nutrition through the application of advanced omics approaches. Foodomics involves the use of genomics, transcriptomics, epigenetics, proteomics, peptidomics, and/or metabolomics to investigate food quality, safety, traceability and bioactivity. In this context, capillary electrophoresis-mass spectrometry (CE-MS) has been applied mainly in food proteomics, peptidomics and metabolomics. The aim of this review work is to present an overview of the most recent developments and applications of CE-MS as analytical platform for Foodomics, covering the relevant works published from 2008 to 2012. The review provides also information about the integration of several omics approaches in the new Foodomics field

  15. Metabolomics, peptidomics and proteomics applications of capillary electrophoresis-mass spectrometry in Foodomics: A review

    Energy Technology Data Exchange (ETDEWEB)

    Ibáñez, Clara; Simó, Carolina; García-Cañas, Virginia; Cifuentes, Alejandro, E-mail: a.cifuentes@csic.es; Castro-Puyana, María

    2013-11-13

    Graphical abstract: -- Highlights: •Foodomics allows studying food and nutrition through the application of advanced omics approaches. •CE-MS plays a crucial role as analytical platform to carry out omics studies. •CE-MS applications for food metabolomics, proteomics and peptidomics are presented. -- Abstract: In the current post-genomic era, Foodomics has been defined as a discipline that studies food and nutrition through the application of advanced omics approaches. Foodomics involves the use of genomics, transcriptomics, epigenetics, proteomics, peptidomics, and/or metabolomics to investigate food quality, safety, traceability and bioactivity. In this context, capillary electrophoresis-mass spectrometry (CE-MS) has been applied mainly in food proteomics, peptidomics and metabolomics. The aim of this review work is to present an overview of the most recent developments and applications of CE-MS as analytical platform for Foodomics, covering the relevant works published from 2008 to 2012. The review provides also information about the integration of several omics approaches in the new Foodomics field.

  16. New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation.

    Science.gov (United States)

    Tulipani, Sara; Mora-Cubillos, Ximena; Jáuregui, Olga; Llorach, Rafael; García-Fuentes, Eduardo; Tinahones, Francisco J; Andres-Lacueva, Cristina

    2015-03-03

    Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics

  17. Blood Transcriptomics and Metabolomics for Personalized Medicine

    Science.gov (United States)

    2015-10-31

    involved in rheumatoid arthritis . PLoS Comput Biol 2011;7. [100] Zhu J. Stitching together multiple data dimensions reveals interacting metabolomic...capability, detecting N10,000 metabo- lites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus...research to clinical care has constantly seen huge disap- pointments. With the accumulation of detailed, information-rich data, human subjects start to

  18. Data fusion in metabolomic cancer diagnostics

    DEFF Research Database (Denmark)

    Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

    2013-01-01

    We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic meas...... measurements in the form of (1)H NMR spectroscopy. The results indicate that using an extensive profile established by combining such measurements together with the biomarkers is better than using single markers....

  19. Metabolomic Analysis in Brain Research: Opportunities & Challenges

    Directory of Open Access Journals (Sweden)

    Catherine G Vasilopoulou

    2016-05-01

    Full Text Available Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s. Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

  20. Environmental metabolomics with data science for investigating ecosystem homeostasis.

    Science.gov (United States)

    Kikuchi, Jun; Ito, Kengo; Date, Yasuhiro

    2018-02-01

    A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches. Copyright © 2017. Published by Elsevier B.V.

  1. PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

    Science.gov (United States)

    Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

    2018-01-04

    The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

    Directory of Open Access Journals (Sweden)

    Jianhong Lu

    2017-08-01

    Full Text Available Coronary heart disease (CHD is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA, myocardial infarction (MI, and healthy control (HC. Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL, and downstream metabolites derived from polyunsaturated fatty acids (PUFAs, such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC. Keywords: Metabolomics, Lipid peroxidation, Lipidomics, Myocardial infarction, Isoprostanes, Coronary heart disease (CHD

  3. Metabolomics to Decipher the Chemical Defense of Cereals against Fusarium graminearum and Deoxynivalenol Accumulation

    Directory of Open Access Journals (Sweden)

    Léa Gauthier

    2015-10-01

    Full Text Available Fusarium graminearum is the causal agent of Fusarium head blight (FHB and Gibberella ear rot (GER, two devastating diseases of wheat, barley, and maize. Furthermore, F. graminearum species can produce type B trichothecene mycotoxins that accumulate in grains. Use of FHB and GER resistant cultivars is one of the most promising strategies to reduce damage induced by F. graminearum. Combined with genetic approaches, metabolomic ones can provide powerful opportunities for plant breeding through the identification of resistant biomarker metabolites which have the advantage of integrating the genetic background and the influence of the environment. In the past decade, several metabolomics attempts have been made to decipher the chemical defense that cereals employ to counteract F. graminearum. By covering the major classes of metabolites that have been highlighted and addressing their potential role, this review demonstrates the complex and integrated network of events that cereals can orchestrate to resist to F. graminearum.

  4. MassTRIX reloaded: combined analysis and visualization of transcriptome and metabolome data.

    Directory of Open Access Journals (Sweden)

    Brigitte Wägele

    Full Text Available Systems Biology is a field in biological science that focuses on the combination of several or all "omics"-approaches in order to find out how genes, transcripts, proteins and metabolites act together in the network of life. Metabolomics as analog to genomics, transcriptomics and proteomics is more and more integrated into biological studies and often transcriptomic and metabolomic experiments are combined in one setup. At a first glance both data types seem to be completely different, but both produce information on biological entities, either transcripts or metabolites. Both types can be overlaid on metabolic pathways to obtain biological information on the studied system. For the joint analysis of both data types the MassTRIX webserver was updated. MassTRIX is freely available at www.masstrix.org.

  5. Assessing Heterogeneity of Osteolytic Lesions in Multiple Myeloma by 1H HR-MAS NMR Metabolomics

    Directory of Open Access Journals (Sweden)

    Laurette Tavel

    2016-10-01

    Full Text Available Multiple myeloma (MM is a malignancy of plasma cells characterized by multifocal osteolytic bone lesions. Macroscopic and genetic heterogeneity has been documented within MM lesions. Understanding the bases of such heterogeneity may unveil relevant features of MM pathobiology. To this aim, we deployed unbiased 1H high-resolution magic-angle spinning (HR-MAS nuclear magnetic resonance (NMR metabolomics to analyze multiple biopsy specimens of osteolytic lesions from one case of pathological fracture caused by MM. Multivariate analyses on normalized metabolite peak integrals allowed clusterization of samples in accordance with a posteriori histological findings. We investigated the relationship between morphological and NMR features by merging morphological data and metabolite profiling into a single correlation matrix. Data-merging addressed tissue heterogeneity, and greatly facilitated the mapping of lesions and nearby healthy tissues. Our proof-of-principle study reveals integrated metabolomics and histomorphology as a promising approach for the targeted study of osteolytic lesions.

  6. Metabolomics to Decipher the Chemical Defense of Cereals against Fusarium graminearum and Deoxynivalenol Accumulation

    Science.gov (United States)

    Gauthier, Léa; Atanasova-Penichon, Vessela; Chéreau, Sylvain; Richard-Forget, Florence

    2015-01-01

    Fusarium graminearum is the causal agent of Fusarium head blight (FHB) and Gibberella ear rot (GER), two devastating diseases of wheat, barley, and maize. Furthermore, F. graminearum species can produce type B trichothecene mycotoxins that accumulate in grains. Use of FHB and GER resistant cultivars is one of the most promising strategies to reduce damage induced by F. graminearum. Combined with genetic approaches, metabolomic ones can provide powerful opportunities for plant breeding through the identification of resistant biomarker metabolites which have the advantage of integrating the genetic background and the influence of the environment. In the past decade, several metabolomics attempts have been made to decipher the chemical defense that cereals employ to counteract F. graminearum. By covering the major classes of metabolites that have been highlighted and addressing their potential role, this review demonstrates the complex and integrated network of events that cereals can orchestrate to resist to F. graminearum. PMID:26492237

  7. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

  8. Metabolome analysis for discovering biomarkers of gastroenterological cancer.

    Science.gov (United States)

    Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-09-01

    Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. A metabolomics study on human dietary intervention with apples

    DEFF Research Database (Denmark)

    Dragsted, L. O.; Kristensen, M.; Ravn-Haren, Gitte

    2009-01-01

    Metabolomics is a promising tool for searching out new biomarkers and the development of hypotheses in nutrition research. This chapter will describe the design of human dietary intervention studies where samples are collected for metabolomics analyses as well as the analytical issues and data...

  10. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental

  11. Gas chromatography mass spectrometry : key technology in metabolomics

    NARCIS (Netherlands)

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with

  12. Metabolomics for Undergraduates: Identification and Pathway Assignment of Mitochondrial Metabolites

    Science.gov (United States)

    Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E. N.; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

    2016-01-01

    Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening…

  13. Using NMR metabolomics to identify responses of an environmental estrogen in blood plasma of fish

    International Nuclear Information System (INIS)

    Samuelsson, Linda M.; Foerlin, Lars; Karlsson, Goeran; Adolfsson-Erici, Margaretha; Larsson, D.G. Joakim

    2006-01-01

    Nuclear magnetic resonance (NMR) based metabolomics in combination with multivariate data analysis may become valuable tools to study environmental effects of pharmaceuticals and other chemicals in aquatic organisms. To explore the usefulness of this approach in fish, we have used 1 H NMR metabolomics to compare blood plasma and plasma lipid extracts from rainbow trout exposed to the synthetic contraceptive estrogen ethinylestradiol (EE 2 ) with plasma from control fish. The plasma metabolite profile was affected in fish exposed to 10 ng/L but not 0.87 ng/L of EE 2 , which was in agreement with an induced vitellogenin synthesis in the high dose group only, as measured by ELISA. The main affected metabolites were vitellogenin, alanine, phospholipids and cholesterol. The responses identified by this discovery-driven method could be put in context with previous knowledge of the effects of estrogens on fish. This adds confidence to the approach of using NMR metabolomics to identify environmental effects of pharmaceuticals and other contaminants

  14. Salivary and fecal microbiota and metabolome of celiac children under gluten-free diet.

    Science.gov (United States)

    De Angelis, Maria; Vannini, Lucia; Di Cagno, Raffaella; Cavallo, Noemi; Minervini, Fabio; Francavilla, Ruggiero; Ercolini, Danilo; Gobbetti, Marco

    2016-12-19

    Celiac disease (CD) is an inflammatory autoimmune disorder resulting from the combination of genetic predisposition and gluten ingestion. A life-long gluten free diet (GFD) is the only therapeutic approach. Dysbiosis, which can precede the CD pathogenesis and/or persist when subjects are on GFD, is reviewed and discussed. Salivary microbiota and metabolome differed between healthy and celiac children treated under GFD (T-CD) for at least two years. The type of GFD (African- vs Italian-style) modified the microbiota and metabolome of Saharawi T-CD children. Different studies showed bacterial dysbiosis at duodenal and/or fecal level of patients with active untreated CD (U-CD) and T-CD compared to healthy subjects. The ratio of protective anti-inflammatory bacteria such as Lactobacillus-Bifidobacterium to potentially harmful Bacteroides-Enterobacteriaceae was the lowest in U-CD and T-CD children. In agreement with dysbiosis, serum, fecal and urinary metabolome from U-CD and T-CD patients showed altered levels of free amino acids and volatile organic compounds. However, consensus across studies defining specific bacteria and metabolites in U-CD or T-CD patients is still lacking. Future research efforts are required to determine the relationships between CD and oral and intestinal microbiotas to improve the composition of GFD for restoring the gut dysbiosis as a preventative or therapeutic approach for CD. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.

    Directory of Open Access Journals (Sweden)

    Rao Guodong

    2017-09-01

    Full Text Available Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering.

  16. Radiation metabolomics : a window to high throughput radiation biodosimetry

    International Nuclear Information System (INIS)

    Rana, Poonam

    2016-01-01

    In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for radiation exposure is critical. In particular, a significant number of victims may sustain radiation injury, which increases mortality and worsens the overall prognosis of victims from radiation trauma. Availability of a high-throughput noninvasive in vivo biodosimetry tool for assessing the radiation exposure is of particular importance for timely diagnosis of radiation injury. In this study, we describe the potential NMR techniques in evaluating the radiation injury. NMR is the most versatile technique that has been extensively used in the diverse fields of science since its discovery. NMR and biomedical sciences have been going hand in hand since its application in clinical imaging as MRI and metabolic profiling of biofluids was identified. We have established an NMR based metabonomic and in vivo spectroscopy approach to analyse and identify metabolic profile to measure metabolic fingerprint for radiation exposure. NMR spectroscopy experiments were conducted on urine and serum samples collected from mice irradiated with different doses of radiation. Additionally, in vivo NMR spectroscopy was also performed in different region of brains post irradiation in animal model. A number of metabolites associated with energy metabolism, gut flora metabolites, osmolytes, amino acids and membrane metabolism were identified in serum and urine metabolome. Our results illustrated a metabolic fingerprint for radiation exposure that elucidates perturbed physiological functions. Quantitative as well as multivariate analysis/assessment of these metabolites demonstrated dose and time dependent toxicological effect. In vivo spectroscopy from brain showed radiation induced changes in hippocampus region indicating whole body radiation had striking effect on brain metabolism as well. The results of the present work lay a

  17. Metabolomics in Sepsis and Its Impact on Public Health.

    Science.gov (United States)

    Evangelatos, Nikolaos; Bauer, Pia; Reumann, Matthias; Satyamoorthy, Kapaettu; Lehrach, Hans; Brand, Angela

    2017-01-01

    Sepsis, with its often devastating consequences for patients and their families, remains a major public health concern that poses an increasing financial burden. Early resuscitation together with the elucidation of the biological pathways and pathophysiological mechanisms with the use of "-omics" technologies have started changing the clinical and research landscape in sepsis. Metabolomics (i.e., the study of the metabolome), an "-omics" technology further down in the "-omics" cascade between the genome and the phenome, could be particularly fruitful in sepsis research with the potential to alter the clinical practice. Apart from its benefit for the individual patient, metabolomics has an impact on public health that extends beyond its applications in medicine. In this review, we present recent developments in metabolomics research in sepsis, with a focus on pneumonia, and we discuss the impact of metabolomics on public health, with a focus on free/libre open source software. © 2018 S. Karger AG, Basel.

  18. New tools and resources in metabolomics: 2016-2017.

    Science.gov (United States)

    Misra, Biswapriya B

    2018-04-01

    Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Compliance with minimum information guidelines in public metabolomics repositories.

    Science.gov (United States)

    Spicer, Rachel A; Salek, Reza; Steinbeck, Christoph

    2017-09-26

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

  20. Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

    Science.gov (United States)

    Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

    2016-07-01

    Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas

  1. Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

    Science.gov (United States)

    Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

    2018-04-01

    Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

  2. Metabolome and proteome profiling of complex I deficiency induced by rotenone.

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    Gielisch, Ina; Meierhofer, David

    2015-01-02

    Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

  3. Metabolomic Profiles of a Midge (Procladius villosimanus, Kieffer Are Associated with Sediment Contamination in Urban Wetlands

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    Katherine J. Jeppe

    2017-12-01

    Full Text Available Metabolomic techniques are powerful tools for investigating organism-environment interactions. Metabolite profiles have the potential to identify exposure or toxicity before populations are disrupted and can provide useful information for environmental assessment. However, under complex environmental scenarios, metabolomic responses to exposure can be distorted by background and/or organismal variation. In the current study, we use LC-MS (liquid chromatography-mass spectrometry and GC-MS (gas chromatography-mass spectrometry to measure metabolites of the midge Procladius villosimanus inhabiting 21 urban wetlands. These metabolites were tested against common sediment contaminants using random forest models and metabolite enrichment analysis. Sediment contaminant concentrations in the field correlated with several P. villosimanus metabolites despite natural environmental and organismal variation. Furthermore, enrichment analysis indicated that metabolite sets implicated in stress responses were enriched, pointing to specific cellular functions affected by exposure. Methionine metabolism, sugar metabolism and glycerolipid metabolism associated with total petroleum hydrocarbon and metal concentrations, while mitochondrial electron transport and urea cycle sets associated only with bifenthrin. These results demonstrate the potential for metabolomics approaches to provide useful information in field-based environmental assessments.

  4. Advances in high-resolution mass spectrometry based on metabolomics studies for food--a review.

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    Rubert, Josep; Zachariasova, Milena; Hajslova, Jana

    2015-01-01

    Food authenticity becomes a necessity for global food policies, since food placed in the market without fail has to be authentic. It has always been a challenge, since in the past minor components, called also markers, have been mainly monitored by chromatographic methods in order to authenticate the food. Nevertheless, nowadays, advanced analytical methods have allowed food fingerprints to be achieved. At the same time they have been also combined with chemometrics, which uses statistical methods in order to verify food and to provide maximum information by analysing chemical data. These sophisticated methods based on different separation techniques or stand alone have been recently coupled to high-resolution mass spectrometry (HRMS) in order to verify the authenticity of food. The new generation of HRMS detectors have experienced significant advances in resolving power, sensitivity, robustness, extended dynamic range, easier mass calibration and tandem mass capabilities, making HRMS more attractive and useful to the food metabolomics community, therefore becoming a reliable tool for food authenticity. The purpose of this review is to summarise and describe the most recent metabolomics approaches in the area of food metabolomics, and to discuss the strengths and drawbacks of the HRMS analytical platforms combined with chemometrics.

  5. Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2016-01-01

    Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

  6. Characterization of the Wheat Leaf Metabolome during Grain Filling and under Varied N-Supply

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    Elmien Heyneke

    2017-11-01

    Full Text Available Progress in improving crop growth is an absolute goal despite the influence multifactorial components have on crop yield and quality. An Avalon × Cadenza doubled-haploid wheat mapping population was used to study the leaf metabolome of field grown wheat at weekly intervals during the time in which the canopy contributes to grain filling, i.e., from anthesis to 5 weeks post-anthesis. Wheat was grown under four different nitrogen supplies reaching from residual soil N to a luxury over-fertilization (0, 100, 200, and 350 kg N ha−1. Four lines from a segregating doubled haploid population derived of a cross of the wheat elite cvs. Avalon and Cadenza were chosen as they showed pairwise differences in either N utilization efficiency (NUtE or senescence timing. 108 annotated metabolites of primary metabolism and ions were determined. The analysis did not provide genotype specific markers because of a remarkable stability of the metabolome between lines. We speculate that the reason for failing to identify genotypic markers might be due to insufficient genetic diversity of the wheat parents and/or the known tendency of plants to keep metabolome homeostasis even under adverse conditions through multiple adaptations and rescue mechanism. The data, however, provided a consistent catalogue of metabolites and their respective responses to environmental and developmental factors and may bode well for future systems biology approaches, and support plant breeding and crop improvement.

  7. Simultaneous measurement of NAD metabolome in aged mice tissue using liquid chromatography tandem-mass spectrometry.

    Science.gov (United States)

    Yaku, Keisuke; Okabe, Keisuke; Nakagawa, Takashi

    2018-06-01

    Nicotinamide adenine dinucleotide (NAD) is a major co-factor that mediates multiple biological processes including redox reaction and gene expression. Recently, NAD metabolism has received considerable attention because administration of NAD precursors exhibited beneficial effects against aging-related metabolic disorders in animals. Although numerous studies have reported that NAD levels decline with aging in multiple animal tissues, the pathway and kinetics of NAD metabolism in aged organs are not completely understood. To determine the NAD metabolism upon aging, we developed targeted metabolomics based on an LC/MS/MS system. Our method is simple and applicable to crude biological samples, including culture cells and animal tissues. Unlike a conventional enzymatic cycling assay, our approach can determine NAD and NADH (reduced form of NAD) by performing a single sample preparation. Further, we validated our method using biological samples and investigated the alteration of the NAD metabolome during aging. Consistent with previous reports, the NAD levels in the liver and skeletal muscle decreased with aging. Further, we detected a significant increase in nicotinamide mononucleotide and nicotinamide riboside in the kidney upon aging. The LC/MS/MS-based NAD metabolomics that we have developed is extensively applicable to biomedical studies, and the results will present innovative ideas for the aging studies, especially for that of NAD metabolism. Copyright © 2018 John Wiley & Sons, Ltd.

  8. From models to crop species: caveats and solutions for translational metabolomics

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    Takayuki eTohge

    2011-10-01

    Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

  9. GC-MS-Based Metabolome and Metabolite Regulation in Serum-Resistant Streptococcus agalactiae.

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    Wang, Zhe; Li, Min-Yi; Peng, Bo; Cheng, Zhi-Xue; Li, Hui; Peng, Xuan-Xian

    2016-07-01

    Streptococcus agalactiae causes severe systemic infections in human and fish. In the present study, we established a pathogen-plasma interaction model by which we explored how S. agalactiae evaded serum-mediated killing. We found that S. agalactiae grew faster in the presence of yellow grouper plasma than in the absence of the plasma, indicating S. agalactiae evolved a way of evading the fish immune system. To determine the events underlying this phenotype, we applied GC-MS-based metabolomics approaches to identify differential metabolomes between S. agalactiae cultured with and without yellow grouper plasma. Through bioinformatics analysis, decreased malic acid and increased adenosine were identified as the most crucial metabolites that distinguish the two groups. Meanwhile, they presented with decreased TCA cycle and elevated purine metabolism, respectively. Finally, exogenous malic acid and adenosine were used to reprogram the plasma-resistant metabolome, leading to elevated and decreased susceptibility to the plasma, respectively. Therefore, our findings reveal for the first time that S. agalactiae utilizes a metabolic trick to respond to plasma killing as a result of serum resistance, which may be reverted or enhanced by exogenous malic acid and adenosine, respectively, suggesting that the metabolic trick can be regulated by metabolites.

  10. Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

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    Amanda L. Peterson

    2016-09-01

    Full Text Available Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions.

  11. Application of Stable Isotope-Assisted Metabolomics for Cell Metabolism Studies

    Science.gov (United States)

    You, Le; Zhang, Baichen; Tang, Yinjie J.

    2014-01-01

    The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other “omics” analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research. PMID:24957020

  12. Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

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    Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

    2016-01-01

    Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

  13. Clinical Metabolomics and Nutrition: The New Frontier in Neonatology and Pediatrics

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    Angelica Dessì

    2014-01-01

    Full Text Available In the pediatric clinic, nutritional research is focusing more and more on preventing the development of long-term diseases as well as supporting the repair processes important in the therapy of already fully developed diseases. Most children who are hospitalized or affected by chronic diseases could benefit from specific and careful attention to nutrition. Indeed, the state of nutrition modulates all body functions, including the different metabolic processes which, all together, have a profound effect on the development of the health and future of all individuals. Inappropriate food, even in the first periods of life, can accelerate the development of chronic metabolic diseases, especially in the pediatric age. To gain further insights into metabolic cycles and how they are connected with diet and health, nutrition and metabolomics interact to develop and apply modern technologies for metabolic assessment. In particular, nutritionists are evaluating the metabolomic approach to establish the single nutritional phenotypes, that is, the way in which diet interacts with individuals’ metabolisms. This strategy offers the possibility of providing a complete definition of the individual’s nutritional and health status, predict the risk of disease, and create metabolomic databases supporting the development of “personalized nutrition,” in which diet is attuned to the nutritional needs of individual patients.

  14. Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs.

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    Metzler-Zebeli, Barbara U; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

    2015-01-01

    Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (Pmetabolome profiling identified characteristic changes in glycerophospholipid, lysophospholipids, sphingomyelins and amino acid metabolome profiles with EMS diet compared to control diet. Results showed rapid adaptations of blood metabolites to dietary starch shifts within 7 days. In conclusion, EMS ingestion showed potential to attenuate postprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid metabolome in response to EMS consumption.

  15. Metabolomics analysis of metabolic effects of nicotinamide phosphoribosyltransferase (NAMPT inhibition on human cancer cells.

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    Vladimir Tolstikov

    Full Text Available Nicotinamide phosphoribosyltransferase (NAMPT plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide-consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry-based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer and HCT-116 (colorectal cancer cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA, and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level.

  16. Exploratory metabolomics study of the experimental opisthorchiasis in a laboratory animal model (golden hamster, Mesocricetus auratus.

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    Daria A Kokova

    2017-10-01

    Full Text Available Opisthorchiasis is a parasitic infection caused by the liver flukes of the Opisthorchiidae family. Both experimental and epidemiological data strongly support a role of these parasites in the etiology of the hepatobiliary pathologies and an increased risk of intrahepatic cholangiocarcinoma. Understanding a functional link between the infection and hepatobiliary pathologies requires a detailed description a host-parasite interaction on different levels of biological regulation including the metabolic response on the infection. The last one, however, remains practically undocumented. Here we are describing a host response on Opisthorchiidae infection using a metabolomics approach and present the first exploratory metabolomics study of an experimental model of O. felineus infection.We conducted a Nuclear Magnetic Resonance (NMR based longitudinal metabolomics study involving a cohort of 30 animals with two degrees of infection and a control group. An exploratory analysis shows that the most noticeable trend (30% of total variance in the data was related to the gender differences. Therefore further analysis was done of each gender group separately applying a multivariate extension of the ANOVA-ASCA (ANOVA simultaneous component analysis. We show that in the males the infection specific time trends are present in the main component (43.5% variance, while in the females it is presented only in the second component and covers 24% of the variance. We have selected and annotated 24 metabolites associated with the observed effects and provided a physiological interpretation of the findings.The first exploratory metabolomics study an experimental model of O. felineus infection is presented. Our data show that at early stage of infection a response of an organism unfolds in a gender specific manner. Also main physiological mechanisms affected appear rather nonspecific (a status of the metabolic stress the data provides a set of the hypothesis for a search

  17. Challenges of metabolomics in human gut microbiota research.

    Science.gov (United States)

    Smirnov, Kirill S; Maier, Tanja V; Walker, Alesia; Heinzmann, Silke S; Forcisi, Sara; Martinez, Inés; Walter, Jens; Schmitt-Kopplin, Philippe

    2016-08-01

    The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine. Copyright © 2016 Elsevier GmbH. All rights reserved.

  18. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

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    Jumpei Washio

    2016-06-01

    Full Text Available Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  19. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond.

    Science.gov (United States)

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

    Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  20. Chemical Composition and Seasonality of Aromatic Mediterranean Plant Species by NMR-Based Metabolomics

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    Monica Scognamiglio

    2015-01-01

    Full Text Available An NMR-based metabolomic approach has been applied to analyse seven aromatic Mediterranean plant species used in traditional cuisine. Based on the ethnobotanical use of these plants, the approach has been employed in order to study the metabolic changes during different seasons. Primary and secondary metabolites have been detected and quantified. Flavonoids (apigenin, quercetin, and kaempferol derivatives and phenylpropanoid derivatives (e.g., chlorogenic and rosmarinic acid are the main identified polyphenols. The richness in these metabolites could explain the biological properties ascribed to these plant species.

  1. Chemical Composition and Seasonality of Aromatic Mediterranean Plant Species by NMR-Based Metabolomics.

    Science.gov (United States)

    Scognamiglio, Monica; D'Abrosca, Brigida; Esposito, Assunta; Fiorentino, Antonio

    2015-01-01

    An NMR-based metabolomic approach has been applied to analyse seven aromatic Mediterranean plant species used in traditional cuisine. Based on the ethnobotanical use of these plants, the approach has been employed in order to study the metabolic changes during different seasons. Primary and secondary metabolites have been detected and quantified. Flavonoids (apigenin, quercetin, and kaempferol derivatives) and phenylpropanoid derivatives (e.g., chlorogenic and rosmarinic acid) are the main identified polyphenols. The richness in these metabolites could explain the biological properties ascribed to these plant species.

  2. Impact of Prolonged Blood Incubation and Extended Serum Storage at Room Temperature on the Human Serum Metabolome

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    Beate Kamlage

    2018-01-01

    Full Text Available Metabolomics is a powerful technology with broad applications in life science that, like other -omics approaches, requires high-quality samples to achieve reliable results and ensure reproducibility. Therefore, along with quality assurance, methods to assess sample quality regarding pre-analytical confounders are urgently needed. In this study, we analyzed the response of the human serum metabolome to pre-analytical variations comprising prolonged blood incubation and extended serum storage at room temperature by using gas chromatography-mass spectrometry (GC-MS and liquid chromatography-tandem mass spectrometry (LC-MS/MS -based metabolomics. We found that the prolonged incubation of blood results in a statistically significant 20% increase and 4% decrease of 225 tested serum metabolites. Extended serum storage affected 21% of the analyzed metabolites (14% increased, 7% decreased. Amino acids and nucleobases showed the highest percentage of changed metabolites in both confounding conditions, whereas lipids were remarkably stable. Interestingly, the amounts of taurine and O-phosphoethanolamine, which have both been discussed as biomarkers for various diseases, were 1.8- and 2.9-fold increased after 6 h of blood incubation. Since we found that both are more stable in ethylenediaminetetraacetic acid (EDTA blood, EDTA plasma should be the preferred metabolomics matrix.

  3. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods.

    Science.gov (United States)

    Boaz, Segal M; Champagne, Cory D; Fowler, Melinda A; Houser, Dorian H; Crocker, Daniel E

    2012-02-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to 7 weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. Copyright © 2011 Elsevier Inc. All rights reserved.

  4. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods

    Science.gov (United States)

    Boaz, Segal M.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian H.; Crocker, Daniel E.

    2011-01-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to seven weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. PMID:21983145

  5. Introduction to metabolomics and its applications in ophthalmology

    Science.gov (United States)

    Tan, S Z; Begley, P; Mullard, G; Hollywood, K A; Bishop, P N

    2016-01-01

    Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers. PMID:26987591

  6. Targeting of the hydrophobic metabolome by pathogens.

    Science.gov (United States)

    Helms, J Bernd; Kaloyanova, Dora V; Strating, Jeroen R P; van Hellemond, Jaap J; van der Schaar, Hilde M; Tielens, Aloysius G M; van Kuppeveld, Frank J M; Brouwers, Jos F

    2015-05-01

    The hydrophobic molecules of the metabolome - also named the lipidome - constitute a major part of the entire metabolome. Novel technologies show the existence of a staggering number of individual lipid species, the biological functions of which are, with the exception of only a few lipid species, unknown. Much can be learned from pathogens that have evolved to take advantage of the complexity of the lipidome to escape the immune system of the host organism and to allow their survival and replication. Different types of pathogens target different lipids as shown in interaction maps, allowing visualization of differences between different types of pathogens. Bacterial and viral pathogens target predominantly structural and signaling lipids to alter the cellular phenotype of the host cell. Fungal and parasitic pathogens have complex lipidomes themselves and target predominantly the release of polyunsaturated fatty acids from the host cell lipidome, resulting in the generation of eicosanoids by either the host cell or the pathogen. Thus, whereas viruses and bacteria induce predominantly alterations in lipid metabolites at the host cell level, eukaryotic pathogens focus on interference with lipid metabolites affecting systemic inflammatory reactions that are part of the immune system. A better understanding of the interplay between host-pathogen interactions will not only help elucidate the fundamental role of lipid species in cellular physiology, but will also aid in the generation of novel therapeutic drugs. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  7. Radiation Metabolomics: Current Status and Future Directions

    Directory of Open Access Journals (Sweden)

    Smrithi eSugumaran Menon

    2016-02-01

    Full Text Available Human exposure to ionizing radiation disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms and peripheral lymphocyte counts are of limited value as organ and tissue specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic ionizing radiation. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure.

  8. The co-feature ratio, a novel method for the measurement of chromatographic and signal selectivity in LC-MS-based metabolomics

    International Nuclear Information System (INIS)

    Elmsjö, Albert; Haglöf, Jakob; Engskog, Mikael K.R.; Nestor, Marika; Arvidsson, Torbjörn; Pettersson, Curt

    2017-01-01

    Evaluation of analytical procedures, especially in regards to measuring chromatographic and signal selectivity, is highly challenging in untargeted metabolomics. The aim of this study was to suggest a new straightforward approach for a systematic examination of chromatographic and signal selectivity in LC-MS-based metabolomics. By calculating the ratio between each feature and its co-eluting features (the co-features), a measurement of the chromatographic selectivity (i.e. extent of co-elution) as well as the signal selectivity (e.g. amount of adduct formation) of each feature could be acquired, the co-feature ratio. This approach was used to examine possible differences in chromatographic and signal selectivity present in samples exposed to three different sample preparation procedures. The capability of the co-feature ratio was evaluated both in a classical targeted setting using isotope labelled standards as well as without standards in an untargeted setting. For the targeted analysis, several metabolites showed a skewed quantitative signal due to poor chromatographic selectivity and/or poor signal selectivity. Moreover, evaluation of the untargeted approach through multivariate analysis of the co-feature ratios demonstrated the possibility to screen for metabolites displaying poor chromatographic and/or signal selectivity characteristics. We conclude that the co-feature ratio can be a useful tool in the development and evaluation of analytical procedures in LC-MS-based metabolomics investigations. Increased selectivity through proper choice of analytical procedures may decrease the false positive and false negative discovery rate and thereby increase the validity of any metabolomic investigation. - Highlights: • The co-feature ratio (CFR) is introduced. • CFR measures chromatographic and signal selectivity of a feature. • CFR can be used for evaluating experimental procedures in metabolomics. • CFR can aid in locating features with poor selectivity.

  9. The co-feature ratio, a novel method for the measurement of chromatographic and signal selectivity in LC-MS-based metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Elmsjö, Albert, E-mail: Albert.Elmsjo@farmkemi.uu.se [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Haglöf, Jakob; Engskog, Mikael K.R. [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Nestor, Marika [Department of Immunology, Genetics and Pathology, Uppsala University (Sweden); Arvidsson, Torbjörn [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Medical Product Agency, Uppsala (Sweden); Pettersson, Curt [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden)

    2017-03-01

    Evaluation of analytical procedures, especially in regards to measuring chromatographic and signal selectivity, is highly challenging in untargeted metabolomics. The aim of this study was to suggest a new straightforward approach for a systematic examination of chromatographic and signal selectivity in LC-MS-based metabolomics. By calculating the ratio between each feature and its co-eluting features (the co-features), a measurement of the chromatographic selectivity (i.e. extent of co-elution) as well as the signal selectivity (e.g. amount of adduct formation) of each feature could be acquired, the co-feature ratio. This approach was used to examine possible differences in chromatographic and signal selectivity present in samples exposed to three different sample preparation procedures. The capability of the co-feature ratio was evaluated both in a classical targeted setting using isotope labelled standards as well as without standards in an untargeted setting. For the targeted analysis, several metabolites showed a skewed quantitative signal due to poor chromatographic selectivity and/or poor signal selectivity. Moreover, evaluation of the untargeted approach through multivariate analysis of the co-feature ratios demonstrated the possibility to screen for metabolites displaying poor chromatographic and/or signal selectivity characteristics. We conclude that the co-feature ratio can be a useful tool in the development and evaluation of analytical procedures in LC-MS-based metabolomics investigations. Increased selectivity through proper choice of analytical procedures may decrease the false positive and false negative discovery rate and thereby increase the validity of any metabolomic investigation. - Highlights: • The co-feature ratio (CFR) is introduced. • CFR measures chromatographic and signal selectivity of a feature. • CFR can be used for evaluating experimental procedures in metabolomics. • CFR can aid in locating features with poor selectivity.

  10. Microbial metabolomics with gas chromatography/mass spectrometry

    NARCIS (Netherlands)

    Koek, M.M.; Muilwijk, B.; Werf, M.J. van der; Hankemeier, T.

    2006-01-01

    An analytical method was set up suitable for the analysis of microbial metabolomes, consisting of an oximation and silylation derivatization reaction and subsequent analysis by gas chromatography coupled to mass spectrometry. Microbial matrixes contain many compounds that potentially interfere with

  11. Impact of Intestinal Microbiota on Intestinal Luminal Metabolome

    Science.gov (United States)

    Matsumoto, Mitsuharu; Kibe, Ryoko; Ooga, Takushi; Aiba, Yuji; Kurihara, Shin; Sawaki, Emiko; Koga, Yasuhiro; Benno, Yoshimi

    2012-01-01

    Low–molecular-weight metabolites produced by intestinal microbiota play a direct role in health and disease. In this study, we analyzed the colonic luminal metabolome using capillary electrophoresis mass spectrometry with time-of-flight (CE-TOFMS) —a novel technique for analyzing and differentially displaying metabolic profiles— in order to clarify the metabolite profiles in the intestinal lumen. CE-TOFMS identified 179 metabolites from the colonic luminal metabolome and 48 metabolites were present in significantly higher concentrations and/or incidence in the germ-free (GF) mice than in the Ex-GF mice (p metabolome and a comprehensive understanding of intestinal luminal metabolome is critical for clarifying host-intestinal bacterial interactions. PMID:22724057

  12. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were...

  13. International NMR-based Environmental Metabolomics Intercomparison Exercise

    Science.gov (United States)

    Several fundamental requirements must be met so that NMR-based metabolomics and the related technique of metabonomics can be formally adopted into environmental monitoring and chemical risk assessment. Here we report an intercomparison exercise which has evaluated the effectivene...

  14. Spectral Relative Standard Deviation: A Practical Benchmark in Metabolomics

    Science.gov (United States)

    Metabolomics datasets, by definition, comprise of measurements of large numbers of metabolites. Both technical (analytical) and biological factors will induce variation within these measurements that is not consistent across all metabolites. Consequently, criteria are required to...

  15. Human gut microbes impact host serum metabolome and insulin sensitivity

    DEFF Research Database (Denmark)

    Pedersen, Helle Krogh; Gudmundsdottir, Valborg; Nielsen, Henrik Bjørn

    2016-01-01

    Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin-resistant individ......Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin......-resistant individuals is characterized by increased levels of branched-chain amino acids (BCAAs), which correlate with a gut microbiome that has an enriched biosynthetic potential for BCAAs and is deprived of genes encoding bacterial inward transporters for these amino acids. Prevotella copri and Bacteroides vulgatus...

  16. Metabolomic profiling of Green Frogs exposed to Mixed Pesticides

    Data.gov (United States)

    U.S. Environmental Protection Agency — GC/MS data from the metabolomic profiling of green frog livers after exposure to pesticides and their mixtures. This dataset is associated with the following...

  17. ROMANCE: A new software tool to improve data robustness and feature identification in CE-MS metabolomics.

    Science.gov (United States)

    González-Ruiz, Víctor; Gagnebin, Yoric; Drouin, Nicolas; Codesido, Santiago; Rudaz, Serge; Schappler, Julie

    2018-05-01

    The use of capillary electrophoresis coupled to mass spectrometry (CE-MS) in metabolomics remains an oddity compared to the widely adopted use of liquid chromatography. This technique is traditionally regarded as lacking the reproducibility to adequately identify metabolites by their migration times. The major reason is the variability of the velocity of the background electrolyte, mainly coming from shifts in the magnitude of the electroosmotic flow and from the suction caused by electrospray interfaces. The use of the effective electrophoretic mobility is one solution to overcome this issue as it is a characteristic feature of each compound. To date, such an approach has not been applied to metabolomics due to the complexity and size of CE-MS data obtained in such studies. In this paper, ROMANCE (RObust Metabolomic Analysis with Normalized CE) is introduced as a new software for CE-MS-based metabolomics. It allows the automated conversion of batches of CE-MS files with minimal user intervention. ROMANCE converts the x-axis of each MS file from the time into the effective mobility scale and the resulting files are already pseudo-aligned, present normalized peak areas and improved reproducibility, and can eventually follow existing metabolomic workflows. The software was developed in Scala, so it is multi-platform and computationally-efficient. It is available for download under a CC license. In this work, the versatility of ROMANCE was demonstrated by using data obtained in the same and in different laboratories, as well as its application to the analysis of human plasma samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Metabolomics and Metabolic Diseases: Where Do We Stand?

    Science.gov (United States)

    Newgard, Christopher B

    2017-01-10

    Metabolomics, or the comprehensive profiling of small molecule metabolites in cells, tissues, or whole organisms, has undergone a rapid technological evolution in the past two decades. These advances have led to the application of metabolomics to defining predictive biomarkers for incident cardiometabolic diseases and, increasingly, as a blueprint for understanding those diseases' pathophysiologic mechanisms. Progress in this area and challenges for the future are reviewed here. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Pediatric obesity: could metabolomics be a useful tool?

    OpenAIRE

    Angelica Dessì; Vassilios Fanos

    2013-01-01

    Pediatric obesity represents an important health issue. In recent years applications of metabolomics have led to evaluation of responses to the various nutrients (nutrigenomics), in particular to lipids, in diseases such as obesity and diabetes. The experimental data and the studies in pediatrics  that evaluated the metabolic condition in infant obesity are presented. It is thus to be hoped that future progress in connection with this new technique, together with a metabolomic study of mother...

  20. Ultrasound: a subexploited tool for sample preparation in metabolomics.

    Science.gov (United States)

    Luque de Castro, M D; Delgado-Povedano, M M

    2014-01-02

    Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. SECIMTools: a suite of metabolomics data analysis tools.

    Science.gov (United States)

    Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

    2018-04-20

    Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

  2. An explorative study of the effect of apple and apple products on the human plasma metabolome investigated by LC–MS profiling

    DEFF Research Database (Denmark)

    Rago, Daniela; Gürdeniz, Gözde; Ravn-Haren, Gitte

    2015-01-01

    Apple is one of the most commonly consumed fruits worldwide and it has been associated with several health effects, especially on plasma cholesterol and risk of cardiovascular disease both in human and animal studies. By using an untargeted metabolomics approach we wanted to investigate whether...... supplementation of whole apple or processed apple products affect the human plasma metabolome. Therefore, 24 healthy volunteers were recruited for a comprehensive 5 × 4 weeks dietary crossover study and receiving supplement of whole apples (550 g/day), clear and cloudy apple juices (500 ml/day), dried apple...... metabolome than the other apple products. We observed an effect on branched-chain amino acids and aromatic amino acids degradation, and a decreased use of lipid fuels indicating an improvement in glucose utilisation. A reduced level of plasma bile acids after apple consumption may indicate less re...

  3. NMR-based stable isotope resolved metabolomics in systems biochemistry

    International Nuclear Information System (INIS)

    Fan, Teresa W-M.; Lane, Andrew N.

    2011-01-01

    An important goal of metabolomics is to characterize the changes in metabolic networks in cells or various tissues of an organism in response to external perturbations or pathologies. The profiling of metabolites and their steady state concentrations does not directly provide information regarding the architecture and fluxes through metabolic networks. This requires tracer approaches. NMR is especially powerful as it can be used not only to identify and quantify metabolites in an unfractionated mixture such as biofluids or crude cell/tissue extracts, but also determine the positional isotopomer distributions of metabolites derived from a precursor enriched in stable isotopes such as 13 C and 15 N via metabolic transformations. In this article we demonstrate the application of a variety of 2-D NMR editing experiments to define the positional isotopomers of compounds present in polar and non-polar extracts of human lung cancer cells grown in either [U– 13 C]-glucose or [U– 13 C, 15 N]-glutamine as source tracers. The information provided by such experiments enabled unambiguous reconstruction of metabolic pathways, which is the foundation for further metabolic flux modeling.

  4. Untargeted Metabolomic Analysis of Capsicum spp. by GC-MS.

    Science.gov (United States)

    Aranha, Bianca Camargo; Hoffmann, Jessica Fernanda; Barbieri, Rosa Lia; Rombaldi, Cesar Valmor; Chaves, Fábio Clasen

    2017-09-01

    In order to conserve the biodiversity of Capsicum species and find genotypes with potential to be utilised commercially, Embrapa Clima Temperado maintains an active germplasm collection (AGC) that requires characterisation, enabling genotype selection and support for breeding programmes. The objective of this study was to characterise pepper accessions from the Embrapa Clima Temperado AGC and differentiate species based on their metabolic profile using an untargeted metabolomics approach. Cold (-20°C) methanol extraction residue of freeze-dried fruit samples was partitioned into water/methanol (A) and chloroform (B) fractions. The polar fraction (A) was derivatised and both fractions (A and B) were analysed by gas chromatography coupled to mass spectrometry (GC-MS). Data from each fraction was analysed using a multivariate principal component analysis (PCA) with XCMS software. Amino acids, sugars, organic acids, capsaicinoids, and hydrocarbons were identified. Outlying accessions including P116 (C. chinense), P46, and P76 (C. annuum) were observed in a PCA plot mainly due to their high sucrose and fructose contents. PCA also indicated a separation of P221 (C. annuum) and P200 (C. chinense), because of their high dihydrocapsaicin content. Although the metabolic profiling did not allow for grouping by species, it permitted the simultaneous identification and quantification of several compounds complementing and expanding the metabolic database of the studied Capsicum spp. in the AGC. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  5. Effects of a prolonged standardized diet on normalizing the human metabolome123

    OpenAIRE

    Winnike, Jason H; Busby, Marjorie G; Watkins, Paul B; O'Connell, Thomas M

    2009-01-01

    Background: Although the effects of acute dietary interventions on the human metabolome have been studied, the extent to which the metabolome can be normalized by extended dietary standardization has not yet been examined.

  6. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

    Science.gov (United States)

    Mahieu, Nathaniel G; Patti, Gary J

    2017-10-03

    When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

  7. Normalization method for metabolomics data using optimal selection of multiple internal standards

    Directory of Open Access Journals (Sweden)

    Yetukuri Laxman

    2007-03-01

    Full Text Available Abstract Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. Results With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS. We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization. Conclusion Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.

  8. Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

    Directory of Open Access Journals (Sweden)

    Mónica Escandón

    2018-04-01

    Full Text Available The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3 at which P. radiata plants changed from an initial stress response program (shorter-term response to an acclimation one (longer-term response. Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs, fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR and isopentenyl adenosine (iPA as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin, crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

  9. Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.

    Science.gov (United States)

    Naser, Fuad J; Mahieu, Nathaniel G; Wang, Lingjue; Spalding, Jonathan L; Johnson, Stephen L; Patti, Gary J

    2018-02-01

    Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C 8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C 8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more

  10. Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

    Science.gov (United States)

    Cuykx, Matthias; Negreira, Noelia; Beirnaert, Charlie; Van den Eede, Nele; Rodrigues, Robim; Vanhaecke, Tamara; Laukens, Kris; Covaci, Adrian

    2017-03-03

    Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. The omics era: what can nuclear magnetic resonance tell us on metabolomics?

    Directory of Open Access Journals (Sweden)

    Franca Castiglione

    2018-02-01

    Full Text Available A brief overview of the potentiality and use of the metabolic fingerprint of a system or biological process is here proposed. The information on the type, quantity and variation of the pool of metabolites and its relationship with a given biological process is commonly referred to as metabolomics. One powerful analytical approach to the detection and quantitation of metabolites is by Nuclear Magnetic Resonance Spectroscopy (NMR. Additionally, the recently introduced High Resolution Magic Angle Spinning (HR-MAS NMR approach improved dramatically the potentiality of the method allowing direct sampling of ex vivo specimens, such as tissues and cells, without any pre-treatment or extraction steps. The NMR data can be processed towards the target or non-target analysis of the metabolites. The former passes through the identification of all the metabolites, the latter adopts a multivariate statistical approach such as Principal Components Analysis. In this article, the main methodological points of NMR analysis with multivariate statistics are briefly outlined and discussed. A final case-study on the discrimination of healthy and neoplastic tissues via HR-MAS NMR metabolomics is reported as a paradigmatic application.

  12. Metabolomic markers of fatigue: Association between circulating metabolome and fatigue in women with chronic widespread pain.

    Science.gov (United States)

    Freidin, Maxim B; Wells, Helena R R; Potter, Tilly; Livshits, Gregory; Menni, Cristina; Williams, Frances M K

    2018-02-01

    Fatigue is a sensation of unbearable tiredness that frequently accompanies chronic widespread musculoskeletal pain (CWP) and inflammatory joint disease. Its mechanisms are poorly understood and there is a lack of effective biomarkers for diagnosis and onset prediction. We studied the circulating metabolome in a population sample characterised for CWP to identify biomarkers showing specificity for fatigue. Untargeted metabolomic profiling was conducted on fasting plasma and serum samples of 1106 females with and without CWP from the TwinsUK cohort. Linear mixed-effects models accounting for covariates were used to determine relationships between fatigue and metabolites. Receiver operating curve (ROC)-analysis was used to determine predictive value of metabolites for fatigue. While no association between fatigue and metabolites was identified in twins without CWP (n=711), in participants with CWP (n=395), levels of eicosapentaenoate (EPA) ω-3 fatty acid were significantly reduced in those with fatigue (β=-0.452±0